2021
DOI: 10.1101/2021.08.02.21261499
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Exploring polygenic-environment and residual-environment interactions for depressive symptoms within the UK Biobank

Abstract: 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 variation of depressive symptoms are modulated by 25 a-priori selected covariate traits: 12 environmental variables, 5 biomarkers and polygenic risk scores for 8 … Show more

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“…Moreover, research utilising polygenic scores (PGSs); genetic measures that can be calculated for each individual by identifying, weighting, and summing genotyped risk variants found to be associated with depression 23, 24 , have yielded inconsistent findings. Whilst some studies have highlighted sex differences and found significant interaction effects associated with MDD outcomes 18, 25-27 , some replication attempts reported null findings 28, 29 and follow up meta-analyses have suggested that reported findings were likely to be false positives. 30 An explanation for the inconsistent findings may lie in the predictive accuracy and validity of PGSs.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, research utilising polygenic scores (PGSs); genetic measures that can be calculated for each individual by identifying, weighting, and summing genotyped risk variants found to be associated with depression 23, 24 , have yielded inconsistent findings. Whilst some studies have highlighted sex differences and found significant interaction effects associated with MDD outcomes 18, 25-27 , some replication attempts reported null findings 28, 29 and follow up meta-analyses have suggested that reported findings were likely to be false positives. 30 An explanation for the inconsistent findings may lie in the predictive accuracy and validity of PGSs.…”
Section: Introductionmentioning
confidence: 99%