The DOI matches its Crossref record; 129 of the 129 references it cites were found in a registry or an index.
Research Review: Polygenic methods and their application to psychiatric traits
Abstract
Background: Despite evidence from twin and family studies for an important contribution of genetic factors to both childhood and adult onset psychiatric disorders, identifying robustly associated specific DNA variants has proved challenging. In the pregenomics era the genetic architecture (number, frequency and effect size of risk variants) of complex genetic disorders was unknown. Empirical evidence for the genetic architecture of psychiatric disorders is emerging from the genetic studies of the last 5 years. Methods and scope: We review the methods investigating the polygenic nature of complex disorders. We provide mini‐guides to genomic profile (or polygenic) risk scoring and to estimation of variance (or heritability) from common SNP s; a glossary of key terms is also provided. We review results of applications of the methods to psychiatric disorders and related traits and consider how these methods inform on missing heritability, hidden heritability and still‐missing heritability. Findings: Genome‐wide genotyping and sequencing studies are providing evidence that psychiatric disorders are truly polygenic, that is they have a genetic architecture of many genetic variants, including risk variants that are both common and rare in the population. Sample sizes published to date are mostly underpowered to detect effect sizes of the magnitude presented by nature, and these effect sizes may be constrained by the biological validity of the diagnostic constructs. Conclusions: Increasing the sample size for genome wide association studies of psychiatric disorders will lead to the identification of more associated genetic variants, as already found for schizophrenia. These loci provide the starting point of functional analyses that might eventually lead to new prevention and treatment options and to improved biological validity of diagnostic constructs. Polygenic analyses will contribute further to our understanding of complex genetic traits as sample sizes increase and as sample resources become richer in phenotypic descriptors, both in terms of clinical symptoms and of nongenetic risk factors.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Slamon, D. J., Clark, G. M., Wong, S. G., Levin, W. J., Ullrich, A., & McGuire, W. L. (1987) · Science · doi:10.1126/science.3798106 · Cited by 11,760
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Finding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279
Self-citationBiological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
Efficient Methods to Compute Genomic Predictions
VanRaden, P. M. (2008) · Journal of Dairy Science · doi:10.3168/jds.2007-0980 · Cited by 6,050
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease
The International IBD Genetics Consortium (IIBDGC), Jostins, L., Ripke, S., Weersma, R. K., Duerr, R. H., McGovern, D. P., Hui, K. Y., Lee, J. C., Philip Schumm, L., Sharma, Y., et al. (2012) · Nature · doi:10.1038/nature11582 · Cited by 4,722
Complement factor H polymorphism in age-related macular degeneration
Klein, R. J., Zeiss, C., Chew, E. Y., Tsai, J.-Y., Sackler, R. S., Haynes, C., Henning, A. K., SanGiovanni, J. P., Mane, S. M., Mayne, S. T., et al. (2005) · Science · doi:10.1126/science.1109557 · Cited by 4,492
Cited by
Clinical use of current polygenic risk scores may exacerbate health disparities
Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2019) · Nature Genetics · doi:10.1038/s41588-019-0379-x · Cited by 2,821
PRSice-2: Polygenic Risk Score software for biobank-scale data
Choi, S. W., & O'Reilly, P. F. (2019) · GigaScience · doi:10.1093/gigascience/giz082 · Cited by 1,532
Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations
Martin, A. R., Gignoux, C. R., Walters, R. K., Wojcik, G. L., Neale, B. M., Gravel, S., Daly, M. J., Bustamante, C. D., & Kenny, E. E. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.03.004 · Cited by 1,391
Integrative omics for health and disease
Karczewski, K. J., & Snyder, M. P. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2018.4 · Cited by 1,158
Attention deficit hyperactivity disorder
Thapar, A., & Cooper, M. (2016) · The Lancet · doi:10.1016/s0140-6736(15)00238-x · Cited by 1,043
Genetics and intelligence differences: five special findings
Plomin, R., & Deary, I. J. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.105 · Cited by 702
Hilker, R., Helenius, D., Fagerlund, B., Skytthe, A., Christensen, K., Werge, T. M., Nordentoft, M., & Glenthøj, B. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.08.017 · Cited by 615
Improved polygenic prediction by Bayesian multiple regression on summary statistics
Lloyd-Jones, L. R., Zeng, J., Sidorenko, J., Yengo, L., Moser, G., Kemper, K. E., Wang, H., Zheng, Z., Magi, R., Esko, T., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12653-0 · Cited by 528
Self-citationTop 10 Replicated Findings From Behavioral Genetics
Plomin, R., DeFries, J. C., Knopik, V. S., & Neiderhiser, J. M. (2016) · Perspectives on Psychological Science · doi:10.1177/1745691615617439 · Cited by 517
Tandem repeats mediating genetic plasticity in health and disease
Hannan, A. J. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2017.115 · Cited by 446
Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses
Wallace, C. (2020) · PLOS Genetics · doi:10.1371/journal.pgen.1008720 · Cited by 441
Psychiatric genetics and the structure of psychopathology
Smoller, J. W., Andreassen, O. A., Edenberg, H. J., Faraone, S. V., Glatt, S. J., & Kendler, K. S. (2019) · Molecular Psychiatry · doi:10.1038/s41380-017-0010-4 · Cited by 398
Early environmental influences on the development of children's brain structure and function
Miguel, P. M., Pereira, L. O., Silveira, P. P., & Meaney, M. J. (2019) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.14182 · Cited by 358
Etiology in psychiatry: embracing the reality of poly‐gene‐environmental causation of mental illness
Uher, R., & Zwicker, A. (2017) · World Psychiatry · doi:10.1002/wps.20436 · Cited by 331
Comparing Within- and Between-Family Polygenic Score Prediction
Selzam, S., Ritchie, S. J., Pingault, J.-B., Reynolds, C. A., O’Reilly, P. F., & Plomin, R. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.06.006 · Cited by 289
Agerbo, E., Sullivan, P. F., Vilhjálmsson, B. J., Pedersen, C. B., Mors, O., Børglum, A. D., Hougaard, D. M., Hollegaard, M. V., Meier, S., Mattheisen, M., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.0346 · Cited by 319
Self-citationA direct test of the diathesis-stress model for depression
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Colodro-Conde, L., Couvy-Duchesne, B., Zhu, G., Coventry, W. L., Byrne, E. M., Gordon, S., Wright, M. J., Montgomery, G. W., Madden, P. A. F., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.130 · Cited by 285
Self-citationPredicting Polygenic Risk of Psychiatric Disorders
Martin, A. R., Daly, M. J., Robinson, E. B., Hyman, S. E., & Neale, B. M. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.12.015 · Cited by 299
Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci
Smith, D. J., Escott-Price, V, Davies, G., Bailey, M. E. S., Colodro-Conde, L., Ward, J., Vedernikov, A., Marioni, R., Cullen, B., Lyall, D., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.49 · Cited by 259
Genome‐wide association study of schizophrenia in Ashkenazi Jews
