Movement disorders in nonpsychotic siblings of patients with nonaffective psychosis

Movement disorders in patients with schizophrenia and in their siblings

Symptoms, side effects and mechanical measurements

Bewegingsstoornissen bij patiënten met schizofrenie en bij hun broers en zussen

Symptomen, bijwerkingen en mechanische metingen

(met een samenvatting in het Nederlands)

Proefschrift

ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof. dr. G.J. van der Zwaan, ingevolge

het besluit van het college voor promoties in het openbaar te verdedigen

op dinsdag 30 augustus 2011 des ochtends te 10.30 uur

door

Jeroen Petrus Franciscus Koning

geboren op 22 april 1977 te ’s-Hertogenbosch

Promotoren: Prof. dr. R.S. Kahn Prof. dr. P.N. van Harten

Co-promotor: Dr. D.E. Tenback

Voor Kim en Sven&

mijn ouders

“Eppur si muove!”

Galileo Galilei

Contents

Part I General introduction and outline of the thesis 1

Part II Movement disorders in patients with schizophrenia and in their siblings 21

2.1 Dyskinesia and parkinsonism in antipsychotic-naive patients with schizophrenia, first-degree relatives and healthy controls: a meta-analysis Published in Schizophrenia Bulletin 23 2.2 Movement disorders are associated with schizotypy in unaffected siblings of patients with non-affective psychosis Published in Psychological Medicine 43

2.3 Associations of two DRD2 gene polymorphisms with acute and tardive antipsychotic-induced movement disorders in young Caucasian patients Published in Psychopharmacology (Berl) 61

Part III Mechanical measurement of dyskinesia and parkinsonism 85

3.1 Instrument measurement of lingual force variability reflects tardive tongue dyskinesia Published in Journal of Medical Engineering & Technology 87

3.2 Movement disorders in nonpsychotic siblings of patients with non-affective psychosis Published in Psychiatry Research 103

Part IV Summary and general discussion 121

4.1 Summary 1234.2 General discussion 126

Summary in Dutch / Nederlandse samenvatting 135

Publication list 141

Abstracts and conference proceedings 142

Acknowledgements/Dankwoord 145

Curriculum Vitae 148

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Part I

General introduction and outline of the thesis

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isPart I General introduction and outline of the thesis

This thesis focuses on several aspects of movement disorders in patients with schizophrenia and in their unaffected siblings. The main hypothesis is that movement disorders are not just side effects of antipsychotic medication but may also be symptoms of the illness itself and are related to the (genetic) risk of developing the disease.

Schizophrenia

Schizophrenia is a complex and devastating psychiatric disease with a lifetime prevalence of between 0.3–0.7% 1. It is most often characterised by a long duration and by recurrent psychotic episodes of positive symptoms (hallucinations and bizarre delusions), negative symptoms (deficits in normal emotional responses or of other thought processes and lack of motivation), a few affective symptoms (non-affective psychosis), and cognitive impairment 2. The prodromal symptoms start in early adolescence, with a modal age at onset of the full syndrome for males between 18 and 25 years and for females between 25 and the mid-30’s with a second smaller peak after 45 years of age 3. The aetiology of schizophrenia remains largely unknown. Family, twin, and adoption studies indicate that genetic factors play an important role and that first-degree relatives of patients have an increased risk of developing the disease 4, 5. Furthermore there is evidence that environmental factors such as early life adversity, growing up in an urban environment, minority group position, and cannabis use may also increase the risk of developing a psychotic disorder such as schizophrenia 6, 7. It is generally believed that the expression of schizophrenia is the result of environmental and genetic interactions 4, 8-11. The cornerstone in the treatment of schizophrenia is antipsychotic drugs, all of which block dopamine D2 receptors 2, 12. The effectiveness of these drugs is consistent with the hypothesis that dopamine and dopaminergic pathway dysfunctions are central to schizophrenia 13. Antipsychotics are particularly effective in the treatment of positive psychotic symptoms 13. However, antipsychotics often induce movement disorder side effects such as dyskinesia, parkinsonism, akathisia, and dystonia 14-16 14, 17-22.

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Movement disorders

Phenomenology

In this thesis the following definitions of the different movement disorders are used:

1. Dyskinesia is a hyperkinetic movement disorder characterised by involuntary writhing and purposeless, irregular movements that may or may not be continuous. The core sign is orofacial dyskinesia, or the buccolinguomasticatory triad. This consists of involuntary movements of the tongue, jaw, lips, or face, for example, twisting, curling, or protrusion of the tongue, chewing or lateral jaw movements, pursing, sucking, pouting, or puckering of the lips, facial tics, and eye blinking. Choreiform purposeless movements of the trunk and/or limbs also occur, including writhing of the finger (‘piano-playing fingers’) or irregular trunk, leg, or toe movements 14, 16, 23.

2. Parkinsonism is a hypokinetic movement disorder with the

following cardinal features: bradykinesia, rigidity, tremor at rest, and postural instability 14, 16,24.

Bradykinesia and hypokinesia are the most common and sometimes the only manifestations of parkinsonism. They account for monotonous speech, hypomimia (reduced rate of eye blinking or normal facial expressions), slowing and poverty of movements in general, muscle fatigue, slow walking with short steps, and decreased arm swing. Sometimes sialorrhea appears, probably because saliva is not swallowed as fast as it is produced.

Rigidity is characterised by a persistent increased muscle tone, which makes the muscles continuously or intermittently firm and tense. The increased resistance to passive movement resembles the feeling of bending a lead pipe. Tremor at rest is a rhythmic tremor with a frequency of 4-6 Hz and can be localised in one or both hands, but limbs, chin (rabbit syndrome) or head can also be affected.

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isPostural instability is reflected in a reduction or absence of postural response, which can be judged with the pull test (a sudden posterior displacement produced by a pull on the shoulders) 14, 16.

3. Dystonia is characterised by slow or sustained involuntary muscle contractions, frequently causing twisting and repetitive movements or abnormal postures. The muscles involved are usually localised in the head, neck, trunk, and/or limbs 14, 16, 25.

4. Akathisia, which means ‘not to sit,’ can be defined as both subjective complaints of restlessness and as objective motor movements. The subjective complaints consist of feelings of restlessness, most often with reference to the legs, subsequently resulting in the objective feature of typically restless movements of the legs 14, 16, 26.

Movement disorders in antipsychotic-naive patients with schizophrenia

The literature predating the neuroleptic era suggests that movement disorders resembling dyskinesia and parkinsonism were a relatively common feature of schizophrenia. In 1919 Kraepelin describes movements in patients with dementia praecox such as “grimacing,” “irregular movements of the lip and tongue,” “slower movement,” “rigidity,” and “tremor” 27. Reiter and Bleuler observe similar motor abnormalities in patients with schizophrenia such as “a well-defined Parkinson syndrome” 28 and “extra-ordinary movements of the tongue and lips” 29. However, since the introduction of antipsychotic medication in 1952, the clinical descriptions of motor symptoms in the pre-neuroleptic era were gradually neglected, which eventually led to the presumption that movement disorders in patients with schizophrenia are primarily a side effect of antipsychotic treatment 14, 17-22. This shift from symptom to side effect is nicely illustrated by the Diagnostic Statistical Manual for Mental Disorder, which defines the diagnostic criteria for dyskinesia and parkinsonism in the context of adverse effects due to neuroleptic treatment. 3

Identifying whether movement disorders are inherent to schizophrenia could be clinically and theoretically relevant. Clinically such a finding would be important because movement disorders at baseline have been

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shown to predict poorer outcome of schizophrenia 30-33. Furthermore, the presence of early movement disorders in patients may be also related to the development of later antipsychotic-induced tardive dyskinesia 34,

35. Theoretically it would be relevant because schizophrenia is probably heterogeneous with regard to phenomenology and pathophysiology 36, 37. Patients with movement disorders (i.e. a distinct nigrostriatal dysfunction) may constitute a distinct subgroup within schizophrenia. However, to examine to what extent movement disorders constitute symptoms of the disease itself, it is first necessary to compare antipsychotic-naive patients with schizophrenia with matched healthy controls.

Movement disorders in unaffected siblings of patients with schizophrenia

Similar albeit more subtle movement disorders have been reported in the premorbid period of schizophrenia, during childhood and adolescence, and may thus indicate an increased risk, 38-40 as do schizotypal traits 38,

41. Additionally, movement disorders and schizotypy are also prevalent in unaffected siblings of patients with schizophrenia 42-45, who have an increased genetic risk of developing the disease 4. Movement disorders and psychoses are both associated with the deregulation of the dopamine system 46, 47 and may therefore share a common aetiology, which could be (partly) genetic and/or environmental. If populations at risk for psychosis, such as siblings of patients with schizophrenia, show a higher prevalence of movement disorders than healthy controls and if movement disorders in siblings associate with schizotypy, these findings would lend weight to the hypothesis that movement disorders are related to the (genetic) risk of schizophrenia and that dopamine-related vulnerability factors for psychosis or schizophrenia cluster in a subgroup of subjects. Furthermore it would suggest that movement disorders might be of value as an intermediate phenotype (endophenotype) in genetic research 48. They also could be of clinical interest as prodromal signs in early detection of individuals with an ultra-high risk for developing a psychotic disorder 49. Movement disorders as side effects of antipsychotic medication

Antipsychotic-induced movement disorders also remain a major concern in the treatment of schizophrenia. Movement disorders are associated

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iswith social stigmatization, physical disabilities, poorer quality of life, and may inhibit treatment adherence 50, 51. Lack of compliance may lead to more relapses, higher admission rates, and poorer prognosis 52,

53. Even after the introduction of the second-generation antipsychotics (SGA), which have a lower propensity for causing motor side effects 54, the prevalence of antipsychotic-induced movement disorders in EUFEST (EUropean patients with First-Episode Schizophrenia Trial) is still substantial, with a frequency up to 28% 55. A similar prevalence was reported in the Dutch GROUP (Genetic Risk and OUtcome Psychosis) study (for more details about the design, see below), which consisted of relatively young patients with a non-affective psychosis (N=979, mean age, 27 years) using primarily SGA 56. The most common movement disorder at baseline was parkinsonism (28.1%), followed by akathisia (10.4%), tardive dyskinesia (3%), and dystonia (1.6%) 57. Thus it is of clinical importance to recognize patients with movement disorders and to identify those who are prone to antipsychotic-induced movement disorders. Risk factors vary among the different movement disorders and include i) for tardive dyskinesia, first-generation antipsychotics (FGA) 58, 59, intermittent neuroleptic treatment 60, early movement disorders, non-white ethnic origin, and probably older age 34, 35, ii) for parkinsonism, particularly higher dosage of antipsychotic medication, older age, and previous parkinsonism 22, 24, iii) for akathisia, higher dosage, FGA, and previous akathisia 20, and iv) for acute dystonia, lower age, male gender, cocaine use, and FGA 15, 61-63. For tardive dystonia almost no risk factors have been established. Individual genetic variations may also in part explain the large differences in the development of drug-induced movement disorders among patients with schizophrenia using similar antipsychotics 64.

Methods of measuring movement disorders (dyskinesia and parkinsonism)

Clinical rating scales versus mechanical instruments

Movement disorders in schizophrenia research are measured with descriptive clinical observation-based rating scales, i.e. ordinal rating scales with defined anchor points for severity classification (for examples see Figures 1 and 2). They were primarily developed to measure movement disorders induced by drug therapies.

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However, clinical rating scales have several disadvantages, including considerable within rater variability 65 –even within trained raters 66–, lack of linearity (a severity score of “4” may not represent a movement disorders twice as severe as a score of “2”) 67, less sensitivity in the detection of subclinical movement disorders 68-71, and potential reporting bias since raters often are aware of subject status. Therefore research into the vulnerability for subtle movement disorders in antipsychotic-naïve patients with schizophrenia and their relatives might have been hampered by the shortcomings of clinical rating scales. To overcome these limitations, mechanical instruments have been developed 67, 69, 72. Indeed, previous studies including antipsychotic-naive patients with schizophrenia have shown that mechanical measurements are more sensitive and reliable than clinical rating scales for detecting subclinical dyskinesia and parkinsonism 68-75. Of interest, studies on mechanical measurement of dyskinesia mostly focus on the upper extremities, despite the fact that orofacial dyskinesia is more prevalent than finger dyskinesia 76-78, though it may be more difficult to quantify. In addition, no studies have measured (subclinical) movement disorders mechanically in relatives of patients with schizophrenia.

Clinical rating scales

• Dyskinesia

The Abnormal Involuntary Movement Scale (AIMS) 79 is a clinical rating scale to assess the severity of dyskinesia (specifically orofacial movements and extremity and truncal movements) in patients taking antipsychotic medication. The AIMS has been used widely to assess tardive dyskinesia in clinical trials of antipsychotic medications. Due to its simple design and short assessment time (5 minutes), the AIMS can easily be integrated into routine clinical care by a clinician or other trained rater. The clinical scale divides the body into seven different areas (face, tongue, lips, jaw, upper limbs, lower limbs, and - neck, shoulders and hips-). Each area is scored from 0 to 4 to indicate the severity of dyskinesia in an individual (see Figure 1 for an example).

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isFigure 1. Rating scale structure of the AIMS, item 4 (”tongue”)

Anchor pointsNone (0): NoneMinimal (1): Tongue may go partly in or out, but not fully so, or it

may wander from midline (no more than twice) but not reach the teeth.

Mild (2): Tongue goes in or out 1–3 times or wanders from midline and touches the teeth 1–3 times.

Moderate (3): Tongue moves more than 3 times but not continually. It must go past the teeth.

Severe (4): Tongue moves continuously in and out, past the teeth, or laterally.

• Parkinsonism

The clinical rating scale used to assess drug-induced parkinsonism is the motor examination part of the Unified Parkinson Disease Rating Scale (UPDRS) 80. This scale was primarily developed to provide a comprehensive but efficient and flexible means of monitoring Parkinson’s disease-related disability and impairment 81. This scale can also be used in psychiatry research because phenomenologically Parkinson’s disease cannot be distinguished from antipsychotic-induced parkinsonism and therefore this scale can be used to assess drug-induced parkinsonism in clinical trials. The motor part of the UPDRS assesses speech, facial mobility, resting and action tremor (face and each limb), rigidity (neck and each limb), rapid hand and foot movements, rising from a chair, posture, gait, postural stability, and body bradykinesia. A trained rater scores each item from 0 to 4 to indicate parkinsonism severity in a subject (see Figure 2).

Figure 2. Rating scale structure for UPDRS, item 20 (”tremor”)

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Mechanical instruments

• Measurement of dyskinesia and resting tremor using Force Variability (FV)

Dyskinesia can be assessed mechanically by measuring FV, as indicated by the subject’s attempt to exert constant pressure on a load cell (see Figure 3) and measuring the variations in the force applied over time 68,

70, 71, 73 (see Figure 4).

ProcedureParticipants are instructed to exert constant target pressure, first by pushing a button with the index finger of their hand to measure hand dyskinesia, and then by lifting a disposable spatula with their tongue to assess lingual dyskinesia 82. The button and spatula are connected to a load cell attached to a monitor showing a real-time graph indicating target and actual force applied (Figures 3 and 4). The strength required to achieve the target height on the graph is set to an equivalent of 3 Newton for the index finger 71 and 0.8 Newton for the tongue 82. Participants perform each exercise 3 times for a duration of 20 seconds each, separated by 5-second rest periods. The first trial is used to accustom the patient to the test. Mean data of the two subsequent measurements are used for analysis. For dyskinesia, only force variation measured in the 0 to 3 Hz frequency range is used as this reflects dyskinesia best 67 and is unaffected by resting tremor (which is measured at the 4 to 6 Hz frequency band) 83. This technique has been validated for finger dyskinesia 68, 70, 71, 73, 75, 84.

Figure 3. Mechanical instrument for measuring force variability and velocity scaling

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• Measurement of bradykinesia using Velocity Scaling (VS)

Bradykinesia can be mechanically quantified by measuring the ability to adjust movement velocity to changing distances 69, 85. For example, normal individuals, when moving from one fixed target to another, perform different movements in roughly equal time. Thus, moving from one object to another 20 cm away takes approximately the same time as moving to an object 40 cm away when instructed to move as quickly as possible. To do this, the average velocity of the arm movement must increase to compensate for the longer target distance. Participants with bradykinesia (e.g. with Parkinson’s’ disease or drug-induced parkinsonism) are less able to scale their movement velocity and require more time as distances increase (Figures 5 and 6) 69, 86, 87.

Procedure Participants are instructed to flex a handle (Figure 3) with their wrist as fast but as accurately as possible in order to move a flexible cursor presented on the computer screen to a target cursor located at 25 degrees and 45 degrees from the midline of the wrist flexion (Figure 5) 69. The handle is connected to a potentiometer (Figure 3) attached to monitor showing in real-time the target and flexible cursor (Figure 5). Participants perform 32 movement measurements consisting of 16 measurements for each of the two randomly presented target locations, for each hand, for a total of 64 movements 69. VS scores are expressed as degrees per second per degree (deg/s/deg). The VS measure is a valid and reliable measure of antipsychotic-induced bradykinesia 69, 85.

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Figure 5. Test for velocity scaling

Figure 6. Examples of a subject with and without bradykinesia as measured with velocity scaling

Y-axis: Maximum speed (peak velocity) of flexing wrist X-axis: Targeted distance located at 25 degrees and 45 degrees from the midline of the wrist flexion

Example of subjectwith bradykinesia

(Unable to increase peak velocitywhen distance increases)

Example of subjectwithout bradykinesia

(Able to increase peak velocitywhen distance increases)

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isThe GROUP project

The GROUP (Genetic Risk and OUtcome Psychosis) project is a naturalistic longitudinal observational study that investigates the interaction between a number of vulnerability and resilience factors (genetic, somatic, psychological, and social) and genetic variation in the Dutch population. The consortium running the GROUP study consists of four academic psychiatric centres (in Amsterdam, Groningen, Maastricht, and Utrecht) and their affiliated mental health care institutions such as GGz Centraal (a fusion between Symforagroep and GGz Meerkanten). It covers an area of more than 10 million inhabitants and establishes a population-based cohorts of patients with a recently developed psychotic disorder (N=1000), of subjects at risk (brothers/sisters, N=1000), of parents (N=350 pairs), and of healthy volunteers (N=500). Assessments include a psychiatric interview, questionnaires, and neuropsychological tests, including clinical assessment of movement disorders. For a more detailed description of the procedures and instruments, see the first and companion paper about the GROUP study 56 and the website www.group-project.nl) This thesis is based on cross-sectional data from baseline assessment (between January 2004 and December 2007).

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Outline of this thesis

In order to address the main hypothesis as to whether movement disorders are related to antipsychotic naive schizophrenia and to the (genetic) risk of developing the disease, the following studies were conducted:

Movement disorders in patients with schizophrenia and in their siblings In the first study we systematically reviewed the literature to calculate the magnitude of the association between movement disorders in antipsychotic-naïve patients with schizophrenia and separately, in their healthy first-degree relatives (Part II, 2.1). The results of this meta-analysis indicate that the association between movement disorders and schizophrenia is a consistent finding. Furthermore, the higher prevalence of movement disorders in unaffected first-degree relatives suggests that movement disorders could be a sign of (genetic) vulnerability for developing the disease. The higher prevalence of movement disorders in patients with schizophrenia and their first-degree relatives was the starting point for the other studies in this thesis. We examined unaffected siblings (parents have less risk) of patients with schizophrenia to determine whether movement disorders cluster with other vulnerability factors (i.e. schizotypy) for schizophrenia or a psychotic disorder (Part II, 2.2). In addition we investigated the genetic vulnerability that may underlie the association between movement disorders and schizophrenia in patients using antipsychotics. We hypothesised that genes related to the dopamine system are candidate genes for antipsychotic-induced movement disorders in schizophrenia and therefore performed a candidate gene study using previously reported polymorphisms (Part II, 2.3).

Mechanical measurement of dyskinesia and parkinsonism

From the literature we realized that mechanical measurement of dyskinesia and parkinsonism is more sensitive and more reliable than traditional clinical rating scales. Therefore we suggested that research of probably more subtle movement disorders in siblings of patients

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iswith schizophrenia might benefit from mechanical measurement. An instrument was developed (based on comparable earlier mechanical instruments 68-71, 73, 85 that could mechanically quantify dyskinesia and parkinsonism (Figure 3). In addition we examined whether mechanical measurement of lingual force variability (FV) reflected tardive tongue dyskinesia, the most prevalent manifestation of dyskinesia (Part III, 3.1). Finally, we hypothesised that measurement with mechanical instruments would reveal that nonpsychotic siblings of patients with a non-affective psychosis have more dyskinesia and parkinsonism than healthy controls whereas clinical assessments would not (Part III, 3.2).

The last section of this thesis is a general discussion, which integrates the results, followed by suggestions for further research.

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53. Weiden PJ. Understanding and addressing adherence issues in schizophrenia: from theory to practice. J Clin Psychiatry 2007;68 Suppl 14:14-19.

54. Correll CU, Schenk EM. Tardive dyskinesia and new antipsychotics. Current opinion in psychiatry Mar 2008;21(2):151-156.

55. Kahn RS, Fleischhacker WW, Boter H, et al. Effectiveness of antipsychotic drugs in first-episode schizophrenia and schizophreniform disorder: an open randomised clinical trial. Lancet Mar 29 2008;371(9618):1085-1097.

56. GROUP I, Kahn R, Linszen D, et al. Genetic Risk and Outcome of Psychosis (GROUP), a multi-side longitudinal cohort study focused on gene-environment

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isinteraction: Objectives, Recruitment, Assessment Methods and Characteristics of included Participants. Submitted.

57. Koning J, Tenback D, Kahn R, Harten van P. Movement disorders in young adolescents with schizophrenia using antipsychotics. Utrecht: GROUP Symposium; 2010.

58. Correll CU, Leucht S, Kane JM. Lower risk for tardive dyskinesia associated with second-generation antipsychotics: a systematic review of 1-year studies. The American journal of psychiatry Mar 2004;161(3):414-425.

59. Kane JM. Tardive dyskinesia circa 2006. Am J Psychiatry Aug 2006;163(8):1316-1318.

60. van Harten PN, Hoek HW, Matroos GE, Koeter M, Kahn RS. Intermittent neuroleptic treatment and risk for tardive dyskinesia: Curacao Extrapyramidal Syndromes Study III. Am J Psychiatry Apr 1998;155(4):565-567.

61. van Harten PN. Tardive dystonia: male:female ratio. Br J Psychiatry Sep 1991;159:440.

62. van Harten PN, Kahn RS. Tardive dystonia. Schizophr Bull 1999;25(4):741-748.63. van Harten PN, van Trier JC, Horwitz EH, Matroos GE, Hoek HW. Cocaine as

a risk factor for neuroleptic-induced acute dystonia. J Clin Psychiatry Mar 1998;59(3):128-130.

64. Lerer B. Pharmacogenetics of Psychotropic Drugs. Cambridge: Cambridge University Press; 2002.

65. Bergen JA, Griffiths DA, Rey JM, Beumont PJ. Tardive dyskinesia: fluctuating patient or fluctuating rater. Br J Psychiatry May 1984;144:498-502.

66. Lane RD, Glazer WM, Hansen TE, Berman WH, Kramer SI. Assessment of tardive dyskinesia using the Abnormal Involuntary Movement Scale. J Nerv Ment Dis Jun 1985;173(6):353-357.

67. Lohr JB, Caligiuri MP. Quantitative instrumental measurement of tardive dyskinesia: a review. Neuropsychopharmacology Jun 1992;6(4):231-239.

68. Caligiuri MP, Lohr JB. Fine force instability: a quantitative measure of neuroleptic-induced dyskinesia in the hand. Journal of Neuropsychiatry and Clinical Neurosciences Fall 1990;2(4):395-398.

69. Caligiuri MP, Lohr JB, Ruck RK. Scaling of movement velocity: a measure of neuromotor retardation in individuals with psychopathology. Psychophysiology Jul 1998;35(4):431-437.

70. Cortese L, Caligiuri MP, Malla AK, Manchanda R, Takhar J, Haricharan R. Relationship of neuromotor disturbances to psychosis symptoms in first-episode neuroleptic-naive schizophrenia patients. Schizophr Res Jun 1 2005;75(1):65-75.

71. Dean CE, Russell JM, Kuskowski MA, Caligiuri MP, Nugent SM. Clinical rating scales and instruments: how do they compare in assessing abnormal, involuntary movements? J Clin Psychopharmacol Jun 2004;24(3):298-304.

72. Caligiuri MP, Lohr JB, Jeste DV. Parkinsonism in neuroleptic-naive schizophrenic patients. Am J Psychiatry Sep 1993;150(9):1343-1348.

73. Caligiuri MP, Lohr JB. A disturbance in the control of muscle force in neuroleptic-naive schizophrenic patients. Biol Psychiatry Jan 15 1994;35(2):104-111.

74. Caligiuri MP, Lohr JB, Bracha HS, Jeste DV. Clinical and instrumental assessment of neuroleptic-induced parkinsonism in patients with tardive dyskinesia. Biol Psychiatry Jan 15 1991;29(2):139-148.

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75. Caligiuri MP, Lohr JB, Rotrosen J, Adler L, Lavori P, Edson R, Tracy K. Reliability of an instrumental assessment of tardive dyskinesia: results from VA Cooperative Study #394. Psychopharmacology (Berl) Jul 1997;132(1):61-66.

76. Jeste D.V. WRJ. Understanding and treating dyskinesia. New York: Guilford; 1982.77. McCreadie RG, Srinivasan TN, Padmavati R, Thara R. Extrapyramidal symptoms

in unmedicated schizophrenia. J Psychiatr Res May 2005;39(3):261-266.78. Mittal VA, Neumann C, Saczawa M, Walker EF. Longitudinal progression of

movement abnormalities in relation to psychotic symptoms in adolescents at high risk of schizophrenia. Archives of general psychiatry Feb 2008;65(2):165-171.

79. Guy E. Abnormal Involuntary Movement Scale, ECDEU assessment manual for psychopharmacology: National institute of mental Health, U.S. Department Health and Human Services; 1976.

80. Martinez-Martin P, Gil-Nagel A, Gracia LM, Gomez JB, Martinez-Sarries J, Bermejo F. Unified Parkinson’s Disease Rating Scale characteristics and structure. The Cooperative Multicentric Group. Mov Disord Jan 1994;9(1):76-83.

81. Fahn S, Elton R, memebers Up. Unified Parkinsons Disease Rating Scale. In: Fahn S, Marsden C, Goldstein M, Calne D, eds. Recent developments in Parkinsons disease. Vol 2. Florham Park: Macmillan Healthcare Information; 1987:153-156.

82. Koning JP, Tenback DE, Kahn RS, Van Schelven LJ, Van Harten PN. Instrument measurement of lingual force variability reflects tardive tongue dyskinesia. J Med Eng Technol 2010;34(1):71-77.

83. Stein RB, Oguztoreli MN. Tremor and other oscillations in neuromuscular systems. Biol Cybern 1976;22(3):147-157.

84. Caligiuri MP, Lohr JB, Vaughan RM, McAdams LA. Fluctuation of tardive dyskinesia. Biol Psychiatry Sep 1 1995;38(5):336-339.

85. Caligiuri MP, Teulings HL, Filoteo JV, Song D, Lohr JB. Quantitative measurement of handwriting in the assessment of drug-induced parkinsonism. Hum Mov Sci Oct 2006;25(4-5):510-522.

86. Benecke R. The pathophysiology of Parkinson’s disease. In: Quinn NP, Jenner PG, eds. Movement disorders. San Diego: Academic Press; 1989:59-72.

87. Berardelli A, Dick JP, Rothwell JC, Day BL, Marsden CD. Scaling of the size of the first agonist EMG burst during rapid wrist movements in patients with Parkinson’s disease. J Neurol Neurosurg Psychiatry Nov 1986;49(11):1273-1279.

