ObjectiveTo investigate the causal relationship between gut microbiota and cholelithiasis using a two-sample Mendelian randomization method. MethodsThe genome-wide association studies (GWAS) data of gut microbiota from the MiBioGen study and the GWAS data of cholelithiasis from the FinnGen Biobank were utilized. Genetic variants significantly associated with the relative abundance of gut microbiota were identified as instrumental variables (IVs) based on a specified threshold. The inverse variance weighted (IVW) method was employed as the primary analytical approach, with results assessed based on the odds ratio (OR) and 95% confidence interval (CI). The robustness and reliability of the findings were ensured through quality control measures, including sensitivity analysis, assessment of heterogeneity, and evaluation for horizontal gene pleiotropy. ResultsClostridiumsensustricto1 [OR=1.160, 95%CI (1.023, 1.314), P=0.020], Coprococcus3 [OR=1.136, 95%CI (1.014, 1.272), P=0.028] and Peptococcus [OR=1.074, 95%CI (1.023, 1.128) , P=0.004] increased the risk of cholelithiasis. Bacilli [OR=0.897, 95%CI (0.818, 0.984), P=0.022], Family Ⅹ ⅢAD3011group [OR=0.908, 95%CI (0.830, 0.992), P=0.033] and Lactobacillales [OR=0.884, 95%CI (0.802, 0.974), P=0.013] were protective factors for cholelithiasis. ConclusionThe study has identified 6 kinds of specific gut microbiota that are causally linked to the development of cholelithiasis, providing new ideas for the diagnosis and treatment of cholelithiasis.
Objective To review the changes of gut microbiota after bariatric surgery and the related mechanisms of improving metabolism. Method Domestic and international literatures in recent ten years on the changes of gut microbiota in bariatric surgery and the mechanisms of improving metabolism were collated and summarized. Result The common bariatric procedures performed to date were vertical sleeve gastrectomy (VSG) and laparoscopic Roux-en-Y gastric bypass (RYGB). The changes of gut microbiota vary in different surgical procedures, which were related to the changes of diet habits, gastrointestinal anatomy, gastrointestinal hormone levels and metabolic complications. The gut microbiota might improve the body metabolism by regulating the levels of short chain fatty acids, branched chain amino acids and bacterial endotoxin in the intestinal lumen. Conclusions Significant changes are found in gut microbiota after bariatric surgery, which may be involved in the improvement of body metabolism by regulating the level of bacterial endotoxin and microbial metabolite. However, more in-depth mechanisms need to be further clarified.
ObjectiveTo review the association of gut microbiota and postoperative gastrointestinal dysfunction (GID) in patients after abdominal surgery and to provide a new idea for the pathogenesis, prevention, and treatment of postoperative GID in patients after abdominal surgery.MethodThe related and latest literatures were reviewed by searching the literatures on “intestinal flora” “gut microbiota” “intestinal microbial population” “brain-gut axis” “gastrointestinal function” “gastric paralysis” “intestinal paralysis” and “ileus” from January 1, 2000 to April 2, 2021 in Chinese and English databases.ResultsGut microbiota diversity was closely related to postoperative GID symptoms in patients after abdominal surgery. Gut microbiota regulated gastrointestinal motility and mucosal barrier function by metabolizing food to produce metabolites such as 5-hydroxytryptamine, melatonin, short-chain fatty acid, succinic acid, lactic acid, and so on.ConclusionsThe imbalance of gut microbiota is closely related to postoperative GID in patients after abdominal surgery. However, the relevant bacterial metabolites that have been found are limited at present, and the relevant mechanism needs to be further investigated.
ObjectiveTo summarise the influencing factors of gut microbiota in the perioperative period and its regulatory mechanism in postoperative pain, with the aim of providing clinical reference for postoperative pain management. MethodRelevant literatures on gut microbiota and postoperative pain in recent years were systematically reviewed and synthesised. ResultsAnaesthesia, preoperative mechanical bowel preparation, surgical stress, etc. could cause gut microbiota dysbiosis. Gut microbiota directly or indirectly modulated the excitability of primary sensory neurons through their derived metabolites and pathogen-associated molecular patterns and influenced the pain signalling process by activating immune cells to release cytokines. ConclusionsGut microbiota play an important role in the development and progression of postoperative pain. Future studies should further clarify its role in different types of postoperative pain and develop innovative therapeutic strategies based on the regulation of gut microbiota to improve the management of postoperative pain.
