Gene 535 (2014) 70–78

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Chromosomal microarray analysis of consecutive individuals with autism spectrumdisorders or learning disability presenting for genetic services

Jennifer L. Roberts a, Karine Hovanes b, Majed Dasouki c,d, Ann M. Manzardo a, Merlin G. Butler a,⁎a Departments of Psychiatry, Behavioral Sciences and Pediatrics, The University of Kansas, Medical Center, Kansas City, KS, USAb CombiMatrix Diagnostics, Irvine, CA, USAc Department of Neurology, The University of Kansas Medical Center, Kansas City, KS, USAd King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia

Abbreviations: A2BP1, ataxin 2-binding protein 1 genelike gene; ADIPOQ, adipocyte-, C1q-, and collagen domainANOVA, analysis of variance; ASD, autism spectrum disoralpha 1C subunit gene; CHRNA7, cholinergic receptor, neDLG1, discs, large homolog 1 gene; DLG4, discs, large homalogram; FAM117B, familywith sequence similarity 117, mfragile X mental retardation, autosomal homolog 2 gene;GDNF-inducible zinc finger protein 1 gene; HAX1, HCLS1receptor accessory protein-like 1 gene; ITPR1, inositol 1,4LMNA, lamin A gene; MAP2, microtubule-associated prot1 gene; NDUFS1, NADH-ubiquinone oxidoreductase Fe-S p2 gene; PARK2, parkin gene; PMP22, peripheral myelin prohomolog gene; PTH2R, parathyroid hormone receptor 2 ggene; SHANK3, SH3 andmultiple ankyrin repeat domainsmatin, subfamily A,member gene; STAG2, stromal antigenspecific protease 6 gene; UCSC, University of California, Savation protein, epsilon isoform gene; ZNF407, zinc finger⁎ Corresponding author at: Department of Psychiatry an

913 588 1873; fax: +1 913 588 1305.E-mail address: mbutler4@kumc.edu (M.G. Butler).

0378-1119/$ – see front matter © 2013 Elsevier B.V. All rhttp://dx.doi.org/10.1016/j.gene.2013.10.020

a b s t r a c t

a r t i c l e i n f o

Article history:Accepted 10 October 2013Available online 2 November 2013

Keywords:Autism spectrum disorders (ASD)Developmental delayLearning disabilityChromosomal microarray analysisCopy number variant (CNV)

Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants(CNVs) in the human genome. We report our experience with the use of the 105 K and 180 K oligonucleotidemicroarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or de-velopmental delay/learning disability for genetic services at the University of Kansas Medical Center during thepast 4 years (2009–2012). Of the 215 patients [140 males and 75 females (male/female ratio = 1.87); 65 withASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with atotal of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presenta-tion and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteenpatientswith ASDhada total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. Themost common chromosome in-volved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n = 20). NineCNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n = 8). For the learning disabil-ity subgroup, chromosomes 2 and 22 weremost involved. Thirteen out of 65 patients (20%) with ASD had a CNVcomparedwith 32 out of 150 patients (21%)with a learning disability. The frequency of chromosomalmicroarrayabnormalities comparedby subject group or genderwas not statistically different. A higher percentage of individ-uals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but notstatistically significant. While both groups containedmore males than females, a significantly higher percentageof males were present in the ASD group.

© 2013 Elsevier B.V. All rights reserved.

; ACADL, acyl-coA dehydrogenase, long chain gene; aCGH, array comparative genomic hybridization; ACOXL, acyl-coA oxidase-containing gene; ANKRD11, ankyrin repeat domain-containing protein 11 gene; ALS2CR8, ALS2 chromosome region gene 8;

der; BAC, bacterial artificial chromosome; BCL2L11, BCL2-like 11 gene; CACNA1C, calcium channel, voltage dependent, L-type,uronal nicotinic, alpha polypeptide 7 gene; CNV, copy number variant; COBL, cordon-bleu gene; CT, computed tomography;olog 4 gene; DNA, deoxyribonucleic acid; EEF1B2, eukaryotic translation elongation factor 1, beta-2 gene; EEG, electroenceph-ember B gene; FAT1, FAT tumor suppressor 1 gene; FBXO45, F-box only 45 gene; FISH, fluorescence in situ hybridization; FXR2,FZD5, frizzled 5 gene; GALR1, galanin receptor 1 gene; GATAD2B, GATA zinc finger domain-containing protein 2B gene; GZF1,-associated protein X1 gene; HDAC, histone deacetylase gene; IDH1, isocitrate dehydrogenase 1 gene; IL1RAPL1, interleukin 1,5-triphosphate receptor, type 1 gene; KLF7, kruppel-like factor 7 gene; KNG1, kininogen 1 gene; LINS, lines homolog gene;ein 2 gene; MBP, myelin basic protein gene; MRPL19, mitochondrial ribosomal protein L19 gene; MYL1, myosin, light peptiderotein 1 gene; NLGN2, neuroligin 2 gene; NPHP1, nephrocystin 1 gene; NRXN1, neurexin 1 gene; PAK2, protein-activated kinasetein 22 gene; POLG, polymerase gamma gene; PRPF8, precursormRNA-processing factor 8 gene; PTEN, phosphatase and tensinene; RPE, ribulose 5-phosphate 3-epimerase gene; SACS, sacsin gene; SD, standard deviation; SH2B1, SH2B adaptor protein 13 gene; SHOX, short stature homeobox gene; SMARCA4, SWI/SNF-related, matrix-associated, actin-dependent regulator of chro-2 gene; SUMF1, sulfatase-modifying factor 1 gene; TRAPPC2, tracking protein particle complex, subunit 2 gene; USP6, ubiquitin-nta Cruz; XIAP, X-linked inhibitor of apoptosis gene; YWHAE, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase acti-protein 407 gene.d Behavioral Sciences, University of KansasMedical Center, 3901 Rainbow Blvd., MS 4015, Kansas City, KS 66160, USA. Tel.:+1

