The pursuit of susceptibility genes for Alzheimer's disease: progress and prospects

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The pursuit of susceptibility genes forAlzheimer’s disease: progress andprospectsKristel Sleegers1,2, Jean-Charles Lambert3, Lars Bertram4, Marc Cruts1,2,Philippe Amouyel3 and Christine Van Broeckhoven1,2

1 Neurodegenerative Brain Diseases Group, VIB-Department of Molecular Genetics; Universiteitsplein 1, B-2610 Antwerp, Belgium2 Laboratory of Neurogenetics, Institute Born-Bunge and University of Antwerp; Universiteitsplein 1, B-2610 Antwerp, Belgium3 Inserm U744; Institut Pasteur de Lille; Universite de Lille Nord de France; Rue Calmette 1, 59019 Lille cedex, France4 Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max-Planck Institute for Molecular Genetics, Ihnestrasse

63-73, 14195 Berlin, Germany

The recent discoveries in genome-wide association stu-dies (GWAS) of novel susceptibility loci (CLU, CR1 andPICALM) for Alzheimer’s disease (AD) have elicited con-siderable interest in the AD community. But what are theimplications of these purely epidemiological findings forour understanding of disease etiology and patient care?In this review, we attempt to place these findings in thecontext of current and future AD genetics research. CLU,CR1 and PICALM support existing hypotheses about theamyloid, lipid, chaperone and chronic inflammatorypathways in AD pathogenesis. We discuss how theseand future findings can be translated into efforts toameliorate patient care by genetic profiling for risk pre-diction and pharmacogenetics and by guiding drug de-velopment.

IntroductionWith each passing year, >4.5 million people around theworld develop dementia [1]. Owing to changing demo-graphics, and in the current absence of a successful cureor preventive strategy, the number of dementia patientsworldwide is projected to increase from 35.6million in 2010to 115.4 million in 2050 [2]. AD, a neurodegenerativedementia clinically characterized by a progressive impair-ment in memory and other areas of cognition, accounts forthe vast majority of dementia patients. Available treat-ment options for AD patients can only reduce symptoms ordelay progress for a few years. Molecular genetic studies ina small proportion of AD patients with an autosomaldominant pattern of inheritance have contributed greatlyto our current knowledge of the pathogenesis of AD byidentifying causal mutations in the amyloid precursorprotein gene (APP) and presenilin-1 and -2 (PSEN1,PSEN2) [3] (Box 1). The heritability of the more common,non-Mendelian form of AD is still high, with estimatesranging from 60–80% [4]. As with the Mendelian form ofAD, genetic research in patients with a genetically morecomplex form of AD has the potential to substantiallyameliorate patient care and avert the ever-increasing

health care problem. Because of the genetic complexityof late-onset AD this has been an arduous task. Despitedecades of research, only one common genetic variant (e4)in the gene encoding apolipoprotein E (APOE e4) has beenindisputably considered a risk factor for disease. However,technological advances are improving the progress of thisfield, and recent discoveries from two large-scale GWASincluding >25 000 individuals are encouraging [5,6]. Inthis review, we highlight what the study of complexgenetics of AD has learned us so far on the pathophysio-logical pathways involved [with specific focus on the poten-tial novel risk genes clusterin (CLU), phosphatidylinositol-binding clathrin assembly protein (PICALM) and comp-lement receptor 1 (CR1)], and we suggest avenues to followto translate these and future findings into genetic riskprofiling and the development of therapeutic approaches.

From genes to therapy and backThe early breakthroughs in molecular genetic studies ofautosomal dominant AD revealed a crucial role for Ab in thepathogenesis of AD (Box 1), inspiring the development ofdrugs preventing or reversing the accumulation of Ab, suchas antifibrillar compounds [7], active or passive immuniz-ation against Ab [8,9] or the selective lowering of Ab42 (e.g.by the inhibition of g-secretase) [10]. Some of the preclinicalresults were very promising [11], but clinical trials havebeen hampered by various factors, including severe adverseevents or a failure of compounds to penetrate the centralnervous system, and have not yet led to a successful therapydirected against Ab [12]. The brain tissue of severalpatients actively immunized against Ab in a phase I clinicaltrial [8] has become available, and those patients with thehighest antibody titers showed an almost complete absenceof Ab plaques post-mortem, implying the effect on Ab

deposition was successful. Despite a striking lack of Ab

deposits, however, these patients displayed severe cognitivedisabilities in the last stages of disease [13]. A full un-derstanding of the events up- and downstream of proteinaggregation is still lacking, but a pattern has emerged of amultifactorial, heterogeneous disorder in which many fac-tors can affect the course of disease in its early or laterstages. Oxidative stress [14], chronic inflammation (Box 2),

Review

Corresponding author: Van Broeckhoven, C. ([email protected]).