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Part II

Movement disorders in patients with schizophrenia and in their siblings

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Chapter 2.1

Dyskinesia and parkinsonism in antipsychotic-naive patients with schizophrenia, first-degree relatives and healthy controls: a meta-analysis

Jeroen P Koning*, Diederik E Tenback*, Jim van Os, André Aleman, René S Kahn, Peter N van Harten

Published in Schizophrenia Bulletin, 2010 Jul;36(4):723-31.

* Both authors contributed equally

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Background

Several studies have reported the presence of dyskinesia and parkinsonism in antipsychotic-naive patients with schizophrenia as well as in their first-degree relatives. These movement disorders may therefore form an integral part of the illness and its (genetic) liability.

Methods

A systematic search was conducted in the Medline, EMBASE, and PsychINFO databases to identify studies reporting on dyskinesia and parkinsonism assessed in antipsychotic-naive patients with schizophrenia (n=213) and controls (n=242) and separately in non-ill first-degree relatives (n=395) and controls (n=379). Effect sizes were pooled using random effect models to calculate odds ratios (ORs) to compare the risk of these movement disorders among patients and healthy relatives each to matched controls.

Results

Antipsychotic-naive schizophrenia was found to be strongly associated with dyskinesia (OR: 3.59; 95% CI: 1.53-8.41) and parkinsonism (OR: 5.32; 95% CI: 1.75-16.23) compared to controls. Dyskinesia and parkinsonism were also significantly more prevalent in healthy first-degree relatives of patients with schizophrenia as compared to healthy controls (OR: 1.38; 95% CI: 1.06-1.81 and OR: 1.37; 95% CI: 1.05-1.79 respectively).

Conclusion

The results suggest that movement disorders, and by inference abnormalities in the nigrostriatal pathway, are not only associated with schizophrenia itself, but may also be related to the (genetic) risk of developing the disease.

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Introduction

Movement disorders such as dyskinesia and parkinsonism are primarily associated with the use of antipsychotic medication, particularly in patients with schizophrenia 1-3. However, involuntary hyper- and hypokinetic movements have been described in patients with schizophrenia long before the introduction of antipsychotic medication 4-6. This suggests that these abnormal movements may be related to the illness itself rather than just the result of antipsychotic medication. If abnormal movements were related to the disease, one would expect these movement disorders to be present in antipsychotic-naive patients with schizophrenia. However, although numerous studies 7-28 examined the presence of these abnormal movements in antipsychotic-naive patients with schizophrenia, only a few have compared the prevalence of these signs with that in a matched healthy control group 7, 8, 11, 12, 15,

22, 24. Interestingly, while the uncontrolled studies (mostly) observed movement disorders in antipsychotic-naive patients 9, 10, 13, 14, 16-21, 25-28 the controlled studies generally did not report significantly more movement disorders in patients than in healthy controls 7, 8, 11, 12, 15, 24. If dyskinesia and parkinsonism are present in first-degree relatives of patients with schizophrenia, these movement disorders may be related to the (genetic) risk of developing the disease. However, studies comparing the presence of dyskinesia and parkinsonism in healthy relatives and controls 22, 29-36 generally report inconclusive results. Therefore, we conducted a meta-analysis to systematically compare the prevalences of dyskinesia and parkinsonism in schizophrenia patients and healthy first-degree relatives each to age matched controls in the same study.

Methods

Data SourcesThe registers of Medline, EMBASE and PsychINFO were searched without year limits up to January 2008 using the following keywords: (dyskinesia or parkinsonism or movement disorders) combined with (antipsychotic-naive or treatment-naïve or naïve and schizophrenia) and separately with (relatives or family members or parents or offspring or children or siblings and schizophrenia). In addition, all relevant references cited in the articles

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gsfound were also retrieved. This yielded 503 results, of which 40 original studies contained relevant information. As listed in figure 1, of these 40 studies, 11 were included according to our inclusion criteria: (1) examined dyskinesia and/or parkinsonism in antipsychotic-naive patients with schizophrenia or in their healthy first-degree relatives, (2) compared the results with a healthy control group matched for age, (3) reported sufficient data to obtain an effect size as measured by prevalences or mean scores, standard deviations, number of subjects in each group. Of the 29 excluded studies, 16 studies were on antipsychotic–naïve patients 9, 10, 13, 14, 16, 17, 19-21, 23, 25-28, 37, 38 of which 13 had no control group 9, 10, 13, 14, 16, 17, 19-21, 25-28 ,one study was a case-control study 23 and 2 studies did not specify for dyskinesia or parkinsonism 37, 38. Of the remaining 13 excluded studies on healthy relatives 32, 34, 35, 39-48 (7 on offspring 39, 40, 42-45, 47, 4 on parents and siblings 32, 34, 35, 46 1 on siblings 48 and 1 on first and second degree relatives 41), 12 studies did not specify for dyskinesia or parkinsonism 32, 34, 35, 39, 40, 42-48 and 1 did not include a control group 41. We had access to the original data of 1 study 29 and 1 author was contacted and provided the information on dyskinesia in the patient and control group, which data was not clearly presented in the published manuscript 7.

Statistical MethodsEffects were pooled calculating the odds ratio comparing the risk of dyskinesia and/or parkinsonism of patients and first-degree relatives, each to age matched healthy controls. The presence of dyskinesia in studies on patients and matched controls was defined by a score of 2 or greater on one item on the Abnormal Involuntary Movement Scale (AIMS) 49 or on the Extrapyramidal Symptoms Rating Scale dyskinesia (ESRS-IV) 50. Presence of parkinsonism in patient studies was defined by a total mean score of at least 0.3 on the Simpson Angus Rating Scale (SAS), which is a 10-item rating scale that has been validated and used widely for the assessment of neuroleptic induced parkinsonism in both clinical practice and research setting 51. If the included studies used less stringent cut-off points and the result sections of those studies provided sufficient information, the results were adjusted using the mentioned research criteria for tardive dyskinesia 7, 25, 52 and parkinsonism 12, 16. The prevalences of dyskinesia in 2 studies 7,12 and of parkinsonism in 1 study 8 could be adjusted according to the cut-off criteria, as sufficient detailed

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information was reported in the result section. Of one study we received information from the author 7.

In case of cell frequencies equal zero using Odds Ratios, 0.5 was added to the cell frequencies to solve this problem by eliminating any zeros but creating a downward bias and slightly understating the strength of the relationship 53, 54. The prevalences of dyskinesia and parkinsonism in studies on first-degree relatives were presented as mean scores, which were used to calculate Cohen’s d (a standardized mean difference effect size) that could be converted into odds ratios with the use of formula 1 55. Formula 1: ESor = e (π x ES / √3)

In this formula, ESor is the odds-ratio equivalent from the continuous dependent measure, ES= Effect size, π = 3.14, and e = natural logarithm.

The following measures or items from the different studies represent dyskinesia in the pooled analysis: AIMS 22, modified AIMS 31, involuntary movements from the Woods Scale (including choreiform and athetotiform movements) 56, limb and orofacial dyskinesia items from the Cambridge Neurological Inventory 30, chorea, athetosis, choreoathetosis, akathisia in accordance with the textbook definitions 36, 57, choreiform movements (from the Woods scale) 29. For parkinsonism the components included were: Simpson Angus Scale,22 modified AIMS including parkinsonian signs 31, involuntary movements from the Woods Scale (including postural, intentional/resting tremor) 33, glabellar sign, increased limb tone, decreased associated movements in walking, shuffling gait, arm dropping test, tremor and neck rigidity from the Cambridge Neurological Inventory 30, resting tremor in accordance with the textbook definition 36,

57, cogwheel rigidity, parkinson gait and resting tremor (from the Woods scale) 29. As the distribution of the mean prevalence scores in siblings and controls were skewed, this might invalidate the results as Cohen’s d assumes normality 58. We therefore combined the probabilities from the independent studies for which a Z-value could be calculated 22, 29-31,

36 to test whether there might be sufficient evidence to reject the null hypothesis 59. Weighting of the studies was according to their power. Meta-regression analysis was used to investigate the impact of continuous study moderators on overall heterogeneity. The regression models were estimated by unrestricted maximum likelihood. For the prevalences of dyskinesia and parkinsonism the following three

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gsmoderators were tested: mean age of patient, mean age at onset, mean duration of untreated illness and sex. To examine the statistical heterogeneity of the individual studies, we tested a homogeneity statistic, Q. Additionally, to examine the possibility of publication bias, a method to indicate the number of unpublished studies with null effects that must reside in file drawers to reduce the observable effect size to a negligible level, we used the fail safe number according to Orwin 54, 60. The threshold criterion for a negligible level was set at an odds ratio of 1.2. All analyses were carried out in the random effects model using the Comprehensive Meta-Analysis package (www.meta-analysis.com).

Results

Table 1 lists the characteristics of the studies, which included antipsychotic-naive patients with schizophrenia. As presented in Figure 2, the results of our meta-analysis indicate that dyskinesia is strongly associated with schizophrenia with an odds ratio of 3.59 (p<0.01). This analysis included 5 studies with a group size of 189 patients with schizophrenia and 218 controls. Excluding the study 22 that contributed most to the effect would reduce the significance level into a trend (OR 3.72; p=0.08). As presented in Figure 3, the odds ratio for an association with parkinsonism was 5.32 (p<0.01). The analysis of parkinsonism included 3 studies, with a group size of 84 patients with schizophrenia and 150 controls. If we excluded the study that contributed most to the effect 22, the significance level would be reduced to a trend; OR 6.53 (p=0.09) An increase in the prevalence of dyskinesia with increasing age was significant and similar in both patients and controls (ß = 0.07, p=0.02 and ß = 0.06, p<0.01). In addition, the prevalence of dyskinesia increased significantly with duration of untreated schizophrenia (ß = 0.28, p<0.01). There was no significant correlation with age at onset of schizophrenia (ß = 0.15, p=0.07). However, age, duration of untreated schizophrenia, and age at onset were significantly correlated with each other (r >0.85, p<0.05). For parkinsonism no significant increase in prevalence was observed in either the patients or controls with regard to age (ß = 0.01, p=0.44 and ß= 0.03, p=0.27 respectively), duration of untreated schizophrenia (ß = 0.04 p=0.43), or age at onset (ß = 0.01, p=0.82). Gender differences could not be calculated as only 1 study provided information on gender distribution in the result section 22.

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Table 2 contains information regarding studies of dyskinesia and parkinsonism in first-degree relatives of patients with schizophrenia. Six studies evaluated dyskinesia and parkinsonism including 395 siblings and 379 healthy controls, of which 4 were on siblings, 30, 31, 33, 36 1 on parents and siblings 22 and 1 on parents 29. The meta-analysis indicates small but significant differences when the prevalences of dyskinesia and parkinsonism in first-degree relatives were compared with healthy control subjects (Figures 4 and 5), with a mean weighted odds ratio of 1.38 (95% CI: 1.06-1.81) and z-value of 2.28 (p=0.02) for dyskinesia and an odds ratio of 1.37 (95% CI: 1.05-1.79) and z-value of 2.21 (p=0.03) for parkinsonism.

Heterogeneity and publication biasNo significant heterogeneity was apparent for the dyskinesia and parkinsonism analyses in patients versus controls (Q = 1.79, p=0.77 and Q = 0.40, p=0.82), or in siblings versus controls (Q = 0.73, p=0.98 and Q = 2.30, p=0.81). The fail-safe number was large enough to provide credence to our findings for the dyskinesia and parkinsonism analyses in patients versus controls (30 and 25), but suggested that the possibility of publication bias warrants a cautious interpretation of the results for siblings versus controls (5 and 5 studies, which is almost equal to the number of published studies).

Discussion

This meta-analysis about dyskinesia and parkinsonism integrated the results of 6 studies in antipsychotic-naive patients (n=213) with schizophrenia and healthy controls (n=242) and separately the results of 6 studies in non-ill siblings (n=395) and healthy control subjects (n=379). We found schizophrenia to be strongly associated with dyskinesia and parkinsonism. Since we only included studies regarding antipsychotic-naive patients, these findings suggest that these movement disorders are related to schizophrenia itself and cannot be explained on the basis of the use of antipsychotic medication. Interestingly, these results are consistent with reports of similar motor symptoms in schizophrenia patients in the pre-neuroleptic era 4-6 and with results of recent publications on neuroleptic-naive patients and relatives using more liberal inclusion criteria 61,62, 63. Age and duration of illness correlated positively with the prevalence of dyskinesia, but as the correlation between age and

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gsduration of illness (and age of illness onset) itself was very high (r> 0.85), it was not possible to discriminate reliable between these factors using multivariate meta-regression analysis due to this multicollinearity. However, since we found no difference between patients and controls on the effect of age on the prevalence, age is most likely a general risk factor for dyskinesia. Additionally, gender differences could not be calculated as only 1 study provided information on gender distribution in the result section 22. Dyskinesia and parkinsonism were also more prevalent in healthy first-degree relatives of patients with schizophrenia compared to controls. The differences were small but significant, suggesting that these movement disorders might also be related to the (genetic) risk of developing schizophrenia. One possible mechanism for a common (genetic) vulnerability for movement disorders and schizophrenia may be an increased presynaptic dopamine activity and/or sensitivity in the nigrostriatal pathway. Imaging studies have not only shown an increased accumulation of labeled dopamine in the striata of unmedicated patients with schizophrenia 64, 65, but also in healthy first-degree relatives (children and siblings) of patients with schizophrenia 66. It has indeed been suggested that in schizophrenia, striatal dysfunction initially manifests itself in the form of movement disorders, and gradually leads to prodromal and eventually to psychotic symptoms as the striatal circuitry matures during adolescence 67-69. Some limitations in this meta-analysis should be noted. First, there was diversity in items and scales used to evaluate dyskinesia and parkinsonism. The adjustments of the diagnostic criteria for dyskinesia and parkinsonism have been thought to facilitate the differences among the studies. In addition, the use of pooled odds ratios as a measure of standardized mean difference should produce results independent of scale and range. Second, the inclusion criteria were limited to studies reporting on dyskinesia and parkinsonism. Therefore, prevalence numbers of other motor abnormalities including neurological soft signs, such as motor coordination and imbalance, are excluded (for a review see Wolff 61). However, by focusing on dyskinesia and parkinsonism which are rather specific for schizophrenia contrary to soft neurological signs which are also seen in mood disorders 70, the strength of the relationship between hard neurological signs and schizophrenia could be estimated.Third, the Duration of Untreated Psychosis (DUP) can be a confounder because longer duration of illness may increase the risk of dyskinesia and parkinsonism. In this meta-analysis one study from Asia 22 had the

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largest DUP and indeed this study contributed the largest effect on the difference in prevalence’s of dyskinesia and parkinsonism between patients and controls. Fourth, a methodological problem in meta-analysis is the variance between the studies in the way the movement disorders are assessed and differentiated from other syndromes. This is particularly a problem for the symptom bradykinesia, which can resemble parkinsonism but also negative symptoms in schizophrenia and other disorders. However, the included studies used the SAS instrument, which items measure mainly rigidity and tremor, which are specific symptoms of parkinsonism. A recent study suggested that the mean cut-off score for the SAS of 0.3 is probably too low 71 resulting in a lower specificity. However, the cut-off point of 0.3 has been validated 51 and is widely accepted in the research of drug induced movement disorders. In this meta-analysis the frequently applied research criteria (score ≥ 2 on the AIMS or ESRS-IV) are used for the screening of dyskinesia. A more stringent criterion such as the Schooler and Kane criteria 72, would underestimate the prevalence. Moreover, prospective studies show that patients with dyskinesia based on the less stringent criteria as used in this meta-analysis, will later meet the Schooler and Kane criteria 52, 72. Fifth, it was not possible to differentiate between dyskinesia and parkinsonism in one study 33 because the involuntary movements subscale included items of both movement disorders (postural/intentional/resting tremors, choreiform and athetotiform movements). Since both movement disorders reflect nigrostriatal dysfunction, the results were incorporated in both analyses (Figures 4 and 5). This again resulted in an underestimation of the effect, since the effect size was very small and insignificant. Excluding that study from the meta-analysis would not have influenced the results. Sixth, one study with healthy parents was included in the meta-analysis on first-degree relatives. Since, parents have less risk on developing schizophrenia than siblings this may have somewhat underestimated the effect. Seventh, the assessments of dyskinesia and parkinsonism in siblings were not all conducted blind to the participant’s group status, which could bias results. However, excluding studies in which the raters were not blind to subjects status 30, 56 would not have influenced the results significantly. Eighth, the skewness of the distributions of the mean scores of the siblings groups could be an issue as Cohen’s d assumes normality 58. Therefore, an additional weighted Z-method was used, validating the statistical differences between the sibling and control groups gained by the meta-analysis. It would be more ideal to restrict to psychotropic-naive patients

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gsand relatives to strengthen our conclusion. However, antipsychotics are by far the most frequent cause of drug induced movement disorders. Moreover, only one study including antipsychotic-naive patients reported about the specific absence of other medication 22. Of the 6 studies on relatives, 5 screened systematically for psychopathology and excluded those with a positive psychiatric history 29-31, 33, 36, minimizing the chance of any other psychotropic medication use. Finally, only a proportion of the patients with schizophrenia demonstrated movement disorders and the differences between siblings and controls were small, though significant. Underestimation of the true prevalence of movement disorders might be one explanation for this finding, since even trained raters, utilizing standard rating scales, have proven to be less sensitive to subclinical dyskinesia and parkinsonism than mechanical assessment 73. Also, schizophrenia is probably heterogeneous with regard to etiology and pathophysiology 74, 75, therefore patients with distinct nigrostriatal dysfunction may constitute a subgroup in schizophrenia. The findings of higher rates of dyskinesia and parkinsonism in this meta-analysis is clinically relevant as the presence of these movement disorders at baseline have predicted poorer outcome of schizophrenia 9, 76, 77. Future research should examine whether dyskinesia and parkinsonism constitute useful endophenotypes 78 and apply to the following criteria; the endophenotype is, 1) associated with the illness in the population, 2) heritable, 3) primarily state independent, 4) within families, co-segregating with the illness, 5) found in affected family members is found in nonaffected family members at a higher rate than in the general population. The results of the current meta-analysis are in line with the first and fifth criterion. The third criterion is evidenced by a longitudinal study 21. Therefore, extended family studies are needed to estimate the heritability and co-segregation of these movement disorders in schizophrenia. As the results of this meta-analysis show that the effects in first-degree relatives are small, future research may benefit from instrumental measurement. In conclusion, the current results suggest that movement disorders, and by inference abnormalities in the nigrostriatal pathway, are not only associated with schizophrenia itself, but may also be related to the (genetic) risk of developing the disease. Moreover, research focusing on the use of symptoms of dyskinesia and parkinsonism as early predictors for schizophrenia may be warranted.

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t./C

on

tr.

C

ou

ntr

y

D

ys

kin

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ia

(m

ea

n s

co

re)

P

at.

/Co

ntr

.

P

ark

ins

on

ism

(me

an

sc

ore

)

Pa

t./C

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tr.

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en

(3

0)

(sib

ling

s)

2

1/2

6

3

1/3

1

2

9/4

2

H

on

g K

on

g

0

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0

.10

/0.0

Ta

rbo

x (

36

) (s

iblin

gs)

3

3/5

5

3

1/2

9

3

9/4

2

U

SA

28

6/2

16

0.3

/0.0

Eg

an

(3

1)

(sib

ling

s)

1

85

/88

36

/33

43

/42

US

A

1

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/0.7

5

0

.58

/0.1

9

Ism

ail

(33

) (s

iblin

gs)

2

1/7

5

3

8/3

6

7

3/7

9

S

we

de

n

0

.19

/0.0

2

0

.19

/0.0

2

McC

rea

die

(2

2)

(pa

ren

ts a

nd

sib

ling

s)

1

03

/10

1

6

3/6

3

4

8/4

7

In

dia

0.5

5/0

.43

11

% /

6%

†

Ap

pe

ls (

29

) (p

are

nts

)

3

2/3

4

5

5/5

5

5

0/5

0

N

eth

erl

an

ds

0

.63

/0.4

0.0

3/0

.06

† N

o m

ea

n s

co

res w

ere

giv

en

, o

nly

pe

rce

nta

ge

s o

f S

AS

me

an

sco

res o

f a

t le

ast

0.3

(se

e m

eth

od

se

ctio

n).

Stu

dy

N

Pa

t./C

on

tr.

M

ea

n a

ge

(Ye

ars

)

Pa

t./C

on

tr.

M

ale

s

(%

) P

at.

/Co

ntr

.

M

ea

n

Du

rati

on

Il

lne

ss

(Ye

ars

)

C

ou

ntr

y

D

ys

kin

es

ia

(%

) P

at.

/Co

ntr

.

P

ark

ins

on

ism

(%)

Pa

t./C

on

tr.

Ch

orf

i (1

1)

5

0/5

0

2

4/2

4

8

8/N

R

1

/-

M

oro

cco

0/0

b

-/

-

Co

rte

se

(1

2)

3

9/2

5

2

4/2

4

8

2/5

6

F

irst

Ep

iso

de

C

an

ad

a

5

/0c

1

8/0

d

Ho

ffm

an

(1

5)

Mo

ussa

ou

i (2

4)

6

2/2

1

30

/29

NR

6/-

Mo

rocco

26

/0e

-/

-

Ca

ligiu

ri (

7)

1

7/2

1

3

7/3

7

1

00

/10

0

6

/-

U

SA

6/0

b

-/

-

Ca

ligiu

ri (

8)

2

4/2

4

4

2/4

2

8

3/N

R

5

/-

U

SA

-/-

4

/0d

McC

rea

die

(22

)

21

/10

1

6

5/6

3

4

3/4

7

1

4/-

Ind

ia

3

8/1

5e

2

4/6

d

Tabl

e 1. C

hara

cter

istics

and p

reva

lenc

es of

dysk

ines

ia an

d par

kins

onism

in an

tipsy

chot

ic-na

ive p

atie

nts w

ith sc

hizo

phre

niaa an

d hea

lthy c

ontro

ls.

35

mov

emen

t di

sord

ers i

n pa

tien

ts w

ith

schi

zoph

reni

a an

d in

the

ir si

blin

gs

32

Ta

ble

1.

Ch

ara

cte

ristics a

nd

pre

va

len

ce

s o

f d

yskin

esia

an

d p

ark

inso

nis

m in

an

tip

sych

otic-n

aiv

e

pa

tie

nts

with

sch

izo

ph

ren

iaa a

nd

he

alth

y c

on

tro

ls.

a

10

0%

Dia

gn

ostic a

nd

Sta

tistica

l M

an

ua

l o

f M

en

tal D

iso

rde

rs,

Th

ird

Ed

itio

n,

Re

vis

ed

, o

r D

iag

no

stic a

nd

Sta

tistica

l M

an

ua

l o

f M

en

tal D

iso

rde

rs,

Fo

urt

h E

ditio

n,

cri

teri

a.

b A

bn

orm

al In

vo

lun

tary

Mo

ve

me

nt

Sca

le (

AIM

S),

ite

m s

co

re ≥

2 (

rese

arc

h c

rite

ria

) c E

xtr

ap

yra

mid

al S

ym

pto

ms S

ca

le (

ES

RS

-IV

), ite

m s

co

re ≥

2.

d

Sim

pso

n A

ng

us S

ca

le (

SA

S),

me

an

sco

re o

f a

t le

ast

0.3

. e

AIM

S,

ite

m s

co

re ≥

3 o

r o

n 2

ite

ms s

co

re ≥

2 (

Sch

oo

ler

an

d K

an

e c

rie

ria

72)

NR

: N

ot

Re

po

rte

d

T

ab

le 2

. C

ha

racte

ristics a

nd

me

an

sco

res o

f d

yskin

esia

an

d p

ark

inso

nis

m in

he

alth

y f

irst-

de

gre

e

rela

tive

s o

f p

atie

nts

with

sch

izo

ph

ren

ia a

nd

he

alth

y c

on

tro

ls

Stu

dy

N

Pa

t./C

on

tr.

M

ea

n a

ge

(Ye

ars

)

Pa

t./C

on

tr.

M

ale

s

(%

)

Pa

t./C

on

tr.

C

ou

ntr

y

D

ys

kin

es

ia

(m

ea

n s

co

re)

P

at.

/Co

ntr

.

P

ark

ins

on

ism

(me

an

sc

ore

)

Pa

t./C

on

tr.

Ch

en

(3

0)

(sib

ling

s)

2

1/2

6

3

1/3

1

2

9/4

2

H

on

g K

on

g

0

.0/0

.0

0

.10

/0.0

Ta

rbo

x (

36

) (s

iblin

gs)

3

3/5

5

3

1/2

9

3

9/4

2

U

SA

28

6/2

16

0.3

/0.0

Eg

an

(3

1)

(sib

ling

s)

1

85

/88

36

/33

43

/42

US

A

1

.15

/0.7

5

0

.58

/0.1

9

Ism

ail

(33

) (s

iblin

gs)

2

1/7

5

3

8/3

6

7

3/7

9

S

we

de

n

0

.19

/0.0

2

0

.19

/0.0

2

McC

rea

die

(2

2)

(pa

ren

ts a

nd

sib

ling

s)

1

03

/10

1

6

3/6

3

4

8/4

7

In

dia

0.5

5/0

.43

11

% /

6%

†

Ap

pe

ls (

29

) (p

are

nts

)

3

2/3

4

5

5/5

5

5

0/5

0

N

eth

erl

an

ds

0

.63

/0.4

0.0

3/0

.06

† N

o m

ea

n s

co

res w

ere

giv

en

, o

nly

pe

rce

nta

ge

s o

f S

AS

me

an

sco

res o

f a

t le

ast

0.3

(se

e m

eth

od

se

ctio

n).

Stu

dy

N

Pa

t./C

on

tr.

M

ea

n a

ge

(Ye

ars

)

Pa

t./C

on

tr.

M

ale

s

(%

) P

at.

/Co

ntr

.

M

ea

n

Du

rati

on

Il

lne

ss

(Ye

ars

)

C

ou

ntr

y

D

ys

kin

es

ia

(%

) P

at.

/Co

ntr

.

P

ark

ins

on

ism

(%)

Pa

t./C

on

tr.

Ch

orf

i (1

1)

5

0/5

0

2

4/2

4

8

8/N

R

1

/-

M

oro

cco

0/0

b

-/

-

Co

rte

se

(1

2)

3

9/2

5

2

4/2

4

8

2/5

6

F

irst

Ep

iso

de

C

an

ad

a

5

/0c

1

8/0

d

Ho

ffm

an

(1

5)

Mo

ussa

ou

i (2

4)

6

2/2

1

30

/29

NR

6/-

Mo

rocco

26

/0e

-/

-

Ca

ligiu

ri (

7)

1

7/2

1

3

7/3

7

1

00

/10

0

6

/-

U

SA

6/0

b

-/

-

Ca

ligiu

ri (

8)

2

4/2

4

4

2/4

2

8

3/N

R

5

/-

U

SA

-/-

4

/0d

McC

rea

die

(22

)

21

/10

1

6

5/6

3

4

3/4

7

1

4/-

Ind

ia

3

8/1

5e

2

4/6

d

Tabl

e 2. C

hara

cter

istics

and m

ean s

core

s of d

yski

nesia

and p

arki

nson

ism in

heal

thy f

irst-d

egre

e rel

ativ

es of

patie

nts w

ith sc

hizo

phre

nia a

nd he

alth

y co

ntro

ls

36

part II

Figure 1. Flowchart of included studies

Figure 2. Forest plot and odds ratios of dyskinesia in antipsychotic-naive patients with schizophrenia compared to healthy controls

33

19studies

Relatives

21studies

Antipsychotic‐naive

patients

4studies

Siblings

1study

Parents&

siblings

1study

Parents

Exclusionof463studies

‐Norelevantinformation

40studies


patientsandRelatives

503studies

(Literaturesearch)


‐1,nocontrolgroup

‐12,nospecificationof

dyskinesia/parkinsonism


‐13,nocontrolgroup

‐2,nospecificationof

dyskinesia/parkinsonism

‐1,case‐controlstudy

norelevantinformation

6studiesRelatives5studies


patients

Figure1.Flowchartofincludedstudies.

