Evaluating the effects of depression genetics and treatment on clinical laboratory values

Abstract

Depression is a common psychiatric disorder characterized by decreased mood, anhedonia, irritability, or suicidal thoughts. In the clinic, laboratory testing provides physicians with targeted biochemical measurements, biomarkers, to aid in diagnosing and treating patients with a variety of diseases. In this thesis, we utilize biomarkers stored in electronic health records (EHRs) to create a lab-wide association method to scan for associations with genetics of depression. Additionally, we use medication information from EHRs to investigate associations between antidepressant treatment and biomarkers. We find an robust association between depression genetics and increased white blood cell count (WBC), an immune biomarker. The association between depression genetics and WBC count remained after controlling for various comorbid phenotypes and replicated in several independent biobanks in the PsycheMERGE Network. In longitudinal models, antidepressant use associated with decreases in WBC count. The anti-inflammatory effect persisted up to a year after antidepressant initiation and was detected across four common antidepressant classes. These results implicate depression genetics as a partial driver of a pro-inflammatory state in depression and confirms an anti-inflammatory effect of antidepressants.