ArticleDiabetes care2026
Integrative Metabolomics of Targeted and Nontargeted Analyses in T2D Progression.
Article in Diabetes care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Metformin Treatment Potentially Modifies Genetically Driven Metabolite-HbA1c Associations: A Gene-Environment Interaction Mendelian Randomization Study.Pharmaceuticals (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
objectiveThis study aimed to identify metabolites characterizing the progression from normal glucose metabolism (NORM) to prediabetes (PreT2D) and type 2 diabetes (T2D), focusing on stage-specific metabolic shifts (early: NORM to PreT2D; late: PreT2D to T2D) and mechanistic relevance. RESEARCH DESIGN AND
methodsWe analyzed 8,240 observations from the KORA cohort, profiling 104 targeted and 312 nontargeted metabolites across three time points: baseline (S4) and follow-ups (F4 and FF4) spanning 14 years. Trajectory analyses of 1,050 individuals identified 211 incident PreT2D and 112 incident T2D cases. Linear mixed-effects models (basic: adjusted for age, sex, BMI, lifestyle; sensitivity: additionally adjusted for glycemic factors like fasting glucose, and cardiovascular factors such as systolic blood pressure (BP) were used to evaluate metabolic differences across glycemic states. Mediation and Mendelian randomization (MR) analyses examined mechanistic and causal relationships.
resultsWe identified 140 Bonferroni-significant metabolites (45 targeted, 109 nontargeted, 14 overlapping), including 68 early-stage metabolites (significant in PreT2D/T2D vs. NORM), primarily energy metabolism markers such as fatty acid oxidation metabolites (e.g., 37 lipids) and tricarboxylic acid cycle metabolites (e.g., citrate). Twenty late-stage metabolites (significant in T2D vs. PreT2D/NORM) included amino acids like branched-chain amino acids (BCAAs) and γ-glutamyl derivatives. Fewer significant associations were observed in incident cases. Sensitivity models validated 50% of early-stage but not late-stage metabolites. Fasting glucose mediated 35.1% of the γ-glutamyl-valine-T2D association, while MR analysis found no causal roles for C2, BCAAs, or γ-glutamyl-valine.
conclusionsEnergy metabolism shifts occur early, while amino acid alterations emerge later stages. These stage-specific signatures may guide diabetes prevention strategies.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.