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Research Review: Polygenic methods and their application to psychiatric traits
Author(s) -
Wray Naomi R.,
Lee Sang Hong,
Mehta Divya,
Vinkhuyzen Anna A.E.,
Dudbridge Frank,
Middeldorp Christel M.
Publication year - 2014
Publication title -
journal of child psychology and psychiatry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.652
H-Index - 211
eISSN - 1469-7610
pISSN - 0021-9630
DOI - 10.1111/jcpp.12295
Subject(s) - heritability , genetic architecture , missing heritability problem , genome wide association study , genetic association , psychiatric genetics , endophenotype , population , schizophrenia (object oriented programming) , psychology , genetics , biology , psychiatry , quantitative trait locus , single nucleotide polymorphism , medicine , genotype , gene , cognition , environmental health
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.