Genetics Roundup: Motley Crew of Variants Kicks Off 2013
12 March 2013. Genetic studies of schizophrenia in the past two months have served up more leads of both the rare and common variety. While some of the rare ones incriminate single genes already familiar to schizophrenia researchers, one implicates a whole new territory on chromosome 16. These findings are complemented by two studies pointing to contributions by common variants to mental illness. One study finds that common variants may have "hyperlocal" effects on risk for bipolar disorder in a single family, not just across a population; a second study fingers a common variant that combines with an environmental factor to increase risk for schizophrenia. These varied findings highlight the complexity of the genetic basis of schizophrenia.
The first study, published online January 16 in JAMA Psychiatry, reports a rare deletion on the far end of 16p11.2 that is associated with schizophrenia in large, and multiple, samples. If you’re thinking you’ve heard of 16p11.2 before, you have: it harbors a locus known for its "mirror phenotypes," with duplications associated with microcephaly, schizophrenia, and autism, and deletions with macrocephaly and autism (see SRF related news story), and recently a common variant there has been associated with psychosis (see SRF related news story). But the new study implicates a completely different, non-overlapping section 600 kilobases away. A transatlantic collaboration led by Todd Lencz of Zucker Hillside Hospital in Glen Oaks, New York, and George Kirov of Cardiff University in Cardiff, U.K., looked for copy number variations (CNVs) in two separate samples, one from Bulgaria, and one of Ashkenazi Jews.
First authors Saurav Guha and Elliott Rees and colleagues found a 220 kb deletion in the distal part of 16p11.2 in two cases from each sample. As ever, the challenge with rare variants is to convincingly link them to disease, so to gather supporting evidence, the researchers scoured eight independent samples for this deletion. This, combined with the events from the initial discovery samples, garnered a total of 13 deletions in 13,850 cases of schizophrenia (0.094 percent) and three among 19,954 controls (0.015 percent). The difference in frequency amounted to an odds ratio of 6.25 (p = 0.001), meaning that the deletion was associated with over a sixfold increase in risk for schizophrenia.
The exact size of the deletion varied among carriers, but all deletions were missing nine genes, some of which have been linked to neurological diseases, or insulin or leptin function. This jibes with previous work that has linked distal 16p11.2 deletions to developmental delay and obesity (e.g., Bachmann-Gagescu et al., 2010).
Do not pass up NPAS3
Taking a more focused approach, Frederick Nucifora of Johns Hopkins University in Baltimore, Maryland, and colleagues sequenced the neuronal PAS domain protein 3 (NPAS3) gene in 34 families affected by multiple cases of schizophrenia. NPAS3 encodes a transcription factor, and has been associated with schizophrenia before, via common variants (Pickard et al., 2009) and rare, gene-disrupting mutations (Kamnasaran et al., 2003). In a brief report published online January 22 in Molecular Psychiatry, first author Lan Yu and colleagues describe a point mutation found in one of these families that converts a valine to an isoleucine in the resulting protein. The mutation was found in a mother and two of her children, all three of whom had schizophrenia. It was also found in another child, who had major depression. Additional risk alleles could be at work in this family, however, because non-carriers in the family also had psychiatric disorders. Still, the mutation seemed potentially pathogenic, as mutant copies of NPAS3 in cultured mouse neurons limited the growth of neuronal processes—something consistent with a role in neuronal wiring, and in line with the idea that schizophrenia stems from disrupted neurodevelopment.
Studying families densely affected by mental illness can be a good way to find a variant with a strong effect, but this is not always the end result, according to another brief report published online December 18, 2012, in Molecular Psychiatry. A team led by Patrick Sullivan of the University of North Carolina in Chapel Hill, together with Markus Nöthen of the University of Bonn, Germany, and Marcella Rietschel of Heidelberg University in Mannheim, Germany, studied a Spanish family with 18 cases of bipolar disorder and seven cases of major depressive disorder. Sequencing the parts of the genome held in common among the family members did not turn up any strong leads, nor did looking for CNVs in the entire genome. But when the researchers added up the risk contributed by common variants linked to bipolar disorder (PGC Bipolar Disorder Working Group, 2011), the risk scores in affected family members were significantly greater than those from the unaffected. These risk scores were similar to those found in an affected sample of unrelated cases, and suggest that an enrichment for multiple, common variants may underlie mental illness in some families.
A diagnostic spectrum
The inhibitory synapse takes center stage in a study published online February 7 in Human Molecular Genetics. Led by Steven Scherer of The Hospital for Sick Children in Toronto, Canada, the study reports deletions and point mutations in gephryin (GPHN), a molecular organizer of inhibitory synapses, in schizophrenia, autism, and seizures. GPHN encodes a protein that forms a bridge between glycine or γ-aminobutyric acid (GABA) receptors and the interior cytoskeleton, and promotes their clustering at the postsynaptic side of an inhibitory synapse. Previous research has implicated GPHN in schizophrenia (Lencz et al., 2007), and the molecule has fallen under further suspicion because of its interactions with other schizophrenia- and autism-associated molecules, including neurexins and neuroligins.
First author Anath Lionel and colleagues combed GPHN for CNVs or point mutations in people with schizophrenia, autism, or seizure disorders. This search turned up small deletions within the protein-coding part of the gene in six cases of either schizophrenia, autism, or seizure disorder (out of 8,775 surveyed) and in three controls (out of 27,019), and protein-changing "missense" mutations in six cases of autism. The results implicate GPHN in autism for the first time, and add GPHN to the list of genetic risk factors shared between autism and schizophrenia. The findings also fit with ideas of impaired inhibitory transmission in schizophrenia (see SRF Hypothesis; see also SRF related news story), and highlight the machinery of inhibitory synapses alongside that of its excitatory counterparts (see SRF related news story).
The precise type of mutation may determine the resulting disorder, according to another paper published online February 5 in Human Molecular Genetics. Liesbeth Rooms of University of Antwerp, Belgium, and colleagues set their sights on the ANK3 gene, a well-established risk factor for bipolar disorder and schizophrenia (see SRF related news story). Like GPHN, ANK3 also bridges membrane-bound receptors to the cytoskeleton, though ANK3 connects with voltage-gated sodium channels that cluster at action potential-propagating zones along the axon. First authors Zafar Iqbal, Geert Vandeweyer, and Monique van der Voet report inactivating disruptions to ANK3 in people with intellectual disability. The researchers suggest that a drastic loss of ANK3 function leads to intellectual disability, whereas subtler changes like those introduced by common variants would promote less severe psychiatric conditions. If true, then genes with an established link to intellectual disability may warrant special attention in the hunt for risk alleles contributing to complex psychiatric disorders.
