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 SNPs; 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.
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 SNPs; 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.
Authors: David T Liebers; Mehdi Pirooznia; Fayaz Seiffudin; Katherine L Musliner; Peter P Zandi; Fernando S Goes Journal: Schizophr Bull Date: 2016-02-12 Impact factor: 9.306
Authors: Sarah Hohmann; Nicoletta Adamo; Benjamin B Lahey; Stephen V Faraone; Tobias Banaschewski Journal: Eur Child Adolesc Psychiatry Date: 2015-04-08 Impact factor: 4.785
Authors: Sinan Guloksuz; Lotta-Katrin Pries; Philippe Delespaul; Gunter Kenis; Jurjen J Luykx; Bochao D Lin; Alexander L Richards; Berna Akdede; Tolga Binbay; Vesile Altınyazar; Berna Yalınçetin; Güvem Gümüş-Akay; Burçin Cihan; Haldun Soygür; Halis Ulaş; EylemŞahin Cankurtaran; Semra Ulusoy Kaymak; Marina M Mihaljevic; Sanja Andric Petrovic; Tijana Mirjanic; Miguel Bernardo; Bibiana Cabrera; Julio Bobes; Pilar A Saiz; María Paz García-Portilla; Julio Sanjuan; Eduardo J Aguilar; José Luis Santos; Estela Jiménez-López; Manuel Arrojo; Angel Carracedo; Gonzalo López; Javier González-Peñas; Mara Parellada; Nadja P Maric; Cem Atbaşog Lu; Alp Ucok; Köksal Alptekin; Meram Can Saka; Celso Arango; Michael O'Donovan; Bart P F Rutten; Jim van Os Journal: World Psychiatry Date: 2019-06 Impact factor: 49.548