Painful Temporomandibular Disorder

Болезненное височно-нижнечелюстное расстройство
Ronald Dubner, Roger B. Fillingim, Richard Ohrbach, Gary D. Slade, Carolina B. Meloto, Luda Diatchenko, Shad B. Smith, William Maixner, Anne E. Sanders, Joel D. Greenspan, Eric Bair
2016-06-23

OPPERApainful temporomandibular disorderpressure pain thresholdssingle-nucleotide polymorphismssomatic symptoms
In 2006, the OPPERA project (Orofacial Pain: Prospective Evaluation and Risk Assessment) set out to identify risk factors for development of painful temporomandibular disorder (TMD). A decade later, this review summarizes its key findings. At 4 US study sites, OPPERA recruited and examined 3,258 community-based TMD-free adults assessing genetic and phenotypic measures of biological, psychosocial, clinical, and health status characteristics. During follow-up, 4% of participants per annum developed clinically verified TMD, although that was a "symptom iceberg" when compared with the 19% annual rate of facial pain symptoms. The most influential predictors of clinical TMD were simple checklists of comorbid health conditions and nonpainful orofacial symptoms. Self-reports of jaw parafunction were markedly stronger predictors than corresponding examiner assessments. The strongest psychosocial predictor was frequency of somatic symptoms, although not somatic reactivity. Pressure pain thresholds measured at cranial sites only weakly predicted incident TMD yet were strongly associated with chronic TMD, cross-sectionally, in OPPERA's separate case-control study. The puzzle was resolved in OPPERA's nested case-control study where repeated measures of pressure pain thresholds revealed fluctuation that coincided with TMD's onset, persistence, and recovery but did not predict its incidence. The nested case-control study likewise furnished novel evidence that deteriorating sleep quality predicted TMD incidence. Three hundred genes were investigated, implicating 6 single-nucleotide polymorphisms (SNPs) as risk factors for chronic TMD, while another 6 SNPs were associated with intermediate phenotypes for TMD. One study identified a serotonergic pathway in which multiple SNPs influenced risk of chronic TMD. Two other studies investigating gene-environment interactions found that effects of stress on pain were modified by variation in the gene encoding catechol O-methyltransferase. Lessons learned from OPPERA have verified some implicated risk factors for TMD and refuted others, redirecting our thinking. Now it is time to apply those lessons to studies investigating treatment and prevention of TMD.
1
Comorbid health condition checklists and nonpainful orofacial symptoms were the most influential predictors of developing clinical TMD.
2
Frequency of somatic symptoms was the strongest psychosocial predictor of TMD incidence, whereas somatic reactivity was not predictive.
3
Genetic analyses of ~300 genes implicated 6 SNPs as risk factors for chronic TMD and 6 SNPs associated with intermediate TMD phenotypes; a serotonergic pathway and COMT gene interactions with stress were identified.
4
OPPERA recruited 3,258 TMD-free adults across 4 US sites and found a clinically verified TMD incidence of 4% per annum versus 19% annual facial pain symptom rate.
5
Pressure pain thresholds at cranial sites weakly predicted incident TMD but were strongly associated with chronic TMD cross-sectionally; repeated measures showed thresholds fluctuated with onset, persistence, and recovery but did not predict incidence.
6
Self-reported jaw parafunction predicted incident TMD much more strongly than examiner-assessed parafunction.

Development of painful temporomandibular disorder (TMD) in community-based adults enrolled in the OPPERA cohort

Risk factors, predictors, and temporal dynamics (biological, genetic, psychosocial, clinical, sensory, and sleep-related) associated with incidence, onset, persistence, and recovery of painful TMD

Publication Details
Publication Date
2016-06-23
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Ronald Dubner
Roger B. Fillingim
Richard Ohrbach
Gary D. Slade
Carolina B. Meloto
Luda Diatchenko
Shad B. Smith
William Maixner
Anne E. Sanders
Joel D. Greenspan
Eric Bair
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat
Make a presentation
100%