34

Study name Statistics for each study Odds ratio and 95% CIOdds Lower Upper ratio limit limit Z-Value p-Value

Chorfi 1.00 0.06 16.43 0.00 1.00Cortese 3.40 0.16 73.81 0.78 0.44Caligiuri 3.91 0.15 102.26 0.82 0.41Hoffman 15.26 0.87 266.31 1.87 0.06McCreadie 3.53 1.25 9.96 2.38 0.02

3.59 1.53 8.41 2.94 p<0.010.01 0.1 1 10 100

Figure2.Forestplotandoddsratiosofdyskinesiainantipsychoticnaivepatientswithschizophrenia

comparedtohealthycontrols

Pooled


Caligiuri 3.13 0.12 80.68 0.69 0.49Cortese 11.77 0.64 215.89 1.66 0.10McCreadie 4.95 1.35 18.15 2.41 0.02

5.32 1.75 16.23 2.94 p<0.01

0.01 0.1 1 10 100

Figure3.Forestplotandoddsratiosofparkinsonisminantipsychoticnaivepatientswithschizophrenia


Pooled

37

mov

emen

t di

sord

ers i

n pa

tien

ts w

ith

schi

zoph

reni

a an

d in

the

ir si

blin

gsFigure 3. Forest plot and odds ratios of parkinsonism in antipsychotic-naive patients with schizophrenia compared to healthy controls

Figure 4. Forest plot and odds ratios of dyskinesia in healthy first-degree relatives of patients with schizophrenia and in healthy controls

Figure 5. Forest plot and odds ratios of parkinsonism in healthy first-degree relatives of patients with schizophrenia and in healthy controls

34


Chorfi 1.00 0.06 16.43 0.00 1.00Cortese 3.40 0.16 73.81 0.78 0.44Caligiuri 3.91 0.15 102.26 0.82 0.41Hoffman 15.26 0.87 266.31 1.87 0.06McCreadie 3.53 1.25 9.96 2.38 0.02

3.59 1.53 8.41 2.94 p<0.010.01 0.1 1 10 100

Figure2.Forestplotandoddsratiosofdyskinesiainantipsychoticnaivepatientswithschizophrenia


Pooled


Caligiuri 3.13 0.12 80.68 0.69 0.49Cortese 11.77 0.64 215.89 1.66 0.10McCreadie 4.95 1.35 18.15 2.41 0.02

5.32 1.75 16.23 2.94 p<0.01

0.01 0.1 1 10 100

Figure3.Forestplotandoddsratiosofparkinsonisminantipsychoticnaivepatientswithschizophrenia


Pooled

35


McCreadie 1.35 0.82 2.23 1.19 0.23Egan

• 1.36 0.85 2.16 1.28 0.20Ismail 1.32 0.55 3.17 0.61 0.54Chen 1.86 0.65 5.32 1.16 0.25Tarbox 1.90 0.86 4.17 1.59 0.11Appels 0.82 0.34 1.97 -0.45 0.66

1.37 1.05 1.79 2.28 0.020.01 0.1 1 10 100

Figure5.Forestplotandoddsratiosofparkinsonisminhealthyfirstdegreerelativesofpatientswithschizophreniaandin

healthycontrols

•Results are corrected for psychotropic medication use (neuroleptics and SSRIs), otherwise p=0.01

Pooled


McCreadie 1.29 0.78 2.12 0.99 0.32Egan

• 1.55 0.98 2.46 1.86 0.06Ismail 1.32 0.55 3.17 0.61 0.54Chen 1.00 0.35 2.84 0,00 1.00Tarbox 1.46 0.67 3.20 0.95 0.34Appels 1.43 0.59 3.43 0.79 0.43

1.38 1.06 1.81 2.37 0.020.01 0.1 1 10 100

Figure4.Forestplotandoddsratiosofdyskinesiainhealthyfirstdegreerelativesofpatientswithschizophrenia

andinhealthycontrols


Pooled

35


McCreadie 1.35 0.82 2.23 1.19 0.23Egan

• 1.36 0.85 2.16 1.28 0.20Ismail 1.32 0.55 3.17 0.61 0.54Chen 1.86 0.65 5.32 1.16 0.25Tarbox 1.90 0.86 4.17 1.59 0.11Appels 0.82 0.34 1.97 -0.45 0.66

1.37 1.05 1.79 2.28 0.020.01 0.1 1 10 100

Figure5.Forestplotandoddsratiosofparkinsonisminhealthyfirstdegreerelativesofpatientswithschizophreniaandin

healthycontrols


Pooled


McCreadie 1.29 0.78 2.12 0.99 0.32Egan

• 1.55 0.98 2.46 1.86 0.06Ismail 1.32 0.55 3.17 0.61 0.54Chen 1.00 0.35 2.84 0,00 1.00Tarbox 1.46 0.67 3.20 0.95 0.34Appels 1.43 0.59 3.43 0.79 0.43

1.38 1.06 1.81 2.37 0.020.01 0.1 1 10 100

Figure4.Forestplotandoddsratiosofdyskinesiainhealthyfirstdegreerelativesofpatientswithschizophrenia

andinhealthycontrols


Pooled

38

part II

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40

part II

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43. Marcus J, Hans SL, Lewow E, Wilkinson L, Burack CM. Neurological findings in high-risk children: childhood assessment and 5-year followup. Schizophr Bull 1985;11(1):85-100.

44. Marcus J, Hans SL, Mednick SA, Schulsinger F, Michelsen N. Neurological dysfunctioning in offspring of schizophrenics in Israel and Denmark. A replication analysis. Arch Gen Psychiatry Aug 1985;42(8):753-761.

45. Rieder RO, Nichols PL. Offspring of schizophrenics. III. Hyperactivity and neurological soft signs. Arch Gen Psychiatry Jun 1979;36(6):665-674.

46. Rossi A, De Cataldo S, Di Michele V, Manna V, Ceccoli S, Stratta P, Casacchia M. Neurological soft signs in schizophrenia. Br J Psychiatry Nov 1990;157:735-739.

47. Schiffman J, Walker E, Ekstrom M, Schulsinger F, Sorensen H, Mednick S. Childhood videotaped social and neuromotor precursors of schizophrenia: a prospective investigation. Am J Psychiatry Nov 2004;161(11):2021-2027.

48. Yazici AH, Demir B, Yazici KM, Gogus A. Neurological soft signs in schizophrenic patients and their nonpsychotic siblings. Schizophr Res Dec 1 2002;58(2-3):241-246.


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51. Simpson GM, Angus JW. A rating scale for extrapyramidal side effects. Acta Psychiatr Scand Suppl 1970;212:11-19.


53. Fleiss JL. The statistical basis of meta-analysis. Stat Methods Med Res 1993;2(2):121-145.

54. Lipsey MW, Wilson DB. The way in which intervention studies have “personality” and why it is important to meta-analysis. Eval Health Prof Sep 2001;24(3):236-254.

55. Hasselblad V, Hedges LV. Meta-analysis of screening and diagnostic tests. Psychol Bull Jan 1995;117(1):167-178.

56. Ismail B, Cantor-Graae E, McNeil TF. Neurodevelopmental origins of tardivelike dyskinesia in schizophrenia patients and their siblings. Schizophr Bull 2001;27(4):629-641.

57. Kaufmann D. Clinical Neurology for PSychiatrists. 5th ed. Philidelphia, PA: Saunder Company, WB; 2001.

58. Cohen J. Statistical power analysis for behavioral sciences. NJ: Lawrence Erlbaum Associates; 1988.

59. Whitlock MC. Combining probability from independent tests: the weighted Z-method is superior to Fisher’s approach. J Evol Biol Sep 2005;18(5):1368-1373.

60. Orwin R. A fail-safe N for effect size in meta-analysis. J Educ stat 1983;8:157-159.61. Wolff AL, O’Driscoll GA. Motor deficits and schizophrenia: the evidence from

neuroleptic-naive patients and populations at risk. J Psychiatry Neurosci Sep 1999;24(4):304-314.

62. Fenton WS. Prevalence of spontaneous dyskinesia in schizophrenia. J Clin Psychiatry 2000;61 Suppl 4:10-14.

63. Torrey EF. Studies of individuals with schizophrenia never treated with antipsychotic medications: a review. Schizophr Res Dec 1 2002;58(2-3):101-115.

64. Hietala J, Syvalahti E, Vuorio K, et al. Presynaptic dopamine function in striatum of neuroleptic-naive schizophrenic patients. Lancet Oct 28 1995;346(8983):1130-1131.

65. Laruelle M. Dopamine transmission in the schizophrenic brain. In: Hirsch S, Weinberger D, eds. Schizophrenia. Part Two, Biological Aspects. 1st ed. Oxford: Blackwell Publishing; 2003:365-387.

66. Huttunen J, Heinimaa M, Svirskis T, et al. Striatal dopamine synthesis in first-degree relatives of patients with schizophrenia. Biol Psychiatry Jan 1 2008;63(1):114-117.

67. Mittal VA, Neumann C, Saczawa M, Walker EF. Longitudinal progression of movement abnormalities in relation to psychotic symptoms in adolescents at high risk of schizophrenia. Arch Gen Psychiatry Feb 2008;65(2):165-171.

68. Mittal VA, Walker EF. Movement abnormalities predict conversion to Axis I psychosis among prodromal adolescents. J Abnorm Psychol Nov 2007;116(4):796-803.

69. Walker EF. Developmentally moderated expressions of the neuropathology

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underlying schizophrenia. Schizophr Bull 1994;20(3):453-480.70. Boks MP, Russo S, Knegtering R, van den Bosch RJ. The specificity of neurological

signs in schizophrenia: a review. Schizophr Res Jun 16 2000;43(2-3):109-116.71. Janno S, Holi MM, Tuisku K, Wahlbeck K. Validity of Simpson-Angus Scale (SAS) in

a naturalistic schizophrenia population. BMC Neurol Mar 17 2005;5(1):5.72. Schooler NR, Kane JM. Research diagnoses for tardive dyskinesia. Arch Gen

Psychiatry Apr 1982;39(4):486-487.73. Dean CE, Russell JM, Kuskowski MA, Caligiuri MP, Nugent SM. Clinical rating

scales and instruments: how do they compare in assessing abnormal, involuntary movements? J Clin Psychopharmacol Jun 2004;24(3):298-304.






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Chapter 2.2

Movement disorders are associated with schizotypy in unaffected siblings of patients with non-affective psychosis

Jeroen P Koning, Diederik E Tenback, René S Kahn, Meinte G Vollema, Wiepke Cahn, Peter N van Harten

Published in Psychological Medicine, 2011 March 22:1-8. [Epub ahead of print]

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Background

Movement disorders and schizotypy are both prevalent in unaffected siblings of patients with schizophrenia and both are associated with the risk of developing psychosis or schizophrenia. However, to date there has been no research into the association between these two vulnerability factors in persons with an increased genetic risk profile. We hypothesised that unaffected siblings of patients with non-affective psychosis have both more movement disorders and schizotypy than do healthy controls and that these co-occur.

Methods

In a cross-sectional design we assessed the prevalence and interrelationship of movement disorders and schizotypy in 115 unaffected siblings (mean age 27 years, 44% males) and in 100 healthy controls (mean age 26 years, 51% males). Movement disorders were measured with the Abnormal Involuntary Movement Scale (AIMS), Unified Parkinson Disease Rating Scale (UPDRS), the Barnes Akathisia Rating Scale (BARS), and one separate item for dystonia. Schizotypy was assessed with the Structured Interview for Schizotypy-revised (SIS-R).

Results

There were significant differences in the prevalence of movement disorders in unaffected siblings versus healthy controls (10% versus 1% p<0.01) but not in the prevalence of schizotypy. Unaffected siblings with a movement disorder displayed significantly more positive and total schizotypy (p=0.02 and p=0.03 respectively) than those without. In addition, dyskinesia correlated with positive schizotypy (r=0.51, p=0.02).

Conclusions

The association between movement disorders (dyskinesia in particular) with positive and total schizotypy in unaffected siblings suggests that certain vulnerability factors for psychosis or schizophrenia cluster in a

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subgroup of subjects with an increased genetic risk of developing the disease.

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gsBackground

Schizophrenia is a complex heterogeneous disorder of unknown origin with an array of characteristics including psychotic symptoms 1 and motor abnormalities (such as dyskinesia, parkinsonism, and akathisia) 2-4. Interestingly, both subtle movement disorders and schizotypal traits have been reported in the premorbid period of schizophrenia, during childhood and adolescence, and may thus be related to an increased risk 5-7. Additionally, schizotypal traits and movement disorders are also prevalent in unaffected siblings of patients with schizophrenia 8-11, who have an increased genetic risk of developing the disease 12. However, the co-occurrence between movement disorders and schizotypy in unaffected siblings has never been studied. This association is of theoretical and clinical relevance. Theoretically, because it would stress that (dopamine related) vulnerability factors for psychosis or schizophrenia could cluster in a subgroup of subjects. Clinically, it could be of use in early detection because in contrast to psychotic symptoms, movement disorders can be measured reliably and objectively and with the use of mechanical instruments even in an early stage 13, 14. Furthermore, recent studies including adolescents with schizotypal personality disorders suggest the predictive value of dyskinetic movement disorders for psychotic disorders 6 and the progressive relationship between dyskinetic movement disorders and psychotic symptoms 15. To analyse the interrelationship between movement disorders and schizotypy, we conducted a cross-sectional study and hypothesised (i) that unaffected siblings have both more movement disorders and schizotypy compared to controls, and (ii) that movement disorders and schizotypy co-occur.

Methods

Subjects were recruited from the Genetic Risk and Outcome of Psychosis (GROUP) program at the University Medical Centre Utrecht, the Netherlands. Included were unaffected siblings of patients with a non-affective psychosis and healthy controls without a first or second-degree relative with a non-affective psychosis. Age for both groups was between 16 and 50 years and IQ was greater than 70. To prevent the inclusion of individuals with possible other causes of movement disorders, exclusion

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criteria for both groups were psychiatric diagnosis, neurological disease, life-time drug or alcohol abuse or dependency, and psychotropic medication use. If more than one subject per family was recruited, the sibling who matched the patient in age most closely and then gender was included. All participants signed a written informed consent after the purpose of the study was explained to them.

Clinical assessments

Residents in psychiatry and research assistants evaluated all participants with the Comprehensive Assessment of Symptoms and History (CASH) for clinical history and use of psychotropic medication, and the Composite International Diagnostic Interview (CIDI) for drug abuse. Movement disorders were assessed with the Abnormal Involuntary Movement Scale (AIMS) 16 for clinical dyskinesia, the Unified Parkinson Disease Rating Scale (UPDRS) 17 for clinical parkinsonism, the Barnes Akathisia Rating Scale (BARS) 18 for akathisia, and one separate item for dystonia. Schizotypy was assessed in three dimensions (positive, negative and disorganisation) and a total score was calculated with the use of Structured Interview for Schizotypy-revised (SIS-R) 19.

We defined movement disorders using the following criteria: For dyskinesia or dystonia the criterion was “mild” involvement (a score of 2 or greater) on any of the items of the AIMS 20 or on the separate item for dystonia, or “mild” involvement on the item “global clinical assessment” for akathisia 18. Parkinsonism was defined as “mild” involvement (a score of 2 or greater) on the items of rest tremor or rigidity, or a score of at least “moderate” (a score of 3 or greater) or twice “mild” for the other items such as bradykinesia 21. This more stringent criterion for items concerning bradykinesia and other items of the UPDRS was chosen because these symptoms are less specific for parkinsonism 21. For the credibility of this study it was important that the raters be blind to (or unaware of) our focus on the association between movement disorders and schizotypy during the assessments. It was not possible to prevent the raters from knowing whether a subject was a sibling or a control. However the raters were unaware of the hypothesis of this study. They could not know from the literature about this association, neither were they told by the researchers. However, raters had to indicate if

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gssubjects used psychotropic medication or drugs. Knowing this could induce a bias, as raters do know from the literature that psychotropic medication or drug abuse can cause movement disorders or induce psychotic symptoms. To prevent the possibility of such a bias (and because psychotropic medication or drug abuse can induce movement disorders and /or psychotic symptoms), we excluded from the analysis subjects who used psychotropic medication or had a diagnosis of drug abuse.

Analyses

To evaluate differences between the groups, Student’s t-test, Mann-Whitney, chi-square and Fisher’s exact tests were used, depending on the type and distribution of data. Inter-rater reliability was calculated with the Intraclass Correlation Coefficients (ICC) based on the raters’ scoring of 8 videos with movement disorders and 4 videos with schizotypy. Post-hoc correlation analyses between the mean scores of each movement disorder and schizotypy were carried out to provide additional information about the direction and magnitude of the reported associations. For the correlation analyses, only siblings with at least a minimal sign of a movement disorder were included, as the great majority of the siblings would be healthy and therefore would not display any variation on either movement or schizotypy scale. Data analyses were performed using SPSS 17.

Results

A total of 215 subjects met the inclusion criteria (115 unaffected siblings and 100 healthy controls). We excluded from the initial sample 27 siblings and 8 controls due to a DSM-IV diagnosis of substance abuse and 4 siblings and 1 control due to a diagnosis of alcohol abuse. Both groups were comparable with regard to demographic variables (Table 1). The included siblings and controls did not differ in their pattern of current cannabis use (X2: 3.49, df:3, p=0.32). One sibling had used cocaine the previous week. The ICCs for movement disorders varied between 0.78 - 0.98; it was 0.76 for schizotypy.

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Based on the definition criteria for movement disorders, siblings exhibited significantly more movement disorders than controls, 10% (n=12) versus 1% (n=1) (Fisher’s exact test p<0.01) (Table 2). Two siblings exhibited more than one type of movement disorder [(dyskinesia and akathisia) and (dyskinesia and parkinsonism)]. The overall sibling group (with and without a movement disorder) did not exhibit significantly more schizotypy as compared to controls. Individual mean (SD) scores and Mann-Whitney’s p-values for siblings and controls were respectively, positive schizotypy, 0.23 (0.29) and 0.18 (0.23) (p=0.33); negative schizotypy, 0.18 (0.21) and 0.16 (0.16) (p=0.78); disorganisation schizotypy, 0.02 (0.07) and 0.02 (0.07) (p=0.98); total schizotypy, 0.21 (0.20) and 0.17 (0.16) (p=0.31). Siblings with a movement disorder had significantly higher scores for positive and total schizotypy compared to siblings without a movement disorder (p=0.02 and p=0.03 respectively) (Table 3). This subgroup included more males. There was no difference between siblings with or without a movement disorder in pattern of current cannabis use (X2: 0.52, df:3, p=0.92). One sibling without a movement disorder had used cocaine the previous week.

Post-hoc Spearman correlation analyses There was a significant correlation between dyskinesia and positive schizotypy and a trend for a correlation with total schizotypy (Table 4). Parkinsonism was not associated with any domain of schizotypy. There were too few cases of akathisia (n=4) and no cases of dystonia to perform a correlation coefficient.

Discussion

This is the first study to report a significant association between movement disorders and (positive) schizotypy in unaffected siblings of patients with a non-affective psychosis. Furthermore, we found that movement disorders are more prevalent in unaffected siblings compared to healthy controls. This association between movement disorders and (positive) schizotypy has been found previously in individuals with a high risk for a psychotic disorder, such as adolescents with a schizotypal personality disorder 6, 15. Those studies reported that in adolescents with schizotypal personality disorders, the presence of baseline dyskinetic movement

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gsabnormalities were associated with psychotic symptoms 6, 15 and differentiated high-risk individuals who eventually developed a psychotic disorder 6. Therefore, finding a similar association in symptomatically unaffected subjects with an increased genetic risk such as siblings of patients with a non-affective psychosis bolsters the hypothesis that certain vulnerability factors for schizophrenia could cluster in a subgroup of subjects at risk. Our results are also supported by the findings of neurological soft signs (NSS) in first-degree relatives of patients with schizophrenia 22-25. One element of the NSS in particular, soft motor signs, has been associated with movement disorders in antipsychotic-naïve patients with schizophrenia spectrum disorders. Both “soft” motor signs and “hard” movement disorders may be aspects of a more global motor dysfunction 26, 27. Moreover, soft motor signs have been associated with (positive) schizotypy in unaffected siblings 24. Indeed, there is even further evidence that only the positive dimension of schizotypy is linked to the genetic vulnerability for schizophrenia 8. The mean age of the siblings in this study was 27 years, but it could be hypothesised that mainly siblings who have yet to reach the modal age of onset for psychosis or schizophrenia are at risk (modal age at onset for males is between 18 and 25 years and for females between 25 and the mid-30’s) 28. Interestingly, in this study the siblings with “mild” or “moderate” dyskinesia (n=5) were relatively young with a mean age (SD) of 23 (7) years. Additionally, based on the correlation analysis, only dyskinesia largely and significantly correlated with positive schizotypy (Spearman’s r:0.51, p=0.02). This finding is consistent with previous studies examining dyskinetic movement disorders in association with (positive) schizotypy and with psychosis conversion 6, 15. Of interest, the association between hypokinetic movement disorders (related to a decreased striatal dopamine activity) and schizotypy has never been investigated in high-risk individuals. However, our correlation analysis found no evidence for such a relation (Table 4). In addition, the siblings with “mild” or “moderate” parkinsonism (n=7) were relatively older with a mean age (SD) of 31 (11) years. Finding an association between movement disorders (dyskinetic in particular) and (positive) schizotypy could be clinically important, if it would facilitate the identification of subjects at risk for psychosis, especially as movement disorders can be measured objectively. However, our study design was cross-sectional, and therefore it is not known

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whether these “siblings at risk” will develop psychosis or in absence of other (environmental) risk factors such as cannabis 1 have not developed a psychotic disorder. One may speculate about the underlying pathophysiological mechanism. It could be a shared vulnerable dopamine-mediated dysfunction affecting the dopaminergic pathways in the brain 29, with the nigrostriatal pathway leading to movement disorders 6, 30 and the mesolimbic pathway explaining the presence of positive schizotypal symptoms 30. Indeed, an increased presynaptic dopamine capacity in the striatum, leading to an accumulation of labelled dopamine, has been confirmed in PET imaging in first-degree relatives of patients with schizophrenia 31 and in subjects with schizotypy 32, 33. Additionally, supersensitivity of ascending dopamine pathways, specifically the striatal pathway mediated by the D2 receptor subtype, is considered to cause hyperkinetic movement abnormalities such as dyskinesia 34, 35. Moreover, striatal hyperdopaminergia is not only associated with psychotic symptoms in schizophrenia 36 but also linked to prodromal signs of schizophrenia 37. Although hypothetical, these findings could explain the correlation we found between dyskinetic motor abnormalities and positive schizotypy in a subgroup of unaffected siblings of patients with schizophrenia. In the same vein it has been suggested that in schizophrenia, striatal dopamine dysfunction initially manifests itself in the form of dyskinetic movement disorders and gradually leads to prodromal and eventually to psychotic symptoms as the development of the striatal circuitry becomes further disturbed during late adolescence 15, 38. Our finding that unaffected siblings display more movement disorders compared to controls is in line with our recent meta-analysis on dyskinesia and parkinsonism in antipsychotic-naïve patients and their first-degree relatives 11. It suggests that movement disorders, and by inference abnormalities in the nigrostriatal pathway, are not only associated with schizophrenia itself but may also be related to the (genetic) risk of developing the disease.

In addition, siblings in the present study did have higher scores compared to controls on all but the disorganised aspects of schizotypy, although the results were not significant. This could be due to our more strict inclusion criteria compared to other studies assessing schizotypy in relatives of patients with schizophrenia. Indeed, a study including relatives with more overt psychotic symptoms (such as schizotypal

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gspersonality disorders) did find significantly more schizotypy 39. Moreover, it has been pointed out that relatives respond more defensively as they fear the discovery of schizotypal phenomena 40, 41. Our results on schizotypy are (partially) consistent with previous studies reporting elevated scores in first-degree relatives of positive 8, 10, 42, 43 and negative schizotypal symptoms 9, 10, 39, 43, but not for disorganised traits. Thus finding a significant association between movement disorders and (positive) schizotypy in unaffected siblings despite our strict inclusion criteria suggests a true relationship between movement disorders and (positive) schizotypy in subjects at risk. Some limitations of this study should be taken into consideration.The results are based on a relatively small sample size; however since a clear a priori hypothesis was formulated and because of the inclusion of more obvious movement disorders (item score of at least “mild” (≥2)), the probability of a type I error is small. In addition, it was not possible to prevent raters from knowing if a subject was a sibling or a control. However, we do not think that this influenced the results because, as extensively mentioned in the methods section, raters were unaware of the hypothesis of the study and could not have known it from the previous literature. Moreover, subjects who used psychotropic medication or had a diagnosis of drug abuse were excluded. Also, the sibling group with a movement disorder and increased (positive) schizotypy included more males (n=9) than females (n=3). However, because of the small number of cases, it was not possible to check for gender interactions. Nevertheless, it can be assumed that male gender does not have an effect on the association between movement disorders and schizotypy as in fact females had higher scores for positive and total schizotypy (data not shown). This applied to the overall sibling group (with and without a movement disorder) (n=115) as well as the subgroup of siblings with a movement disorder (n=12). In conclusion, our results indicate that movement disorders (dyskinetic in particular) are associated with (positive) schizotypy in unaffected siblings of patients with a non-affective psychosis. This suggests that both vulnerability indicators share an underlying mechanism, which could be of etiological interest in the quest for the genes or origin of schizophrenia or a psychotic disorder. Further prospective studies are needed to examine whether this subgroup of siblings with both (dyskinetic) movement disorders and (positive) schizotypy are more at

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risk to develop a psychotic disorder than siblings with only one of these vulnerability factors.

AcknowledgementsWe wish to thank all of the participants who took part in this study

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Table 1. Demographic characteristics of unaffected siblings of patients with a non-affective psychosis and healthy controls

Siblings

(N=115)

Controls

(N=100)

Siblings versus

Controls

Mean (SD)

Mean (SD)

p-valuea

Age, Years

26.6 (7.0)

26.4 (8.1)

0.79

Education, Years

13.7 (2.4)

13.9 (2.3)

0.45

% (N)

% (N)

p-valueb

Gender, Male

44 (51)

51 (51)

0.33

Handedness, Right

87 (100)

86 (86)

0.84

Ethnicity, Caucasian

90 (103)

88 (88)

0.83

a: Independent Student’s T-test, b: Chi-square test

Table 2. Distribution of movement disorders in unaffected siblings of patients with a non-affective psychosis and healthy controls

Siblings

(N=115)

Controls

(N=100)

Siblings versus

Controls

% (N)

% (N)

p-valuea

Dyskinesia

Parkinsonism

Akathisia

Dystonia

Any movement disorder

4 (5)

6 (7)

2 (2)

0 (0)

10 (12)

1 (1)

0 (0)

0 (0)

0 (0)

1 (1)

<0.01

Case definitions movement disorders: see Methods section - Clinical assessments.

Two siblings exhibited more than one type of movement disorder [(dyskinesia and akathisia) and (dyskinesia and

parkinsonism)].

a Fisher’s exact test.



