Polygenic Index for Depressive Symptoms and Stress Response : An exploration of genetic influence on the diathesis-stress model

Sammanfattning

Major depressive disorder (MDD) is one of the most prevalent and debilitating psychiatric conditions in the world, but little is still known about its aetiology and what causes some individuals to develop it while others do not. Large genome wide association studies (GWAS) have established a multitude of gene variations that are associated with depressive symptoms, which provide us with a polygenic risk index (PGI) which has the ability to predict the risk of an individual developing MDD. PGI however does still not itself offer any explanation of why an individual develops MDD, but could aid the research in the matter, which is what this study aims to do. The theoretical framing of the present study is the diathesis-stress model which suggests that some people are more genetically susceptible to stress which increases the risk of developing psychiatric conditions like depression. We investigated this by recruiting non-clinical individuals from the Swedish Twin Registry and then exposing them (n = 200) to the Trier Social Stress Test (TSST) to examine if PGI scores modulated the stress response through measures of heart rate (HR), heart rate variability (HRV), cortisol levels and self-reported anxiety. Overall, the findings provided little evidence for the hypothesis that individuals with higher PGI levels would be more susceptible to stress. We did however observe a statistically significant association between PGI and the mean heart rate during the arithmetic phase of the TSST, which indicated that PGI predicted a more blunted HR stress response for individuals with higher PGI scores. These findings may suggest that the relationship between genetic susceptibility and acute psychophysiological stress responses are more complex than a diathesis-stress model would predict, at least when diathesis is defined by a PGI for depressive symptoms, and that larger samples or analyses of downstream biological processes might be needed to detect these effects.