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The World Journal of Biological Psychiatry

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Genetics of schizophrenia: A consensus paper ofthe WFSBP Task Force on Genetics

Ina Giegling, Ladislav Hosak, Rainald Mössner, Alessandro Serretti, FrankBellivier, Stephan Claes, David A. Collier, Alejo Corrales, Lynn E. DeLisi, CarlaGallo, Michael Gill, James L. Kennedy, Marion Leboyer, Wolfgang Maier,Miguel Marquez, Isabelle Massat, Ole Mors, Pierandrea Muglia, Markus M.Nöthen, Jorge Ospina-Duque, Michael J. Owen, Peter Propping, YongYongShi, David St Clair, Florence Thibaut, Sven Cichon, Julien Mendlewicz,Michael C. O'Donovan & Dan Rujescu

To cite this article: Ina Giegling, Ladislav Hosak, Rainald Mössner, Alessandro Serretti, FrankBellivier, Stephan Claes, David A. Collier, Alejo Corrales, Lynn E. DeLisi, Carla Gallo, MichaelGill, James L. Kennedy, Marion Leboyer, Wolfgang Maier, Miguel Marquez, Isabelle Massat,Ole Mors, Pierandrea Muglia, Markus M. Nöthen, Jorge Ospina-Duque, Michael J. Owen, PeterPropping, YongYong Shi, David St Clair, Florence Thibaut, Sven Cichon, Julien Mendlewicz,Michael C. O'Donovan & Dan Rujescu (2017): Genetics of schizophrenia: A consensus paperof the WFSBP Task Force on Genetics, The World Journal of Biological Psychiatry, DOI:10.1080/15622975.2016.1268715

To link to this article: http://dx.doi.org/10.1080/15622975.2016.1268715

Published online: 23 Jan 2017.

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WFSBP CONSENSUS PAPER

Genetics of schizophrenia: A consensus paper of the WFSBP Task Force onGenetics

Ina Gieglinga,b , Ladislav Hosakc, Rainald M€ossnerd, Alessandro Serrettie , Frank Bellivierf,g,Stephan Claesh,i, David A. Collierj,k , Alejo Corralesl, Lynn E. DeLisim,n, Carla Galloo, Michael Gillp,James L. Kennedyq,r,s,t , Marion Leboyeru,v,w,x, Wolfgang Maiery, Miguel Marquezz,Isabelle Massataa,ab,ac,ad, Ole Morsae,af, Pierandrea Mugliaag, Markus M. N€othenah,ai, Jorge Ospina-Duqueaj,Michael J. Owenak,al, Peter Proppingam, YongYong Shian,ao,ap, David St Clairaq, Florence Thibautar ,Sven Cichonah,ai,as,at , Julien Mendlewiczau, Michael C. O'Donovanak,al and Dan Rujescua,b

aDepartment of Psychiatry, Psychotherapy, and Psychosomatics, Martin Luther University of Halle-Wittenberg, Halle, Germany;bDepartment of Psychiatry, Ludwig-Maximilians-University Munich, Munich, Germany; cDepartment of Psychiatriy, Charles University,Faculty of Medicine and University Hospital in Hradec Kr�alov�e, Prague, Czech Republic; dDepartment of Psychiatry and Psychotherapy,University of T€ubingen, T€ubingen, Germany; eDepartment of Biomedical and Neuromotor Sciences, University of Bologna, Bologna,Italy; fFondation Fondamental, Cr�eteil, France AP-HP, GH Saint-Louis-Lariboisi�ere-Fernand-Widal, Pole Neurosciences, Paris, France;gEquipe 1, Universit�e Paris Diderot, Paris, France; hGRASP-Research Group, Department of Neuroscience, University of Leuven, Leuven,Belgium; iDepartment of Neurosciences, University Psychiatric Center KU Leuven, Leuven, Belgium; jSocial, Genetic andDevelopmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK; kEli Lilly and Company Ltd, Erl WoodManor, Surrey, UK; lArgentinean Association of Biological Psychiatry, National University, UNT, Buenos Aires, Argentina; mVA BostonHealth Care System, Brockton, MA, USA; nDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA; oDepartamento deCiencias Celulares y Moleculares, Laboratorios de Investigaci�on y Desarrollo, Facultad de Ciencias y Filosof�ıa, Universidad PeruanaCayetano Heredia, Lima, Peru; pNeuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin,Ireland; qNeurogenetics Section, Centre for Addiction and Mental Health, Toronto, ON, Canada; rCentre for Addiction and MentalHealth, Campbell Family Mental Health Research Institute, Toronto, ON, Canada; sDepartment of Psychiatry, University of Toronto,Toronto, ON, Canada; tCollaborative Program in Neuroscience, Institute of Medical Science, University of Toronto, Toronto, ON,Canada; uEquipe Psychiatrie Translationnelle, Facult�e de M�edecine, Universit�e Paris-Est Cr�eteil, Inserm U955, Cr�eteil, France; vDHU Pe-Psy, Pole de Psychiatrie et d'Addictologie, AP-HP, Hopitaux Universitaires Henri Mondor, Cr�eteil, France; wPole de Psychiatrie, HopitalAlbert Chenevier, Cr�eteil, France; xFondation FondaMental, Cr�eteil, France; yDepartment of Psychiatry and Psychotherapy, University ofBonn, Bonn, Germany; zAsistencia, Docencia e Investigaci�on en Neurociencia, Buenos Aires, Argentina; aaUNI - ULB NeurosciencesInstitute, ULB, Bruxelles, Belgium; abNational Fund of Scientific Research (FNRS), Bruxelles, Belgium; acLaboratory of ExperimentalNeurology, ULB, Bruxelles, Belgium; adUR2NF - Neuropsychology and Functional Neuroimaging Research Unit, Centre de RechercheCognition et Neurosciences, Universit�e Libre de Bruxelles (ULB), Bruxelles, Belgium; aePsychosis Research Unit, Aarhus UniversityHospital, Risskov, Denmark; afThe Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; agUCBBiopharma, Brussels, Belgium; ahHead, Institute of Human Genetics, University of Bonn, Bonn, Germany; aiDepartment of Genomics,Life and Brain Center, Bonn, Germany; ajGrupo de Investigaci�on en Psiquiatr�ıa, Departamento de Psiquiatr�ıa, Facultad de Medicina,Universidad de Antioquia, Medell�ın, Colombia; akMRC Centre for Neuropsychiatric Genetics and Genomics, Institute of PsychologicalMedicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK; alNational Centre for Mental Health, CardiffUniversity, Cardiff, UK; amUniversity of Bonn, Bonn, Germany; anBio-X Institutes, Key Laboratory for the Genetics of Developmentaland Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China; aoShandong Provincial KeyLaboratory of Metabloic Disease, The Affiliated Hospital of Qingdao University, Qingdao, P.R. China; apInstitute of Social Cognitive andBehavioral Sciences, Shanghai Jiao Tong University, Shanghai, P.R. China; aqDepartment of Psychiatry, University of Aberdeen,Institute of Medical Sciences, Aberdeen, UK; arINSERM U 894 Centre Psychiatry and Neurosciences, University Hospital Cochin (SiteTarnier), University Sorbonne Paris Cit�e (Faculty of Medicine Paris Descartes), Paris, France; asDivision of Medical Genetics, Departmentof Biomedicine, University of Basel, Basel, Switzerland; atGenomic Imaging, Institute of Neuroscience and Medicine, Research CenterJuelich, Juelich, Germany; auLaboratoire de Psychologie Medicale, Centre Europe�en de Psychologie Medicale, Universite�Libre deBruxelles and Psy Pluriel, Brussels, Belgium