ights reserved.

71J.L. Roberts et al. / Gene 535 (2014) 70–78

1. Introduction

Classical autism, first described in 1943 by Kanner, belongs to agroup of heterogeneous disorders known as autism spectrum disorders(ASD) (American Psychiatric Association, 2000; Kanner, 1943). Autismspectrum disorders are characterized by impairment in three domains:social interaction, communication skills, and restricted repetitiveand stereotyped patterns of behavior, interests, and activities. Theonset of these impairments begins before the age of 3 years(American Psychiatric Association, 2000). About 40% of individualswith ASD also have a learning disability (Autism, DevelopmentalDisabilities Monitoring Network Surveillance Year, 2008 PrincipalInvestigators, 2012).

The etiology of ASD is complex and involves genetic factors, epige-netics, and the environment. Single gene disorders are recognized ascausative in less than 20% of subjects with ASD while the remaininghave other causative genetic or polygenic factorswhichmaybe impactedby epigenetic changes influenced by the environment (El-Fishawy andState, 2010; Schaefer and Lutz, 2006). Thus, the role of genetic testingand clinical genetic evaluation for individuals with ASD is emphasizedwhen identifying a cause. A diagnostic yield reported in the literatureranges from 6 to 40% (El-Fishawy and State, 2010; Miles and Hillman,2000; Schaefer and Lutz, 2006; Schaefer et al., 2010) with themost com-mon single genedisorders being fragile X syndrome and tuberous sclero-sis (Devlin and Scherer, 2012). Chromosomal microarray analysis in theclinical setting is now recommended as a first tier test for children andadults presenting with ASD (Battaglia et al., 2013) to improve thediagnostic yield. Microarray testing can detect copy number variationand type (i.e., deletions or duplications), size (e.g., b1 Mb) and presenceof known genes within the chromosome region.

Historically, the recurrence risk for ASD in families in which onechild has ASD has varied from 4% if the first affected child is female to7% if the first affected child is male (Folstein and Piven, 1991) butmore recent evidence indicates that the gender and functioning of theolder sibling do not predict ASD outcome (Ozonoff et al., 2011). The re-currence rate of ASD for families in which two children are diagnosedwith ASD is significantly higher, estimated at 25 to 30% with recent ev-idence indicating that first degree relatives of those with ASD are also atan increased risk for ASD-related characteristics (Messinger et al.,2013). Studies of identical twins in which one twin is diagnosed withASD have shown at least 60% concordance (Folstein and Piven, 1991).

Developmental delay involves any significant lag in physical,cognitive, communication, social, emotional, and/or adaptive skills(Individuals with Disabilities Education Improvement Act and 20U.S.C.). Global developmental delay is defined as performing at morethan two standard deviations below same-aged peers in two or moredevelopmental domains (Petersen et al., 1998) and affects between 1and 3% of children (Flore and Milunsky, 2012; Michelson et al., 2011).Many children with global developmental delay will also develop intel-lectual disability which is classified as having an IQ below 70. For ourstudy, we will group infants and children with developmental delayand older children and adults with intellectual disability into a singlecategory referred to as learning disability. Various studies have exam-ined the etiology of learning disabilities with chromosomal microarrayanalysis which is now considered as a first tier test for children andadults in the clinic setting (Battaglia et al., 2013; Miller et al., 2010).Herein, we report our experience over the past 4 years using chromo-somalmicroarray analysis to identify copy number variation (deletions/duplications) in consecutive patients referred with ASD or learning dis-ability and presenting for genetic services at a rural-based Midwesternacademic medical center in the United States.

2. Patient data

We studied 215 consecutive patients (140 males and 75 females;mean age ± SD = 10 years ± 9.7 years; age range = 5 months to

52 years) referred for genetic services to the Clinical Genetics settingat the University of Kansas Medical Center (KUMC), Kansas City, Kansasduring the past 4 years (2009–2012) with autism spectrum disorders(ASD, N = 65) or learning disability (N = 150). The patients were un-related based on family history obtained by a genetic counselor at thetime of clinical genetics evaluation. Patients were referred from privatepractice settings (family medicine, pediatricians, internists, psychia-trists/psychologists), hospitals, and medical centers in the Kansas Cityand surrounding Midwestern region of the nation. KUMC is a primaryand tertiary care academic center and includes the University of KansasHospital and Clinics. In 2012, KUMC reported 530,918 outpatient en-counters and 28,331 inpatient discharges representing all 105 countiesin Kansas, a rural population-based state. Themajority of counties in theadjoining state of Missouri were also represented.

