{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T08:22:52Z","timestamp":1772180572481,"version":"3.50.1"},"reference-count":78,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T00:00:00Z","timestamp":1772150400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020772","name":"Basic Scientific Foundation of Guangxi Institute of Public Welfare Scientific Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100020772","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cell. Infect. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Exposure to particulate matter pollution with aerodynamic diameters &amp;lt; 2.5 \u03bcm (PM\n                      <jats:sub>2.5<\/jats:sub>\n                      ) has been linked to gestational diabetes mellitus (GDM) and gut microbiota dysbiosis. However, few studies have illustrated the associations among PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure, gut microbiota, blood metabolites, circular RNAs (circRNAs) and GDM risk. This study aimed to explore the moderating effects of the gut microbiota on the association between PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure and GDM, and to analyze the interaction network of PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure, gut microbiota, blood metabolites and circRNAs.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Participants (n = 1,248) were selected from the Pregnancy Metabolic Disease and Adverse Pregnancy Outcome (PMDAPO) cohort in Guangzhou, China. Demographic information, blood and fecal samples were collected from the participants. The fecal microbial composition and relative abundance were characterized using 16S rRNA gene sequencing, while blood differential metabolites and circRNAs of pregnant women with GDM were assessed using non-targeted metabolomics and RT-qPCR, respectively. Exposure levels of air pollutants were assessed using data from the nearest monitoring station. Spearman correlation and regression models were conducted to estimate the associations among PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure, gut microbiota, blood metabolites, circRNAs and GDM.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Elevated PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure levels were significantly associated with an increased risk of GDM, impaired glucose homeostasis and gut microbiota dysbiosis.\n                      <jats:italic>Solobacterium<\/jats:italic>\n                      and\n                      <jats:italic>Escherichia_Shigella<\/jats:italic>\n                      showed a positive effect modification on the association between PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure and fasting blood glucose, while\n                      <jats:italic>Fusicatenibacter<\/jats:italic>\n                      ,\n                      <jats:italic>Ruminococcaceae_UBA1819<\/jats:italic>\n                      ,\n                      <jats:italic>Raoultibacter<\/jats:italic>\n                      ,\n                      <jats:italic>Anaerofustis<\/jats:italic>\n                      and\n                      <jats:italic>Phascolarctobacterium<\/jats:italic>\n                      showed a negative effect modification on the association between PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure and 2-h OGTT glucose. GDM-associated gut microbiota, including\n                      <jats:italic>Catabacter<\/jats:italic>\n                      ,\n                      <jats:italic>Angelakisella<\/jats:italic>\n                      ,\n                      <jats:italic>Romboutsia<\/jats:italic>\n                      and\n                      <jats:italic>Fusicatenibacter<\/jats:italic>\n                      , were associated with both GDM-associated metabolites (such as sphinganine-1-phosphate, sphingomyelin) and GDM-associated circRNAs (such as hsa_circ_0006732 and hsa_circ_0001439), which were involved in glycerophospholipid metabolism, sphingolipid metabolism and insulin signaling pathway.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      The gut microbiota may moderate the associations between PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure and blood glucose levels, and both PM\n                      <jats:sub>2.5<\/jats:sub>\n                      exposure and gut microbiota may be related to GDM, potentially involving pathways such as glycerophospholipid metabolism, sphingolipid metabolism and the insulin signaling pathway. However, lifestyle factors (diet and physical activity) and residential mobility were not measured, and the fecal microbiota was assessed at a single time point in mid-pregnancy. Thus, these limitations may contribute to residual confounding, exposure misclassification, and limited causal inference.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcimb.2026.1749504","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:52:27Z","timestamp":1772175147000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Longitudinal associations between PM2.5 with gestational diabetes mellitus mediated by gut microbiome and potential mechanism: based on a prospective pregnant women cohort in China"],"prefix":"10.3389","volume":"16","author":[{"given":"Shanshan","family":"Mei","sequence":"first","affiliation":[{"name":"Department of Obstetrics, Guangzhou Women and Children\u2019s Medical Centre, Guangzhou Medical University","place":["Guangzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyi","family":"Ye","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Health Statistics, School of Public Health, Guangzhou Medical University","place":["Guangzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaoyao","family":"Teng","sequence":"additional","affiliation":[{"name":"Department of Microbiological Laboratory, Chongqing Jiulongpo District Center for Disease Control and Prevention","place":["Chongqing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yisheng","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Disease Prevention and Control, Dachong Community Health Service Center","place":["Zhongshan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Long","sequence":"additional","affiliation":[{"name":"Liuzhou Hospital, Guangzhou Women and Children\u2019s Medical Center, Guangzhou Medical University","place":["Liuzhou, China"]},{"name":"Department of Laboratory, Guangzhou Women and Children\u2019s Medical Centre, Guangzhou Medical University","place":["Guangzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueqin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Laboratory, Guangzhou Women and Children\u2019s Medical Centre, Guangzhou Medical University","place":["Guangzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueqing","family":"Cen","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Health Statistics, School of Public Health, Guangzhou Medical University","place":["Guangzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics, Guangzhou Women and Children\u2019s Medical Centre, Guangzhou Medical University","place":["Guangzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Health Statistics, School of Public Health, Guangzhou Medical University","place":["Guangzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,2,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1789","DOI":"10.2337\/db16-1416","article-title":"Longitudinal associations between ambient air pollution with insulin sensitivity, \u03b2-cell function, and adiposity in los angeles latino children","volume":"66","author":"Alderete","year":"2017","journal-title":"Diabetes."},{"key":"B2","doi-asserted-by":"publisher","first-page":"S17","DOI":"10.2337\/dc22-S002","article-title":"2. 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