Ravi Prakash

My research career began in the field of infectious disease genetics, with a focus on the genetic epidemiology of Mycobacterium tuberculosis (MTB). During my doctoral training, I studied strain diversity and genetic variations in drug resistance–associated target genes. As a postdoctoral fellow at Fudan University in Shanghai, I investigated compensatory mutations contributing to the transmission of multi-drug resistant tuberculosis (MDR-TB) and explored cell-free small RNAs as potential diagnostic biomarkers.
In 2022, I transitioned to musculoskeletal genetics as a Senior Research Scientist on the CuffGEN Study at UT Southwestern Medical Center, where I focused on identifying genetic risk factors for rotator cuff tears. In 2024, I joined the University of Michigan as a Research Assistant Professor in the Department of Physical Medicine and Rehabilitation.
My current research centers on the genetics and genomics of musculoskeletal disorders, particularly rotator cuff tears and glenohumeral osteoarthritis. I use genome-wide association studies (GWASs) and single-cell transcriptomic approaches to investigate the cellular and molecular mechanisms underlying these conditions. I am also an active member of the Michigan Integrative Musculoskeletal Health Core Center (MiMHC).

My research interests encompass to study the genetics and genomics of Glenohumeral Osteoarthritis (GH OA).
GH OA is characterized by degeneration in cartilage represents a crucial area of investigation. Understanding the contribution of potential genes to the pathophysiology of disease is essential. Furthermore, I am keen to investigate the tissue-specific gene expression profiles associated with GH OA, as this could provide valuable insights into the underlying biological mechanisms driving cartilage degeneration and joint pathology. By integrating genetic data with transcriptomic analyses, I aim to identify key genes and pathways dysregulated in GH OA, paving the way for targeted therapeutic interventions and precision medicine approaches. By leveraging the advanced genomic techniques and comprehensive data analysis methodologies, I aim to unravel the genetic architecture underlying GH OA.