ABSTRACTObjectives: Schizophrenia is a severe psychiatric disease affecting about 1% of the generalpopulation. The relative contribution of genetic factors has been estimated to be up to 80%.The mode of inheritance is complex, non-Mendelian, and in most cases involving the combinedaction of large numbers of genes.Methods: This review summarises recent efforts to identify genetic variants associated withschizophrenia detected, e.g., through genome-wide association studies, studies on copy-numbervariants or next-generation sequencing.

ARTICLE HISTORYReceived 18 November 2016Accepted 29 November 2016

KEYWORDSGenetics; schizophrenia;psychiatry; psychosis;genome; sequencing;polygenic; genetic

CONTACT Dan Rujescu dan.rujescu@uk-halle.de Department of Psychiatry, Psychotherapy, and Psychosomatics, Martin Luther University ofHalle-Wittenberg, Halle, Germany� 2017 Informa UK Limited, trading as Taylor & Francis Group

THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY, 2017http://dx.doi.org/10.1080/15622975.2016.1268715

Results: A large, new body of evidence on genetics of schizophrenia has accumulated overrecent years. Many new robustly associated genetic loci have been detected. Furthermore, thereis consensus that at least a dozen microdeletions and microduplications contribute tothe disease. Genetic overlap between schizophrenia, other psychiatric disorders, and neurodeve-lopmental syndromes raised new questions regarding the current classification of psychiatric andneurodevelopmental diseases.Conclusions: Future studies will address especially the functional characterisation of genetic var-iants. This will hopefully open the doors to our understanding of the pathophysiology of schizo-phrenia and other related diseases. Complementary, integrated systems biology approaches togenomics, transcriptomics, proteomics and metabolomics may also play crucial roles in enablinga precision medicine approach to the treatment of individual patients.

Heritability of schizophrenia

Evidence for a strong genetic component to the aeti-ology of schizophrenia was first demonstrated by clas-sical genetic epidemiology in the form of family, twin,and adoption studies (Cardno & Gottesman 2000;Sullivan et al. 2003; Wray & Gottesman 2012) and hasmore recently been confirmed by molecular genetics(Gusev et al. 2014). While the lifetime risk in the popula-tion for developing schizophrenia varies within coun-tries, the overall rate is estimated at around 0.5–1%. Riskfor an individual increases non-linearly with the degreeof genetic relatedness to a person suffering from thedisorder; for third-degree relatives it is approximately2% rising to approximately 9% for first-degree relatives,or, in the case of the children of two affected parents,around 27% (Gottesman et al. 2010). For monozygotic(MZ) twins, the concordance rate is approximately 50%(Lichtenstein et al. 2006, 2009). For adopted childrenwith a biological parent with schizophrenia the risk ofdeveloping schizophrenia is 6–10 times higher than inthe general population (Shih et al. 2004).

Altogether, the heritability of schizophrenia is esti-mated to be between 64 and 81% (Sullivan et al.2003; Lichtenstein et al. 2009). Large amounts of gen-etic variations contribute to the disorder making themode of inheritance complex. Only a small proportionof these DNA variants have been identified so far andit is now clear that genetic susceptibility is the resultof many common variants of low penetrance, somerare variants of moderately high penetrance (Kendler2015; Schizophrenia Working Group of the PsychiatricGenomics Consortium 2014) as well as presumablyuncommon and rare variants of small to moderatelyhigh effect that cannot be detected individually insample sizes studied to date. Progress in understand-ing the genetics of complex disease is closely tied totechnological developments. The potential of thosetechnologies, which include arrays capable of detect-ing millions of common variants as well as large struc-tural variations, and newer sequencing technologies,has led to an explosion of findings in human genetics

as a field. In parallel with the technological capabil-ities, approaches to complex disease genetics hasextended from linkage studies to candidate associationstudies, genome-wide association (GWA) studies and,currently, to exome or whole-genome sequencing.

