Characterization of Common Genetic Variants in P2RX7 and Their Contribution to Chronic Pain Conditions.

The adenosine triphosphate (ATP)-gated channel P2X7 is encoded by a gene enriched for common nonsynonymous variants. Many of these variants have functional cellular effects, and some have been implicated in chronic pain. In this study, we first systematically characterized all 17 common nonsynonymous variants using whole-cell patch clamp electrophysiology. Then, we analyzed these variants for statistical association with chronic pain phenotypes using both individual P2RX7 variants as predictors and cumulative allele counts of same-direction cellular effect in univariate models. Association and validation analyses were conducted in the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) cohort (N = 3260) and in the Complex Persistent Pain Conditions (CPPC) cohort (N = 900), respectively. Our results showed an association between allele A of rs7958311 and an increased risk of chronic pelvic pain, with convergent evidence for contribution to fibromyalgia and irritable bowel syndrome, confirmed in a meta-analysis. This allelic variant produced a unique cellular phenotype: a gain-of-function in channel opening, and a loss-of-function in pore opening. A computational study using a 12-state Markov model of ATP binding to the P2X7 receptor suggested that this cellular phenotype arises from an increased ATP binding affinity and an increased open channel conductance combined with a loss of sensitization. Cumulative allele count analysis did not provide additional insights. In conclusion, our results go beyond reproducing association for rs7958311 with chronic pain and suggest that its unique combination of gain-of-function in channel and loss-of-function in pore activity may explain why it is likely the only common P2RX7 variant with contribution to chronic pain. PERSPECTIVE: This study characterizes all common P2RX7 variants using cellular assays and statistical association analyses with chronic pain, with Markov state modeling of the most robustly associated variant.

Duke Scholars

Author Luda Diatchenko Anesthesiology