Computational Modeling of Human Hormone Homeostasis in Bone to Predict Sex-Specific Disease and Therapeutic Responses - Musculoskeletal (MSK) disorders like osteoporosis, fractures, and rare skeletal diseases are the second most common cause of morbidity and mortality in the USA and a leading cause of disability worldwide. Osteoporosis overwhelmingly affects people over the age of 50, with postmenopausal women accounting for over 93% of female deaths related to low bone mineral density. Fractures lead to major economic losses, particularly in under- resourced areas. In addition, complications from conditions of bone overgrowth, like heterotopic ossification (HO) after hip replacement or burn injuries, appear to be hormone-driven and show sex-specific clinical trajectories. Changes in hormone signaling during puberty, menstrual cycling, menopause, aging, and through therapeutic endocrine manipulation produce profound effects on skeletal health, yet the mechanisms linking hormone homeostasis to sex-specific disease outcomes, therapeutic efficacy, and treatment toxicity remain poorly understood. Current experimental models, such as those in mice, often fail to capture the specifics of human endocrine physiology and the complex interactions among hormones and other biological functions. There is a critical need for innovative computational approaches capable of modeling these dynamic processes in humans and predicting clinically meaningful responses to therapeutic interventions. This project proposes to develop the Hormonal and Endocrine Regulation of Osteogenesis (HERO) platform, a next- generation computational framework that integrates human clinical, multi-omic, microbiome, genetic, biomechanical, and experimental data with mechanistic biological knowledge to model hormone-regulated skeletal physiology and pathology. Our central hypothesis is that AI-enabled, multiscale models of hormone homeostasis can capture sex-specific and hormone-driven biological responses and accurately predict disease trajectories, therapeutic efficacy, and adverse skeletal outcomes across bone disease states. Because common diseases like osteoporosis can result from failure of bone-forming pathways, from increases in bone-resorbing pathways, or failures of the material properties of the bone, knowledge frameworks for bone formation (heterotopic ossification), bone loss (osteoporosis), and ECM properties will be developed and integrated. High-quality datasets from multiple resources will be incorporated, with the ultimate goal of creating the multidimensional integrated HERO (iHERO) computational model of osteogenesis that will allow us to model the complex, multifactorial, high-burden disease of osteoporosis. Successful completion of this project will generate a validated, extensible computational platform for modeling hormone homeostasis and predicting sex-specific therapeutic responses in human skeletal disease. All data and tools will be shared publicly, through abstracts, publications, workshops, outreach, and collaborations.
