Molecular Psychiatry (2013) 18, 38 -- 52 & 2013 Macmillan Publishers Limited All rights reserved 1359-4184/13 www.nature.com/mp

EXPERT REVIEW The emerging spectrum of allelic variation in schizophrenia: current evidence and strategies for the identification and functional characterization of common and rare variants

BJ Mowry1,2 and J Gratten1

After decades of halting progress, recent large genome-wide association studies (GWAS) are finally shining light on the genetic architecture of schizophrenia. The picture emerging is one of sobering complexity, involving large numbers of risk alleles across the entire allelic spectrum. The aims of this article are to summarize the key genetic findings to date and to compare and contrast methods for identifying additional risk alleles, including GWAS, targeted genotyping and sequencing. A further aim is to consider the challenges and opportunities involved in determining the functional basis of genetic associations, for instance using functional genomics, cellular models, animal models and imaging genetics. We conclude that diverse approaches will be required to identify and functionally characterize the full spectrum of risk variants for schizophrenia. These efforts should adhere to the stringent standards of statistical association developed for GWAS and are likely to entail very large sample sizes. Nonetheless, now more than any previous time, there are reasons for optimism and the ultimate goal of personalized interventions and therapeutics, although still distant, no longer seems unattainable.

Molecular Psychiatry (2013) 18, 38--52; doi:10.1038/mp.2012.34; published online 1 May 2012 Keywords: CNV; functional genomics; GWAS; schizophrenia; sequencing; SNP

THE NATURE OF THE PROBLEM complications (obesity, nicotine dependence, metabolic syndrome 13 Schizophrenia is a chronic psychiatric disorder characterized by and premature mortality), low employment and substantial 14 delusional beliefs, auditory hallucinations, disorganized thought homelessness. The disorder ranks ninth in the global burden of and behaviour, negative symptoms, and cognitive deficits illness, and ranks fifth (males) and sixth (females) in the leading 15 producing profound impairment of emotional and social behav- global causes of years lost because of disability. iour. Onset of psychosis is typically in late adolescence or early Despite the magnitude of its disease burden, the aetiology of adulthood, although subtle, nonspecific signs such as delayed schizophrenia remains poorly understood. The prevailing hypoth- 16--18 milestones1 and reduced intelligence quotient2 predate psychosis esis is that schizophrenia is a neurodevelopmental disorder, onset. These data are consistent with a reformulation of illness but the underlying molecular and cellular mechanisms remain a comprising pre-symptomatic risk, prodrome, acute psychosis and mystery. Diverse aetiological clues, including family history, early chronic illness.3 The schizophrenia phenotype is defined accord- life adversity, urban upbringing, migrant status, cannabis use and 19 ing to reliable international criteria (DSM-IV; ICD-10), but is a variety of pre/perinatal factors, have emerged from a large 20 nonetheless heterogeneous and is generally thought to comprise body of epidemiological studies. By far the most compelling of an amalgam of related disorders, a plurality that was proclaimed in these is family history, recognized for almost a century since the title of Bleuler’s classic 1911 text, ‘Dementia praecox or the Kraepelin observed ‘dementia praecox not at all infrequently is 21 group of schizophrenias’.4 Over the subsequent 100 years, many familial, often appearing in brothers and sisters’. Decades of attempts have been made to carve schizophrenia ‘at its joints’ in family, twin and adoption studies have established high 22,23 order to develop homogeneous sub-types for more intensive heritability (81%, confidence interval: 73--90%), which has aetiological study. The deficit syndrome,5 and antipsychotic compelled the search for genetic variation contributing to disease. treatment resistance6 serve as examples. In parallel with this drive to refine, is the more recent trend, based on accumulating evidence, to question the ‘Kraepelinian divide’ between schizo- THE PRE-GWAS ERA phrenia and bipolar disorder.7 Before the development of genome-wide association study Lifetime prevalence for established illness is B0.72%8 and the (GWAS) methodology, genetic studies of schizophrenia relied on suicide rate is B7%, the majority occurring in the first 3 years after karyotyping, linkage studies and candidate gene association onset.9 Only a minority (o14%) experience sustained recovery studies. Two of the best-known chromosomal rearrangements within the first 5 years of illness10 and another 16% later in the are large deletions on chromosome 22q11.2 and a balanced illness.11 Current treatments have limited efficacy (80% relapse chromosomal translocation t(1:11) (q43,q21) that led to the rates)10 and financial costs are high (for example, E94 billion for discovery of the DISC1 (disrupted-in-schizophrenia 1) gene. The psychotic disorders in Europe, 2010),12 with attendant medical chromosome 22q11.2 deletion syndrome (22q11.2DS) occurs in 1

1Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia and 2Queensland Centre for Mental Health Research, Wacol, Brisbane, Queensland, Australia. Correspondence: Professor BJ Mowry, Queensland Brain Institute, Building # 79, Upland Road, The University of Queensland, Brisbane, QLD 4072, Australia. E-mail: [email protected] Received 30 January 2012; revised 23 February 2012; accepted 19 March 2012; published online 1 May 2012 The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 39 in 2000--4000 live births.24,25 Most carriers of the 22q11.2DS have complex disease.45,46 GWAS methodology has been facilitated either a 3 or 1.5 Mb deletion, affecting between 30 and 60 by technological advances that enable the simultaneous and primarily brain-expressed genes. Unsurprisingly, this syndrome cost-effective analysis of large numbers of genetic markers (that is, displays extensive phenotypic heterogeneity including a range of up to 5 million) that tag a high proportion of all common single physical manifestations, cognitive impairments and behavioural nucleotide polymorphisms (SNPs) in the human genome. disturbances.25 One example is the velocardiofacial syndrome Although designed primarily to identify common small effect (palatal dysfunction, ventricular septal defects, dysmorphic facies alleles hypothesized under the common disease common variant and learning disabilities),26 the syndrome most frequently hypothesis, data from GWAS arrays can also be used to identify reported as having both the deletion (85--100%) and psychosis, rare submicroscopic chromosomal deletions and duplications in particular schizophrenia (up to 30%).27--29 Moreover, 22q11.2DS known as copy number variants, or CNVs. Recent years have seen occurs more frequently in schizophrenia than in the general a spate of reports identifying common, polygenic and rare variants population,30 and there does not appear to be any significant in schizophrenia, hinting at a large number of risk alleles across clinical differences in schizophrenia with or without 22q11.2.31 the entire allelic spectrum. Support for this locus has strengthened with the application of GWAS methodology and it is now widely accepted as the Common variation most robust association in schizophrenia (see below). The The first GWAS for schizophrenia were reported in 2006--2007.47,48 chromosomal translocation involving DISC1 and a non-coding These and other early studies49--52 failed to identify loci surpassing RNA named DISC2 (ref. 32) was first identified in a four- modern standards for genome-wide significance (P 5 Â 10À8), generational Scottish pedigree33 in which the proband had severe o presumably because sample sizes were inadequate for the effect conduct disorder.34 The translocation is strongly associated with sizes that we now know are typical of common variants in psychiatric disorders in this pedigree, including recurrent major complex neuropsychiatric disorders. The community has since depression, bipolar disorder and schizophrenia, with strongest coalesced into large international consortia with impressive statistical support for a broad, cross-disorder clinical phenotype.35 results: the number of studies (including meta-analyses) reporting A large body of functional work motivated by the initial discovery SNPs with genome-wide support has risen to 9 (refs 53--61) supports an important role for DISC1 in neurodevelopment,36 but (Table 1), and the total number of genome-wide significant loci statistical support from linkage and association studies in has grown to 12, some of which include evidence for multiple schizophrenia is lacking in populations other than the focal independent associations (for example, 10q24.3, 11q24.2, family.37,38 18q21.2). Additionally, four other loci have been identified in Linkage analysis assesses the co-segregation of genetic loci joint analyses of schizophrenia and bipolar disorder,57,61 consis- with disease in families. This strategy has been very successful for tent with clinical and epidemiological evidence for shared genetic Mendelian traits, but less so for complex diseases. In schizo- aetiology between these disorders (see below). As for other phrenia, over 30 genome-wide linkage analyses have been complex diseases, the identified risk alleles are common (majority conducted, and although some have reported genome-wide 40.3) and confer small increases in risk (odds ratios mostly 1.2; significant findings39--42 no locus has consistently replicated o Table 1). The largest study to date, by the Psychiatric GWAS across studies. In the largest schizophrenia linkage meta-analysis Consortium (PGC; N ¼ 51 695),57 identified 10 independent SNPs in to date, involving 32 independent genome-wide linkage scans eight loci (Table 1), five of which were novel (1p21.3, 2q32.3, (3255 pedigrees; 7413 genotyped schizophrenia/schizoaffective 8p23.2, 8q21.3 and 10q24.3). The strongest new finding was cases) no loci surpassing genome-wide significance were within an intron of the primary transcript of MIR137, a microRNA identified.43 The limited success of linkage may be a conse- that has an important role in the regulation of neuronal quence of the involvement of many genes in schizophrenia and maturation and adult neurogenesis.62,63 Interestingly, four other the expected rarity of mutations with large effect size. loci with genome-wide support in the same GWAS, or in joint In contrast to linkage, candidate gene association studies aim to analyses of schizophrenia and bipolar disorder (TCF4, CSMD1, identify commonly occurring variants of small effect. More than CACNA1A and C10orf26), contain predicted MIR137 target sites, 1000 studies of candidate schizophrenia genes have been consistent with a possible MIR137-related mechanism in the conducted, their candidature being based primarily on location aetiology of schizophrenia.57 The strongest PGC hit, and the in linkage regions or near cytogenetic abnormalities, or on schizophrenia locus with most consistent support, is a 5.5 Mb psychopharmacological hypotheses regarding monoaminergic region spanning the extended major histocompatibility complex receptor genes. Results from these studies are generally incon- at 6p21.3-p22.1 (Table 1), a highly polymorphic, gene-dense sistent, and with hindsight it is clear that they have limited power region that has a central role in development of host defence because of small sample size and sparse marker density. and immunity. Initially identified in Europeans, this locus has now Systematic meta-analyses of genetic variants that had been been identified in Han Chinese,60 and finds more modest studied in at least four independent case--control samples (118 support in Japanese.64 There is some indication that susceptibility variants from 52 genes) revealed a ‘strong’ degree of epidemio- variants in Europeans and Chinese represent different loci, logical credibility for four genes (DRD1, DTNBP1, MTHFR, TPH1;44 although strong and complex linkage disequilibrium in this www.szgene.org/), although the ranking of these genes has region creates significant challenges for resolving causal variants since changed. More recently, a pathway analysis observed no underlying associations. A second locus attracting support enrichment of smaller P-values in hypothesis-driven candidate across both European56 and Chinese60 ancestral groups is genes in the International Schizophrenia Consortium (ISC) 11p11.2; these associations appear to be independent, being GWAS, implying that these genes do not harbour commonly separated by B1.7 Mb. occurring disease-related genetic variants.38 It remains to be seen whether rare alleles of moderate to large effect will be identified in these genes. Polygenic variation Common SNPs surpassing genome-wide significance in schizo- phrenia (Po5 Â 10À8) explain very little of the variance in liability, THE GWAS ERA: SHINING LIGHT ON THE SPECTRUM OF either individually (o0.1%) or collectively (B2--3%).65 This has led ALLELIC VARIATION IN SCHIZOPHRENIA to a preoccupation with ‘missing heritability’ and a polarized In contrast to linkage and candidate gene studies, GWAS has been debate about the relative importance of common and rare successful for schizophrenia, as it has across the breadth of human genetic variation in schizophrenia.66,67 Although this is still an

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 38 -- 52 40 oeua scity(03,3 -52 -- 38 (2013), Psychiatry Molecular

Table 1. Multi-stage GWAS reporting genome-wide significant (o5 Â 10À8 ) findings in schizophrenia, or schizophrenia combined with bipolar disorder h mrigsetu fallcvraini schizophrenia in variation allelic of spectrum emerging The Lead author Ancestry Discoverya Replication Combined Locus SNP Position (Mb) Allele Freq. Odds ratio (95% CI) P-value Closest gene

Schizophrenia Purcell53 EU 3322/3587 4686/15 490 8008/19 077 6p22.1 rs13194053 27.3 C 0.16 0.82 (NR) 9.54 Â 10À9 HIST1H2BJ ISC MGS/SG+ ISC/MGS/SG+ Shi54 EU 2681/2653 5327/16 424 8008/19 077 6p22.1 rs13194053 27.3 C 0.16 0.88 (NR) 9.54 Â 10À9 HIST1H2BJ AA 1286/973 ------MGS ISC/SG+ MGS/ISC/SG+ Stefansson55 EU 2663/13 498 1: 4999/15 555 1: 7662/29 053 6p21.3-22.1 rs6932590 27.4 T 0.78 1.16 (1.11--1.21) 1.4 Â 10À12 PRSS16 SG+ SG-fu SG+/SG-fu 11q24.2 rs12807809 124.1 T 0.83 1.15 (1.10--1.20) 2.4 Â 10À9 NRGN 2: 5283/5538 2: 12 945/34 591 18q21.2 rs9960767 51.3 C 0.06 1.23 (1.15--1.32) 4.1 Â 10À9 TCF4