Linkage studies

Linkage studies are based on the fact that genetictraits located closely together on a chromosome aremore likely to segregate together, that is, be co-inher-ited in families, than are genetic variants located fur-ther apart. Linkage is most powerful under models ofgenetic transmission whereby genes of major effectcause disease in all affected family members. For com-mon diseases this may not be the case and multiplyaffected families may mimic Mendelian architecture.Early linkage studies suggested involvement of a majorrisk allele on chromosome 5 [5q11.2 to 5q13.3](Bassett et al. 1988; Sherrington et al. 1988), but thatfinding has not been extensively replicated (Kennedyet al. 1988; St Clair et al. 1989). One of the largestmeta-analyses was provided by Ng et al. (2009),including 32 independent genome-wide linkage scansand a total of 3,255 pedigrees and 7,413 genotypedcases affected with schizophrenia or related disorders.The results pointed to evidence for linkage on 5q(142–168Mb) and 2q (103–134Mb). A secondary ana-lysis restricted to the studies based on families ofEuropean ancestry provided suggestive evidence forlinkage on chromosome 8p (16–33Mb) (Ng et al.2009). So far these linkage studies failed to conclu-sively identify any susceptibility gene, although somerecent meta-analyses showed partial overlap for5p14.1 and 10q26.12 (Vieland et al. 2014).

Candidate gene studies

As methods of DNA amplification were developed,association studies became more feasible (Mullis et al.1986; Mullis et al. 1994). These were mainly based on

2 I. GIEGLING ET AL.

case–control analysis of single-nucleotide polymor-phisms (SNPs) within candidate genes derived fromneurobiological hypotheses. Gatt et al. (2015) pre-sented a review of meta-analyses based on candidategenes. From a total of 97 variants reported in schizo-phrenia, the strongest evidence (P< 0.001) wasreported for genes involved in the modulation ofdopamine (e.g., COMT, DRD2, DRD3 and DRD4), glu-tamate (e.g., DAOA, GABRB2 and NRG1), neuronaldevelopment and function (e.g., AHI1, MTHFR, RELNand TRKA), serotonin neurotransmission (HTR2A,SLC6A4 and TPH1) or the immune system (IL1B). Theauthors focussed not only on schizophrenia but onspecific mental disorders that have core disruptions toemotional and cognitive function and contribute mostto burden of illnesses including major depressive dis-order (MDD), anxiety disorders (including panic dis-order and obsessive compulsive disorder),schizophrenia, bipolar disorder (BD) and attention def-icit hyperactivity disorder (ADHD). A total of 1,519meta-analyses were conducted across 157 studiesreporting multiple genes implicated in one or more ofthe five disorders. A total of 134 genes (206 variants)were identified as significantly associated risk variants.Thirteen genetic variants were shared in commonbetween two or more disorders (APOE, ACE, BDNF,COMT, DAOA, DAT1, DRD4, SLC6A4, HTR1A, MTHR,MTHR and TPH1) demonstrating evidence for pleiotro-phy (Gatt et al. 2015). Nevertheless, the significancethreshold was not as strict as applied for genome-wide studies indicating that there could be spuriousassociations among these genes. Another drawback isthat there tends to be a publication bias towards ori-ginal articles reporting on positive findings, and onlythese could be used for meta-analyses.

GWA studies

Due to technical developments in array genotyping,research is no longer limited to testing a small numberof candidate variants in sample sizes that are under-powered to detect the small effect sizes of commonvariants we now know to typically associate with com-plex diseases. Array genotyping instead makes it pos-sible to conduct GWA studies which extractinformation for more than 10 million SNPs per samplein a single experiment. That implies that stringent cor-rection for multiple testing has to be performed and,as discussed later, power to detect associations at thegenome wide significance threshold is incompleteeven in the largest studies to date and therefore manyof the hits not reaching genome-wide significancemay turn out to be true associations in larger samples.

From a technical point of view, association with alocus not necessarily implicates a particular gene butrather a region, each with a small effect size.

The first GWA studies on schizophrenia performedin 2007/2008 were clearly underpowered, including178 cases, 144 controls (Lencz et al. 2007) and 738cases, 733 controls, respectively (Sullivan et al. 2008).The problem of insufficient power to detect genome-wide significant markers directly was addressed byO’Donovan et al. (2008) by using top markers(P< 10�5) from an initial GWA study on 479 cases and2,937 controls, as candidates to be followed up in anindependent replication cohort of up to 6,829 casesand 9,897 controls. Three out of 12 loci were shown tohave a strong independent support, and the overallpattern of replication was unlikely to occur by chance.Most interestingly, evidence for association at the topSNP which maps to a locus containing the geneZNF804A, strengthened when the affected phenotypeincluded BD, which challenges the traditional diagnos-tic boundaries (O'Donovan et al. 2008). The study ofStefansson et al. (2009) used basically the sameapproach. A GWA study performed with 2,663 casesand 13,498 controls from eight European locationswithin the SGENEþ consortium revealed no genome-wide significant signal. The findings for the top 1,500SNPs were combined with results for these SNPs (orproxies) from two independent cohorts (2,602 cases/2,885 controls from the International SchizophreniaConsortium (ISC), and 2,687 cases/2,656 controls fromthe European-American portion of the MolecularGenetics of Schizophrenia Consortium (MGS)). Themost significant association signals were followed upin 5,013 cases and 15,559 controls from four additionalsample sets from Europe, leading to the identificationof three novel candidate schizophrenia loci: NRGRN(coding for neurogranin), TCF4 (coding for transcrip-tion factor 4) and the major histocompatibility com-plex (MHC) region (Stefansson et al. 2009). At thesame time the ISC and the MGS reported GWA studiesof the MHC region (International SchizophreniaConsortium 2009; Shi et al. 2009).