84 0168-9525/$ – see front matter � 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.tig.2009.12.004


alterations in lipid metabolism [15] and the age-relateddepletion of molecular chaperones [16] are generallybelieved to contribute to the pathogenesis of AD. Otherage-related conditions such as cardiovascular risk factors[15], for instance type 2 diabetes [17], can complicate orexacerbate the pathological process. A meta-analysis ofepidemiological studies exploring the association betweendiabetes and AD has demonstrated that diabetes patientsare at an increased risk of developing AD, with a hazardratio of 1.51 (95% CI 1.31–1.73) (AlzRisk database, http://www.alzrisk.org, accessed December 2009). At the histo-pathological level, this etiological complexity is evidencedby the fact that the hallmarkAD lesions (Box 1) rarely occurindependent of other pathologies. A significant proportionof AD brains shows concomitant cerebrovascular ischemicdamage, Lewy bodies or TDP-43 pathology [18,19].

This has several implications for patient care. First,monotherapy targeting only one molecular entity mightnot be sufficient. Second, the etiological signature (the sumof an individual’s risk and protective factors) will varybetween patients, which should be reflected in a person-alized therapeutic approach. Third, if Ab can initiate apathological cascade that progresses along its destructivepath even when Ab is removed [13], early detection and

risk prediction will be of vital importance to enable theadministration of drugs before the onset of pathology. Riskprediction and preclinical detection are especially perti-nent because the pathological process already commencesyears, if not decades, ahead of overt symptoms. Whereasthemolecular genetics of autosomal dominant ADhas beencrucial in establishing and affirming a role for Ab in ADpathogenesis, genetic studies of complex, late-onset ADwill be important in enabling personalized health care forAD, for example by uncovering novel biological pathwaysor through risk prediction and pharmacogenetics. How-ever, despite years of intense investigation, only onegenetic susceptibility factor for AD, the e4 allele of APOEe4, stands out (Box 3).

AD susceptibility from a candidate gene perspectiveMost studies aimed at identifying common genetic variantsother than APOE e4 that affect the susceptibility to ADhave followed a traditional candidate gene-based associ-ation approach. As such, they have largely probed existingbiological hypotheses in the hope of providing geneticevidence for their validity. A plethora of promising geneticassociations (with AD or its endophenotypes (e.g. episodicmemory, hippocampal atrophy or plasma Ab)) has beenreported over the years, related to most AD suspectedmechanisms such as the Ab cascade, inflammation, oxi-dative stress or vascular risk-associated genes. Neverthe-less, AD is a textbook example of a complex geneticdisorder with relative risk estimates rarely exceeding1.2, and every report of a positive association has beenrapidly followed by studies claiming the opposite [20]. Inaddition to plainly representing a false-positive finding, arange of factors such as lack of power, insufficient coverageof common and rare genetic variations in a gene, locus or

Box 1. Protein accumulation in AD

AD is a proteopathy, neuropathologically characterized by accumu-

lations of two proteins, amyloid beta (Ab) and tau, against a

background of progressive cortical atrophy resulting from the loss

of neurons and synapses. Ab is proteolytically processed from

amyloid precursor protein (APP) through the sequential cleavage by

two proteases, b- and g-secretase [3]. In AD brains, Ab monomers

aggregate into fibrils, which accumulate as microscopically visible

deposits, or ‘plaques’, in the parenchyma or surrounding the

vasculature of the brain. Either these plaques and the local

inflammatory reaction they invoke, or a soluble oligomeric inter-

mediate phase of Ab, or a combination of both, are neurotoxic [92–

94]. Tau, a microtubule-associated protein important for the stability

of the neuronal cytoskeleton and axonal transport, is subject to

hyperphosphorylation and accumulates as paired helical filaments

in AD brains, which assemble in intraneuronal inclusions known as

neurofibrillary tangles. These two characteristic lesions have long

been recognized, and a large body of scientific literature exists

trying to understand, unite or refute the importance of these two

proteins and their accumulation in AD pathophysiology [93,95–97].

Nevertheless, the discovery of pathogenic mutations in the genes

encoding APP (APP) [98] and the g-secretase-complex components

presenilin-1 and -2 (PSEN1, PSEN2) [99–101] in rare patients with

autosomal dominant, early-onset AD provided incontestable evi-

dence that aberrant APP processing can be sufficient to trigger the

pathological cascade leading to AD. Mutations in APP (missense

mutations, single codon deletion and locus duplications) can affect

the total amount of Ab produced, the relative amount of a longer

species of Ab peptide (cleaved at residue 42 rather than 40, hence

the acronym Ab42) and/or the amyloidogenic potential of the Ab

peptide. Mutations in PSEN1 or PSEN2 affect the catalytic activity of

g-secretase, leading to pro-amyloidogenic changes in Ab production

(http://www.molgen.ua.ac.be/ADMutations) [3]. Although these mu-

tations are not detected in the vast majority of AD patients, who

usually show a much later onset age and no or incomplete familial

aggregation of the disease, their neuropathological phenotype is

similar to that found in autosomal dominant AD. The pathological

accumulation of Ab in late-onset AD patients is more likely to be the

result of defects in the clearance of Ab, either through transport

across the blood–brain barrier or cellular uptake, or an increased

aggregation of Ab through the interaction with other proteins

(Figure 1).