While it is clear that the effects of genetic risk alleles may be modulated by environment, it is harder to know which of the seemingly infinite environmental factors to study. As previously reported in a dispatch from WCPG 2012 (see SRF related conference story), a team has been exploring whether cytomegalovirus infection of mothers during pregnancy might interact with genetic risk factors carried by their fetuses. Cytomegalovirus targets the nervous system, and maternal infection with it has been connected to schizophrenia risk (see SRF related news story). Led by Anders Børglum of Aarhus University in Denmark, and published online January 29 in Molecular Psychiatry, the study plumbs Danish population databases that contain mental health information on all people born in Denmark since 1981, as well as stored blood spots collected upon their birth. DNA extracted from the babies’ blood can give clues about their genetic risk for the disorder, and antibodies detected in the blood can give a readout as to whether the mother was infected with cytomegalovirus at the time of birth because newborns do not yet make their own antibodies.
The researchers first did a straightforward genomewide association study (GWAS) by surveying single nucleotide polymorphisms (SNPs) in 888 people with schizophrenia and 882 controls. Not surprisingly for the smallish sample size, no one SNP reached genomewide significance (i.e., p <5 x 10-8). Follow-up analyses in a separate Danish sample and a German-Dutch sample also did not produce any genomewide significant signals, nor did combining the samples. When looking for SNPs that boosted risk for schizophrenia in the presence of maternal cytomegalovirus infection, the researchers found one flagging CTNNA3, a gene encoding a cell adhesion protein. On its own, cytomegalovirus infection did not increase risk for schizophrenia, nor did the SNP marking CTNNA3, but when combined they produced a fivefold increase in risk (p = 7.3 x 10-7). Though other confounding factors, such as socioeconomic status, may explain this result (i.e., socioeconomic status correlates with cytomegalovirus infection, and with schizophrenia risk), it suggests that considering environmental factors in concert with GWAS may reveal entirely new leads.—Michele Solis.
Børglum AD, Demontis D, Grove J, Pallesen J, Hollegaard MV, Pedersen CB, Hedemand A, Mattheisen M; GROUP investigators, Uitterlinden A, Nyegaard M, Orntoft T, Wiuf C, Didriksen M, Nordentoft M, Nöthen MM, Rietschel M, Ophoff RA, Cichon S, Yolken RH, Hougaard DM, Mortensen PB, Mors O. Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci. Mol Psychiatry. 2013 Jan 29. Abstract
Collins AL, Kim Y, Szatkiewicz JP, Bloom RJ, Hilliard CE, Quackenbush CR, Meier S, Rivas F, Mayoral F, Cichon S, Nöthen MM, Rietschel M, Sullivan PF. Identifying bipolar disorder susceptibility loci in a densely affected pedigree. Mol Psychiatry. 2012 Dec 18. Abstract
Guha S, Rees E, Darvasi A, Ivanov D, Ikeda M, Bergen SE, Magnusson PK, Cormican P, Morris D, Gill M, Cichon S, Rosenfeld JA, Lee A, Gregersen PK, Kane JM, Malhotra AK, Rietschel M, Nöthen MM, Degenhardt F, Priebe L, Breuer R, Strohmaier J, Ruderfer DM, Moran JL, Chambert KD, Sanders AR, Shi J, Kendler K, Riley B, O'Neill T, Walsh D, Malhotra D, Corvin A, Purcell S, Sklar P, Iwata N, Hultman CM, Sullivan PF, Sebat J, McCarthy S, Gejman PV, Levinson DF, Owen MJ, O'Donovan MC, Lencz T, Kirov G, . Implication of a rare deletion at distal 16p11.2 in schizophrenia. JAMA Psychiatry. 2013 Mar 1; 70(3):253-60. Abstract
Iqbal Z, Vandeweyer G, van der Voet M, Waryah AM, Zahoor MY, Besseling JA, Roca LT, Vulto-van Silfhout AT, Nijhof B, Kramer JM, Van der Aa N, Ansar M, Peeters H, Helsmoortel C, Gilissen C, E L M Vissers L, Veltman JA, de Brouwer AP, Frank Kooy R, Riazuddin S, Schenck A, van Bokhoven H, Rooms L. Homozygous and heterozygous disruptions of ANK3: at the crossroads of neurodevelopmental and psychiatric disorders. Hum Mol Genet. 2013 Feb 18. Abstract
Lionel AC, Vaags AK, Sato D, Gazzellone MJ, Mitchell EB, Chen HY, Costain G, Walker S, Egger G, Thiruvahindrapuram B, Merico D, Prasad A, Anagnostou E, Fombonne E, Zwaigenbaum L, Roberts W, Szatmari P, Fernandez BA, Georgieva L,
Brzustowicz LM, Roetzer K, Kaschnitz W, Vincent JB, Windpassinger C, Marshall CR, Trifiletti RR, Kirmani S, Kirov G, Petek E, Hodge JC, Bassett AS, Scherer SW. Rare exonic deletions implicate the synaptic organizer Gephyrin (GPHN) in risk for autism, schizophrenia and seizures. Hum Mol Genet. 2013 Feb 20. Abstract
Yu L, Arbez N, Nucifora LG, Sell GL, Delisi LE, Ross CA, Margolis RL, Nucifora FC Jr. A mutation in NPAS3 segregates with mental illness in a small family. Mol Psychiatry. 2013 Jan 22. Abstract
Comments on News and Primary Papers
Primary Papers: A mutation in NPAS3 segregates with mental illness in a small family.Comment by: Ben Pickard
Submitted 5 February 2013
Posted 5 February 2013
The paper by Yu et al. places another tick next to the NPAS3 candidate gene. Since the discovery of its disruption by a chromosomal translocation in a mother and daughter—both diagnosed with schizophrenia—it has cropped up several times in case-control association and mutation screens. This transcription factor has also accrued a catalogue of functional characteristics that align it well with potential schizophrenia pathologies. These include behavioral, neurodevelopmental, metabolic, and hippocampal neurogenesis deficits detected in a mouse knockout model, and a cellular pathology that includes mitochondrial fragility (Pickard et al., 2006; Sha et al., 2012; Pieper et al., 2010).