MGS/ISC SG+/SG-fu/ISC/MGS Gratten J and Mowry BJ Rietschel56 EU 1169/3714 2569/4088 3738/7802 11p11.2 rs11819869 46.5 T 0.16 1.25 (NR) 3.89 Â 10À9 AMBRA1 NW Europe NW Europe NW Europe Ripke57 EU 9394/12 462 8442/21 397 17 836/33 859 1p21.3 rs1625579 98.3 T 0.80 1.12 (1.09--1.16) 1.59 Â 10À11 MIR137 PGC-SCZ PGC-SCZ PGC-SCZ 2q32.3 rs17662626 193.7 A 0.91 1.20 (1.13--1.26) 4.65 Â 10À8 PCGEM1 6p21.3-22.1 rs2021722 30.3 C 0.78 1.15 (1.11--1.19) 2.18 Â 10À12 TRIM26 8p23.2 rs10503253 4.2 A 0.19 1.11 (1.07--1.15) 4.14 Â 10À8 CSMD1 8q21.3 rs7004633 89.8 G 0.18 1.16 (1.11--1.21) 1.45 Â 10À8 MMP16 10q24.32 rs7914558 104.8 G 0.59 1.10 (1.07--1.13) 1.82 Â 10À9 CNNM2 10q24.33 rs11191580 104.9 T 0.91 1.15 (1.10--1.20) 1.11 Â 10À8 NT5C2 11q24.2 rs548181 125.0 G 0.88 1.20 (1.13--1.26) 2.91 Â 10À8 STT3A 18q21.2 rs12966547 50.9 G 0.58 1.09 (1.06--1.12) 2.60 Â 10À10 CCDC68 18q21.2 rs17512836 51.3 C 0.02 1.40 (1.28--1.52 2.35 Â 10À8 TCF4 Shi58 HC 3750/6468 4383/4539 8133/11 007 1q24.2 rs10489202 166.2 A 0.14 1.19 (1.09--1.29) 9.50 Â 10À9 BRP44 BIOX BIOX BIOX 8p12 rs16887244 38.2 G 0.32 0.83 (0.78--0.89) 1.27 Â 10À10 LSM1 rs1488935 38.3 T 0.32 0.87 (0.82--0.93) 5.06 Â 10À9 WHSC1L1 Steinberg59 EU 7946/19 036 1: 9246/22 356 18 206/42 536 2p15.1 rs2312147 58.1 C 0.61 1.09 (1.06--1.12) 1.9 Â 10À9 VRK2 SG+/ISC/MGS 2: 1014/1144 18q21.2 rs4309482 50.9 A 0.58 1.09 (1.06--1.12) 7.8 Â 10À9 TCF4 Yue60 HC 746/1599 4027/5603 4773/7207 6p21-22.1 rs1635 28.3 T 0.33 0.78 (0.73--0.82) 6.91 Â 10À12 NKAPL 11p11.2 rs11038167 44.8 A 0.40 1.29 (1.23--1.36) 1.09 Â 10À11 TSPAN18

Schizophrenia and bipolar disorder & O’Donovan61 EU SCZ: 479/2937 SCZ: 6666/9897 9173/12 834 2q32.1 rs1344706 185.5 T 0.59 1.12 (NR) 9.96 Â 10À9 ZNF804A 03McilnPbihr Limited Publishers Macmillan 2013 BP: 1865/--- Ripke57 EU 16 374/14 044 3p21.1 rs2239547 52.8 T 0.72 1.12 (1.08--1.16) 7.83 Â 10À9 ITIH3/4 PGC-SCZ/BP 10q21.2 rs10994359 61.9 C 0.06 1.22 (1.15--1.29) 2.5 Â 10À8 ANK3 12p13.3 rs4765905 2.2 C 0.33 1.11 (1.07--1.15) 7.0 Â 10À9 CACNA1C Abbreviations: AA, African American; CI, confidence interval; EU, European; GWAS, genome-wide association study; HC, Han Chinese; NR, not reported; SNP, single nucleotide polymorphism. aNumber of cases and controls for each ethnicity; consortia/sample name (ISC, International Schizophrenia Consortium; MGS, Molecular Genetics of Schizophrenia; SG+, SGENE-plus; SG-fu, SGENE follow-up; PGC, Psychiatric GWAS Consortium; SCZ, schizophrenia; BP, bipolar disorder). The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 41 open question, a number of recent studies have provided strong evidence for a substantial contribution from a large 210 number of common alleles with small individual effects. The ISC 213 , IGE demonstrated that common SNPs surpassing a liberal significance 207 ,DD

threshold (that is, Po0.5) in the ISC GWAS explained up to 3% 113 112 205 113,209 213 214 of liability in several independent schizophrenia and bipolar disorder cohorts, but not in six non-psychiatric diseases.53 ,MR ,MR ,MR , PWS/AS ,MR ,MR ,MR 25 202 202 205 207 208 212 214

By using simulations they were able to show that the proportion 215

of heritability explained was probably much larger, about one- Other disorders ASD ASD ASD ASD ASD ASD ASD HN VCFS third of the total, implying that in addition to the handful of genome-wide significant SNPs described above, there must be

many (possibly thousands) more with individual effects too small a 204 ,81,201 206 ,86 to achieve statistical significance. This result has since been 211 86 ,203,206 77 ,80,81,86 ,81,86,119 77 57 ,82,84,201,203 ,80,83,86,119 81 replicated in the PGC schizophrenia GWAS, in a non-European 77 77 ,201,203,206 77

64 68 77 GWAS and in a family-based GWAS. The latter study effectively 85 rules out the possibility that the ISC finding is due to population stratification. Nonetheless, some have questioned the validity of 16 76,

69,70 893 52,75-- 52,75, 2 3 77,80,203, 492 80, 76, 3 5 80, 203, 12 75, À

the ISC’s approach, maintaining instead that the majority of À À À À À À À À À À À 10 10 10 10 10 10 10 10 10 10 10 genetic risk will be explained by rare, highly penetrant variants. 10  value Studies          70  Similarly, Dickson et al. have proposed that many common loci  P- D, developmental delay; Del, deletion; Ex del, exonic deletion; identified by GWAS may be explained by ‘synthetic associations’ 1.0 o involving multiple rare variants. The importance of synthetic ; Mat dup, maternally-derived duplication, MR, mental retardation; associations is a subject of debate,71,72 but further evidence for an ) important contribution from common variation in schizophrenia ) 1.0 73 N has been provided by recent work using an independent N method74 that is not vulnerable to the same criticisms as the ISC’s approach. This analysis, using all SNPs in a large schizophrenia (1.6-- (35.9-- OR (95% CI) GWAS data set, estimated that 22% of the total liability, N N approximately one-third of the genetic liability, could be explained by SNPs on commercial genotyping arrays.73 This result is consistent with the ISC’s estimate for the role of common variation and suggests that many additional common variants are yet to be discovered.

Rare and de novo structural variation 0.00013 (0/7431) 0.00002 (0/45 361)

Structural genomic variants that increase risk of schizophrenia o o have long been appreciated on the basis of cytogenetic studies, such as those identifying large recurrent deletions in chromo- some 22q11.2.27,29,30 More recently, data from GWAS and comparative genome hybridization arrays have facilitated CNV frequency (with/without) genome-wide screens for CNVs associated with elevated risk of Cases Controls disease. Three major findings have emerged from these studies. First, there is evidence for a modest increase in the burden of rare (o1%) and large (4100 kb) CNVs in schizophrenia cases ) 0.00182 (23/12 627) 0.00022 (10/45 284) 8.2 (3.8--19.4) 5.5 compared with controls.75--77 Second, de novo CNVs are ) 0.00191 (14/7322) 0.00047 (7/14 814) 4.0 (1.5--11.9) 2.0 associated with higher risk of disease.78--80 Third, specific CNVs VIPR2 have now been identified that confer substantial increases in risk NRXN1 of schizophrenia:75--77,81--86 at the time of writing, deletions and duplications at 10 loci had been replicated (Table 2). These CNVs values are taken from the bolded study.

are at low frequency in the general population (majority o0.1%) P- and are associated with substantially higher risks (odds ratios 2.7 to 426) than common SNPs, although none have yet been identified that are necessary and sufficient to cause disease. A majority of CNVs that have been identified are large (4100 kb) and span multiple genes. Exceptions include deletions in 2p16.3, which disrupt exons of the NRXN1 gene, and duplications in 7q36.3, which disrupt the VIPR2 gene. For some loci (for example, 3q29) both deletions and duplications are associated with increased risk of schizophrenia. Studies involving parents and offspring suggest that a high proportion of CNVs at identified schizophrenia loci are de novo in the individuals in which they occur (for example, 480% of deletions in 3q29 and 22q11.2).79,87 This is consistent with evidence for reduced fecundity in schizophrenia88 and suggests that deleterious CNVs are main- Replicated CNVs in schizophrenia tained in the population by recurrent mutation in spite of selection.87,89 The mutation rate at known CNVs is substantially 2p16.33q293q297q36.3 Ex del15q11.215q13.3 Del15q11.2-13.1 Dup 49.9--51.5 Ex dup Del16p11.2 Mat dup 0.02--0.42 Del16p13.1 197.2--198.8 158.5--158.8 1 196.8--196.917p12 20.3--26.4 ( 0.12--0.36 0.84--1.6 Dup22q11.2 20.3--20.8 1 Dup 0.05 4.1--9.0 ( 28.7--30.3 19 Del Del 29.4--30.1 13--24 0.5 14.6--18.7 1.5 0.00080 2 0.00053 (6/7539) (4/7578) 0.7 14.1--15.4 17.1--20.2 1.16 4 0.00121 (10/8280) 0.93--1.31 0.00003 0.00007 (1/39 8 747) (3/41 1.4--2.5 367) 26 17.0 0.00551 15 (1.4--1198.4) 11 (26/4692) 7.3 29--43 (1.2--50.0) 0.00193 (21/10 866) 9.7 0.00313 0.00307 (31/9859) 0.00151 (35/11 0.00299 0.00192 365) (8/5292) (13/4332) (79/41 115) 0.00020 1.0 (9/45 913) 2.7 0.00027 (1.5--4.9) (8/29 589) 0.00091 9.9 (32/35 0.00015 047) (4.3--24.4) (6/39 213) 11.6 (5.6--29.3) 3.3 (1.3--7.9) 6.0 9.9 2.0 (3.4--28.5) 1.5 7.1 5.0 Locus CNV Position (Mb) Size (Mb) Genes 1q21.1 Del 144.6--146.3 1.67 11 0.00176 (20/11 372) 0.00021 (10/47 311) 8.3 (3.7--19.9) 2.2 For each CNV case--control frequencies, ORs and Table 2. Abbreviations: ADHD, attention deficit hyperactivity disorder; ASD, autism spectrum disorder; CI, confidencea interval; CNV, copy number variant; D higher than the human nucleotide mutation rate, presumably Dup, duplication; Ex dup, exonicOR, duplication; odds HN, ratio; hereditary PWS/AS, neuropathy Prader--Willi with syndrome/Angelman liability syndrome; to VCFS, pressure velocardiofacial palsies; IGE, syndrome. idiopathic generalized epilepsy

