Postpartum depression (PPD), a common complication of childbirth, has significant morbidity and mortality for mother and child, yet etiology is still poorly understood. PPD is a more heritable subtype of MDD, yet significant heterogeneity exists within the PPD phenotype, which may reflect differences in etiology. This study aims to disentangle the heterogeneity of PPD to understand etiology by leveraging existing data from two unique global resources, the Norwegian Mother and Child Cohort Study (MoBa) and the US arm of the Postpartum Depression: Action Towards Causes and Treatment Consortium. The study aims to 1) apply modern statistical learning methods in a master training set (N=63,528) and two independent testing sets (N=31,716 and N=4,978) to identify PPD subtypes, 2) identify genetic contributors to PPD subtypes and genetic overlap with other traits, and 3) examine the extent to which PPD subtypes predict longer-term mental health prognosis. This research will support my primary career goal to become an independently funded investigator with the expertise necessary to conduct integrated epidemiologic and genomic research to understand the complex etiology of PPD. My long-term research objective is to develop comprehensive risk prediction models that can ultimately be translated into effective preventive interventions and novel individualized treatments for PPD. I have expertise is in epidemiology and perinatal health, but I need additional mentored training to conduct large- scale, integrated gene-environment analyses to understand the biological basis of PPD. The specific objectives to meet my career goal are to 1) develop skills in data science to effectively analyze large, complex datasets, 2) establish an in-depth understanding of genomics and statistical genetics, and 3) understand the complex phenotypes of PPD and other related psychiatric conditions. The core mentorship team consists of Dr. Samantha Meltzer-Brody, lead mentor, an internationally recognized expert in perinatal mental health research, and Dr. Patrick Sullivan, co-lead mentor, a psychiatric geneticist who has built a collaborative network of depression research in Scandinavia. Dr. Yun Li, co-mentor, has extensive experience in developing statistical and computational methods for genomic and high-dimensional data. Dr. Ted Reichborn-Kjennerud, co-mentor, and Drs. Helga Ask and Alexandra Havdahl, collaborators, have extensive experience with assessment of psychiatric outcomes in the MoBa cohort. Dr. Cathryn Lewis, collaborator, is a leading expert in the development of genetic risk score methodology. Their combined mentorship will place me in an ideal position to succeed as an independent investigator. This work will inform further investigation of unique contributions of genes and environment to develop multifactorial predictive models for PPD, representing an important step towards personalized medicine in perinatal mental health. The vital skills I attain during this grant award will provide a foundation for future research evaluating interventions for prevention and personalized therapeutic treatments of PPD.
PPD is a common complication of childbirth with substantial morbidity, mortality, and personal and societal costs. Identifying subtypes of PPD (Aim 1), their genetic overlap with other psychiatric disorders and traits (Aim 2), and examining how they predict longer-term mental health prognosis (Aim 3) will make a significant contribution to understanding the biological underpinnings of PPD and determining potential points of intervention. Disentangling the heterogeneity of PPD and developing sophisticated risk prediction models that integrate genetic and epidemiologic risk factors could ultimately assist in early detection, differential diagnosis, and development of personalized intervention and treatment options for these devastating disorders.
