Longitudinal change of gut microbiota in hypertensive disorders in pregnancy: a nested case-control and Mendelian randomization study.

Mounting evidence has shown that gut microbiota (GM) is related to hypertensive disorders in pregnancy (HDP), however, most studies only focused on one time point in pregnancy. In this study, we conducted a nested case-control study utilizing a follow-up cohort, resulting in the collection of 47 HDP patients and 30 healthy controls. The GM profiles were explored using 16S rRNA sequencing at three time points during pregnancy. The diversity analysis of GM showed no significant difference between HDP patients and controls, however, we found 21 differential GM during pregnancy. Trend analysis showed that there are statistical differences in the relative abundance of Thermomonas, Xanthomonas, and Phenylobacteriumat during pregnancy in the gestational hypertension group, and of Xanthomonas, Polycyclovorans, and Phenylobacterium in the control group. The correlation study found that six genera of GM are related to blood pressure. Furthermore, the MR analysis identified the causal relationship between Methanobrevibacter and pre-eclampsia (PE). This study first explored the longitudinal change of GM in HDP patients during pregnancy, found the differential GM, and detected the causal association. Our findings may promote the prevention and treatment of HDP from the perspective of GM and provide valuable insights into the pathogenesis of HDP.

Gut microbiota and hypertensive disorders in pregnancy: evidence from the Mendelian randomization study.

BACKGROUND: Recent studies have shown that gut microbiota (GM) is related to hypertensive disorders in pregnancy (HDP). However, the causal relationship needs to be treated with caution due to confounding factors and reverse causation. METHODS: We obtained genetic variants from genome-wide association studies including GM (N = 18,340) in MiBioGen Consortium as well as HDP (7,686 cases/115,893 controls) and specific subtypes in FinnGen Consortium. Then, Inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS methods were applied to examine the causal association. Reverse Mendelian randomization (RMR) and multivariable MR were performed to confirm the causal direction and adjust the potential confounders, respectively. Furthermore, sensitivity analyses including Cochran's Q statistics, MR-Egger intercept, MR-PRESSO global test, and the leave-one-out analysis were conducted to detect the potential heterogeneity and horizontal pleiotropy. RESULTS: The present study found causalities between eight gut microbial genera and HDP. The HDP-associated gut microbial genera identified by MR analyses varied in different subtypes. Specifically, our study found causal associations of LachnospiraceaeUCG010, Olsenella, RuminococcaceaeUCG009, Ruminococcus2, Anaerotruncus, Bifidobacterium, and Intestinibacter with GH, of Eubacterium (ruminantium group), Eubacterium (ventriosum group), Methanobrevibacter, RuminococcaceaeUCG002, and Tyzzerella3 with PE, and of Dorea and RuminococcaceaeUCG010 with eclampsia, respectively. CONCLUSIONS: This study first applied the MR approach to detect the causal relationships between GM and specific HDP subtypes. Our findings may promote the prevention and treatment of HDP targeted on GM and provide valuable insights to understand the mechanism of HDP in different subtypes from the perspective of GM.

Investigating causal associations among gut microbiota, gut microbiota-derived metabolites, and gestational diabetes mellitus: a bidirectional Mendelian randomization study.

BACKGROUND: Previous studies have shown that gut microbiota (GM) and gut microbiota-derived metabolites are associated with gestational diabetes mellitus (GDM). However, the causal associations need to be treated with caution due to confounding factors and reverse causation. METHODS: This study obtained genetic variants from genome-wide association study including GM (N = 18,340), GM-derived metabolites (N = 7,824), and GDM (5,687 cases and 117,89 controls). To examine the causal association, several methods were utilized, including inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS. Additionally, reverse Mendelian Randomization (MR) analysis and multivariable MR were conducted to confirm the causal direction and account for potential confounders, respectively. Furthermore, sensitivity analyses were performed to identify any potential heterogeneity and horizontal pleiotropy. RESULTS: Greater abundance of Collinsella was detected to increase the risk of GDM. Our study also found suggestive associations among Coprobacter, Olsenella, Lachnoclostridium, Prevotella9, Ruminococcus2, Oscillibacte, and Methanobrevibacter with GDM. Besides, eight GM-derived metabolites were found to be causally associated with GDM. For the phenylalanine metabolism pathway, phenylacetic acid was found to be related to the risk of GDM. CONCLUSIONS: The study first used the MR approach to explore the causal associations among GM, GM-derived metabolites, and GDM. Our findings may contribute to the prevention and treatment strategies for GDM by targeting GM and metabolites, and offer novel insights into the underlying mechanism of the disease.