49


Siblings

(N=115)

Controls

(N=100)

Siblings versus

Controls

Mean (SD)

Mean (SD)

p-valuea

Age, Years

26.6 (7.0)

26.4 (8.1)

0.79

Education, Years

13.7 (2.4)

13.9 (2.3)

0.45

% (N)

% (N)

p-valueb

Gender, Male

44 (51)

51 (51)

0.33

Handedness, Right

87 (100)

86 (86)

0.84

Ethnicity, Caucasian

90 (103)

88 (88)

0.83

a: Independent Student’s T-test, b: Chi-square test


Siblings

(N=115)

Controls

(N=100)

Siblings versus

Controls

% (N)

% (N)

p-valuea

Dyskinesia

Parkinsonism

Akathisia

Dystonia

Any movement disorder

4 (5)

6 (7)

2 (2)

0 (0)

10 (12)

1 (1)

0 (0)

0 (0)

0 (0)

1 (1)

<0.01

Case definitions movement disorders: see Methods section - Clinical assessments.

Two siblings exhibited more than one type of movement disorder [(dyskinesia and akathisia) and (dyskinesia and

parkinsonism)].

a Fisher’s exact test.

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Table 3. Demographic and clinical data of unaffected siblings of patients with a non-affective psychosis with and without a movement disorder

Table 4: Correlation coefficients between individual movement disorders and domains of schizotypy in unaffected siblings of patients with a non-affective psychosis

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Siblings with a

movement disorder

(n=12)

Siblings without a

movement disorder

(N=103)

Comparison of

siblings with and without a

movement disorder

Mean (SD)

Mean (SD)

p-valuea

Age, Years

28.4 (9.4)

26.4 (6.6)

0.35

Education, Years

13.7 (2.3)

13.7 (2.4)

0.98

Schizotypy (SIS-R scores)

Positive

Negative

Disorganisation

Total

0.35 (0.22)

0.21 (0.19)

0.03 (0.10)

0.27 (0.14)

0.22 (0.30)

0.18 (0.21)

0.02 (0.07)

0.20 (0.21)

0.02b

0.48b

0.61b

0.03b

% (N)

% (N)

p-valuec

Gender, Male

75 (9)

41 (42)

0.05

a: Independent Student’s T-test, b: Mann-Whitney test, c: Chi-square test with continuity correction. SIS-R: Structured Interview for Schizotypy-Revised.


AIMS

(N=22)

UPDRS

(N=31)

R

P-value

R

P-value

Schizotypy (SIS-R)

Positive

Negative

Disorganisation

Total

0.51

-0.06

-0.13

0.37

0.02

0.80

0.56

0.09

0.01

-0.09

0.22

-0.06

0.95

0.54

0.24

0.73

N: number of siblings with at least a minimal movement disorder (item score ≥1) R: Spearman’s correlation coefficient. AIMS: Abnormal Involuntary Movement Scale

UPDRS: Unified Parkinson Disease Rating Scale Correlations for the BARS (Barnes Akathisia Rating Scale) could not be calculated, because of the limited number of siblings with akathisia (n=4). No sibling displayed any sign of dystonia.

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Siblings with a

movement disorder

(n=12)

Siblings without a

movement disorder

(N=103)

Comparison of

siblings with and without a

movement disorder

Mean (SD)

Mean (SD)

p-valuea

Age, Years

28.4 (9.4)

26.4 (6.6)

0.35

Education, Years

13.7 (2.3)

13.7 (2.4)

0.98

Schizotypy (SIS-R scores)

Positive

Negative

Disorganisation

Total

0.35 (0.22)

0.21 (0.19)

0.03 (0.10)

0.27 (0.14)

0.22 (0.30)

0.18 (0.21)

0.02 (0.07)

0.20 (0.21)

0.02b

0.48b

0.61b

0.03b

% (N)

% (N)

p-valuec

Gender, Male

75 (9)

41 (42)

0.05

a: Independent Student’s T-test, b: Mann-Whitney test, c: Chi-square test with continuity correction. SIS-R: Structured Interview for Schizotypy-Revised.


AIMS

(N=22)

UPDRS

(N=31)

R

P-value

R

P-value

Schizotypy (SIS-R)

Positive

Negative

Disorganisation

Total

0.51

-0.06

-0.13

0.37

0.02

0.80

0.56

0.09

0.01

-0.09

0.22

-0.06

0.95

0.54

0.24

0.73

N: number of siblings with at least a minimal movement disorder (item score ≥1) R: Spearman’s correlation coefficient. AIMS: Abnormal Involuntary Movement Scale

UPDRS: Unified Parkinson Disease Rating Scale Correlations for the BARS (Barnes Akathisia Rating Scale) could not be calculated, because of the limited number of siblings with akathisia (n=4). No sibling displayed any sign of dystonia.

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1. van Os J, Kapur S. Schizophrenia. Lancet Aug 22 2009;374(9690):635-645.2. Wolff AL, O’Driscoll GA. Motor deficits and schizophrenia: the evidence from

neuroleptic-naive patients and populations at risk. J Psychiatry Neurosci Sep 1999;24(4):304-314.

3. Pappa S, Dazzan P. Spontaneous movement disorders in antipsychotic-naive patients with first-episode psychoses: a systematic review. Psychol Med Jul 2009;39(7):1065-1076.

4. van Harten PN, Tenback DE. Letter to the Editor: Movement disorders should be a criterion for schizophrenia in DSM-V. Psychol Med Jul 17 2009:1-3.




8. Vollema MG, Sitskoorn MM, Appels MC, Kahn RS. Does the Schizotypal Personality Questionnaire reflect the biological-genetic vulnerability to schizophrenia? Schizophr Res Mar 1 2002;54(1-2):39-45.

9. Calkins ME, Curtis CE, Grove WM, Iacono WG. Multiple dimensions of schizotypy in first degree biological relatives of schizophrenia patients. Schizophr Bull 2004;30(2):317-325.

10. Delawalla Z, Barch DM, Fisher Eastep JL, Thomason ES, Hanewinkel MJ, Thompson PA, Csernansky JG. Factors mediating cognitive deficits and psychopathology among siblings of individuals with schizophrenia. Schizophr Bull Jul 2006;32(3):525-537.

11. Koning JP, Tenback DE, van Os J, Aleman A, Kahn RS, van Harten PN. Dyskinesia and parkinsonism in antipsychotic-naive patients with schizophrenia, first-degree relatives and healthy controls: a meta-analysis. Schizophr Bull Jul 2010;36(4):723-731.

12. Cardno AG, Marshall EJ, Coid B, et al. Heritability estimates for psychotic disorders: the Maudsley twin psychosis series. Arch Gen Psychiatry Feb 1999;56(2):162-168.


14. Koning JP, Kahn RS, Tenback DE, van Schelven LJ, van Harten PN. Movement disorders in nonpsychotic siblings of patients with nonaffective psychosis. Psychiatry Res Jan 28 2011.


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19. Vollema MG, Ormel J. The reliability of the structured interview for schizotypy-revised. Schizophr Bull 2000;26(3):619-629.


21. van Harten PN, Matroos GE, Hoek HW, Kahn RS. The prevalence of tardive dystonia, tardive dyskinesia, parkinsonism and akathisia The Curacao Extrapyramidal Syndromes Study: I. Schizophr Res May 1996;19(2-3):195-203.


23. Ismail B, Cantor-Graae E, McNeil TF. Neurological abnormalities in schizophrenic patients and their siblings. Am J Psychiatry Jan 1998;155(1):84-89.

24. Mechri A, Gassab L, Slama H, Gaha L, Saoud M, Krebs MO. Neurological soft signs and schizotypal dimensions in unaffected siblings of patients with schizophrenia. Psychiatry Res Jan 30 2010;175(1-2):22-26.

25. Yazici AH, Demir B, Yazici KM, Gogus A. Neurological soft signs in schizophrenic patients and their nonpsychotic siblings. Schizophr Res Dec 1 2002;58(2-3):241-246.

26. Peralta V, de Jalon EG, Campos MS, Basterra V, Sanchez-Torres A, Cuesta MJ. Risk factors, pre-morbid functioning and episode correlates of neurological soft signs in drug-naive patients with schizophrenia-spectrum disorders. Psychol Med Sep 22 2010:1-11.

27. Whitty PF, Owoeye O, Waddington JL. Neurological signs and involuntary movements in schizophrenia: intrinsic to and informative on systems pathobiology. Schizophr Bull Mar 2009;35(2):415-424.

28. APA. Diagnostic and Statistical Manual of Mental Disorders. 4th ed, text revision. Washington, DC:: American Psychiatric Association; 2000.

29. Tenback DE, van Harten PN, Slooff CJ, van Os J. Incidence and persistence of tardive dyskinesia and extrapyramidal symptoms in schizophrenia. J Psychopharmacol Jul 2010;24(7):1031-1035.

30. Carlsson A. The current status of the dopamine hypothesis of schizophrenia. Neuropsychopharmacology Sep 1988;1(3):179-186.


32. Abi-Dargham A, Kegeles LS, Zea-Ponce Y, et al. Striatal amphetamine-induced dopamine release in patients with schizotypal personality disorder studied with single photon emission computed tomography and [123I]iodobenzamide. Biol Psychiatry May 15 2004;55(10):1001-1006.

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gs33. Soliman A, O’Driscoll GA, Pruessner J, Holahan AL, Boileau I, Gagnon D, Dagher A. Stress-induced dopamine release in humans at risk of psychosis: a [11C]raclopride PET study. Neuropsychopharmacology Jul 2008;33(8):2033-2041.


35. Casey DE. Pathophysiology of antipsychotic drug-induced movement disorders. J Clin Psychiatry 2004;65 Suppl 9:25-28.

36. Howes OD, Kapur S. The dopamine hypothesis of schizophrenia: version III--the final common pathway. Schizophr Bull May 2009;35(3):549-562.

37. Howes OD, Montgomery AJ, Asselin MC, et al. Elevated striatal dopamine function linked to prodromal signs of schizophrenia. Arch Gen Psychiatry Jan 2009;66(1):13-20.


39. Kendler KS, Thacker L, Walsh D. Self-report measures of schizotypy as indices of familial vulnerability to schizophrenia. Schizophr Bull 1996;22(3):511-520.

40. Grove WM, Lebow BS, Clementz BA, Cerri A, Medus C, Iacono WG. Familial prevalence and coaggregation of schizotypy indicators: a multitrait family study. J Abnorm Psychol May 1991;100(2):115-121.

41. Lenzenweger MF. Explorations in schizotypy and the psychometric high-risk paradigm. In: Chapman LJ, Chapman JP, Fowles D, eds. Progress in Experimental Personality and Psychopathology Research. New York: Springer; 1993:66-116.

42. Appels MC, Sitskoorn MM, Vollema MG, Kahn RS. Elevated levels of schizotypal features in parents of patients with a family history of schizophrenia spectrum disorders. Schizophr Bull 2004;30(4):781-790.

43. Laurent A, Biloa-Tang M, Bougerol T, et al. Executive/attentional performance and measures of schizotypy in patients with schizophrenia and in their nonpsychotic first-degree relatives. Schizophr Res Dec 15 2000;46(2-3):269-283.

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Chapter 2.3

Associations of two DRD2 gene polymorphisms with acute and tardive antipsychotic-induced movement disorders in young Caucasian patients

Jeroen P Koning*, Jelle Vehof *, Huibert Burger, Bob Wilffert, Asmar Al Hadithy, Behrooz Alizadeh, Peter N van Harten**, Harold Snieder**, GROUP Investigators

Published in Psychopharmacology (Berl), 2011 July 13. [Epub ahead of print]

* Both authors contributed equally ** Both authors contributed equally

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Rationale

Pharmacogenetic studies on antipsychotic-induced movement disorders (MD) in schizophrenia so far have focused mainly on tardive dyskinesia. Only a few examined the more acute antipsychotic induced MD, such as parkinsonism and akathisia. Notably, all MD relate to deregulation of the dopamine system.

Objective

This study aimed to replicate previously reported associations in candidate genes for acute and tardive antipsychotic-induced MD in a young Caucasian sample.

Methods

In 402 patients (median age 26 years) a total of 13 polymorphisms were genotyped in 8 dopamine related candidate genes selected a priori from the literature (regarding dopamine and serotonin receptors, dopamine degradation, and free radicals scavenging enzymes pathways).

Results

Patients with MD used on average a higher haloperidol dose equivalent, when compared to those without MD. Prevalence of MD was high and did not differ between first generation antipsychotics and second generation antipsychotics. Significant associations were found between (i) the TaqI_D polymorphism and akathisia (OR=2.3, p=0.001 for each extra C- allele) and (ii) the -141C polymorphism and tardive dyskinesia (OR=0.20, p=0.001 for each extra Del allele). The other polymorphisms were not significantly associated with an MD.

Conclusion

Two associations were found between genetic variation TaqI_D and the -141C polymorphisms in the DRD2 gene and antipsychotic-induced MD: one with acute akathisia and one with tardive dyskinesia. These were

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previously reported to be associated with tardive dyskinesia and acute parkinsonism, respectively. These results suggest that the contribution of these DRD2 gene variants in the vulnerability of antipsychotic-induced MD takes place in a more general or pleiotropic way.

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gsIntroduction

Antipsychotic induced movement disorders (MD), i.e. tardive dyskinesia, parkinsonism, akathisia and dystonia, remain a major concern in the treatment of schizophrenia. They are associated with social stigmatization, physical disabilities, and poorer quality of life and may intervene with treatment adherence 1, 2. Lack of compliance is particularly of interest in relatively young patients diagnosed with schizophrenia as it may lead to more relapses, higher admission rate and poorer prognosis 3, 4.

Despite the introduction of the second generation antipsychotics with generally a lower propensity for motor side effects, the prevalence of antipsychotic-induced MD in patients with first episode schizophrenia, is still substantial with a frequency up to 19% 5.

It is therefore of clinical importance to detect patients who are prone to antipsychotic-induced MD. Well known risk factors include the use of first generation antipsychotics, higher dosages and duration of antipsychotic use, drug abuse, male gender in first episode schizophrenia, older age and ethnicity 6-17. The presence of early antipsychotic-induced MD is also a risk factor for development of later tardive dyskinesia 18, 19. In addition, genetic variations may in part explain the large inter-individual differences in the development of antipsychotic induced MD among patients with schizophrenia using similar antipsychotics 20.

We hypothesize that genes related to the dopamine system are candidate genes for antipsychotic induced MD in schizophrenia 21. Dopamine 2 and 3 receptors (DRD2 and DRD3) are relevant being the primary targets for antipsychotic drugs 22, 23. In addition, the DRD2 is densely expressed in the striatum 20, 24, 25 and even more so in schizophrenia 26. The DRD3 is also selectively expressed in brain regions associated with schizophrenia including the striatum and pallidum, each implicated in motor function 27,

28. Several associations with mainly tardive dyskinesia have been reported for genetic DRD2 and DRD3 variants 29-33.

In addition, serotonin receptors 2a and 2c (5HTR2A and 5HTR2C, respectively) are involved because many antipsychotics, in particularly second generation antipsychotics, have a high affinity to these receptors. They are strongly expressed in the striatum 34, 35. Moreover, the

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serotonergic system interacts with the dopaminergic system and may be responsible for some of the dyskinetic effects of antipsychotics 36, 37. Several candidate studies reported significant associations for 5HTR2A and 5HTR2C 29, 38-42.

Furthermore, the Catechol-O-methyltransferase (COMT) gene is of interest as it encodes the central dopamine catabolic enzyme (COMT) that degrades dopamine and noradrenaline. As COMT is mainly located in the frontal cortex, the relation with MD most likely results from secondary changes or upregulation in the frontal-striatal circuit 29. One significant association study with tardive dyskinesia has been published 43.

Additionally, oxidative stress may also contribute to the development of antipsychotic-induced MD and schizophrenia as free radicals may damage the dopamine receptor 44, 45. Indeed, several genetic variants in free radial scavenging enzymes have reported to be associated with tardive dyskinesia; NADPH Quinone Oxidoreductase 1 (NQO1), Glutathione S-transferases (GSTP1), Regulator of G protein signaling 2 (RGS2) and Mangase superoxide dismutase (MnSOD).46, 47,48, 49,29, 50.

In the present study we aim to replicate reported associations in candidate genes for acute and tardive antipsychotic-induced MD in a young Caucasian sample with psychotic disorders.

Methods

Study populationA sample of 402 in- and outpatients using antipsychotic medication was collected from the ongoing longitudinal Genetic Risk and Outcome of Psychosis study (GROUP)51. In GROUP, patients were identified in selected representative geographical areas in the Netherlands and Belgium. Inclusion criteria for GROUP were: (i) age range 16 to 50 years, (ii) diagnosis of non-affective psychotic disorder and (iii) good command of Dutch language. For the present analysis the following extra inclusion criteria were applied: (iv) use of antipsychotic medication at the time of assessment for at least one month and (v) Caucasian ethnicity of Northern European ancestry. The study was approved by the Ethics Committee of the University Medical Center Utrecht and by the institutional review boards of all other participating hospitals. All subjects gave written

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gsinformed consent in accordance with the committee’s guidelines. Clinical variables included DSM-IV diagnosis, duration of illness, antipsychotic medication and dose. PhenotypingTrained raters evaluated all participants once for MD using standardized clinical instruments. As part of the GROUP study protocol, yearly training sessions were held to maintain reliability on the assessment of movement disorders. Acute antipsychotic induced MD were measured by the Unified Parkinson Disease Rating Scale (UPDRS)52, the Barnes Akathisia Rating Scale (BARS)53, and one extra item for dystonia. Parkinsonism was considered present when there was ‘mild’ (≥ 2) involvement on one of the items tremor or rigidity, or at least one ‘moderate’ (≥ 3) or two ‘mild’ scores on any of the other items of the UPDRS52. Akathisia was considered present when there was a ‘mild’ (≥ 2) involvement on the global item of the BARS 53 and dystonia was considered present when there was a ‘mild’ (≥ 2) involvement. Tardive dyskinesia (TD) was evaluated with the Abnormal Involuntary Movement Scale (AIMS)54. The aim of this study was to identify early genetic markers of vulnerability to all antipsychotic induced MD, including tardive dyskinesia. However, the included patients of the GROUP population had a relatively short duration of illness (median of 3.1 years). Therefore TD was considered present when any of the AIMS items scored at least ‘minimal’ (≥ 1) following the research criteria for TD of the GWAS in the CATIE-trial 55.

GenotypingOn the basis of significantly associated single nucleotide polymorphisms (SNPs) reported in the literature we genotyped 14 SNPs in the following 9 candidate genes. For DRD2: (i) rs1800497 (TaqI_A), (ii) rs6277 (C957T), (iii) rs1799732 (-141CIns/Del) and (iv) rs1800498 (TaqI_D). For DRD3: (i) rs6280 (Ser9Gly). For 5HTR2A: (i) rs6313 (T102C>T), (ii) rs6314 (His452Tyr). For 5HTR2C: (i) rs6318 (Cys23Ser), (ii) rs3813929 (-759C_T). For COMT: (i) rs4680 (Val158Met), For oxidative stress enzymes: NQO1 (i) rs1800566 (C609T), GSTP1 (ii) rs1695 (Ile105Va), RGS2 gene (iii) rs4606, MnSOD (iv) rs4880 (Ala-9Val). These a priori selected polymorphisms were genotyped by Sequenom (Hamburg, Germany) using the Sequenom MassARRAY iPLEX platform at the facilities of the manufacturer. Quality check for genotyping was performed in the total GROUP study, which encompassed exclusion of polymorphisms based on departure from

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Hardy-Weinberg equilibrium in a sample of 398 unaffected controls without a psychotic disorder.

Statistical analysisDifferences in prevalence of MD between users of fist generation antipsychotics and second generation antipsychotics and between men and women were evaluated and tested for statistical significance using Fisher’s exact tests. Study inter-rater agreements of ratings were calculated with the multi-rater kappas 56, 57 using 8 videotaped examinations of movement disorders. Kappa is a summary measure, ranging between -1 and +1, of the level of agreement beyond chance. According to Landis and Koch58, kappa values below 0.40 should be considered poor, between 0.41 to 0.60 should be considered moderate, 0.61 to 0.80 should be considered substantial, and above 0.81 should be considered almost perfect. Haloperidol dose equivalents were subsequently calculated using power formulas 59. Differences in age, duration of illness and haloperidol dose equivalents between patients with and without a MD were evaluated and tested for statistical significance using a Mann-Whitney test. Logistic regression was used to test the association between genotyped polymorphisms and parkinsonism, akathisia, and tardive dyskinesia. Acute dystonia was not tested separately, because of its low prevalence. Two polymorphisms positioned on the X-chromosome were tested separately by gender, and in a dominant model for the total sample. Covariables corrected for in our regression model were age and gender.

Pairwise linkage disequilibrium (LD) between polymorphisms was calculated by D’ and r2. The haplotype trend regression (HTR) approach, as outlined by Zaykin et al.60 was used to test the associations of statistically inferred haplotypes with extrapyramidal side-effects. The HTR tests for the contribution of individual haplotypes taking into account the uncertainty of haplotype estimation by PHASE 2.0 software 61, 62. The most frequent haplotype was used as the reference haplotype with which effects of the other haplotypes were contrasted. This was performed for the genes DRD2, 5HTR2A, and 5HTR2C, where multiple polymorphisms were genotyped. Similarly, correction for age and gender was performed in these regression analyses.

All statistical analyses, other than those involving haplotype estimation, were performed using (SPSS 16.0 for Windows). Since polymorphisms

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gsand MD variables are both partly correlated and the choice of the polymorphisms was based on earlier positive association studies, application of Bonferroni’s procedure for correcting alpha for multiple testing was considered too conservative. In adjusting the significance level to account for multiple testing we follow the recommendations of Van den Oord and Sullivan 63, 64. The adjustment depends on p0, the number of markers for which there is no true effect (i.e. the null hypothesis is not true), which is generally unknown in candidate gene studies. For a range of plausible p0 values for candidate gene studies, a significance level of P=0.01 will, on average, control the false discovery rate at 0.10. Lower false discovery rates generally resulted in sharp increase in sample size, i.e., loss of power. Thus, the significant level of this study was pragmatically set at 0.01, two-sided.

Results

Descriptive statistics of our study sample are presented in Table 1, shown stratified by patients with and without a MD present. The interrater agreement for MD using multi-rater kappas varied between 0.56 and 0.98. The prevalence of an MD was 46.8% (n=188). The most frequent MD was parkinsonism (n=122, 30.3%), followed by tardive dyskinesia (n=88, 21.9%), akathisia (n=37, 9.2%), and dystonia (n=7, 1.7%). Patients with an MD used on average a significantly higher haloperidol dose equivalents (Mann Whitney P value 0.009) than patients without an MD. Age and duration of illness were higher in patients with an MD but were not significantly associated (Mann Whitney P value 0.06 and 0.44, respectively). Prevalence of an MD did not significantly differ between users of first generation and second generation antipsychotics or between men and women (Fisher’s exact test P value 0.28 and 0.09, respectively).

Genotyping failed for the rs4880 polymorphism in the MnSOD gene, yielding the remaining set of 13 SNPs in 8 genes. All other polymorphisms were validated and had a missing genotype rate below 10% in our sample. No polymorphism deviated from Hardy-Weinberg equilibrium (data not shown). The allele and genotype frequencies are shown in Tables 2. LD patterns of the DRD2 gene can be seen in Table 3. D’ and r2 between the two SNPs in HTR2A were 0.28 and 0.01, respectively, and in HTR2C 1.00 and 0.04, respectively.

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In Table 4 the results of the genetic association tests of all MD (except dystonia) are depicted, corrected for age and gender. The TaqI_D polymorphism in the DRD2 gene was significantly associated with akathisia (p=0.001). For each extra C-allele a 2.3 (95% CI 1.43-3.82) times higher risk of having akathisia was found. Also, -141C of the DRD2 gene was significantly associated with TD (P= 0.001). Each extra Del allele decreased the risk of having TD by 0.20 (95% CI 0.08-0.50). None of the other polymorphisms showed a significant association with any of the MD. Haplotype analysis on genes DRD2, 5HTR2A, and 5HTR2C did not lead to significant results with any of the MD (data not shown).

Discussion This study aimed to replicate previously reported associations in candidate genes for acute and tardive antipsychotic-induced MD in a young Caucasian sample. Of the previously reported polymorphisms two showed significant associations with MD: the DRD2 gene polymorphisms TaqI_D and -141C were associated to akathisia and tardive dyskinesia, respectively. The MD-prevalence per se did relate to the dosage of the prescribed antipsychotics as expressed in haloperidol equivalents, but not to the type of antipsychotics or to the duration of illness. The reported association between functional DRD2 promoter allele -141 C Del and tardive dyskinesia was not found previously 32, 65-67 but an association was found between this promoter allele and antipsychotic induced parkinsonism 33. This may be of clinical interest as antipsychotic induced parkinsonism has been shown to be a risk factor for the development of tardive dyskinesia 9, 18, 19. It could be argued that the blockade of the postsynaptic DRD2 receptors by antipsychotics induces hypersensitivity of the DRD2 receptor, leading to tardive dyskinesia over time, as has been demonstrated in rodent models 68-70. The -141CIns/Del polymorphism -although debated by some 71, 72- has been suggested to be functional 73 or in linkage disequilibrium with another functional polymorphism 74. Thus, involvement of this DRD2-allele in antipsychotic induced MD is in line with findings in healthy volunteers, where striatal receptor density is related to this DRD2 promoter allele (-141C Del) 75.

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gsThis study also reports an association between TaqI_D and akathisia. This intronic SNP has previously only been investigated for tardive dyskinesia 32, 67, 76 and was significantly associated in a two marker haplotype with C939T 32. Although the pathophysiology of akathisia is still largely unknown, there is clinical evidence that medication interfering with the dopamine system and leading to a low dopaminergic tone is associated with the insistent feeling of restlessness and the urge to move 77, 78.

Taken together our results suggest a more pleiotropic effect, where involvement of genetic variants in the DRD2 gene may lead to multiple phenotypic traits of antipsychotic-induced MD, which are pathophysiologically related to each other, albeit with differential clinical expression. This expression is directed additionally by contextual genetic and environmental factors such as population characteristics (i.e. age, ethnicity, duration and type of AP use)

The present study did not replicate other previously reported significant associations with either tardive or acute antipsychotic induced MD. Non-replication is a common problem in pharmacogenetic research 79. The majority of the previous candidate gene studies focuses on chronic MD (tardive dyskinesia) and older patients, many of them using first generation antipsychotics. Here in contrast to most previous studies, the patients are relatively young and the majority of them use second generation antipsychotics. Shorter duration of illness and use of second generation antipsychotics are both associated with lower prevalence and less severity of tardive dyskinesia 8. Five studies so far have reported associations with acute antipsychotic-induced MD, without specifying the MD under study 39-41, 48, 49. To our knowledge, only one candidate study has reported significant results with akathisia specifically 80 and only one with parkinsonism 33 both in an older sample with a mean age of 40 and 49 years, respectively. The affinities for multiple receptors of second generation antipsychotics, other than the prevailing affinity for the DRD2 receptor of the first generation antipsychotics, may be responsible for the differing pharmacogenetic associations found in our group of patients. To explore heterogeneity of different side effect profiles, we repeated our analyses in two subgroups of patients, using the most frequently prescribed antipsychotics, risperidone (22%) and olanzapine (26%). This did not change the results. Finally, it is well established that susceptibility and risk factors differ among ethnic groups 16, 17. We studied Caucasian

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patients only, whereas the -141 C Del association with antipsychotic induced parkinsonism was reported in African Caribbean patients 33. The pharmacogenetic differences observed in our study may therefore reflect differential vulnerability for the observed MD in this specific population.

Of note, the prevalence of an MD in this study did not significantly differ between users of first and second generation antipsychotics, despite that second generation antipsychotics are associated with lower risk for MD as compared to first generation antipsychotics 8. However, the finding that patients with an MD used on average a significant higher haloperidol dose equivalent is in line with the clinical notion that the emergence of antipsychotic-induced MD relates first of all to the degree of dopamine blockade. This may pertain even more for the current population, being young and having a relatively short treatment history.

