Chronic pain is a significant problem for patients with lower extremity fractures, and the consequences are substantial. Individuals with fracture-related chronic pain miss more days of work, and seek medical care more frequently than those without chronic pain, along with reporting high levels of pain intensity, anxiety, and depression. Several factors (e.g. older age, being female, fewer years of education, high pain intensity) have been identified as chronic pain risk factors, but the ability to predict who will experience chronic pain after lower extremity fracture has been understudied. While many patients develop chronic pain at the site of fracture, there is variability in the number, type, and severity of symptoms, suggesting that -omics mechanisms may be key contributors. Gene expression profiling can be conducted in smaller cohorts and has been successfully used to identify biomarkers of several chronic pain conditions (chronic visceral pain, osteoarthritis pain, and acute low back pain). Thus, physiological, psychological and differences in gene expression may account for the variability in lower extremity fracture patients who develop chronic pain versus those who do not. This study will rigorously phenotyping a cohort of 240 fibula and/or tibia fracture patients and a cohort of 40 healthy controls for two years. The outcome will be measured using the Chronic Pain Grading Scale. Participants scoring 1 - 30 on the characteristic pain intensity score in the last 3 months will be classified as having chronic pain, and those reporting no pain (0) in the last 3 months will be classified as having no chronic pain. Data will be analyzed using a direct-entry multiple logistic regression analysis and the results will be presented as odds ratios. Association analyses with gene expression data, accounting for age and sex as potential moderators of inter-individual differences, will be conducted to identify phenotypic and biomarker signatures of those who are likely to develop chronic pain. The combination of rigorous phenotyping with genetic/genomic association analyses will increase our understanding of the contributing risk factors of chronic pain after lower extremity fracture and accelerate the identification of new therapeutic targets to prevent and/or manage post-trauma chronic pain, ultimately leading to improved quality of life and decreased healthcare cost.
Aim 1 will examine physiological (peripheral sensory nerve function), psychological (anxiety, depressive symptoms, sleep, pain catastrophizing), clinical (pain intensity, treatment), and sociodemographic factors (age, race, ethnicity, income, education, etc.) predictive of chronic pain phenotype at 52 weeks following lower extremity fracture.
Aim 2 will test the hypothesis that differences in gene expression will be associated with the chronic pain phenotype following lower extremity fracture. Analyses will examine how changes in gene expression differ between extreme phenotypes at baseline and 52 weeks and construct a database of altered gene expression profiles as well as novel therapeutic targets and pathways for better pain management.
Chronic pain following fracture is a significant problem with many negative physical, psychological, social, emotional, and economical consequences. However, the underlying biological mechanism associated with chronic pain following fracture remains unclear. The combination of rigorous phenotyping with genetic/genomic association analyses will increase our understanding of the risk factors that contribute to the development of chronic pain after lower extremity fracture. This will accelerate the identification of new therapeutic targets to prevent and/or manage post-trauma chronic pain, ultimately leading to improved quality of life and decreased healthcare cost.
