The Restoring Joint Health and Function to Reduce Pain (RE-JOIN) Consortium represents a groundbreaking initiative within the NIH HEAL (Helping to End Addiction Long-term) Initiative, bringing together multiple research teams to address the urgent need for non-opioid approaches to managing joint pain. Supported by NIAMS and leveraging data coordination through the SPARC DRC, RE-JOIN focuses on creating comprehensive 3D maps of sensory neuron networks in the knee and temporomandibular joint (TMJ)—two of the body's most clinically significant yet understudied joints. The consortium's overarching goal is to understand how joint innervation patterns change with aging, disease, and injury, laying the groundwork for novel therapeutic interventions that could reduce opioid dependency.
The five funded research teams employ cutting-edge technologies across diverse animal models and human tissue samples. At Baylor College of Medicine, the team led by Brendan Lee, M.D., Ph.D., uses advanced neuronal labeling techniques to capture 3D images of entire limbs in mice, comparing innervation patterns across different ages, osteoarthritis models, and pain relief interventions. Anne-Marie Malfait, M.D., Ph.D., at Rush University and her team combines state-of-the-art imaging with transcriptomics to map both mouse and human knee joints, measuring the gene activity that drives neural network reorganization. Christopher Donnelly, D.D.S., Ph.D., at Duke University employs magnetic resonance imaging to map sensory neural networks of jaw tissues in both mice and humans, analyzing how different neuron types contribute to TMJ pain development at the molecular level. Armen Akopian, Ph.D., and colleagues at the University of Texas Health Sciences Center at San Antonio focus on identifying the function, type, distribution, and molecular signatures of nerves providing sensation to facial and neck structures, including the TMJ, with the goal of developing robust animal models for TMJ disorders. Kyle Allen, Ph.D., and the University of Florida team uses advanced behavioral testing in rodents alongside clinical assessments in human patients to connect changes in joint innervation with pain symptoms and functional outcomes, enabling patient stratification for personalized treatment approaches.
At the 3rd Annual RE-JOIN Scientific Meeting, the consortium unveiled an ambitious slate of collaborative projects marking the transition into the consortium's next phase. These initiatives showcase RE-JOIN's evolution from technology development and data generation to cross-team integration efforts designed to accelerate therapeutic discovery for joint pain.
The Joint Atlas project will develop a user-controlled RE-JOIN portal enabling teams to upload, convert, and annotate 3D imaging data using GPU-accelerated AI models. This platform will support collaborative annotation of anatomical structures across different imaging modalities, creating comprehensive spatial references for both knee and TMJ tissues that will enable scientists to compare their imaging data to data generated by others across the consortium and broader research community.
The Joint Innervation Maps initiative will develop sensory and sympathetic innervation maps for the knee and temporomandibular joints by integrating data across RE-JOIN teams. These comprehensive maps will lay the foundation for comparing sensory or sympathetic innervation patterns across disease models to understand sprouting phenomena observed in osteoarthritis and neuropathic pain, providing critical insights into how neural networks reorganize in pathological conditions.
The Single Cell and Spatial Profiling of Whole Joints project combines three complementary efforts using spatial transcriptomics and single cell transcriptomic-based platforms to characterize dorsal root ganglia, trigeminal ganglia, and synovial tissues at single-cell resolution across species, ages, and disease states. This molecular-level characterization will reveal the diverse neuronal subtypes and their functional states, enabling precise identification of cell populations that mediate joint pain.
The Novel Gene Therapies for Joint Disease and Pain project will leverage high-capacity adenoviral vectors with established GMP production and clinical translation potential to test consortium-identified therapeutic targets. With initial demonstrations planned in naturally-occurring equine osteoarthritis, rat TMJ models, and myofascial pain systems, this project bridges the gap between target discovery and therapeutic development, capitalizing on vectors with proven safety profiles and translational feasibility.
Finally, the Cross-Species Profiling of Joint Pain Behaviors project takes a two-pronged approach: developing flexible supervised machine learning pipelines to identify objective facial pain features across rodent, equine, and potentially human models, while simultaneously conducting comparative phenotypic analysis of clinical pain presentations using TMJ and knee patient data already collected across consortium sites. This work will establish standardized, objective pain assessment tools that can be applied across species and clinical settings.
Together, these collaborative projects position RE-JOIN to move beyond descriptive studies toward identifying generalizable, biologically relevant drivers of joint pain. By integrating data across teams, species, and methodologies, the consortium aims to create a comprehensive blueprint for joint innervation that will serve as a foundation for developing targeted, non-addictive therapies. All RE-JOIN data will be made publicly accessible through the SPARC portal and HEAL Data Ecosystem following FAIR (Findable, Accessible, Interoperable, and Reusable) principles, ensuring that these valuable resources benefit the broader scientific and medical communities working to end the opioid epidemic and restore joint health.
