Key result
Metabolomic profiling in prediabetes identifies three distinct subgroups with varying 20-year T2D risk.
Why the study?
Patients with T2D can be clustered into distinct etiologic subgroups, but it is not clear whether individuals with prediabetes can also be clustered into subgroups.
Do metabolome-based subgroups of individuals with prediabetes have different likelihoods of developing Type 2 Diabetes?
Cohort (n=5,567)
Yes
Do metabolome-based subgroups of individuals with prediabetes have different likelihoods of developing Type 2 Diabetes?
p-value: p=0.03
Metabolomic profiling can identify distinct subgroups of individuals with prediabetes who have differing long-term risks of developing type 2 diabetes, independent of standard glycemic markers.
Metabolomic subgroups stratify T2D risk beyond glycemia; hypothesis-generating and requires validation before clinical use.
Introduction and Objective: Patients with T2D can be clustered into distinct etiologic subgroups, but it is not clear if the same is true for those with prediabetes (preDM). As metabolites mark the onset of T2D prior to clinical thresholds, we clustered individuals with preDM by preDM-related metabolites and examined subgroups for long-term T2D risk. Methods: Data were included from N=5567 participants, N=2003 of whom had preDM (100≤fasting glucose<126 mg/dL). Machine learning was used to select baseline metabolites that distinguished preDM from normoglycemia. Those with preDM were clustered into subgroups by their values of the selected compounds, and chi-squared tests quantified baseline subgroup differences. Cox-proportional hazards models, controlling for demographics, and fasting glucose and insulin, examined subgroup differences in T2D risk over 20 years follow-up. Results: N=31 metabolites discriminated preDM from normoglycemia (AUC=0.96;fig1A). Clustering individuals by these compounds identified 3 subgroups (fig1B). Fasting glucose and insulin did not differ between subgroups (p<.001;fig1C), but the likelihood of developing T2D did (P=.03;fig1C &1D). Conclusion: Individuals with preDM represent discrete metabolome-based subgroups, informative for T2D progression. Future analyses will include validation in additional DEFINE-T2D cohorts. Disclosure A. Wood: Research Support; Current; Beef Checkoff. Consultant; Ended; Lundquist Institute for Biomedical Innovation. M.R. Rooney: None. I.R. Konigsberg: None. Z. Chen: None. A. Manning: None. R.E. Gerszten: None. L. Szczerbinski: Research Support; Current; Novo Nordisk. Consultant; Current; Eli Lilly and Company. M. Mi: None. M. Sevilla-Gonzalez: Research Support; Current; Novo Nordisk. Q. Qi: None. Q. Pan: None. S.K. Das: None. J.I. Rotter: None. Funding Veterans Affairs, United States Department of Agriculture (USDA-3092-10700-068-006-N), and National Institutes of Health (1U01DK140757; HL181500; DK127073; U01DK140761; U01DK140738; U01DK140778)
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WOOD et al. (2026) conducted a cohort in Prediabetes (n=5,567). Metabolome-based subgroups vs. Other prediabetes subgroups was evaluated on Development of type 2 diabetes (T2D) (p=0.03). Metabolomic profiling of individuals with prediabetes identified three distinct subgroups with significantly different likelihoods of developing type 2 diabetes over 20 years (P=0.03).
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