Metabolomics Signature for Non‐Responders to Total Joint Replacement Surgery in Primary Osteoarthritis Patients: The Newfoundland Osteoarthritis Study

Abstract

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

Differential correlation network analysis identified novel metabolomics signatures for non-responders to total joint replacement in primary osteoarthritis patients

“…Metabolic profiling was performed on plasma as per our previous study (Costello et al 2019) using a commercially available generic metabolomic assay kit-the Biocrates AbsoluteIDQ p180 commercial kit (BIOCRATES Life Sciences AG, Innsbruck, Austria) which assesses 186 metabolites, including acylcarnitines, amino acids, biogenic amines, glycerophospholipids, monosaccharides, and sphingolipids. The full list of the metabolites is provided in Supplementary Table 1.…”

“…Participants were recruited from those undergoing TJR in St. John's, Newfoundland and Labrador (NL), Canada (Costello et al 2019). Diagnosis was made as per the American College of Rheumatology clinical diagnostic criteria (Altman et al 1991) and confirmed using pathology reports postsurgery.…”

“…While total joint replacement (TJR) is the most effective intervention for advanced osteoarthritis (OA), up to one third of patients undergoing total knee replacement (TKR) and total hip replacement (THR) reported unfavourable longterm pain outcomes (Beswick et al 2012). Such patients are classified as non-responders to TJR; our previous study (Costello et al 2019) further subdivided non-responders to clarify whether long-term outcome from surgery sees a lack of improvement in joint pain and/or joint function. It is prudent, therefore, to identify factors that are associated with these non-responders, provide insights into the potential mechanisms leading to poor TJR outcome, and develop strategies for improving patient-reported outcome.…”

“…Using a metabolomics approach, we previously identified two metabolite ratios (acetylcarnitine (C2) to phosphatidylcholine (PC) acyl-alkyl (ae) C40:1 and PC diacyl (aa) C36:4 to isoleucine) associated with pain nonresponders and one metabolite ratio (glutamine to isoleucine) associated with function non-responders (Costello et al 2019) in plasma. However, as the previous analysis used an individual metabolite-based analytic method with a conservative significance level, we might miss other important markers that play a role in TJR response.…”

“…Such data driven methods have been applied to OA research by different research groups (Hu et al 2018;Nelson et al 2019). In this study, we applied a differential correlation network analysis method (Hu et al 2018) to the same dataset of our previous study (Costello et al 2019) to identify further metabolic markers and pathways for non-responders to TJR.…”