Genetic influences on treatment-seeking for common mental health problems in the UK biobank. (October 2019) - Rayner, Christopher; Coleman, Jonathan R.I.; Purves, Kirstin L.; Cheesman, Rosa; Hübel, Christopher; Gaspar, Helena; Glanville, Kylie; Krebs, Georgina; Morneau-Vaillancourt, Genevieve; Breen, Gerome; Eley, Thalia C.
Abstract: The majority of those who experience clinical anxiety and/or depressive symptoms in the population do not receive treatment. Studies investigating inequalities in treatment outcomes rarely consider that individuals respond differently to their experience of the environment. Much of our environment is under genetic influence, via our behaviour, whereby individuals actively select their experiences. If genes influence who seeks and receives treatment, selection bias will confound genomic studies of treatment response. Furthermore, if some individuals are at high genetic risk of needing but not commencing treatment, then greater efforts could be made to engage them. The role of common genetic variation on four lifetime treatment-seeking behaviours ( treatment-seeking, treatment-receipt, self-help, self-medication with alcohol/drugs ) was examined in participants of the UK Biobank (sample size range: 48, 106 - 75, 322). Treatment-related behaviours were only modestly heritable in these data. Nonetheless, genetic correlations reveal substantial genetic overlap between lifetime treatment-related behaviours and psychiatric disorders, symptoms and behavioural traits. To our knowledge, this is the first study to examine genetic influences on treatment-related behaviours. Further work is required to determine whether genetic factors could be used alongside clinical, social and demographic factors to identify at risk groups and inform strategies which target early intervention. Highlights: Many individuals with anxiety and depression who need treatment, do not receive treatment. Personalised medicine is needed to improve treatment access and retention, as well as response. Such approaches may benefit from integration of genetic information, alongside social and clinical data. We detect genetic overlap between treatment-seeking behaviours and traits of interest, which provides some preliminary insights into treatment-related behaviours and suggests polygenic scores may add predictive value in the future.