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 38 -- 52 The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 42 because many are flanked by segmental duplications that are bipolar disorder.78,83,114 The broad clinical outcomes associated known to mediate genomic deletions and duplications via non- with these CNVs imply that the genetic background upon which allelic homologous recombination.86 This fact and the limited they are expressed is crucial. More generally, sharing of common resolution of current generation array-based CNV detection SNPs or rare CNVs may be due to pleiotropy, whereby a single platforms,90 implies that many additional CNVs are likely to exist gene is associated with more than one distinct phenotype,115 or to for schizophrenia. clinical overlap, exemplified by occurrence of psychosis in schizophrenia and bipolar disorder. Rare and de novo sequence variation Rare sequence variants, unlike rare CNVs, are not amenable to Risk-conferring molecular pathways discovery using GWAS or comparative genome hybridization A large number of risk alleles, both common and rare, are likely to array data and must instead be identified by sequencing. exist for schizophrenia, but these are expected to cluster in a more Although there is great interest in the use of sequencing to manageable number of molecular pathways, as has been shown identify rare variants in schizophrenia, such studies are in their for height.116 O’Dushlaine et al.117 identified the cell adhesion infancy. The majority that have been published to date have molecule pathway as associated with both schizophrenia and focused on the role of de novo mutations in protein-coding genes, bipolar disorder using SNP data from the ISC (N ¼ 6909) and based on the idea that disease prevalence is maintained by Genetic Association Information Network (N ¼ 2729) studies. This de novo mutation across many genes in spite of negative selec- pathway is involved in synaptic formation and normal cell 91 tion. The benefit of this approach is that whereas thousands of signalling and includes the candidate genes NRXN1 and CNTNAP2. inherited rare variants are present in the average exome (the set Further support for synaptic genes has been reported by Lips of all coding exons), fewer than one de novo missense or nonsense et al.,118 using the same data but a different analytic approach, 92 mutation is expected per father--mother--child trio. Conse- and by Glessner et al.,119 on the basis of genome-wide CNV quently, the disruption of the same gene by de novo mutations analyses. An important caveat to the latter study is that brain- in multiple unrelated affected individuals is unlikely to be a expressed genes are relatively large and gene size has been 93 94,95 chance occurrence. Two whole exome sequencing studies shown to be a major confounder in CNV-based pathway analyses 96--104 and a handful of hypothesis-driven candidate gene studies in neuropsychiatric disorders.120 When this confounder is have been published. Key reported findings from the exome accounted for synapse genes (N ¼ 209) are not supported by studies include evidence for an elevated exonic de novo mutation pathway analysis of ISC CNVs, but genes involved in neuronal 94 rate in schizophrenia, consistent with an earlier report based on activity are supported.120 Conversely, a more recent analysis by 97 B400 synapse genes, and an excess of putatively damaging Kirov et al.,80 which is the largest to date and which also accounts missense de novo mutations in schizophrenia cases compared for confounders such as gene size, demonstrated that de novo 95 with controls. These are interesting results that support an CNVs identified in 662 parent-case trios were significantly important role for de novo mutations in neuropsychiatric disease. enriched for genes involved in the postsynaptic density, However, sample sizes are modest and no study has yet identified particularly members of the NMDAR postsynaptic signalling single genes that were disrupted in multiple probands. Published complex. Larger studies of both common and rare variation will findings of putatively functional variants in candidate genes are help clarify the potential role of these and other pathways in descriptive rather than statistically supported and claims regard- schizophrenia. ing the identification of functional de novo mutations should be viewed with caution.105 Larger studies including analysis of extended pedigrees will be required to confirm the role and GENETIC ARCHITECTURE COMES INTO FOCUS effect size of de novo coding mutations. The genetic architecture of schizophrenia has been the subject of protracted and polarized debate.66,67 The predominant views until Shared genetic aetiology with other neurodevelopmental recent times were the common disease common variant (CDCV) disorders hypothesis, which supposes that disease is underpinned by a large Two recent strands of evidence, epidemiological and genetic, number of common variants of individually small effect, and the have converged to challenge the conventional diagnostic common disease rare variant (CDRV) hypothesis, which argues for distinction between schizophrenia and bipolar disorder. A large a model of extreme genetic heterogeneity involving many rare register-based study involving over two million Swedish families but highly penetrant mutations.67,69 Findings from the latest demonstrated that first-degree relatives of probands with either GWAS and genome-wide CNV studies make it abundantly clear schizophrenia or bipolar disorder were at increased risk of both that the truth lies somewhere between these two extremes and is these disorders because of substantial (B63%) shared additive likely to involve a spectrum of allelic variation from common to genetic effects.106 Genetic overlap of schizophrenia and bipolar rare, as others65,121 have noted (Figure 1). The variants that have was also supported by a Danish register-based study.107 been identified have effect sizes that are roughly inversely Consistent with these studies, recent genetic analyses have proportional to allele frequency.121 Although we do not yet know reported evidence for shared polygenic variation between these the strength of this relationship, it is expected because schizo- disorders,53 and four individual loci (ANK3, CACNA1C, ITIH3-ITIH4 phrenia is known to be associated with reduced fecundity88 and and ZNF804A) have achieved genome-wide significance in recent negative selection is expected to act on deleterious variants in GWAS of combined schizophrenia and bipolar disorder samples proportion to their correlation with fitness.122,123 The growing (Table 1).57,61,108--111 Genetic evidence in the form of shared rare evidence for an elevated de novo mutation rate in schizophrenia, CNVs is also challenging the distinction between schizophrenia both for CNVs79 and putatively functional protein-coding point and other neurodevelopmental disorders, including autism, mutations,94,95 is also consistent with the idea that schizophrenia mental retardation, developmental delay and epilepsy. For is maintained by a balance between mutation and selection across example, deletions in 2p16.3 (NRXN1), 1q21.1 and 15q13.3 have a large mutational target.87,91 In spite of this recent progress, there all been identified in autism spectrum disorders and mental is still much that we do not know. For instance, the proportion of retardation (Table 2),112,113 in addition to schizophrenia. Evidence genetic liability explained by rare sequence variants is unknown, for sharing of CNVs between schizophrenia and bipolar disorder is as is the relative importance of rare sequence variants compared also accumulating, with several studies reporting preliminary with rare CNVs. To date, variants at intermediate frequencies (that support for established schizophrenia loci 3q29 and 16p11.2 in is, between common SNPs with minor allele frequency 0.05 and

Molecular Psychiatry (2013), 38 -- 52 & 2013 Macmillan Publishers Limited The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 43 CDRV Polygenic mutation - selection balance Genetic Model CDCV ~ GWAS

Linkage NGS & Imputation / genotyping Customised chips Methodology GWAS / aCGH GWAS

Up to ~ 2/3 ~ 1/3 Genetic Variance

Mendelian Rare CNVs Low frequency Common SNPs and mutations variation polygenic variation Genetic Findings - none yet - none yet known known High No common SNPs Mendelian mutations with odds ratio that are necessary and >1.5 sufficient for disease - none yet identified

Known rare CNVs with moderate to high effect size Effect Size

Variants with intermediate effect size - none yet known

Common SNPs and Rare variants unrelated to polygenic variation schizophrenia with small effect size Low 0.0001 0.001 0.010.5 0.1 1 Rare Common Risk allele frequency Figure 1. Schematic representation of current genetic findings in schizophrenia (brown panels) in relation to prevailing genetic models of disease (green panel: CDRV, common disease rare variant hypothesis; CDCV, common disease common variant hypothesis), major genomics methodologies (orange panel: NGS, next-generation sequencing; GWAS genome-wide association studies; aCGH array-comparative genomic hybridization) and proportion of genetic variance explained (blue/purple panel). More than a dozen common alleles with small individual effects have been identified, and many more are inferred to exist on the basis of genome-wide analysis of GWAS data sets (yellow ellipse). This polygenic variation is consistent with the CDCV and may account for up to one-third of the genetic risk. Rare copy number variants (CNVs) with larger individual effects have also been identified on the basis of genome-wide analyses of GWAS and aCGH data sets (orange ellipse). These variants are more consistent with the CDRV, although to date no Mendelian mutations that are necessary and sufficient to cause disease have been identified (red panel). Similarly, no variants with intermediate allele frequency (that is, between that of common single nucleotide polymorphisms (SNPs) with minor allele frequency (MAF)X0.05 and rare CNVs with MAFo0.001) have been identified, but this region of the allelic spectrum is yet to be systematically investigated by customized genotyping and next-generation sequencing approaches. The effect size of identified risk alleles is roughly inversely proportional to allele frequency (approximated by the black curve), although the strength of this relationship is currently unknown (blue shading). Many rare variants that do not impact on risk of schizophrenia are expected to exist.

rare CNVs with minor allele frequency typically o0.001) have ascertain the strength of the relationship between risk allele not been identified, although it seems coincidental that this frequency and effect size. allele frequency window is yet to be systematically investigated (Figure 1). With regard to structural variation, we do not know to what extent inversions and translocations contri- STRATEGIES FOR IDENTIFYING COMMON, LOW FREQUENCY bute along with CNVs, and if risk is primarily associated with AND RARE GENETIC VARIANTS large structural variants (4100 kb), or if smaller and/or more The primary goal of schizophrenia genetics is to identify genetic common variants are also risk conferring. With respect to the variants and pathways underlying risk of the disorder. In light of genomic context of common and rare variation underlying the emerging evidence for a spectrum of allelic variation in disease, there is remarkably little data on the relative schizophrenia, diverse approaches, including GWAS, dense importance of variation in protein-coding genes as opposed targeted genotyping, sequencing and studies that combine these to regulatory elements and non-coding genes (but see Richards methods, will all be important priorities for establishing novel et al.).124 Finally, more data are required before we can statistical associations.

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 38 -- 52 The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 44 GWAS array-based solution for screening functional coding variants of There is widespread agreement that larger GWAS will attain the potential disease relevance. The exome chip will include 525 top statistical power required to identify additional common SNPs GWAS SNPs for schizophrenia, and a planned extension known as that are known to exist on the basis of polygenic ana- the ‘Psych-chip’ will include B20K schizophrenia GWAS SNPs lyses.53,65,121,125,126 The conflicting view that GWAS is not worth (Naomi Wray, personal communication). A major advantage of persisting with,67,69 which is based on the premise that most of these customized chips is that consortiums can achieve very the heritability is due to rare highly penetrant variants, appears competitive pricing (for example, oUS$40/Immunochip com- increasingly untenable in light of the accumulating evidence for pared with BUS$250 for standard GWAS chips) by ordering large an important contribution from common variation.126 The largest batches of chips, making them a cost-effective solution for schizophrenia GWAS to date, that of the PGC (Ripke et al.,57 interrogating a broad spectrum of allelic variation in known N ¼ 21 856 GWAS, N ¼ 29 839 replication), is modest in compar- disease loci and in protein-coding genes. Limitations include a ison with other common diseases (for example, type 2 diabetes, reliance on findings from previous GWAS studies, and the fact that N ¼ 47 117 GWAS, N ¼ 94 337 replication, Voight et al.)127 because only a small fraction of all rare variants, including those in protein- of the substantial costs of clinical ascertainment and diagnosis. coding genes, have been identified. For these reasons, agnostic Nonetheless, the rate of discovery of novel loci per 1000 cases in screening for rare and low-frequency sequence variants in schizophrenia is typical of other diseases,121 and efforts are schizophrenia will require sequencing. ongoing to accumulate larger samples for meta-analysis as part of the ‘PGC2’ collaboration. It has been estimated that a schizo- phrenia GWAS with 50 000 cases and 50 000 controls would have Sequencing equivalent power to a study of height with 180 000 participants,128 There is currently enormous interest in the application of next- a recent example of which identified 180 genome-wide significant generation sequencing in studies of complex disease, driven by loci that clustered non-randomly in biologically plausible path- recent technological advances that have led to stunning increases ways.116 This suggests that larger GWAS in schizophrenia are likely in throughput and corresponding reductions in per nucleotide to identify many additional loci, thereby providing important costs.131 The expectation is that rare risk alleles will exhibit larger biological leads for functional studies into disease mechanisms. effects than common SNPs identified by GWAS,132 and that their For these reasons, we concur with others (for example, Sullivan)125 identification, especially those whose functional consequences are that GWAS should continue to be a high priority for the field. readily interpretable (for example, in protein-coding genes), may At the same time, it is important to note that GWAS has yield commensurate insights into disease mechanisms.133 This limitations. Most SNPs identified by GWAS are expected to be promise is yet to be realized in schizophrenia, or indeed any proxies for the unobserved risk-conferring variants, rather than psychiatric disease, and will entail far greater challenges than the directly functional,45 and many occur in extended blocks of widely celebrated successes in studies of rare Mendelian linkage disequilibrium containing multiple candidate genes and disorders.134,135 The sequencing paradigms developed for such other strongly associated SNPs, as is the case for schizophrenia in diseases, for instance involving small numbers of unrelated the extended major histocompatibility complex region.57 individuals with the same rare condition (for example, Miller Consequently, GWAS rarely provides conclusive evidence for a syndrome, Roach et al.),136 will not work for schizophrenia, single gene or causal variant and fine-mapping is an important because there are (to our knowledge) no known Mendelian consideration. A second limitation is that commercial genotyping forms. Rather, current evidence suggests that multiple genetic arrays tag very little of the rare and low-frequency variation in the variants, rare, low-frequency and common, combine with envir- genome, which is likely to account for a substantial fraction onmental risk factors to form disease. Differentiating the small of the two-thirds of the heritability that cannot be attributed to percentage of disease-relevant rare and low-frequency alleles common SNPs.126 Consequently, even the largest GWAS that from the huge number present in the typical exome (thousands) are currently envisaged will explain only a modest proportion of or genome (millions)92 represents a major analytic challenge. the genetic liability.116 Other approaches, including targeted Power to establish a genetic association is a function of the genotyping and sequencing, will be required to fine-map variance in liability explained, which is determined by allele common alleles and to expand the catalogue of identified variants frequency and effect size. As effect size is expected to be inversely to include those (other than large CNVs) at the rare end of the proportional to risk allele frequency,123 reflecting the role of allelic spectrum. negative selection, very large sample sizes, rivalling those for GWAS, will be required to establish statistical associations with individual sequence variants; because those with large effects are Customized SNP chips likely to be very rare, whereas low-frequency variants are likely to One option for targeting a broader spectrum of allelic variation, have more modest effect size. Collapsing methods for gene-based and for fine-mapping existing associations, is to undertake very analysis of rare variants have been shown to be more power- dense genotyping of specific loci previously implicated by GWAS ful,137,138 but nonetheless will require large sample sizes when in diseases with shared aetiology. An example is provided by the undertaken on an exome or genome-wide level. Such studies will Immunochip, which includes all known variants (NE200 000), entail major challenges, not least in terms of the computational common and rare, in 4180 distinct genome-wide significant loci resources that are required for processing, quality control and for multiple autoimmune and inflammatory diseases.129 Early annotation of the typically very large data sets. Additionally, indications from a study of Crohn’s disease are promising,130 and although sequencing costs are dropping rapidly (BUS$1000 for suggest that this approach may be an efficient means of fine- whole exome and BUS$4000 for whole genome at the time of mapping causal variants in immune diseases. Although designed writing), they remain high in comparison with genotyping for immunogenetics, the Immunochip is likely to be a valuable (BUS$250), and we are not yet at the point where exome or tool in psychiatric genetics because it includes or tags many of the genome sequencing of large case--control samples (that is, tens of SNPs in the PGC GWAS with P-values o1 Â 10À5. Another ongoing thousands) is feasible. There is little doubt that this time is rapidly development is the exome chip, which aims to include a high approaching, but presently, the optimal design for identification of proportion of putatively functional variants (for example, nonsynon- rare and low-frequency variants in schizophrenia is likely to ymous, splicing and nonsense) present in a collection of B12 000 involve exome or genome sequencing in discovery samples sequenced genomes and exomes (http://genome.sph.umich.edu/ followed by targeted genotyping (or imputation) in large wiki/Exome_Chip_Design). The aim is to provide an affordable independent, ethnically matched case--control cohorts.

