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Infant to Elder: Microbes Across the Lifespan (Poster Theater Flash Session 2)

(PTFS02-01-25) Integrated Gut Microbiota and Lipidome Profiles in Early Pregnancy for Predicting Gestational Diabetes Mellitus Risk

Saturday, May 31, 2025
2:00 PM - 2:04 PM ET
Location: South Hall B (The Hub) - Poster Theater / Poster Board Number PT-1

    Presenting Author(s)

  • CH

    Chang He (she/her/hers)

    n/a
    Fudan University
    Shanghai, Shanghai, China (People's Republic)

    Disclosure(s): No relevant financial relationship(s) with ineligible companies to disclose.

    • Co-Author(s)

  • ZS

    Zhonghan Sun

    Fudan University, China (People's Republic)

  • PW

    Ping Wu

    Huazhong University of Science and Technology, China (People's Republic)

  • JY

    Jiaying Yuan

    Shuangliu Maternal and Child Health Hospital, China (People's Republic)

  • YP

    Yanni Pu

    Fudan University, China (People's Republic)

  • XZ

    Xiaofeng Zhou

    Fudan University, China (People's Republic)

  • ZM

    Zhendong Mei

    Brigham and Women's Hospital and Harvard Medical School, United States

  • HS

    Huiling Song

    Fudan University, School of Life Sciences and Human Phenome Institute, China (People's Republic)

  • YW

    Yetong Wang

    Fudan University, China (People's Republic)

  • HY

    Haiyan Yue

    Fudan University, China (People's Republic)

  • YF

    Yuanqing Fu, n/a

    Research associate professor
    Westlake University
    Hangzhou, Zhejiang, China (People's Republic)

  • Jusheng Zheng, PHD (he/him/his)

    Principal Investigator
    Westlake University
    Hangzhou, Zhejiang, China (People's Republic)

  • AP

    An Pan, PhD

    Professor
    Huazhong University of Science and Technology
    Wuhan, Hubei, China (People's Republic)

  • DC

    Da Chen

    Jinan University, China (People's Republic)

  • XP

    Xiong-Fei Pan

    Huazhong University of Science and Technology, China (People's Republic)

  • YZ

    Yan Zheng

    Fudan University, China (People's Republic)

Objectives: Gestational diabetes mellitus (GDM) is a common pregnancy complication with adverse effects on both mothers and their offspring. This study aims to investigate the complex relationship between gut microbiome and lipidome, which contribute to metabolic dysregulation during pregnancy, potentially leading to improving the prediction and prevention of GDM.

Methods: This prospective study included 784 pregnant women, including 222 with GDM. We collected baseline characteristics and conducted gut metagenomic measurements and plasma lipidome profiling in the first trimester. The associations between microbial features, lipid metabolic features, and GDM status and related metrics were estimated by linear models adjusting for potential covariates. Bidirectional mediation analysis was applied to explore the role of lipids in the association between microbiome and the risk of GDM. Random forest classifiers were constructed to explore the performance of different omics features in predicting the risk of GDM. The additive interaction effects of gut microbiome and plasma lipidome were estimated by adding an interaction term into logistic regression model using omics risk score.

Results: At early pregnancy, decreased gut microbial diversity and altered composition were observed among women who later developed GDM. 26 microbial species associated with GDM risk were identified, with eight species, such as Ruminococcus bicirculans and Intestinibacter bartlettii, successfully replicated in independent external populations of GDM or type 2 diabetes. Enhanced microbial capacity for lipid biosynthesis was linked to increased GDM risk, with specific lipid metabolites mediating the microbiota-GDM relationship. Importantly, integrating gut microbiome and plasma lipidome data substantially improved GDM risk prediction beyond traditional factors, with high microbiome and lipidome scores in combination associated with a 19-fold increase in GDM risk.

Conclusions: Our findings underscore the complex interplay between the gut microbiome, plasma lipidome, and GDM risk. The gut microbiome and plasma lipidome provide significant predictions for GDM, suggesting a potential for early detection and personalized intervention strategies.

Funding Sources: Funded by NKRDPC, NSFC, SMSTP, SPNSF, and FRFCU.