3. Methods

We obtained peripheral blood samples in EDTA tubes and sent byovernight delivery to the clinically approved and certified commerciallyavailable CombiMatrix Diagnostics Laboratory (Irvine, CA) for DNA iso-lation for 105 Kor 180 K oligonucleotidemicroarray analysis. The 105 Karray containedmore than 99,000 probes and the 180 K array containedmore than 170,000 probes covering coding and non-coding human ge-nome sequences. The average spatial resolution between probes for the105 K arraywas approximately 21 Kb,while that of the 180 K arraywasapproximately 16 Kb. A copy number changewas identifiedwhenmorethan 6 consecutive probeswere involved in a segmentwith amaximumof contiguous probe spacing of 1 Mb. The patientDNAcopy numberwascompared to a reference diploid sex-matched DNA sample. Targetedevaluation of copy number changes involving more than 6 probes wasperformed in all regions of the genome with confirmation of abnormalresults by BAC aCGH or FISH probes targeted to the identified region.Most parental testing was performed by using FISH probes. Analysiswas performed using Nexus Copy Number software (BioDiscovery,Hawthorne, CA).

We conducted a clinical genetics evaluation, including a physical anddysmorphologic examination, and obtained pregnancy, medical, family,and social histories from each patient. We then summarized the chro-mosomalmicroarray data for comparisonwith findings from the clinicalgenetics evaluation. The reason for referral was ASD or learning disabil-ity. Those found with a recognized syndrome such as Down syndrome,fragile X syndrome, or single gene disorders (e.g., neurofibromatosis,tuberous sclerosis) were not included in the analysis and not a focusof this study.

Among families in which more than one affected family memberwas evaluated, microarray results from only one affected family mem-ber were included. For patients with abnormal microarray results,parental testing (e.g., FISH analysis) for the deletion and/or duplicationwas undertakenwhen possible to determine the origin of the diagnosticfinding or variant of unknown significance.

3.1. Statistical analysis

Analysis of clinical and microarray data was performed using SASStatistical Analysis Software Version 9.2 (SAS Institute Inc., Cary, NorthCarolina, USA). Statistical significance was tested for differences incategorical distributions using the Fisher's Exact test and mean differ-ences using ANOVA.

4. Results

Our study included 215 consecutive male and female patients pre-senting with autism spectrum disorders (ASD) or learning disabilityover the past four years seeking genetic services at the University ofKansasMedical Center. Both study groups containedmoremale than fe-male subjects but statistically significantlymoremaleswere observed in

Table 1Summary of abnormal microarray data for autism spectrum disorders (N = 13 of 65 subjects).

Age Gender Clinical features Del/Dup Parent oforigin

Chromosomelocation

Chromosomecoordinates

Size Number of genes indeletion or duplication

Selected gene(s) and/orchromosome regions of interest

Reference

5 y M Dysmorphism del + Unknown 2p13.3-p12 72,554,557-78,190,171

5.6 Mb 76 2p12ab

MRPL19Scerri et al. (2012)

11 y F Obesity, macrocephaly del + Paternal 2p16.3 51,027,443-51,123,408

96 Kb 1 NRXN1a,b Bena et al. (2013)

12 y* M ADHD, OCD, easy bruising, irregu-lar sleep disturbances

del − Unknown 4q35.2 187,471,061-188,661,633

1.2 Mb 2 FAT1a Abou et al. (2008)Chien et al. (2012)Youngs et al. (2012a)

9 y M Dysmorphism dup− Unknown,non-paternal

7p12.1 51,000,278-51,236,004

236 Kb 1 COBLa Griswold et al. (2012)

dup − Unknown,non-paternal

15q26.1 87,456,775-87,706,924

250 Kb 4 POLG Uusimaa et al. (2013)

11 y M Dysmorphism del + Unknown 7q11.23 72,360,373-73,795,527

1.4 Mb 26 7q11.23b

(Williams syndrome)Merla et al. (2010)

9 y M None dup − De novo 12p13.33 2,350,189-2,626,105

276 Kb 1 CACNA1Cb Cross-Disorder Group of the PsychiatricGenomics Consortium (2013)Lu et al. (2012)

9 y** M None dup + Maternal 15q11.2 19,623,685-20,325,942

702 Kb 5 15q11.2a,b Burnside et al. (2011)

20 y M None dup − Unknown 15q11.2 20,306,985-20,860,610

554 Kb 8 15q11.2a,b Burnside et al. (2011)

27y M None dup − Maternal 15q13.3 29,792,719-30,340,762

548 Kb 1 15q13.3b

CHRNA7Szafranski et al. (2010)Williams et al. (2012)