This latest chapter in the NPAS3 story details how the authors carried out resequencing in families densely affected with schizophrenia diagnoses. They identified a missense mutation (rs146677388) that changed the valine residue normally at this site into isoleucine in one such family. Although not large enough to generate a significant LOD score, the mutation obeys co-segregation with the diagnosis of schizophrenia in the family. However, it should be noted that all non-carriers in the family were diagnosed with lesser psychiatric conditions. In follow-on studies, the authors demonstrated that the variant is indeed rare, but not entirely exclusive to the family or a diagnosis of schizophrenia.
The NPAS3 gene is both very highly conserved at the protein level (down to fish) while also containing intronic regions that show strong evidence for rapid evolution in humans (Pollard et al., 2006). The identified V->I change is actually located within a span of four residues that show a breakdown in conservation in fish and amphibians. Therefore, as ever, the problem becomes one of trying to demonstrate that a rare variant has a pathological effect. The first steps on that path are taken in the paper when the authors demonstrate an in-vitro inhibitory effect of the mutation on neurite outgrowth in comparison to the wild-type NPAS3.
What next? More mutations and positive associations would certainly add supporting evidence, but the real struggle will be to unify the disparate nature of the phenotypes linked with NPAS3 dysfunction at the level of a specific pathology—one that must involve altered regulation of this transcription factor’s target genes.
Pickard BS, Pieper AA, Porteous DJ, Blackwood DH, Muir WJ. The NPAS3 gene--emerging evidence for a role in psychiatric illness. Ann Med . 2006 ; 38(6):439-48. Abstract
Sha L, Macintyre L, Machell JA, Kelly MP, Porteous DJ, Brandon NJ, Muir WJ, Blackwood DH, Watson DG, Clapcote SJ, Pickard BS. Transcriptional regulation of neurodevelopmental and metabolic pathways by NPAS3. Mol Psychiatry . 2012 Mar ; 17(3):267-79. Abstract
Pieper AA, Xie S, Capota E, Estill SJ, Zhong J, Long JM, Becker GL, Huntington P, Goldman SE, Shen CH, Capota M, Britt JK, Kotti T, Ure K, Brat DJ, Williams NS, MacMillan KS, Naidoo J, Melito L, Hsieh J, De Brabander J, Ready JM, McKnight SL. Discovery of a proneurogenic, neuroprotective chemical. Cell . 2010 Jul 9 ; 142(1):39-51.
Pollard KS, Salama SR, Lambert N, Lambot MA, Coppens S, Pedersen JS, Katzman S, King B, Onodera C, Siepel A, Kern AD, Dehay C, Igel H, Ares M, Vanderhaeghen P, Haussler D. An RNA gene expressed during cortical development evolved rapidly in humans. Nature . 2006 Sep 14 ; 443(7108):167-72. Abstract
View all comments by Ben Pickard
Comments on Related News
Related News: GWAS Goes Bigger: Large Sample Sizes Uncover New Risk Loci, Additional Overlap in Schizophrenia and Bipolar DisorderComment by: David J. Porteous, SRF Advisor
Submitted 21 September 2011
Posted 21 September 2011
Consorting with GWAS for schizophrenia and bipolar disorder: same message, (some) different genes
On 18 September 2011, Nature Genetics published the results from the Psychiatric Genetics Consortium of two separate, large-scale GWAS analyses, for schizophrenia (Ripke et al., 2011) and for bipolar disorder (Sklar et al., 2011), and a joint analysis of both. By combining forces across several consortia who have previously published separately, we should now have some clarity and definitive answers.
For schizophrenia, the Stage 1 GWAS discovery data came from 9,394 cases and 12,462 controls from 17 studies, imputing 1,252,901 SNPs. The Stage 2 replication sample comprised 8,442 cases and 21,397 controls. Of the 136 SNPs which reached genomewide significance in Stage 1, 129 (95 percent) mapped to the MHC locus, long known to be associated with risk of schizophrenia. Of the remaining seven SNPs, five mapped to previously identified loci. In total, just 10 loci met or exceeded the criteria of genomewide significance of p <5 x 10-8 at Stage 1 and/or Stage 2. The 10 "best" SNPs identified eight loci: MIR137, TRIM26, CSM1, CNNM2, NT5C2 and TCF4 were tagged by intragenic SNPs, while the remaining two were at some distance from a known gene (343 kb from PCGEM1 and 126 kb from CCDC68). More important than the absolute significance levels, the overall odds ratios (with 95 percent confidence intervals) ranged from 1.08 (0.96-1.20) to 1.40 (1.28-1.52). These fractional increases contrast with the ~10-fold increase in risk to the first-degree relative of someone with schizophrenia (Gottesman et al., 2010).
Six of these eight loci have been reported previously, but ZNF804A, a past favorite, was noticeably absent from the "top 10" list. The main attention now will surely be on MIR137, a newly discovered locus which encodes a microRNA, mir137, known to regulate neuronal development. The authors remark that 17 predicted MIR137 targets had a SNP with a p <10-4, more than twice as many as for the control gene set (p <0.01), though this relaxed significance cutoff seems somewhat arbitrary and warrants further examination. The result for MIR137 immediately begs the questions, Does the "risk" SNP affect MIR137 function directly or indirectly, and if so, does it affect the expression of any of the putative targets identified here? These are fairly straightforward questions: positive answers are vital to the biological validation of these statistical associations. As has been the case for follow-up studies of ZNF804A, however (reviewed by Donohoe et al., 2010), unequivocal answers from GWAS "hits" can be hard to come by, not least because of the very modest relative risks that they confer. Let us hope that this is not the case for MIR137, but it is of passing note that for two of the eight replication cohorts, the direction of effect for MIR137 was in the opposite direction from the Stage 1 finding. Taken together with the odds ratios reported in the range of 1.11-1.22, the effect size for the end phenotype of schizophrenia may be challenging to validate functionally. Perhaps a relevant intermediate phenotype more proximal to the gene will prove tractable.
For bipolar disorder, Stage 1 comprised 7,481 cases versus 9,250 controls, and identified 34 promising SNPs. These were replicated in Stage 2 in an independent set of 4,496 cases and a whopping 42,422 controls: 18 of the 34 SNPs survived at p <0.05. Taking Stage 1 and 2 together confirmed the previous "hot" finding for CACNA1C (Odds ratio = 1.14) and introduced a new candidate in ODZ4 (Odds ratio = 0.88, i.e., the minor allele is presumably "protective" or under some form of selection). Previous candidates ANK3 and SYNE1 looked promising at Stage 1, but did not replicate at Stage 2.
