PROJECT SUMMARY The prevalence of depression and pharmacologic treatments for depression are both approximately twice the prevalence of these in non-diabetic populations. However, case reports, animal studies, and epidemiologic studies have suggested an increased risk of hypoglycemia associated with antidepressant use. One potential mechanism explaining this association is possible drug-drug interactions (DDIs) between antidepressants and oral antidiabetic drugs (OADs). Certain selective serotonin reuptake inhibitors (SSRIs) inhibit the CYP2C9 enzyme, which is responsible for the metabolism of some diabetes medications. Only one epidemiologic study investigating this potential DDI has been published and reported imprecise results. There is a need for evidence generated by well-designed studies, particularly in U.S. populations to better understand the clinical implications of this potential DDI. The goal of the proposed research is to examine the potential effect of co- utilization of CYP2C9-metabolized OADs and CYP2C9-inhibiting antidepressants on the risk of serious hypoglycemia, using rigorous study design approaches and a database of Medicare claims linked with electronic health records (EHRs) for a population of patients 65 years or older who have interacted with the UNC healthcare system. In Aim 1, we will determine the prevalence of concomitant use of OADs and antidepressants that are either metabolized by or inhibit the CYP2C9 enzyme and evaluate prescribing trends over time and estimate the association between concomitant OAD and antidepressant use and hypoglycemia using an active comparator design. Among a population of OAD users, we will compare the risk of hypoglycemia between those who concomitantly receive CYP2C9 inhibiting antidepressants and those who receive antidepressants that are not thought to interact with CYP2C9. In Aim 2, we will validate an algorithm for identifying the outcome severe hypoglycemia using ICD-10-CM codes mapped from an existing ICD-9-CM based algorithm. Leveraging appropriate and reliable study-design approaches in combination with rich healthcare data can provide evidence on the potential link between OAD-antidepressant interactions and severe hypoglycemia. This question is especially important, given the need to balance adequate treatment of mental health with the immense burden of hypoglycemia. The results from this study will inform clinical care for diabetes patients and assist healthcare providers in optimizing treatment for prevalent comorbid mental health conditions. In the long-term, this work will be a part of the much-needed effort to generate reliable evidence for patients and providers managing chronic conditions with complex pharmacologic treatment strategies.