Goes, F. S., McGrath, J., Avramopoulos, D., Wolyniec, P., Pirooznia, M., Ruczinski, I., Nestadt, G., Kenny, E. E., Vacic, V., Peters, I., et al. (2015) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32349 · Cited by 226
The genetic basis of major depression
Kendall, K. M., Van Assche, E., Andlauer, T. F. M., Choi, K. W., Luykx, J. J., Schulte, E. C., & Lu, Y. (2021) · Psychological Medicine · doi:10.1017/s0033291721000441 · Cited by 213
Hickie, I. B., Scott, E. M., Cross, S. P., Iorfino, F., Davenport, T. A., Guastella, A. J., Naismith, S. L., Carpenter, J. S., Rohleder, C., Crouse, J. J., et al. (2019) · Medical Journal of Australia · doi:10.5694/mja2.50383 · Cited by 208
Using genetics for social science
Harden, K. P., & Koellinger, P. D. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0862-5 · Cited by 180
Krapohl, E., & Plomin, R. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.2 · Cited by 160
Jami, E. S., Hammerschlag, A. R., Bartels, M., & Middeldorp, C. M. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01300-2 · Cited by 145
Self-citationCommon alleles contribute to schizophrenia in CNV carriers
Tansey, K. E., Rees, E., Linden, D. E., Ripke, S., Chambert, K. D., Moran, J. L., McCarroll, S. A., Holmans, P., Kirov, G., Walters, J., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.143 · Cited by 132
International 22q11.2 Brain and Behavior Consortium, Davies, R. W., Fiksinski, A. M., Breetvelt, E. J., Williams, N. M., Hooper, S. R., Monfeuga, T., Bassett, A. S., Owen, M. J., Gur, R. E., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1103-1 · Cited by 139
The Genetic Epidemiology of Treated Major Depression in Sweden
Kendler, K. S., Ohlsson, H., Lichtenstein, P., Sundquist, J., & Sundquist, K. (2018) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.17111251 · Cited by 132
Brikell, I., Larsson, H., Lu, Y., Pettersson, E., Chen, Q., Kuja-Halkola, R., Karlsson, R., Lahey, B. B., Lichtenstein, P., & Martin, J. (2020) · Molecular Psychiatry · doi:10.1038/s41380-018-0109-2 · Cited by 126
iPSYCH-SSI-Broad Autism Group, St Pourcain, B., Robinson, E. B., Anttila, V, Sullivan, B. B., Maller, J., Golding, J., Skuse, D., Ring, S., Evans, D. M., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2016.198 · Cited by 125
Heterogeneity in polygenic scores for common human traits
Ware, E. B., Schmitz, L. L., Faul, J., Gard, A., Mitchell, C., Smith, J. A., Zhao, W., Weir, D., & Kardia, S. L. (2017) · doi:10.1101/106062 · Cited by 123
Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences
Rosenberg, N. A., Edge, M. D., Pritchard, J. K., & Feldman, M. W. (2019) · Evolution, Medicine, and Public Health · doi:10.1093/emph/eoy036 · Cited by 105
Stergiakouli, E., Davey Smith, G., Martin, J., Skuse, D. H., Viechtbauer, W., Ring, S. M., Ronald, A., Evans, D. E., Fisher, S. E., Thapar, A., et al. (2017) · Molecular Autism · doi:10.1186/s13229-017-0131-2 · Cited by 97
Nigg, J. T., Gustafsson, H. C., Karalunas, S. L., Ryabinin, P., McWeeney, S. K., Faraone, S. V., Mooney, M. A., Fair, D. A., & Wilmot, B. (2018) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2017.12.013 · Cited by 93
Polygenic Risk Score for Schizophrenia and Treatment-Resistant Schizophrenia
Wimberley, T., Gasse, C., Meier, S. M., Agerbo, E., MacCabe, J. H., & Horsdal, H. T. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx007 · Cited by 89
Choi, K. W., Zheutlin, A. B., Karlson, R. A., Wang, M., Dunn, E. C., Stein, M. B., Karlson, E. W., & Smoller, J. W. (2020) · Depression and Anxiety · doi:10.1002/da.22967 · Cited by 68
“More recently, genome‐wide association studies (GWAS) have enabled researchers to capture genetic risk for complex disorders by deriving polygenic scores that combine the effects of many variants across the genome (Wray et al., 2014).”
