4.3 Review

Metabolomics of Type 1 and Type 2 Diabetes: Insights into Risk Prediction and Mechanisms

Journal

CURRENT DIABETES REPORTS
Volume 22, Issue 2, Pages 65-76

Publisher

CURRENT MEDICINE GROUP
DOI: 10.1007/s11892-022-01449-0

Keywords

Metabolomics; Type 1 diabetes; Type 2 diabetes; Risk prediction

Funding

  1. NIH [K23-HL138260, R01-HL156975]
  2. Department of Medicine, Boston University School of Medicine

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This review explores the current status of metabolomic investigation in diabetes, emphasizing its potential in improving risk prediction and mechanistic understanding. It discusses the associations between metabolites and type 2 diabetes risk, abnormal metabolite patterns in type 1 diabetes, and specific metabolite signatures of diabetes complications. The review also highlights the acute response of metabolites to pharmacologic treatment.
Purpose of Review Metabolomics enables rapid interrogation of widespread metabolic processes making it well suited for studying diabetes. Here, we review the current status of metabolomic investigation in diabetes, highlighting its applications for improving risk prediction and mechanistic understanding. Recent findings Findings of metabolite associations with type 2 diabetes risk have confirmed experimental observations (e.g., branched-chain amino acids) and also pinpointed novel pathways of diabetes risk (e.g., dimethylguanidino valeric acid). In type 1 diabetes, abnormal metabolite patterns are observed prior to the development of autoantibodies and hyperglycemia. Diabetes complications display specific metabolite signatures that are distinct from the metabolic derangements of diabetes and differ across vascular beds. Lastly, metabolites respond acutely to pharmacologic treatment, providing opportunities to understand inter-individual treatment responses. Metabolomic studies have elucidated biological mechanisms underlying diabetes development, complications, and therapeutic response. While not yet ready for clinical translation, metabolomics is a powerful and promising precision medicine tool.

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