Musculoskeletal (MSK) injuries and diseases are the leading cause of disability across the lifespan. The pathophysiology of MSK disease is complex, and clinical research requires a broad range of data types including electronic health record (EHR) data (patient characteristics, treatments, and clinical outcomes), standardized physical performance measures, bone imaging, laboratory measures, omics data (e.g. genomics, proteomics, metabolomics), patient reported outcome tools, and social determinants of health. A lack of integration of these complex ‘big data’ sources impedes access and utilization by investigators. The goal of the Indiana Center for Musculoskeletal Health-Clinical Research Center is to provide access to state-of-the-art informatics resources and technology to define and characterize MSK biology and disease genotypes; computable, molecular, functional, and clinical phenotypes; and the social factors, collectively mediating MSK health, disease and disability across the lifespan, and to develop cures. In our initial P30 funding period, we established a Musculoskeletal Informatics Methodology (MIM) Core, leveraging a large inter-organizational integrated health information exchange of EHR data to detect several computable (assessed from the EHR) MSK phenotypes, that incorporate diagnosis and other codes, medications, laboratory values and/or clinical text notes. We integrated such computable phenotypes with the measurements (physical performance and bone assessments) and associated biospecimens from the ICMH-CRC FIT Core, to support investigators in clinical study design, feasibility assessments, and translating bench discoveries to humans. In the current proposal, the MIM Core will expand our support of investigators in multi-disciplinary clinical and translational research leveraging the use of novel informatics methods and resources, to improve musculoskeletal health. The MIM Core will develop a large facile, secure Musculoskeletal Data Mart that integrates and makes ready for clinical research, data from multiple resources including: 1) EHR systems of the Indiana Network for Patient Care, using computable phenotypes to generate a cohort of more than 880,000 patients with MSK disorders, 2) community data systems information on social determinants of health and other risk factors, and 3) the full data from the FIT Core musculoskeletal phenotyping, biospecimens, and genomic data. This Data Mart will facilitate feasibility analyses, grant support, and retrospective and prospective studies to support translational research from bench to bedside and back. The MIM Core will also provide statistical support for clinical trial design, and informatics and data science approaches such as applying natural language processing to extract EHR text data, health informatics analyses of outcomes, integrative genomic analyses, and applying machine learning models to predict clinical outcomes. These new and innovative initiatives will link the resear...