26 y M Dysmorphism dup + Paternal 16p11.2 29,514,266-30,239,774

726 Kb 42 16p11.2a,b Weiss et al. (2008)

41 y*** M Macrocephaly dup + Unknown 16p13.2 6,936,805-6,990,017

53 Kb 1 A2BP1a Martin et al. (2007)Butler et al. (2012)

4 y F None dup − Maternal 19p13.2 10,867,787-11,685,678

818 Kb 26 SMARCA4b Tsurusakia et al. (2013)

11 y M Dysmorphism del − Unknown Xp21.3 28,719,810-28,757,691

38 Kb 1 IL1RAPL1b Franek et al. (2011)Behnecke et al. (2011)

* = patient previously reported (Youngs et al., 2012a), ** = patient previously reported (Burnside et al., 2011), *** = patient previously reported (Butler et al., 2012).+ = CNVs (deletions or duplications) that were reported previously to be associated with disease or disorder.− = CNVs (deletions or duplications) not previously reported at the time of genetic testing.Chromosome coordinates from UCSC hg18 Human Genome (Mar. 2006). Available from: http://genome.ucsc.edu.

a Autism spectrum disorders (ASD).b Learning disability.

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Table 3Summary of the clinical findings seen in our subjects with abnormal microarray results.

Clinicalfinding

Autism spectrumdisorders &abnormalmicroarray

Developmentaldelay/learningdeficits &abnormalmicroarray

All subjectswith abnormalmicroarray

Fisher'sExacttest

N = 13/65 (20%) N = 32/150(21%)

N = 45/215(21%)

P value

Seizures 0 4 (13%) 4 (9%) 0.31Dysmorphicfeatures

4 (31%) 18 (56%) 22 (49%) 0.19

Microcephaly 0 8 (25%) 8 (18%) 0.08Macrocephaly 3 (23%) 1 (3%) 4 (9%) 0.07

(continued on next page)

73J.L. Roberts et al. / Gene 535 (2014) 70–78

the ASD group (52 males, 13 females) compared with the learning dis-ability group (88 males, 62 females; Fisher's Exact test, p b 0.003). Wefound that approximately one out of every five patients had an abnor-mal microarray finding (deletion/duplication) identified using eitherthe 105 K or 180 K oligonucleotide microarray. By searching genomevariant databases, including the UCSC Genome Browser (http://genome.ucsc.edu/cgi-bin/hgGateway), the Database of Genomic Vari-ants (http://projects.tcag.ca/cgi-bin/variation/gbrowse/hg18/), OnlineMendelian Inheritance in Man (http://www.ncbi.nlm.nih.gov/omim),DECIPHER (http://decipher.sanger.ac.uk/), CombiTrak (CombiMatrix'sinternal database of over 20,000 samples) and dbVar (http://www.ncbi.nlm.nih.gov/dbvar/) along with cited published literature, thegenetic change was characterized as diagnostic copy numbervariant (CNV) when reported previously to be associated with dis-ease such as ASD or learning disability or due to a non-diagnosticCNV or variant of unknown significance at the time of the report.Chromosome 15 was the most common chromosome involved inthe ASD group, as previously reported (Schroer et al., 1998),while chromosomes 2 and 22 were most involved in those withlearning disabilities.

Although a higher frequency of chromosomal microarray abnormal-ities were observed in females (N = 20 or 27%) compared with males(N = 25 or 18%), no statistically significant differences were observedin the frequency when compared by subject group (Fisher's Exact test,p = 1.0) or gender (Fisher's Exact test, p = 0.16). For patients present-ing with ASD, 13 of 65 (20%) were found to have an abnormality onmi-croarray analysis (Table 1). The 13 patients with ASD and abnormalmicroarray results had a total of 14 findings, including 6 diagnosticabnormalities (36%) and 8 variants of unknown significance(64%) (Tables 1 and 2). Of the 13 patients with ASD and abnormalresults, 3 (23%) had a family history of ASD, 3 (23%) hadmacrocephaly, and 4 (31%) had dysmorphic features (Table 3).None of the patients with ASD and abnormal microarray resultshad a history of seizures. The mean ± SD size of the abnormality(deletion/duplication) on the microarray results for those withASD was 966 ± 1464 Kb.

For patients presenting with learning disability, 32 of 150 (21%)were found to have an abnormality on microarray analysis (Table 4).The 32 patients with abnormal results had a total of 35 findings, includ-ing 26 diagnostic abnormalities (74%) and 9 variants of unknown signif-icance (26%) (Tables 2 and 4). Of the 32 patients with learning disabilityand abnormal results, 9 (28%) had a family history of developmentaldelay, 8 (25%) had microcephaly, 1 (3%) had macrocephaly, 18 (56%)

Table 2Summary of abnormal microarray data for our subjects.

