A Precision Medicine Approach for Sub-Classification of Mood Disorders and Prediction of Treatment Outcomes

The Mood Disorders Precision Medicine Consortium (MDPMC) is an integrated team of academic researchers dedicated to improving the lives of patients who suffer from major depressive disorder and bipolar disorder. Comprised of leading experts in the fields of genetics, metabolomics, neuroimaging, bioinformatics, and clinical trials, the MDPMC’s mission is to achieve the precision medicine goals of individualizing treatment for mood disorder patients based on an integrated biological understanding of their illnesses and variation in response to treatments.

The MDPMC originated from a decade of collaboration between Rima Kaddurah-Daouk, PhD, of Duke University and Richard Weinshilboum, MD, of the Mayo Clinic, who laid the groundwork for using large data (metabolomics and genomics) to better sub-classify patients with major depression and to define signatures that can inform about treatment outcomes.  Subsequently, the mood disorders precision medicine team from Emory University, with expertise in neuroimaging, inflammation, and genetics, engaged as a third MDPMC partner.  Beyond this core, the MDPMC has ongoing collaborations with experts in the epigenetics of environmental exposure from Helmholtz Zentrum of Munich, Germany, the metabolomics center of University of California, Davis, and with John Rush, MD, a highly experienced clinician-researcher in mood disorders. Together, the work of this consortium applies expertise across the crucial areas of prediction medicine for mood disorders.

The MDPMC is supported by private and public funding.  Rima Kaddurah-Daouk, PhD, and Boadie Dunlop, MD (Emory) are co-PIs on an NIH R01 that aims to define and replicate across two large datasets the metabolic signatures of exposure and outcomes to treatment with escitalopram, duloxetine, and cognitive behavioral therapy among depressed patients. This project builds off the 800-patient Mayo Pharmacogenomics Research Network (PGRN) sample examining the metabolomic and genetic predictors of response to pharmacotherapy, and the 344-subject Emory Prediction of Remission to Individual and Combined Treatments (PReDICT) study of treatment-naïve patients with depression. A second NIH R01 funds Dr. Weinshilboum’s cutting-edge “pharmacometabolomics-informed pharmacogenomics” approach to identifying relevant metabolic pathways and their genetic variation. This work has already identified several metabolites and genes implicated in response to escitalopram, followed by functional validation, demonstrating how joining multiple “omics” creates novel insight into mechanisms of variation of response to treatment with antidepressants.  Finally, the MDPMC is the beneficiary of funding from the Dr. Ranga Krishnan Duke Fund, supporting the development of data-mining bioinformatics analyses of electronic medical records of depressed patients across the Mayo Clinic and Mindlinc, an organization with access to electronic health records on hundreds of thousands of patients with psychiatric diseases.

With the state of its funding, expertise, and organization, the MDPMC is poised to make substantial gains in our understanding of the molecular variation underlying the heterogeneity of mood disorders, and the pharmacogenetic and pharmacometabolomic basis for variation in treatment response. Moving forward, the MDPMC will apply these results to analyses of the gut microbiome and the fMRI and PET neuroimaging data from Helen Mayberg’s studies at Emory. Our vision of creating a richly integrated understanding of the sources of biological variation in mood disorders is the driving force behind the MDPMC, thereby enabling us to develop clinically actionable individualized treatment approaches for patients suffering from these conditions.