There are some caveats when interpreting these data. For reasons described in the methods section the significance level of this study was pragmatically set at 0.01, two-sided. Even though unlikely with p-values of 0.001, which would even survive the more conservative Bonferroni correction, we cannot entirely exclude the possibility that our two significant findings still represent false positive associations and therefore caution is required in interpreting the results. The design of this study was cross-sectional. Therefore definite conclusions about the predictive value of the reported associations cannot be made yet. Nonetheless, a reverse association from MD to polymorphism can be excluded. More importantly, the similar prevalence of MD for all prescribed antipsychotics may be the result of confounding by indication. Information on type and dose of antipsychotic medication was additionally provided by the treating physician but may nevertheless be insufficient, as non-compliance is prevalent among patients with schizophrenia 81. Non-compliance is not accounted for by most candidate studies 82. Future pharmacogenetic studies could increase their reliability by including blood levels of antipsychotic medication. For diagnosing TD we have chosen a more liberal case definition of at least a ‘minimal’ (≥ 1) score on at least one item of the AIMS 55 instead of the stricter Schooler and Kane criteria of a ‘mild’ (≥ 2) score on at least two items or at least a ‘moderate’ (≥ 3) score on at least one item 83. Therefore the risk of false positive, TD case definitions could be increased. However, as mentioned earlier we included a relatively young population in which the phenotype

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gswas probably not yet fully expressed. In addition, there is evidence that initially subtle dyskinesia is progressive and will eventually fulfill the stricter case definitions for TD 84. Of interest, the reported significant association between dyskinesia and the -141C/Del polymorphism was also found by ordinal regression analysis (four ordinal groups of patients, ranked on mean AIMS scores, beta: -1.47, p=0.001), supporting the validity of the finding. Finally, training and ascertaining of interrater-relaibility is uncommon in pharmacogenetic studies. Here the raters were trained yearly in the recognition of movement disorders and the degree of agreement varied from moderate (kappa: 0.56) to good (kappa: 0.98). Nonetheless, a certain degree of misclassification of MD cannot be ruled out.

The present study has several strengths. We focussed on previously reported significant associations in candidate genes, taking into account both acute and tardive MD. Our sample is relatively large, consisting of a homogeneous group of Caucasian patients, all diagnosed with a non-affective psychosis. The young age of the included population makes it unlikely that primarily neurological co-morbidity is interfering with the results.

During our candidate study and the preparation of this article, several genome-side association studies (GWAS) have been performed to identify susceptibility genes for antipsychotic induced movement disorders 55, 85-

87. Those results suggest that genes associated with the gamma amino butyric acid receptor-signaling pathway 87, the GLI2 gene 86, and an intergenetic polymorphism marker rs7669317 55 may also be involved in tardive dyskinesia in patients using antipsychotics. The ZNF202 gene and the intergenetic marker rs17022444 were identified as potentially relevant for parkinsonism 55. It would be of interest to attempt to replicate these non-hypothesis driven associations in follow up studies as well.

In conclusion, this study did not replicate previously reported polymorphisms. However, we found two novel SNPs associations in the DRD2 gene. The TaqI_D variant was associated with acute akathisia and the -141C variant with tardive dyskinesia. These polymorphisms were previously reported in tardive dyskinesia and acute parkinsonism, respectively. These results suggest involvement of genetic variants in the DRD2 gene for susceptibility of MD in a more general or pleiotropic

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way. Findings of associated polymorphisms in patients with a relatively short duration of illness are clinically relevant as they could further help to identify early markers of vulnerability for MD. Follow-up studies in similar samples with young patients and atypical antipsychotics are warranted to support our findings.

AcknowledgementsWe are grateful for the generosity of time and effort by the patients and their families, healthy subjects, and all researchers who make this GROUP project possible

Group investigators are: René S. Kahn, MD, PhD, Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands; Don H. Linszen, MD, PhD, Department of Psychiatry, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands; Jim van Os, MD, PhD, South Limburg Mental Health Research and Teaching Network, EURON, Maastricht University Medical Centre, Maastricht, the Netherlands, and King’s College London, King’s Health Partners, Department of Psychosis Studies, Institute of Psychiatry, London, England; Durk Wiersma, PhD, Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands; Richard Bruggeman, MD, PhD, Department of Psychiatry, University Medical Center Groningen, University of Groningen; Wiepke Cahn, MD, PhD, Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht; Lieuwe de Haan, MD, PhD, Department of Psychiatry, Academic Medical Centre, University of Amsterdam; Lydia Krabbendam, PhD, South Limburg Mental Health Research and Teaching Network, EURON, Maastricht University Medical Centre; and Inez Myin-Germeys, PhD, South Limburg Mental Health Research and Teaching Network, EURON, Maastricht University Medical Centre.

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gsTable 1: Descriptive statistics of 402 Caucasian patients using antipsychotics, stratified by presence of a movement disorder (MD).

MD present (n=188)

No MD present (n=214)

Age (years), median (range) 28 (16-47) 26 (16-48)

Gender (male) 153 (81%) 159 (74%)

Duration of illness (years), median (range) 3.9 (0.1-21.7) 3.2 (0.1-20.6)

Diagnosis Schizophrenia Schizo-affective disorder Schizophreniphorm disorder Delusional disorder Psychotic disorders NOS Other

137 (73%)26 (14%)2 (1%)3 (2%)

19 (10%)1 (1%)

140 (65%)29 (14%)8 (4%)7 (3%)

23 (11%)7 (3%)

Antipsychotic use First generation antipsychotics (FGA) Second generation antipsychotics (SGA) FGA and SGA Missing

14 (7%)144 (77%)10 (5%)20 (11%)

23 (11%)159 (74%)

5 (2%)27 (13%)

Current Haloperidol equivalents (mg), median (range) 6.7 (0.7-21.0) 4.7 (0.6-20.4)

76

part II

66

Ta

ble

2:

Fre

qu

en

cie

s o

f a

llele

s a

nd

ge

no

typ

es o

f p

oly

mo

rph

ism

s in

do

pa

min

e r

ela

ted

ca

nd

ida

te g

en

es

in 4

02

Ca

uca

sia

n p

atie

nts

with

sch

izo

ph

ren

ia.

Ge

ne

rs-i

d

Ch

rom

oso

me

po

sitio

n

V

ari

an

t

Alle

les

*

M

AF

Ge

no

typ

es 1

1

1

2

2

2

DR

D2

rs

18

00

49

7

Ch

r11

:11

32

70

82

8

Ta

qI_

A

C/T

0

.19

2

73

1

09

2

0

rs

62

77

C

hr1

1:1

13

28

34

59

C

95

7T

T

/C

0.4

7

11

5

18

9

95

rs

18

00

49

8

Ch

r11

:11

32

91

58

8

Ta

qI_

D

T/C

0

.39

1

51

1

85

6

3

rs

17

99

73

2

Ch

r11

:11

33

46

25

2

-14

1C

C

/De

l 0

.11

3

21

7

3

6

DR

D3

rs

62

80

C

hr3

:11

38

90

81

5

Se

r9G

ly

T/C

0

.30

1

93

1

65

3

8

5H

TR

2A

rs

63

13

C

hr1

3:4

74

69

94

0

T1

02

C

C/T

0

.45

1

15

2

11

7

4

rs

63

14

C

hr1

3:4

74

09

03

4

His

45

2T

yr

C/T

0

.09

3

15

6

6

3

5H

TR

2C

rs

38

13

92

9

X:1

13

81

85

20

-7

59

C_

T

C/T

0

.18

3

19

8

2**

rs

63

18

X

:11

39

65

73

5

Cys2

3S

er

G/C

0

.16

3

27

7

3**

CO

MT

rs

46

80

C

hr2

2:1

99

51

27

1

Va

l15

8M

et

A/G

0

.47

1

09

2

08

8

4

NQ

O1

rs

18

00

56

6

Ch

r16

:69

74

51

45

C

60

9T

C

/T

0.1

8

27

6

10

7

18

RG

S2

rs

46

06

C

hr1

:19

27

81

17

2

- C

/G

0.2

6

22

2

15

4

26

GS

TP

1

rs1

69

5

Ch

r11

:67

35

26

89

Ile

10

5V

a

A/G

0

.41

1

40

1

95

6

7

*Ma

jor

alle

le is g

ive

n f

irst.

**

Nu

mb

er

of

pa

tie

nts

wh

o is c

arr

ier

of

the

min

or

alle

le.

MA

F =

min

or

alle

le f

req

ue

ncy

Tabl

e 2:

Freq

uenc

ies o

f alle

les a

nd ge

noty

pes o

f pol

ymor

phism

s in

dopa

min

e rel

ated

cand

idat

e gen

es in

402

Cau

casia

n pa

tient

s with

schi

zoph

reni

a.

77

mov

emen

t di

sord

ers i

n pa

tien

ts w

ith

schi

zoph

reni

a an

d in

the

ir si

blin

gsTable 3: LD patterns of polymorphisms in DRD2, D’ (lower triangle) and r2 (upper triangle) between polymorphisms are given.

67

Table 3: LD patterns of polymorphisms in DRD2, D' (lower triangle) and r2 (upper triangle) between

polymorphisms are given.

DRD2 rs1800497 rs6277 rs1800498 rs1799732

rs1800497 - 0.08 0.13 0.01

rs6277 0.56 - 0.58 0.04

rs1800498 0.59 0.91 - 0.13

rs1799732 0.59 0.56 0.83 -

78

part II

68

Ta

ble

4:

Asso

cia

tio

n o

f d

op

am

ine

re

late

d p

oly

mo

rph

ism

s w

ith

an

tip

sych

otic in

du

ce

d m

ove

me

nt

dis

ord

ers

in

40

2 C

au

ca

sia

n p

atie

nts

with

sch

izo

ph

ren

ia.

Genoty

pe info

rmation

Logis

tic r

egre

ssio

n

Gene

rs

-id

V

ariant

Alle

les*

Park

insonis

m

Akath

isia

T

ard

ive D

yskin

esia

OR

(95%

C.I.)

P

O

R (

95%

C.I.)

P

O

R (

95%

C.I.)

P

DR

D2

rs

1800497

T

aqI_

A

C/T

1.2

5 (

0.8

7-1

.79)

0.2

3

1.7

6 (

1.0

5-2

.96)

0.0

3

1.0

9 (

0.7

3-1

.63)

0.6

8

rs

6277

C

957T

T

/C

1.1

1 (

0.8

2-1

.49)

0.5

1

1.5

8 (

0.9

8-2

.55)

0.0

6

0.8

8 (

0.6

4-1

.23)

0.4

7

rs

1800498

T

aqI_

D

T/C

1.1

9 (

0.8

8-1

.62)

0.2

7

2.3

3 (

1.4

3-3

.82)

0.0

01

0.8

9 (

0.6

3-1

.26)

0.5

1

rs

1799732

-1

41C

C

/Del

1.0

1 (

0.6

2-1

.64)

0.9

7

1.4

8 (

0.7

5-2

.89)

0.2

6

0.2

0 (

0.0

8-0

.50)

0.0

01

DR

D3

rs

6280

S

erG

ly

T/C

0.9

2 (

0.6

6-1

.28)

0.6

1

0.9

0 (

0.5

3-1

.54)

0.7

0

1.2

3 (

0.8

6-1

.76)

0.2

7

5H

TR

2A

rs

6313

T

102C

C

/T

1.2

1 (

0.8

8-1

.66)

0.2

4

1.3

7 (

0.8

3-2

.26)

0.2

2

0.8

5 (

0.6

0-1

.21)

0.3

7

rs

6314

H

is452T

yr

C/T

1.3

5 (

0.8

1-2

.27)

0.2

5

0.8

6 (

0.3

6-2

.08)

0.7

4

0.6

6 (

0.3

4-1

.29)

0.2

2

5H

TR

2C

rs

3813929**

-7

59C

_T

C

/T

0.5

8 (

0.3

3-1

.04)

0.0

7

0.9

1 (

0.3

8-2

.16)

0.8

2

0.8

0 (

0.4

3-1

.50)

0.5

0

rs

6318**

C

ys23S

er

G/C

1.2

0 (

0.6

9-2

.09)

0.5

2

1.1

1 (

0.4

6-2

.67)

0.8

3

1.3

6 (

0.7

4-2

.50)

0.3

2

CO

MT

rs

4680

V

al1

58M

et

A/G

0.8

4 (

0.6

1-1

.15)

0.2

7

1.0

1 (

0.6

2-1

.65)

0.9

6

0.9

1 (

0.6

4-1

.29)

0.6

0

NQ

O1

rs1800566

C

609T

C

/T

0.7

9 (

0.5

3-1

.17)

0.2

4

1.2

8 (

0.7

3-2

.24)

0.3

8

1.2

0 (

0.8

0-1

.81)

0.3

7

RG

S2

rs

4606

-

C/G

0.8

0 (

0.5

6-1

.14)

0.2

2

0.8

7 (

0.4

9-1

.54)

0.6

3

1.0

1 (

0.6

9-1

.49)

0.9

6

GS

TP

1

rs1695

Ile105V

a

A/G

0.9

3 (

0.6

8-1

.27)

0.6

5

1.0

3 (

0.6

3-1

.68)

0.9

0

0.9

6 (

0.6

8-1

.35)

0.8

0

OR

= O

dd

s r

atio

, 9

5%

C.I

. =

95

% C

on

fid

en

ce

In

terv

al, P

= p

-va

lue

*M

ajo

r a

llele

is g

ive

n f

irst.

**

Te

ste

d in

a d

om

ina

nt

mo

de

l, b

eca

use

of

po

sitio

n o

n X

-ch

rom

oso

me.

Tabl

e 4:

Ass

ocia

tion

of d

opam

ine

rela

ted

poly

mor

phism

s w

ith a

ntip

sych

otic

indu

ced

mov

emen

t di

sord

ers

in 4

02 C

auca

sian

patie

nts

with

sc

hizo

phre

nia.

Gen

otyp

e in

form

atio

n Lo

gist

ic re

gres

sion

Gen

e rs

-id

Var

iant

A

llele

s*

Par

kins

onis

m

Aka

this

ia

Tard

ive

Dys

kine

sia

OR

(95%

C.I.

) P

OR

(95%

C.I.

) P

OR

(95%

C.I.

) P

DR

D2

rs18

0049

7 Ta

qI_A

C

/T

1.25

(0.8

7-1.

79)

0.23

1.

76 (1

.05-

2.96

) 0.

03

1.09

(0.7

3-1.

63)

0.68

rs

6277

C

957T

T/

C

1.11

(0.8

2-1.

49)

0.51

1.

58 (0

.98-

2.55

) 0.

06

0.88

(0.6

4-1.

23)

0.47

rs

1800

498

TaqI

_D

T/C

1.

19 (0

.88-

1.62

) 0.

27

2.33

(1.4

3-3.

82)

0.00

1 0.

89 (0

.63-

1.26

) 0.

51

rs

1799

732

-141

C

C/D

el

1.01

(0.6

2-1.

64)

0.97

1.

48 (0

.75-

2.89

) 0.

26

0.20

(0.0

8-0.

50)

0.00

1

DR

D3

rs62

80

Ser

Gly

T/

C

0.92

(0.6

6-1.

28)

0.61

0.

90 (0

.53-

1.54

) 0.

70

1.23

(0.8

6-1.

76)

0.27

5HTR

2A

rs63

13

T102

C

C/T

1.

21 (0

.88-

1.66

) 0.

24

1.37

(0.8

3-2.

26)

0.22

0.

85 (0

.60-

1.21

) 0.

37

rs

6314

H

is45

2Tyr

C

/T

1.35

(0.8

1-2.

27)

0.25

0.

86 (0

.36-

2.08

) 0.

74

0.66

(0.3

4-1.

29)

0.22

5HTR

2C

rs38

1392

9**

-759

C_T

C

/T

0.58

(0.3

3-1.

04)

0.07

0.

91 (0

.38-

2.16

) 0.

82

0.80

(0.4

3-1.

50)

0.50

rs

6318

**

Cys

23S

er

G/C

1.

20 (0

.69-

2.09

) 0.

52

1.11

(0.4

6-2.

67)

0.83

1.

36 (0

.74-

2.50

) 0.

32

CO

MT

rs46

80

Val

158M

et

A/G

0.

84 (0

.61-

1.15

) 0.

27

1.01

(0.6

2-1.

65)

0.96

0.

91 (0

.64-

1.29

) 0.

60

NQ

O1

rs18

0056

6 C

609T

C

/T

0.79

(0.5

3-1.

17)

0.24

1.

28 (0

.73-

2.24

) 0.

38

1.20

(0.8

0-1.

81)

0.37

RG

S2

rs46

06

- C

/G

0.80

(0.5

6-1.

14)

0.22

0.

87 (0

.49-

1.54

) 0.

63

1.01

(0.6

9-1.

49)

0.96

GS

TP1

rs16

95

Ile10

5Va

A/G

0.

93 (0

.68-

1.27

) 0.

65

1.03

(0.6

3-1.

68)

0.90

0.

96 (0

.68-

1.35

) 0.

80

79

mov

emen

t di

sord

ers i

n pa

tien

ts w

ith

schi

zoph

reni

a an

d in

the

ir si

blin

gsReferences

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43. Zai CC, Tiwari AK, Muller DJ, et al. The catechol-O-methyl-transferase gene in tardive dyskinesia. World J Biol Psychiatry Sep 2010;11(6):803-812.

44. Tsai G, Goff DC, Chang RW, Flood J, Baer L, Coyle JT. Markers of glutamatergic neurotransmission and oxidative stress associated with tardive dyskinesia. Am J Psychiatry Sep 1998;155(9):1207-1213.

45. Ng F, Berk M, Dean O, Bush AI. Oxidative stress in psychiatric disorders: evidence base and therapeutic implications. Int J Neuropsychopharmacol Sep 2008;11(6):851-876.

46. Kang SG, Lee HJ, Choi JE, An H, Rhee M, Kim L. Association study between glutathione S-transferase GST-M1, GST-T1, and GST-P1 polymorphisms and tardive dyskinesia. Hum Psychopharmacol Jan 2009;24(1):55-60.

47. Al Hadithy AF, Ivanova SA, Pechlivanoglou P, et al. Missense polymorphisms in three oxidative-stress enzymes (GSTP1, SOD2, and GPX1) and dyskinesias in Russian psychiatric inpatients from Siberia. Hum Psychopharmacol Jan 2010;25(1):84-91.

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48. Greenbaum L, Smith RC, Rigbi A, et al. Further evidence for association of the RGS2 gene with antipsychotic-induced parkinsonism: protective role of a functional polymorphism in the 3’-untranslated region. Pharmacogenomics J Apr 2009;9(2):103-110.

49. Greenbaum L, Strous RD, Kanyas K, et al. Association of the RGS2 gene with extrapyramidal symptoms induced by treatment with antipsychotic medication. Pharmacogenet Genomics Jul 2007;17(7):519-528.

50. Bakker PR, van Harten PN, van Os J. Antipsychotic-induced tardive dyskinesia and polymorphic variations in COMT, DRD2, CYP1A2 and MnSOD genes: a meta-analysis of pharmacogenetic interactions. Mol Psychiatry May 2008;13(5):544-556.

51. GROUP I. Evidence That Familial Liability for Psychosis Is Expressed as Differential Sensitivity to Cannabis: An Analysis of Patient-Sibling and Sibling-Control Pairs. Arch Gen Psychiatry Oct 4 2010.




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72. Ritchie T, Noble EP. Association of seven polymorphisms of the D2 dopamine receptor gene with brain receptor-binding characteristics. Neurochem Res Jan 2003;28(1):73-82.

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74. Duan J, Wainwright MS, Comeron JM, Saitou N, Sanders AR, Gelernter J, Gejman PV. Synonymous mutations in the human dopamine receptor D2 (DRD2) affect mRNA stability and synthesis of the receptor. Hum Mol Genet Feb 1 2003;12(3):205-216.

75. Jonsson EG, Nothen MM, Grunhage F, Farde L, Nakashima Y, Propping P, Sedvall GC. Polymorphisms in the dopamine D2 receptor gene and their relationships to striatal dopamine receptor density of healthy volunteers. Mol Psychiatry May 1999;4(3):290-296.

76. Wu SN, Gao R, Xing QH, Li HF, Shen YF, Gu NF, Feng GY, He L. Association of DRD2 polymorphisms and chlorpromazine-induced extrapyramidal syndrome in Chinese schizophrenic patients. Acta Pharmacol Sin Aug 2006;27(8):966-970.

77. Kane JM, Fleischhacker WW, Hansen L, Perlis R, Pikalov A, 3rd, Assuncao-Talbott S. Akathisia: an updated review focusing on second-generation antipsychotics. J Clin Psychiatry May 2009;70(5):627-643.

78. Marsden CD, Jenner P. The pathophysiology of extrapyramidal side-effects of neuroleptic drugs. Psychol Med Feb 1980;10(1):55-72.

79. Jorgensen AL, Williamson PR. Methodological quality of pharmacogenetic studies: issues of concern. Stat Med Dec 30 2008;27(30):6547-6569.

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80. Eichhammer P, Albus M, Borrmann-Hassenbach M, Schoeler A, Putzhammer A, Frick U, Klein HE, Rohrmeier T. Association of dopamine D3-receptor gene variants with neuroleptic induced akathisia in schizophrenic patients: a generalization of Steen’s study on DRD3 and tardive dyskinesia. Am J Med Genet Apr 3 2000;96(2):187-191.

81. Masand PS, Roca M, Turner MS, Kane JM. Partial adherence to antipsychotic medication impacts the course of illness in patients with schizophrenia: a review. Prim Care Companion J Clin Psychiatry 2009;11(4):147-154.

82. Zhang JP, Lencz T, Malhotra AK. D2 receptor genetic variation and clinical response to antipsychotic drug treatment: a meta-analysis. Am J Psychiatry Jul 2010;167(7):763-772.

83. Schooler NR, Kane JM. Research diagnoses for tardive dyskinesia. Arch Gen Psychiatry Apr 1982;39(4):486-487.


85. Alkelai A, Greenbaum L, Rigbi A, Kanyas K, Lerer B. Genome-wide association study of antipsychotic-induced parkinsonism severity among schizophrenia patients. Psychopharmacology (Berl) Oct 2009;206(3):491-499.

86. Greenbaum L, Alkelai A, Rigbi A, Kohn Y, Lerer B. Evidence for association of the GLI2 gene with tardive dyskinesia in patients with chronic schizophrenia. Mov Disord Dec 15 2010;25(16):2809-2817.

87. Inada T, Koga M, Ishiguro H, et al. Pathway-based association analysis of genome-wide screening data suggest that genes associated with the gamma-aminobutyric acid receptor signaling pathway are involved in neuroleptic-induced, treatment-resistant tardive dyskinesia. Pharmacogenet Genomics Apr 2008;18(4):317-323.

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Part III

Mechanical measurement of dyskinesia and parkinsonism

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Chapter 3.1

Instrument measurement of lingual force variability reflects tardive tongue dyskinesia

Jeroen P Koning, Diederik E Tenback, René S Kahn, Leonard J Van Schelven, Peter N van Harten

Published in Journal of Medical Engineering & Technology, 2010;34(1):71-7.

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nismAbstract

Introduction

Tardive tongue dyskinesia is under- and/or misdiagnosed. Instrument measurement of lingual force variability may be a valid and reliable method for assessing tardive tongue dyskinesia.

Material and Methods

Instrument measurement of lingual force variability was compared to the clinical level of tardive tongue dyskinesia and total body dyskinesia as measured by the Abnormal Involuntary Movement Rating Scale (AIMS) in 35 subjects, 23 patients with a psychiatric disorder using antipsychotics of which 11 with and 12 without tardive tongue dyskinesia, and 12 age- and gender-matched healthy controls.

Results

Lingual force variability correlated with tardive tongue dyskinesia (Spearman r = 0.56 p <0.01) and with total dyskinesia (r = 0.47 p =0.02); there was no association with age, antipsychotic dose, or psychiatric diagnosis. Instrument test-retest reliability corresponded with an ICC of 0.85 p < 0.0001.

Conclusion

Instrument measurement of lingual force variability is a valid and reliable method for assessing tardive tongue dyskinesia.

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Recognition and management of tardive dyskinesia (TD) is clinically important since these hyperkinetic side effects of antipsychotics are associated with physical disabilities, social stigmatisation, and poorer quality of life 1. However, tardive dyskinesia, tongue dyskinesia in particular, is often under- and / or misdiagnosed 2. The use of instruments to quantify lingual force variability may be a valid and reliable method for assessing tardive tongue dyskinesia (TTD). In fact, most diagnoses of TD are based on clinical rating scales, although instrument assessment has been shown to be superior in regard to sensitivity, specificity and reliability 3-13. Nevertheless, instrumental assessment has not gained wide appeal in clinical setting of psychiatry. Several factors could play a role; first psychiatrists were not used to add mechanical instruments for diagnostic purposes. However, new developments has changed this view and instruments such as neuroimaging and pharmacogenetic will be or are already entering the clinical office. Second; in the past, early diagnosis of tardive dyskinesia could not or only slightly influence the clinical management of tardive dyskinesia and no effective preventive strategies were available. Nowadays, with the introduction of Second Generation Antipsychotics prevention of tardive dyskinesia became a new issue and early recognition of dyskinetic movements may play a major role in this process 14, 15. Moreover, early recognition may even become more important as subtle movement disorders are predictive for schizophrenia 16, 17 and there is some evidence that early treatment of individuals at risk can influence the course positively 18. Interestingly, previous studies on instrument assessment of TD mostly focus on the upper extremities 5-10, 13, 19-21, despite the fact that orofacial dyskinesia is more prevalent than finger dyskinesia 22-24. To date, only one study has reported that the degree of lingual motor instability was associated with TTD in patients with schizophrenia 25 . We hypothesized that instrument measurement of lingual force variability is a valid and reliable technique for assessing TTD and therefore carried out a validation study analyzing the sensitivity, specificity and the reliability of instrumental assessment with the AIMS as the golden standard.

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Material and Methods

SubjectsThirty-five subjects were recruited from a psychiatric hospital in the Netherlands; 11 patients with a psychiatric disorder using antipsychotics and tardive tongue dyskinesia, 12 patients with a psychiatric disorder using antipsychotics without tardive tongue dyskinesia, and 12 age- and gender-matched healthy controls. The twenty-three patients used antipsychotics and had a diagnosis of schizophrenia, schizoaffective, schizophreniform, mood, or personality disorder according to DSM-IV criteria 26. The healthy controls consisted out of the nursing and support staff with no history of psychiatric disorders or antipsychotic use. Patients with neurological disorders other than dyskinesia were excluded. The Medical Ethical Committee approved the study. After the purpose of the study was explained, all subjects signed a written informed consent.

Assessment of clinical TTD (the gold standard)All subjects were videotaped during the examination for movement disorders. The tapes were rated with the use of the Abnormal Involuntary Movement Scale (AIMS) 27 by two psychiatrists with expertise in movement disorders (PvH, RB*). Videotaping is regularly used in research 28, 29 and contributed to the accuracy and reliability of the assessment and enable raters to score independently. Furthermore, mute videos were used to prevent that raters could detect the subject’s status by the conversation. In the event of disagreement, the mean score was calculated. The presence of TTD was defined by a score of 2 or higher on the item of the tongue on the AIMS.

Instrument assessment of lingual force variabilityInstrument measurement of force variability consisted of the subject’s attempt to apply constant pressure on a load cell and measuring the amount of variability in the force applied. This method has been extensively validated for finger dyskinesia 5-10, 13, 19-21. Based on the information presented in prior articles, the technique was modified to permit quantification of lingual force variability (Figure 1). Subjects were instructed to lift and apply constant pressure to a replaceable spatula with the tip (2 cm) of their tongue to a target level. The spatula was connected via a load cell to a real-time display, which indicated the target height. The strength required to achieve the targeted

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maximum lifting ability and was easily achieved by all subjects. Subjects performed 3 x 20-second trials, separated by 5-second rest periods. The first trial was regarded as a learning trial. Data of the 2 subsequent trials were used for analysis.

