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Updated: Feb 11, 2026

A Zebrafish Model of Diabetes Mellitus and Metabolic Memory
Published on: February 28, 2013
Early characterization of pregnancy glycemic traits in gestational diabetes mellitus by plasma cell-free mRNA and
Songchang Chen1, Yuwei Liu2,3, Tingyu Yang2,3
1Institute of Reproduction and Development, Shanghai Key Laboratory of Reproduction and Development, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China.
In recent years, the incidence of gestational diabetes mellitus (GDM) has been steadily increasing, posing risks to the long-term health of both mother and child. We aim to characterize blood glucose levels of pregnant women and predict the risk of GDM during early pregnancy through plasma cell-free mRNA and non-coding RNA (cfRNA). Here, we collected plasma samples from 108 pregnant women (54 with GDM and 54 controls) at around 16 weeks of gestation. Following high-throughput sequencing, we performed differentially abundant genes analysis and evaluated correlations between cfRNA profiles and blood glucose levels. Based on these findings, we developed a predictive model utilizing cf-mRNA and cf-lncRNA signatures. We found that ribosomal genes (RPL/RPS) are decreased in GDM, negatively correlated with 1hGlu and 2hGlu, and enriched in protein synthesis metabolic pathways. Additionally, placental-derived cfRNA contributed less to plasma in GDM, with placental-specific gene IGF2 significantly negatively correlated with blood glucose. Furthermore, 35 blood glucose correlated-cfRNA genes accurately predict GDM, with area under the curve of 0.84 in internal testing and 0.73 in external validation cohort. Our study reveals significant alterations in protein metabolic pathways and placenta-derived RNAs in plasma cfRNA prior to GDM diagnosis.
In recent years, the incidence of gestational diabetes mellitus (GDM) has been steadily increasing, posing risks to the long-term health of both mother and child. We aim to characterize blood glucose levels of pregnant women and predict the risk of GDM during early pregnancy through plasma cell-free mRNA and non-coding RNA (cfRNA). Here, we collected plasma samples from 108 pregnant women (54 with GDM and 54 controls) at around 16 weeks of gestation. Following high-throughput sequencing, we performed differentially abundant genes analysis and evaluated correlations between cfRNA profiles and blood glucose levels. Based on these findings, we developed a predictive model utilizing cf-mRNA and cf-lncRNA signatures. We found that ribosomal genes (RPL/RPS) are decreased in GDM, negatively correlated with 1hGlu and 2hGlu, and enriched in protein synthesis metabolic pathways. Additionally, placental-derived cfRNA contributed less to plasma in GDM, with placental-specific gene IGF2 significantly negatively correlated with blood glucose. Furthermore, 35 blood glucose correlated-cfRNA genes accurately predict GDM, with area under the curve of 0.84 in internal testing and 0.73 in external validation cohort. Our study reveals significant alterations in protein metabolic pathways and placenta-derived RNAs in plasma cfRNA prior to GDM diagnosis.
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