Polysubstance Addiction Research Center - ABSTRACT OVERALL Substance use disorders (SUDs) remain a major public health crisis, driven increasingly by polysubstance use. Despite decades of research, we still lack an integrated framework that explains how genetic, cellular, and physiological vulnerabilities converge to promote compulsive drug use, abstinence, and relapse. Most studies isolate single drugs, narrow behavioral phenotypes, or individual biological levels, producing fragmented results that limit predictive power and therapeutic development. The Polysubstance Addiction Research Center (PARC) directly addresses this gap by uniting behavioral, molecular, circuit, and immunometabolic data within the same genetically diverse Heterogeneous Stock (HS) rats and aligning these findings with human omics and imaging datasets with three Research Pojects: Brain Connectomic, Brain Transcriptomic, and Gut-Vagus Multiomic. This design enables systematic comparisons across drugs (cocaine, oxycodone, alcohol, and their co-use), across species (HS rats versus human SUD/AUD cohorts and healthy controls), and across the severity spectrum of addiction-like behaviors. All data converge in the One-Individual Multiscale Atlas, a center-wide mandate that harmonizes multimodal datasets into a reusable translational resource. Specific Aim 1 will identify multilevel biomarkers of addiction-like behaviors by quantifying behavioral, neural, molecular, and immunometabolic signatures across sex, drugs, and severity of addiction-like behaviors. Advanced AI/ML approaches will integrate these data into interpretable profiles of vulnerability and resilience, spanning genes to behavior. Specific Aim 2 will reveal and validate druggable targets. Candidate targets, including oxidative phosphorylation stress pathways, cholinergic and immune signaling pathways, will be tested using pharmacological and viral approaches and translationally-relevant models of relapse. Specific Aim 3 will accelerate discovery by deploying an integrated Center platform. This includes expanding the Addiction Biobank, creating cloud-based pipelines for data sharing and analysis, providing pilot funding for innovative projects, and training the next generation of scientists in multiscale addiction research. All projects share harmonized longitudinal cohorts, experimental designs, and time points, ensuring cross-validation and immediate bidirectional feedback. Integration is further supported by four Cores: Behavioral Phenotyping, Biobank, Computational & Analytical, and Pilot Projects. Expected outcomes include a validated biomarker panel for diagnosis and stratification, experimentally confirmed therapeutic targets, publicly available datasets and biospecimens, and a trained workforce fluent in integrative addiction science. Together, PARC will transform addiction research from siloed observations into a predictive, mechanistic, and translational enterprise.
