Polygenic Risk for Depression is Associated with the Severity and Rate of Change in Depressive Symptoms Across Adolescence

Abstract

AbstractAdolescence marks a period where depression will commonly onset and previous research using twin studies has suggested that genetic influences play a role in how depression develops and changes across adolescence. Recent genome-wide association studies have also shown that common genetic variants – which can be combined into a polygenic risk score (PRS) – are also implicated in depression. However, the role of PRS in adolescent depression and changes in adolescent depression is not yet understood. We aimed to examine the association between a PRS for depressive symptoms and depressive symptoms across adolescence and young adulthood, and how polygenic risk is associated with changes in depressive symptoms using two methods: cross-sectional analysis and multilevel growth curve modelling to examine the rate of change over time. Using data from over 6000 participants of the Avon Longitudinal Study of Parents and Children (ALSPAC) we examined associations between genetic liability to depressive symptoms (PRS for depressive symptoms) and self-reported depressive symptoms (short mood and feelings questionnaire over 9 occasions from 10-24 years). We examined cross-sectional associations at each age and longitudinal trajectories of depressive symptoms in a repeated measures framework using growth curve analysis. The PRS was associated with depressive symptoms throughout adolescence and young adulthood in cross-sectional and growth curve analyses, though associations were stronger in the latter analyses. Growth curve analyses also provided additional insights, demonstrating that individuals with a higher PRS had steeper trajectories of depressive symptoms across adolescence with a greater increasing rate of change. These results show that common genetics variants as indexed by a PRS for depressive symptoms influence both the severity and rate of change in adolescent depressive symptoms. Longitudinal data that make use of repeated measures designs have the potential to provide greater insights into the factors that influence the onset and persistence of adolescent depression.