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Exploring polygenic-environment and residual-environment interactions for depressive symptoms within the UK Biobank.
Gillett, Alexandra C; Jermy, Bradley S; Lee, Sang Hong; Pain, Oliver; Howard, David M; Hagenaars, Saskia P; Hanscombe, Ken B; Coleman, Jonathan R I; Lewis, Cathryn M.
Afiliación
  • Gillett AC; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Jermy BS; NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK.
  • Lee SH; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Pain O; NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK.
  • Howard DM; Australian Centre for Precision Health, University of South Australia, SA, Adelaide, Australia.
  • Hagenaars SP; UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.
  • Hanscombe KB; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Coleman JRI; NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK.
  • Lewis CM; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Genet Epidemiol ; 46(5-6): 219-233, 2022 07.
Article en En | MEDLINE | ID: mdl-35438196
Substantial advances have been made in identifying genetic contributions to depression, but little is known about how the effect of genes can be modulated by the environment, creating a gene-environment interaction. Using multivariate reaction norm models (MRNMs) within the UK Biobank (N = 61294-91644), we investigate whether the polygenic and residual variance components of depressive symptoms are modulated by 17 a priori selected covariate traits-12 environmental variables and 5 biomarkers. MRNMs, a mixed-effects modelling approach, provide unbiased polygenic-covariate interaction estimates for a quantitative trait by controlling for outcome-covariate correlations and residual-covariate interactions. A continuous depressive symptom variable was the outcome in 17 MRNMs-one for each covariate trait. Each MRNM had a fixed-effects model (fixed effects included the covariate trait, demographic variables, and principal components) and a random effects model (where polygenic-covariate and residual-covariate interactions are modelled). Of the 17 selected covariates, 11 significantly modulate deviations in depressive symptoms through the modelled interactions, but no single interaction explains a large proportion of phenotypic variation. Results are dominated by residual-covariate interactions, suggesting that covariate traits (including neuroticism, childhood trauma, and BMI) typically interact with unmodelled variables, rather than a genome-wide polygenic component, to influence depressive symptoms. Only average sleep duration has a polygenic-covariate interaction explaining a demonstrably nonzero proportion of the variability in depressive symptoms. This effect is small, accounting for only 1.22% (95% confidence interval: [0.54, 1.89]) of variation. The presence of an interaction highlights a specific focus for intervention, but the negative results here indicate a limited contribution from polygenic-environment interactions.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Depresión / Interacción Gen-Ambiente Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Genet Epidemiol Asunto de la revista: EPIDEMIOLOGIA / GENETICA MEDICA Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Depresión / Interacción Gen-Ambiente Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Genet Epidemiol Asunto de la revista: EPIDEMIOLOGIA / GENETICA MEDICA Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos