Precision Functional Mapping in Treatment-Resistant Depression

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Treatment-resistant depression (TRD), defined as repeated failure to respond to treatment, is the most virulent form of major depressive disorder (MDD), and claims a disproportionate fraction of morbidity and mortality. The overwhelming costs of depression have motivated a decades-long search for meaningful biomarkers. However, despite substantial effort, and the promise of functional brain imaging as a non-invasive tool for whole-brain measurements, the identification of biomarkers of depression for ready clinical use has remained elusive. The major impediments to progress include substantial phenotypic heterogeneity in typical MDD cohorts and unreliable and imprecise imaging measures. During his graduate and residency years, the principal investigator of this proposal developed novel methods for precise functional neuroimaging, known as `precision functional mapping' (PFM), which have been previously applied to study brain organization in healthy individuals. The present K99/R00 Pathway to Independence award proposal is designed to apply these new methods to address these previous limitations and identify trait and state biomarkers of pathology in TRD. In order to achieve these goals, a comprehensive career development agenda has been structured to train the PI in the evaluation and management of this severely ill population. The PI will also learn how to implement ecologically valid tools for precise behavioral and psychiatric assessments. These training aims will be pursued with the guidance and mentorship of Drs. Charles Conway, Deanna Barch, Eric Lenze, Nico Dosenbach, and Abraham Snyder, world experts in psychiatric assessment, dimensions of psychopathology, human subjects study design, ecological momentary assessment (EMA), cognitive neuroscience, and functional neuroimaging methods. During the training K phase, the PI will acquire a proof-of-principle dataset of extended and repeated resting fMRI data on well-characterized TRD patients, treatment-responsive MDD patients, and healthy controls, in order to optimize the quantitative reproducibility of single-subject functional network maps derived from resting state functional connectivity (RSFC; Aim 1). In the R00 phase of the award, a large cohort (n=90) of TRD, treatment-responsive MDD and healthy controls will be evaluated to identify brain imaging trait biomarkers of treatment-resistant depression (Aim 2). To separate state from trait biomarkers, dense time courses of imaging data, as well as EMA, will be acquired on TRD patients while they undergo electroconvulsive therapy (ECT) treatment (Aim 3). Together, these studies are likely to reveal underlying network features of disease and will determine whether RSFC can be reliably used as a biomarker for TRD. The tools and approach laid out in this proposal will naturally extend to evaluations of other treatment modalities and neuropsychiatric disorders. With the skills and expertise gained through this training and research program, the PI will be well-positioned to pursue an independent career as a physician scientist.