The neurobiological mechanisms of untreated pain and depression to relapse risk in substance dependence

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It is well known that alcohol use disorder (AUD) is highly co-morbid with both depression and chronic pain. Chronic pain and depression are particularly high and debilitating in the veteran population. The majority of research in AUD has been in samples of participants without co- occurring disorders since research typically excludes common co-morbidities from recruitment. Therefore, we would benefit enormously from studies where we include these co-morbidities, examine them, and build a neural signature (constellation of neuroimaging and clinical symptoms) of chronic pain and depression in AUD as a model to test with advanced machine learning algorithms. What is currently unknown is the neurobiological and neurochemical patterns that form a brain signature (the neural circuitry) of depression and of chronic pain within AUD. This study will use multi-modal neuroimaging data and behavioral symptomology measures to attain the overall objective of this proposal, which is to delineate the separate and overlapping contributions of co-morbid depression and chronic pain brain signatures on the neural signature of AUD. We will use advanced computational modeling algorithms (machine learning) of clinical and multi-modality neuroimaging data. Results from this proposal will provide a deeper understanding of AUD neurobiology and will identify a pattern of neural circuitry that signifies depression versus chronic pain in AUD neurobiology as the scientific basis for individualized precision medicine treatment approaches that target AUD co-morbidities of depression and chronic pain. My overarching career goal as an independent investigator is to build a multidisciplinary research program on neuroimaging of substance use disorders. I will achieve this by clarifying brain mechanisms contributing to co-occurring symptomology (depression, chronic pain) that often presents in substance use disorders and particularly high and debilitating in Veterans. A better understanding of to what extent behavior and co-morbid symptomatology relates to brain neurobiology could facilitate more accurate predictive modeling of individual treatment response and relapse using multi-modal imaging and advanced computational analyses methods. My short-term research goals for this career mentored proposal are to identify the separate and overlapping neural mechanisms of co-morbidities (depression and chronic pain) prevalent in alcohol use disorders, and relate these mechanisms to behavior and relapse risk in Veterans. These goals will be accomplished using state-of-the art multi-modal neuroimaging techniques (whole-brain magnetic resonance (MR) spectroscopic imaging, resting state functional MR imaging) which will be directly related to clinical/behavioral measures and self-report questionnaires of depression and pain, combined with the use of advanced computational analysis methods such as machine learning techniques of neuroimaging and clinical measures.