A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry.

OBJECTIVE Gene-by-environment interaction (G×E) studies in psychiatry have typically been conducted using a candidate G×E (cG×E) approach, analogous to the candidate gene association approach used to test genetic main effects. Such cG×E research has received widespread attention and acclaim, yet cG×E findings remain controversial. The authors examined whether the many positive cG×E findings reported in the psychiatric literature were robust or if, in aggregate, cG×E findings were consistent with the existence of publication bias, low statistical power, and a high false discovery rate. METHOD The authors conducted analyses on data extracted from all published studies (103 studies) from the first decade (2000-2009) of cG×E research in psychiatry. RESULTS Ninety-six percent of novel cG×E studies were significant compared with 27% of replication attempts. These findings are consistent with the existence of publication bias among novel cG×E studies, making cG×E hypotheses appear more robust than they actually are. There also appears to be publication bias among replication attempts because positive replication attempts had smaller average sample sizes than negative ones. Power calculations using observed sample sizes suggest that cG×E studies are underpowered. Low power along with the likely low prior probability of a given cG×E hypothesis being true suggests that most or even all positive cG×E findings represent type I errors. CONCLUSIONS In this new era of big data and small effects, a recalibration of views about groundbreaking findings is necessary. Well-powered direct replications deserve more attention than novel cG×E findings and indirect replications.

[1]  Aribert Rothenberger,et al.  Genome‐wide association scan of quantitative traits for attention deficit hyperactivity disorder identifies novel associations and confirms candidate gene associations , 2008, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

[2]  P. Donnelly,et al.  Replicating genotype–phenotype associations , 2007, Nature.

[3]  K. Shedden,et al.  The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: evidence of genetic moderation. , 2011, Archives of general psychiatry.

[4]  C. Land,et al.  Improving the efficiency of nested case-control studies of interaction by selecting controls using counter matching on exposure. , 2004, International journal of epidemiology.

[5]  A. Caspi,et al.  Moderation of the Effect of Adolescent-Onset Cannabis Use on Adult Psychosis by a Functional Polymorphism in the Catechol-O-Methyltransferase Gene: Longitudinal Evidence of a Gene X Environment Interaction , 2005, Biological Psychiatry.

[6]  Cynthia M. Kuhn,et al.  Effects of Environmental Stress and Gender on Associations among Symptoms of Depression and the Serotonin Transporter Gene Linked Polymorphic Region (5-HTTLPR) , 2008, Behavior genetics.

[7]  P. Lee,et al.  Publication bias in meta-analysis: its causes and consequences. , 2000, Journal of clinical epidemiology.

[8]  P. McKeigue,et al.  Problems of reporting genetic associations with complex outcomes , 2003, The Lancet.

[9]  J. L. Tang,et al.  Misleading funnel plot for detection of bias in meta-analysis. , 2000, Journal of clinical epidemiology.

[10]  W. Gauderman,et al.  Gene-environment interaction in genome-wide association studies. , 2008, American journal of epidemiology.

[11]  Patrick F. Sullivan,et al.  Spurious Genetic Associations , 2007, Biological Psychiatry.

[12]  M. Munafo,et al.  Gene × Environment Interactions at the Serotonin Transporter Locus , 2009, Biological Psychiatry.

[13]  David B. Goldstein,et al.  A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia , 2009, PLoS genetics.

[14]  Lindon J. Eaves,et al.  Genotype × Environment Interaction in Psychopathology: Fact or Artifact? , 2006, Twin Research and Human Genetics.

[15]  J. Lieberman,et al.  Genomewide association for schizophrenia in the CATIE study: results of stage 1 , 2009, Molecular Psychiatry.

[16]  A. Caspi,et al.  PERSPECTIVES ON PSYCHOLOGICAL SCIENCE Measured Gene-Environment Interactions in Psychopathology Concepts, Research Strategies, and Implications for Research, Intervention, and Public Understanding of , 2022 .

[17]  Ahmad R. Hariri,et al.  Genetic Sensitivity to the Environment: The Case of the Serotonin Transporter Gene and Its Implications for Studying Complex Diseases and Traits , 2010 .

[18]  P. Lachenbruch Statistical Power Analysis for the Behavioral Sciences (2nd ed.) , 1989 .

[19]  F. Mayoral,et al.  The risk for depression conferred by stressful life events is modified by variation at the serotonin transporter 5HTTLPR genotype: evidence from the Spanish PREDICT-Gene cohort , 2007, Molecular Psychiatry.

[20]  J. Brooks Why most published research findings are false: Ioannidis JP, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece , 2008 .

[21]  S. Cichon,et al.  Genomewide association studies: history, rationale, and prospects for psychiatric disorders. , 2009, The American journal of psychiatry.

[22]  Judy H. Cho,et al.  Finding the missing heritability of complex diseases , 2009, Nature.

[23]  Jonathan Flint,et al.  Replication and heterogeneity in gene x environment interaction studies. , 2009, The international journal of neuropsychopharmacology.

[24]  Peter Boyle,et al.  Tobacco smoking and cancer: A meta‐analysis , 2008, International journal of cancer.

[25]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[26]  J H Lubin,et al.  Power and sample size calculations in case-control studies of gene-environment interactions: comments on different approaches. , 1999, American journal of epidemiology.

[27]  P. Terpstra,et al.  Poor replication of candidate genes for major depressive disorder using genome-wide association data , 2011, Molecular Psychiatry.

[28]  Kenneth S Kendler,et al.  Genetic influences on measures of the environment: a systematic review , 2006, Psychological Medicine.

[29]  E. Lenze,et al.  Gene-environment interactions and depression. , 2009, JAMA.

[30]  L. Eaves,et al.  Genotype x Environment interaction in psychopathology: fact or artifact? , 2006, Twin research and human genetics : the official journal of the International Society for Twin Studies.

[31]  N. Risch,et al.  Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: a meta-analysis. , 2009, JAMA.

[32]  Nathaniel Rothman,et al.  Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. , 2004, Journal of the National Cancer Institute.

[33]  N E Day,et al.  The design of case-control studies: the influence of confounding and interaction effects. , 1984, International journal of epidemiology.

[34]  J. Sinacore Multiple regression: Testing and interpreting interactions , 1993 .

[35]  P. Kraft,et al.  Integrating epidemiology and genetic association: the challenge of gene–environment interaction , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[36]  R S Kahn,et al.  Investigating gene environment interaction in complex diseases: increasing power by selective sampling for environmental exposure. , 2007, International journal of epidemiology.

[37]  Kent W. Smith,et al.  Decreasing Multicollinearity , 1979 .

[38]  T H Beaty,et al.  Minimum sample size estimation to detect gene-environment interaction in case-control designs. , 1994, American journal of epidemiology.

[39]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[40]  C. Judd,et al.  Statistical difficulties of detecting interactions and moderator effects. , 1993, Psychological bulletin.

[41]  Muin J. Khoury,et al.  Quantifying realistic sample size requirements for human genome epidemiology , 2008 .

[42]  F. Collins,et al.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits , 2009, Proceedings of the National Academy of Sciences.

[43]  A. Caspi,et al.  Influence of Life Stress on Depression: Moderation by a Polymorphism in the 5-HTT Gene , 2003, Science.

[44]  N E Day,et al.  Sample size determination for studies of gene-environment interaction. , 2001, International journal of epidemiology.