Preclinical atherosclerosis and prediabetes: a cross-sectional metabolic assessment in apparently healthy population.

Abstract

Introduction: Prediabetes and preclinical atherosclerosis are interrelated conditions contributing to cardiovascular risk, even in apparently healthy individuals. Metabolomics provides insights into the early metabolic alterations underpinning these diseases.

Objectives: This study aimed to investigate the shared and distinct metabolic signatures associated with prediabetes and preclinical atherosclerosis in a population with low to moderate cardiovascular risk, using a targeted metabolomic approach.

Methods: A cross-sectional analysis was performed on 447 participants (mean age 39.7 ± 9.6 years) from the Białystok PLUS cohort. Prediabetes was diagnosed based on HbA1c and OGTT criteria. Preclinical atherosclerosis was assessed by carotid ultrasound. Targeted metabolomics profiling encompassed 434 metabolites and 218 metabolite sums or ratios using HPLC-MS/MS. Statistical analyses included ANOVA, linear regression, correlation analysis, and metabolite set enrichment analysis (MSEA).

Results: Prediabetes was significantly associated with preclinical atherosclerosis (30.8% vs. 19.5%, p = 0.006). Prediabetes had a broader metabolic impact than atherosclerosis, particularly affecting amino acid and lipid metabolism. Glutamic acid, lactic acid, and L-alanine were strongly associated with prediabetes. Trimethylamine N-oxide (TMAO) was uniquely linked to both prediabetes and its interaction with atherosclerosis, suggesting a context-dependent metabolic response. Glutaminase activity emerged as a robust shared metabolic feature of both conditions. Pathway analyses revealed converging disturbances in glutathione and folate metabolism, mitochondrial function, and redox regulation.

Conclusions: Prediabetes is associated with more pronounced metabolic alterations than preclinical atherosclerosis. TMAO and glutaminase activity may represent key metabolic links between these conditions. These findings highlight the potential of metabolomics in identifying early biomarkers and mechanisms relevant to the prevention of cardiometabolic diseases.