Autismspectrumdisorder

Developmentaldelay/learningdeficits

Total

N = 65 N = 150 N = 215

Microarray abnormality 14 36 50a

Diagnostic CNV 6 27 33Deletion 3 20 23Duplication 3 6 9Other 1 (XY female) 1

Non-diagnostic CNVb 8 9 17Deletion 2 1 3Duplication 6 8 14

Fisher Exact Test (p = 0.09) was performed and indicated a possible trend for morediagnostic CNVs in the developmental delay group but not significant.

a 50 CNVs identified in 45 subjects [13 with ASD including a 9-year-old male with twovariants of unknown significance and 32 with developmental delay including a 9-month-old female with three diagnostic CNVs, a 9-year-oldmale with two diagnostic CNVs and a2-year-old female with two variants of unknown significance].

b Non-diagnostic CNV now referred to as variant of unknown significance.

had dysmorphic features, and 4 (13%) had a history of seizures(Table 3). No obvious gender differences were seen in the frequencyof seizures, dysmorphic features, microcephaly, macrocephaly or posi-tive family history between the two subject groups. The mean ± SDsize of the abnormality (deletion/duplication) on themicroarray resultsof infants and younger children with developmental delay or older chil-dren and adults with an intellectual disability was 2.90 ± 2.87 Mb.The mean age of the microarray abnormality in those with learningdisability was significantly larger than that seen in ASD (F = 2.6;p b 0.03).

4.1. Clinical case report

We describe a 42-year old white male with a learning disability, as arepresentative example of a patient identified with an abnormal chro-mosomal microarray result in our study. This patient had moderateintellectual disability, autistic features, and intermittent explosive disor-der. The parents were unavailable and therefore the prenatal and earlychildhood histories were unrecorded. Medical history included congen-ital absence of the right kidney, hypothyroidism, type II diabetes, perni-cious anemia, and history of seizures (petit mal and grand mal). He didnot graduate from high school. He received special education trainingand has limited verbal communication. He lives in a group home settingfor the intellectually disabled. EEGs performed at age 16 years and atage 22 years noted no epileptiform discharges. A head CT at age24 years was normal. At age 25 years, he sustained a closed head injuryfroma bicycle accident caused by a seizure. A headCT performed shortlyafter the injury showed small right parietal contusions with a minimalamount of surrounding edema. A complete blood count with differen-tial, coagulation studies, and lipids were normal at that time. A compre-hensivemetabolic panel showed low potassium and high CO2 levels. AnEEG obtained at age 29 years showed a rare focal epileptiformdischargein the left central area andmild diffuse slowwave abnormalities indicat-ing diffuse cerebral dysfunction. He was previously diagnosed with anintestinal volvulus and had an ischemic area in the sigmoid colonwhich required removal with placement of a colostomy. At age41 years of age, he experienced a nose bleed and aspiration pneumoniafollowing a dental procedure in which general anesthesia was used.He was hospitalized for 4 weeks due to pneumonia, and a lung CTscan showed bilateral pneumonia, pleural effusion, and right lungabnormality.

Physical examination revealed a normal head circumference(40th centile), normal height (50th centile), and normal weight(75th centile). He did have two posterior hair whorls and prematuregraying. Malar hypoplasia, downslanting palpebral fissures, bilateralptosis, a high arched palate and missing teeth were seen along with adeviated nasal septum (injury-related) with an elongated nose,

Fig. 1. Frontal and profile facial views of the proband with a 7.8 Mb deletion at chromo-some 2q33.1-q34 region at 42 years of age showing malar hypoplasia, ptosis,downslanting palpebral fissures, an elongated abnormal nose, Cupid's bow appearanceto upper lip, dental anomalies, and attached ear lobes.

74 J.L. Roberts et al. / Gene 535 (2014) 70–78

attached ear lobes, and hallux valgus deformity of both feet (Fig. 1).He had brown coloration of both legs below the knees including thefeet with sparse hair on the legs. The 180 K microarray showed a2q33.1-q34 deletion (7.8 Mb in size) containing 46 genes (see Fig. 2).Parents were not available for testing to determine if this deletion wasinherited or de novo in origin.

We previously reported a similar but smaller deletion (2q33.3-q34,3.7 Mb in size) in a young male with autistic and dysmorphic features,including downslanting palpebral fissures, mild right ptosis, a promi-nent nasal tip, abnormal ears, Cupid's bow of upper lip, dental anoma-lies, malar hypoplasia, and a high forehead (Brandau et al., 2008).Several of the cranio-facial and developmental features seen in that re-port were in common with our 42-year-old male with an overlappingbut larger 2q33.1-q34 deletion. This chromosome region containsgenes deleted in both subjects and involved the WNT pathway fororgan development (FZD5), calcium regulation (ALS2CR8, PTH2R), tran-scription (KLF7, EEF1B2), muscle function and energy production (IDH1,MYL1, RPE, ACADL, NDUFS1) thought to contribute to their clinicalpresentations.

