PuSH - Publikationsserver des Helmholtz Zentrums München: Integrative metabolomics of targeted and non-targeted analyses in T2D progression.

Informationen

Hinweise zu Qualitätskriterien von Zeitschriften

Open-Access-Richtlinie der Helmholtz-Gemeinschaft 2016

CC Licencences

Metriken für Publikationen

Navigation

Startseite

English

Recherche

Erweiterte Suche

Durchblättern nach ...

... HMGU-Autoren/Konsortien

... Organisationsstruktur

... Zeitschriften

... Publikationstypen

... Forschungsdaten

... Arbeitsgruppen

... Erscheinungsjahr

Publikationen im Überblick

Statistik

HGF Fortschrittsbericht

OA Publikationen

Eintragen

Neue Publikation eintragen

Neue Publikation holen aus...

...EVA

Fehlende Publikation melden

Highlights

Suche

Hilfe & Kontakt

Ansprechpartner

Hilfe

Datenschutz

Helmholtz Open Science

Bibliometrische Indikatoren

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

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

Forschungsdaten

DOI

PMC

	Open Access Green

Abstract
Metriken
Zusatzinfos

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.

Impact Factor

Scopus SNIP

Altmetric

16.600

0.000