Box 2. Neuroinflammation and AD

Patients with AD exhibit substantial microglial activation in the

affected areas of their brains, where microglia surround and

infiltrate the amyloid plaques. Components of the complement

system are upregulated in AD and observed in neurofibrillary

tangles and neuritic plaques. Although this can reflect a local

response to neuronal damage or misfolded protein, numerous lines

of evidence suggest that this inflammatory process is not merely a

byproduct of the pathological cascade, but that it can contribute to

disease progression, or even the initiation of AD (Figure 1). Ab

deposits can recruit activated microglia shortly after their formation

[102], possibly stimulating the microglia to clear Ab through

phagocytosis [94]. Whereas this route of Ab clearance might not

be (fully) effective because the ablation of microglia has no effect on

plaque turnover in APP transgenic mice [103], the local inflamma-

tory response can have adverse effects on disease outcome. For

example, Ab can trigger microglia to secrete neurotoxic, proin-

flammatory factors [104], which might exacerbate the local neuro-

degenerative process, and peripheral markers of inflammation seem

to be predictors of progression to AD [105]. Epidemiological studies

have reported a substantial decrease in the risk of AD after the long-

term use of NSAIDs [106]. NSAIDs have been shown to reduce

microglial activation and deposition of Ab in cell culture and animal

models, some even suggesting an effect on g-secretase because of

the selective reduction of Ab42 [10]. Nevertheless, randomized

clinical trials have been unsuccessful [107]. Finally, several of the

most interesting current genetic risk factors [in the genes APOE,

CLU, IL1B and CR1 (Table 1)] are either directly or indirectly involved

in the regulation of inflammatory mechanisms, further supporting

the predominant role of the immune system in AD pathogenesis.

Review Trends in Genetics Vol.26 No.2

85


allelic heterogeneity, hidden epistasis or population differ-ences might have also resulted in non-replication of gen-uine association signals. By contrast, negative studies areless likely to be published, further complicating theinterpretation of candidate gene-based studies. Becausethe bar was set high by the strength of the associationbetween APOE e4 and AD, subsequent associations havegenerally been received with a touch of skepticism, eventhough systematic meta-analyses currently highlight >30different loci showing particularly promising results (fordetails, see the AlzGene database at http://www.alzgene.org) [20]).

AD susceptibility from a genome-wide perspectiveFacilitated by technological advances, GWAS have startedtomake inroads intoADgenetics.Theallure ofGWASlies intheir hypothesis-generating potential based on purelygenetic evidence. Several independentADGWAShavebeenperformed to date [5,6,21–27; for an up-to-date overview seeAlzGene], mostly differing in the number and selection ofsingle nucleotide polymorphisms (SNPs) tested (gene-cen-tric versus linkage disequilibrium (LD)-based; ranging from50 000 to 600 000 SNPs), sample size (ranging from�400 to>16 000 individuals) and study design (e.g. case control or

family-based design). In spite of these differences, theassociation betweenAPOE e4 andADdominated the results[28]. Although shortlists with putative novel susceptibilityloci have been generated (not always near known genes),confidence in many of these findings remains limitedbecause most associations did not attain genome-wide sig-nificance, and because of the lack of independent replicationdata. However, most GWAS have been within the past 12months and, therefore, only a limited number of indepen-dent replication attempts have been published. Neverthe-less, two recentADGWAShaveprovided strongevidence forhaving unraveled at least one genuine novel AD risk factorin or near the gene encoding clusterin (CLU), also known asapolipoprotein J (apoJ) [5,6]. Importantly, both studiesindependently observed the genome-wide significant associ-ation of AD with the same polymorphism and direction ofeffect at this locus. These studies differed from previousGWAS by their larger sample size (involving 14 000–16 000patients and controls), which yielded sufficient power todetect genetic effect sizes common in genetically complexdiseases. Owing to its functional relatedness to apoE, CLUactually represents one of the oldest AD candidate genes[29,30]. Given the effect estimate from both GWAS (i.e. anodds ratio (OR) �1.18), the original candidate gene studyhad a power <40% to detect this association, even underoptimal conditions (i.e. no effect of population stratificationand complete LD between markers and the susceptibilityallele).

