Deconstructing TMJD Classifiers at the Single Cell Level

Goal

The goal of this initiative is to encourage research focused on deciphering the cellular and molecular mechanisms underpinning TMJD pain and tissue dysfunction using single-cell omics approaches. Delineation of cellular and molecular mechanisms that mediate TMJD resolution and homeostasis are also desired. Identification of cell populations and their effector pathways, in TMJD target tissue (e.g. synovial fluid, muscle, skin), as 1) molecular disease classifiers allowing for patient stratification, 2) diagnostic, prognostic, and/or predictive biomarkers, and/or 3) novel therapeutic targets are desired outcomes of this initiative.

Background

TMJDs are a heterogenous and poorly understood set of painful conditions that manifest in the temporomandibular joint (TMJ), muscles of mastication and surrounding tissues compromising quality of life for many individuals. They affect between 5-10% of the U.S. population with an annual incidence rate that is greater in females compared to males (~2:1) and often lack correlation between overt signs of injury and pain intensity ratings. TMJDs may also present with other systemic and comorbid medical conditions and overlapping pain conditions (e.g., fibromyalgia, back pain, headache, irritable bowel syndrome). As such, these disorders have long confounded medical and dental health care providers often resulting in misdiagnosis and delayed or ineffective treatment. The absence of a firm mechanistic understanding of TMJDs has precluded stratification of patients into clinically meaningful and mechanistically based subgroups¹ and identification of clear etiological targets for development of effective evidence-based treatments.

The Orofacial Pain: Evaluation and Risk Assessment (OPPERA) study has made progress in TMJD patient stratification through the identification of three distinct patient subgroups across an array of biopsychosocial risk factors using supervised cluster analysis. The cluster with the most severe symptoms also had the greatest burden of comorbid pain conditions.² OPPERA also identified several potential genetic risk factors for TMD found to be associated with pain perception, affective responses, and inflammation.³ Epidermal growth factor receptor (EGFR)—activated by numerous endogenous ligands that promote cellular growth, proliferation, and tissue regeneration—and its natural ligand, epiregulin (EREG), were identified as genetically associated with the development of chronic pain in several TMJD clinical cohorts.⁴ Evidence that muscle RAS oncogene homolog (MRAS) expression moderates resiliency to pain, is male specific and may contribute to lower rates of painful TMJD in men has also been reported.⁵ While genetic variants that may be associated with TMJD pathophysiology have been identified, further research focused on discerning mechanisms of molecular pathogenesis or resilience, in target tissue, that correlate with stratification approaches and TMJD clinical heterogeneity are needed.

While data indicate that the immune system is critically involved in the development and maintenance of chronic pain, the role of immune-nervous system interactions on the pathophysiology of pain and tissue dysfunction in TMDs remains unclear.⁶ T cells have become a focus of investigation in chronic pain pathophysiology as subsets release mediators such as cytokines and endogenous opioid peptides that can promote, suppress, or resolve pain.⁷ Females have a higher number of circulating CD4+ and CD8+ T cells than males and data suggests that female mice might preferentially use adaptive immune cells instead of microglia to produce mechanical allodynia after injury.^8,9 Additionally, regulatory T (Treg) cell ablation has been found to be sufficient to trigger experimental autoimmune encephalomyelitis (EAE) and facial allodynia in female mice that is reduced by adoptive Treg cell transfer.¹⁰ Emerging clinical data suggest that patients with chronic pain have different phenotypic circulating T cell profiles compared to controls. Congruent with this, circulating proinflammatory cytokines are increased in TMJD patients and cases with widespread pain differed in allelic frequency of single nucleotide polymorphisms (SNPs) that mapped to a T-cell receptor pathway.¹¹ The presence of other inflammatory mediators such as serotonin and prostaglandins have been noted in the synovial fluid of inflamed joints and absent in healthy individuals, as have certain neuropeptides.¹² Levels of elastin derived peptides, from human TMJD synovial fluid, have been found to correlate with duration of TMJ locking and pain scores and may induce inflammatory responses in synovial cells implicating elastin degradation as a potential precipitating event.¹³ Identification and analysis of neuroimmune mediators and their regulatory pathways—in distinct TMJDs with or without COPCs—may offer new disease modifying strategies.