As power and, therefore, sample size is the mostlimiting factor in GWA studies, a new consortium, thePsychiatric Genome Wide Association StudyConsortium (PGC) started a highly successful initiativeto collect existing GWAS data from as many schizo-phrenia cases and controls as possible. The first publi-cation in 2011 contained a total sample of more than51,000 individuals of European ancestry. Genome-widesignificant association was identified for seven loci,five representing novel loci (1p21, 2q32.3, 8p23.2,8q21.3 and 10q24.32-q24.33) and two with previous

THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 3

implication (6p21.32-p22.1 and 18q21.2). The strongestnew finding was for rs1625579, located within anintron of a putative primary transcript of microRNA137 (MIR137), which is involved in regulation of neur-onal development. Supporting a role of MIR137 dysre-gulation as a previously unknown aetiologicalmechanism in schizophrenia was the finding that add-itional markers in four predicted targets of MIR137also showed genome-wide significant P values.Combining the schizophrenia sample with a BD sam-ple (16,374 cases and 14,044 controls) led to the iden-tification of three loci that confer susceptibility to bothBD and schizophrenia, i.e. CACNA1C, ANK3 and theITIH3-ITIH4 region (Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium 2011).Given the large sample, the yield of five new locimight be considered disappointing, but a follow-upstudy by Hamshere et al. (2013) demonstrated, in anindependent sample, that the vast majority of the 81associations in the PGC study that met an intermediatethreshold of significance (P< 10�5) represented trueassociations, providing a robust rationale for expand-ing the GWAS to larger samples. Moreover, when theycombined their small (in current GWAS terms) samplewith those of the PGC, they identified three additionalgenome wide significant loci, stressing the cumulativevalue of building up the large datasets.

In 2013, Ripke et al. re-analysed the PGC schizophre-nia data using 1000 Genomes imputation and con-ducted a study comprising an initial analysis based on5,001 cases and 6,243 controls followed by meta-ana-lysis with previous schizophrenia GWAS data (8,832cases and 12,067 controls) and finally by replication ofSNPs in up to 168 genomic regions in independentsamples (7,413 cases, 19,762 controls and 581 parent-offspring trios). Of the 22 loci associated at genome-wide significance level, previous reports had been pub-lished for seven loci with schizophrenia alone (MHC,WBP1L/C10orf26, DPYD-MIR137, SDCCAG8 and MMP16,CACNA1C, and ITIH3-ITIH4), one with a combinedphenotype consisting of schizophrenia and BD(CACNB2), and one with BD (NCAN). The remaining 13newly identified loci consisted of regions includingMAD1L1, TSNARE1, SNX19, QPCT, SLC06A1, ZEB2,FONG, C2orf82, AKT3, C12orf65 as well as loci nearGRIA1, TCF4 and ZSWIM6. Examination of candidateregions suggested the involvement of neuronal calciumsignalling, the MHC region, which showed the highestsignificance, MIR137 (dys)regulation via target sites andepigenetic regulation, and development through longintergenic non-coding RNAs (Ripke et al. 2013).

The latest and largest GWAS on schizophrenia waspublished in 2014 by the schizophrenia PGC team

featuring a multi-stage GWA study of 36,989 cases and113,075 controls. A total of 128 associations in 108 inde-pendent loci were identified, with the strongest associ-ated locus being an extended region of chromosome 6containing a large number of genes including the MHCregion (P¼ 3.48� 10–31) (Schizophrenia Working Groupof the Psychiatric Genomics Consortium 2014; bioinfor-matic data for the 108 loci is found in theSupplementary Information). Novel associations wereobserved for 83 loci not necessarily implicating a genebut rather a region. Associations were enriched amonggenes showing epigenetic markers indicative of expres-sion in the brain. Interestingly, a number of loci contain-ing former known candidate genes like DRD2 andseveral genes involved in glutamatergic neurotransmis-sion (GRM3, GRIN2A, SRR and GRIA1) reached genome-wide significance, supporting gene products of knownand potential therapeutic relevance to schizophrenia,and broadly supporting leading pathophysiologicalhypotheses of the disorder. The PGC study also reportedevidence that associations were enriched in genesexpressed in tissues relevant to immunity, although amore sophisticated re-analysis of the data failed to sup-port this, confirming only the enrichment for brain-expressed genes (Finucane et al. 2015).

The most consistent result throughout the GWAS ofschizophrenia is the association to the extended MHCregion. This was found in several independent samplesof moderate (International Schizophrenia Consortium2009; Stefansson et al. 2009; Shi et al. 2009; IrishSchizophrenia Genomics Consortium and theWellcome Trust Case Control Consortium 2 2012) tolarge sizes (Ripke et al. 2013; Schizophrenia WorkingGroup of the Psychiatric Genomics Consortium 2014).Interestingly, allelic variation at the Complement com-ponent C4A locus, which is located in the MHC region,explains part of the heritability of schizophrenia. Thereis evidence that C4A is involved in synaptic plasticity,providing a potential functional explanation for theinvolvement of the immune system in schizophreniapathogenesis (Sekar et al. 2016).

Polygenic risk scores

GWA studies have provided strong evidence that psy-chiatric disorders are highly polygenic, with a geneticarchitecture consisting of many common genetic var-iants. As discussed later, rare risk variants are alsoinvolved. To achieve genome-wide significance, P val-ues have to pass a stringent threshold. It is estimatedthat in common variant GWAS, around 1 million inde-pendent association tests are conducted and thethreshold for significance after multiple testing is

4 I. GIEGLING ET AL.

therefore 0.05/1 million or 5� 10�8 (NCI-NHGRIWorking Group on Replication in Association Studies2007). Attaining this for alleles of small effect requiresvery large sample sizes of many tens of thousands ofpatients and controls. Interestingly, although the totalnumber of loci surpassing the genome-wide signifi-cance threshold is often small (or even zero in smallstudies), the GWAS typically yield many more associa-tions with small P values than expected by chance.This finding is consistent with a polygenic geneticarchitecture, and provided the impetus for new statis-tical methods (Wray et al. 2014). Two frequentlyapplied methods are “polygenic risk scoring” and“estimating variance explained by all SNPs” (for detailssee Wray et al. 2014).

The first genomic profile risk scoring for schizophre-nia was reported by the International SchizophreniaConsortium (2009). This study provides evidence for apolygenic component to risk of schizophrenia involv-ing at least 1,000 common alleles of very small effect(Nagelkerke R2¼0.032; a measure of variance in case–control status explained). Furthermore, the risk profilescore was also associated with risk of BD, but not tomultiple non-psychiatric diseases.