5. Discussion

Our study describes our experience of 215 consecutive patients withASD or learning disability and presenting for genetic services at an aca-demic medical center in the rural-based Midwestern region of theUnited States. We also describe a representative clinical case reportidentified using chromosomal microarray analysis in this patient popu-lation. The overall diagnostic yield in our study was 21% for patientswith ASD or learning disability. This yield is similar to the 18.2% yield re-ported by Shen et al. (2010) in microarray studies with 932 patientswith ASD. Schaefer et al. (2010) further reported their experience andfound significant copy number abnormalities in 22% (14 of 68) of ASDsubjects. In our study the size of the CNVs seen in each subject group

FAM117B

Genes

203 Mb 204 Mb 205 Mb 206 Mb 207 M

ABI2, ACADL, ADAM23, ALS2CR8, C2orf21, C2orf67CRYGB, CRYGC, CRYGD, CTLA4, CYP20A1, DYTGPR1, ICA1L, ICOS, IDH1, INO80D, KLF7, LOC2007NRP2, PARD3B, PIP5K3, PLEKHM3, PTH2R, RAPH1

Fig. 2. An array comparative genomic hybridization (aCGH) was carried out using DNA Array7.8 Mb deletion at 2q33.1-q34 (203,191,088-210,989,186 bp from the p terminus). The 46 g(FAM117B) and last (MYL1) genes located in the deleted region are highlighted at the top of fi

varied. However, the size of the CNVs in the ASD group (966 ± 1464Kb) was significantly smaller than seen in the learning disability group(2.90 ± 2.87 Mb). The significance or meaning of this observation inmicroarray analysis is unclear but may relate to differences in geneticcausation (i.e., single gene in ASDversus larger genomic deletions or du-plications involving more than one gene in those with learningdisability).

Prior to chromosomal microarray studies in ASD reported in the lit-erature, Miles and Hillman (2000) tested 94 children for genetic causesand found that 6% (6 of 94) had identifiable genetic disorders whileHerman et al. (2007) reported genetic causes in 10% (7 of 71) of ASDsubjects. Schaefer and Lutz (2006) reported positive genetic findingsin 40% (13 of 32) of subjects with ASD including 5% with a high resolu-tion chromosome abnormality, 5% with fragile X syndrome, 5% withRett syndrome, 3% with PTEN gene mutations, 10% with other geneticsyndromes such as tuberous sclerosis, and about 10% with small dele-tions or duplications not detectable with high resolution chromosome

MYL1

b 208 Mb 209 Mb 210 Mb 211 Mb 212 Mb

, C2orf80, CCNYL1, CD28, CPO, CREB1, CRYGA, N, EEF1B2, FAM117B, FAM119A, FASTKD2, FZD5, 26, MAP2, MDH1B, MYL1, NBEAL1, NDUFS1, , RPE, SNORA41, SNORD51, WDR12, ZDBF2

-Oligo 180 K oligonucleotide array (CombiMatrix Diagnostics, Irvine, CA) and showed aenes found to be deleted in this chromosome region are listed alphabetically. The firstgure.

Table 4Summary of abnormal microarray data for learning disability (N = 32 of 150 subjects).

Age Gender Clinical features Del/Dup Parent of origin Chromosomelocation

Chromosome coordinates Size Number of genes in deletion orduplication

Selected gene(s) and/or chromosomeregions of interest

Reference

1.5 y M Dysmorphism dup + Unknown 1q21.3-q23.1 150,406,974-156,451,142 6.0 Mb 169 GATAD2Bb

HAX1b

LMNA

De Ligt et al. (2012)Matsubara et al.(2007)Hattori et al. (2012)

18 y M Microcephaly,dysmorphism

del + De novo 2p21-p16.3 44,726,451-48,990,449 4.3 Mb 27 2p16.2p21b Sanders et al. (2003)

2 y M Microcephaly,dysmorphism

del + Unknown 2q13 110,850,204-112,829,316 2.0 Mb 12 2q13b

ACOXL, BCL2L11Yu et al. (2012)

3 y F Macrocephaly, obesity dup − Paternal 2q13 111,104,335-112,879,277 1.8 Mb 11 2q13b

ACOXL, BCL2L11Yu et al. (2012)

42 y* M Seizures del + Unknown 2q33.1-q34 203,191,088-210,989,186 7.8 Mb 46 2q33.3q34b

MAP2abBrandau et al. (2008)Pescuccia et al. (2003)

1 y F Seizures del + Maternal 2q37.3 237,763,137-242,951,149 5.2 Mb 58 2q37.3b

HDACbKitsiou-Tzeli et al.(2007)Williams et al. (2010)

1 y F None del + Maternal 3p26.2 3,982,658-4,937,707 955 Kb 4 ITPR1b

SUMF1a,bDi Gregorio et al.(2010)Vardarajan et al.(2013)

19 y F Dysmorphism dup − Unknown 3q27.3 187,712,288-189,031,898 1.3 Mb 22 ADIPOQKNG1

Breitfeld et al. (2012)

8 y** F Dysmorphism del + De novo 3q29 197,174,369-198,842,531 1.7 Mb 24 3q29a,b

PAK2, DLG1, FBXO45Dasouki et al. (2011)Sagar et al. (2013)