In addition to CLU, two other gene loci (PICALM andCR1) were associated at a genome-wide significance level inthese two GWAS, both in one study, but they proved to bedetectable with sub-genome-wide significance in the otherstudy, increasing confidence in their relevance for AD [5,6].The most significant SNPs in these loci are relatively com-mon, but their associated ORs are <1.2, as expected forcomplexdiseases. Population-attributable fractions are cur-rently estimated to range from 4% (CR1) to 9% (CLU andPICALM) compared with 20–25% for APOE, but theseestimates assume an as yet not established biological linkbetween the associated SNPs at these loci and AD.With theidentification of the actual disease-related variants, theseestimates are likely to change. Interestingly, some of theassociated SNPs in both CR1 and PICALM have alreadybeen tested in previous GWAS [e.g. 22,24]. Although theywerenothighlighted specifically in any of theseGWAS, theyshowedat leastmarginal evidence of anassociationwith thesame direction of effect (see AlzGene), lending further cre-dence to these results.

Clusterin, Ab and lipid metabolismRather than generating novel biochemical hypotheses,some of these novel risk genes actually recapitulate exist-ing hypotheses. Clusterin is a secreted chaperone moleculethat can bind an array of ligands with low specificitybecause of a molten globular domain [31]. Among itsligands are lipids and complement factors, but also Ab.It has been hypothesized that the accumulation of mis-folded protein, such as Ab fibrils, can induce CLU throughthe binding of heat shock factors to a heat shock element inthe promoter of CLU [32]. CLU has been observed inamyloid deposits [33], and its levels seem to be increased

Box 3. Apolipoprotein E in AD

The gene encoding APOE is indisputably implicated in the etiology

of AD. ApoE exists in three different isoforms (E2, E3 and E4)

differentiated by amino acid substitutions at residues 112 and 158.

Individuals heterozygous for the APOE e4 allele, encoding isoform

E4, have approximately a threefold increased risk of developing AD,

whereas those homozygous for e4 have a �15-fold increased risk

compared with those that do not carry a e4 allele [108]. This strong

effect on genetic susceptibility for sporadic AD, combined with the

observation that apoE colocalizes with parenchymal and vascular

Ab deposits, has been the incentive for in vitro and murine

experiments exploring its link to Ab (Figure 1). These studies have

demonstrated that apoE can physically interact with Ab peptides in

an isoform-specific manner, affecting the physical/conformational

properties of Ab and enhancing plaque formation [109,110].

Alternatively, but most likely not mutually exclusive, the physical

interaction between apoE and Ab affects the efficiency of Ab

clearance, either across the blood–brain barrier [36] or by modulat-

ing cellular uptake through receptor-mediated endocytosis [111]. In

vivo, an APOE e4 dose-dependent increase in fibrillar Ab burden has

been demonstrated in cognitively healthy individuals using an

amyloid imaging compound [112].

But APOE could also affect AD through pathways not directly

linked to Ab. As the major apolipoprotein of the brain, apoE is

important for cholesterol homeostasis by serving as a ligand in

receptor-mediated endocytosis of cholesterol-containing lipoprotein

particles. There is increasing evidence that abnormal cholesterol

metabolism per se is key in the pathological cascade leading to AD

[15]. Cholesterol is a major constituent of the neuronal membrane

and the synapse, and impaired redistribution of lipids and

cholesterol might affect neuronal plasticity (Figure 1). Moreover,

APP processing through g-secretase takes place in the cholesterol-

rich membrane, with high intracellular cholesterol enhancing the

amyloidogenic processing of APP. The degree of lipidation of apoE

seems to affect the clearance rate of Ab [36]. Finally, apoE is also

associated with circulating levels of cholesterol as well as athero-

sclerosis, and might as such also affect the risk of AD indirectly

through a vascular component [15] (Figure 1). From a mechanistic

point of view, its implication in AD remains to be clarified.

Moreover, despite a high strength of association with the disease,

within the past 15 years no concrete treatment has been derived

from this discovery.


86


in the cerebrospinal fluid of AD patients [34], strengthen-ing the observed genetic association. CLU can mediate theclearance of Ab by enhancing endocytosis [35] and/orthrough transport across the blood–brain barrier [36],and it can influence fibrillogenesis [37] (Figure 1). Thisreinforces the hypothesis that an imbalance in the pro-duction and clearance of Ab is important in the pathologi-cal cascade leading to AD. Strikingly, CLU encodes thesecond major apolipoprotein of the brain, apoJ. It sharesmany of apoE’s properties (Box 3), not only in relation toAb, but also to lipid transport. It is involved in the trans-port of cholesterol and phospholipids [38], and increasedCLU levels have been observed in atherosclerosis [39](Figure 1). Polymorphisms in CLU have been associatedwith lipid levels and carotid intima media thickness [40].This suggests that genetic variation in CLU might alsoindirectly modify susceptibility to AD by increasing therisk of cerebrovascular disease, which in turn could accel-erate the primary neurodegenerative process (Figure 1).The challenge now lies in identifying the genetic variant(s)in CLU underlying the association (Box 4). One missensemutation has been associated with hemolytic uremic syn-drome [41], but to date no variants have been shown tohave a functional effect on AD.

