Abstract
OBJECTIVE: To identify endotypes of osteoarthritis (OA) by a metabolomics analysis. METHODS: Study participants included hip/knee OA patients and controls. Fasting plasma samples were metabolomically profiled. Common factor analysis and K-means clustering were applied to the metabolomics data to identify the endotypes of OA patients. Logistic regression was utilized to identify the most significant metabolites contributing to the endotypes. Clinical and epidemiological factors were examined in relation to the identified OA endotypes. RESULTS: Six hundred and fifteen primary OA patients and 237 controls were included. Among the 186 metabolites measured, 162 passed the quality control analysis. The 615 OA patients were classified in three clusters (A, 66; B, 200; and C, 349). Patients in cluster A had a significantly higher concentration of butyrylcarnitine (C4) than other clusters and controls (all P < 0.0002). Elevated C4 is thought to be related to muscle weakness and wasting. Patients in cluster B had a significantly lower arginine concentration than other clusters and controls (all P < 7.98 × 10-11). Cluster C patients had a significantly lower concentration of lysophosphatidylcholine (with palmitic acid), which is a pro-inflammatory bioactive compound, than other clusters and controls (P < 3.79 × 10-6). Further, cluster A had a higher BMI and prevalence of diabetes than other clusters (all P ≤ 0.0009), and also a higher prevalence of coronary heart disease than cluster C (P = 0.04). Cluster B had a higher prevalence of coronary heart disease than cluster C (P = 0.003) whereas cluster C had a higher prevalence of osteoporosis (P = 0.009). CONCLUSION: Our data suggest three possible clinically actionable endotypes in primary OA: muscle weakness, arginine deficit and low inflammatory OA.