Single-cell omics approaches to investigate TMD

项目总结/文摘

Project Summary/Abstract Temporomandibular disorders (TMD) are the most common form of orofacial pain, affecting 5-10% of adults in the U.S. Many causes and risk factors have been linked to TMD, but our understanding of the physiological mechanisms underlying the development of chronic TMD pain is limited. The current theoretical framework implicates sensitization at the peripheral and central levels due to a network of inflammatory, immune, neuropathic, and nociplastic processes. Further studies of the tissues affected in TMD, including muscles of mastication, the temporomandibular joint and synovium, and the trigeminal nerve branches, are necessary to elucidate etiological processes, but these tissues are not easily accessible for research or for diagnosis. Evidence supports a role for circulating inflammatory and immune mediators from blood and saliva, but the relationship between these potential biomarkers and pathology in orofacial tissues needs to be rigorously established in experiments with direct comparisons. We propose to conduct simultaneous assessments of masseter muscle tissue and immune cell populations in peripheral blood from both TMD cases and controls in order to identify etiological pathways at the cellular level. In the Planning and Feasibility phase of this project we will first develop novel techniques of collection and processing of tissues enabling state-of-the-art single-cell analysis. In the Implementation phase, we will assess gene transcription using single-cell RNA-seq in blood, comparing expression patterns with spatial transcriptomics in slices of masseter biopsy tissue. In masseter muscle we will also examine sensory nerve density and morphology to investigate neuropathic mechanisms, and cell-surface proteins to explore neuroimmune interactions. We will identify cellular patterns that distinguish cases from controls, as well as look for differences between individuals that represent distinct subcategories of patients with similar etiological mechanisms. Finally, we will integrate bioinformatics datasets from these unbiased omics approaches to discover biomarkers with predictive and prognostic value. This project will develop techniques and improve mechanistic understanding to advance the science of TMD from a rudimentary symptom-based classification toward a more complete understanding of biopsychosocial etiology across the spectrum of nociceptive, nociplastic, and neuropathic mechanisms at the cellular level.