Finally, in a combined analysis of schizophrenia plus bipolar disorder versus controls, three of the respective "top 10" loci, CACNA1C, ANK3, and the ITIH3-ITIH4 region, came out as significant overall. This is consistent with the earlier evidence from the ISC for an overlap between the polygenic index for schizophrenia and bipolar disorder (Purcell et al., 2009). It is also consistent with the epidemiological evidence for shared genetic risk between schizophrenia and bipolar disorder (Lichtenstein et al., 2009; Gottesman et al., 2010).
What can we take from these studies? The authorship lists alone speak to the size of the collaborative effort involved and the sheer organizational task, depending on your point of view, that most of the positive findings were reported on previously could be seen as valuable "replication," or unnecessary duplication of cost and effort. Whichever way you look at it, though, just two new loci for schizophrenia and one for bipolar looks like a modest return for such a gargantuan investment. It begs the question as to whether the GWAS approach is gaining the hoped-for traction on major mental illness. Indeed, the evidence suggests that the technology tide is rapidly turning away from allelic association methods and towards rare mutation detection by copy number variation, exome, and/or whole-genome sequencing (Vacic et al., 2011; Xu et al., 2011).
Family studies are, as ever and always, of critical importance in genetics, and to distinguish between inherited and de-novo mutations. While the emphasis of GWAS has been on the impact of common, ancient allelic variation, it has become ever more obvious from both past linkage studies and from contemporary GWAS and CNV studies just how heterogeneous these conditions are, and how little note individual cases and families take of conventional DSM diagnostic boundaries. Improved genetic and other tools through which to stratify risk, define phenotypes, and predict outcomes are clearly needed. Whether such tools can be derived for GWAS data remains to be seen. It is important to remind ourselves of two things. First, case/association studies tell us something about the average impact (odds ratio, with confidence interval) of a given allele in the population studied. In these very large GWAS, this measure of impact will be approximating to the European population average. The odds ratios tell us that the impact per allele is modest. More importantly in some ways, the allele frequencies also tell us that the vast majority of allele carriers are not affected. Likewise, a high proportion of cases are not carriers. In the main, they are subtle risk modifiers rather than causal variants. That said, follow-up studies may define rare, functional genetic variants in MIR137 or CACNA1C or ANK3 that are tagged by the risk allele and that have sufficiently strong effects in a subset of cases for a causal link to be made. With this new GWAS data in hand, these sorts of questions can now be addressed.
It should also be said that there is clearly a wealth of potentially valuable information lying below the surface of the most statistically significant findings, but how to sort the true from the false associations? Should the MIR137 finding, and the targets of MIR137, be substantiated by biological analysis, then that would certainly be something well worth knowing and following up on. Network analysis by gene ontology and protein-protein interaction may yield more, but these approaches need to be approached with caution when not securely anchored from a biologically validated start point. Epistasis and pleiotropy are most likely playing a role, but even in these large sample sets, the power to determine statistical (as opposed to biological) evidence is challenging. All told, one is left thinking that more incisive findings have and will in the future come from family-based approaches, through structural studies (CNVs and chromosome translocations), and, in the near future, whole-genome sequencing of cases and relatives.
Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA, Lin DY, Duan J, Ophoff RA, Andreassen OA, Scolnick E, Cichon S, St Clair D, Corvin A, Gurling H, Werge T, Rujescu D, Blackwood DH, Pato CN, Malhotra AK, Purcell S, Dudbridge F, Neale BM, Rossin L, Visscher PM, Posthuma D, Ruderfer DM, Fanous A, Stefansson H, Steinberg S, Mowry BJ, Golimbet V, de Hert M, Jönsson EG, Bitter I, Pietiläinen OP, Collier DA, Tosato S, Agartz I, Albus M, Alexander M, Amdur RL, Amin F, Bass N, Bergen SE, Black DW, Børglum AD, Brown MA, Bruggeman R, Buccola NG, Byerley WF, Cahn W, Cantor RM, Carr VJ, Catts SV, Choudhury K, Cloninger CR, Cormican P, Craddock N, Danoy PA, Datta S, de Haan L, Demontis D, Dikeos D, Djurovic S, Donnelly P, Donohoe G, Duong L, Dwyer S, Fink-Jensen A, Freedman R, Freimer NB, Friedl M, Georgieva L, Giegling I, Gill M, Glenthøj B, Godard S, Hamshere M, Hansen M, Hansen T, Hartmann AM, Henskens FA, Hougaard DM, Hultman CM, Ingason A, Jablensky AV, Jakobsen KD, Jay M, Jürgens G, Kahn RS, Keller MC, Kenis G, Kenny E, Kim Y, Kirov GK, Konnerth H, Konte B, Krabbendam L, Krasucki R, Lasseter VK, Laurent C, Lawrence J, Lencz T, Lerer FB, Liang KY, Lichtenstein P, Lieberman JA, Linszen DH, Lönnqvist J, Loughland CM, Maclean AW, Maher BS, Maier W, Mallet J, Malloy P, Mattheisen M, Mattingsdal M, McGhee KA, McGrath JJ, McIntosh A, McLean DE, McQuillin A, Melle I, Michie PT, Milanova V, Morris DW, Mors O, Mortensen PB, Moskvina V, Muglia P, Myin-Germeys I, Nertney DA, Nestadt G, Nielsen J, Nikolov I, Nordentoft M, Norton N, Nöthen MM, O'Dushlaine CT, Olincy A, Olsen L, O'Neill FA, Orntoft TF, Owen MJ, Pantelis C, Papadimitriou G, Pato MT, Peltonen L, Petursson H, Pickard B, Pimm J, Pulver AE, Puri V, Quested D, Quinn EM, Rasmussen HB, Réthelyi JM, Ribble R, Rietschel M, Riley BP, Ruggeri M, Schall U, Schulze TG, Schwab SG, Scott RJ, Shi J, Sigurdsson E, Silverman JM, Spencer CC, Stefansson K, Strange A, Strengman E, Stroup TS, Suvisaari J, Terenius L, Thirumalai S, Thygesen JH, Timm S, Toncheva D, van den Oord E, van Os J, van Winkel R, Veldink J, Walsh D, Wang AG, Wiersma D, Wildenauer DB, Williams HJ, Williams NM, Wormley B, Zammit S, Sullivan PF, O'Donovan MC, Daly MJ, Gejman PV. Genome-wide association study identifies five new schizophrenia loci. Nat Genet . 2011 Sep 18. Abstract
