Evidence map›Paper›PMID 41933349›Full record

ArticleCardiovascular diabetology2026

Novel amino acid and fatty acid signatures linked to type 2 diabetes risk after gestational diabetes mellitus.

Chenyu Qiu, Wu Chen, Ni Kang, Jiawen Liao, Zhenchun Yang, ViLinh Tran, Dean P Jones, Frank D Gilliland, Thomas A Buchanan, Anny H Xiang and 1 more

Abstract read
In one paragraph

Article in Cardiovascular diabetology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Chenyu QiuDepartment of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA.
Wu ChenDepartment of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA.
Ni KangDepartment of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA.
Jiawen LiaoDepartment of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA.
Zhenchun YangDepartment of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA.
ViLinh TranDepartment of Medicine, Emory University School of Medicine, Atlanta, GA, USA.
Dean P JonesDepartment of Medicine, Emory University School of Medicine, Atlanta, GA, USA.
Frank D GillilandDepartment of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA.
Thomas A BuchananDepartment of Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA.
Anny H XiangDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Zhanghua ChenDepartment of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. zhanghuc@usc.edu.

Funding

Translational Research Support CoreP30ES007048 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ROB S MCCONNELL · 1996 to 2026
$46.4M
Vector and Transgenic Mouse CoreP30DK017047 · NIDDK · UNIVERSITY OF WASHINGTON · PI Sakeneh Zraika · 1986 to 2026
$41.4M
PATHOGENESIS OF TYPE 2 DIABETES IN LATINO WOMENR01DK046374 · NIDDK · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BUCHANAN, THOMAS A · 1993 to 2006
$2.6M
The Long-term Influence of Persistent Organic Pollutants Exposure During and After Pregnancy on Metabolic Decline in Women After Pregnancies Complicated by Gestational DiabetesR01ES032247 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHEN, ZHANGHUA · 2020 to 2023
$1.9M
Metabolomic Signatures Linking Air Pollution, Obesity and DiabetesR00ES027870 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHEN, ZHANGHUA · 2019 to 2021
$747k
NIDDK NIH HHS P30 DK017047NIDDK NIH HHS R01 DK046374NIDDK NIH HHS R01DK046374NIEHS NIH HHS P30 ES007048NIEHS NIH HHS R00 ES027870NIEHS NIH HHS R01 ES032247NIEHS NIH HHS R01ES032247
6 · The paper itself

Abstract

backgroundWomen with gestational diabetes mellitus (GDM) history carry increased risks of type 2 diabetes compared to women without GDM history. This study aims to identify the dysregulated metabolic pathways and metabolite signatures during pregnancy that predict the risk of developing type 2 diabetes post-GDM.

methods101 Hispanic women with GDM diagnoses were followed from the 3rd trimester of index pregnancy to 12 years post-delivery. Oral and intravenous glucose tolerance tests were performed every 12–15 months until development of type 2 diabetes, lost-to-follow-up or the end of the study. Type 2 diabetes incidence was identified as a fasting glucose concentration ≥ 126 mg/dL or 2-hour glucose ≥ 200 mg/dL. In this study, archived plasma samples from the 3rd trimester of pregnancy were assayed for untargeted metabolomics using mass-spectrometry to explore metabolic signatures of diabetes development. Metabolome-wide association analysis was performed to assess the association of metabolomic features with type 2 diabetes incidence using Cox proportional hazards models adjusted for age at delivery, along with post-delivery body mass index, additional pregnancy, and self-reported daily calorie intake at each follow-up visit as time-varying covariates, followed by Mummichog pathway enrichment analysis.

resultsAmong the 101 women, 52 developed diabetes in 12 years. Metabolomics analysis suggested that nine amino acid and fatty acid metabolic pathways were associated with the risk of developing type 2 diabetes in GDM women (p-values of pathway enrichment tests < 0.05). Higher plasma levels of agmatine, hydroxyproline/5-aminolevulinate, along with lower plasma levels of threonine/homoserine, 25-hydroxycholesterol, FA12:0 (laurate), FA20:0 (arachidic acid), FA20:3 (homolinoleic acid), FA18:3 n-3 or n-6 (linolenic acid) in 3rd trimester were associated with a 12%–60% higher hazard of developing type 2 diabetes during the up to 12 years’ post-delivery period (all p-values < 0.05).

conclusionLevels of amino acid and fatty acid metabolomic signatures in pregnancy may help identify individuals at an elevated risk of developing type 2 diabetes after GDM-complicated pregnancy, highlighting opportunities for earlier, more targeted prevention that require confirmation in larger, prospective studies.

Indexed as

Amino AcidsDiabetes, GestationalDiabetes Mellitus, Type 2Fatty AcidsAdultBiomarkersBlood GlucoseFemaleHumansIncidenceMetabolomicsPregnancyPregnancy Trimester, ThirdProspective StudiesRisk AssessmentRisk FactorsAmino AcidsBiomarkersBlood GlucoseFatty AcidsGestational diabetes mellitusMetabolic disordersMetabolomicsType 2 diabetes

Identifiers

PMID41933349
PMCPMC13072498

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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 OpenQuestion graph.