25 y F Dysmorphism dup − Unknown 6q26 162,247,153-162,594,464 347 Kb 1 PARK2a,b Scheuerle and Wilson(2011)Mariani et al. (2013)

3 y M None del + De novo 9p13.3-p13.1 33,394,668-38,459,158 5.1 Mb 89 9p13b Niemi et al. (2012)6 y M Dysmorphism del + De novo 9p13.3-p13.1 33,521,700-38,781,172 5.3 Mb 86 9p13b Niemi et al. (2012)5 y M Dysmorphism del + Unknown 11q24.1-q25 122,813,651-134,452,384 11.6 Mb 93 11q24.1b

(Jacobsen syndrome)Manolakos et al.(2009)

9 y M Microcephaly, cataract,dysmorphism

del +del +

PaternalMaternal

13q12.1215q11.2

22,385,973-23,818,06520,290,385-20,640,325

1.4 Mb350 Kb

105

SACSb

15q11.2a,bBreckpot et al. (2008)Burnside et al. (2011)

5 y F Dysmorphism del − Unknown, non-maternal

15q26.3 98,800,411-99,434,987 634 Kb 5 LINSb Akawi et al. (2013)

9 m M Dysmorphism del + Maternal 16p11.2 28,730,299-29,009,896 280 Kb 10 16p11.2a,b

SH2B1bBachmann-Gagescuet al. (2010)

17 y M Dysmorphism dup + Maternal 14,651,493-16,504,719 1.9 Mb 28 16p13.11a,b

(continued on next page)

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Table 4 (continued)

Age Gender Clinical features Del/Dup Parent of origin Chromosomelocation

Chromosome coordinates Size Number of genes in deletion orduplication

Selected gene(s) and/or chromosomeregions of interest

Reference

16p13.12-p13.11

Ramalingam et al.(2011)

8 y M Microcephaly del + Unknown 16q24.3 87,920,905-88,102,506 182 Kb 1 16q24.3b

ANKRD11Sacharow et al. (2012)

9 m F Microcephaly,dysmorphism

dup +del +

UnknownUnknown

17pter-p13.120p11.21

0-8,261,26723,050,819-23,557,142

8.3 Mb506 Kb

21610

DLG4a

FXR2b

NLGN2a

USP6aa

YWHAEa,b

20p11.21b

GZF1

Feyder et al. (2010)Schluth-Bolard et al.(2010)Pettem et al. (2013)Tentler et al. (2003)Capra et al. (2012)Bruno et al. (2010)D'Angelo et al. (2010)

3 y F Microcephaly,dysmorphism

dup + Unknown 17p12-p11.2 11,826,994-16,316,855 4.5 Mb 24 17p11.2a,b

PMP22Doco-Fenzy et al.(2008)

46 y F Seizures dup − Unknown 17p13.3 1,383,290-1,537,874 155 Kb 4 PRPF8 Liu and Zack (2013)17 y F Microcephaly,

dysmorphismdel + Unknown 18q22.3-qter 70,596,888-76,117,153 5.5 Mb 20 18q23b

GALR1MBPZNF407a,b

Margarit et al. (2012)Ren et al. (1832)

6 y F Seizures dup + Paternal 22q11.21 17,002,559-20,140,494 3.1 Mb 62 22q11.21b Bittel et al. (2009)Alberti et al. (2007)

32 y F Dysmorphism del + Unknown, non-maternal

22q11.21 17,036,698-18,739,379 &18,927,136-19,967,262

2.7 Mb 67 22q11.2b

(DiGeorge/velocardiofacial syndrome)Bittel et al. (2009)Shprintzen (2008)

8 y F None del + Unknown 22q11.21 17,145,346-19,958,163 2.8 Mb 51 22q11.2b

(DiGeorge/velocardiofacial syndrome)Bittel et al. (2009))Shprintzen (2008)

4 y F Dysmorphism del + De novo 22q13.32-q13.33

47,953,197-49,691,432 1.7 Mb 40 22q13b

(Phelan-McDermid syndrome)SHANK3

Dhar et al. (2010)

8 y F None del + De novo 22q13.33 49,379,810-49,691,432 312 Kb 7 22q13b

(Phelan-McDermid syndrome)SHANK3

Dhar et al. (2010)

15 y*** M Dysmorphism del + Maternal Xp21.3-p21.2 29,134,047-30,084,234 950 Kb 1 IL1RAPL1b Nawara et al. (2008)Youngs et al. (2012b)

7 y M None dup − Maternal Xp22.2 13,337,055-13,800,520 463 Kb 6 TRAPPC2 Gedeon et al. (2001)2 y M Immune deficiency dup − Paternal Xp22.33/

Yp11.32525,304-1,228,569 703 Kb 1 SHOX Thomas et al. (2009)

2 y F Microcephaly dup −dup −

Unknown, non-maternalMaternal

Xq252q13

122,801,654-123,444,057110,046,870-111,145,135

642 Kb1.1 Mb

414

Xq25b

STAG2XIAPNPHP1b

Philippe et al. (2013)Baris et al. (2006)

6 y F None NA + NA XY female NA NA

* = patient reported within (see Clinical Case Report), ** = patient previously reported (Dasouki et al., 2011), *** = patient previously reported (Youngs et al., 2012b).+ = CNVs (deletions or duplications) reported previously to be associated with disease or disorder.− = CNVs (deletions or duplications) not previously reported at the time of genetic testing.Chromosome coordinates from UCSC hg18 Human Genome (Mar. 2006). Available from: http://genome.ucsc.edu.

a Autism spectrum disorders (ASD).b Learning disability.