Psychiatric GWAS Consortium Bipolar Disorder Working Group, Sklar P, Ripke S, Scott LJ, Andreassen OA, Cichon S, Craddock N, Edenberg HJ, Nurnberger JI Jr, Rietschel M, Blackwood D, Corvin A, Flickinger M, Guan W, Mattingsdal M, McQuillin A, Kwan P, Wienker TF, Daly M, Dudbridge F, Holmans PA, Lin D, Burmeister M, Greenwood TA, Hamshere ML, Muglia P, Smith EN, Zandi PP, Nievergelt CM, McKinney R, Shilling PD, Schork NJ, Bloss CS, Foroud T, Koller DL, Gershon ES, Liu C, Badner JA, Scheftner WA, Lawson WB, Nwulia EA, Hipolito M, Coryell W, Rice J, Byerley W, McMahon FJ, Schulze TG, Berrettini W, Lohoff FW, Potash JB, Mahon PB, McInnis MG, Zöllner S, Zhang P, Craig DW, Szelinger S, Barrett TB, Breuer R, Meier S, Strohmaier J, Witt SH, Tozzi F, Farmer A, McGuffin P, Strauss J, Xu W, Kennedy JL, Vincent JB, Matthews K, Day R, Ferreira MA, O'Dushlaine C, Perlis R, Raychaudhuri S, Ruderfer D, Hyoun PL, Smoller JW, Li J, Absher D, Thompson RC, Meng FG, Schatzberg AF, Bunney WE, Barchas JD, Jones EG, Watson SJ, Myers RM, Akil H, Boehnke M, Chambert K, Moran J, Scolnick E, Djurovic S, Melle I, Morken G, Gill M, Morris D, Quinn E, Mühleisen TW, Degenhardt FA, Mattheisen M, Schumacher J, Maier W, Steffens M, Propping P, Nöthen MM, Anjorin A, Bass N, Gurling H, Kandaswamy R, Lawrence J, McGhee K, McIntosh A, McLean AW, Muir WJ, Pickard BS, Breen G, St Clair D, Caesar S, Gordon-Smith K, Jones L, Fraser C, Green EK, Grozeva D, Jones IR, Kirov G, Moskvina V, Nikolov I, O'Donovan MC, Owen MJ, Collier DA, Elkin A, Williamson R, Young AH, Ferrier IN, Stefansson K, Stefansson H, Thornorgeirsson T, Steinberg S, Gustafsson O, Bergen SE, Nimgaonkar V, Hultman C, Landén M, Lichtenstein P, Sullivan P, Schalling M, Osby U, Backlund L, Frisén L, Langstrom N, Jamain S, Leboyer M, Etain B, Bellivier F, Petursson H, Sigur Sson E, Müller-Mysok B, Lucae S, Schwarz M, Schofield PR, Martin N, Montgomery GW, Lathrop M, Oskarsson H, Bauer M, Wright A, Mitchell PB, Hautzinger M, Reif A, Kelsoe JR, Purcell SM. Large-scale genome-wide association analysis of bipolar disorder reveals a new susceptibility locus near ODZ4. Nat Genet. 2011 Sep 18. Abstract
Lichtenstein P, Yip BH, Björk C, Pawitan Y, Cannon TD, Sullivan PF, Hultman CM. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet . 2009 Jan 17 ; 373(9659):234-9. Abstract
Gottesman II, Laursen TM, Bertelsen A, Mortensen PB. Severe mental disorders in offspring with 2 psychiatrically ill parents. Arch Gen Psychiatry . 2010 Mar 1 ; 67(3):252-7. Abstract
Donohoe G, Morris DW, Corvin A. The psychosis susceptibility gene ZNF804A: associations, functions, and phenotypes. Schizophr Bull . 2010 Sep 1 ; 36(5):904-9. Abstract
Purcell SM, Wray NR, Stone JL, Visscher PM, O'Donovan MC, Sullivan PF, Sklar P. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature . 2009 Aug 6 ; 460(7256):748-52. Abstract
Vacic V, McCarthy S, Malhotra D, Murray F, Chou HH, Peoples A, Makarov V, Yoon S, Bhandari A, Corominas R, Iakoucheva LM, Krastoshevsky O, Krause V, Larach-Walters V, Welsh DK, Craig D, Kelsoe JR, Gershon ES, Leal SM, Dell Aquila M, Morris DW, Gill M, Corvin A, Insel PA, McClellan J, King MC, Karayiorgou M, Levy DL, DeLisi LE, Sebat J. Duplications of the neuropeptide receptor gene VIPR2 confer significant risk for schizophrenia. Nature . 2011 Mar 24 ; 471(7339):499-503. Abstract
Xu B, Roos JL, Dexheimer P, Boone B, Plummer B, Levy S, Gogos JA, Karayiorgou M. Exome sequencing supports a de novo mutational paradigm for schizophrenia. Nat Genet . 2011 Jan 1 ; 43(9):864-8. Abstract
View all comments by David J. Porteous
Related News: GWAS Goes Bigger: Large Sample Sizes Uncover New Risk Loci, Additional Overlap in Schizophrenia and Bipolar Disorder
Comment by: Patrick Sullivan, SRF Advisor
Submitted 26 September 2011
Posted 26 September 2011
I recommend the Primary Papers
The two papers appearing online in Nature Genetics last Sunday are truly important additions to our increasing knowledge base for these disorders. The core analyses have been presented multiple times at international meetings in the past two years.
Since then, the available sample sizes for both schizophrenia and bipolar disorder have grown considerably. If the recently published data are any guide, the next round of analyses should be particularly revealing.
The PGC results and almost all of the data that were used in these reports are available by application to the controlled-access repository.
Please see the references for views of this area that contrast with those of Professor Porteous.
Sullivan P. Don't give up on GWAS. Molecular Psychiatry. 2011 Aug 9. Abstract
Kim Y, Zerwas S, Trace SE, Sullivan PF. Schizophrenia genetics: where next? Schizophr Bull. 2011;37:456-63. Abstract
View all comments by Patrick Sullivan
Related News: GWAS Goes Bigger: Large Sample Sizes Uncover New Risk Loci, Additional Overlap in Schizophrenia and Bipolar Disorder
Comment by: Edward Scolnick
Submitted 28 September 2011
Posted 29 September 2011
I recommend the Primary Papers
It is clear in human genetics that common variants and rare variants have frequently been detected in the same genes. Numerous examples exist in many diseases. The bashing of GWAS in schizophrenia and bipolar illness indicates, by those who make such comments, a lack of understanding of human genetics and where the field is. When these studies were initiated five years ago, next-generation sequencing was not available. Large samples of populations or trios or quartets did not exist. The international consortia have worked to collect such samples that are available for GWAS now, as well as for detailed sequencing studies. Before these studies began there was virtually nothing known about the etiology of schizophrenia and bipolar illness. The DISC1 gene translocation in the famous family was an important observation in that family. But almost a decade later there is still no convincing data that variants in Disc1 or many of its interacting proteins are involved in the pathogenesis of human schizophrenia or major mental illness.
