Metabolomic analysis coupled with extreme phenotyp sampling identified that lysophosphatidylcholines are associated with multisite musculoskeletal pain

Abstract

Purpose: Musculoskeletal pain is the most common cause of disability globally and imposes a significant socioeconomic burden. Up to 80 percent of those with musculoskeletal pain have pain at multiple sites, which is associated with poorer health status, greater psychological distress and worse health-related quality of life when compared to people with no or single site pain. To help better our understanding in the pathogenesis of multisite musculoskeletal pain (MSMP), we undertook this metabolomic analysis using extreme MSMP phenotype sampling approach to identify metabolomic signatures that associate with MSMP. Methods: The study participants were derived from the Newfoundland Osteoarthritis Study (NFOAS). Musculoskeletal pain was assessed using a simple pain questionnaire where patients were asked to circle painful sites on a manikin. The number of painful sites were calculated and two extremes (1≥ painful sites ≥7) were selected and used in the analysis. Targeted metabolic profiling on overnight fasting plasma samples was performed using Biocrates AbsoluteIDQ® p180 kit which quantifies 186 metabolite concentrations. The concentrations were then standardised using the Z-score for subsequent analysis. Further, plasma levels of cytokines including Macrophage Migration Inhibitory Factor (MIF), Tumour Necrosis Factor-alpha (TNF-α), Interleukin 6 (IL-6), and Interleukin-1 beta (IL-1β) were also assessed by enzyme-linked immunosorbent assay (ELISA). Data on conventional blood lipid profiles including total cholesterol, HDL, LDL, and triglycerides were retrieved from Eastern Health Meditech Health Care Information System. Univariable and multivariable analyses were performed by logistic regression and the multiple testing was corrected with the Bonferroni method. Results: Among the total 617 participants of the NFOAS who had pain data available, 20% reported no pain or single site musculoskeletal pain (n=123, mean age 66.66±8.33 years, mean BMI 32.88±6.44 kg/m2, 51.22% females), and 13% reported pain at 7-21 sites (n=83, mean age 64.27±7.25 years, mean BMI 33.56±8.30 kg/m2, 67.47% females). MSMP cases were relatively younger (p=1.86*10-2) and had more females (p=2.06*10-2), but there was no difference in BMI between MSMP cases and controls. The data also showed that there was no association between MSMP and four cytokines including MIF, IL-6, IL-1β, and TNF-α and blood lipid profiles including total cholesterol, HDL, LDL, and triglycerides (all p>0.05). Among the 186 metabolites measured, 164 passed the quality control and were included in the analysis. We found two lysophosphatidylcholines, one with 26 carbons but no double bonds (lysoPC26:0) and one with 28 carbons and 1 double bond (lysoPC 28:1), were associated with MSMP. Per SD increase was associated with 2.1 times increased risk for MSMP for lysoPC26:0 (p=6.52*10-4) and 2.07 times for lysoPC 28:1(p=1.23*10-4). The significances remained after adjustment for age, sex, and BMI (all p<3.3*10-3). Two metabolites belong to the same metabolite class and were highly correlated (r=0.68, p<2.20*10-16). To demonstrate their potential in clinical utility as biomarkers for MSMP, we examined the concentrations of these two metabolites in the between-group (e.g.: patients with 2-6 painful sites) and found that the concentrations were right between the two extremes. The concentrations of lysoPC 26:0 were 0.17±0.09 uM; 0.18±0.11 uM; 0.23±0.15 uM for patients with painful sites ≤1; 2-6; and ≥7, respectively. They were 0.26±0.08 uM; 0.28±0.11 uM; 0.33±0.14 uM for lysoPC 28:1. Conclusions: Our data showed that lysoPC26:0 and lysoPC28:1 were associated with MSMP, suggesting the signalling pathways involved in oxidative stress and inflammatory responses are involved in MSMP. Further, our data suggest lysoPC26:0 and lysoPC28:1 have clinical actionable potential and could be considered as novel plasma markers for MSMP.