Within the much larger PGC-schizophrenia samplethe R2 increased to 0.184. Under the assumption of aliability-threshold model, a lifetime risk of 1%, inde-pendent SNP effects and adjusting for case–controlascertainment, the polygenic risk score explained about7% of variation on the liability scale to schizophreniaacross the samples, about half of which (3.4%) isexplained by genome-wide significant loci in this study(Schizophrenia Working Group of the PsychiatricGenomics Consortium 2014). Many other studies usingpolygenic risk scores have been conducted, includingcross-disorder overlaps, schizophrenia symptoms orphenotypes (for review see Wray et al. 2014). Given thatpolygenic scores represent biomarkers (Schmitt et al.2016) that tap into liability to the disorder even inunaffected people, we anticipate they will becomemore and more important in research, although to date,they do not capture enough risk to be clinically useful.

Identification of rare risk variants before GWAstudies

Up to the mid-2000s, the only genetic variant defini-tively known to contribute to schizophrenia was amicrodeletion at chromosome 22q11.2. The deletionregion contains over 40 genes including a number ofplausible candidates like COMT (catechol-O-methyltransferase), ProDH, TBX1 and GNB1L, which areknown to be involved in brain function and

neurodevelopment (Raux et al. 2007; Squarcione et al.2013; Schneider et al. 2014). However, despite severalstudies that have tried to do so, it has not proven pos-sible to identify which gene(s) within 22q11.2 explainthe link between deletion of this region and schizo-phrenia. Also worth noting from the pre-GWAS era isDisrupted-in-Schizophrenia-1 (DISC1), another key his-torical candidate gene that has been widelyresearched. DISC1 was identified as being disrupted byone of two chromosomal breakpoints (Millar et al.2000) involved in a balanced translocation betweenchromosome 1 and chromosome 11 (1;11)(q42.1;q14.3)that co-segregates with multiple forms of psychiatricdisorder in a single large Scottish pedigree (St Clairet al. 1990; Muir et al. 2008). Although the eponymousbut, given the range of phenotypes exhibited in familymembers, somewhat inaccurately named DISC1 genehas plausibility given it has been shown to disruptnumerous important functions of the brain (Porteouset al. 2014; Randall et al. 2014), additional evidencebeyond co-segregation is required to decisively impli-cate this gene in major mental illness.

Copy number variants identified through GWAstudies

It was originally possible to link the 22q11.2 deletionto schizophrenia because the same mutation alsocauses a recognisable genomic syndrome called velo-cardiofacial syndrome (VCFS) or DiGeorge syndrome,and it had been observed that those individuals withVCFS had high rates of psychosis (Shprintzen et al.1992; Pulver et al. 1994). In the mid-2000s, techno-logical developments, particularly those that allowGWAS studies, started to fill the resolution gapbetween the traditional cytogenetic analysis (>2Mb)and mutation analysis by DNA sequencing (<1 kb),making it possible to perform systematic scans of thegenome for chromosomal microdeletions and duplica-tions (collectively known as copy number variants orCNVs) without any prior knowledge of phenotypic co-morbidity between schizophrenia and a particular gen-omic syndrome (see Table 1).

A number of investigators (Kirov et al. 2008; Walshet al. 2008; Xu et al. 2008) were prompted to screen pro-band–parent trios for newly occurring or de novo muta-tions, the idea being that the loss of schizophrenia riskalleles resulting from the reduced fecundity of peoplewith the disorder must be counter-balanced by theoccurrence of new mutations unless the disorder wasvanishing in the population. Early support for theinvolvement of CNVs was obtained in all these studies,but none was powered to convincingly implicate any

THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 5

specific CNVs due to insufficient sample size. However,these were rapidly followed by two larger studies, oneby the SGENEþ consortium and one by the ISC. In a firststep the SGENEþ consortium analysed 9,878 individualsfor transmission from parents to descendant(Stefansson et al. 2008). The study identified 66 novelCNVs which were tested for association in a subsequentcase–control study. Three deletions (1q21.1, 15q11.2and 15q13.3) showing nominal association in the firstsample were followed-up in a second sample of 3,285cases and 7,951 controls. The combined sample showedenrichment of all three microdeletions. Two of these,deletions at 15q13.3 (containing the nicotinergic alpha7 gene) and 1q21.1, were independently identified inthe ISC study, which analysed 3,391 schizophreniapatients and 3,181 controls (International SchizophreniaConsortium 2008). Moreover, in the ISC study, comparedto controls, patients with schizophrenia had a 1.15-foldincrease of rare CNVs (frequency less than 1% in thisstudy) of more than 100 kb in length. Together, thesestudies decisively confirmed a collective enrichment ofrare CNVs in schizophrenia patients and identified spe-cific CNVs associated with risk of the disorder. The dele-tion identified by SGENEþbut not the ISC, that at15q11.2, was subsequently confirmed in the ISC andother data by Kirov et al. (2009a), and overall evidencefor all three loci is beyond doubt in a recent meta-ana-lysis (Rees et al. 2014).

Additional deletions significantly associated withschizophrenia at 3q29 (Levinson et al. 2011; Mulle et al.2010), 16p11.2 (Guha et al. 2013), 17p12 (Kirov et al.2009a) and 17q12 (Moreno-De-Luca et al. 2010) werereplicated in the meta-analysis by Rees et al. (2014),with 3q29 showing highest ORs (OR¼ 57.65).Additional CNV studies suggested a role for the neu-rexin 1 gene (NRXN1; 2p16.3). Deletions within this

gene previously associated with autism have also beenreported in two families with schizophrenia (Kirovet al. 2008; Walsh et al. 2008). In a study conducted bythe SGENEþ consortium using 2,977 schizophreniapatients and 33,746 controls, NRXN1 CNVs (>100 kb)disrupting exons were significantly enriched in cases(0.24 vs. 0.015% in controls) with an odds ratio of 8.97(Rujescu et al. 2009). A meta-analysis in 8,789 casesand 42,054 controls further supports these results(Kirov et al. 2009b). Significant associations with dele-tions were also reported by Levinson et al. (2011) andin a recent meta-analysis by Rees et al. (2014). Severalstudies supported not only the role of deletions butalso of duplications in the development of schizophre-nia. Within the SGENEþ consortium, a 15q11-q13(Ingason et al. 2011a) and a 16p13.11 duplication(Ingason et al. 2011b) were identified. Both of them, aswell as a duplication at 16p11.2 (McCarthy et al. 2009;Levinson et al. 2011; Steinberg et al. 2014), were con-firmed in the Rees et al. (2014) meta-analysis. Severalother loci could not be confirmed by this meta-ana-lysis and are subject of further investigation: 1q21.1(Levinson et al. 2011), 7q11.23 associated with William-Beuren syndrome (Kirov et al. 2012; Mulle et al. 2014)and 7q36.3 containing VIPR2, a neuropeptide receptorgene (Levinson et al. 2011; Vacic et al. 2011).