Molecular Psychiatry (2013), 38 -- 52 & 2013 Macmillan Publishers Limited The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 45 Combined sequencing and genotyping approaches Despite this technical progress, functional genomic studies in Several successful examples of this strategy have appeared complex neurodevelopmental disorders such as schizophrenia recently for non-psychiatric disorders. Sulem et al.139 undertook face manifold challenges (Figure 2). A key difficulty is that the whole genome sequencing in 457 Icelanders and imputed 16 changes in gene expression or splicing (for example) that underlie million SNPs into 41 675 previously GWAS’ed Icelandic individuals, many genetic associations are likely to be age, tissue and cell-type identifying low-frequency variants at high levels of significance for specific.146 This imposes important constraints on functional gout and serum uric acid levels. In another study, Rivas et al.140 investigations that rely on peripheral tissues such as lympho- performed pooled sequencing of 56 confirmed GWAS genes for cytes150 or on post-mortem brain samples.151 The former is readily Crohn’s disease in 350 cases and 350 controls, and then accessible, but only a modest proportion of genes appear to be genotyped 70 rare candidate variants in 16 054 Crohn’s disease co-expressed in blood and brain.152 This knowledge places cases, 12 153 ulcerative colitis disease cases and 17 575 controls, significant caveats on blood-based expression studies in psychia- identifying multiple rare variants in pre-existing genes that are tric disorders, although lymphocyte-based expression profiling likely to be functional. Other successful examples include studies may yet be valuable for investigating immune-related hypotheses in age-related macular degeneration,141 type 2 diabetes142 and of schizophrenia aetiology,153 and there remains substantial melanoma.143 Some in the schizophrenia genetics community interest in the identification of blood-based biomarkers for have cautioned against unrealistic expectations from sequen- schizophrenia (for example, metabolites) that may augment cing.121 Although we concur, it is clear that DNA sequencing clinical diagnoses.154 In contrast, post-mortem brain tissue technologies131 and bioinformatics tools for processing, annotat- provides a unique opportunity to perform in-depth molecular ing and interpreting sequence variation are maturing rapidly.144 analyses not possible with living subjects, and which may not Studies combining sequencing with imputation and targeted occur in peripheral tissues.155 A major limitation of post-mortem genotyping appear promising, and large GWAS data sets collected studies is that brain samples are typically collected years or by consortiums such as the PGC should enable similar studies to decades after disease onset, at which time expression level in be performed for schizophrenia. We suggest that GWAS, targeted cases may be more reflective of medication history than primary genotyping and sequencing will all be essential to future progress disease aetiology. Additionally, several other factors can confound and we urge the community (and major funding bodies) to expression levels in post-mortem brain studies, including sex, age, embrace them. post-mortem interval, tissue pH and agonal state;146 obtaining large samples that are matched for these confounders represents a significant challenge.155 FUNCTIONAL CHARACTERIZATION OF GENETIC ASSOCIATIONS: OPPORTUNITIES AND CHALLENGES Cellular and animal models Genetic variants that are robustly associated with schizophrenia In vivo models of disease including cellular and animal models provide essential biological leads for subsequent functional circumvent some of the difficulties presented by primary human studies that aim to improve understanding of biological mechan- tissues (Figure 2). The rapidly expanding field of induced isms involved in disease aetiology. It is expected that by pluripotent stem cells (iPSC) and their differentiation into neurons determining how risk alleles contribute to aberrant functioning and glial cells, or the direct conversion of somatic cells into at the molecular, cellular, synaptic and neural circuitry levels, that neurons, provides the opportunity to address the inaccessibility of we will ultimately gain the necessary aetiological and pathophy- the human brain by studying live patient-specific neurons, and to siological understanding to inform the development of evidence- observe disordered molecular networks that take into account the based therapeutics. complete genetic background of the individual.156 As such, patient-derived neuronal cell lines may be the most appropriate and relevant cell model system for drug screening to find Functional genomics potential therapeutics.157 There are now several schizophrenia Recent technological advances are providing powerful new tools iPSC reports;158--160 Brennand et al.,159 for example, reported for characterizing the transcriptional landscape in disease-relevant reduced neuronal connectivity, decreased glutamatergic receptor tissues (Figure 2). In particular, new methods for high-throughput expression, and altered gene expression in many cyclic AMP and RNA sequencing (known as RNA-seq) are enabling transcriptome- Wnt signalling pathways, ameliorated following antipsychotic wide profiling of expression level and splicing variation of coding administration. However, sample sizes are small and as with any and non-coding RNAs.145 This data can be related to genotype at new field a cautious approach is required. Current challenges candidate SNPs in order to identify genetic variants (referred to as include reproducibility, neuronal characterization and uncertain- expression quantitative trait loci (QTL) and splicing QTL) involved ties about the correlation of expression level in cultured cells in regulation of gene expression, a mechanism that is expected to compared with primary brain neurons, particularly with respect to explain many common risk alleles identified by GWAS.124 This changes during disease onset. approach may also help to isolate disease genes in regions of high Animal models provide a solution to this difficulty because they linkage disequilibrium containing multiple candidates. An im- can be surveyed, at molecular, cellular and neural circuitry levels, portant resource for such analyses has been generated by several at multiple developmental time-points and brain regions (Fig- recent studies that performed large-scale expression profiling ure 2).161 They also enable the behavioural consequences of in multiple brain regions and across age groups.146,147 Other candidate mutations to be evaluated, although with the caveats functional genomics methods, including chromatin immunopre- that positive symptoms such as delusions and auditory hallucina- cipitation followed by sequencing (CHiP-seq) and bisulphite tions cannot be modelled in animals, and typical behavioural sequencing (Meth-seq), among others, are enabling genome-wide paradigms, such as prepulse inhibition, measures of attention and surveys of DNA--protein interactions and epigenetic modifications working memory tasks, although relevant to schizophrenia, are (respectively), thereby helping to annotate regulatory elements in not specific to this disorder.161 One major class of mouse models the genome.148 Integration of these data using systems biology are those that aim to model specific aetiological factors such as approaches (for example, by creating protein--protein interaction genetic risk loci. Many such models have been developed using networks or gene co-expression networks) will be essential for sophisticated genetic tool kits that enable mouse homologues of gaining understanding of which molecular pathways are disrupted human genes to be ‘knocked out’ (that is, inactivated), or specific in schizophrenia.149 human mutations to be ‘knocked in’ to the mouse genome.

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 38 -- 52 The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 46

Figure 2. Roadmap for the identification and functional investigation of schizophrenia risk alleles. The primary goal of schizophrenia genetics is to identify genetic variants that increase risk of the disorder. In light of the growing evidence for a spectrum of allelic variation in the disorder, diverse approaches, including GWAS, customized chips and sequencing, will all be important priorities for establishing novel statistical associations. These discoveries provide the foundation for functional investigations that aim to advance understanding of disease mechanisms at the molecular, cellular, synaptic and neural circuitry levels. Major advances in sequence-based functional genomics (RNA-seq, CHiP-seq, Meth-seq) are enabling detailed profiling of expression level and transcriptional regulation. These studies can be undertaken in peripheral tissues, post-mortem brain samples, iPSC-derived neuronal cell lines or animal models, each of which has strengths and weak- nesses. Integration of genetic, transcriptomic and epigenomic data using systems biology approaches has the potential to identify the key molecular pathways that are disrupted in schizophrenia. A parallel avenue of functional investigation involves the study of neuroimaging, neurocognitive and neuroanatomical correlates of confirmed risk loci in healthy and affected individuals. It is anticipated that in combination such studies will yield the necessary biological insight to facilitate personalized interventions and develop novel therapeutics. CNV, copy number variant; DLPFC, dorsolateral prefrontal cortex; DTI, diffusion tensor imaging; eQTL, expression quantitative trait locus; fMRI, functional magnetic resonance imaging; GWAS genome-wide association studies; HC, hippocampus; iPSC, induced pluripotent stem cell; miRNA, microRNA; ncRNA, non-coding RNA; PET, positron emission tomography; sMRI, structural magnetic resonance imaging; SNP, single nucleotide polymorphism.

Common risk alleles are generally considered more difficult to is that mouse models generally have a poor record in translating model, because they have subtle effects and most are proxies for genetic findings into human therapeutics,167 possibly due to the unobserved causal variants. For this reason, the most tractable human-specific differences in signalling and expression path- risk alleles for study using animal (and indeed cellular) models are ways.168,169 likely to be rare CNVs associated with high risk, such as 22q11.2 and NRXN1. A number of 22q11.2 mouse models have been developed, including several that are heterozygous for the 1.5 Mb Neuroimaging, neurocognitive and neuroanatomical deletion,162,163 and which therefore most closely recapitulate the endophenotypes human mutation, and others involving knockouts of individual A parallel avenue of functional investigation of genetic associa- genes in the deletion region.161 Characterizing rodents such as tions involves studying their correlation with neuroimaging, these may help improve our neurobiological understanding of neurocognitive and neuroanatomical intermediate phenotypes170 each particular candidate. Other model organisms such as the in healthy171 and affected participants (Figure 2). These inter- worm, fly, bee and zebra fish provide other advantages, such as mediate phenotypes must be repeatable, stable (occur pre-illness cost-effective high-throughput screening of potential therapeutic onset and throughout the illness), and heritable. Many neurocog- targets, rapid life cycles and easy housing.164,165 Limitations of nitive intermediate phenotypes have been shown to be heritable, animal models include the problem that knockouts or knock-ins of although estimates appear to be lower than that of the clinical single loci do not reflect the polygenic architecture of human phenotype.172 The evidence for heritable neuroimaging inter- disease,166 and the consequences of complete inactivation of mediate phenotypes is more mixed, with hippocampal volume genes, for instance in knockout models, may not faithfully reduction attracting most support.173,174 The endophenotyping represent the subtle effects of human risk alleles. A final caveat paradigm is exemplified by studies of two GWAS-identified loci,