CR1, Ab and inflammationCR1 is located on 1q32 in a cluster of the receptors ofthe complement activation gene family and encodes

complement receptor type 1, a 2039 amino acid single-passtype I membrane protein. CR1 belongs to the Knops bloodgroup system [42] and plays an important role in theregulation of the complement cascade and clearance ofimmune complexes, particularly those opsonized by comp-lement components C3b and C4b [43]. CR1 genetic var-iants or changes in expression have previously beenimplicated in a variety of conditions, ranging from systemiclupus erythematosus (SLE) [44] to the severity of Plasmo-dium falciparummalaria [45]. The extracellular part of theprotein contains a variable number of binding sites for C3band C4b, determined by the number of long homologousrepeats (LHR A-D) [46]. Another frequently describedpolymorphism is associated with the density of CR1 mol-ecules on the erythrocyte cell membrane [47]. Although thefunctional relevance of these two polymorphisms for AD isstill unclear, it might be worthwhile exploring their con-tribution to the observed association betweenCR1 and AD.Ab oligomers can become bound by C3b and adhere toerythrocyte CR1, with subsequent clearance from the cir-culation [48]. In line with this, APP transgenic mice withan inhibition or deficiency of C3 display increased Ab

accumulation and neurodegeneration [49]. Decreasederythrocyte CR1 expression is associated with theimpaired clearance of immune complexes and has alreadybeen connected to autoimmune disorders such as SLE [44].This suggests a protective role for CR1 in AD through thebinding of C3b and subsequent Ab clearance [6] (Figure 1).

Figure 1. Linking the genes to the pathophysiology of AD. An overview of how APOE, CLU, PICALM and CR1 are implicated in AD susceptibility. The information based on

current experimental or observational evidence is depicted by solid black arrows, with hypotheses shown by blue arrows. Several pathophysiological pathways thought to

contribute to disease (Ab (in pink), neurofibrillary tangles (blue), chronic inflammation (green), atherosclerosis (yellow), loss of physiological function at the synapse

(purple) and others (orange)) are indicated by interrupted arrows. Note that neurofibrillary tangles are not necessarily downstream of Ab deposition. Abbreviation: BBB,

blood–brain barrier.


87


However, it is conceivable that genetic variation in CR1might also affect AD directly through neuroinflammation,independent of its function in Ab clearance (Box 2;Figure 1). A small fraction of CR1 is soluble (sCR1) andis thought to exert local complement inhibiting and anti-inflammatory activities, but its role in the central nervoussystem remains to be explored [43].

Interestingly, CLU has also been linked to chronicinflammation (Figure 1). Its expression is increased inconditions of chronic inflammation of the brain, and bothC3 and CLU, but not CR1, have been observed in the sameneuritic plaques [50]. CLU can inhibit complement systemactivation, defending neurons against cytolysis caused bythe membrane attack complex of complement [51], a com-plex that is abundantly present in dystrophic neurites inAD [52]. It has been suggested that CLU canmask fibrillarstructures from recognition by the immune system [31].Moreover, apoE and one of the apolipoprotein receptors(LRP1) can also modulate the innate immune response invitro [53].

PICALM and the synapsePICALM, located on 11q23, encodes the ubiquitouslyexpressed 652 amino acid phosphatidylinositol-binding cla-thrin assembly protein involved in clathrin-mediated endo-cytosis [54]. PICALM is also known as a clathrin assemblylymphoid myeloid leukemia protein (CALM), and fusionproteins involving PICALM have been implicated in acutemyeloid leukemia [55] and T-cell acute lymphoblastic leu-kemia [56]. PICALM draws attention to another elementimportant in AD pathology. It is involved in clathrin-mediatedendocytosisand intracellular traffickingof, amongothers, the synaptic vesicleproteinVAMP2that isnecessaryfor neurotransmitter release at the presynaptic membrane,which is important for neuronal function and memory for-mation [57].PICALM can less easily be tracedback to theAb

hypothesis, but a role for PICALM-mediated endocytosis inthe recycling of APP has been suggested [5] (Figure 1). Thereduction of PICALM in cultured embryonic hippocampalneurons results in dendritic dystrophy, reduced endocytosis

anddisrupted secretory transport [58]. The strongestassoci-ation signal has been identified at the 50 end ofPICALM [5],which hints at the involvement of genetic variation in theregulatory region of PICALM, but a more in-depth explora-tion of PICALM genetic variability is warranted (Box 4).

