Polygenic Interactions With Environmental Adversity In The Aetiology Of Major Depressive Disorder

Mullins, N.; Power, R. A.; Fisher, H. L.; Hanscombe, K. B.; Euesden, J.; Iniesta, R.; Levinson, D F; Weissman, Myrna M.; Potash, J B; Shi, J; Uher, R.; Cohen-Woods, S.; Rivera, M; Jones, L.; Jones, I.; Craddock, N; Owen, M J; Korszun, A.; Craig, I. W.; Farmer, A. E.; McGuffin, P; Breen, G; Lewis, C M

Background. Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene–environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD. Method. The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them. Results. PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10−6). SLEs and CT were also associated with MDD status (p = 2.19 × 10−4 and p = 5.12 × 10−20, respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples. Conclusions. CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene–environment interactions in complex traits.


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February 1, 2022