# Metabolomic signatures in adults with metabolic syndrome indicate preclinical disruptions in pathways associated with high-density lipoprotein cholesterol, sugar alcohols

## TL;DR

The study identifies specific metabolites linked to metabolic syndrome and preclinical signs of diabetes and heart disease, offering potential biomarkers for early risk detection.

## Contribution

Novel associations between metabolites like alpha-tocopherol and sugar alcohols with preclinical metabolic disruptions in diabetes and cardiovascular risk.

## Key findings

- 42 metabolites were significantly associated with high-density lipoprotein cholesterol (HDL), indicating preclinical pathway disruptions.
- Sugar-derived metabolites like xylose and threitol were linked to age and glucose measures, suggesting early metabolic perturbations.
- Branched-chain amino acids and alpha-tocopherol showed significant associations with BMI, lipid profiles, and diabetes risk markers.

## Abstract

Metabolic syndrome is a pressing public health issue and risk factor for the development of type 2 diabetes (T2D) and cardiovascular disease (CVD), yet clinical practice is lacking in biomarkers that represent pre-clinical perturbations of the heterogenous subtypes of risk. This study aimed to characterize the baseline metabolome in relation to known clinical characteristics of risk in a sample of obese adults.

Untargeted metabolome data from N = 126 plasma samples with baseline data from a previously completed study including obese adults with metabolic syndrome. Metabolites were acquired using validated liquid chromatography mass spectrometry methods with 15–25 internal standards quantified by peak heights. Pearson’s correlations were used to determine relationships between baseline metabolites, sample characteristics (e.g., age, body mass index (BMI)), and atherosclerotic clinical characteristics (e.g., high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), triglycerides), adjusting for multiple comparisons using the Benjamini–Hochberg False Discovery Rate (FDR) method. Differences in metabolite levels between clinical classifications of dysglycemia (e.g., normal, prediabetes, diabetes) at baseline were assessed using ANOVA and adjusted for multiple comparisons and adjusted for covariates.

The sample consisted primarily of female (74%) participants, predominantly white (70%), with an average age of 56 years. After FDR adjustment, two baseline metabolites were significantly associated with age (xylose, threitol), two with BMI (shikimic acid, propane-1,3-diol), one with LDL (tocopherol-alpha), and 42 with HDL cholesterol. Three metabolites were significantly associated with fasting blood glucose (FBG) levels at baseline (glucose, gluconic acid lactone, pelargonic acid).

This study identified novel metabolite associations with known markers of T2D and CVD risk. Specific metabolites, such as alpha-tocopherol, branched-chain amino acids (BCAAs), and sugar-derived metabolites like mannose and xylose, were significantly associated with age, BMI, lipid profiles, and glucose measures. Although most sample participants had normal HDL cholesterol at baseline, 42 metabolites including branched chain amino acids were significantly associated with HDL, suggesting pre-clinical perturbations in biological pathways associated with both diabetes and cardiovascular comorbidities. Metabolomic signatures specific to prediabetes and metabolic syndrome can enhance risk stratification and enable targeted prevention strategies for T2D. Longitudinal studies are needed to understand how these associations change over time in at-risk individuals compared with controls.

The online version contains supplementary material available at 10.1186/s40842-025-00223-x.