Effects of genotype on TENS effectiveness in controlling knee pain in persons with mild to moderate osteoarthritis

摘要

Abstract Background This study examined the extent to which genetic variability modifies Transcutaneous Electrical Nerve Stimulation (TENS) effectiveness in osteoarthritic knee pain. Methods Seventy‐five participants with knee osteoarthritis were randomly assigned to either: (a) High‐frequency TENS, (b) Low‐frequency TENS or (c) Transient Placebo TENS. Pain measures were collected pre‐ and post‐treatment. Participants were genotyped on genes implicated in central or peripheral pain pathways: NGFB, NTRK1, EDNRA, EDNRB, EDN1, OPRM1, TAC1, TACR1, BDNF, BDKRB1, 5HTT, COMT, ESR2, IL6 and IL1B . Genetic association using linear regression modelling was performed separately for the transient placebo TENS subjects, and within the High‐frequency TENS?+?Low‐frequency TENS participants, including TENS level as a covariate. Results In the placebo group, SNPs rs165599 ( COMT ) was significantly associated with an increased heat pain threshold (β?=??1.87; p ?=?.003) and rs6827096 ( EDNRA ) with an increased resting pain (β?=?2.68; p ?=?.001). Within the treatment groups, TENS effectiveness was reduced by the SNP rs6537485 ( EDNRA ) minor allele in relationship to mechanical sensation (β?=?184.13; p ?=?5.5E?9). Individuals with the COMT rs4680 minor allele reported lowered pain at rest after TENS (β?=??42.30; p? =?.001), with a higher magnitude of pain reduction (28 unit difference) in the low‐frequency TENS group compared to the high‐frequency TENS group (β?=?28.37; p ?=?.0004). Conclusions EDNRA and COMT are implicated in osteoarthritic knee pain and provide a basis for tailoring TENS interventions according to individual characteristics. Significance Findings from this study demonstrate that genetic variation within the COMT and EDNRA genes influences the effectiveness of TENS, a non‐pharmacologic pain‐reduction intervention, in the context of osteoarthritic knee pain. Evidence such as this may contribute to risk models that provide a clinically useful tool for personalizing TENS interventions according to individual characteristics in order to best control pain and maximize functional status.