Metabolomics Signature in Prediabetes and Diabetes: Insights From Tandem Mass Spectrometry Analysis

TL;DR

This study identifies specific metabolites that differ between normal, prediabetic, and diabetic individuals, which could help in early diabetes detection and management.

Contribution

The study provides a metabolomics signature for prediabetes and diabetes, including differences between well- and poorly-controlled diabetes.

Findings

Amino acids like glycine, serine, and proline differ between prediabetes and normal groups.

Acylcarnitines such as C16 and C18 show significant differences in diabetes compared to normal groups.

Glucose and HbA1c levels correlate with specific metabolites in both prediabetes and diabetes groups.

Abstract

This study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC).

In this study, 1102 individuals were included, and 50 metabolites were analysed using tandem mass spectrometry. The diabetes diagnosis and treatment standards of the American Diabetes Association (ADA) were used to classify patients.

The nearest neighbour method was used to match controls and cases in each group on the basis of age, sex and BMI. Factor analysis was used to reduce the number of variables and find influential underlying factors. Finally, Pearson's correlation coefficient was used to check the correlation between both glucose and HbAc1 as independent factors with binary classes.

Amino acids such as glycine, serine and proline, and acylcarnitines (AcylCs) such as C16 and C18 showed significant differences between the prediabetes and normal groups. Additionally, several metabolites, including C0, C5, C8 and C16, showed significant differences between the diabetes and normal groups. Moreover, the study found that several metabolites significantly differed between the GGC and PGC diabetes groups, such as C2, C6, C10, C16 and C18. The correlation analysis revealed that glucose and HbA1c levels significantly correlated with several metabolites, including glycine, serine and C16, in both the prediabetes and diabetes groups. Additionally, the correlation analysis showed that HbA1c significantly correlated with several metabolites, such as C2, C5 and C18, in the controlled and uncontrolled diabetes groups.

These findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.

This study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC). These findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.

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