Metabolic signature of protein energy wasting among Malaysian hemodialysis patients

End-stage renal disease (ESRD) patients undergoing maintenance hemodialysis (HD) often experience a state of metabolic and nutritional derangements that is highly associated with morbidity and mortality due to the protein energy wasting (PEW) disorder. Identification of PEW was recommended by International Society of Renal Nutrition and Metabolism (ISRNM) with a reported prevalence of 18-75%. However, direct quantification of muscle wasting remains unsolved for this population besides there are no consistent guidelines and standardized scoring tools in a diverse patient-wide population that making it difficult to diagnose PEW. Thus, it is prudent to identify biomarkers signature of PEW using proton nuclear magnetic resonance (1H-NMR) based metabolomics approach which will assist in diagnosis of PEW. In this cross-sectional study, a total of 106 subjects of ESRD patients undergoing chronic HD were stratified into PEW (n=53) and Non-PEW (NPEW) (n=53) based on the established ISRNM criteria. Fasting predialysis plasma samples with filtration were analyzed by 1H-NMR and the data acquired through by the combination of presaturation (PRESAT) and the Carr–Purcell– Meiboom–Gill (CPMG) pulse sequence were further processed using Chenomx. Multivariate data analysis and the statistical analysis were performed using SIMCA-P and the SPSS softwares to discriminate the metabolomics profiles between the two groups. Orthogonal partial least square discriminant analysis (OPLS-DA) demonstrated the difference in metabolomics profiles between PEW and NPEW patients by the principal component 1 and indicates that PEW syndrome induced specific metabolic pattern alteration. Combination of loading plots and variable importance in projection (VIP) plots of OPLS-DA model provides the important variable that contributed to the group separation. A total of 32 metabolites were identified and quantified using Chenomx, with 18 metabolites belong to PEW groups and 14 metabolites represented NPEW groups. Among all the metabolites analyzed using Mann-Whitney U Test, 3-hydroxybutyrate (p<0.001), acetate (p=0.027), arabinose (p=0.029), maltose (p=0.021), ribose (p=0.041), sucrose (p=0.008), and tartrate (p=0.018) were significantly increased (p<0.05) in PEW subjects whilst creatinine (p<0.001) was significantly decreased. However, analysis of covariance (ANCOVA) revealed that the contribution of arabinose, maltose, ribose, sucrose and tartrate on the group discrimination might be affected by age and dialysis vintage. Besides, creatinine was also showed to be significantly correlated (p<0.01) with the anthropometric mid-arm muscle area (MAMA) (rs =0.426), lean tissue mass (LTM) (rs=0.362) and albumin (rs=-0.315). Our results signified that patients who experienced PEW had different metabolic profiles as opposed to NPEW patients. Pathway analysis indicated that PEW-related metabolites triggered perturbation in fatty acid mechanism and induced gluconeogenesis as well as glyoxylate and dicarboxylate metabolism. These results provide primary data in understanding metabolic perturbation of PEW and corresponding abnormal metabolites that potentially serve as biomarker of PEW.

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