Gut microbiota plays an important role in development of diabetes with frailty. Therefore, it is of great significance to study the structural and functional characteristics of gut microbiota in Chinese with frailty. Totally 30 middle-aged and the aged participants in communities with diabetes were enrolled in this study, and their feces were collected. At the same time, we developed a metagenome analysis to explore the different of the structural and functional characteristics between diabetes with frailty and diabetes without frailty. The results showed the alpha diversity of intestinal microbiota in diabetes with frailty was lower. Collinsella and Butyricimonas were more abundant in diabetes with frailty. The functional characteristics showed that histidine metabolism, Epstein-Barr virus infection, sulfur metabolism, and biosynthesis of type Ⅱ polyketide products were upregulated in diabetes with frailty. Otherwise, butanoate metabolism and phenylalanine metabolism were down-regulated in diabetes with frailty. This research provides theoretical basic for exploring the mechanism of the gut microbiota on the occurrence and development of diabetes with frailty, and provides a basic for prevention and intervention of it.
Including gut microbiota and oral microbiota, various microorganisms in different human ecosystem constitute the human microbiota, which play an important role in human metabolism, immunity and maintaining microecological homeostasis. Abnormal changes in gut microbiota known as dysbiosis may lead to metabolic abnormalities and inflammatory changes, which are closely related to disease states including hypertension, diabetes, inflammatory bowel disease, and autoimmune diseases. The main cause of coronary artery disease is coronary atherosclerosis, a chronic and progressive inflammatory disease. Many evidences have shown that there is a correlation between gut microbiota and coronary artery disease. Therefore, we aim to review the relationship between gut microbiota and coronary artery disease, and discuss the possible research directions and application prospects.
ObjectiveTo investigate the heterogeneity of gut microbiota between patients with solitary pulmonary nodules (SPN) and multiple pulmonary nodules (MPN), and to explore the intrinsic relationship between Traditional Chinese Medicine (TCM) constitution types and the intestinal microecology. MethodsA prospective study was conducted on 280 patients with pulmonary nodules enrolled between April 2022 and December 2024 from Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, Chengdu Integrated Traditional Chinese Medicine & Western Medicine Hospital. Among them, 118 (42.1%) were male and 162 (57.9%) were female, with a median age of 50 (42, 57) years. Based on imaging findings, patients were divided into a SPN group (n=65) and an MPN group (n=215). TCM constitution types were identified using a Constitution in Chinese Medicine Questionnaire. Fecal samples were collected for 16S rRNA sequencing. Bioinformatics analysis was employed to analyze inter-group differences in microbial community structure. The correlation between TCM constitutions and gut microbiota was examined using Procrustes analysis and Spearman correlation analysis. ResultsThe distribution of TCM constitution types between the two groups showed a statistically significant difference (P<0.05). The SPN group was predominantly characterized by the Qi-depression constitution, while the MPN group was more commonly associated with Yang-deficiency and Phlegm-dampness constitutions. Microbiota analysis revealed that the gut microbiota health index was significantly higher in the SPN group than in the MPN group (P<0.05), whereas the microbiota dysbiosis index showed the opposite pattern. Taxonomic analysis identified higher abundances of Ruminococcus_torques_group, Haemophilus, and Fusobacterium in the SPN group. The abundance of Leuconostoc was significantly increased in the MPN group. Procrustes analysis and Spearman correlation analysis indicated that in the SPN group, the Qi-depression constitution was positively correlated with Ruminococcus_torques_group and Bacteroides. In the MPN group, the Yang-deficiency constitution was negatively correlated with Faecalibacterium, while no statistically significant correlations were found between specific bacterial genera and the Phlegm-dampness or Qi-deficiency constitutions. ConclusionSPN and MPN exhibit significant heterogeneity in TCM constitutional tendencies and microecological characteristics. The abundance of specific bacterial genera may serve as potential biomarkers for distinguishing between SPN and MPN. The interaction between TCM constitutions and specific gut microbiota provides a theoretical basis for the precise TCM syndrome differentiation and microecological intervention in pulmonary nodules.
