Evidence map›Paper›PMID 41776572›Full record

ArticleDiabetology & metabolic syndrome2026

Association between gestational diabetes mellitus and long-term all-cause and cause-specific mortality risks: a prospective cohort study based on metabolomics.

Yuyu Chen, Mingjian Huang, Lei Zheng, Minjia Wu, Shaoni Huang, Sijia Dai, Jiangyan Hao, Feiling Liu, Xiaowei He, Guangfeng Long and 1 more

Abstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 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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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

11 authors.

Yuyu Chen *Department of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Mingjian Huang *The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China.
Lei Zheng *Department of Neurosurgery, Children's Hospital of Nanjing Medical University, Nanjing, China.
Minjia WuDepartment of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Shaoni HuangDepartment of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Sijia DaiDepartment of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Jiangyan HaoDepartment of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Feiling LiuDepartment of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Xiaowei HeEditorial Office of Journal of Guangxi Medical University, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China.
Guangfeng LongDepartment of Clinical Laboratory, Children's Hospital of Nanjing Medical University, 72 Guangzhou Road, Nanjing, 210008, China. guangfenglong@njmu.edu.cn.
Cheng XuDepartment of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China. chengxunjmu@163.com.

Funding

Nanjing medical key science and technology development project ZKX24040
6 · The paper itself

Abstract

backgroundGestational diabetes mellitus (GDM) is one of the most common metabolic disorders during pregnancy. Women with GDM face an increased risk of type 2 diabetes and cardiovascular disease (CVD) after childbirth, even after accounting for obesity, lifestyle, and socioeconomic factors. However, whether GDM raises long-term all-cause and cause-specific mortality remains uncertain. This study aimed to clarify the long-term links between GDM-related metabolic profiles and mortality using nuclear magnetic resonance (NMR) metabolomics.

methodsUsing data from the UK Biobank (UKB) prospective female cohort, we combined GDM history with NMR metabolomic data to examine associations between GDM-related metabolic signature and all-cause and cause-specific mortality. Cox proportional hazards models were employed to estimate risk, and the added predictive value of these metabolic profiles beyond traditional risk factors was assessed. Sensitivity analyses verified the robustness of the results.

resultsOver a median follow-up of 13.5 years, each 1-SD increase in the GDM-related metabolic signature was associated with higher risks of all-cause (hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.15–1.19), cardiovascular (1.29, 1.24–1.34), cancer (1.10, 1.07–1.12) and respiratory mortality (1.17, 1.09–1.25). The signature combined lower glutamine, glycine, and histidine, more small, dense, low-density lipoprotein particles, a lower linoleic acid ratio, and disturbed glycolytic intermediates, consistent with insulin resistance, chronic inflammation, and impaired energy metabolism. These associations were robust in sensitivity analyses, and adding the metabolic signature to conventional models improved risk reclassification for cardiovascular mortality (Net Reclassification Improvement [NRI] = 0.24, P < 0.001), with modest changes in time-dependent AUC.

conclusionsThis study provides observational evidence that a GDM-related metabolic signature is associated with increased long-term all-cause and cause-specific mortality in women with a history of GDM. Women with GDM exhibit a systemic metabolic profile characterized by insulin resistance and disruptions in glucose, amino acid, and lipid metabolism, which may explain the association between GDM and mortality. These results shed light on GDM-related metabolic pathways and support metabolomics-based approaches for risk assessment and targeted intervention, underscoring the importance of long-term systemic risk monitoring beyond controlling blood sugar levels.

Indexed as

All-cause mortalityCardiovascular diseaseGestational diabetes mellitusMetabolic risk profileUK Biobank

Identifiers

PMID41776572
PMCPMC13063902

What Socratic holds

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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 Socratic graph.