Evidence map›Paper›PMID 42577959›Full record

ArticleiMeta2026

A gut microbiome-lipid axis in early pregnancy is associated with metabolic dysregulation and diabetes risk.

Zhonghan Sun, Chang He, Xiaonan Ma, Ping Wu, Tianlei Wang, Jiaying Yuan, Yanni Pu, Xiaofeng Zhou, Zhendong Mei, Huiling Song and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Zhonghan SunState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Shanghai Institute of Infectious Disease and Biosecurity, Zhongshan Hospital Shanghai China.ORCID https://orcid.org/0000-0003-4171-9794
Chang HeState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.
Xiaonan MaState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.
Ping WuDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College Huazhong University of Science and Technology Wuhan China.
Tianlei WangLaboratory of Epidemiology and Population Health & Children's Medicine Key Laboratory of Sichuan Province, West China Institute of Women and Children's Health West China Second University Hospital, Sichuan University Chengdu China.
Jiaying YuanDepartment of Science and Education Shuangliu Maternal and Child Health Hospital Chengdu China.
Yanni PuState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.
Xiaofeng ZhouState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.
Zhendong MeiDepartment of Medicine Brigham and Women's Hospital and Harvard Medical School Boston USA.
Huiling SongState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.
Yetong WangState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.
Haiyan YueState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.
Yuanqing FuAffiliated Hangzhou First People's Hospital, School of Medicine Westlake University Hangzhou China.
Jusheng ZhengAffiliated Hangzhou First People's Hospital, School of Medicine Westlake University Hangzhou China.ORCID https://orcid.org/0000-0001-6560-4890
An PanDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College Huazhong University of Science and Technology Wuhan China.
Da ChenCollege of Environment and Climate, Guangdong Key Laboratory of Environmental Pollution and Health Jinan University Guangzhou China.ORCID https://orcid.org/0009-0008-5302-9823
Shangyu HongState Key Laboratory of Genetics and Development of Complex Phenotypes, Department of Endocrinology, Shanghai Pudong Hospital School of Life Sciences, Fudan University Pudong Medical Center, Fudan University Shanghai China.ORCID https://orcid.org/0000-0001-6144-5618
Xiong-Fei PanLaboratory of Epidemiology and Population Health & Children's Medicine Key Laboratory of Sichuan Province, West China Institute of Women and Children's Health West China Second University Hospital, Sichuan University Chengdu China.ORCID https://orcid.org/0000-0002-9350-9230
Yan ZhengState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences Human Phenome Institute, Zhongshan Hospital Shanghai China.ORCID https://orcid.org/0000-0003-1129-3147

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gestational diabetes mellitus (GDM) reflects metabolic dysregulation that becomes clinically apparent during pregnancy and shares key pathophysiological features with broader forms of diabetes. Gut microbiome-host metabolic interactions may contribute to this process, yet their role in early pregnancy remains incompletely understood. In this prospective nested case-control study within the Tongji-Huaxi-Shuangliu Birth Cohort, 784 pregnant women, including 222 who developed GDM, underwent first-trimester gut metagenomic and plasma lipidomic profiling. Cross-omics analyses were performed to identify microbiome-lipid associations and potential mediation patterns. Women who later developed GDM showed reduced gut microbial diversity and altered microbial profiles in early pregnancy. We identified 26 microbial species associated with GDM risk, with seven species, including

Indexed as

birth cohortgestational diabetes mellitusgut microbiomelipid/glucose metabolismlipidome

Identifiers

PMID42577959
PMCPMC13455838

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.