scholarly journals Determine independent gut microbiota-diseases association by eliminating the effects of human lifestyle factors

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Congmin Zhu ◽  
Xin Wang ◽  
Jianchu Li ◽  
Rui Jiang ◽  
Hui Chen ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Disease Risk ◽  
Bacterial Overgrowth ◽  
Small Intestinal Bacterial Overgrowth ◽  
Classification Performance ◽  
Considerable Proportion ◽  
Case Control Studies ◽  
Physiological Variables ◽  
Building Models ◽  
Disease Associations

AbstractLifestyle and physiological variables on human disease risk have been revealed to be mediated by gut microbiota. Low concordance between case-control studies for detecting disease-associated microbe existed due to limited sample size and population-wide bias in lifestyle and physiological variables. To infer gut microbiota-disease associations accurately, we propose to build machine learning models by including both human variables and gut microbiota. When the model’s performance with both gut microbiota and human variables is better than the model with just human variables, the independent gut microbiota -disease associations will be confirmed. By building models on the American Gut Project dataset, we found that gut microbiota showed distinct association strengths with different diseases. Adding gut microbiota into human variables enhanced the classification performance of IBD significantly; independent associations between occurrence information of gut microbiota and irritable bowel syndrome, C. difficile infection, and unhealthy status were found; adding gut microbiota showed no improvement on models’ performance for diabetes, small intestinal bacterial overgrowth, lactose intolerance, cardiovascular disease. Our results suggested that although gut microbiota was reported to be associated with many diseases, a considerable proportion of these associations may be very weak. We proposed a list of microbes as biomarkers to classify IBD and unhealthy status. Further functional investigations of these microbes will improve understanding of the molecular mechanism of human diseases.

scholarly journals Determine independent gut microbiota-diseases association by eliminating the effects of human lifestyle factors

2021 ◽  
Author(s):  
Xin Wang ◽  
Yuqing Yang ◽  
Jianchu Li ◽  
Rui Jiang ◽  
Ting Chen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Gut Microbiota ◽  
Large Scale ◽  
Disease Risk ◽  
Bacterial Overgrowth ◽  
Considerable Proportion ◽  
Learning Models ◽  
Case Control Studies ◽  
Physiological Variables ◽  
Machine Learning Models

ABSTRACTHuman lifestyle and physiological variables on human disease risk have been revealed to be mediated by gut microbiota. Low concordance between many case-control studies for detecting disease-associated microbe existed and it is likely due to the limited sample size and the population-wide bias in human lifestyle and physiological variables. To infer association between whole gut microbiota and diseases accurately, we propose to build machine learning models by including both human variables and gut microbiota based on the American Gut Project data, the largest known publicly available human gut bacterial microbiota dataset. When the model's performance with both gut microbiota and human variables is better than the model with just human variables, the independent association of gut microbiota with the disease will be confirmed. We found that gut microbes showed different association strengths with different diseases. Adding gut microbiota into human variables enhanced the association strengths with inflammatory bowel disease (IBD) and unhealthy status; showed no effect on association strengths with Diabetes and IBS; reduced the association strengths with small intestinal bacterial overgrowth, C. difficile infection, lactose intolerance, cardiovascular disease and mental disorders. Our results suggested that although gut microbiota was reported to be associated with many diseases, a considerable proportion of these associations may be spurious. We also proposed a list of microbes as biomarkers to classify IBD and unhealthy status, and validated them by reference to previously published research.IMPORTANCEwe reexamined the association between gut microbiota and multiple diseases via machine learning models on a large-scale dataset, and by considering the effect of human variables ignored by previous studies, truly independent microbiota-disease associations were estimated. We found gut microbiota is associated independently with IBD and overall health of human, but more evidence is needed to judge associations between microbiota and other diseases. Further functional investigations of our reported disease-related microbes will improve understanding of the molecular mechanism of human diseases.

scholarly journals Mechanism of action and therapeutic benefit of rifaximin in patients with irritable bowel syndrome: a narrative review

2020 ◽  
Vol 13 ◽  
pp. 175628481989753 ◽  
Author(s):  
William D. Chey ◽  
Eric D. Shah ◽  
Herbert L. DuPont
Keyword(s):  
Irritable Bowel Syndrome ◽  
Gut Microbiota ◽  
Mechanism Of Action ◽  
Bacterial Overgrowth ◽  
Gastrointestinal Disorder ◽  
Small Intestinal Bacterial Overgrowth ◽  
The United States ◽  
Clinical Effects ◽  
Healthy Individuals ◽  
Irritable Bowel

Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder with a multifactorial pathophysiology. The gut microbiota differs between patients with IBS and healthy individuals. After a bout of acute gastroenteritis, postinfection IBS may result in up to approximately 10% of those affected. Small intestinal bacterial overgrowth (SIBO) is more common in patients with IBS than in healthy individuals, and eradication of SIBO with systemic antibiotics has decreased symptoms of IBS in some patients with IBS and SIBO. The nonsystemic (i.e. low oral bioavailability) antibiotic rifaximin is indicated in the United States and Canada for the treatment of adults with IBS with diarrhea (IBS-D). The efficacy and safety of 2-week single and repeat courses of rifaximin have been demonstrated in randomized, placebo-controlled studies of adults with IBS. Rifaximin is widely thought to exert its beneficial clinical effects in IBS-D through manipulation of the gut microbiota. However, current studies indicate that rifaximin induces only modest effects on the gut microbiota of patients with IBS-D, suggesting that the efficacy of rifaximin may involve other mechanisms. Indeed, preclinical data reveal a potential role for rifaximin in the modulation of inflammatory cytokines and intestinal permeability, but these two findings have not yet been examined in the context of clinical studies. The mechanism of action of rifaximin in IBS is likely multifactorial, and further study is needed.

scholarly journals The Gut Microbiota and Irritable Bowel Syndrome: Friend or Foe?