Analysis of instrument lingual force variabilityThe force generated by the tongue was measured continuously (12 bit sampling at 2.5 kHz, digital low-pass filtering at 3 Hz, storage and further analysis at 100 Hz) and was Fourier transformed. Total power in the 0 – 3 Hz band was calculated and converted to assess the standard deviation for the 0 – 3 Hz signal components. The spread of the data is presented as a percentage of error, or coefficient of variation (CV, standard deviation divided by mean force). Only force measured at the 0 – 3 Hz frequency band was used, as this reflects dyskinesia best and is unaffected by resting tremor artifact secondary to antipsychotic-induced parkinsonism 30 (measured at the 4 – 6 Hz frequency band) and has proven to be a reliable, sensitive, and valid approach in studies measuring hand dyskinesia 5-10, 13,

19-21.

Statistical methodsThe concurrent validity of the instrument was evaluated by calculating Spearman’s correlation coefficient between the lingual force variability and the clinical level of TTD measured with the AIMS (the gold standard). To determine the optimal threshold value of lingual force variability to discriminate between the diagnosis of TTD or none, a Receiver Operating Characteristic (ROC) curve was calculated (a graphical plot of the sensitivity versus 1- specificity). To test differences between the groups, Student’s t-test, Chi-square and Mann-Whitney tests were applied according to the type and distribution of data. A weighted kappa reflected the degree of agreement between the two raters. The test- retest reliability of the instrument was assessed using intra-class correlation coefficients (ICC) after a one-hour interval. Logistic regression analysis was conducted to investigate the effects of age, psychiatric diagnosis, and antipsychotic use on the diagnosis of TTD in relation to lingual force variability.

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Results

Table 1 shows the demographic characteristics and the results of the three groups. Pairwise comparison did not show significant differences in group characteristics. When comparing the mean AIMS scores of the tongue and the degree of lingual force variability between the three groups, patients with TTD had significantly higher scores compared to the patients without TTD and the controls. A comparison using the AIMS of patients without TTD and controls found no difference in mean AIMS scores of the tongue, however patients without TTD tended to have higher mean scores of lingual force variability than controls. Based on the range scores of the controls, 7 patients (58%) without and all patients with TTD displayed more lingual force variability (p=0.03 and p<0.001 respectively) (figure 2).

ValidityThe lingual force variability correlated significantly with the AIMS score of the tongue (for the patient group, with and without TTD, n=23) Spearman r= 0.56, p < 0.01, and for the total group, r=0.62, p < 0.01, n=35). Lingual force variability also correlated significantly with total dyskinesia (excluding the AIMS tongue item dyskinesia (r= 0.47, p=0.02)) in the patient group. No significant correlation was found between lingual force variability with any of the other separate AIMS items. Logistic regression indicated a significant relationship between lingual force variability and the diagnosis of TTD in the patient group and remained significant after adding age, psychiatric diagnosis, and antipsychotic use as covariates to the logistic regression analysis. The best cut off value to discriminate between the presence and absence of TTD was a lingual force variability CV of 22% in the patient group (sensitivity of 82%, specificity of 75% and a total Area-Under-the-Curve (AUC) of 0.84, CI:0.67-1.00)) as well in the total group (sensitivity of 82% and specificity of 83% and a total AUC of 0.92, CI:0.82-1.00)) (figure 3 and 4 respectively).

ReliabilityThe interrater reliability between the two psychiatrists (PvH, RB*) using a weighted kappa was 0.73. The intra-rater test-retest reliability of the instrument after a one-hour interval using ICC was 0.85 (p<0.001) for the patient group (n=22) and 0.90 (p<0.001) for the total group (n=34). One patient refused the retest, due to lack of motivation.

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This study indicates that instrument measurement of lingual force variability is a valid and reliable method to assess tardive tongue dyskinesia. We found a moderate and significant correlation between lingual force variability and both TTD and total body dyskinesia measured with the AIMS. Furthermore, the classification performance using lingual force variability to diagnose TTD was good. Moreover there was no overlap in steadiness error between the TTD+ group and the healthy controls. Both results strongly support the face and content validity of the instrument. In addition, the results showed that lingual force variability differentiated better between controls and patients without TTD. Interestingly, 5 patients without TTD displayed lingual force variability in the TTD+ range suggesting that instrumental measurement is more sensitive than the AIMS to detect subclinical dyskinesia. Indeed, the superior sensitivity of instrumental measurements has been reported previously in a similar study comparing force variability of the hand with a clinical rating scale 10. Our study also reports a test- retest reliability that was more reliable than the clinical ratings. This study confirms the previous reported correlation (r = 0.65, p <0.001) between instrument assessment of lingual force variability and TTD in patients 25 and test- retest reliability of instrument assessment of TD (ICC’s ranging between 0.81 and 0.97) 4, 5, 8, 13, 20. Instrumental assessment of tardive tongue dyskinesia in the clinical setting has several advantages. First, the procedure is not vulnerable to reporting bias, and variability in experience and/or subjectivity of raters. Second, the test can easily be incorporated in clinical practice because it is not invasive, is easy to handle, needs no specific training, and takes only a few minutes. Third, the apparatus and the required laptop are portable. Some limitations should be noted. First, the results are based on a small sample size. However, despite the small numbers, significant results were found that confirmed the validity and the reliability of instrument assessment of lingual force variability in association with TTD. Second, it remains possible that the decreased capacity of patients to hold their tongues steady is (partly) explained by other neurological dysfunctions. Neurological soft signs (and by inference cerebellar dysfunction) 31 are present in schizophrenia and mood disorders 32, 33 and correlate with dyskinesia 34, 35. The relationship between drug-induced parkinsonism

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(including resting tremor) and TD remains unclear, since positive 36 as well as negative 37 associations have been reported. However, TD is measured in the 0 – 3 Hz frequency range and therefore unaffected by a resting tremor, which is measured in the 4 – 6 Hz frequency range 19, 30. Interestingly, in more than half of the patients, subclinical tongue dyskinesia was found by measuring lingual force variability, which may be of clinical value for predicting the risk for clinical TD. However, longitudinal studies are needed to ascertain the predictive value of abnormal force variability for TD.

AcknowledgementsWe thank all patients and members of the nursing and support staff who participated in this study, the Department of Medical Technology and Clinical Physics of the University Medical Center Utrecht for the hard- and software provided, psychiatrist R. Bakker (RB) and author P.N. van Harten (PvH) for their clinical rating of all movement disorders. This work was supported by an unrestricted grant from the foundation “De Open Ankh“, the Netherlands.

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nismFigure 1. Instrument and method for measuring lingual force variability.

Figure 2. Scatterplot of lingual force variability in % CV and the mean scores for controls, patients without (-) and patients with (+) tardive tongue dyskinesia.

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Figure 1. Instrument and method for measuring lingual force variability.

Front side Box Spatula

Loadcell

Subject’s attempt to match the target height

Target height (0.8 Newton)

Spatula

Back side box

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Figure 2. Scatterplot of lingual force variability in % CV and the mean scores for controls, patients without (-) and patients with (+) tardive tongue dyskinesia.

Figure 3. The ROC curve to discriminate between the presence and absence of TTD in the patients group (n=23). The AUC is 0.84

Figure 4. The ROC curve to discriminate between the presence and absence of TTD in the total group (n=35). The AUC is 0.92

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Figure 3. The ROC curve to discriminate between the presence and absence of TTD in the patients group (n=23). The AUC is 0.84

Figure 4. The ROC curve to discriminate between the presence and absence of TTD in the total group (n=35). The AUC is 0.92

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References


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3. Bergen JA, Griffiths DA, Rey JM, Beumont PJ. Tardive dyskinesia: fluctuating patient or fluctuating rater. Br J Psychiatry May 1984;144:498-502.

4. Caligiuri MP, Harris MJ, Jeste DV. Quantitative analyses of voluntary orofacial motor control in schizophrenia and tardive dyskinesia. Biol Psychiatry Nov 1988;24(7):787-800.



7. Caligiuri MP, Lohr JB, Panton D, Harris MJ. Extrapyramidal motor abnormalities associated with late-life psychosis. Schizophr Bull 1993;19(4):747-754.




11. Gardos G, Cole JO, La Brie R. The assessment of tardive dyskinesia. Arch Gen Psychiatry Oct 1977;34(10):1206-1212.

12. Lane RD, Glazer WM, Hansen TE, Berman WH, Kramer SI. Assessment of tardive dyskinesia using the Abnormal Involuntary Movement Scale. J Nerv Ment Dis Jun 1985;173(6):353-357.


14. Tenback DE, van Harten PN, Slooff CJ, Belger MA, van Os J. Effects of antipsychotic treatment on tardive dyskinesia: a 6-month evaluation of patients from the European Schizophrenia Outpatient Health Outcomes (SOHO) Study. J Clin Psychiatry Sep 2005;66(9):1130-1133.

15. Margolese HC, Chouinard G, Kolivakis TT, Beauclair L, Miller R, Annable L. Tardive dyskinesia in the era of typical and atypical antipsychotics. Part 2: Incidence and management strategies in patients with schizophrenia. Can J Psychiatry Oct 2005;50(11):703-714.


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nism17. Walker EF. Developmentally moderated expressions of the neuropathology

underlying schizophrenia. Schizophr Bull 1994;20(3):453-480.18. Haroun N, Dunn L, Haroun A, Cadenhead KS. Risk and protection in prodromal

schizophrenia: ethical implications for clinical practice and future research. Schizophr Bull Jan 2006;32(1):166-178.

19. Caligiuri MP, Lohr JB, Bracha HS, Jeste DV. Clinical and instrumental assessment of neuroleptic-induced parkinsonism in patients with tardive dyskinesia. Biol Psychiatry Jan 15 1991;29(2):139-148.

20. Caligiuri MP, Lohr JB, Vaughan RM, McAdams LA. Fluctuation of tardive dyskinesia. Biol Psychiatry Sep 1 1995;38(5):336-339.

21. Lohr JB, Caligiuri MP. Motor asymmetry, a neurobiologic abnormality in the major psychoses. Psychiatry Res Aug 28 1995;57(3):279-282.

22. Jeste D.V. WRJ. Understanding and treating dyskinesia. New York: Guilford; 1982.23. McCreadie RG, Srinivasan TN, Padmavati R, Thara R. Extrapyramidal symptoms

in unmedicated schizophrenia. J Psychiatr Res May 2005;39(3):261-266.24. Mittal VA, Neumann C, Saczawa M, Walker EF. Longitudinal progression of

movement abnormalities in relation to psychotic symptoms in adolescents at high risk of schizophrenia. Arch Gen Psychiatry Feb 2008;65(2):165-171.

25. Caligiuri MP, Jeste DV, Harris MJ. Instrumental assessment of lingual motor instability in tardive dyskinesia. Neuropsychopharmacology Dec 1989;2(4):309-312.

26. APA. Diagnostic and Statistical Manual of Mental Disorders. 4 th ed. Washington, DC: American Psychiatric Association; 1994.


28. Ondo WG, Hanna PA, Jankovic J. Tetrabenazine treatment for tardive dyskinesia: assessment by randomized videotape protocol. Am J Psychiatry Aug 1999;156(8):1279-1281.

29. Slotema CW, van Harten PN, Bruggeman R, Hoek HW. Botulinum toxin in the treatment of orofacial tardive dyskinesia: a single blind study. Prog Neuropsychopharmacol Biol Psychiatry Feb 15 2008;32(2):507-509.


31. Ho BC, Mola C, Andreasen NC. Cerebellar dysfunction in neuroleptic naive schizophrenia patients: clinical, cognitive, and neuroanatomic correlates of cerebellar neurologic signs. Biol Psychiatry Jun 15 2004;55(12):1146-1153.

32. Boks MP, Russo S, Knegtering R, van den Bosch RJ. The specificity of neurological signs in schizophrenia: a review. Schizophr Res Jun 16 2000;43(2-3):109-116.

33. Buchanan RW, Heinrichs DW. The Neurological Evaluation Scale (NES): a structured instrument for the assessment of neurological signs in schizophrenia. Psychiatry Res Mar 1989;27(3):335-350.

34. King DJ, Wilson A, Cooper SJ, Waddington JL. The clinical correlates of neurological soft signs in chronic schizophrenia. Br J Psychiatry Jun 1991;158:770-775.

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36. Lauterbach EC, Carter WG, Rathke KM, et al. Tardive dyskinesia--diagnostic issues, subsyndromes, and concurrent movement disorders: a study of state hospital inpatients referred to a movement disorder consultation service. Schizophr Bull 2001;27(4):601-613.

37. van Harten PN, Hoek HW, Matroos GE, van Os J. Incidence of tardive dyskinesia and tardive dystonia in African Caribbean patients on long-term antipsychotic treatment: the Curacao extrapyramidal syndromes study V. J Clin Psychiatry Dec 2006;67(12):1920-1927.

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Chapter 3.2

Movement disorders in nonpsychotic siblings of patients with non-affective psychosis

Jeroen P Koning, René S Kahn, Diederik E Tenback, Leonard J van Schelven, Peter N van Harten

Published in Psychiatry Research, 2011 Jun 30;188(1):133-7.

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Introduction

Movement disorders such as dyskinesia and parkinsonism have frequently been reported in (drug-naive) patients with nonaffective psychosis. Therefore movement disorders may be related to schizophrenia. Siblings of patients with nonaffective psychosis also appear to have subtle forms of movement disorders. This suggests that motor abnormalities may also be related to the risk of developing the disease. Subtle forms are not always detected with the use of the standard observation-based clinical rating scales, which are less sensitive than mechanical instrument measurement.

Methods

This study compared the presence and severity of dyskinesia and parkinsonism in 42 non-psychotic siblings of patients with nonaffective psychosis and in 38 controls as measured by mechanical instruments and clinical rating scales.

Results

There were no significant differences in movement disorders between siblings and controls on the basis of clinical assessments. However, mechanical measurements indicated that siblings compared to controls displayed significantly more dyskinesia and parkinsonism signs.

Discussion

These results suggest that motor signs could be markers of vulnerability for psychosis or schizophrenia. In addition this study shows that mechanical instrument measurement of movement disorders is more sensitive than assessment with clinical rating scales. Therefore, it may be used in screening programs for populations at risk for psychosis.

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Movement disorders such as dyskinesia and parkinsonism (resting tremor, bradykinesia, rigidity, and postural instability) have been reported in patients with psychosis or schizophrenia since long before the introduction of antipsychotic medication and might possibly be regarded as one of the core features of the illness 1-4. Furthermore, there is evidence that these hyper- and hypokinetic movement disorders also occur in populations that are at risk for schizophrenia or other nonaffective psychoses, such as adolescents with schizotypal symptoms 5-8, children of patients with schizophrenia 7, first degree relatives of schizophrenia (see for meta-analysis 1 and may even precede the onset of psychotic symptoms in patients with schizophrenia 8. Movement disorders and psychosis are both associated with the deregulation of the dopamine system 9, 10 and may therefore share a common aetiology, which could be (partly) genetic or environmental. If populations at risk for psychosis, such as siblings of patients with a non-affective psychosis, show a higher prevalence of movement disorders than healthy controls, this would substantiate the hypothesis that movement disorders are related to the risk of psychosis. A recent meta-analysis comparing movement disorders in siblings and controls found a significant difference in prevalence only after the results of the individual studies were pooled 1. One explanation could be that the rating scales used, clinical observation-based assessments primarily developed to evaluate drug-induced movement disorders, are not sensitive enough to detect subtle movement disturbances. In fact several studies show that mechanical instrument measurements of dyskinesia and parkinsonism are more sensitive and reliable than clinical observation-based rating scales 11-18. We hypothesised that measurement with mechanical instruments would reveal that nonpsychotic siblings of patients with a nonaffective psychosis have more dyskinesia and parkinsonism than healthy controls whereas clinical assessments would not.

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2. Methods

2.1 Subjects

Nonpsychotic siblings (n=42) of patients with a nonaffective psychosis and healthy controls (n=38) were recruited from the Genetic Risk and Outcome of Psychosis (GROUP) program at the University Medical Centre Utrecht and the Psychiatric Centre Symfora Group in Amersfoort, the Netherlands. Patients were identified through screening caseloads of clinicians working in regional psychotic disorders services for inclusion criteria. Controls were recruited by advertising in the local newspapers. Inclusion criteria for both groups were age (between 18–45 years) and no diagnosis of psychosis. To prevent the inclusion of individuals with possible other causes of movement disorders, the exclusion criteria for both groups were a history of neurological disease, the use of psychotropic medication 19, and substance abuse 20. Controls with a first- or second-degree relative with psychosis or schizophrenia were also excluded. If more than one sibling per affected family was recruited, only one full biological sibling with the best demographical match with the control group was included. The Utrecht Medical Ethics Committee, the Netherlands, approved the study. All participants signed a written informed consent after the purpose of the study was explained to them.

2.2 Clinical assessments

All participants were evaluated with the Comprehensive Assessment of Symptoms and History (CASH) for clinical history and use of psychotropic medication. The mood disorder sections of the CASH were used to diagnose affective syndromes. The Composite International Diagnostic Interview (CIDI) was administered for drug abuse, the Abnormal Involuntary Movement Scale (AIMS) 21 for clinical dyskinesia, and the Unified Parkinson Disease Rating Scale (UPDRS) 22 for clinical parkinsonism. Mood disorders were Residents in psychiatry (n=3) and research assistants (n=5) administered the assessments. As part of the GROUP study protocol, yearly training sessions were held to maintain reliability. In addition, the research staff involved in this study received additional training by 2 psychiatrists with expertise in movement disorders (PvH and DT*). Inter-rater reliability was calculated by comparing the raters’

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nismscoring of 8 videotapes of patients with and without dyskinesia and

parkinsonism.

2.3 Clinical definitions of dyskinesia and parkinsonism

2.3.1 Clinical dyskinesia

Dyskinesia is characterized by involuntary writhing and purposeless, irregular movements that may or may not be continuous. The AIMS, the clinical scale used to evaluate dyskinesia, divides the body into 7 different areas (Face, Tongue, Lips, Jaw, Upper limbs, Lower limbs and Neck, shoulders and hips). Each item is scored from 0 to 4 to indicate disorder severity (0=absent, 1=questionable, 2= mild, 3= moderate, 4= severe). We defined clinical dyskinesia as a score of 2 or greater on any of the 7 items of the AIMS, as based on the research criteria for dyskinesia 23.

2.3.2 Clinical parkinsonism

Parkinsonism is an akinetic rigid syndrome with the following cardinal features: resting tremor (frequency of 4 to 6 Hz), bradykinesia, rigidity and postural instability.The clinical rating scale used to assess parkinsonism, the motor examination part of the UPDRS (excluding the item of action tremor), assesses speech, facial mobility, resting tremor (face and each limb), rigidity (neck and each limb), rapid hand and foot movements, rising from chair, posture, gait, postural stability and body bradykinesia. Each item is scored from 0 to 4 to indicate disorder severity (0=absent, 1=questionable, 2= mild, 3= moderate, 4= severe). Clinical parkinsonism was considered a case when any item was scored at least “mild” (a score of 2 or greater) on the UPDRS 22.

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2.4 Mechanical definitions of dyskinesia and parkinsonism (resting tremor and bradykinesia)

2.4.1 Dyskinesia using mechanical measurement

Dyskinesia was assessed mechanically by measuring force variability (FV), as indicated by the subject’s attempt to exert constant pressure on a load cell and measuring the variations in the force applied over time. Participants were asked to exert constant target pressure, first by pushing a button with the index finger of their dominant hand, then of their non-dominant hand, and finally by lifting a disposable spatula with their tongue 17. The button and spatula were connected to a load cell attached to monitor showing a real-time graph indicating target and actual force applied. The strength required to achieve the target height on the graph was set to an equivalent of 3 Newton for the index finger 24 and 0.8 Newton for the tongue 17. All participants performed each exercise 3 times for duration of 20 seconds each, separated by 5-second rest periods. The first trial was used to accustom the patient to the test. Mean data of the two subsequent measurements trials were used for analysis. The force generated was measured continuously (12 bit sampling at 2.5 kHz, digital low pass filtering, storage, and further analysis at 100 Hz) and presented graphically to the subject with virtually no delay. The average force was calculated for each 20-second test period. After subtracting this mean from the signal, it was Fourier transformed. Total power in the 0 to 3 Hz range was calculated and converted to find the standard deviation for the 0 to 3 Hz signal components. This standard deviation is technically equivalent to the one found after very sharp 3 Hz low-pass filtering of the force signal. The standard deviation was presented as the percentage of error, or coefficient of variation (CV, standard deviation divided by mean force). For dyskinesia, only force measured in the 0 to 3 Hz frequency range was used as this reflects dyskinesia best 18 and is unaffected by resting tremor (which measured at the 4 to 6 Hz frequency band) 25. This technique has been extensively validated for finger and tongue dyskinesia 17, 18. Mechanically measured dyskinesia was defined as force variability scores (in the 0 to 3 Hz frequency range) of the tongue or hands that were higher than the 95th percentile cut-point scores of the control group 16, 24.

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nism2.4.2 Parkinsonism (resting tremor and bradykinesia) using mechanical

measurement

The data generated in the preceding procedure were also used to mechanically evaluate resting tremor, by calculating the amount of variability in the force applied, with the difference that now only total force in the 4 to 6 Hz frequency range was used, as this frequency reflects resting tremor best 25 and movements in this range are unaffected by dyskinesia. Bradykinesia can be mechanically quantified by measuring the ability to adjust movement velocity to changing distances 14, 15. Participants with bradykinesia (Parkinson’s’ disease or drug induced parkinsonism) are less able to scale their movement velocity and require more time as distances increase. Velocity scaling (VS) scores are expressed as degrees per second per degree (deg/s/deg). Participants were instructed to flex a handle with their wrist as fast but as accurately as possible in order to move a flexible cursor presented on the computer screen to a target cursor located at 25 degrees and 45 degrees from the midline of the wrist flexion 14. The handle was connected to a potentiometer attached to monitor showing real-time the target and flexible cursor. Participants started with the dominant hand and then switched to the non-dominant hand and performed 32 movement measurements, consisting of 16 measurements for each of the two randomly presented target locations, for each hand, for a total of 64 movements 14. Mechanically measured parkinsonism was defined with the use of the control group. When force variability scores (in the 4 to 6 Hz frequency range) were higher or velocity scaling scores of the hands were lower than the 95th percentile cut-point scores of the control group it was considered a case of parkinsonism 16, 24.

2.5 Statistical analysis

To test differences between the groups, Student’s t-test, Mann-Whitney and Chi-square were used, depending on the type and distribution of data. Inter-rater reliability of the raters for the AIMS and the UPDRS was assessed with the Intra-class Correlations Coefficients (ICC). Data analyses were performed using SPSS 17. Because the velocity scaling test

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was not yet available at the beginning of the study, only a subset of the participants could perform this task (siblings n=30 and controls n=35).

3. Results

3.1 Demographic comparison

A total of 80 participants met the inclusion criteria, 42 nonpsychotic siblings of patients with a nonaffective psychosis and 38 controls. The siblings were comparable to the control group in regard to every demographic variable (Table 1). Inter-rater reliability of the raters for the AIMS and UPDRS corresponded to an ICC of 0.88 (p=0.01) and 0.98 (p=0.01) respectively.

3.2 Comparison of clinical assessment of movement disorders

Screening the data revealed that distributions of the AIMS and UPDRS did not met the assumptions for parametric statistics.

3.2.1 Normal mean scores and standard deviations

The normal mean scores (sd) for the AIMS and UPDRS for the sibling and control groups were respectively 0.06 (0.13) and 0.07 (0.17) for the AIMS and 0.05 (0.10) and 0.02 (0.05) for the UPDRS.

3.2.2 Dichotomous scores

Cut-point scores for clinical dyskinesia and parkinsonism based on the clinical assessment of movement disorders using the case definition of at least “mild” (a score of 2 or greater) on any of the items of the AIMS or UPDRS revealed that 3 (7%) siblings and 1 (3%) control (Fisher’s exact test 2-sided; p=0.62) met the clinical definition of dyskinesia (Table 2). Two (5%) of the siblings had an AIMS score of “mild” for hand dyskinesia and 1 (2%) sibling and 1 (3%) control had a score of “mild” for the jaw. None of the siblings or the controls met the clinical definition of parkinsonism (Table 2).

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Screening the data revealed that distributions of mechanically measured dyskinesia and velocity scaling met the assumptions for parametric statistics, but resting tremor did not.

3.3.1 Normal mean scores and standard deviations

The normal mean scores (sd) for FV and VS for the sibling and control groups were respectively 11.30% (3.51) and 10.63% (2.49) for tongue dyskinesia, 2.29% (0.88) and 1.99% (0.52) for hand dyskinesia, 0.28% (0.11) and 0.28% (0.14) for resting tremor, and 3.61 (1.00) deg/s/deg and 4.32 deg/s/deg (1.23) for bradykinesia.

3.3.2 Dichotomous scores

Cut-point scores for FV and VS based on the 95th percentile scores of the control group were 16.21% for tongue dyskinesia, 2.91% for hand dyskinesia, 0.64% for resting tremor and 2.78 deg/s/deg for bradykinesia. Based on these cut-points, dyskinesia was found in 9 (21%) siblings and 2 (5%) controls (Fisher’s exact test 2-sided; p=0.05) (table 2); 7 (17%) siblings showed hand dyskinesia compared to 1 (3%) control and 4 (10%) siblings showed tongue dyskinesia compared to 1 (3%) control. Two siblings (5%) displayed both hand and tongue dyskinesia.Parkinsonism was found in 9 (30%) siblings and 2 (6%) controls (Fisher’s exact test 2-sided; p=0.02) (table 2); 8 (27%) siblings showed bradykinesia compared to 1 (3%) control and 1 (3%) sibling and 1 (3%) control showed resting tremor. No siblings or controls exhibited both instrumentally derived tremor and bradykinesia. One subject, a sibling, did show both instrumentally derived hand dyskinesia and parkinsonism (resting tremor). The two siblings with clinically assessed “mild” dyskinesia of the hands also exhibited mechanically measured dyskinesia of the hands, which finding supports the validity of mechanical measurement of hand dyskinesia.

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4. Discussion

This study shows that nonpsychotic siblings of patients with a nonaffective psychosis display more dyskinesia and parkinsonism than comparable healthy controls. The higher prevalence was found with the use of a mechanical instrument measurement, but not with clinical assessment. Previous studies measuring clinical dyskinesia and parkinsonism in first-degree relatives of patients with schizophrenia versus controls have also reported differences in prevalence 1, although the results in individual studies never attained significance 26-31. This may be due to their reliance on clinical rating scales that are less sensitive than mechanical instrument measurement 16, 24, an argument supported by the findings in this study. Both study groups were comparable in regard to all demographic variables. Therefore, the finding of more dyskinesia and parkinsonism signs in siblings than in healthy controls is not likely to be attributable to differences in baseline characteristics. However, two siblings and one control had a concurrent mood disorder. Because a current mood disorder may be related to movement disorders 32, the data were reanalysed excluding these 3 subjects. This did not influence the results significantly. The significant difference in prevalence for mechanically measured dyskinesia and parkinsonism between siblings and controls remained (17%, p=0.05, and 23%, p=0.03, respectively, both Fisher’s exact test 2-sided). Pathogenetically, movement disorders and psychosis are both related to a dysregulated dopamine system involving the striatum 9, 10. In addition, since imaging studies have also reported striatal abnormalities in unaffected siblings 33, 34, movement disorders and by inference striatal abnormalities, may be related to an increased (genetic) risk of developing psychosis or schizophrenia. If subtle movement disorders are related to the risk of psychosis or schizophrenia, they may be useful as a premorbid symptom or as an endophenotype in screening studies. Including mechanical instrument measurement of movement disorders in screening studies could have several major advantages. First, movement disorders are objective, concrete neurological signs not biased by psychological phenomena or degree of psychopathology 16 and not subject to the potential reporting bias, experience, or subjectivity of the rater. Second, instrument assessment of movement disorders is highly reliable with reliability coefficients ranging between 0.85 and 0.98 11, 14. Third, the test takes only

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nisma few minutes and is easy to administer. However, longitudinal studies

are needed to determine the positive predictive value of the presence of subtle movement disorders in screening for psychosis. Although, mechanical measurement of movement disorders is very reliable, the additional value in a screening process of high risk subjects remains to be clarified.

