Research Review: How to interpret associations between polygenic scores, environmental risks, and phenotypes / Jean-Baptiste PINGAULT in Journal of Child Psychology and Psychiatry, 63-10 (October 2022)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 63-10 (October 2022) . - p.1125-1139 Titre : Research Review: How to interpret associations between polygenic scores, environmental risks, and phenotypes Type de document : Texte imprimé et/ou numérique Auteurs : Jean-Baptiste PINGAULT, Auteur ; Andrea G. ALLEGRINI, Auteur ; Tracy ODIGIE, Auteur ; Leonard FRACH, Auteur ; Jessie R. BALDWIN, Auteur ; Frühling V. RIJSDIJK, Auteur ; Frank DUDBRIDGE, Auteur Année de publication : 2022 Article en page(s) : p.1125-1139 Langues : Anglais (eng) Mots-clés : Cohort Studies  Environmental Exposure/adverse effects  Genetic Predisposition to Disease  Genome-Wide Association Study  Humans  Midazolam  Multifactorial Inheritance  Phenotype  Polygenic scores  biases  environment  epidemiology  phenotypes Index. décimale : PER Périodiques Résumé : BACKGROUND: Genetic influences are ubiquitous as virtually all phenotypes and most exposures typically classified as environmental have been found to be heritable. A polygenic score summarises the associations between millions of genetic variants and an outcome in a single value for each individual. Ever lowering costs have enabled the genotyping of many samples relevant to child psychology and psychiatry research, including cohort studies, leading to the proliferation of polygenic score studies. It is tempting to assume that associations detected between polygenic scores and phenotypes in those studies only reflect genetic effects. However, such associations can reflect many pathways (e.g. via environmental mediation) and biases. METHODS: Here, we provide a comprehensive overview of the many reasons why associations between polygenic scores, environmental exposures, and phenotypes exist. We include formal representations of common analyses in polygenic score studies using structural equation modelling. We derive biases, provide illustrative empirical examples and, when possible, mention steps that can be taken to alleviate those biases. RESULTS: Structural equation models and derivations show the many complexities arising from jointly modelling polygenic scores with environmental exposures and phenotypes. Counter-intuitive examples include that: (a) associations between polygenic scores and phenotypes may exist even in the absence of direct genetic effects; (b) associations between child polygenic scores and environmental exposures can exist in the absence of evocative/active gene-environment correlations; and (c) adjusting an exposure-outcome association for a polygenic score can increase rather than decrease bias. CONCLUSIONS: Strikingly, using polygenic scores may, in some cases, lead to more bias than not using them. Appropriately conducting and interpreting polygenic score studies thus requires researchers in child psychology and psychiatry and beyond to be versed in both epidemiological and genetic methods or build on interdisciplinary collaborations. En ligne : http://dx.doi.org/10.1111/jcpp.13607 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=486 [article] Research Review: How to interpret associations between polygenic scores, environmental risks, and phenotypes [Texte imprimé et/ou numérique] / Jean-Baptiste PINGAULT, Auteur ; Andrea G. ALLEGRINI, Auteur ; Tracy ODIGIE, Auteur ; Leonard FRACH, Auteur ; Jessie R. BALDWIN, Auteur ; Frühling V. RIJSDIJK, Auteur ; Frank DUDBRIDGE, Auteur . - 2022 . - p.1125-1139. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 63-10 (October 2022) . - p.1125-1139 Mots-clés : Cohort Studies  Environmental Exposure/adverse effects  Genetic Predisposition to Disease  Genome-Wide Association Study  Humans  Midazolam  Multifactorial Inheritance  Phenotype  Polygenic scores  biases  environment  epidemiology  phenotypes Index. décimale : PER Périodiques Résumé : BACKGROUND: Genetic influences are ubiquitous as virtually all phenotypes and most exposures typically classified as environmental have been found to be heritable. A polygenic score summarises the associations between millions of genetic variants and an outcome in a single value for each individual. Ever lowering costs have enabled the genotyping of many samples relevant to child psychology and psychiatry research, including cohort studies, leading to the proliferation of polygenic score studies. It is tempting to assume that associations detected between polygenic scores and phenotypes in those studies only reflect genetic effects. However, such associations can reflect many pathways (e.g. via environmental mediation) and biases. METHODS: Here, we provide a comprehensive overview of the many reasons why associations between polygenic scores, environmental exposures, and phenotypes exist. We include formal representations of common analyses in polygenic score studies using structural equation modelling. We derive biases, provide illustrative empirical examples and, when possible, mention steps that can be taken to alleviate those biases. RESULTS: Structural equation models and derivations show the many complexities arising from jointly modelling polygenic scores with environmental exposures and phenotypes. Counter-intuitive examples include that: (a) associations between polygenic scores and phenotypes may exist even in the absence of direct genetic effects; (b) associations between child polygenic scores and environmental exposures can exist in the absence of evocative/active gene-environment correlations; and (c) adjusting an exposure-outcome association for a polygenic score can increase rather than decrease bias. CONCLUSIONS: Strikingly, using polygenic scores may, in some cases, lead to more bias than not using them. Appropriately conducting and interpreting polygenic score studies thus requires researchers in child psychology and psychiatry and beyond to be versed in both epidemiological and genetic methods or build on interdisciplinary collaborations. En ligne : http://dx.doi.org/10.1111/jcpp.13607 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=486

Research Review: Polygenic methods and their application to psychiatric traits / Naomi R. WRAY in Journal of Child Psychology and Psychiatry, 55-10 (October 2014)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 55-10 (October 2014) . - p.1068-1087 Titre : Research Review: Polygenic methods and their application to psychiatric traits Type de document : Texte imprimé et/ou numérique Auteurs : Naomi R. WRAY, Auteur ; Sang Hong LEE, Auteur ; Divya MEHTA, Auteur ; Anna A. E. VINKHUYZEN, Auteur ; Frank DUDBRIDGE, Auteur ; Christel M. MIDDELDORP, Auteur Article en page(s) : p.1068-1087 Langues : Anglais (eng) Mots-clés : Polygenic risk scoring  genome-wide association studies  psychiatric disorders  heritability  SNP analyses  disease traits Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1111/jcpp.12295 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=238 [article] Research Review: Polygenic methods and their application to psychiatric traits [Texte imprimé et/ou numérique] / Naomi R. WRAY, Auteur ; Sang Hong LEE, Auteur ; Divya MEHTA, Auteur ; Anna A. E. VINKHUYZEN, Auteur ; Frank DUDBRIDGE, Auteur ; Christel M. MIDDELDORP, Auteur . - p.1068-1087. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 55-10 (October 2014) . - p.1068-1087 Mots-clés : Polygenic risk scoring  genome-wide association studies  psychiatric disorders  heritability  SNP analyses  disease traits Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1111/jcpp.12295 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=238

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