CNVs enriched in psychosis are also involved in thepathology of other neurodevelopmental and neuro-logical disorders, including intellectual disability, autismand seizures (Grayton et al. 2012; Grozeva et al. 2012).Within the group of 1q21.1 deletion carriers, psychiatricand behavioural abnormalities can include epilepsy,autism or ADHD (Haldeman-Englert & Jewett1993–2016; de Kovel et al. 2010; Sanders et al. 2015).Neurexin 1 deletions are also associated with autismspectrum disorders, intellectual disability, language

Table 1. Microdeletions and microduplications involved in schizophrenia.Replicationa Meta-Analysisa

Deletions1q21.1b Stefansson et al. 2008; International Schizophrenia Consortium 2008; Levinson et al. 2011 0.0027 4.1 x 10–13

2p16.3 Kirov et al. 2008; Walsh et al. 2008; Rujescu et al. 2009; Kirov et al. 2009b 7.7� 10-04 1.3� 10–11

3q29 Mulle et al. 2010; Levinson et al. 2011 0.074 1.5� 10–9

15q11.2b Stefansson et al. 2008; Kirov et al. 2009a 0.046 2.5� 10–10

15q13.3b Stefansson et al. 2008; International Schizophrenia Consortium 2008; Levinson et al. 2011 0.38 4.0� 10–10

16p11.2b Walsh et al. 2008; Guha et al. 2013 1.0 0.01717p12 Kirov et al. 2009a 0.55 0.001217q12 Moreno-De-Luca et al. 2010 0.52 0.0072

Duplications1q21.1b Levinson et al. 2011 0.35 9.9� 10–5

7q11.23 Kirov et al. 2012; Mulle et al. 2014 0.35 6.9� 10–5

7q36.3 Levinson et al. 2011; Vacic et al. 2011 0.99 0.2715q11-13b Kirov et al. 2008; Ingason et al. 2011a 0.0055 5.6� 10–6

16p11.2b Walsh et al. 2008; McCarthy et al. 2009; Levinson et al. 2011: Steinberg et al. 2014 2.3� 10-08 2.9� 10–24

16p13.11 Kirov et al. 2009a; Ingason et al. 2011b 0.056 5.7� 10–5

aRees et al. (2014), replication study: cases, n¼ 6.882; controls n¼ 6.316.bRegion with both deletions and duplications.

6 I. GIEGLING ET AL.

delays (Schaaf et al. 2012), developmental delay orintellectual disability (Jenkins et al. 2016). Very similaroverlaps are seen for the 15q11.2 region includingintellectual disability, developmental delay, neuro-logical problems, autism, attention problems andspeech delay (Abdelmoity et al. 2012; Derks et al.2013). Similarly, the 15q13.3 CNVs are present in mul-tiple neurodevelopmental syndromes that cause intel-lectual disability, epilepsy and variable facial anddigital dysmorphisms. Interestingly, the discovered denovo deletions in this region have also been shown togive rise to a number of other phenotypes, includingabnormal EEG, significant expressive language deficits,and a spectrum of neuropsychiatric impairments thatinclude autism, ADHD, anxiety disorder, mood disorderand cognitive impairment (Helbig et al. 2009;Pagnamenta et al. 2009; Adams et al. 2012; Williamset al. 2012; Isles et al. 2016).

Other studies have continued to pursue de novomutations in schizophrenia (e.g., Kirov et al. 2012;Malhotra & Sebat 2012). Both provide an estimated ratefor large de novo CNVs in schizophrenia of about 5%,2–3 times higher than that of controls. Based on themeta-analysis of Rees et al. (2014) the question arisesconcerning the implications of the CNV findings forgenetic counselling. Out of 15 previously implicatedCNV loci, 11 were strongly associated in this meta-ana-lysis. The evidence for the remaining four loci is stillequivocal and requiring further investigation. Thesefindings indicate that approximately 2.5% of individualswith schizophrenia carry at least one known pathogenicCNV. The odds ratios for schizophrenia range betweenapproximately 2 and more than 50. As noted above,most are also found in a range of other neurodevelop-mental disorders, including epilepsy (15q11.2 and15q13.3), autism and intellectual disability. As Reeset al. (2014) postulated, a number of the pathogenicCNVs are associated with particular physical diseasephenotypes including congenital heart disease (1q21.1and 22q11.2), microcephaly (1q21.1, 3q29 and 16p11.2)and obesity (16p11.2 distal). These findings suggestthat screening for CNVs should be considered at leastin the case of non-brain-related physical comorbidity.These results have the potential to directly guide every-day clinical patient care (Rees et al. 2014).

Kirov et al. (2012) noted multiple de novo CNVsspanned components of the post-synaptic density(PSD). This was largely explained by enrichment formembers of the N-methyl-D-aspartate receptor(NMDAR) and neuronal activity-regulated cytoskeleton-associated protein (ARC) postsynaptic signalling com-plexes; both known to be important in synaptic plasti-city and cognition. They also found recurrent CNVs

affecting EHMT1, a histone methyl transferase knownto directly regulate DLG family members and othercomponents of the PSD. Large-scale follow-up case–control analyses (Pocklington et al. 2015) have con-firmed the enrichments for schizophrenia-related CNVsin PSD, ARC and NMDAR complexes, and haveextended this to implicate inhibitory post-synapticGABAergic complexes, which have strong functionallinks in regulating synaptic plasticity with the majorexcitatory glutamatergic system.

