Gestational diabetes is driven by microbiota-induced inflammation months before diagnosis

Yishay Pinto, Sigal Frishman, Sondra Turjeman, Adi Eshel, Meital Nuriel-Ohayon, Oshrit Shrossel, Oren Ziv, William Walters, Julie Parsonnet, Catherine Ley, Elizabeth L. Johnson, Krithika Kumar, Ron Schweitzer, Soliman Khatib, Faiga Magzal, Efrat Muller, Snait Tamir, Kinneret Tenenbaum-Gavish, Samuli Rautava, Seppo SalminenErika Isolauri, Or Yariv, Yoav Peled, Eran Poran, Joseph Pardo, Rony Chen, Moshe Hod, Elhanan Borenstein, Ruth E. Ley, Betty Schwartz, Yoram Louzoun, Eran Hadar, Omry Koren*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


Objective Gestational diabetes mellitus (GDM) is a condition in which women without diabetes are diagnosed with glucose intolerance during pregnancy, typically in the second or third trimester. Early diagnosis, along with a better understanding of its pathophysiology during the first trimester of pregnancy, may be effective in reducing incidence and associated short-term and long-term morbidities. Design We comprehensively profiled the gut microbiome, metabolome, inflammatory cytokines, nutrition and clinical records of 394 women during the first trimester of pregnancy, before GDM diagnosis. We then built a model that can predict GDM onset weeks before it is typically diagnosed. Further, we demonstrated the role of the microbiome in disease using faecal microbiota transplant (FMT) of first trimester samples from pregnant women across three unique cohorts. Results We found elevated levels of proinflammatory cytokines in women who later developed GDM, decreased faecal short-chain fatty acids and altered microbiome. We next confirmed that differences in GDM-associated microbial composition during the first trimester drove inflammation and insulin resistance more than 10 weeks prior to GDM diagnosis using FMT experiments. Following these observations, we used a machine learning approach to predict GDM based on first trimester clinical, microbial and inflammatory markers with high accuracy. Conclusion GDM onset can be identified in the first trimester of pregnancy, earlier than currently accepted. Furthermore, the gut microbiome appears to play a role in inflammation-induced GDM pathogenesis, with interleukin-6 as a potential contributor to pathogenesis. Potential GDM markers, including microbiota, can serve as targets for early diagnostics and therapeutic intervention leading to prevention.

Original languageEnglish
Pages (from-to)918-928
Number of pages11
Issue number5
StatePublished - May 2023


FundersFunder number
Israeli Ministry of Economy62046
Israeli Ministry of Innovation, Science & Technology3-15521
European Research Council101001355
European Research Council




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