Insight into pathophysiological pathwaysWhat has been the revenue of our decade-long search fornovel AD susceptibility genes in terms of insight into ADpathogenesis and translation into risk prediction, drugdevelopment and pharmacogenetic studies? The three nov-el risk genes exemplify that a potential connection to Ab isalmost always conceivable, but they also reinforce otherbiological hypotheses (Table 1, Figure 1). This stronglysuggests that these pathways are not mutually exclusive,but rather all contribute to the endpoint of disease, tovarying degrees in different patients.

Of the 35 genes associated with AD after systematicmeta-analysis of the entire AD genetics field (AlzGene,accessed December 2009 [20]), nine genes are involved inlipid homeostasis and/or cardiovascular disease, under-scoring the epidemiological evidence of an associationbetween lipid metabolism and AD [15]. Some caution iswarranted for the misinterpretation of this clusteringbecause the majority of genes were studied in a candidategene approach, and therefore hypothesis-driven. However,the observation of an association with CLU in two inde-pendent GWAS provides strong support for a role of thispathophysiological pathway in AD. In addition to CR1,CLU and APOE, five more of the 35 genes are involved inthe immune response, and of those, two were identified inrelatively hypothesis-free approaches (GAB2 in a genome-wide association study [59]; IL-33 in a multi-stage geneticassociation study of genes differentially expressed in ADbrain tissue [60]), underscoring the relevance of inflam-mation in AD (Box 2).

Our understanding of the pathophysiological pathwaysinvolved in AD is likely to change with the progress ofGWAS because of their hypothesis-generating natureand the ability to correct for population stratifications by

Box 4. Identifying sequence variants underlying association signals

Whereas finding consistent and reproducible evidence of association

between certain disease phenotypes and genetic markers has proved

daunting, pinpointing the actual disease-related variants underlying

the association signals is a separate, highly challenging task in itself.

The situation is aggravated by the fact that association signals are not

always identified in regions harboring known genes. In cases where

an association signal is located in or near a known gene (as is the case

for CLU, PICALM and CR1), the typical next step is to assess the

presence of known or plausible functional sequence variants in the

gene in publicly available sequence and genotype data [e.g. ‘‘dbSNP’’

(http://www.ncbi.nlm.nih.gov/projects/SNP) and the ‘‘1000 Genomes

project’’ (http://www.1000genomes.org)]. However, the success of

this step is limited by the often incomplete resolution and coverage of

regions of interest in the public datasets – especially for rare variants

with intermediate levels of penetrance – and our only incomplete

understanding of how specific variants might interfere with protein

function, especially if they are located in regulatory or other non-

coding regions of the genome (e.g. within transcription factors,

microRNAs and/or their respective binding sites). In addition to this in

silico assessment, regions of interest can also be fine-mapped in

vitro, for example via resequencing of the implicated regions in

individuals carrying the disease-associated haplotypes. Ancient

populations in which LD extends over shorter regions might be

advantageous at this stage.

Experimentally, these fine-mapping analyses were traditionally

based on small-scale (<10 kb) PCR-based enrichment of the implied

regions followed by Sanger sequencing in a few individuals, followed

by assessments of their population frequency, attributable fractions

and, eventually, functional experiments. Recent technological ad-

vances now allow researchers to specifically target and enrich

substantially larger genomic regions, followed by massively parallel

(so called ‘next-generation’) sequencing of hundreds and thousands

of genes and/or large contiguous regions of interest (currently up to

several dozen Mbs). Eventually, sequencing the whole genome will

alleviate the need for any targeted enrichment procedure by

delivering an individual’s entire genome sequence in one experiment.

In addition to identifying rare and common variants excluded from

genome-wide marker panels, next-generation sequencing techniques

also promise to examine the effect of copy number variation and

other larger scale structural rearrangements, which might shed

further light on the genetic architecture of AD and other genetically

complex diseases.


88


Tab

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3.5

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3.9

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of

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CLU

Clu

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rs11136000

GW

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5(0

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9)