Sequencing studies touted to be the Occam's razor for the field are beginning, and already, as in the past in this field, preemptive papers are appearing inadequately powered to draw any conclusions with certainty. Samples collected by the consortia will be critical to clarify the role of rare variants. This will take time and care so as not to set the field back into the morass it used to be. GWAS are basically modern public health epidemiology providing important clues to disease etiology. Much work is clearly needed once hits are found, just as it has been in traditional epidemiology. But in many fields, GWAS has already led to important biological insights, and it is certain it will do so in this field as well because the underlying principles of human genetics apply to this field, also. The primary problem in the field is totally inadequate funding by government organizations that consistently look for shortcuts to gain insights and new treatments, and forget how genetics has transformed cancer, immunology, autoimmune and inflammatory diseases, and led to better diagnostics and treatments. The field will never understand the pathogenesis of these illnesses until the genetic architecture is deciphered. The first enzyme discovered in E. coli DNA biochemistry was a repair enzyme—not the enzyme that replicated DNA—and this was discovered through genetics. The progress in this field has been dramatic in the past five years. All doing this work realize that this is only a beginning and that there is a long hard road to full understanding. But to denigrate the beginning, which is clearly solid, makes no sense and indicates a provincialism unbecoming to a true scientist.
View all comments by Edward Scolnick
Related News: GWAS Goes Bigger: Large Sample Sizes Uncover New Risk Loci, Additional Overlap in Schizophrenia and Bipolar Disorder
Comment by: Nick Craddock, Michael O'Donovan (SRF Advisor)
Submitted 11 October 2011
Posted 11 October 2011
At the start of the millennium, only two molecular genetic findings could be said with a fair amount of confidence to be etiologically relevant to schizophrenia and bipolar disorder. The first of these was that deletions of chromosome 22q11 that are known to cause velo-cardio-facial syndrome also confer a substantial increase in risk of psychosis. The second was the discovery by David St Clair, Douglas Blackwood, and colleagues (St Clair et al., 1990) of a balanced translocation involving chromosomes 1 and 11 that co-segregates with a range of psychiatric phenotypes in a single large family, was clearly relevant to the etiology of illness in that family (Blackwood et al., 2001). The latter finding has led to the conjecture, based upon a translocation breakpoint analysis reported by Kirsty Millar, David Porteous, and colleagues (Millar et al., 2000), that elevated risk in that family is conferred by altered function of a gene eponymously named DISC1. Just over a decade later, what can we now say with similar degrees of confidence? The relevance of deletions of 22q11 has stood the test of time—indeed, has strengthened—through further investigation (Levinson et al., 2011, being only one example), while the relevance of DISC1 remains conjecture. That the evidence implicating this gene is no stronger than it was all those years ago provides a clear illustration of the difficulties inherent in drawing etiological inferences from extremely rare mutations regardless of their effect size.
However, with the publication of several GWAS and CNV papers, culminating in the two mega-analyses reported by the PGC that are the subject of this commentary, one on schizophrenia, one on bipolar disorder, together reporting a total of six novel loci, very strong evidence has accumulated for approximately 20 new loci in psychosis. The majority of these are defined by SNPs, the remainder by copy number variants, and virtually all (including the rare, relatively high-penetrance CNVs) have emerged through the application of GWAS technology to large case-control samples, not through the study of linkage or families. Have GWAS approaches proven their worth? Clearly, the genetic findings represent the tip of a very deeply submerged iceberg, and it is possible that not all will stand the test of time and additional data, although the current levels of statistical support suggest the majority will do so. Nevertheless, the findings of SNP and CNV associations (including 22q11 deletions) seem to us to provide the first real signs of progress in uncovering strongly supported findings of primary etiological relevance to these disorders. Although SNP effects are small, the experience from other complex phenotypes is that statistically robust genetic associations, even those of very small effect, can highlight biological pathways of etiological (height; Lango Allen et al., 2010) and of possible therapeutic relevance (Alzheimer's disease; Jones et al., 2010). Moreover, it would seem intuitively likely that even if capturing the total heritable component of a disorder is presently a distant goal, the greater the number of associations captured, the better will be the snapshot of the sorts of processes that contribute to a disorder, and that might therefore be manipulated in its treatment. Thus, there is evidence that building even a very incomplete picture of the sort of genes that influence risk is an excellent method of informing understanding of pathogenesis of a highly complex disorder (or set of disorders).
As in previous GWAS and CNV endeavors, the PGC studies have required a significant degree of altruism from the hundreds of investigators and clinicians who have shared their data with little hope of significant academic credit. Moreover, where ethical approval permitted, the datasets have been made virtually open source for other investigators who are not part of the study. Sadly, this generosity of spirit is not matched in the rather curmudgeonly commentary provided by David Porteous. Rather than challenging the science or conduct of the study, it appears to us that the commentary takes the easier route of damnation by faint praise, distortion, and even innuendo.
The strongest finding, that being of association to the extended MHC region, is dismissed as "long known to be associated with risk of schizophrenia." How that knowledge was acquired a long time ago is unclear, but it cannot have been based upon data. It is true that weak and inconsistent associations at the MHC locus have been reported, even predating the molecular genetic era (McGuffin et al., 1978), but not until the landmark studies of the International Schizophrenia Consortium (2009), the Molecular Genetics of Schizophrenia Consortium (AbstractShi et al., 2009), and the SGENE+ Consortium (Stefansson et al., 2009) have the findings been strong enough to be described as knowledge. Porteous’ dismissive tone continues with the phrase "just 10 loci met….," the word "just" being a qualifier that seems designed to denigrate rather than challenge the results. Given the paucity of etiological clues, others might consider this a good yield. The observation in which the effect sizes at the detected loci are contrasted "with the ~10-fold increase in risk to the first-degree relative of someone with schizophrenia" is so fatuous it is difficult to believe its function is anything other than to insinuate in the mind of the reader the impression of failure. Yet no one remotely aware of the expectations behind GWAS would expect that the effect sizes of any common risk allele would bear any resemblance to that of family history, the latter reflecting the combined effects of many risk alleles.