Gaps and Opportunities

There are few examinations of target tissues (e.g. synovial fluid, muscle, skin) or blood from human subjects with TMJDs that use large-scale, non-targeted approaches, in the areas of genomics, epigenetics, transcriptomics, immune profiling, metabolomics, proteomics and immunophenotyping.⁶ While our mechanistic understanding of TMJDs has been advanced through human and animal studies, progress has been hampered by limited emphasis on changes in affected human target tissues and few integrated analyses combining findings in multiple cells and tissues. Recent technological advances in microfluidics, machine learning, and gene expression profiling have led to advances in single cell biology—such as single-cell RNA sequencing (scRNA-seq), single-cell mass spectrometry (CyTOF), single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq), and Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq)—that allow multi-dimensional profiling of individual cells from complex tissues and organs. For example, single-cell gene expression profiling now allows for identification of gene expression signatures of small populations of cells within a tissue, that may yield unique insights into mechanisms driving disease pathogenesis and outcomes. Application of such technological advances to TMJDs is critical to enable deconstruction of key events in cells and tissues related to disease, disease severity, resolution, and response to therapy.

Specific Areas of Interest

Areas of interest include, but are not limited to:

Customization of cell-isolation, sample preparation and data generation methods—to the TMJ and surrounding tissues—that produce FAIRⁱ-friendly data with improved sensitivity, spatiotemporal resolution, multiplexing capability and scalability.
Generation of an integrated data set of changes at the molecular level obtained by extensive profiling of gene expression and signaling in immune and tissue-resident cells.
Characterization of modules and pathways, and how they can be used to understand differences across TMJD disease states and between chronic TMJDs and chronic TMJD that present with other COPCs.
Chart rewiring of cell-cell interactions by mapping receptor-ligand pairs onto cell subsets to construct putative cell-cell interaction networks across disease states.
Identification of changes in circulating cells in blood that correlate with activation of specific pathways in target tissues that can be used to improve patient stratification, serve as surrogate biomarkers for diagnostic or treatment decisions, or improve therapeutic targeting.
Application of machine learning and computational modeling for a systematic approach to integration of datasets into pathways.

References

Harper DE, Schrepf A, Clauw DJ. Pain Mechanisms and Centralized Pain in Temporomandibular Disorders. J Dent Res, 2016. 95(10): p. 1102-8.
Bair E, et al. Identification of clusters of individuals relevant to temporomandibular disorders and other chronic pain conditions: the OPPERA study. Pain, 2016. 157(6): p. 1266-78.
Smith SB, et al. Potential genetic risk factors for chronic TMD: genetic associations from the OPPERA case control study. J Pain, 2011. 12(11 Suppl): p. T92-101.
Martin LJ, et al. Epiregulin and EGFR interactions are involved in pain processing. J Clin Invest, 2017. 127(9): p. 3353-3366.
Smith SB, et al. Genome-wide association reveals contribution of MRAS to painful temporomandibular disorder in males. Pain, 2019. 160(3): p. 579-591.
The National Academies of Sciences Engi (Washington District of Columbia), Temporomandibular disorders : priorities for research and care. 2020, Washington: The National Academies Press. pages cm.
Laumet G, et al. T Cells as an Emerging Target for Chronic Pain Therapy. Front Mol Neurosci, 2019. 12: p. 216.
Amadori A, et al. Genetic control of the CD4/CD8 T-cell ratio in humans. Nat Med, 1995. 1(12): p. 1279-83.
Sorge RE, et al. Different immune cells mediate mechanical pain hypersensitivity in male and female mice. Nat Neurosci, 2015. 18(8): p. 1081-3.
Duffy SS, et al. Regulatory T Cells and Their Derived Cytokine, Interleukin-35, Reduce Pain in Experimental Autoimmune Encephalomyelitis. J Neurosci, 2019. 39(12): p. 2326-2346.
Slade GD, et al. Facial pain with localized and widespread manifestations: separate pathways of vulnerability. Pain, 2013. 154(11): p. 2335-43.
Sessle BJ. Peripheral and central mechanisms of orofacial inflammatory pain. Int Rev Neurobiol, 2011. 97: p. 179-206.
Kobayashi K, et al. Elastinderived peptides are involved in the processes of human temporomandibular disorder by inducing inflammatory responses in synovial cells. Mol Med Rep, 2017. 16(3): p. 3147-3154.

ⁱFAIR-friendly data refers to data that is Findable, Accessible, Interoperable, and Reusable.

Last Reviewed
April 2024