Some limitations of this study should be taken into consideration. First, the results are based on a relatively small sample size. However, despite the small numbers, significant results were found and since a clear a priori hypothesis was formulated, the chance of a type I error is small. Second, we chose to dichotomize the abnormal movements instead of using the continuous data and thereby reducing the power to detect subtle motor signs with the clinical rating scales. However, we hypothesized that only a subgroup of siblings would display more abnormal movement disorders compared to controls and other siblings and that this subgroup may be of interest for follow-up. Indeed, a recent follow-up study on adolescents at risk for psychosis comparing converted and nonconverted participants at baseline showed that participants who converted to an Axis-I psychosis (e.g. schizophrenia) exhibited significantly more movement abnormalities compared to non converted 6. In addition, a supplementary post hoc analysis examining the observer based and instrumentally based scores in a continuous manner only changed the results slightly. There were still no significant differences between siblings and controls comparing the mean AIMS and UPDRS scores (Mann-Whitney z= -0.27, p=0.98 and z= -1.24, p=0.22, respectively). To compare instrumentally based scores in a continuous manner we added the individual p values using the program MetaP as different signs were used (i.e. velocity scaling for bradykinesia (deg/s/deg) and force variability for rest tremor (percentage of error, or coefficient of variation). The differences between siblings and controls comparing mechanical dyskinesia (hand dyskinesia t=-1.77, df 78, p=0.08 and tongue dyskinesia; t=-0.97, df 78, p= 0.34) and mechanical parkinsonism (bradykinesia t=-2.54, df 63, p-value 0.01 and resting tremor; z=-1.07, p=0.28) corresponded with a combined p-value of 0.06 and 0.02 respectively. This supports our hypothesis that clinical observation based rating scales are not sensitive enough to detect subtle motor signs and that our results are not a consequence of chosen statistical strategy.

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Third, the differences in mechanical assessment between siblings and controls were greater for hand dyskinesia than for tongue dyskinesia, even though orofacial dyskinesia is more prevalent than finger dyskinesia 5, 35. A possible explanation may be that the feedback loop between tongue and eye necessary to maintain a desired pressure is not as well developed in people as the feedback loop between hand and eye. Fourth, it remains possible that the movement disorders detected with mechanical instruments can be (partly) explained by other neurological dysfunctions. Neurological soft signs (and by inference cerebellar dysfunction) 6, 8, 36 also correlate with movement disorders 37, 38. However, the concurrence between the clinical and mechanical instrument assessment of movement disorders found in our study supports the validity of mechanical instrument measurement of movement disorders. Finally, the study design was cross-sectional, and therefore a conclusion about the predictive value of movement disorders for the risk of psychotic disorders cannot be made. Therefore longitudinal and larger studies are needed. In conclusion, our study shows that movement disorders are significantly more prevalent in nonpsychotic siblings of patients with a nonaffective psychosis (due to a schizophrenia spectrum disorder) than in controls when measured with mechanical instruments, but not when assessed with clinical rating scales. This suggests that motor signs could be markers of vulnerability for psychosis or schizophrenia. Since mechanical instrument measurement of movement disorders is more sensitive than assessment with clinical rating scales, it may be of value in screening programs for populations at risk for psychosis.

* (PvH = P. N. van Harten and DT = D.E. Tenback)

AcknowledgementsWe thank all participants who participated in this study and the Department of Medical Technology and Clinical Physics of the University Medical Centre Utrecht for the hard- and software provided. This work was supported by an unrestricted grant from the foundation “De Open Ankh“, the Netherlands.

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nismTable 1. Demographic and clinical characteristics of nonpsychotic siblings of patients with a non-

affective psychosis and of healthy controls

Table 2. Prevalence of movement disorders in nonpsychotic siblings of patients with a nonaffective psychosis and healthy controls, as found in clinical and mechanical instrument assessments

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Table 1. Demographic and clinical characteristics of nonpsychotic siblings of patients with a non-affective psychosis and of healthy controls

Siblings

(N=42)

Controls

(N=38)

Siblings versus

Controls

Mean (SD)

Mean (SD)

p-value1

Age

Years

27.2 (7.1)

26.4 (9.3)

0.69

Education

Years

13.7 (2.1)

14.1 (1.8)

0.32

% (N)

% (N)

p-value2

Gender

Male

50 (21)

53 (20)

0.83

Ethnicity

Caucasian

100 (42)

95 (36)

0.22

Handedness

Right

90 (38)

90 (34)

1.00

Diagnosis

Mood disorders

12 (5)*

5 (2) #

0.44

1 Student’s T-test,

2 Fisher’s exact test.

* N=3 Major depressive disorders (MDD) in full remission, N=1 MDD NOS, N=1 adjustment disorder #

N=1 MDD in full remission, N=1 bereavement, N=number of subjects with that mood disorder


Siblings

(N=42)

Controls

(N=38)

Siblings

versus

Controls

% (N) % (N) p-value1

Dyskinesia prevalence

Clinical assessment (AIMS item score ≥ 2)

Mechanical measurement (using FV)

7 (3)

21 (9)

3 (1)

5 (2)

0.62

0.05

Parkinsonism prevalence

Clinical assessment (UPDRS item score ≥ 2)

Mechanical measurement resting tremor (using FV)

Mechanical measurement bradykinesia (using VSa)

Mechanical measurement (using FV and VS

a)

0 (0)

2 (1)

27a (8)

30a (9)

0 (0)

3 (1)

3a (1)

6a (2)

1.00

1.00

0.01

0.02

1 Fisher’s exact test 2-sided. FV: Force Variability. VS: Velocity Scaling.

a Mechanical measurement using VS was only performed in 30 siblings and 35 controls (see methods section)

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Table 1. Demographic and clinical characteristics of nonpsychotic siblings of patients with a non-affective psychosis and of healthy controls

Siblings

(N=42)

Controls

(N=38)

Siblings versus

Controls

Mean (SD)

Mean (SD)

p-value1

Age

Years

27.2 (7.1)

26.4 (9.3)

0.69

Education

Years

13.7 (2.1)

14.1 (1.8)

0.32

% (N)

% (N)

p-value2

Gender

Male

50 (21)

53 (20)

0.83

Ethnicity

Caucasian

100 (42)

95 (36)

0.22

Handedness

Right

90 (38)

90 (34)

1.00

Diagnosis

Mood disorders

12 (5)*

5 (2) #

0.44

1 Student’s T-test,

2 Fisher’s exact test.

* N=3 Major depressive disorders (MDD) in full remission, N=1 MDD NOS, N=1 adjustment disorder #

N=1 MDD in full remission, N=1 bereavement, N=number of subjects with that mood disorder


Siblings

(N=42)

Controls

(N=38)

Siblings

versus

Controls

% (N) % (N) p-value1

Dyskinesia prevalence

Clinical assessment (AIMS item score ≥ 2)

Mechanical measurement (using FV)

7 (3)

21 (9)

3 (1)

5 (2)

0.62

0.05

Parkinsonism prevalence

Clinical assessment (UPDRS item score ≥ 2)

Mechanical measurement resting tremor (using FV)

Mechanical measurement bradykinesia (using VSa)

Mechanical measurement (using FV and VS

a)

0 (0)

2 (1)

27a (8)

30a (9)

0 (0)

3 (1)

3a (1)

6a (2)

1.00

1.00

0.01

0.02

1 Fisher’s exact test 2-sided. FV: Force Variability. VS: Velocity Scaling.

a Mechanical measurement using VS was only performed in 30 siblings and 35 controls (see methods section)

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References

1. Koning JP, Tenback DE, van Os J, Aleman A, Kahn RS, van Harten PN. Dyskinesia and parkinsonism in antipsychotic-naive patients with schizophrenia, first-degree relatives and healthy controls: a meta-analysis. Schizophr Bull Jul 2010;36(4):723-731.


3. Pappa S, Dazzan P. Spontaneous movement disorders in antipsychotic-naive patients with first-episode psychoses: a systematic review. Psychol Med Jul 2009;39(7):1065-1076.

4. van Harten PN, Tenback DE. Letter to the Editor: Movement disorders should be a criterion for schizophrenia in DSM-V. Psychol Med Jul 17 2009:1-3.





9. Kestler LP, Walker E, Vega EM. Dopamine receptors in the brains of schizophrenia patients: a meta-analysis of the findings. Behav Pharmacol Sep 2001;12(5):355-371.






15. Caligiuri MP, Teulings HL, Filoteo JV, Song D, Lohr JB. Quantitative measurement of handwriting in the assessment of drug-induced parkinsonism. Hum Mov Sci Oct 2006;25(4-5):510-522.


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nism17. Koning JP, Tenback DE, Kahn RS, Van Schelven LJ, Van Harten PN. Instrument

measurement of lingual force variability reflects tardive tongue dyskinesia. J Med Eng Technol 2010;34(1):71-77.


19. Damsa C, Bumb A, Bianchi-Demicheli F, Vidailhet P, Sterck R, Andreoli A, Beyenburg S. “Dopamine-dependent” side effects of selective serotonin reuptake inhibitors: a clinical review. J Clin Psychiatry Aug 2004;65(8):1064-1068.

20. Potvin S, Blanchet P, Stip E. Substance abuse is associated with increased extrapyramidal symptoms in schizophrenia: A meta-analysis. Schizophr Res Jul 14 2009;113:181-188.






26. Appels MC, Sitskoorn MM, de Boo M, Klumpers UM, Kemps A, Elderson A, Kahn RS. Neurological signs in parents of schizophrenic patients. Neuroreport Apr 16 2002;13(5):575-579.

27. Chen YL, Chen YH, Mak FL. Soft neurological signs in schizophrenic patients and their nonpsychotic siblings. J Nerv Ment Dis Feb 2000;188(2):84-89.


29. Ismail B, Cantor-Graae E, McNeil TF. Neurodevelopmental origins of tardivelike dyskinesia in schizophrenia patients and their siblings. Schizophr Bull 2001;27(4):629-641.

30. McCreadie RG, Thara R, Kamath S, Padmavathy R, Latha S, Mathrubootham N, Menon MS. Abnormal movements in never-medicated Indian patients with schizophrenia. Br J Psychiatry Feb 1996;168(2):221-226.

31. Tarbox SI, Pogue-Geile MF. Spontaneous dyskinesia and familial liability to schizophrenia. Schizophr Res Jan 31 2006;81(2-3):125-137.

32. Fenton WS, Blyler CR, Wyatt RJ, McGlashan TH. Prevalence of spontaneous dyskinesia in schizophrenic and non-schizophrenic psychiatric patients. Br J Psychiatry Sep 1997;171:265-268.

33. Vink M, Ramsey NF, Raemaekers M, Kahn RS. Striatal dysfunction in schizophrenia and unaffected relatives. Biol Psychiatry Jul 1 2006;60(1):32-39.

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35. McCreadie RG, Srinivasan TN, Padmavati R, Thara R. Extrapyramidal symptoms in unmedicated schizophrenia. J Psychiatr Res May 2005;39(3):261-266.

36. Ho BC, Mola C, Andreasen NC. Cerebellar dysfunction in neuroleptic naive schizophrenia patients: clinical, cognitive, and neuroanatomic correlates of cerebellar neurologic signs. Biol Psychiatry Jun 15 2004;55(12):1146-1153.

37. King DJ, Wilson A, Cooper SJ, Waddington JL. The clinical correlates of neurological soft signs in chronic schizophrenia. Br J Psychiatry Jun 1991;158:770-775.


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Part IV

Summary and general discussion

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Part I Introduction

Part I provides a general introduction to schizophrenia and movement disorders and the outline of this thesis.

Part II Movement disorders in patients with schizophrenia and in their siblings

Part II, 2.1 describes the meta-analysis we conducted to determine i) whether movement disorders are associated with antipsychotic-naïve patients with schizophrenia and ii) to what extent they are associated with healthy first-degree relatives of persons with schizophrenia as compared to controls. We systematically searched the Medline, EMBASE, and PsychINFO databases to identify studies reporting on dyskinesia and parkinsonism in antipsychotic-naive patients with schizophrenia (n=213) and controls (n=242) and separately in non-ill first-degree relatives (n=395) and controls (n=379). Effect sizes were pooled using random effect models to calculate odds ratios (ORs) to compare the risk of these movement disorders among patients and healthy relatives each to matched controls. We found that antipsychotic-naïve schizophrenia was strongly associated with dyskinesia (OR: 3.59; 95% CI: 1.53-8.41) and parkinsonism (OR: 5.32; 95% CI: 1.75-16.23) compared to controls. Dyskinesia and parkinsonism were also more prevalent in healthy first-degree relatives of patients with schizophrenia as compared to healthy controls (for dyskinesia, OR: 1.38; 95% CI: 1.06-1.81 and for parkinsonism, OR: 1.37; 95% CI: 1.05-1.79). The results suggest that movement disorders, and by inference abnormalities in the nigrostriatal pathway, are not only associated with schizophrenia itself, but may also be related to the (genetic) risk of developing the disease.

In Part II, 2.2 we examined in a clinical study whether movement disorders are more present in unaffected siblings of patients with schizophrenia than in controls and whether they cluster with schizotypy, another sign of vulnerability for schizophrenia. In a cross-sectional study design the prevalence and interrelationship of movement disorders and schizotypy were assessed in 115 unaffected siblings (mean age 27 years,

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44% males) and in 100 healthy controls (mean age 26 years, 51% males). Movement disorders were measured with the Abnormal Involuntary Movement Scale (AIMS), Unified Parkinson Disease Rating Scale (UPDRS), the Barnes Akathisia Rating Scale (BARS), and one separate item for dystonia. Schizotypy was assessed with the Structured Interview for Schizotypy-revised (SIS-R). There were significant differences in the prevalence of movement disorders in unaffected siblings versus healthy controls (10% versus 1%, p<0.01) but not in the prevalence of schizotypy. Unaffected siblings with a movement disorder displayed significantly more positive and total schizotypy (p=0.02 and p=0.03 respectively) than those without. In addition, dyskinesia correlated with positive schizotypy (r=0.51, p=0.02). In conclusion, our results indicate that movement disorders are more prevalent in unaffected siblings of patients with schizophrenia as compared to controls. In addition the association between movement disorders (dyskinesia in particular) with positive (and total) schizotypy in unaffected siblings suggests that certain vulnerability factors for psychosis or schizophrenia cluster.

In Part II, 2.3 we investigated whether there is a genetic vulnerability of antipsychotic-induced movement disorders in patients with schizophrenia. In a cross-sectional study we examined whether we could replicate previously reported associations in candidate genes for acute and tardive antipsychotic-induced movement disorders (MD) in a young Caucasian sample. In 402 patients (median age 26 years) a total of 13 polymorphisms were genotyped in 8 dopamine-related candidate genes selected a priori from the literature (regarding dopamine and serotonin receptors, dopamine degradation, and free radicals scavenging enzymes pathways). Patients with movement disorders used on average a higher haloperidol dose equivalent, when compared to those without movement disorders. Prevalence of movement disorders was high and did not differ between first generation antipsychotics and second generation antipsychotics. Significant associations were found between (i) the TaqI_D polymorphism and akathisia (OR=2.3, p=0.001 for each extra C- allele) and (ii) the -141C polymorphism and tardive dyskinesia (OR=0.20 for each extra Del allele, p = 0.001), both DRD2 gene polymorphisms. The other polymorphisms were not significantly associated with a movement disorder.

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TaqI_D was associated with akathisia (previously reported with tardive dyskinesia) and the -141C with tardive dyskinesia (previously reported with acute parkinsonism). These results suggest that the contribution of these DRD2 gene variants in vulnerability for antipsychotic-induced movement disorders takes place in a more general or pleiotropic way.

Part III Mechanical measurement of dyskinesia and parkinsonism

In Part III, 3.1 we examined in a cross-sectional study whether mechanical measurement of lingual force variability reflects tardive tongue dyskinesia. Instrument measurement of lingual force variability was compared to the clinical level of tardive tongue dyskinesia and total body dyskinesia as measured by the AIMS in 35 subjects, 23 patients with a psychiatric disorder on antipsychotics, of whom 11 with and 12 without tardive tongue dyskinesia, and 12 age- and gender-matched healthy controls. Lingual force variability correlated with tardive tongue dyskinesia (Spearman r = 0.56, p <0.01) and with total dyskinesia (r = 0.47, p =0.02); there was no association with age, antipsychotic dose, or psychiatric diagnosis. Instrument test-retest reliability corresponded with an ICC of 0.85, p < 0.0001. Based on these results we suggest that instrument measurement of lingual force variability may be a valid and reliable method for assessing tardive tongue dyskinesia.

Part III, 3.2. Since previous studies suggest that siblings of patients with schizophrenia have subtle forms of movement disorders more often than controls, we compared cross-sectionally the presence and severity of dyskinesia and parkinsonism in 42 nonpsychotic siblings of patients with nonaffective psychosis and in 38 controls as measured by mechanical instruments and clinical rating scales. There were no significant differences in movement disorders between siblings and controls on the basis of clinical assessments. However, mechanical measurements indicated that siblings compared to controls displayed significantly more dyskinetic and parkinsonian signs. In conclusion, our study suggests that motor signs are more present in nonpsychotic siblings of patients with schizophrenia compared to controls. In addition this study shows that mechanical instrument

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measurement of movement disorders is more sensitive than assessment with clinical rating scales.

4.2 General discussion

Part I. Outline

This thesis focuses on several aspects of movement disorders in patients with schizophrenia and in their unaffected siblings. The main hypothesis is that movement disorders are not just side effects of antipsychotic medication but may also be symptoms of the illness itself and are related to the (genetic) risk of developing the disease.

To address these questions a systematic literature search (Part II, 2.1) was followed by a clinical prevalence and association study of movement disorders with schizotypy in siblings of patients with schizophrenia (Part II, 2.2), and a candidate gene study of movement disorders in patients using antipsychotic medication (Part II, 2.3). Further, we developed a mechanical instrument and examined whether mechanical measurement of lingual force variability reflects tardive tongue dyskinesia (Part III, 3.1) and whether mechanical measurement of movement disorders in siblings of patients with schizophrenia is more sensitive than clinical rating scales (Part III, 3.2).

Part II. Movement disorders in patients with schizophrenia and in their siblings

This thesis suggests that movement disorders are associated to antipsychotic naïve patients with schizophrenia and are also more prevalent in their unaffected siblings compared to controls. This could imply that movement disorders represent symptoms of schizophrenia and may be markers of vulnerability of developing the disease. The finding that movement disorders are associated with antipsychotic naïve schizophrenia is pathophysiologically and clinically relevant. Schizophrenia is probably heterogeneous in regard to phenomenology and pathophysiology 1, 2; and patients with movement disorders may constitute a subgroup within schizophrenia, i.e. characterised by distinct nigrostriatal dysfunction. This finding is clinically relevant, as the

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poorer outcome of schizophrenia 3-6. The reported association between patients with movement disorders and two D2 dopamine receptor (DRD2) polymorphisms in the candidate gene study may be of clinical relevance as the subgroup of patients with movement disorders did use on average a higher antipsychotic dosage, than those without movement disorders. It could be that these genes that are associated with a higher risk for movement disorders, are also related to a more severe expression of schizophrenia 6. However other explanations are also possible such as an increased risk for movement disorders caused by a higher dosage of antipsychotics. A prospective study may shed more light on this relationship. In the meta-analysis we also found evidence that first-degree relatives (mainly siblings) display significantly more movement disorders than controls. This finding was bolstered by our clinical studies, in which we found that there is a subgroup of unaffected siblings of patients with schizophrenia who also display more movement disorders than controls. Higher rates of movement disorders could be of pathophysiological interest because movement disorders may serve as an intermediate phenotype (endophenotype); these findings may facilitate further genetic research into the origin of schizophrenia or psychotic disorders 7. Further, an association between movement disorders, in particular dyskinetic movements, with positive schizotypy in unaffected siblings has not been reported before. This is of both theoretical and clinical relevance. Theoretically, because it would stress that dopamine-related vulnerability factors for psychosis or schizophrenia could cluster in a subgroup of subjects. Clinically, it could be of use in early detection because in contrast to psychotic symptoms, movement disorders can be measured reliably and objectively. Recent prospective studies, that included adolescents with schizotypal personality disorders, support the predictive value of dyskinetic movements for a psychotic disorder such as schizophrenia 8, 9.

Part III Mechanical measurement of dyskinesia and parkinsonism

To explore more sensitive and reliable methods for measuring movement disorders, we constructed an instrument to mechanically assess dyskinesia and parkinsonism. We found that mechanical measurement of lingual dyskinesia using force variability reflects tardive tongue

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dyskinesia. In addition the results of this thesis indicate that in siblings of patients with schizophrenia, mechanical instruments may also be more sensitive for detecting subclinical movement disorders than traditional clinician-based rating scales. The use of mechanical measurement of movement disorders in schizophrenia research, and in screening studies for a psychotic disorder in particular, could have additional advantages. Firstly, mechanical measurement is not subject to the potential reporting bias, experience, or subjectivity of the rater and it is highly reliable with inter and intra rater coefficients ranging between 0.85 and 0.98 10, 11. Secondly, contrary to clinician-based ratings, mechanical measurements of the severity of movement disorders are linear. Thirdly, the test takes only a few minutes, is easy to administer.

Methodological considerations

When interpreting the results of this thesis, some methodological considerations should be taken into account. We used a cross-sectional design for all studies and therefore no conclusions can be made about the predictive value of the reported associations. For example in the meta-analysis (Part II, 2.1) we found that movement disorders are associated with the illness schizophrenia but we do not know whether these movement disorders are progressive and possibly associated with poorer outcome, a caveat which has been suggested previously 3-6. In addition, finding an association between movement disorders (dyskinesia in particular) and (positive) schizotypy in a subgroup of unaffected siblings (Part II, 2.2) could be clinically important, if it were to facilitate the identification of subjects at risk for psychosis. However, it remains to be determined whether these “siblings at risk” actually develop psychosis or, in the absence of other (environmental) risk factors such as cannabis use 12, do not develop a psychotic disorder. The same is true for a subgroup of siblings that displays more mechanically measured movement disorders compared to the other siblings and controls (Part III, 3.2). In the candidate gene study (Part II, 2.3) we suggest a more pleiotropic effect, where involvement of genetic variants in the DRD2 gene may lead to multiple phenotypic traits of antipsychotic-induced MD, which are pathophysiologically related to each other, albeit with a differential clinical expression. However, prospective studies are needed to confirm this hypothesis.

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sion Another limitation that must be addressed concerns the diversity in

rating methods for movement disorders. This concerns both clinician-based rating scales as well as mechanical instruments. In the meta-analysis (Part II, 2.1) this could be resolved by the use of pooled odds ratios as a measure of standardized mean difference, which produce results independent of scale and range. In the clinical studies (Part II, 2.2, 2.3 and Part III, 3.1, 3.2) we could overcome this limitation by applying similar clinician-based rating scales and cut-off points (AIMS for dyskinesia, UPDRS for parkinsonism, BARS for akathisia and one item for dystonia). However, mechanical instruments assess movement disorders differently than clinician-based ratings scales, both in method and range of body parts. For example, while the clinical ratings evaluated a broad spectrum of movement disorders, mechanical instruments only assess specific aspects of movement disorders (hands and tongue). Furthermore, mechanical instruments measure severity in a linear way, whereas clinical rating scales use anchor points describing severity in terms of duration and amplitude. Therefore, a rating of 4 versus 2 on the AIMS or the UPDRS does not necessarily indicate that the dyskinesia or parkinsonism are twice as severe, whereas an instrumental measurement of 4 versus 2 on force stability or velocity scaling objectively denotes a doubling of severity 13. Of clinical value is the validity of mechanical measurement. In what extent does mechanical quantification, using force variability, measures dyskinesia and/or tremor (figure 3 and 4) and does velocity scaling measures bradykinesia (Figures 5 and 6)? Mechanical measurement of tremor at one finger of each hand has a high degree of face validity as it quantifies the oscillations of the typical frequency range of rest tremor and most tremors occur at the hands. This method has been validated extensively 14-17. Bradykinesia is closely related to velocity scaling. Several studies show that the relationship between peak velocity and target distance reflects the extent of bradykinesia 11, 18, 19. Mechanical measurement of force variability integrates both aspects of dyskinesia; the durational component and the amplitude of the abnormal movements. On the other hand, the mechanical measurement of force variability by means of sustained control of isometric force is not similar to the clinical description of tardive dyskinesia. However, force variability scores of the finger are highly correlated with hand AIMS score (r=0.73; p=0.01) 10. For lingual force variability we report a more moderate correlation with tongue AIMS score (r=0.56; p<0.01) (Part III, 3.1).

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Another important question remains the specificity of movement disorders for schizophrenia. Dyskinesia has in a lesser extent also been reported in neuroleptic-naive patients with a schizoaffective, bipolar, unipolar, and borderline personality disorder 20 and in some healthy controls (see our meta-analysis, Part II, 2.1, and clinical studies, Part II, 2.2 and Part III, 3.2). In the same vein, motor retardation is also a common feature of a major depressive disorder 21, 22. The clinical studies in this thesis were not designed to evaluate movement disorders in other psychiatric disorders. However, combining our results with the available literature suggests that dyskinetic movement disorders are associated with the development of a psychotic disorder in general and probably schizophrenia in particular. Indeed, it has been reported that the presence of baseline movement abnormalities in high-risk individuals with schizotypal symptoms differentiates those who eventually convert to an Axis-I psychosis (schizophrenia, schizoaffective, bipolar disorders, and depression with psychotic features) 8. This is in line with our finding of an association (cross-sectional design) between dyskinetic movements with the degree of positive schizotypy in unaffected siblings, who have an increased genetic risk of developing a psychotic disorder (Part II, 2.2).

Directions for future research

Screening for movement disorders in individuals with a high risk for a psychotic disorder

One of the main objectives of the GROUP (Genetic Risk and Outcome Psychosis) program is to test vulnerability and protective factors for i) developing a psychotic disorder and ii) variations over the course of the disorder. Interestingly, movement disorders have been associated with poorer outcome in patients with schizophrenia 3-6. In addition, movement disorders may be also signs of vulnerability for developing a psychotic disorder, as they have been reported in subjects with an increased (genetic) risk of developing the disease 8, 9. This observation could be of great clinical value as to date the majority (>65%) of the ultra-high-risk youth (with mainly positive subclinical symptoms) who meet the current criterion for the prodromal phase does not develop an Axis 1 psychotic disorder 9, 23. It has thus been suggested that introducing ‘the psychosis risk syndrome’ in the DSM-V may be premature, since it is not specific enough 24. Further prospective studies are therefore needed to examine

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(dyskinetic) movement disorders and (positive) schizotypy are more at risk for developing a psychotic disorder than siblings with only one of these vulnerability factors. This could increase the specificity of the identification of new groups at genuinely high risk for psychosis.