Among the most important findings of the PGC schizophrenia group were those of strong evidence for association between a variant in the vicinity of a gene encoding regulatory RNA MIR137, and the subsequent finding that schizophrenia association signals were significantly enriched (P <0.01) among predicted targets of this regulatory RNA. Of course, like the other findings, there is room for the already very strong data to be further strengthened, but that finding alone opens up a whole new window in potential pathogenic mechanisms. Yet Porteous casually throws four handfuls of mud, dismissing the enrichment p <0.01 as a "relaxed significance cutoff," which "seems somewhat arbitrary," and that "warrants further examination," and commenting that "it is of passing note that for two of the eight replication cohorts, the direction of effect for MIR137 was in the opposite direction from the Stage 1 finding." If Porteous feels he has the expertise to pronounce on this analysis, it would behoove him well to choose his words more carefully. Since when is a P value of <0.01 "relaxed" when applied to a test of a single hypothesis? Can he really be unaware of the longstanding convention of regarding P <0.05 as significant in specific hypothesis testing? If he is not unaware of this, why is it generally applicable but "somewhat arbitrary" in the context of the PGC study? As for "further examination being warranted," this is true of any scientific finding, but what does he specifically mean in the context of his commentary? And why is it of "passing note" that not all samples show trends in the same direction? In the context of the well-known issues in GWAS concerning individual small samples and power, what is surprising about that? There may be simple answers to these questions, but we find it difficult to draw any other conclusion than that the choice of language is anything other than another attempt to sow seeds of doubt through innuendo rather than analysis.
The remark that "ZNF804A, a past favourite, was noticeably absent" falls well short of the standard one might expect of serious discourse. The choice of language suggests a desire to denigrate rather than analyse, and to insinuate without specific evidence that any interest in this gene should now be over. In fact, the largest study of this gene to date is that of Williams et al. (2010), which actually includes at least two-thirds of the PGC discovery dataset and is based on over 57,000 subjects, a sample almost three times as large as the mega-analysis sample of the PGC.
Porteous’ overall conclusion from the two studies is "whichever way you look at it, though, just two new loci for schizophrenia and one for bipolar looks like a modest return for such a gargantuan investment." This appraisal is misleading. The PGC studies were actually relatively small investments, being based on a synthesis of pre-existing data. Since the studies use existing data, there is naturally an expectation that some of the loci identified will have been previously reported as either significant or have otherwise been flagged up as of interest, while some will be new. Overall, the return on the GWAS investment is not just the six novel loci (rather than three); it is the totality of the findings, which, as noted above, currently number about 20 loci. The schizophrenia research community should also be made aware, if they are not already, that the return on these investments is not "one off"; it is cumulative. In the coming years, the component datasets will continue to generate a return in new gene discoveries (including CNVs yet to be reported by the PGC) as they are added (at essentially no cost) to other emerging GWAS datasets being generated largely through charitable support. With the returns in the bank already, one could (and we do) argue that the investment is negligible, particularly given the cost in human and economic terms of continued ignorance about these illnesses that blight so many lives.
It is true that with so little being known compared with what is yet to be known, the biological insights that can be made from the existing data are limited. This is equally true of the common and rare variants identified so far, and we are not aware of any of the "incisive findings" that Porteous claims have already come from alternative approaches, although the emergence of strong evidence for deletions at NRXN1 as a susceptibility variant for schizophrenia through meta-analysis of case-control GWAS data (one of the extra returns on the GWAS data we referred to above) deserves that description (Kirov et al., 2009). But this is not a cause for despair; in contrast to the future promises made on behalf of other as yet unproven designs, for eyes and minds that are open enough to see, the recent papers provide unambiguous evidence for a straightforward route to identifying more genes and pathways involved in the disorder. Even Porteous has partial sight of this, since he notes that "there is clearly a wealth of potentially valuable information lying below the surface of the most statistically significant findings." What he appears unable to see is "how to sort the true from the false associations?" The answer for a large number of loci is simple. Better-powered studies based upon larger sample sizes.
We would like to add a note of caution for those who too readily denigrate case-control approaches in favor of hyping other approaches, none of which are yet so well proven routes to success. We are not against those approaches; indeed, we are actively involved in them. But we are concerned that the hype surrounding sequencing, and the generation of what we think are unrealistic expectations, will make those designs vulnerable to attack from those who seem only too keen to make premature and inaccurate pronouncements of failure, who seem desperate to derive straw from nuggets of gold. If, as we believe is likely, it turns out to be quite a few years more before sequencing studies become sufficiently powered to provide large numbers of robust findings, as for GWAS, the consequence could be withdrawal of substantial government funding before those designs have had a chance to live up to their potential. That such an outcome has already largely been achieved for GWAS in some countries might be a source of rejoicing in some quarters, but it should also send out a warning to all who broadly hold the view that understanding the genetics of these disorders is central to understanding their origins, and to improving their future management.
The recent PGC papers represent an impressive, international collaboration based upon methodologies that have a proven track record in delivering important biological insights into other complex disorders, and now in psychiatry. Given the complexity of psychiatric phenotypes, we believe it is likely that a variety of approaches, paradigms, and ideas will be essential for success, including the approaches espoused by those who believe the evidence is compatible with essentially Mendelian inheritance. Inevitably, there will be sincerely held differences of opinion concerning the best way forward, and, of course, in any area of science, reasoned arguments based upon a fair assessment of the evidence are essential. Nevertheless, given there are sufficient uncertainties about what can be realistically delivered in the short term by the newer technologies, we suggest that the cause of bringing benefit to patients will most likely be better served by humility, realism, and a constructive discussion in which there is no place for belittling real achievements, for arrogance, or for dogmatic posturing.