As overlapping genes affected by rare variants andthose localised within the associated GWAS loci alsoshow convergence in terms of functional clustering itseems likely that common and rare variant studies arecomplementary rather than antagonistic, and thatmechanistic studies driven by rare genetic variationwill be informative for schizophrenia (SchizophreniaWorking Group of the Psychiatric GenomicsConsortium 2014). The latest CNV analysis on 41,321subjects observed a global enrichment of CNV burden(OR¼ 1.11, P¼ 5.7 � 10-15). CNV burden was especiallyenriched for genes associated with synaptic function(OR¼ 1.68, P¼ 2.8 � 10-11) and neurobehavioral phe-notypes in mouse (OR¼ 1.18, P¼ 7.3 � 10-5). Genome-wide significant evidence was obtained for eight loci,including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2,15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2(CNV and Schizophrenia Working Groups of thePsychiatric Genomics Consortium & PsychosisEndophenotypes International Consortium, 2016).

Next generation sequencing

Major developments in sequencing technology havetaken place in the last years, enabling rapid andincreasingly economical whole-exome or whole-gen-ome sequencing. These sequencing methods can, e.g.,be applied for case–control studies or for the detec-tion of de novo mutations by sequencing bothunaffected parents and the affected child. A study byXu et al. (2011) sequenced the exomes of 53 trios withsporadic cases and their unaffected parents, as well as22 unaffected controls trios. They identified 40 denovo mutations in 27 cases affecting 40 genes, includ-ing a potentially disruptive mutation in DGCR2, a genelocated in the schizophrenia-predisposing 22q11.2microdeletion region. A follow-up study by the samegroup sequenced 795 exomes from 231 parent–pro-band trios enriched for sporadic schizophrenia cases,as well as 34 unaffected trios. They observed an excessof de novo nonsynonymous single-nucleotide variantsas well as a higher prevalence of gene-disruptive denovo mutations relative to controls. They found four

THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 7

genes (LAMA2, DPYD, TRRAP and VPS39) affected byrecurrent de novo events, which is unlikely to haveoccurred by chance (Xu et al. 2012). Moreover, a denovo deletion of DPYD had first been found in autism(Marshall et al. 2008).

Interestingly, a de novo mutation in another mem-ber of the laminin gene family, LAMA1 was describedin another schizophrenia sequencing study reportedby Girard et al. (2011).

Exome sequencing of genomic DNA carried out for399 persons, including 105 probands with schizophre-nia, 84 unaffected sibs and their 210 unaffectedparents was performed by Gulsuner et al. (2013). Theresults suggest that disruptions of foetal prefrontalcortical neurogenesis may be critical to the patho-physiology of schizophrenia (Gulsuner et al. 2013).McCarthy et al. (2014) carried out exome sequencingon 57 trios with sporadic or familial schizophrenia. Insporadic trios, they observed an �3.5-fold increase inthe proportion of nonsense de-novo mutations. Genesat these loci overlapped with genes implicated in aut-ism (e.g., AUTS2, CHD8 and MECP2) and intellectualdisability (e.g., HUWE1 and TRAPPC9), supporting ashared genetic aetiology between these disorders.Functionally, CHD8, MECP2 and HUWE1 converge onepigenetic regulation of transcription suggesting thatthis may be an important risk mechanism.

The largest individual de novo trios and case–controlsequencing studies of schizophrenia so far were those,respectively, of Fromer et al. (2014) and Purcell et al.(2014). Fromer et al. (2014) obtained further evidencefor shared genetic aetiology between schizophrenia andboth intellectual disability and ASD by testing for over-lap of genes affected by de novo loss-of-function muta-tions in schizophrenia, ASD and intellectual disability.The study shows an overlap between schizophrenia,ASD and intellectual disability at the resolution not justof loci or even individual genes, but even of mutationswith similar functional (loss-of-function) effects.

Although Fromer et al. (2014) were unable to confirmthe findings from some of the smaller studies that, atthe genome wide level, cases are enriched for small denovo mutations, they did find that this type of mutationwas overrepresented among the same complexes impli-cated by de novo CNVs, specifically the ARC andNMDAR complexes. Mutations were additionallyenriched in messenger RNAs that are targets of fragile Xmental retardation protein (FMRP). Purcell et al. (2014)identified a polygenic burden arising from very rare (fre-quency less than 1 in 1,000 chromosomes) mutationsand that, once again, these were enriched among ARC,NMDAR and PSD protein complexes as well as FMRP tar-gets and calcium channel complexes. Despite their size,

neither of these studies was able to implicate specificgenes. However, very recently, the UK10K group, in col-laboration with many of the other groups, has done soby meta-analysis of their own case–control and de novomutation datasets with much of the data referred toabove in this section. This study (Singh et al. 2016),which included a total of 4,264 schizophrenia cases,9,343 controls and 1,077 parent–proband trios, obtainedgenome-wide significant association (P¼ 5.6� 10�9)between schizophrenia and a rare loss-of-functionvariant in SETD1A a histone methyl-transferase, whichthe group also showed was implicated in othersevere developmental disorders. The finding estab-lishes histone methylation pathways in the pathogen-esis of the disorder, and establishes overlap betweenschizophrenia and other neurodevelopmental disor-ders at the level of a specific highly penetrant recur-rent mutation in a single gene.

