Non-invasive metabolic biomarkers for early diagnosis of diabetic nephropathy: Meta-analysis of profiling metabolomics studies

Abstract

Aim: Diabetic nephropathy (DN) is one of the worst complications of diabetes. Despite a growing number of DN metabolite profiling studies, most studies are suffering from inconsistency in their findings. The main goal of this meta-analysis was to reach to a consensus panel of significantly dysregulated metabolites as potential biomarkers in DN. Data synthesis: To identify the significant dysregulated metabolites, meta-analysis was performed by "vote-counting rank" and "robust rank aggregation" strategies. Bioinformatics analyses were performed to identify the most affected genes and pathways. Among 44 selected studies consisting of 98 metabolite profiles, 17 metabolites (9 up-regulated and 8 downregulated metabolites), were identified as significant ones by both the meta-analysis strategies (p-value 0.05 and OR 2 or <0.5) and selected as DN metabolite meta-signature. Furthermore, enrichment analyses confirmed the involvement of various effective biological pathways in DN pathogenesis, such as urea cycle, TCA cycle, glycolysis, and amino acid metabolisms. Finally, by performing a meta-analysis over existing time-course studies in DN, the results indicated that lactic acid, hippuric acid, allantoin (in urine), and glutamine (in blood), are the topmost noninvasive early diagnostic biomarkers. Conclusion: The identified metabolites are potentially involved in diabetic nephropathy pathogenesis and could be considered as biomarkers or drug targets in the disease. Prospero registration number: CRD42020197697. (c) 2021 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.