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Recycli

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principal component adjustments in homogeneous popu-lations, to avoid spurious associations [61], particularlywhen low increases in risk are involved [62]. Because of themany statistical tests performed, genome-wide associationapproaches require an adjustment of significance levelsdue to multiple testing, e.g. by computation of experiment-wide false discovery rates or by simple (but conservative)Bonferroni correction. In this context, it is clearly possiblethat genetic determinants – slightly but truly associatedwith AD – can be rejected on purely statistical grounds(false-negative). In this context, approaches have beendeveloped to extract pertinent information from the SNPsnominally associated with disease risk. For instance, it hasbeen postulated that genetic determinants are not ran-domly distributed among the biological pathways butinstead grouped together among specific biological pro-cesses. This postulate results from analogy with transcrip-tomics experiments in which tens or hundreds of geneshave subtle differences in expression levels. Rather thanonly focusing on individuals genes that have the strongestevidence of differential expression, pathway-basedapproaches have been developed to characterize specificbiological pathway enrichments [63]. However, theseapproaches need to be adapted in genome-wide associationanalyses for at least two reasons: (i) LD between SNPstends to favor the artificial enrichment of gene clusters in asame locus; and (ii) gene set enrichment analysis tends tohighlight any pathway that contains several large genes(many SNPs potentially associated with disease risk bychance) and tends to miss pathways that contain onlysmall genes [64]. Because of these and other reasons,pathway-based analyses run a relatively high risk of yield-ing false-positive results. Finally, gene set enrichmentanalyses also strongly depend on the quality and exhaus-tiveness of the biological databases. Programs haverecently been developed to test for the overrepresentationof GO (gene ontology) categories (e.g. biological processes)in lists of significant SNPs from GWAS [65,66]. However,these programs, as most of the techniques based on GOcategory analyses, are limited by the fact that each func-tional category is analyzed independently without unifyinganalysis at a pathway or system level [67]. Furthermore,less than 1% of GO annotations have been confirmedexperimentally [68]. To take into account these limitations,other programs have been based on the detection of anoverrepresentation of genes in a specific pathway using theKEGG database [69] and these allow us to define theposition of the associated genes on a given pathway docu-mented on biological evidence [70].

However, even if pathway-based genome-wide associ-ation analyses present some important caveats, suchapproaches have been already successful e.g. the IL12/IL23 pathway in Crohn’s disease [71]. Furthermore, thisfield is very active with the publication of new programsand statistical approaches likely to lead to a strong im-provement and pertinence of these approaches in thecoming years.

Towards genetic profilingOther than increasing insight into the pathogenesis, howcan these and future genetic discoveries advance patient

care? One potential application is to incorporate estab-lished genetic susceptibility factors into a diagnostic orpredictive test for AD (‘genetic profiling’), ideally comple-mented with information on non-genetic risk exposures, toallow targeted medical intervention before the onset ofsymptoms. The viability of this application might be lim-ited, however, because the currently identified genes willonly explain a small proportion of the heritability of AD[72]. Likewise, the diagnostic utility of genetic profilingseems limited in other common complex diseases andtraits. For example, individuals with the highest scoreon a genetic risk scale including 16 susceptibility loci formultiple sclerosis had a 2.3 to 3.6 times increased odds ofdeveloping multiple sclerosis compared with the meanpopulation risk [73], comparable to the effect of APOE e4alone in the prediction of AD risk (Box 3). A 54-locusgenetic profile for the highly heritable trait height couldonly predict 5.6% of variation in height compared with 40%by traditional predictions based on parental height [74]. Asimulation study of genetic profiles for coronary heartdisease suggests that 100 genes of a similar allele fre-quency and effect size as CLU rs1113600 are needed toreach a discriminative accuracy of �70% (where 50%indicates a lack of discrimination) [75]. Clearly, the levelof discriminative accuracy deemed acceptable is dependenton the future applications of the risk profile and its con-sequences (e.g. the invasive nature of the treatment).Nevertheless, the current large-scale collaborative studiesgive hope that new genes will continue to be identified bymeta-analyses or pathway-based approaches. Other tech-niques that come within reach, such as whole-genome copynumber variant analysis or whole exome or genomesequencing, might identify genetic variants that are nottypically detected in GWAS (Box 4).

Alternatively, a genomic profiling approach can be fol-lowed that includes all nominally associated SNPs in agenome-wide association study, rather than only the estab-lished, genome-wide significant risk variants. However,the gain in discriminative accuracy of this method seemslimited for complex diseases, reaching discriminativevalues of only 55–60% for diseases such as bipolar disorder,coronary heart disease and type 2 diabetes with no knownstrong genetic risk determinants [76]. Because of thestrength of association between APOE and AD, a weightedor log-odds risk score seems more appropriate for AD thansimply counting the number of risk genotypes [76]. Incontrast to a genetic profile, a genomic profile gives nobiological information, limiting its use in personalizedmedicine. Moreover, both genetic and genomic profilesdo not incorporate information on non-additive effects suchas epistasis, which are likely to be involved in complexdiseases such as AD. Pathway-based analyses of ADGWAS data will hopefully allow the incorporation of theseeffects in risk prediction.