Molecular Psychiatry (2013), 38 -- 52 & 2013 Macmillan Publishers Limited The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 47 ZNF804A61,110 and CACNA1C.57,111 Neuroimaging studies of there is insufficient information available to construct a healthy carriers of ZNF804A risk allele rs1344706 exhibit changes genetic risk score because genome-wide significant common mirroring those found in schizophrenia patients, including fronto- SNPs and rare CNVs collectively explain only B2% of the hippocampal dysconnecitivity,175--177 larger white matter volumes genetic variance. Larger and diverse genetic studies (as and reduced grey matter volumes (for example, parahippocampal outlined above) will be needed before genetic risk prediction gyrus) and impaired visuomotor performance.178 Healthy carriers becomes a reality. of the CACNA1C risk variant (rs1006737) have been reported to show reduced hippocampal activation and connectivity during Development of novel therapeutics episodic memory recall, reduced activation of the subgenual anterior cingulate cortex,179 and impaired spatial working memory Existing therapeutics, including first- and second-generation that was also shown in those with schizophrenia but not bipolar antipsychotics, have limited efficacy in many patients and disorder.180 These ‘healthy carrier’ studies have the major benefit pronounced side effect profiles, including tardive dyskinesia and extra-pyramidal symptoms, weight gain and metabolic syndrome, that illness confounds such as medication history can be avoided. 187 However, current endophenotype findings are weaker than the agranulocytosis, and cadiomyopathies. There is thus a pressing primary genetic associations, and as in early schizophrenia GWAS, need to discover safe, efficacious therapeutics that are based on this is likely a reflection of limited sample size. Hence, their pathophysiological mechanisms. This has proven to be an inherently complex, difficult and risky process,188 particularly in primary value lies in investigating known genetic loci, rather than 189 discovery of novel loci underlying endophenotypic variation. In psychiatry. The main obstacles involve insufficient knowledge of the long term, these studies together with intermediate pheno- the mechanisms underlying the impact of genetic variation on type studies of affected individuals with known CNVs, such as treatment response. Many (but not all) major pharmaceutical the 22q11 deletion syndrome,181 may help identify more homo- companies are withdrawing from traditional neurotransmitter- geneous clinical sub-types for further aetiological study.182 Long- focused research and at least one (Novartis) is purported to be itudinal studies of 22q11.2 children (for example) who do and do investing heavily in genetic studies as the most promising avenue of research to gain the necessary understanding of disease not develop psychosis may be particularly important for clarifying 190 the trajectory from risk to disorder.183 mechanisms. Although relatively few genetic loci have been identified to date, some may provide novel drug targets. Genes mapping to CNVs may be particularly promising because of PROSPECTS FOR PERSONALIZED INTERVENTIONS AND the large individual effect sizes of these loci. One such gene is the THERAPEUTICS nicotinic cholinergic receptor alpha-7, CHRNA7, situated in the 15q13-q14 locus, which is strongly supported in schizophrenia on The ultimate goal of schizophrenia genetics is to advance aetio- the basis of genome-wide evidence for 15q13.3 duplications,77 as logical understanding to the point where individuals at elevated well as from linkage191,192 and association193 studies. Several risk can be identified before disease onset, and intervention alpha-7 agonists are in clinical development for schizophrenia. strategies and therapeutics can be personally tailored based on These compounds show P50 deficit normalization in schizophrenia, understanding of underlying disease mechanisms. It is anticipated fewer alpha-7 receptors in hippocampus and cortex194 and are that such evidence-based therapeutics will have higher clinical involved in the CHRNA7-mediated release of gamma-aminobutyric efficacy and fewer side effects compared with current options. This acid by hippocampal interneurons.195 A particular alpha-7 receptor goal remains distant, but recent genetic discoveries are providing partial agonist 3-[2,4-dimethoxybenzylidene] anabaseine, appears novel candidates for therapeutic evaluation and provide the promising in phase I and II trials; it appears to improve foundation for future work that may lead to accurate prediction neurocognitive deficits196,197 and default network function in of genetic risk. schizophrenia.198 One cautionary note is the rapid desensitization in vitro, questioning its applicability as a clinically relevant drug Genetic risk prediction target.199 Another potential novel therapeutics target, also implicated by a replicated duplication (in chromosome 7q36), is Predicting individuals at increased risk of disease has the potential 77,86 to expedite early diagnosis and develop more effective interven- VIPR2. This gene encodes the vasoactive intestinal peptide (VIP) tions. The assessment of risk predictors in complex disease is receptor VPAC2, a G-protein-coupled receptor that appears to be based on the area under the receiver operator characteristic curve. overexpressed in patients with the duplication. Selective antago- nists of VPAC2 may have therapeutic potential in these indivi- The receiver operator characteristic curve is calculated from the 86 relationship between the cumulative proportion of disease cases duals. CHRNA7 and VIPR2 constitute two promising leads for and the proportion of the population following ranking (from novel therapeutics. However, translating genetic findings into highest to lowest) according to the particular risk predictor. In effective therapies in schizophrenia is a distal rather than proximal goal for the field and will be a defining challenge in the coming schizophrenia, the current best predictor is family history, with the 200 area under the receiver operator characteristic curve for three- decades. generation families equal to 0.66.184 In principle, given sufficient knowledge of the genetic factors underlying risk of disease, it may be possible to develop genetic risk predictors that surpass family CONCLUSION history, which has limitations, for instance because siblings are The onset of large-scale genome-wide association and CNV predicted to have equal risk despite genetic differences. It is studies has led to rapid advances in our understanding of the important to note that this is not contingent upon discovering genetic architecture of schizophrenia. A growing number of causal variants, because knowledge of markers that tag causal common SNPs and rare CNVs have now been replicated, including variants will suffice. By extension, the value of this approach lies some (for example, MIR137 and its putative targets TCF4, CSMD1 not in understanding pathophysiology, but in identifying those at and others) that hint at possible novel aetiological mechanisms. risk of disease. A number of studies184--186 have addressed this Despite this tangible progress, identified loci collectively explain question in light of the growing number of common and rare risk only a few percent of the genetic risk. The source of the remaining loci that have been identified by genome-wide analyses (see heritability has been the subject of intense debate, particularly above). Wray et al.184 demonstrated that a genetic predictor made regarding the relative importance of common and rare alleles. Like up of alleles collectively explaining 25% of the heritability would others,65 we consider this dichotomous view to be unhelpful, out-perform family history (area under the curve B0.8). Currently, because the current evidence supports the existence of a large

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 38 -- 52 The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 48 number of risk alleles across the entire allelic spectrum. In this 16 Feinberg I. Schizophrenia: caused by a fault in programmed synaptic elimination article, we argue that diverse approaches, including larger GWAS, during adolescence? J Psychiatr Res 1982; 17: 319--334. targeted and customized genotyping, sequencing and combina- 17 Weinberger DR. Implications of normal brain development for the pathogenesis tions of these methods, will be required to identify additional of schizophrenia. Arch Gen Psychiatry 1987; 44: 660--669. risk alleles from common to rare. In all instances, large samples 18 Murray RM, Jones P, O0Callaghan E. Fetal brain development and later sizes (that is, tens of thousands) will be key in order to establish schizophrenia. Ciba Found Symp 1991; 156: 155--163, discussion 163--170. statistical significance. A second major focus of the field is 19 van Os J, Kenis G, Rutten BP. The environment and schizophrenia. Nature 2010; functional investigation of genetic associations in order to 468: 203--212. 20 Sullivan PF. The genetics of schizophrenia. PLoS Med 2005; 2: e212. determine how risk alleles contribute to aberrant functioning at 21 Kraepelin E. Dementia Præcox and Paraphrenia. Chicago Medical Book Company: the molecular, cellular, synaptic and neural circuitry levels. Such Chicago, 1919. studies are being facilitated by rapid advances in functional 22 Sullivan PF, Kendler KS, Neale MC. Schizophrenia as a complex trait: evidence genomics, cellular biology and neuroimaging, and it is anticipated from a meta-analysis of twin studies. Arch Gen Psychiatry 2003; 60: 1187--1192. that the resulting aetiological and pathophysiological under- 23 Cardno AG, Gottesman. Twin studies of schizophrenia: from bow-and-arrow standing will inform the development of evidence-based ther- concordances to star wars Mx and functional genomics. Am J Med Genet 2000; apeutics. Significant challenges remain and few if any genetic risk 97: 12--17. factors have been definitively functionally characterized to date. 24 Karayiorgou M, Simon TJ, Gogos JA. 22q11.2 microdeletions: linking DNA We can expect this to be a crucial rate-limiting step in the structural variation to brain dysfunction and schizophrenia. Nat Rev Neurosci 189 2010; 11: 402--416. translation of genetic findings into clinical benefits. 25 Kobrynski LJ, Sullivan KE. Velocardiofacial syndrome, DiGeorge syndrome: the chromosome 22q11.2 deletion syndromes. Lancet 2007; 370: 1443--1452. 26 Shprintzen RJ, Goldberg RB, Lewin ML, Sidoti EJ, Berkman MD, Argamaso RV CONFLICT OF INTEREST et al. A new syndrome involving cleft palate, cardiac anomalies, typical The authors declare no conflict of interest. facies, and learning disabilities: velo-cardio-facial syndrome. Cleft Palate J 1978; 15: 56--62. 27 Murphy KC, Jones LA, Owen MJ. High rates of schizophrenia in adults with velo- cardio-facial syndrome. Arch Gen Psychiatry 1999; 56: 940--945. ACKNOWLEDGEMENTS 28 Pulver AE, Nestadt G, Goldberg R, Shprintzen RJ, Lamacz M, Wolyniec PS et al. This work was supported in part by Australian National Health and Medical Research Psychotic illness in patients diagnosed with velo-cardio-facial syndrome and Council Grants 631406, 631671 and by Queensland Health. We thank the anonymous their relatives. J Nerv Ment Dis 1994; 182: 476--478. referees for their helpful comments and Dee McGrath for help with the figures. 29 Bassett AS, Hodgkinson K, Chow EW, Correia S, Scutt LE, Weksberg R. 22q11 deletion syndrome in adults with schizophrenia. Am J Med Genet 1998; 81: 328--337. REFERENCES 30 Karayiorgou M, Morris MA, Morrow B, Shprintzen RJ, Goldberg R, Borrow J et al. 1 Sorensen HJ, Mortensen EL, Schiffman J, Reinisch JM, Maeda J, Mednick SA. Early Schizophrenia susceptibility associated with interstitial deletions of chromosome developmental milestones and risk of schizophrenia: a 45-year follow-up of the 22q11. Proc Natl Acad Sci USA 1995; 92: 7612--7616. Copenhagen Perinatal Cohort. Schizophrenia Res 2010; 118: 41--47. 31 Bassett AS, Chow EW, AbdelMalik P, Gheorghiu M, Husted J, Weksberg R. The 2 Woodberry KA, Giuliano AJ, Seidman LJ. Premorbid IQ in schizophrenia: a meta- schizophrenia phenotype in 22q11 deletion syndrome. Am J Psychiatry 2003; analytic review. Am J Psychiatry 2008; 165: 579--587. 160: 1580--1586. 3 McGorry PD, Yung AR, Bechdolf A, Amminger P. Back to the future: predicting 32 Millar JK, Wilson-Annan JC, Anderson S, Christie S, Taylor MS, Semple CA et al. and reshaping the course of psychotic disorder. Arch Gen Psychiatry 2008; 65: Disruption of two novel genes by a translocation co-segregating with 25--27. schizophrenia. Hum Mol Genet 2000; 9: 1415--1423. 4 Bleuler E. Dementia Praecox or the Group of Schizophrenias (1911). International 33 Jacobs PA, Brunton M, Frackiewicz A, Newton MPJLC, Robson EB. Studies on a Universities Press: New York, 1950. family with three cytogenetic markers. Ann Hum Genet 1970; 33: 325--336. 5 Carpenter Jr WT, Heinrichs DW, Wagman AM. Deficit and nondeficit forms of 34 St Clair D, Blackwood D, Muir W, Carothers A, Walker M, Spowart G et al. schizophrenia: the concept. Am J Psychiatry 1988; 145: 578--583. Association within a family of a balanced autosomal translocation with major 6 Kane J, Honigfeld G, Singer J, Meltzer H. Clozapine for the treatment-resistant mental illness. Lancet 1990; 336: 13--16. schizophrenic. A double-blind comparison with chlorpromazine. Arch Gen 35 Blackwood DH, Fordyce A, Walker MT, St Clair DM, Porteous DJ, Muir WJ. Psychiatry 1988; 45: 789--796. Schizophrenia and affective disorders--cosegregation with a translocation at 7 Craddock N, O0Donovan MC, Owen MJ. Psychosis genetics: modeling the chromosome 1q42 that directly disrupts brain-expressed genes: clinical and relationship between schizophrenia, bipolar disorder, and mixed (or P300 findings in a family. Am J Hum Genet 2001; 69: 428--433. 00schizoaffective00) psychoses. Schizophr Bull 2009; 35: 482--490. 36 Ishizuka K, Kamiya A, Oh EC, Kanki H, Seshadri S, Robinson JF et al. DISC1- 8 Saha S, Chant D, Welham J, McGrath J. A systematic review of the prevalence of dependent switch from progenitor proliferation to migration in the developing schizophrenia. PLoS Med 2005; 2: e141. cortex. Nature 2011; 473: 92--96. 9 Alaraisanen A, Miettunen J, Rasanen P, Fenton W, Koivumaa-Honkanen HT, 37 Sanders AR, Duan J, Levinson DF, Shi J, He D, Hou C et al. No significant Isohanni M. Suicide rate in schizophrenia in the Northern Finland 1966 Birth association of 14 candidate genes with schizophrenia in a large European Cohort. Social Psychiatry Psychiatric Epidemiol 2009; 44: 1107--1110. ancestry sample: implications for psychiatric genetics. Am J Psychiatry 2008; 165: 10 Robinson DG, Woerner MG, McMeniman M, Mendelowitz A, Bilder RM. 497--506. Symptomatic and functional recovery from a first episode of schizophrenia or 38 Collins AL, Kim Y, Sklar P, O0Donovan MC, Sullivan PF. Hypothesis-driven schizoaffective disorder. Am J Psychiatry 2004; 161: 473--479. candidate genes for schizophrenia compared to genome-wide association 11 Harrison G, Hopper K, Craig T, Laska E, Siegel C, Wanderling J et al. Recovery from results. Psychological Med 2011; 42: 1--10. psychotic illness: a 15- and 25-year international follow-up study. Br J Psychiatry J 39 Paunio T, Ekelund J, Varilo T, Parker A, Hovatta I, Turunen JA et al. Genome-wide Mental Sci 2001; 178: 506--517. scan in a nationwide study sample of schizophrenia families in Finland 12 Gustavsson A, Svensson M, Jacobi F, Allgulander C, Alonso J, Beghi E et al. Cost reveals susceptibility loci on chromosomes 2q and 5q. Hum Mol Genet 2001; of disorders of the brain in Europe 2010. Eur Neuropsychopharmacol 2011; 21: 10: 3037--3048. 718--779. 40 Maziade M, Roy MA, Chagnon YC, Cliche D, Fournier JP, Montgrain N et al. Shared 13 Marwaha S, Johnson S, Bebbington P, Stafford M, Angermeyer MC, Brugha T and specific susceptibility loci for schizophrenia and bipolar disorder: a dense et al. Rates and correlates of employment in people with schizophrenia in the genome scan in Eastern Quebec families. Mol Psychiatry 2005; 10: 486--499. UK, France and Germany. Br J Psychiatry J Mental Sci 2007; 191: 30--37. 41 Holliday EG, Nyholt DR, Tirupati S, John S, Ramachandran P, Ramamurti M et al. 14 Folsom DP, Hawthorne W, Lindamer L, Gilmer T, Bailey A, Golshan S et al. Strong evidence for a novel schizophrenia risk locus on chromosome 1p31.1 Prevalence and risk factors for homelessness and utilization of mental health in homogeneous pedigrees from Tamil Nadu, India. Am J Psychiatry 2009; 166: services among 10 340 patients with serious mental illness in a large public 206--215. mental health system. Am J Psychiatry 2005; 162: 370--376. 42 Holmans PA, Riley B, Pulver AE, Owen MJ, Wildenauer DB, Gejman PV et al. 15 WHO. The Global Burden of Disease: 2004 Update. WHO Press: Geneva, Switzer- Genomewide linkage scan of schizophrenia in a large multicenter pedigree land, 2008. sample using single nucleotide polymorphisms. Mol Psychiatry 2009; 14: 786--795.