Implementation of mechanical measurements of movement disorders

Another important issue in psychiatry research is a valid, reliable, sensitive, and objective assessment of symptoms. Movement disorders are objective, concrete neurological signs not biased by psychological phenomena or degree of psychopathology 25 and not subject to the potential reporting bias, experience, or subjectivity of the rater. In addition, this thesis clearly shows that mechanical measurement is in other aspects superior to clinical based rating scales. However mechanical assessment has not gained wide appeal in clinical or research settings in psychiatry. We suggest that mechanical measurement of (dyskinetic) movement disorders should be of particular interest in screening programs for psychosis risk because mechanical instruments have proven to be more sensitive in detecting subclinical movement disorders objectively and are very reliable. Finally, mechanical measurement of movement disorders using velocity scaling may also be of value in clinical practice. For example, mechanical measurement of bradykinesia could be of clinical value in patients using antipsychotics, if mechanical measurement using velocity scaling correlated with the degree of D2 receptor occupancy. If mechanically measured subclinical bradykinesia equals a D2 receptor occupancy between 70 and 80%, than this would offer clinicians a tool for more refined pharmacotherapy of individualized dosage finding 26.

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References



3. Ascher-Svanum H, Zhu B, Faries D, Peng X, Kinon BJ, Tohen M. Tardive Dyskinesia and the 3-Year Course of Schizophrenia: Results From a Large, Prospective, Naturalistic Study. J Clin Psychiatry Jun 24 2008:e1-e9.









12. van Os J, Kapur S. Schizophrenia. Lancet Aug 22 2009;374(9690):635-645.13. Dean CE, Russell JM, Kuskowski MA, Caligiuri MP, Nugent SM. Clinical rating

scales and instruments: how do they compare in assessing abnormal, involuntary movements? J Clin Psychopharmacol Jun 2004;24(3):298-304.

14. Homberg V, Reiners K, Hefter H, Freund HJ. The muscle activity spectrum: spectral analysis of muscle force as an estimator of overall motor unit activity. Electroencephalogr Clin Neurophysiol Mar 1986;63(3):209-222.

15. Joyce GC, Rack PM. The effects of load and force on tremor at the normal human elbow joint. J Physiol Jul 1974;240(2):375-396.

16. Matthews PB, Muir RB. Comparison of electromyogram spectra with force spectra during human elbow tremor. J Physiol May 1980;302:427-441.


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sion18. Benecke R. The pathophysiology of Parkinson’s disease. In: Quinn NP, Jenner PG,

eds. Movement disorders. San Diego: Academic Press; 1989:59-72.19. Berardelli A, Dick JP, Rothwell JC, Day BL, Marsden CD. Scaling of the size of

the first agonist EMG burst during rapid wrist movements in patients with Parkinson’s disease. J Neurol Neurosurg Psychiatry Nov 1986;49(11):1273-1279.

20. Fenton WS, Blyler CR, Wyatt RJ, McGlashan TH. Prevalence of spontaneous dyskinesia in schizophrenic and non-schizophrenic psychiatric patients. Br J Psychiatry Sep 1997;171:265-268.

21. Caligiuri MP, Ellwanger J. Motor and cognitive aspects of motor retardation in depression. J Affect Disord Jan-Mar 2000;57(1-3):83-93.

22. Chong SA, Subramaniam M, Verma S. Spontaneous parkinsonism in antipsychotic-naive patients with first-episode psychosis. Can J Psychiatry Jun 2005;50(7):429-431.


24. Carpenter WT. Anticipating DSM-V: should psychosis risk become a diagnostic class? Schizophr Bull Sep 2009;35(5):841-843.


26. Fitzgerald PB, Kapur S, Caligiuri MP, Jones C, Silvestri S, Remington G, Zipursky RB. Instrumentally detected changes in motor functioning in patients with low levels of antipsychotic dopamine D2 blockade. Neuropsychopharmacology Jan 2000;22(1):19-26.

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gSummary in Dutch / Nederlandse Samenvatting

Deel I Inleiding

Deel I geeft een algemene inleiding over schizofrenie en bewegings-stoornissen en beschrijft het doel en de opzet van dit proefschrift.

De belangrijkste hypothese is dat bewegingsstoornissen bij schizofrenie niet alleen bijwerkingen zijn van antipsychotica, maar mogelijk ook symptomen van de ziekte zelf en markers van kwetsbaarheid voor de ontwikkeling van deze aandoening.

Deel II Bewegingsstoornissen bij patiënten met schizofrenie en hun broers en zussen

Deel II, 2.1 beschrijft de meta-analyse die we hebben uitgevoerd om te bepalen in welke mate bewegingsstoornissen geassocieerd zijn met i) antipsychotica naïeve patiënten met schizofrenie en ii) met gezonde eerstegraads familieleden van patiënten met schizofrenie. Hiertoe doorzochten we de Medline, EMBASE en PsychINFO databases op relevante studies die dyskinesie en parkinsonisme analyseerden in antipsychotica naïeve patiënten met schizofrenie (n=213) en gezonde controles (n=242) en afzonderlijk in gezonde eerstegraads familieleden (n=395) en gezonde controles (n=379). Effect sizes werden samengevoegd om odds ratio’s (OR’s) te berekenen. Dyskinesie en parkinsonisme kwamen vaker voor bij antipsychotica naïeve patiënten met schizofrenie in vergelijking met controles (voor dyskinesie, OR: 3.59; 95% BI: 1.53-8.41 en voor parkinsonisme, OR: 5.32; 95% BI: 1.75-16.23). Dyskinesie en parkinsonisme kwamen ook vaker voor bij gezonde eerstegraads familieleden van patiënten met schizofrenie in vergelijking met controles (voor dyskinesie, OR: 1.38; 95% BI: 1.06-1.81 en voor parkinsonisme, OR: 1.37; 95% BI: 1.05-1.79). De resultaten suggereren dat bewegingsstoornissen, en dus waarschijnlijk afwijkingen in het nigrostriatale systeem, niet alleen geassocieerd zijn met schizofrenie zelf, maar mogelijk ook met het (genetische) risico om de ziekte te ontwikkelen.

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In deel II, 2.2 hebben we onderzocht of bewegingsstoornissen meer aanwezig zijn bij niet psychotische broers en zussen van patiënten met schizofrenie dan bij gezonde controles en of ze clusteren met schizotypie, een ander teken van kwetsbaarheid voor het ontwikkelen van schizofrenie. In een cross-sectionele studie werden de prevalentie en de onderlinge samenhang van bewegingsstoornissen en schizotypische kenmerken onderzocht in 115 niet psychotische broers en zussen (gemiddelde leeftijd 27 jaar, 44% mannen) en in 100 gezonde controles (gemiddelde leeftijd 26 jaar, 51% mannen). Bewegingsstoornissen werden gemeten met de Abnormal Involuntary Movement Scale (AIMS), Unified Parkinson Disease Rating Scale (UPDRS), de Barnes Acathisia Rating Scale (BARS), en een apart item voor dystonie. Schizotypische kenmerken werden gemeten met de Structured Interview for Schizotypy-revised (SIS-R). Er waren significante verschillen in prevalentie van bewegingsstoornissen bij niet psychotische broers en zussen versus gezonde controles (10% versus 1%, p <0.01), maar niet in de prevalentie van schizotypische kenmerken. Niet psychotische broers en zussen met een bewegingsstoornis hadden aanzienlijk hogere scores op de positieve en de totale schizotypie schaal (p = 0.02 en p = 0.03 respectievelijk) dan niet psychotische broers en zussen zonder bewegingsstoornissen. Daarnaast was dyskinesie specifiek gecorreleerd met positieve schizotypie (r = 0.51, p = 0.02). Onze resultaten wijzen erop dat bewegingsstoornissen vaker voorkomen bij niet psychotische broers en zussen van patiënten met schizofrenie in vergelijking met controles. Daarnaast is er een associatie gevonden tussen bewegingsstoornissen en schizotypische kenmerken bij niet psychotische broers en zussen. Dit doet vermoeden dat bepaalde kwetsbaarheidfactoren voor het ontwikkelen van een psychose of schizofrenie clusteren.

In deel II, 2.3 onderzochten we of er een genetische kwetsbaarheid is voor antipsychotica geïnduceerde bewegingsstoornissen bij patiënten met schizofrenie. In een cross-sectionele studie met Kaukasische patiënten probeerden we eerdere associaties tussen kandidaat-genen en acute en tardieve bewegingsstoornissen te repliceren. Bij 402 patiënten (gemiddelde leeftijd 26 jaar) genotypeerden we in totaal 13 polymorfismes in 8 dopamine-gerelateerde kandidaat-genen (met betrekking tot dopamine en serotonine-receptoren, dopamine afbraak, en enzymen die vrije radicalen opruimen).

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gPatiënten met bewegingsstoornissen gebruikten gemiddeld een hogere dosis haloperidol equivalent dan patiënten zonder bewegingsstoornissen. De prevalentie van de bewegingstoornissen was hoog en verschilde niet tussen de eerste generatie antipsychotica en tweede generatie antipsychotica. Er werden significante associaties gevonden tussen (i) de TaqI_D polymorfisme en acathisie (OR = 2.3, p = 0.001 voor elke extra C-allel) en (ii) de -141C polymorfisme en tardieve dyskinesie (OR = 0.20 voor elk extra Del allel, p = 0.001), beide DRD2 gen polymorfismes. De andere polymorfismes waren niet significant geassocieerd met een bewegingsstoornis. Interessant genoeg was de TaqI_D polymorfisme eerder geassocieerd met tardieve dyskinesie en de-141C polymorfisme eerder met acute parkinsonisme. Deze resultaten suggereren een meer algemene of pleiotrope bijdrage van DRD2 genvarianten voor antipsychotica geïnduceerde bewegingsstoornissen.

Deel III Mechanisch meten van dyskinesie en parkinsonisme

In deel III, 3.1 hebben we in een cross-sectionele studie onderzocht of mechanisch meten van de variabiliteit van de tongkracht overeenkomt met klinische tardieve tong dyskinesie. De mechanisch gemeten variabiliteit van de tongkracht werd vergeleken met de mate van tardieve tong dyskinesie en met totale dyskinesie zoals gemeten met de Abnormal Involuntary Movement Scale (AIMS). In totaal werden 35 personen in deze studie geïncludeerd; 23 patiënten met een psychiatrische stoornis die antipsychotica gebruikten, van wie er 11 met en 12 zonder tardieve tong dyskinesie en 12 gezonde controles, gematched op leeftijd en geslacht. Variabiliteit van de tongkracht correleerde met tardieve tong dyskinesie (Spearman r = 0.56, p <0.01) en met totale dyskinesie (r = 0.47, p = 0.02). Er was geen verband met leeftijd, dosis antipsychotica of psychiatrische diagnose. De instrumentele test-hertest betrouwbaarheid kwam overeen met een ICC van 0.85, p <0.0001. Op basis van deze resultaten concluderen we dat mechanisch meten van de variabiliteit van de tongkracht een valide en betrouwbare methode is voor het registeren van tardieve dyskinesie van de tong.

Uit eerdere studies komt naar voren dat niet psychotische broers en zussen van patiënten met schizofrenie meer subtiele vormen van bewegingsstoornissen hebben dan controles. In deel III, 3.2 vergeleken

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we in een cross-sectionele studie de aanwezigheid en de ernst van dyskinesie en parkinsonisme bij 42 niet psychotische broers en zussen van patiënten met een niet-affectieve psychose en bij 38 controles, gemeten met mechanische meetinstrumenten en klinische observatieschalen. Op basis van de klinische observatieschalen werden er geen significante verschillen gevonden in bewegingstoornissen tussen broers en zussen versus controles. Echter, op basis van de mechanische metingen bleek dat niet psychotische broers en zussen in vergelijking met controles significant meer symptomen van dyskinesie en parkinsonisme hadden. Onze studie suggereert dat motorische symptomen meer aanwezig zijn bij niet psychotische broers en zussen van patiënten met schizofrenie in vergelijking met gezonde controles. Bovendien toont deze studie aan dat mechanisch meten van bewegingsstoornissen gevoeliger is dan meten met klinische observatie schalen.

Deel IV Algemene discussie

De resultaten van dit proefschrift suggereren dat bewegingsstoornissen bij schizofrenie niet alleen bijwerkingen zijn van antipsychotica, maar mogelijk ook symptomen van de ziekte zelf en markers van kwetsbaarheid voor de ontwikkeling van deze aandoening. Daarnaast werd er een instrument ontwikkeld voor het mechanisch meten van dyskinesie, rusttremor en bradykinesie. Mechanisch meten bleek, zoals verwacht, een meer gevoelige en betrouwbare methode in vergelijking met de gangbare klinische observatie schalen.

Methodologische overwegingen

Bij de interpretatie van onze resultaten moeten enkele methodologische overwegingen in ogenschouw worden genomen. Zo waren de studies cross-sectioneel en kunnen er derhalve geen conclusies worden getrokken omtrent de voorspellende waarde van de gevonden resultaten. Daarnaast werden er verschillende meetmethodes naast elkaar gebruikt. De vraag blijft in hoeverre de data van de mechanische metingen exact 1 op 1 vertaald kunnen worden naar de klinische bewegingsstoornissen. Ten slotte het punt van de specificiteit van bewegingsstoornissen voor schizofrenie. Zo blijkt uit de literatuur dat bijvoorbeeld dyskinesie in mindere mate ook voorkomt bij andere psychotische stoornissen. De studies in dit proefschrift hebben zich voornamelijk geconcentreerd op

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ghet ziektebeeld schizofrenie. Wanneer we onze resultaten combineren met de beschikbare literatuur lijkt het erop dat dyskinesie geassocieerd is met de ontwikkeling van een psychotische stoornis in het algemeen en waarschijnlijk met schizofrenie in het bijzonder.

Suggesties voor toekomstig onderzoek

Mochten prospectieve studies bevestigen dat bewegingstoornissen inderdaad een marker van kwetsbaarheid zijn voor het ontwikkelen van schizofrenie of een psychotische stoornis, dan zouden personen met een verhoogd risico op het ontwikkelen van een psychose ook gescreend kunnen worden op bewegingsstoornissen. Mogelijk dat bewegingsstoornissen in combinatie met andere kwetsbaarheidfactoren voor de ontwikkeling van schizofrenie (bv. schizotypie) de specificiteit van identificatie voor een eerste psychose kan vergroten.

Daarnaast willen we voorstellen om in wetenschappelijk onderzoek naar bewegingsstoornissen bij schizofrenie meer gebruik te gaan maken van mechanische registratie. Het is belangrijk om symptomen op een objectieve, valide, betrouwbare en sensitieve wijze te kunnen registeren, met name in de psychiatrie.

Tenslotte zou mechanische registratie van bradykinesie van klinisch belang kunnen zijn voor patiënten die antipsychotica gebruiken, mocht de mate van mechanische gemeten bradykinesie samenhangen met de mate van de D2 receptor bezetting.

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listPublication list

International journals

Koning JP, Vehof J, Burger H, Wilffert B, Al Hadithy A, Alizadeh B, van Harten PN, Snieder H, GROUP Investigators. (2011) Associations of two DRD2 gene polymorphisms with acute and tardive antipsychotic-induced movement disorders in young Caucasian patients.

Psychopharmacology (Berl) 2011 Jul 13. [Epub ahead of print]

Koning JP, Tenback DE, Kahn RS, Vollema MG, Cahn W, van Harten PN. (2011) Movement disorders are associated with schizotypy in unaffected siblings of patients with non-affective psychosis.

Psychological Medicine 2011 Mar 22 1:8. [Epub ahead of print]

Koning JP, Kahn RS, Tenback DE, van Schelven LJ, van Harten PN. (2011) Movement disorders in nonpsychotic siblings of patients with nonaffective psychosis. Psychiatry Research 2011 Jun 30;188(1):133-7.

[Epub 2011 Jan 31]

Koning JP, Tenback DE, Kahn RS, Van Schelven LJ, van Harten PN. (2010) Instrument measurement of lingual force variability reflects tardive tongue dyskinesia.

Journal of Medical Engineering & Technology 2010 Jan;34: 71-7.

Koning JP, Tenback DE, van Os J, Aleman A, Kahn RS, van Harten PN. (2010) Dyskinesia and parkinsonism in antipsychotic-naive patients with schizophrenia, first-degree relatives and healthy controls: a meta-analysis.

Schizophrenia Bulletin 2010 Jul;36: 723-31. [Epub 2008 Nov 5]

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Krabbe PF, Koning JP, Heinen N, Laheij RJ, van Cauter RM, De Jong CA. (2003) Rapid detoxification from opioid dependence under general anaesthesia versus standard methadone tapering: abstinence rates and withdrawal distress experiences.

Addiction Biology 2003 Sep;8(3):351-8.

National Journals

Koning JP, van Harten PN. (2008) Referaat: Relatie tussen bewegingsstoornissen en psychotische symptomen bij jongeren met een verhoogd risico op schizofrenie. Tijdschrift voor Psychiatrie 50 11, 752-753.

Abstracts and conference proceedings

International conference abstracts

Koning JP, Kahn RS, Tenback DE, van Schelven LJ, van Harten PN. (2010) Instrumental assessment of movement disorders is more sensitive than traditional rating scales in schizophrenia research, Schizophrenia Research - April 2010 (Vol. 117, Issue 2, Page 145, DOI: 10.1016/j.schres.2010.02.128) (oral)

Florence Italy, 2nd Schizophrenia International Research Society Conference

Koning JP, van Harten PN, Kahn RS. (2009) Instrumental assessment of movement disorders in patients with schizophrenia, their siblings and controls, Schizophr Bull (2009) 35(suppl 1): 1-377 DOI:10.1093/schbul/sbn173 (poster)

San Diego USA, 12th International Congress on Schizophrenia Research

Koning JP, van Harten PN, Aleman A, Kahn RS. (2008) Spontaneous dyskinesia and parkinsonism in schizophrenia and their siblings. a systematic review and meta-analysis, Schizophrenia Research - June 2008 (Vol. 102, Issue 1, Supplement 2, Page 153, DOI: 10.1016/S0920-9964(08)70466-3) (poster)

Venice Italy, 1st Schizophrenia International Research Society Conference

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listKoning JP, van Harten PN, Kahn RS (2008) Instrumental assessment

of tongue dyskinesia, schizophrenia Research - June 2008 (Vol. 102, Issue 1, Supplement 2, Pages 238-239, DOI: 10.1016/S0920-9964(08)70719-9) (poster)

Venice Italy, 1st Schizophrenia International Research Society Conference

National conference abstracts

Koning JP, Tenback DE, Kahn RS, Vollema MG, Cahn W, van Harten PN (2011)

Associatie tussen bewegingsstoornissen en schizotypie bij broers en zussen van patiënten met een niet-affectieve psychose. Samenvattingen 39de NVvP voorjaarscongres 2011/suppl.1 (oral)

Koning JP, Vehof J, Burger H, Wilffert B, Al Hadithy A, Alizadeh B, van Harten PN, Snieder H, GROUP Investigators. (2011) Associaties tussen het dopamine D2- receptorgen en antipsychotica geïnduceerde bewegingsstoornissen bij jonge patiënten met schizofrenie. Samenvattingen 39ste voorjaarscongres NVvP 2011/suppl.1 (oral)

Koning JP, Kahn RS, Tenback DE, van Schelven LJ, van Harten PN. (2010) Instrumentele en klinische registratie van bewegingsstoornissen in schizofrenieonderzoek, wat is sensitiever? Samenvattingen 38ste

voorjaarscongres NVvP 2010/suppl.1 (oral)

Koning JP. Tenback DE, Kahn RS, van Harten PN. (2009) Prevalentie van medicatiegeïnduceerde bewegingsstoornissen bij relatief jonge patiënten met schizofrenie. Samenvattingen 37ste voorjaarscongres NVvP 2009/suppl.1 (oral)

Koning JP, van Harten PN, Kahn RS. (2009) Instrumental assessment of EPS movements in schizophrenic patients, siblings and controls. Samenvattingen 37ste voorjaarscongres NVvP 2009/suppl.1 (poster)

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Koning JP, van Harten PN, Aleman A, Kahn RS. (2008) Spontane dyskinesie en parkinsonisme bij patiënten met schizofrenie en hun broers en zussen; een systematische review en meta-analyse. Samenvattingen 36ste voorjaarscongres NVvP 2008/suppl. 1 (oral)

Koning JP, Tenback DE, Kahn RS, Van Schelven LJ, van Harten PN. Instrumentele registratie van tongdyskinesia. Samenvattingen 35ste voorjaarscongres NVvP 2007/suppl. 1 (oral)

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Na zeven jaar is het dan zover, ik kan aan het dankwoord beginnen!

Talloze mensen wil ik bedanken, want promoveren is vooral het resultaat van samenwerken met enthousiaste anderen.

In het bijzonder dank ik prof. dr. P.N. van Harten, beste Peter, het was een eer dat je mijn begeleider wilde zijn, eerst als co-promotor en later als promotor. Ik heb veel van je geleerd en je kennis, je bevlogenheid, je didactische vaardigheden, je consciëntieusheid, je betrouwbaarheid en de ruimte die je me gaf hebben van mijn promotie traject een waardevolle en plezierige tijd gemaakt.

Prof. dr. R.S. Kahn, beste René, bedankt voor je begeleiding als promotor. Je inzicht en besluitvorming omtrent wetenschappelijk relevantie, zoals van dataverzameling en de beschrijving ervan, hebben me veel geleerd.

Dr. D.E. Tenback, beste Diederik, als co-promotor ben ik je dankbaar voor je stimulerende houding. Je methodologische visies hebben het geheel naar een hoger plan gebracht.

Prof. dr. M.P. Caligiuri (UCSD, USA), dear Michael, thank you for sharing the principles of mechanical measurement of movement disorders; it enabled us to build an instrument of our own.

De medewerkers van het cluster Medische Technologie en Klinische Fysica van het UMC Utrecht en dan met name Leonard; indrukwekkend hoe jij met je team onze ideeën hebt kunnen omzetten tot een mechanisch werkend apparaat. Ary, bedankt voor je inzet om de hard- en software verder te vervolmaken.

Mijn mede GROUP onderzoekers, inmiddels dr. Heleen, bijna dr. Monica, (give me the no-machine), en Ahmet, dank voor jullie gezelligheid en medewerking in de weekenden. Natuurlijk ook Joyce en Esther bedankt voor jullie onderzoeksondersteuning.

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Daarnaast ben ik ook dank verschuldigd aan Marijn en Willemijn, de onderzoekassistentes (en inmiddels beiden GZ-psycholoog) van het eerste en tweede uur. Jullie voorbereidende en logistieke planning van de dataverzameling heb ik als zeer prettig ervaren.

Mijn oprechte dank gaat ook uit naar alle patiënten, familieleden en controles van het GROUP project, die bereid zijn geweest om deel te nemen aan de verschillende onderzoeken. Moge de resultaten van dit onderzoek uiteindelijk bijdragen aan meer begrip en een betere zorg voor patiënten met schizofrenie.

De medeauteurs van de artikelen: André, Jim, Meinte, Richard, Asmar, Huib, Harold, Behrooz, Bob en Wiepke, jullie inbreng hebben de kwaliteit van de artikelen verder verbeterd. Jelle, bedankt voor de genetische analyses; het was een hels karwei, ik vond het prettig samenwerken.

Beste Dessa, bedankt voor je revisie van het Engels, it has improved the readability.

Rob, als medepromovendus bewegingsstoornissen van de Symforagroep was het heerlijk om samen over ons onderzoek te filosoferen, dat gaf me steeds weer nieuwe energie.

Alle assistenten psychiatrie van de Symforagroep die ik de revue heb zien passeren (het merendeel is inmiddels psychiater en de organisatie is ondertussen gefuseerd tot GGz Centraal), alle werkbegeleiders, supervisoren, medewerkers van Zon & Schild, de Rembrandthof, de Meregaard, Innova en Toos; bedankt voor jullie niet aflatende belangstelling en jullie vraag of de promotie al een beetje opschiet; ik kan nu zeggen; het is bijna volbracht.

Erik, als eerste onderzoekscoördinator heb jij me als nieuweling op de Symforagroep en in de wetenschap geholpen mijn weg te vinden, heel waardevol.

Wouter, bedankt voor de mogelijkheid om ook medicatie naïeve patiënten met autisme (mechanisch) te screenen op bewegingsstoornissen.

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rdDe inclusie is inmiddels bijna klaar en ik ben zeer benieuwd naar de resultaten.

Mijn paranimfen Metten en Elemi, beiden ook begonnen als agiko’s en het gehele promotietraject vanaf het eerste uur meegemaakt. Sindsdien zijn we elkaar binnen en buiten het werk blijven opzoeken en dat heeft samen met Chris geleid tot een mooie vriendschap. Ik kijk nu alweer uit naar ons volgende samenzijn in Sancerre of Vézelay!

Verder bedankt vrienden van dp (jazeker; alweer een “afstudeerfeest”), de Schotland groep (Keep on walking) en het toneelgezelschap Joost (Eén Meeuw maakt nog geen Tsjechov), jullie zorgen ervoor dat ik steeds het aangename met het nuttige kan blijven verenigen en zodoende geïnspireerd blijf.

Zeker ook veel dank aan mijn (schoon)familie voor jullie interesse in en medeleven over de voortgang van de artikelen en dit boekje, en mij. Met name dank ik mijn ouders, van jullie heb ik geleerd door te zetten als je ergens in gelooft.

Tot slot, lieve Kim en Sven bedankt voor jullie optimisme, humor, steun, geduld en relativering de afgelopen jaren; promoveren is prachtig, maar jullie liefde het mooist!

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Vitae

Curriculum Vitae

De auteur werd geboren op 22 april 1977 te ‘s-Hertogenbosch, Nederland. In 1995 behaalde hij het Gymnasium-B diploma aan het Titus Brandsma Lyceum in Oss. In 1999 voltooide hij zijn master Biomedische Gezondheidswetenschappen aan de Radboud Universiteit Nijmegen met als hoofdvak Evaluatie in de Geneeskunde en als bijvak Klinische Psychopathologie. Vanaf 1999 studeerde hij geneeskunde aan dezelfde universiteit. Vervolgens behaalde hij het artsenexamen in 2004, na zijn laatste co-schap ontwikkelingslanden in Sengerema Hospital Tanzania te hebben gedaan. Sinds 2004 is hij werkzaam in de psychiatrie, eerst als een assistent geneeskunde niet in opleiding (agnio) bij de GGz Nijmegen. Vervolgens begon hij in datzelfde jaar als assistent geneeskunde in opleiding tot specialist en klinisch onderzoeker (agiko) bij de Symfora groep (inmiddels GGz Centraal). Het promotie onderzoek onder supervisie van prof. dr. R.S. Kahn en prof. dr. P.N. van Harten (tevens de opleider van de auteur) maakt onderdeel uit van het landelijke Geestkracht psychose project. De auteur verwacht naast het promotie onderzoek ook de opleiding tot psychiater eind augustus 2011 succesvol af te ronden.

The author was born on April 22th, 1977 in ‘s-Hertogenbosch, the Netherlands. In 1995 he completed the secondary school (Gymnasium-B, Titus Brandsma Lyceum, Oss). In 1999 he received his masters Biomedical Health Sciences at Radboud University Nijmegen with his major in Health Technology Assessment and minor in Clinical Psychopathology. From 1999 he studied Medicine at the same university. He received his medical degree in 2004, after performing a last internship in tropical medicine at Sengerema Hospital, Tanzania. Since 2004, he has been working in psychiatry, first as a non-resident in GGz Nijmegen. In September of that year he started his residency in psychiatry in comination with a PhD at the Symfora Group (now GGz Centraal). This thesis, under supervision of prof. dr. R.S. Kahn and prof. dr. P.N. van Harten (also the supervisor of the psychiatric training of the author), is part of the Geestkracht psychosis project. The author expects to complete both PhD and psychiatric training at the end of august 2011.

Movement disorders in nonpsychotic siblings of patients with nonaffective psychosis

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