Evidence map›Paper›PMID 38724219›Full record

ArticleGut2024

Landscape of the gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health.

Yuanqing Fu, Wanglong Gou, Ping Wu, Yuwei Lai, Xinxiu Liang, Ke Zhang, Menglei Shuai, Jun Tang, Zelei Miao, Jieteng Chen and 8 more

Abstract read
In one paragraph

Article in Gut, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  14. Dietary Supplementation with Protocatechuic Acid and a ComplexAnimals : an open access journal from MDPI · 2025
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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

18 authors.

Yuanqing Fu *Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.ORCID 0000-0002-3955-9376
Wanglong Gou *Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
Ping Wu *Department 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.
Yuwei Lai *Department 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.
Xinxiu LiangWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Ke ZhangWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Menglei ShuaiWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Jun TangWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Zelei MiaoWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Jieteng ChenWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Jiaying YuanDepartment of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, China.
Bin ZhaoAntenatal Care Clinics, Shuangliu Maternal and Child Health Hospital, Chengdu, China.
Yunhaonan YangSection of Epidemiology and Population Health & Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, China.
Xiaojuan LiuDepartment of Laboratory Medicine, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, China.
Yayi HuDepartment of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, China.
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 zhengjusheng@westlake.edu.cn pxiongfei@scu.edu.cn panan@hust.edu.cn.
Xiong-Fei PanSection of Epidemiology and Population Health & Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, China zhengjusheng@westlake.edu.cn pxiongfei@scu.edu.cn panan@hust.edu.cn.
Ju-Sheng ZhengAffiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China zhengjusheng@westlake.edu.cn pxiongfei@scu.edu.cn panan@hust.edu.cn.ORCID 0000-0001-6560-4890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe remodelling of gut mycobiome (ie, fungi) during pregnancy and its potential influence on host metabolism and pregnancy health remains largely unexplored. Here, we aim to examine the characteristics of gut fungi in pregnant women, and reveal the associations between gut mycobiome, host metabolome and pregnancy health.

designBased on a prospective birth cohort in central China (2017 to 2020): Tongji-Huaxi-Shuangliu Birth Cohort, we included 4800 participants who had available ITS2 sequencing data, dietary information and clinical records during their pregnancy. Additionally, we established a subcohort of 1059 participants, which included 514 women who gave birth to preterm, low birthweight or macrosomia infants, as well as 545 randomly selected controls. In this subcohort, a total of 750, 748 and 709 participants had ITS2 sequencing data, 16S sequencing data and serum metabolome data available, respectively, across all trimesters.

resultsThe composition of gut fungi changes dramatically from early to late pregnancy, exhibiting a greater degree of variability and individuality compared with changes observed in gut bacteria. The multiomics data provide a landscape of the networks among gut mycobiome, biological functionality, serum metabolites and pregnancy health, pinpointing the link between

conclusionThis study provides a landscape of gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health, which lays the foundation of the future gut mycobiome investigation for healthy pregnancy.

Indexed as

Gastrointestinal MicrobiomeMycobiomeAdultChinaFemaleFungiHumansInfant, NewbornMetabolomePregnancyProspective StudiesINTESTINAL MICROBIOLOGY

Identifiers

PMID38724219
PMCPMC11287620

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Registered trials

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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.