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77J.L. Roberts et al. / Gene 535 (2014) 70–78

analysis. Diagnostic yields are now being reported with microarrayanalysis showing a wide range of deletions and duplications whilethe most common chromosomal abnormality associated with non-syndromal autism prior to chromosomal microarray analysis was a ma-ternal duplication of the 15q11-q13 region which accounted for 5% ofcases with autism (Schroer et al., 1998). Large microdeletions in thechromosome 16p11.2 and 22q regions also accounted for another 1%of cases.

Unexplained learning disability/autism spectrumdisorders associat-ed with dysmorphic features in pediatric patients were studied byBattaglia et al. (2013) using chromosomal microarray analysis andfound 91 CNVs ranging in size from 1 Mb to 60 Kb in 77 (or 22%) of349 patients. Additionally, Aggarwal et al. (2012) reported that 58%(196 of 338) of their patients with developmental delay or intellectualdisability had an identifiable genetic cause. These causes includedDown and microdeletion syndromes and unbalanced and balancedchromosomal rearrangements in 33% (112 of 338) of their subjects.Non-chromosomal syndromes, such as fragile X syndrome, tuberoussclerosis, Noonan syndrome, and Cornelia de Lange syndromewere rec-ognized in an additional 10% (32 of 338). Various neurometabolic disor-ders were identified in 10% (34 of 338) with the remaining subjectsclassified as having structural central nervous system defects, cerebralpalsy, environmental insults, or idiopathic intellectual disability. A sep-arate report byMichelson et al. (2011) on individuals with learning dis-ability found the diagnostic yield for karyotype studies to be at least 4%,and the diagnostic yield for fragile X testing was approximately 2% fora full mutation. However, with chromosomal microarray analysis,they found diagnostic abnormalities in 8% of subjects with learningdisabilities (Michelson et al., 2011) and 11% in those with learning dis-ability and dysmorphic features, congenital anomalies, or neurologicsymptoms.

Selected genes in the deletion/duplication detected by microarrayanalysis and/or chromosome regions of interest were identified bysearching the medical literature for biological functions of involvedgenes and OMIM [Online Mendelian Inheritance in Man (www.ncbi.nlm.nih.gov/omim)], as a comprehensive, authoritative compendiumof human genes and genetic phenotype including chromosome regionsand genomic coordinates that is freely available online and updateddaily. The goal was to search for information about CNVs, chromosomeregions, genes involved and their function (if known) alongwith recog-nized syndromeswith ASD or learning disability. Those genes present inthe deletion or duplication regions were studied to determine if theycould play a role in neurological development or function (i.e., ASD orlearning disability) when disturbed by searching published medical lit-erature reports, websites, OMIM or previously reported as a feature of arecognized genetic syndrome (e.g., Williams syndrome). For example,for 13 of the 65 subjects within the ASD group, selected genes and/orchromosome regions of interest were found, see Table 1, with litera-ture citations listed for each subject. Recognized genetic syndromes(e.g., Williams syndrome) were noted with disturbed genes known tocontribute to ASD and also genes found in deletions/duplications re-ported onmore than one occasion to cause ASD (e.g.,NRXN1, CACNA1C).Similarly, 32 subjects with learning disability were found to have CNVdeletions/duplications by microarray analysis with selected genes orchromosome regions of interest known to play a role in their clinicalpresentation (see Table 4). Known genetic syndromes includedDiGeorge/velocardiofacial syndrome. Selected genes included NLGN2,IL1RAP1, ANKRD11 and PARK2 known to play a role in neurologicaldevelopment or function and when disturbed can account for learningdisability are listed in Table 4.

The diagnostic yield of chromosomalmicroarray analysis for individ-uals with ASD or learning disability in our study, and results reported byothers, is consistently greater than the diagnostic yield of chromosomalkaryotype studies alone or for fragile X DNA testing (Herman et al.,2007; Michelson et al., 2011). As genetic technology continues to im-prove with advances in testing platforms and access to next generation

exome sequencing, further genetic lesions will be identified, reported,and characterized as a cause of ASDor learningdisability in patients pre-senting for genetic services. This informationwill be important formed-ical management and therapy with more accurate and specific geneticcounseling for affected individuals and at-risk family members. The au-thors encourage the reporting of other microarray experiences at aca-demic medical centers with similar patients presenting in the clinicalsetting for genetic services to increase our knowledge base, therebyimpacting on the quality of life and outcome for affected individualsand their families.

Conflict of interest

The authors of this study have no competing financial interestspertaining to this work.

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