PharmacogeneticsGenetic profiling can already be incorporated in research,for example, in prospective epidemiological studies, whichare currently often stratified by the APOE e4 genotypealone to explore interactions and risk modification, or inpharmacogenetics to identify high risk individuals who


90


might specifically benefit from the drug under study. TheAPOE e4 genotype has already been incorporated intosome studies to assess genotypic differences in the thera-peutic response to cholinesterase inhibitors [77] and rosi-glitazone, an agonist of the peroxisome proliferator-activated receptor g (PPARg) involved in glucose and lipidmetabolism and the suppression of inflammatory geneexpression [78]. These studies, however, have not led tothe inclusion of APOE genotypes in treatment decisions, atleast for the currently prescribed cholinesterase inhibitors.The cholesterol-lowering statins have been suggested todecrease the risk of AD in epidemiological studies [79], butclinical trials have been unsuccessful [80]. APOE e4 influ-ences the effect of statins on cholesterol levels [81], so theAPOE genotype might have influenced treatmentresponse. A broader genetic profile might advance drugdevelopment by identifying participants eligible for, mostlikely to benefit from or least likely to experience adverseeffects of a targeted therapeutic approach. For example,non-steroidal anti-inflammatory drugs (NSAIDs) haveemerged as protective drugs for AD in epidemiologicalstudies, but trials have remained largely unsuccessful(Box 2). The selective inclusion of those patients with agenetically altered immune response might amelioratestudy outcomes. Moreover, NSAIDs are not routinelyrecommended for the prevention of AD because of poten-tially severe side effects, but evidence that these adverseevents are also under genetic influence is increasing [82].Likewise, drug trials aimed at reducing Ab by immu-notherapymight improvewhen individuals at an increasedrisk of an adverse immune response can be identifiedbefore inclusion, and antibody response to Ab vaccination,which is highly variable and independent of the dose [8,13],might also be genetically determined [83]. This area ofresearch deserves exploration in AD, and current andfuture GWAS have the potential to contribute.

Newly identified risk genes can also more directlyadvance drug development for AD by highlighting noveltherapeutic targets or, as could be the case for CLU andCR1, refocusing existing efforts for drug development totarget the complement, chaperone or cholesterol pathways.Facilitating progress, the therapeutic potential of bothCR1 andCLU is already being explored in other conditions.A recombinant form of soluble CR1, which inhibits allcomplement pathways by dissociating the C3 convertasesand targetingC3b andC4b for degradation [84], was shownto block complement activation upon acute nerve injury[85] and inhibit inflammation in an approximate model ofmultiple sclerosis in rats [86]. For CLU, inhibition via anantisense oligonucleotide approach is explored in cancerbecause of the putative antiapoptotic effect CLU has[87,88], whereas the administration of recombinant CLUseems to exert beneficial effects on peripheral neuropathyand atherosclerosis in mice [89,90]. However, an athero-genic diet has the potential to elevate CLU levels, at leastin mice [91]. Whether these strategies are worth pursuingin AD not only depends on the potential of the compoundsto cross the blood–brain barrier, but also on the underlyingmechanism of action through which these genes areinvolved in AD. A more in-depth genetic screening is likelyto uncover functional variants that shed light on these

mechanisms by their nature (gain or loss of function) and/or location in specific functional domains, splice sites (e.g.alternative splicing of CLU can give rise to a nuclearvariant that is involved in apoptosis) or regulatory regions.

Concluding remarksDespite recent advances, a full understanding of the(genetic) etiology of AD is still a long way off. To reachthat final goal will require large collaborative efforts aswell as the exploration of the contribution of other sourcesof genetic variation, including rare variants of intermedi-ate penetrance, structural variation, epistasis and epige-netic phenomena. However, the discovery of three novelpotential AD genes in two well-powered GWAS spurs ourhope that our efforts to ameliorate AD patient care becomereality in the not too distant future. These genes under-score the importance of amyloid, lipid homeostasis andchronic inflammation in AD pathophysiology, and supportongoing efforts towards intervention in these pathways.

AcknowledgementsResearch in the authors’ research groups was funded in part by the Fundfor Scientific Research Flanders (FWO-V), the Special Research Fund ofthe University of Antwerp, the Interuniversity Attraction Poles programP6/43 of the Belgian Science Policy Office, the Foundation forAlzheimer’s Research Belgium (SAO/FRMA) and a MethusalemExcellence Grant of the Flemish Government to C.V.B., M.C. and K.S.;by the French National Foundation for Alzheimer’s disease and relateddisorders, the Institut Pasteur de Lille, Institut National de la Sante etde la Recherche Medicale (Inserm), University of Lille Nord de France toJ-C.L. and P.A.; by the German Federal Ministry of Education andResearch and the Cure Alzheimer’s Fund to L.B.; K.S. is a seniorpostdoctoral fellow of the FWO-V.

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The pursuit of susceptibility genes for Alzheimer's disease: progress and prospects

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