Molecular Psychiatry (2013), 38 -- 52 & 2013 Macmillan Publishers Limited The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 49 43 Ng MY, Levinson DF, Faraone SV, Suarez BK, DeLisi LE, Arinami T et al. Meta- 68 Ruderfer DM, Kirov G, Chambert K, Moran JL, Owen MJ, O0Donovan MC et al. analysis of 32 genome-wide linkage studies of schizophrenia. Mol Psychiatry A family-based study of common polygenic variation and risk of schizophrenia. 2009; 14: 774--785. Mol Psychiatry 2011; 16: 887--888. 44 Allen NC, Bagade S, McQueen MB, Ioannidis JPA, Kavvoura FK, Khoury MJ et al. 69 Mitchell KJ, Porteous DJ. Rethinking the genetic architecture of schizophrenia. Systematic meta-analyses and field synopsis of genetic association studies in Psychol Med 2010; 41: 1--14. schizophrenia: the SzGene database. Nat Genet 2008; 40: 827--834. 70 Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB. Rare variants create 45 Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS et al. synthetic genome-wide associations. PLoS Biol 2010; 8: e1000294. Potential etiologic and functional implications of genome-wide association loci 71 Anderson CA, Soranzo N, Zeggini E, Barrett JC. Synthetic associations are unlikely for human diseases and traits. Proc Natl Acad Sci USA 2009; 106: 9362--9367. to account for many common disease genome-wide association signals. PLoS 46 Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery. Am J Biol 2011; 9: e1000580. Human Genet 2012; 90: 7--24. 72 Wray NR, Purcell SM, Visscher PM. Synthetic associations created by rare variants 47 Mah S, Nelson MR, Delisi LE, Reneland RH, Markward N, James MR et al. do not explain most GWAS results. PLoS Biol 2011; 9: e1000579. Identification of the semaphorin receptor PLXNA2 as a candidate for 73 Lee SH, DeCandia TR, Ripke S, Yang J, The Schizophrenia Psychiatric Genome susceptibility to schizophrenia. Mol Psychiatry 2006; 11: 471--478. Wide Association Study Consortium (PGC-SCZ), The International Schizophrenia 48 Lencz T, Morgan TV, Athanasiou M, Dain B, Reed CR, Kane JM et al. Converging Consortium (ISC) et al. Estimating the proportion of variation in susceptibility to evidence for a pseudoautosomal cytokine receptor gene locus in schizophrenia. schizophrenia captured by common SNPs. Nat Genet 2012; 44: 247--250. Mol Psychiatry 2007; 12: 572--580. 74 Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR et al. 49 Sullivan PF, Lin D, Tzeng JY, van den Oord E, Perkins D, Stroup TS et al. Common SNPs explain a large proportion of the heritability for human height. Genomewide association for schizophrenia in the CATIE study: results of stage 1. Nat Genet 2010; 42: 565--569. Mol Psychiatry 2008; 13: 570--584. 75 Walsh T, McClellan JM, McCarthy SE, Addington AM, Pierce SB, Cooper GM et al. 50 Kirov G, Zaharieva I, Georgieva L, Moskvina V, Nikolov I, Cichon S et al. A Rare structural variants disrupt multiple genes in neurodevelopmental pathways genome-wide association study in 574 schizophrenia trios using DNA pooling. in schizophrenia. Science 2008; 320: 539--543. Mol Psychiatry 2009; 14: 796--803. 76 Stone JL, O0Donovan MC, Gurling H, Kirov GK, Blackwood DHR, Corvin A et al. 51 Liu Y, Chen G, Norton N, Liu W, Zhu H, Zhou P et al. Whole genome association Rare chromosomal deletions and duplications increase risk of schizophrenia. study in a homogenous population in Shandong peninsula of China reveals Nature 2008; 455: 237--241. JARID2 as a susceptibility gene for schizophrenia. J Biomed Biotechnol 2009; 77 Levinson DF, Duan J, Oh S, Wang K, Sanders AR, Shi J et al. Copy number variants 2009: 536918. in schizophrenia: confirmation of five previous findings and new evidence 52 Need AC, Ge D, Weale ME, Maia J, Feng S, Heinzen EL et al. A genome- for 3q29 Microdeletions and VIPR2 Duplications. Am J Psychiatry 2011; 168: wide investigation of SNPs and CNVs in schizophrenia. PLoS Genet 2009; 5: 302--316. e1000373. 78 Malhotra D, McCarthy S, Michaelson JJ, Vacic V, Burdick KE, Yoon S et al. High 53 Purcell SM, Wray NR, Stone JL, Visscher PM, O0Donovan MC, Sullivan PF et al. frequencies of De Novo CNVs in bipolar disorder and schizophrenia. Neuron Common polygenic variation contributes to risk of schizophrenia and bipolar 2011; 72: 951--963. disorder. Nature 2009; 460: 748--752. 79 Xu B, Roos JL, Levy S, Van Rensburg EJ, Gogos JA, Karayiorgou M. Strong 54 Shi J, Levinson DF, Duan J, Sanders AR, Zheng Y, Pe0er I et al. Common variants association of de novo copy number mutations with sporadic schizophrenia. Nat on chromosome 6p22.1 are associated with schizophrenia. Nature 2009; 460: Genet 2008; 40: 880--885. 753--757. 80 Kirov G, Pocklington AJ, Holmans P, Ivanov D, Ikeda M, Ruderfer D et al. 55 Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D De novo CNV analysis implicates specific abnormalities of postsynaptic signalling et al. Common variants conferring risk of schizophrenia. Nature 2009; 460: complexes in the pathogenesis of schizophrenia. Mol Psychiatry 2012; 17: 744--747. 142--153. 56 Rietschel M, Mattheisen M, Degenhardt F, Kahn RS, Linszen DH, Os JV et al. 81 Stefansson H, Rujescu D, Cichon S, Pietilainen OPH, Ingason A, Steinberg S et al. Association between genetic variation in a region on chromosome 11 and Large recurrent microdeletions associated with schizophrenia. Nature 2008; 455: schizophrenia in large samples from Europe. Mol Psychiatry advance online 232--236. publication, 12 July 2011; doi:10.1038/mp.2011.80. 82 Kirov G, Rujescu D, Ingason A, Collier DA, O0Donovan MC, Owen MJ. Neurexin 1 57 Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA et al. Genome- (NRXN1) deletions in schizophrenia. Schizophr Bull 2009; 35: 851--854. wide association study identifies five new schizophrenia loci. Nat Genet 2011; 43: 83 McCarthy SE, Makarov V, Kirov G, Addington AM, McClellan J, Yoon S et al. 969--976. Microduplications of 16p11.2 are associated with schizophrenia. Nat Genet 2009; 58 Shi Y, Li Z, Xu Q, Wang T, Li T, Shen J et al. Common variants on 8p12 and 1q24.2 41: 1223--1227. confer risk of schizophrenia. Nat Genet 2011; 43: 1224--1227. 84 Rujescu D, Ingason A, Cichon S, Pietila¨inen OPH, Barnes MR, Toulopoulou T et al. 59 Steinberg S, de Jong S, Andreassen OA, Werge T, Borglum AD, Mors O et al. Disruption of the neurexin 1 gene is associated with schizophrenia. Hum Mol Common variants at VRK2 and TCF4 conferring risk of schizophrenia. Human Mol Genet 2009; 18: 988--996. Genet 2011; 20: 4076--4081. 85 Ingason A, Rujescu D, Cichon S, Sigurdsson E, Sigmundsson T, Pietilainen OP 60 Yue W-H, Wang H-F, Sun L-D, Tang F-L, Liu Z-H, Zhang H-X et al. Genome-wide et al. Copy number variations of chromosome 16p13.1 region associated with association study identifies a susceptibility locus for schizophrenia in Han schizophrenia. Mol Psychiatry 2011; 16: 17--25. Chinese at 11p11.2. Nat Genet 2011; 43: 1228--1231. 86 Vacic V, McCarthy S, Malhotra D, Murray F, Chou H-H, Peoples A et al. 61 O0Donovan MC, Craddock N, Norton N, Williams H, Peirce T, Moskvina V et al. Duplications of the neuropeptide receptor gene VIPR2 confer significant risk for Identification of loci associated with schizophrenia by genome-wide association schizophrenia. Nature 2011; 471: 499--503. and follow-up. Nat Genet 2008; 40: 1053--1055. 87 Rees E, Moskvina V, Owen MJ, O0Donovan MC, Kirov G. De novo rates and 62 Smrt RD, Szulwach KE, Pfeiffer RL, Li X, Guo W, Pathania M et al. MicroRNA miR- selection of schizophrenia-associated copy number variants. Biol Psychiatry 2011; 137 regulates neuronal maturation by targeting ubiquitin ligase mind bomb-1. 70: 1109--1114. Stem Cells 2010; 28: 1060--1070. 88 Haukka J, Suvisaari J, Lonnqvist J. Fertility of patients with schizophrenia, their 63 Silber J, Lim DA, Petritsch C, Persson AI, Maunakea AK, Yu M et al. miR-124 and siblings, and the general population: a cohort study from 1950 to 1959 in miR-137 inhibit proliferation of glioblastoma multiforme cells and induce Finland. Am J Psychiatry 2003; 160: 460--463. differentiation of brain tumor stem cells. BMC Med 2008; 6:14. 89 Melhem N, Middleton F, McFadden K, Klei L, Faraone SV, Vinogradov S et al. 64 Ikeda M, Aleksic B, Kinoshita Y, Okochi T, Kawashima K, Kushima I et al. Genome- Copy number variants for schizophrenia and related psychotic disorders in wide association study of schizophrenia in a Japanese population. Biol Psychiatry oceanic Palau: risk and transmission in extended pedigrees. Biol Psychiatry 2011; 2011; 69: 472--478. 70: 1115--1121. 65 Visscher PM, Goddard ME, Derks EM, Wray NR. Evidence-based psychiatric 90 Pinto D, Darvishi K, Shi X, Rajan D, Rigler D, Fitzgerald T et al. Comprehensive genetics, AKA the false dichotomy between common and rare variant assessment of array-based platforms and calling algorithms for detection of hypotheses. Mol Psychiatry advance online publication, 14 June 2011; copy number variants. Nat Biotechnol 2011; 29: 512--520. doi:10.1038/mp.2011.65. 91 Keller MC, Miller G. Resolving the paradox of common, harmful, heritable mental 66 Craddock N, O0Donovan MC, Owen MJ. Phenotypic and genetic complexity of disorders: which evolutionary genetic models work best? Behav Brain Sci 2006; psychosis. Invited commentary on Schizophrenia: a common disease caused by 29: 385. multiple rare alleles. Br J Psychiatry 2007; 190: 200--203. 92 Durbin RM, Abecasis GR, Altshuler DL, Auton A, Brooks LD, Gibbs RA et al. A map 67 McClellan JM, Susser E, King M-C. Schizophrenia: a common disease caused by of human genome variation from population-scale sequencing. Nature 2010; multiple rare alleles. Br J Psychiatry 2007; 190: 194--199. 467: 1061--1073.

