Dataset Information

The Gut Microbial Signature of Gestational Diabetes Mellitus and the Association With Diet Intervention.

ABSTRACT: Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The link between microbiota and diet management contributes to metabolic homeostasis in GDM. Therefore, it is crucial to understand the structure of the gut microbiota in GDM and to explore the effect of dietary management on the microbiota structure. In this study, we analyzed the composition of the gut microbiota between 27 GDM and 30 healthy subjects at two time points using Illumina HiSeq 2500 platform. The taxonomy analyses suggested that the overall bacteria clustered by diabetes status, rather than diet intervention. Of particular interest, the phylum Acidobacteria in GDM was significantly increased, and positively correlated with blood glucose levels. Moreover, Partial least-squares discriminant analysis (PLS-DA) revealed that certain genera in the phyla Firmicutes, Bacteroidetes, Proteobacteria, and Lentisphaerae characterized the GDM gut microbiota. Correlation analysis indicated that blood glucose levels and BMI index were correlated with the relative abundance of SCFAS-producing genera. Through the comparison between the GDM and healthy samples with or without diet intervention, we discovered that the role of short-term diet management in GDM processes is associated with the change in the Firmicutes/Bacteroidetes ratio and some specific taxa, rather than an alternative gut microbial pattern. Our study have important implications for understanding the beneficial effects of diet intervention on the specific gut microbiota and thus possibly their metabolism in pregnant women with GDM.

SUBMITTER: Wu N

PROVIDER: S-EPMC8795975 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We will explore the genetic (including APC, k-ras, p53, MSI, etc.) and environmental (including family history, life style, diet, nutritional status, DM, serum IGF-I, IGFBP-3, etc.) risk factors of colorectal tumorigenesis. We will accrue approximately 1000 patients as experimental group. The control group consists of 2000 individuals who were confirmed without colorectal cancer or polyps by colonoscopy. We estimated the statistical power of this study will reach more than 90%. In the second year, we will explore the association between various environmental risk factors with the epigenetic changes of various oncogenes and tumor suppressor genes. Firstly, we will study the correlation between hypermethylation of promoter region of hMLH1 gene with various environmental factors. Next, we will explore the genetic polymorphisms of promoter of E-cadherin gene. Recently, it has been reported that the C→A genetic polymorphism in the promoter region of E-cadherin gene in prostate cancer. Since this phenomenon has not been reported in colorectal cancer, it is mandatory for us to extend our research to the E-cadherin polymorphisms of colorectal cancer. Moreover, this project will focus on exploration of the association between the genetic polymorphisms of promoter of TS gene with chemosensitivity to 5-Fu-based therapy. We speculated that the better prognosis in colorectal tumors with MSI is related to their expression of TS gene. In summary, the second year of this project will extend our accumulated experience in the study of genetic polymorphisms to further clarify the association between genetic polymorphisms of TS gene with the prognosis of colorectal cancers after chemotherapy. We believe that this project will facilitate: (1) the further clarification of colorectal cancer tumorigenesis; (2) the establishment of domestic epidemiological data of colorectal cancer of Taiwan, and (3) the improvement of the quality of clinical management of patients with colorectal cancer.

Dataset Information

The Gut Microbial Signature of Gestational Diabetes Mellitus and the Association With Diet Intervention.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets