Shujuan Ma

Shujuan Ma

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

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Previous Organizations / Institutes

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Shujuan Ma has a total of 16 co-authors. Here are the top co-authors by number of shared publications:

  • Hongzhuan Tan

    Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China

    2 shared publications
  • Huijun Lin

    Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health, Central South University, Changsha 410013, China

    2 shared publications
  • Mengshi Chen

    Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China

    2 shared publications
  • Rongjing An

    Chaoyang District Center for Diseases Prevention and Control of Beijing, Beijing 100020, China

    2 shared publications
  • Hongzhuan Tan

    Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, No. 172 Tongzipo Road, Yuelu District, Changsha 410013, China

    1 shared publication
  • Junru Chen

    Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha 410000, China

    1 shared publication

Latest Publications

  • Open Access

    Study on Association Between Gut Microbiota, Serum Metabolism and Gestational Diabetes Mellitus Based on Metagenomic and Metabolomics Analysis

    by Wenduo Yu, Kun Tang, Rongjing An, Sujuan Ma, Hongzhuan Tan, Mengshi Chen

    Background/Objectives: This study aimed to explore the association between maternal gut microbiota and metabolic profiles in the first trimester and the subsequent risk of gestational diabetes mellitus (GDM), as well as to characterize association patterns linking gut microbiota, serum metabolites, and metabolic traits. Methods: A nested case–control study was conducted among women with GDM (n = 47) and those without GDM (n = 94). Metagenomic sequencing was applied to analyze fecal microbiota, and liquid chromatography–mass spectrometry (LC–MS) was used for non-targeted plasma metabolomics. Differential microbiota and metabolites between groups were identified, and correlation analyses were conducted to assess their associations with clinical indicators. Results: Women who later developed GDM showed lower alpha diversity and higher beta diversity. Eleven differential species were identified, with Collinsella aerofaciens and Clostridium bartlettii enriched in GDM, while nine species such as Alistipes putredinis and Bacteroidales bacterium ph8 were enriched in controls. Sixty-four plasma metabolites differed between groups, including increased glycerol-3-phosphate, aromatic amino acids, and glycerophosphocholine, and decreased cysteine, tryptophan, niacinamide, and stearic acid. Correlation analyses revealed significant relationships between Alistipes putredinis, Eubacterium eligens, and Bacteroidales bacterium ph8 with metabolic and clinical indicators (e.g., TG, TC, LDL). Conclusions: In this nested case–control study, women who later developed GDM exhibited reduced gut microbial diversity and altered metabolic profiles during the first trimester of pregnancy. Several microbial taxa and microbiota–metabolite associations were observed in relation to subsequent GDM status, highlighting early-pregnancy microbial and metabolic features that may be relevant to GDM-related metabolic changes.

  • Open Access

    Association between the Maternal Gut Microbiome and Macrosomia

    by Zixin Zhong, Rongjing An, Shujuan Ma, Na Zhang, Xian Zhang, Lizhang Chen, Xinrui Wu, Huijun Lin, Tianyu Xiang, Hongzhuan Tan, et al.

    Fetal macrosomia is defined as a birthweight ≥4000 g and causes harm to pregnant women and fetuses. Studies reported that the maternal intestinal microbiome plays a key role in the establishment, growth, and development of the fetal intestinal microbiome. However, whether there is a relationship between maternal gut microbiota and macrosomia remains unclear. Our study aimed to identify gut microbiota that may be related to the occurrence of macrosomia, explore the possible mechanisms by which it causes macrosomia, and establish a prediction model to determine the feasibility of predicting macrosomia by early maternal gut microbiota. We conducted a nested case-control study based on an early pregnancy cohort (ChiCTR1900020652) in the Maternity and Child Health Hospital of Hunan Province on fecal samples of 93 women (31 delivered macrosomia as the case group and 62 delivered normal birth weight newborns as the control group) collected and included in this study. We performed metagenomic analysis to compare the composition and function of the gut microbiome between cases and controls. Correlation analysis was used to explore the association of differential species and differential functional pathways. A random forest model was used to construct an early pregnancy prediction model for macrosomia. At the species level, there were more Bacteroides salyersiae, Bacteroides plebeius, Ruminococcus lactaris, and Bacteroides ovatus in the intestinal microbiome of macrosomias’ mothers compared with mothers bearing fetuses that had normal birth weight. Functional pathways of the gut microbiome including gondoate biosynthesis, L-histidine degradation III, cis-vaccenate biosynthesis, L-arginine biosynthesis III, tRNA processing, and mannitol cycle, which were more abundant in the macrosomia group. Significant correlations were found between species and functional pathways. Bacteroides plebeius was significantly associated with the pathway of cis-vaccenate biosynthesis (r = 0.28, p = 0.005) and gondoate biosynthesis (r = 0.28, p < 0.001) and Bacteroides ovatus was positively associated with the pathway of cis-vaccenate biosynthesis (r = 0.29, p = 0.005) and gondoate biosynthesis (r = 0.32, p = 0.002). Bacteroides salyersiae was significantly associated with the pathway of cis-vaccenate biosynthesis (r = 0.24, p = 0.018), gondoate biosynthesis (r = 0.31, p = 0.003), and L–histidine degradation III (r = 0.22, p = 0.291). Finally, four differential species and four clinical indicators were included in the random forest model for predicting macrosomia. The areas under the working characteristic curves of the training and validation sets were 0.935 (95% CI: 0.851~0.979) and 0.909 (95% CI: 0.679~0.992), respectively. Maternal gut microbiota in early pregnancy may play an important role in the development of macrosomia and can be used as potential predictors to prevent macrosomia.


  • Open Access

    The Association between Gut Microbiome and Pregnancy-Induced Hypertension: A Nested Case–Control Study

    by Huijun Lin, Junru Chen, Shujuan Ma, Rongjing An, Xingli Li, Hongzhuan Tan

    (1) Background: Pregnancy-induced hypertension (PIH) is associated with obvious microbiota dysbiosis in the third trimester of pregnancy. However, the mechanisms behind these changes remain unknown. Therefore, this study aimed to explore the relationship between the gut microbiome in early pregnancy and PIH occurrence. (2) Methods: A nested case–control study design was used based on the follow-up cohort. Thirty-five PIH patients and thirty-five matched healthy pregnant women were selected as controls. The gut microbiome profiles were assessed in the first trimester using metagenomic sequencing. (3) Results: Diversity analyses showed that microbiota diversity was altered in early pregnancy. At the species level, eight bacterial species were enriched in healthy controls: Alistipes putredinis, Bacteroides vulgatus, Ruminococcus torques, Oscillibacter unclassified, Akkermansia muciniphila, Clostridium citroniae, Parasutterella excrementihominis and Burkholderiales bacterium_1_1_47. Conversely, Eubacterium rectale, and Ruminococcus bromii were enriched in PIH patients. The results of functional analysis showed that the changes in these different microorganisms may affect the blood pressure of pregnant women by affecting the metabolism of vitamin K2, sphingolipid, lipid acid and glycine. (4) Conclusion: Microbiota dysbiosis in PIH patients begins in the first trimester of pregnancy, and this may be associated with the occurrence of PIH. Bacterial pathway analyses suggest that the gut microbiome might lead to the development of PIH through the alterations of function modules.