Genetic propensity to mental health traits and their associations with social connection phenotypes: evidence from the English Longitudinal Study of Ageing

Abstract There is a wealth of phenotypic literature on the interplay between mental health and social connections. However, how genetic propensity to mental health traits may be associated with distinct social connections phenotypes (i.e., structural, functional and quality aspects) is largely unexplored. Using polygenic scores (PGSs), we explored the associations between genetic propensity for five mental health traits (PGSdepressive-symptoms, PGSanxiety, PGSbipolar- disorder, PGSschizophrenia, PGSwellbeing) and four social connection phenotypes (social isolation, loneliness, social support and relationship strain). Linear regressions were conducted in a representative sample of unrelated older adults living in the UK, and analyses were controlled for age, sex, and principal components to account for population stratification. The results show that higher PGSdepressive-symptoms was associated with greater loneliness (B=0.11, CI-95%=0.07, 0.15) and relationship strain (B=0.09, CI-95%=0.05, 0.13) and lower social support (B=-0.07, CI-95%=-0.13, -0.01). Higher PGSanxiety was associated with higher social isolation (B=0.05, CI-95%=0.00, 0.10) and greater relationship strain (B=0.05, CI-95%=0.01, 0.09). Higher PGSbipolar-disorder was associated with greater loneliness (B=0.05, CI-95%=0.01, 0.09) and relationship strain (B=0.06, CI-95%=0.02, 0.10). Higher PGSwellbeing was associated with lower loneliness (B=-0.07, CI-95%=-0.11, -0.03), relationship strain (B=- 0.07, CI-95%=-0.11, -0.03), and social isolation (B=-0.07, CI-95%=-0.12, -0.02), and greater social support (B=0.14, CI-95%=0.08, 0.21). This suggests differential associations between different mental health PGSs and distinct aspects of social connections, indicating a nuanced picture. Our findings confirm that genetics play a role in having adequate social connections, which can be supported through social, community, and cultural schemes. They also highlight that genetic confounding is important when using observational data assessing the associations between mental health and social connections. Competing Interest Statement The authors have declared no competing interest. Funding Statement This work is supported by UK Research and Innovation [MR/Y01068X/1], and this work was developed from SFs PhD work, which was supported by the ESRC-BBSRC Soc-B Centre for Doctoral Training (ES/P000347/1). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The data are freely available through the UK data services and can be accessed here: https://discover.ukdataservice.ac.uk I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability The data are freely available through the UK data services and can be accessed here: https://discover.ukdataservice.ac.uk