Blackwood DH, Fordyce A, Walker MT, St Clair DM, Porteous DJ, Muir WJ. Schizophrenia and affective disorders--cosegregation with a translocation at chromosome 1q42 that directly disrupts brain-expressed genes: clinical and P300 findings in a family. Am J Hum Genet. 2001 Aug;69(2):428-33. Abstract
International Schizophrenia Consortium Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009 Aug 6;460(7256):748-52. Abstract
Jones L, Holmans PA, Hamshere ML, Harold D, Moskvina V, Ivanov D, et al. Genetic evidence implicates the immune system and cholesterol metabolism in the etiology of Alzheimer's disease. PLoS One. 2010 Nov 15;5(11):e13950. Erratum in: PLoS One. 2011;6(2). Abstract
Kirov G, Rujescu D, Ingason A, Collier DA, O'Donovan MC, Owen MJ. Neurexin 1 (NRXN1) deletions in schizophrenia. Schizophr Bull. 2009 Sep;35(5):851-4. Epub 2009 Aug 12. Review. Abstract
Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F, et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature. 2010 Oct 14;467(7317):832-8. Abstract
Levinson DF, Duan J, Oh S, Wang K, Sanders AR, Shi J, et al. Copy number variants in schizophrenia: confirmation of five previous findings and new evidence for 3q29 microdeletions and VIPR2 duplications. Am J Psychiatry. 2011 Mar;168(3):302-16. Abstract
McGuffin P, Farmer AE, Rajah SM. Histocompatability antigens and schizophrenia. Br J Psychiatry. 1978 Feb;132:149-51. Abstract
Millar JK, Wilson-Annan JC, Anderson S, Christie S, Taylor MS, Semple CA, et al. Disruption of two novel genes by a translocation co-segregating with schizophrenia. Hum Mol Genet. 2000 May 22;9(9):1415-23. Abstract
Shi J, Levinson DF, Duan J, Sanders AR, Zheng Y, Pe'er I, et al. Common variants on chromosome 6p22.1 are associated with schizophrenia. Nature. 2009 Aug 6;460(7256):753-7. Abstract
St Clair D, Blackwood D, Muir W, Carothers A, Walker M, Spowart G, et al. Association within a family of a balanced autosomal translocation with major mental illness. Lancet. 1990 Jul 7;336(8706):13-6. Abstract
Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D, et al Common variants conferring risk of schizophrenia. Nature. 2009 Aug 6;460(7256):744-7. Abstract
The Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium. Genome-wide association study identifies five new schizophrenia loci. Nat Genet. 2011 Sep 18;43(10):969-976. Abstract
Williams HJ, Norton N, Dwyer S, Moskvina V, Nikolov I, Carroll L, et al. Fine mapping of ZNF804A and genome-wide significant evidence for its involvement in schizophrenia and bipolar disorder. Mol Psychiatry. 2011 Apr;16(4):429-41. Abstract
View all comments by Nick Craddock
View all comments by Michael O'Donovan
Related News: GWAS Goes Bigger: Large Sample Sizes Uncover New Risk Loci, Additional Overlap in Schizophrenia and Bipolar Disorder
Comment by: Todd Lencz, Anil Malhotra (SRF Advisor)
Submitted 11 October 2011
Posted 11 October 2011
It is worth re-emphasizing that efforts such as the Psychiatric GWAS Consortium do not rule out potentially important discoveries from alternative strategies such as endophenotypic approaches or examination of rare variants. Indeed, such strategies will be necessary to understand the functional mechanisms implicated by GWAS hits.
Moreover, we note that the two recently published PGC papers were not designed to exclude a role for previously identified candidate loci such as DISC1 (Hodgkinson et al., 2004), or prior GWAS findings such as rs1344706 at ZNF804A (Williams et al., 2011). For both these loci, and many others that have been proposed, meta-analysis of available samples suggest very small effect sizes (OR ~1.1), as might be expected for common variants. As noted in Supplementary Table S12 of the schizophrenia PGC paper (Ripke et al., 2011), the currently available sample size (~9,000 cases/~12,000 controls) of the discovery cohort was still underpowered to detect variants with odds ratios of 1.1, especially if they have a minor allele frequency of 20 percent or below.
An instructive example arises from the field of diabetes genetics. An association of a missense variant (rs1801282, Pro12Ala) in PPARG to type 2 diabetes was first reported in a sample of n = 91 Japanese-American patients (Deeb et al., 1998). Many subsequent studies failed to replicate the effect, and the initial large GWAS meta-analysis (involving >14,000 cases and ~18,000 controls; Zeggini et al., 2007) only detected the association at a p-value that would be considered non-significant by today’s standard (p =1.7*10-6). Interestingly, the authors deemed the association to be “confirmed,” and the result was widely accepted within that field. Subsequent meta-analysis, involving twice as many subjects (total n = 67,000), finally obtained conventional genomewide levels of significance (p <5*10-8; Gouda et al., 2010).
Deeb SS, Fajas L, Nemoto M, Pihlajamäki J, Mykkänen L, Kuusisto J, Laakso M, Fujimoto W, Auwerx J. A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet. 1998 Nov;20(3):284-7. Abstract
Gouda HN, Sagoo GS, Harding AH, Yates J, Sandhu MS, Higgins JP. The association between the peroxisome proliferator-activated receptor-gamma2 (PPARG2) Pro12Ala gene variant and type 2 diabetes mellitus: a HuGE review and meta-analysis. Am J Epidemiol. 2010 Mar 15;171(6):645-55. Abstract
Hodgkinson CA, Goldman D, Jaeger J, Persaud S, Kane JM, Lipsky RH, Malhotra AK. Disrupted in schizophrenia 1 (DISC1): association with schizophrenia, schizoaffective disorder, and bipolar disorder. Am J Hum Genet. 2004 Nov;75(5):862-72. Abstract
Williams HJ, Norton N, Dwyer S, Moskvina V, Nikolov I, Carroll L, Georgieva L, Williams NM, Morris DW, Quinn EM, Giegling I, Ikeda M, Wood J, Lencz T, Hultman C, Lichtenstein P, Thiselton D, Maher BS; Molecular Genetics of Schizophrenia Collaboration (MGS) International Schizophrenia Consortium (ISC), SGENE-plus, GROUP, Malhotra AK, Riley B, Kendler KS, Gill M, Sullivan P, Sklar P, Purcell S, Nimgaonkar VL, Kirov G, Holmans P, Corvin A, Rujescu D, Craddock N, Owen MJ, O'Donovan MC. Fine mapping of ZNF804A and genome-wide significant evidence for its involvement in schizophrenia and bipolar disorder. Mol Psychiatry. 2011 Apr;16(4):429-41. Abstract
Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, Timpson NJ, Perry JR, Rayner NW, Freathy RM, Barrett JC, Shields B, Morris AP, Ellard S, Groves CJ, Harries LW, Marchini JL, Owen KR, Knight B, Cardon LR, Walker M, Hitman GA, Morris AD, Doney AS; Wellcome Trust Case Control Consortium (WTCCC), McCarthy MI, Hattersley AT. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007 Jun 1;316(5829):1336-41. Abstract
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