Abstract

Predicting Resilience and Susceptibility to Stress in a College Freshman Sample: Validating the Affect Score

Khalil H, Murphy-Weinberg V, Lopez JF, Watson SJ, Akil H
53rd Annual Meeting of the Society for Neuroscience. 2024.

We used a longitudinal approach to understand the various factors shaping resilience and vulnerability to stress, as indexed by the development of anxiety or depression symptoms in a sample of University of Michigan freshmen. At the start of their freshman year, subjects were genotyped and a polygenic risk score for depression (MDD-PRS) was calculated. At baseline we gathered information regarding their family history as well multiple psychological variables using survey instruments. Subjects were then sampled at multiple timepoints during their freshman year on clinical rating scales, including PHQ-9 for depression and GAD-7 for anxiety. Daily sleep levels and physical activity were collected as well. We found that while the MDD-PRS was useful in significantly predicting follow-up depression scores prior to the COVID-19 pandemic, its usefulness faded in the two cohorts (starting in Fall 2019 and Fall 2020) sampled during the pandemic. In particular, depression scores in female subjects with lower genetic risk increased the most dramatically during this pandemic period. We also used machine learning to determine which of the psychological instruments collected at baseline were best at predicting follow-up depression scores. These instruments, which included family history, state and trait variables, were then combined into a single index which we have termed the “Affect Score”. This index proved highly predictive of follow-up depression scores. Here, we present data validating the Affect Score in two new cohorts (starting in Fall 2021 and Fall 2022). While the MDD-PRS is still not significantly predictive of follow-up depression scores in these new cohorts, the Affect Score continues to be highly predictive, independent of sex.