BackgroundA genome-wide association study for extremely high intelligence
Zabaneh, D., Krapohl, E., Gaspar, H. A., Curtis, C., Lee, S. H., Patel, H., Newhouse, S., Wu, H. M., Simpson, M. A., Putallaz, M., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.121 · Cited by 71
Self-citationInvestigating the genetic architecture of general and specific psychopathology in adolescence
Jones, H. J., Heron, J., Hammerton, G., Stochl, J., Jones, P. B., Cannon, M., Smith, G. D., Holmans, P., Lewis, G., Linden, D. E. J., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0204-9 · Cited by 59
Incorporating epigenetic mechanisms to advance fetal programming theories
Conradt, E., Adkins, D. E., Crowell, S. E., Raby, K. L., Diamond, L. M., & Ellis, B. (2018) · Development and Psychopathology · doi:10.1017/s0954579418000469 · Cited by 60
Polygenic risk score and heritability estimates reveals a genetic relationship between ASD and OCD
Guo, W., Samuels, J. F., Wang, Y., Cao, H., Ritter, M., Nestadt, P. S., Krasnow, J., Greenberg, B. D., Fyer, A. J., McCracken, J. T., et al. (2017) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2017.03.011 · Cited by 59
Jansen, A. G., Dieleman, G. C., Jansen, P. R., Verhulst, F. C., Posthuma, D., & Polderman, T. J. C. (2020) · Behavior Genetics · doi:10.1007/s10519-019-09965-8 · Cited by 58
Pathway analysis in attention deficit hyperactivity disorder: An ensemble approach
Mooney, M. A., McWeeney, S. K., Faraone, S. V., Hinney, A., Hebebrand, J., IMAGE2 Consortium, German ADHD GWAS Group, Nigg, J. T., & Wilmot, B. (2016) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32446 · Cited by 48
Asthma and affective traits in adults: a genetically informative study
Lehto, K., Pedersen, N. L., Almqvist, C., Lu, Y., & Brew, B. K. (2019) · European Respiratory Journal · doi:10.1183/13993003.02142-2018 · Cited by 48
Current clinical use of polygenic scores will risk exacerbating health disparities
Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2018) · doi:10.1101/441261 · Cited by 2,813
Childhood Antisocial Behavior: A Neurodevelopmental Problem
van Goozen, S. H. M., Langley, K., & Hobson, C. W. (2022) · Annual Review of Psychology · doi:10.1146/annurev-psych-052621-045243 · Cited by 43
Choi, K. W., Chen, C.-Y., Ursano, R. J., Sun, X., Jain, S., Kessler, R. C., Koenen, K. C., Wang, M.-J., Wynn, G. H., Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, et al. (2020) · Psychological Medicine · doi:10.1017/s0033291719000527 · Cited by 33
Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data
Dueñas, H. R., Seah, C., Johnson, J. S., & Huckins, L. M. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa192 · Cited by 31
Moses, M., Tiego, J., Demontis, D., Bragi Walters, G., Stefansson, H., Stefansson, K., Børglum, A. D., Arnatkeviciute, A., & Bellgrove, M. A. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01775-5 · Cited by 31
Bell, C. J. M., Mehta, M., Mirza, L., Young, A. H., & Beck, K. (2025) · Psychopharmacology · doi:10.1007/s00213-024-06735-1 · Cited by 28
Recent quantitative genetic research on psychotic experiences: New approaches to old questions
Ronald, A. (2015) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2014.10.001 · Cited by 25
Continuity of Genetic Risk for Aggressive Behavior Across the Life-Course
van der Laan, C. M., Morosoli-García, J. J., van de Weijer, S. G. A., Colodro-Conde, L., the ACTION Consortium, Ip, H. F., van der Laan, C. M., Krapohl, E. M. L., Brikell, I., Sánchez-Mora, C., et al. (2021) · Behavior Genetics · doi:10.1007/s10519-021-10076-6 · Cited by 24
Self-citationGene set enrichment analysis to create polygenic scores: a developmental examination of aggression
Elam, K. K., Clifford, S., Shaw, D. S., Wilson, M. N., & Lemery-Chalfant, K. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0513-7 · Cited by 23
Van Assche, E., Moons, T., Cinar, O., Viechtbauer, W., Oldehinkel, A. J., Van Leeuwen, K., Verschueren, K., Colpin, H., Lambrechts, D., Van den Noortgate, W., et al. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12766 · Cited by 19
Barth, B., Portella, A. K., Dubé, L., Meaney, M. J., & Silveira, P. P. (2019) · Healthy Ageing and Longevity · doi:10.1007/978-3-030-24958-8_7 · Cited by 13
Metadata
- Authors
- Wray, N. R., Lee, S. H., Mehta, D., Vinkhuyzen, A. A. E., Dudbridge, F., & Middeldorp, C. M.
- Venue
- Journal of Child Psychology and Psychiatry
- Publisher
- Wiley
- Published
- 2014-08
- Volume
- 55
- Issue
- 10
- Pages
- 1068-1087
- ISSN
- 0021-9630 (ISSN-L)
- 1469-7610
- OpenAlex
- W2020663825
- Cited by
- 666
- References
- 129
- FWCI
- 28.93
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