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 38 -- 52 The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 50 93 State MW, Levitt P. The conundrums of understanding genetic risks for autism 116 Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F et al. spectrum disorders. Nat Neurosci 2011; 14: 1499--1506. Hundreds of variants clustered in genomic loci and biological pathways affect 94 Girard SL, Gauthier J, Noreau A, Xiong L, Zhou S, Jouan L et al. Increased human height. Nature 2010; 467: 832--838. exonic de novo mutation rate in individuals with schizophrenia. Nat Genet 117 O0Dushlaine C, Kenny E, Heron E, Donohoe G, Gill M, Morris D et al. Molecular 2011; 43: 860--863. pathways involved in neuronal cell adhesion and membrane scaffolding 95 Xu B, Roos JL, Dexheimer P, Boone B, Plummer B, Levy S et al. Exome sequencing contribute to schizophrenia and bipolar disorder susceptibility. Mol Psychiatry supports a de novo mutational paradigm for schizophrenia. Nat Genet 2011; 43: 2010; 16: 286--292. 864--868. 118 Lips ES, Cornelisse LN, Toonen RF, Min JL, Hultman CM, Holmans PA et al. 96 Addington AM, Gauthier J, Piton A, Hamdan FF, Raymond A, Gogtay N et al. Functional gene group analysis identifies synaptic gene groups as risk factor for A novel frameshift mutation in UPF3B identified in brothers affected with schizophrenia. Mol Psychiatry advance online publication, 20 September 2011; childhood onset schizophrenia and autism spectrum disorders. Mol Psychiatry doi:10.1038/mp.2011.117. 2011; 16: 238--239. 119 Glessner JT, Reilly MP, Kim CE, Takahashi N, Albano A, Hou C et al. Strong 97 Awadalla P, Gauthier J, Myers RA, Casals F, Hamdan FF, Griffing AR et al. Direct synaptic transmission impact by copy number variations in schizophrenia. Proc measure of the de novo mutation rate in autism and schizophrenia cohorts. Am J Natl Acad Sci USA 2010; 107: 10584--10589. Hum Genet 2010; 87: 316--324. 120 Raychaudhuri S, Korn JM, McCarroll SA, Consortium IS, Altshuler D, Sklar P et al. 98 Carroll LS, Williams NM, Moskvina V, Russell E, Norton N, Williams HJ et al. Accurately assessing the risk of schizophrenia conferred by rare copy-number Evidence for rare and common genetic risk variants for schizophrenia at protein variation affecting genes with brain function. PLoS Genet 2010; 6: e1001097; kinase C, alpha. Mol Psychiatry 2010; 15: 1101--1111. doi:10.1371/journal.pgen.1001097. 99 Frank RA, McRae AF, Pocklington AJ, van de Lagemaat LN, Navarro P, Croning 121 Kim Y, Zerwas S, Trace SE, Sullivan PF. Schizophrenia genetics: where next? MD et al. Clustered coding variants in the glutamate receptor complexes Schizophrenia Bull 2011; 37:456--463. of individuals with schizophrenia and bipolar disorder. PLoS One 2011; 122 Pritchard JK. Are rare variants responsible for susceptibility to complex diseases? 6: e19011. Am J Hum Genet 2001; 69: 124--137. 100 Gauthier J, Champagne N, Lafrenie`re RG, Xiong L, Spiegelman D, Brustein E et al. 123 Eyre-Walker A. Evolution in health and medicine sackler colloquium: genetic De novo mutations in the gene encoding the synaptic scaffolding protein architecture of a complex trait and its implications for fitness and genome- SHANK3 in patients ascertained for schizophrenia. Proc Natl Acad Sci USA 2010; wide association studies. Proc Natl Acad Sci USA 2010; 107(Suppl 1): 107: 7863--7868. 1752--1756. 101 Knight HM, Pickard BS, Maclean A, Malloy MP, Soares DC, McRae AF et al. A 124 Richards AL, Jones L, Moskvina V, Kirov G, Gejman PV, Levinson DF et al. cytogenetic abnormality and rare coding variants identify ABCA13 as a Schizophrenia susceptibility alleles are enriched for alleles that affect gene candidate gene in schizophrenia, bipolar disorder, and depression. Am J Hum expression in adult human brain. Mol Psychiatry 2011; 17: 193--201. Genet 2009; 85: 833--846. 125 Sullivan P. Don0t give up on GWAS. Mol Psychiatry 2011; 17:2--3. 102 Kushima I, Nakamura Y, Aleksic B, Ikeda M, Ito Y, Shiino T et al. Resequencing and 126 Lee SH, Wray NR, Goddard ME, Visscher PM. Estimating missing heritability for association analysis of the KALRN and EPHB1 genes and their contribution to disease from genome-wide association studies. Am J Human Genet 2011; 88: schizophrenia susceptibility. Schizophr Bull advance online publication, 1 294--305. November 2010; doi:10.1093/schbul/sbq118. 127 Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP et al. Twelve 103 Piton A, Gauthier J, Hamdan FF, Lafrenie`re RG, Yang Y, Henrion E et al. type 2 diabetes susceptibility loci identified through large-scale association Systematic resequencing of X-chromosome synaptic genes in autism spectrum analysis. Nat Genet 2010; 42: 579--589. disorder and schizophrenia. Mol Psychiatry 2011; 16: 867--880. 128 Yang J, Wray NR, Visscher PM. Comparing apples and oranges: equating the 104 Tarabeux J, Champagne N, Brustein E, Hamdan FF, Gauthier J, Lapointe M et al. power of case-control and quantitative trait association studies. Genet Epidemiol De novo truncating mutation in kinesin 17 associated with schizophrenia. Biol 2010; 34: 254--257. Psychiatry 2010; 68: 649--656. 129 Cortes A, Brown MA. Promise and pitfalls of the immunochip. Arthritis Res Ther 105 Vermeesch JR, Balikova I, Schrander-Stumpel C, Fryns JP, Devriendt K. The 2011; 13: 101. causality of de novo copy number variants is overestimated. Eur J Hum Genet 130 Trynka G, Hunt KA, Bockett NA, Romanos J, Mistry V, Szperl A et al. Dense 2011; 19: 1112--1113. genotyping identifies and localizes multiple common and rare variant 106 Lichtenstein P, Yip BH, Bjo¨rk C, Pawitan Y, Cannon TD, Sullivan PF et al. Common association signals in celiac disease. Nat Genet 2011; 43: 1193--1201. genetic determinants of schizophrenia and bipolar disorder in Swedish families: 131 Mardis ER. A decade0s perspective on DNA sequencing technology. Nature 2011; a population-based study. Lancet 2009; 373: 234--239. 470: 198--203. 107 Gottesman II, Laursen TM, Bertelsen A, Mortensen PB. Severe mental dis- 132 Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to orders in offspring with 2 psychiatrically ill parents. Arch Gen Psychiatry 2010; 67: common diseases. Nat Genet 2008; 40: 695--701. 252--257. 133 Shendure J. Next-generation human genetics. Genome Biol 2011; 12: 408. 108 Moskvina V, Craddock N, Holmans P, Nikolov I, Pahwa JS, Green E et al. Gene- 134 Bamshad MJ, Ng SB, Bigham AW, Tabor HK, Emond MJ, Nickerson DA et al. wide analyses of genome-wide association data sets: evidence for multiple Exome sequencing as a tool for Mendelian disease gene discovery. Nat Rev common risk alleles for schizophrenia and bipolar disorder and for overlap in Genet 2011; 12: 745--755. genetic risk. Mol Psychiatry 2009; 14: 252--260. 135 Najmabadi H, Hu H, Garshasbi M, Zemojtel T, Abedini SS, Chen W et al. Deep 109 Williams HJ, Craddock N, Russo G, Hamshere ML, Moskvina V, Dwyer S et al. Most sequencing reveals 50 novel genes for recessive cognitive disorders. Nature genome-wide significant susceptibility loci for schizophrenia and bipolar 2011; 478: 57--63. disorder reported to date cross-traditional diagnostic boundaries. Human Mol 136 Roach JC, Glusman G, Smit AF, Huff CD, Hubley R, Shannon PT et al. Analysis of Genet 2011; 20: 387--391. genetic inheritance in a family quartet by whole-genome sequencing. Science 110 Williams HJ, Norton N, Dwyer S, Moskvina V, Nikolov I, Carroll L et al. Fine 2010; 328: 636--639. mapping of ZNF804A and genome-wide significant evidence for its involvement 137 Li B, Leal SM. Discovery of rare variants via sequencing: implications for the in schizophrenia and bipolar disorder. Mol Psychiatry 2011; 16: 429--441. design of complex trait association studies. PLoS Genet 2009; 5: e1000481. 111 Sklar P, Ripke S, Scott LJ, Andreassen OA, Cichon S, Craddock N et al. Large-scale 138 Morris AP, Zeggini E. An evaluation of statistical approaches to rare genome-wide association analysis of bipolar disorder identifies a new variant analysis in genetic association studies. Genet Epidemiol 2010; 34: susceptibility locus near ODZ4. Nat Genet 2011; 43: 977--983. 188--193. 112 Glessner JT, Wang K, Cai G, Korvatska O, Kim CE, Wood S et al. Autism genome- 139 Sulem P, Gudbjartsson DF, Walters GB, Helgadottir HT, Helgason A, Gudjonsson wide copy number variation reveals ubiquitin and neuronal genes. Nature 2009; SA et al. Identification of low-frequency variants associated with gout and serum 459: 569--573. uric acid levels. Nat Genet 2011; 43: 1127--1130. 113 Mefford HC, Sharp AJ, Baker C, Itsara A, Jiang Z, Buysse K et al. Recurrent 140 Rivas MA, Beaudoin M, Gardet A, Stevens C, Sharma Y, Zhang CK et al. Deep rearrangements of chromosome 1q21.1 and variable pediatric phenotypes. resequencing of GWAS loci identifies independent rare variants associated with N Engl J Med 2008; 359: 1685--1699. inflammatory bowel disease. Nat Genet 2011; 43: 1066--1073. 114 Quintero-Rivera F, Sharifi-Hannauer P, Martinez-Agosto JA. Autistic and 141 Raychaudhuri S, Iartchouk O, Chin K, Tan PL, Tai AK, Ripke S et al. Arare psychiatric findings associated with the 3q29 microdeletion syndrome: case penetrant mutation in CFH confers high risk of age-related macular degenera- report and review. Am J Med Genet A 2010; 152A: 2459--2467. tion. Nat Genet 2011; 43: 1232--1236. 115 Sivakumaran S, Agakov F, Theodoratou E, Prendergast JG, Zgaga L, Manolio T 142 Bonnefond A, Clement N, Fawcett K, Yengo L, Vaillant E, Guillaume JL et al. Rare et al. Abundant pleiotropy in human complex diseases and traits. Am J Human MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 Genet 2011; 89: 607--618. diabetes. Nat Genet 2012; 44: 297--301.

