Although total joint replacement (TJR) surgery is considered as the most effective treatment for advanced osteoarthritis (OA) patients, up to one‐third of patients reported unfavorable long‐term post‐operative pain outcomes. We aimed to identify metabolic biomarkers to predict non‐responders to TJR using a metabolomics approach. TJR patients were recruited and followed‐up at least 1‐year post‐surgery; TJR outcomes were assessed by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function subscales. Targeted metabolomic profiling was performed on plasma samples collected pre‐surgery and pairwise metabolite ratios, as proxies for enzymatic reactions, were calculated. Association tests were performed between each metabolite ratio and non‐responders. The metabolome‐wide significance was defined as p < 2 × 10−5. A total of 461 TJR patients due to primary OA were included in the analysis. Fifteen percent of patients were classified as pain non‐responders; 16% were classified as function non‐responders. Lower baseline WOMAC pain and function scores were significantly associated with pain and function non‐responders, respectively (both p < 0.03). Two metabolite ratios were significantly associated with pain non‐responders; acetylcarnitine (C2) to phosphatidylcholine acyl‐alkyl C40:1 (PC ae C40:1) was five times higher in pain non‐responders whereas phosphatidylcholine diacyl C36:4 (PC aa C36:4) to isoleucine was twenty one times lower in pain non‐responders than responders (all p ≤ 1.93 × 10−5). One metabolite ratio, glutamine to isoleucine, was significantly lower in function non‐responders than responders (eight times lower; p = 1.08 × 10−5). Three metabolite ratios (C2 to PC ae C40:1, PC aa C36:4, and glutamine to isoleucine) related to inflammation and muscle breakdown could be considered as novel plasma markers for predicting non‐responders to TJR and warrant further investigation. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:793‐802, 2020

Supplemental Digital Content is Available in the Text. Metabolic profiling coupled with extreme sampling identified lysophosphatidylcholines 26:0 and 28:1 to be potential biomarkers for multisite musculoskeletal pain.

Introduction Up to one third of total joint replacement patients (TJR) experience poor surgical outcome. Objectives To identify metabolomic signatures for non-responders to TJR in primary osteoarthritis (OA) patients. Methods A newly developed differential correlation network analysis method was applied to our previously published metabolomic dataset to identify metabolomic network signatures for non-responders to TJR. Results Differential correlation networks involving 12 metabolites and 23 metabolites were identified for pain non-responders and function non-responders, respectively. Conclusion The differential networks suggest that inflammation, muscle breakdown, wound healing, and metabolic syndrome may all play roles in TJR response, warranting further investigation.

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Objectives Knee pain is the major driver for osteoarthritis (OA) patients to seek healthcare; but after pursuing both conservative and surgical pain interventions, approximately 20% of patients continue to report long-term pain following total knee arthroplasty (TKA). The study aimed to identify a metabolomic signature for sustained knee pain after TKA to elucidate possible underlying mechanisms. Methods Two independent cohorts from St. John’s, NL, Canada (n = 430), and Toronto, ON, Canada (n = 495) were included in the study. Sustained knee pain was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale (five questions) at least one year after TKA for primary OA. Those reporting any pain on all five questions were considered to have sustained knee pain. Metabolomic profiling was performed on fasted pre-operative plasma samples using the Biocrates Absolute IDQ p180 kit. Associations between metabolites and pair-wise metabolite ratios with sustained knee pain in each individual cohort were assessed using logistic regression with adjustment for age, sex, and BMI. Random-effects meta-analysis using inverse variance as weights was performed on summary statistics from both cohorts. Results One metabolite, phosphatidylcholine (PC) diacyl (aa) C28:1 (OR = 0.66, p = 0.00026), and three metabolite ratios, PC aa C32:0 to PC aa C28:1, PC aa C28:1 to PC aa C32:0, and tetradecadienylcarnitine (C14:2) to sphingomyelin C20:2 (ORs=1.59, 0.60, and 1.59, respectively; all p &lt; 2 × 10−5), were significantly associated with sustained knee pain. Conclusions Though further investigations are needed, our results provide potential predictive biomarkers and drug targets that could serve as a marker for poor response and be modified pre-operatively to improve knee pain and surgical response to TKA.