PROJECT SUMMARY Over the past several decades, obesity has risen to epidemic proportions and now affects over 40% of older adults in America. While intentional weight loss is a highly effective treatment for severe obesity and its associated comorbidities, increasing evidence suggests it disrupts skeletal health and increases fracture risk. Protein supplementation may reduce osteoporotic fracture risk and be effective in minimizing bone loss associated with intentional weight loss among the aging population. An ongoing clinical trial at Wake Forest University is exploring whether higher protein intake during a 6-month weight loss intervention followed by a 12- month follow-up in obese older adults results in better 18-month bone health compared to recommended protein intake or higher protein intake during the 6-month weight loss intervention only. This proposal enhances the parent study assessment of bone health and fracture prediction by streamlining the collection of advanced 3D bone measures from quantitative computed tomography (CT) and bone strength measures from finite element (FE) modeling. Aim 1 will develop an automated imaging informatics platform to analyze baseline, 6-month, and 18-month participant CT scans to measure volumetric bone mineral density (vBMD) and cortical thickness in the hip. Aim 2 will use subject-specific FE modeling to assess longitudinal bone strength and predict fracture. Taken together, these methodologic advancements will improve our understanding of how protein supplementation affects bone quality. The findings of this analysis could also establish the plausibility of protein supplementation as a clinically relevant therapeutic for attenuating bone loss and mitigating fracture risk in older adults undergoing weight loss. This research will be conducted in the Center for Injury Biomechanics at the Wake Forest School of Medicine as an interdisciplinary collaboration between the Departments of Biomedical Engineering, Gerontology and Geriatric Medicine, Radiology, and Biostatistics and Data Science. This fellowship will also serve as a unique opportunity to train the predoctoral principal investigator in gerontology research, clinical trials design, biostatistics, bone metabolism biology, image-based informatics, and computational biomechanics. Ultimately, the project will refine the principal investigator's biomedical engineering skillset in image analysis and computational modeling to provide valuable experience applying engineering techniques to improve bone health in older adults.