PSYCHOSOCIAL AND GENOMIC DRIVERS OF MENTAL WELL-BEING IN UNIVERSITY STUDENTS: NOVEL FINDINGS FROM A WORLD-FIRST LONGITUDINAL STUDY

Abstract Background Exposure to stressors during the university years contribute to the increasing rates of psychiatric disorders among university students. Genome-wide association studies have identified genes significantly associated with depression, anxiety, and subjective well-being. Psychosocial factors such as university belonging and receiving social support are protective of university students’ mental health. In contrast, microstressors such as daily hassles are psychosocial factors that contribute to the development of psychopathological symptoms. No study to date has investigated trajectories of mental health and well-being and how these change across time in response to different risk and protective factors. Aims & Objectives This world-first and unique longitudinal study investigated the association between psychosocial risk and protective factors and mental health and well-being from a genomics perspective. Method Psychological, health surveys and saliva samples were collected from over 150 first year university students at an Australian University at 3 time-points. Genotyping was performed using the Illumina GSA array (>600k SNPs) and DNA methylation was performed using the Illumina EPICv2 array (>900K probes). Association analysis was performed via generalised linear regressions and mixed effects models in R to evaluate the association between the psychosocial factors (university belonging, receiving social support and daily hassles) and DNA methylation levels with mental health well-being. Genome-wide gene- by-environment interaction study (GWGEIS) was performed using PLINK 1.9, multiple testing corrections was performed using Bonferroni. Pathway analysis was done using the KEGG and gProfiler functional databases. Results Psychosocial factors university belonging and social support were positively associated with mental being and negatively associated with psychiatric symptoms of depression, anxiety and stress (p <0.05). The GWGEIS identified 36 SNPs that interacted with university belonging including SNPs in PLCB1 (associated with long-term depression) to predict mental well-being (p <5e-8). Interestingly, daily hassles interacted with multiple SNPs in LINC01445 and HSD17B3 to predict depressive and anxiety symptoms. Analyses of the longitudinal DNA methylation changes and novel gene findings will also be presented. Replication of results in an independent cohort are underway. Discussion & Conclusions These findings identify biological correlates and psychosocial factors that may contribute to the development of psychiatric symptoms. The genome-wide gene-by-environment interaction study identified novel candidate genes interacting with protective psychosocial factors such as university belonging and social support, as well as microstressors such as daily hassles. The genes mapped to plausible biological pathway such as cell adhesion molecule binding providing novel insight into the understanding of the biological mechanism of psychiatric disorders.