Gene� environment effects

Besides the genetics of schizophrenia, gene–environ-ment interactions and epigenetic studies seem promis-ing (van Dongen & Boomsma 2013; Agerbo et al. 2015;Owen et al. 2016). A gene–environment interaction(G� E) represents a genetic influence on vulnerabilityto environmental factors (Rutter et al. 2006). A compre-hensive review of G� E interactions in schizophreniawas presented by van Os et al. (2008). However, so far,thorough replication of findings is rare and G� Eresearch still faces several conceptual and methodo-logical challenges (EU-GEI 2014). Published environ-mental exposures for psychosis for which G� E hasbeen suggested include complications of pregnancy,paternal age, urban environment, cannabis use, migra-tion and childhood maltreatment. Urbanicity, migration,a lack of social support and negative expressed emo-tions are considered as proxies for environmental stres-sors. Van Winkel et al. (2008) reviewed the role ofpsychosocial stress in the development of positivepsychotic symptoms (hallucinations or delusions). Theauthors asserted the concept of “behaviouralsensitisation”, meaning that repetitive stress progres-sively increases the biological and behavioural (psycho-pathological) response to subsequent exposure. Thesubstrate for this effect was postulated to be a dysregu-lation of the hypothalamic-pituitary-adrenal (HPA) axis,namely elevated plasma cortisol contributing to thehypothesised final common pathway of dopaminerelease and sensitisation in the mesolimbic brain area.Polymorphisms of the genes related to catecholamineneurotransmission, neuroplasticity and stress activation(e.g., COMT, DA receptors, BDNF and the HPA axis) may

8 I. GIEGLING ET AL.

influence the extent of the sensitisation process thoughthe genetic findings concerning G� E in schizophreniaare not yet widely considered to be robust. A reviewand meta-analysis of the role of life events in psychosiswas carried out by Beards et al. (2013). The meta-ana-lysis yielded an OR of 3.19. Miller et al. (2013) reviewedrelevant human studies related to prenatal inflamma-tion and risk of schizophrenia. The authors concludedthat inflammation may be associated with abnormalneurodevelopment. Epigenetics (DNA methylation, his-tone/chromatin modifications and non-coding RNA) isrelated to potentially heritable or acquired changes ingene expression and function that are not caused byvariation in the DNA sequence (Perkins et al. 2005; Szyf2015). Epigenetic DNA status may be partially heritable,but during an individual�s life may also be modified by abroad spectrum of environmental stimuli (e.g., alimen-tation, toxins, stress or medication) (Waterland & Jirtle2003). They may be different in different tissues or evendifferent regions in the brain in the same subject. Theymay contribute to phenotypical differences in MZ twins(Wong et al. 2005). The first studies on epigeneticmechanisms in schizophrenia aetiopathogenesis havealready been performed (e.g., for review see Akbarian2014). Based on a review, Maric and Svrakic (2012)

suggest that epigenetic misregulation of the genomeand direct CNS injury are probably the main mecha-nisms to mediate prenatal environmental effects (e.g.,viruses, ethanol or nutritional deficiency), whereas post-natal risk factors (e.g., stress, urbanicity or cannabis use)may also affect risk via potentiation of vulnerable CNSpathways implicated in schizophrenia (Pelayo-Teranet al. 2012). A review of empirical G� E studies usingcandidate genes in schizophrenia was published byModinos et al. (2013).

For future G� E research in schizophrenia, it wouldbe better to assess environmental variables quantita-tively in a prospective way. The timing of environmen-tal events is also important. Dimensions ofschizophrenia should be monitored quantitatively.Important genes previously found in the GWA schizo-phrenia studies should be applied in G� E researchinto schizophrenia as well as schizophrenia endophe-notypes. Epigenetic variables should likewise bestudied (Moffitt et al. 2005; Jaffee & Price 2007; van Oset al. 2008; van Os & Rutten 2009; Modinos et al. 2013;Svrakic et al. 2013; EU-GEI 2014; Uher 2014).

In summary, well-powered and designed studies ofG� E interactions and epigenetic studies are stillmissing.

Figure 1. Risk factors of schizophrenia.

THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 9

Conclusion/outlook

The last few years resulted in the establishment ofmajor new contributions to our knowledge of schizo-phrenia. The systematic identification of genetic var-iants throughout the genome opened new avenues tothe biology of the disease. GWA studies identified newloci containing genes involved in pathophysiology.One interesting aspect is that the genetic overlapbetween schizophrenia and BD which has beendebated upon for decades could be demonstrated onthe molecular level. Many studies are under way tocharacterise these genetic variants and to find path-ways of the disease. A next major milestone was thediscovery of multiple microdeletions and microduplica-tions involved in schizophrenia. It became clear thatstructural genetic variants also contribute to the dis-ease, making them highly interesting targets for newpharmaceuticals. Especially interesting is the majoroverlap regarding the expressivity and thus clinicalpresentation or particular deletions or duplications.There is a whole neurodevelopmental spectrum includ-ing, besides schizophrenia, e.g., autism, intellectual dis-ability, developmental delay, attention problems andspeech delay, sometimes in combination with otherphysical manifestations. This observation raised manynew questions regarding the diagnostic criteria of psy-chiatric diseases and the current classification in gen-eral. Although still in its infancy, whole-genomesequencing of large samples will become the standardin genetic research in the very near future. The hopeis to detect even very rare variants that are possiblyresponsible for subsamples or subtypes of the dis-eases. Furthermore, integrated systems biologyapproaches integrating genomics, epigenomics, tran-scriptomics, proteomics and metabolomics may furthercontribute to the identification of the pathways contri-buting to schizophrenia, enabling a precision medicineapproach to the treatment of individual patients.Whole-genome sequencing of very large samples andsystem biology applications have the potential to leadto the desperately needed precision medicine in indi-vidual patients.

Disclosure statement

The authors report no conflicts of interest. The authors aloneare responsible for the content and writing of this article.

ORCID

Ina Giegling http://orcid.org/0000-0001-8407-7512Alessandro Serretti http://orcid.org/0000-0003-4363-3759David A. Collier http://orcid.org/0000-0003-4087-1559

JamesL. Kennedy http://orcid.org/0000-0002-8733-3806Florence Thibaut http://orcid.org/0000-0002-0204-5435Sven Cichon http://orcid.org/0000-0002-9475-086XDan Rujescu http://orcid.org/0000-0002-1432-313X

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