Objective To assess any potential associations between lung cancer and gut microbiota. Methods Mendelian randomization (MR) analysis was carried out by utilizing summary data from genome-wide association studies (GWAS) of the gut microbiota and lung cancer. The gut microbiota served as an exposure. Instrumental ariables (IVs) were identified from the GWAS of 18340 participants. The GWAS study of lung cancer from Europe served as an outcome, including 29 266 lung cancer patients and 56450 controls. We used the inverse-variance weighted (IVW) method as the primary analysis. Sensitivity analysis was used to test the reliability of MR analysis results. Results IVW results showed that Genus Parabacteroides (OR=1.258, 95%CI 1.034 to 1.531, P=0.022) and Phylum Bacteroidetes (OR=1.192, 95%CI 1.001 to 1.419, P=0.048) had a positive causal association with lung cancer, and there was a negative causal association between family Bifidobacteriaceae (OR=0.845, 95%CI 0.721 to 0.989, P=0.037) and order Bifidobacteriales (OR=0.865, 95%CI 0.721 to 0.989, P=0.037) with lung cancer. Sensitivity analysis showed no evidence of reverse causality, pleiotropy, and heterogeneity. Conclusion This study demonstrates that Genus Parabacteroides and Phylum Bacteroidetes are related to an increased risk of lung cancer, family Bifidobacteriaceae and order Bifidobacteriales can reduce the risk of lung cancer. Our thorough investigations provide evidence in favor of a potential causal relationship between a number of gut microbiota-taxa and lung cancer. To demonstrate how gut microbiota influences the development of lung cancer, further research is necessary.
Objective To analyze the causal relationship between gut microbiota and tic disorder based on Mendelian randomization (MR). Methods A total of 196 known microbiota (9 phyla, 16 classes, 20 orders, 32 families, and 119 genera) in the human intestinal microbiota dataset downloaded from the MiBioGen database were selected as the exposure factors, and the dataset of tic disorder (finn-b-KRA_PSY_TIC) containing 172 patients and 218620 controls was downloaded from the genome-wide association study database as the outcome variable. Inverse variance weighted was used as the main analysis method, and the causal relationship between gut microbiota and tic disorder was evaluated using odds ratio (OR) and its 95% confidence interval (CI). Horizontal pleiotropy was tested by MR-Egger intercept and MR-PRESSO global test, heterogeneity was assessed by Cochran’s Q test, and sensitivity analysis was performed by leave-one-out method. Results Inverse variance weighted results showed that the Family Rhodospirillaceae [OR=0.398, 95%CI (0.191, 0.831), P=0.014], Order Rhodospirillales [OR=0.349, 95%CI (0.164, 0.743), P=0.006], and Parasutterella [OR=0.392, 95%CI (0.171, 0.898), P=0.027] had negative causal relationships with tic disorder. The Genus Lachnospira [OR=8.784, 95%CI (1.160, 66.496), P=0.035] and Candidatus Soleaferrea [OR=2.572, 95%CI (1.161, 5.695), P=0.020] had positive causal relationships with tic disorder. In addition, MR-Egger intercept and MR-PRESSO global test showed no horizontal pleiotropy, Cochran’s Q test showed no heterogeneity, and leave-one-out sensitivity analysis showed the results were stable. Conclusions A causal relationship exists between gut microbiota and tic disorder. The Family Rhodospirillaceae, Order Rhodospirillales, and Parasutterella are associated with a decreased risk of tic disorder, while the Genus Lachnospira and Candidatus Soleaverea can increase the risk of tic disorder.
There is a bidirectional association between tumor-associated macrophage (TAM) and colorectal cancer. Small molecular substances metabolized by colorectal cancer affect the reprogramming of TAM, and TAM in turn regulates the biological behavior of colorectal cancer cells by secreting small molecular substances, and promotes the progression of colorectal cancer. In addition, gut microbiota metabolites are closely related to TAM reprogramming, and intestinal flora imbalance leads to gut barrier damage, favoring bacterial translocation and causing chronic tumorigenic inflammation. Studying the reprogramming mechanism affecting TAM and its relationship with the occurrence and development of colorectal cancer may provide new ideas for the study of immunotherapy in patients with colorectal cancer. This article reviews the research progress of TAM in patients with colorectal cancer, aims to provide a reference for clinical research.