Molecular Psychiatry (2013), 38 -- 52 & 2013 Macmillan Publishers Limited The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 51 143 Yokoyama S, Woods SL, Boyle GM, Aoude LG, MacGregor S, Zismann V et al. A 171 Meyer-Lindenberg A. From maps to mechanisms through neuroimaging of novel recurrent mutation in MITF predisposes to familial and sporadic schizophrenia. Nature 2010; 468: 194--202. melanoma. Nature 2011; 480: 99--103. 172 Greenwood TA, Braff DL, Light GA, Cadenhead KS, Calkins ME, Dobie DJ et al. 144 Cooper GM, Shendure J. Needles in stacks of needles: finding disease-causal Initial heritability analyses of endophenotypic measures for schizophrenia: the variants in a wealth of genomic data. Nat Rev Genet 2011; 12: 628--640. consortium on the genetics of schizophrenia. Arch Gen Psychiatry 2007; 64: 145 Ozsolak F, Milos PM. RNA sequencing: advances, challenges and opportunities. 1242--1250. Nat Rev Genet 2011; 12: 87--98. 173 Boos HB, Aleman A, Cahn W, Hulshoff Pol H, Kahn RS. Brain volumes in relatives 146 Kang HJ, Kawasawa YI, Cheng F, Zhu Y, Xu X, Li M et al. Spatio-temporal of patients with schizophrenia: a meta-analysis. Arch Gen Psychiatry 2007; 64: transcriptome of the human brain. Nature 2011; 478: 483--489. 297--304. 147 Colantuoni C, Lipska BK, Ye T, Hyde TM, Tao R, Leek JT et al. Temporal dynamics 174 Goldman AL, Pezawas L, Mattay VS, Fischl B, Verchinski BA, Zoltick B et al. and genetic control of transcription in the human prefrontal cortex. Nature 2011; Heritability of brain morphology related to schizophrenia: a large-scale automated 478: 519--523. magnetic resonance imaging segmentation study. Biol Psychiatry 2008; 63:475--483. 148 Werner T. Next generation sequencing in functional genomics. Brief Bioinform 175 Esslinger C, Walter H, Kirsch P, Erk S, Schnell K, Arnold C et al. Neural mechanisms 2010; 11: 499--511. of a genome-wide supported psychosis variant. Science 2009; 324: 605. 149 Ala-Korpela M, Kangas AJ, Inouye M. Genome-wide association studies and 176 Esslinger C, Kirsch P, Haddad L, Mier D, Sauer C, Erk S et al. Cognitive state and systems biology: together at last. Trends Genet 2011; 27: 493--498. connectivity effects of the genome-wide significant psychosis variant in 150 Dempster EL, Pidsley R, Schalkwyk LC, Owens S, Georgiades A, Kane F et al. ZNF804A. Neuroimage 2011; 54: 2514--2523. Disease-associated epigenetic changes in monozygotic twins discordant 177 Paulus FM, Krach S, Bedenbender J, Pyka M, Sommer J, Krug A et al. Partial for schizophrenia and bipolar disorder. Hum Mol Genet 2011; 20: support for ZNF804A genotype-dependent alterations in prefrontal connectivity. 4786--4796. Human Brain Mapping advance online publication, 31 October 2011; 151 Mudge J, Miller NA, Khrebtukova I, Lindquist IE, May GD, Huntley JJ et al. doi:10.1002/hbm.21434. Genomic convergence analysis of schizophrenia: mRNA sequencing reveals 178 Lencz T, Szeszko PR, DeRosse P, Burdick KE, Bromet EJ, Bilder RM et al. A altered synaptic vesicular transport in post-mortem cerebellum. PLoS One 2008; schizophrenia risk gene, ZNF804A, influences neuroanatomical and neurocog- 3: e3625. nitive phenotypes. Neuropsychopharmacol Off Publication Am Coll Neuropsycho- 152 Rollins B, Martin MV, Morgan L, Vawter MP. Analysis of whole genome biomarker pharmacol 2010; 35: 2284--2291. expression in blood and brain. Am J Med Genet B Neuropsychiatr Genet 2010; 179 Erk S, Meyer-Lindenberg A, Schnell K, Opitz von Boberfeld C, Esslinger C, Kirsch P 153B: 919--936. et al. Brain function in carriers of a genome-wide supported bipolar disorder 153 Goldsmith CA, Rogers DP. The case for autoimmunity in the etiology of variant. Arch Gen Psychiatry 2010; 67: 803--811. schizophrenia. Pharmacotherapy 2008; 28: 730--741. 180 Zhang Q, Shen Q, Xu Z, Chen M, Cheng L, Zhai J et al. The effects of CACNA1C 154 Yang J, Chen T, Sun L, Zhao Z, Qi X, Zhou K et al. Potential metabolite markers of gene polymorphism on spatial working memory in both healthy controls schizophrenia. Mol Psychiatry advance online publication, 25 October 2011; and patients with schizophrenia or bipolar disorder. Neuropsychopharmacology doi:10.1038/mp.2011.131. 2012; 37; 677--684. 155 Deep-Soboslay A, Benes FM, Haroutunian V, Ellis JK, Kleinman JE, Hyde TM. 181 Chow EW, Ho A, Wei C, Voormolen EH, Crawley AP, Bassett AS. Association of Psychiatric brain banking: three perspectives on current trends and future schizophrenia in 22q11.2 deletion syndrome and gray matter volumetric deficits directions. Biol Psychiatry 2011; 69: 104--112. in the superior temporal gyrus. Am J Psychiatry 2011; 168: 522--529. 156 Wu SM, Hochedlinger K. Harnessing the potential of induced pluripotent stem 182 Neul JL. Unfolding neurodevelopmental disorders: the mystery of developing cells for regenerative medicine. Nat Cell Biol 2011; 13: 497--505. connections. Nat Med 2011; 17: 1353--1355. 157 Huttner A, Rakic P. Diagnosis in a dish: your skin can help your brain. Nat Med 183 Insel TR. Rethinking schizophrenia. Nature 2010; 468: 187--193. 2011; 17: 1558--1559. 184 Wray NR, Yang J, Goddard ME, Visscher PM. The genetic interpretation of area 158 Chiang CH, Su Y, Wen Z, Yoritomo N, Ross CA, Margolis RL et al. Integration-free under the ROC curve in genomic profiling. PLoS Genet 2010; 6: e1000864. induced pluripotent stem cells derived from schizophrenia patients with a DISC1 185 Wray NR, Goddard ME, Visscher PM. Prediction of individual genetic risk to disease mutation. Mol Psychiatry 2011; 16: 358--360. from genome-wide association studies. Genome Res 2007; 17: 1520--1528. 159 Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S et al. 186 Wray NR, Goddard ME, Visscher PM. Prediction of individual genetic risk of Modelling schizophrenia using human induced pluripotent stem cells. Nature complex disease. Curr Opin Genet Dev 2008; 18: 257--263. 2011; 473: 221--225. 187 Arranz MJ, Rivera M, Munro JC. Pharmacogenetics of response to antipsychotics 160 Pedrosa E, Sandler V, Shah A, Carroll R, Chang C, Rockowitz S et al. Development in patients with schizophrenia. CNS Drugs 2011; 25: 933--969. of patient-specific neurons in schizophrenia using induced pluripotent stem 188 Paul SM. Therapeutic antibodies for brain disorders. Sci Transl Med 2011; 3: cells. J Neurogenet 2011; 25: 88--103. 84ps20. 161 Kvajo M, McKellar H, Gogos JA. Avoiding mouse traps in schizophrenia genetics: 189 Muglia P. From genes to therapeutic targets for psychiatric disorders - what to lessons and promises from current and emerging mouse models. Neuroscience expect? Curr Opin Pharmacol 2011; 11: 563--571. advance online publication, 27 July 2011; doi:10.1016/j.neuroscience. 190 Abbott A. Novartis to shut brain research facility. Nature 2011; 480: 161--162. 2011.07.051 (in press). 191 Freedman R, Coon H, Myles-Worsley M, Orr-Urtreger A, Olincy A, Davis A et al. 162 Merscher S, Funke B, Epstein JA, Heyer J, Puech A, Lu MM et al. TBX1 is Linkage of a neurophysiological deficit in schizophrenia to a chromosome 15 responsible for cardiovascular defects in velo-cardio-facial/DiGeorge syndrome. locus. Proc Natl Acad Sci USA 1997; 94: 587--592. Cell 2001; 104: 619--629. 192 Leonard S, Gault J, Moore T, Hopkins J, Robinson M, Olincy A et al. Further 163 Stark KL, Xu B, Bagchi A, Lai WS, Liu H, Hsu R et al. Altered brain microRNA investigation of a chromosome 15 locus in schizophrenia: analysis of affected biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model. sibpairs from the NIMH Genetics Initiative. Am J Med Genet 1998; 81: 308--312. Nat Genet 2008; 40: 751--760. 193 Stephens SH, Franks A, Berger R, Palionyte M, Fingerlin TE, Wagner B et al. 164 Burne T, Scott E, van Swinderen B, Hilliard M, Reinhard J, Claudianos C et al. Big Multiple genes in the 15q13-q14 chromosomal region are associated with ideas for small brains: what can psychiatry learn from worms, flies, bees and fish? schizophrenia. Psychiatr Genet 2012; 22: 1--14. Mol Psychiatry 2011; 16: 7--16. 194 Court J, Spurden D, Lloyd S, McKeith I, Ballard C, Cairns N et al. Neuronal nicotinic 165 van Alphen B, van Swinderen B. Drosophila strategies to study psychiatric receptors in dementia with Lewy bodies and schizophrenia: alpha-bungarotoxin disorders. Brain Res Bull advance online publication, 17 September 2011; and nicotine binding in the thalamus. J Neurochem 1999; 73: 1590--1597. doi:10.1016/j.brainresbull.2011.09.007 (in press). 195 Martin LF, Kem WR, Freedman R. Alpha-7 nicotinic receptor agonists: potential 166 Brennand KJ, Gage FH. Concise review: the promise of human induced new candidates for the treatment of schizophrenia. Psychopharmacology 2004; pluripotent stem cell-based studies of schizophrenia. Stem Cells 2011; 29: 174: 54--64. 1915--1922. 196 Olincy A, Harris JG, Johnson LL, Pender V, Kongs S, Allensworth D et al. Proof-of- 167 Dolmetsch R, Geschwind DH. The human brain in a dish: the promise of iPSC- concept trial of an alpha7 nicotinic agonist in schizophrenia. Arch Gen Psychiatry derived neurons. Cell 2011; 145: 831--834. 2006; 63: 630--638. 168 Dragunow M. The adult human brain in preclinical drug development. Nat Rev 197 Freedman R, Olincy A, Buchanan RW, Harris JG, Gold JM, Johnson L et al. Initial Drug Discovery 2008; 7: 659--666. phase 2 trial of a nicotinic agonist in schizophrenia. Am J Psychiatry 2008; 165: 169 Rakic P. Evolution of the neocortex: a perspective from developmental biology. 1040--1047. Nat Rev Neurosci 2009; 10: 724--735. 198 Tregellas JR, Tanabe J, Rojas DC, Shatti S, Olincy A, Johnson L et al. Effects of an 170 Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology alpha 7-nicotinic agonist on default network activity in schizophrenia. Biol and strategic intentions. Am J Psychiatry 2003; 160: 636--645. Psychiatry 2011; 69: 7--11.

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 38 -- 52 The emerging spectrum of allelic variation in schizophrenia BJ Mowry and J Gratten 52 199 Williams DK, Wang J, Papke RL. Positive allosteric modulators as an approach to 208 Miller DT, Shen Y, Weiss LA, Korn J, Anselm I, Bridgemohan C et al. nicotinic acetylcholine receptor-targeted therapeutics: advantages and limita- Microdeletion/duplication at 15q13.2q13.3 among individuals with features of tions. Biochem Pharmacol 2011; 82: 915--930. autism and other neuropsychiatric disorders. J Med Genet 2009; 46: 242--248. 200 Green ED, Guyer MS. Charting a course for genomic medicine from base pairs to 209 Sharp AJ, Mefford HC, Li K, Baker C, Skinner C, Stevenson RE et al. A recurrent bedside. Nature 2011; 470: 204--213. 15q13.3 microdeletion syndrome associated with mental retardation and 201 Ikeda M, Aleksic B, Kirov G, Kinoshita Y, Yamanouchi Y, Kitajima T et al. Copy seizures. Nat Genet 2008; 40: 322--328. number variation in schizophrenia in the Japanese population. Biol Psychiatry 210 Helbig I, Mefford HC, Sharp AJ, Guipponi M, Fichera M, Franke A et al. 15q13.3 2010; 67: 283--286. microdeletions increase risk of idiopathic generalized epilepsy. Nat Genet 2009; 202 Szatmari P, Paterson AD, Zwaigenbaum L, Roberts W, Brian J, Liu XQ et al. 41: 160--162. Mapping autism risk loci using genetic linkage and chromosomal rearrange- 211 Ingason A, Kirov G, Giegling I, Hansen T, Isles AR, Jakobsen KD et al. Maternally ments. Nat Genet 2007; 39: 319--328. derived microduplications at 15q11-q13: implication of imprinted genes in 203 Magri C, Sacchetti E, Traversa M, Valsecchi P, Gardella R, Bonvicini C et al. New psychotic illness. Am J Psychiatry 2011; 168: 408--417. copy number variations in schizophrenia. PLoS One 2010; 5: e13422. 212 Weiss LA, Shen Y, Korn JM, Arking DE, Miller DT, Fossdal R et al. Association 204 Mulle JG, Dodd AF, McGrath JA, Wolyniec PS, Mitchell AA, Shetty AC et al. between microdeletion and microduplication at 16p11.2 and autism. NEnglJ Microdeletions of 3q29 confer high risk for schizophrenia. Am J Hum Genet 2010; Med 2008; 358: 667--675. 87: 229--236. 213 Fernandez BA, Roberts W, Chung B, Weksberg R, Meyn S, Szatmari P et al. 205 Willatt L, Cox J, Barber J, Cabanas ED, Collins A, Donnai D et al. 3q29 Phenotypic spectrum associated with de novo and inherited deletions and dupli- microdeletion syndrome: clinical and molecular characterization of a new cations at 16p11.2 in individuals ascertained for diagnosis of autism spectrum syndrome. Am J Hum Genet 2005; 77: 154--160. disorder. J Med Genet 2010; 47: 195--203. 206 Kirov G, Grozeva D, Norton N, Ivanov D, Mantripragada KK, Holmans P et al. 214 Ullmann R, Turner G, Kirchhoff M, Chen W, Tonge B, Rosenberg C et al. Array Support for the involvement of large copy number variants in the pathogenesis CGH identifies reciprocal 16p13.1 duplications and deletions that predispose to of schizophrenia. Hum Mol Genet 2009; 18: 1497--1503. autism and/or mental retardation. Human Mutation 2007; 28: 674--682. 207 Christian SL, Fantes JA, Mewborn SK, Huang B, Ledbetter DH. Large genomic 215 Chance PF, Alderson MK, Leppig KA, Lensch MW, Matsunami N, Smith B et al. duplicons map to sites of instability in the Prader-Willi/Angelman syndrome DNA deletion associated with hereditary neuropathy with liability to pressure chromosome region (15q11-q13). Hum Mol Genet 1999; 8: 1025--1037. palsies. Cell 1993; 72: 143--151.

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