The Relationship Between Genetic Chronotype and PHQ-9 Score for Intern Physicians Modeled Through Two Different Polygenic Risk Scores

Abstract

This research was conducted as part of the Intern Health Study, which uses mobile health data, genetic data and survey data to analyze mental health outcomes in physicians undergoing training. This research seeks to determine whether there is a correlation between genetic chronotype and depression. Generally, the hypothesis is that those genetically predisposed to be "night owls" - wake up later and stay up later - will have higher PHQ-9 (Patient Health Questionnaire - 9) scores during the intern year, than those who are "early birds" - wake up earlier and go to sleep earlier. The genetic chronotype variable refers to a polygenic risk score calculation that measures the effect of various SNPs regarding who are more likely to be "early birds" or "night owls". These polygenic risk scores were calculated using two different methods. The first being from a survey of participants and the second using objective sleep midpoint calculations from mobile health technology. A Pearson's product moment correlation test between these two methodologies found a value of 0.857, with a 95% confidence interval of (0.8510461, 1.000000), indicating that there is a large positive correlation between the two polygenic risk scores. Depression was most directly calculated using mean PHQ-9 scores of their intern year of residency and sleep averages were calculated through wearables, almost exclusively FitBits and Apple Watches. One of the most consistent findings of the Sen Lab's Intern Health Study is that there is a positive relationship between lack of sleep and depression, and so a relationship between chronotype and the sleep averages made possible through mobile health technology could act as a proxy to depression. Data analysis conducted as of now, has shown through the survey based polygenic risk score of chronotype that those with a higher chronotype - genetic predisposition to wake up later and stay up later - have an elevated mean PHQ-9 score that has shown to be statistically significant as a result of a two sample t-test. Data was analyzed at the two extremes, where the average mean PHQ-9 score of the top 25% genetic chronotype (survey data PRS) was higher than the average mean PHQ-9 score of the bottom 25% genetic chronotype (survey data PRS) to a statistically significant degree. The next steps in data analysis are running a two sample t-test on chronotype extremes using the polygenic risk score based on objective sleep midpoint in comparison to the mean PHQ9 score. As well as looking at the relationship between sleep averages and genetic chronotype.