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Ge, J. ; Han, S. ; Shi, M. ; Harada, M. ; Yu, S. ; Zheng, J. ; Prehn, C. ; Adamski, J. ; Kastenmüller, G. ; Schlesinger, S.* ; Koenig, W.* ; Linkohr, B. ; Thorand, B. ; Suhre, K.* ; Gieger, C. ; Peters, A. ; Wang-Sattler, R.

Integrative metabolomics of targeted and non-targeted analyses in T2D progression.

Diabetes Care:dc251707 (2025)
Postprint Research data DOI PMC
Open Access Green
OBJECTIVE: This 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 METHODS: We analyzed 8,240 observations from the KORA cohort, profiling 104 targeted and 312 non-targeted 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. RESULTS: We identified 140 Bonferroni-significant metabolites (45 targeted, 109 non-targeted, 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 TCA cycle metabolites (e.g., citrate). Twenty late-stage metabolites (significant in T2D vs. PreT2D/NORM) included amino acids like 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. CONCLUSIONS: Energy metabolism shifts occur early, while amino acid alterations emerge later stages. These stage-specific signatures may guide diabetes prevention strategies.
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Publication type Article: Journal article
Document type Scientific Article
Language english
Publication Year 2025
HGF-reported in Year 2025
ISSN (print) / ISBN 0149-5992
e-ISSN 1935-5548
Journal Diabetes Care
Quellenangaben Volume: , Issue: , Pages: , Article Number: dc251707 Supplement: ,
Publisher American Diabetes Association
Publishing Place Alexandria, Va.
Reviewing status Peer reviewed
Institute(s) Institute of Translational Genomics (ITG)
CF Metabolomics & Proteomics (CF-MPC)
Institute of Experimental Genetics (IEG)
Institute of Computational Biology (ICB)
Institute of Epidemiology (EPI)
POF-Topic(s) 30205 - Bioengineering and Digital Health
30505 - New Technologies for Biomedical Discoveries
30201 - Metabolic Health
30202 - Environmental Health
Research field(s) Genetics and Epidemiology
Enabling and Novel Technologies
PSP Element(s) G-506700-001
A-630710-001
G-500600-001
G-503891-001
G-504000-006
G-504000-002
G-504091-004
G-504000-010
DOI 10.2337/dc25-1707
PubMed ID 41335123
Erfassungsdatum 2025-12-04
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