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Uday C. Ghoshal ◽  
Ratnakar Shukla ◽  
Ujjala Ghoshal ◽  
Kok-Ann Gwee ◽  
Siew C. Ng ◽  
...  
Keyword(s):  
Irritable Bowel Syndrome ◽  
Gut Microbiota ◽  
Pathogenic Bacteria ◽  
Bacterial Overgrowth ◽  
Small Intestinal Bacterial Overgrowth ◽  
Low Grade ◽  
Psychosomatic Disease ◽  
Irritable Bowel ◽  
Low Grade Inflammation ◽  
Qualitative Changes

Progress in the understanding of the pathophysiology of irritable bowel syndrome (IBS), once thought to be a purely psychosomatic disease, has advanced considerably and low-grade inflammation and changes in the gut microbiota now feature as potentially important. The human gut harbours a huge microbial ecosystem, which is equipped to perform a variety of functions such as digestion of food, metabolism of drugs, detoxification of toxic compounds, production of essential vitamins, prevention of attachment of pathogenic bacteria to the gut wall, and maintenance of homeostasis in the gastrointestinal tract. A subset of patients with IBS may have a quantitative increase in bacteria in the small bowel (small intestinal bacterial overgrowth). Qualitative changes in gut microbiota have also been associated with IBS. Targeting the gut microbiota using probiotics and antibiotics has emerged as a potentially effective approach to the treatment of this, hitherto enigmatic, functional bowel disorder. The gut microbiota in health, quantitative and qualitative microbiota changes, and therapeutic manipulations targeting the microbiota in patients with IBS are reviewed in this paper.

Systematic Review and Meta-Analysis: Prevalence of Small Intestinal Bacterial Overgrowth in Chronic Liver Disease

2017 ◽  
Vol 37 (04) ◽  
pp. 388-400 ◽  
Author(s):  
Ayesha Shah ◽  
Erin Shanahan ◽  
Graeme Macdonald ◽  
Linda Fletcher ◽  
Pegah Ghasemi ◽  
...  
Keyword(s):  
Liver Disease ◽  
Chronic Liver Disease ◽  
Meta Analysis ◽  
Bacterial Overgrowth ◽  
Small Intestinal Bacterial Overgrowth ◽  
Chronic Liver ◽  
Case Control Studies ◽  
Culture Techniques ◽  
Intestinal Bacterial Overgrowth ◽  
Small Intestinal

AbstractThe authors conducted a meta-analysis of the prevalence of small intestinal bacterial overgrowth (SIBO) in patients with chronic liver disease (CLD) and controls. Using the search terms “small intestinal bacterial overgrowth (SIBO)” and “chronic liver disease (CLD)” or “cirrhosis,” 19 case-control studies were identified. Utilizing breath tests, the prevalence of SIBO in CLD was 35.80% (95% CI, 32.60–39.10) compared with 8.0% (95% CI, 5.70–11.00) in controls. Using culture techniques, the prevalence was 68.31% (95% CI, 59.62–76.00) in CLD patients as compared with 7.94% (95% CI, 3.44–12.73) in controls. No difference between cirrhotic and noncirrhotic patients was found. SIBO is significantly more frequent in CLD patients as compared with controls. The association of SIBO and CLD was not confined to patients with advanced CLD, suggesting that SIBO is not a consequence of advanced liver disease but may play a role in the progression of CLD.

Small Intestinal Bacterial Overgrowth Is Associated with Non- Alcoholic Fatty Liver Disease

2016 ◽  
Vol 25 (2) ◽  
pp. 159-165 ◽  
Author(s):  
Andrea Fialho ◽  
Andre Fialho ◽  
Prashanthi Thota ◽  
Arthur J. McCullough ◽  
Bo Shen
Keyword(s):  
Risk Factors ◽  
Fatty Liver Disease ◽  
Bacterial Overgrowth ◽  
Small Intestinal Bacterial Overgrowth ◽  
Study Group ◽  
Alcoholic Fatty Liver ◽  
Intestinal Bacterial Overgrowth ◽  
Small Intestinal ◽  
Alcoholic Fatty Liver Disease

Background: Changes in gut bacteria play a role in type 2 diabetes mellitus (DM) and hepatic steatosis. There is a lack of studies evaluating the frequency and risk factors for non-alcoholic fatty liver disease (NAFLD) in patients tested for small intestinal bacterial overgrowth (SIBO). Aim: To evaluate the frequency of NAFLD and associated risk factors in patients tested for SIBO. Methods: In this case-control study, 372 eligible patients submitted to glucose hydrogen/methane breath test for SIBO who also had an abdominal imaging study were included. Patients were divided into SIBO-positive and SIBO-negative groups. Clinical, demographic and laboratory variables were evaluated in addition to the presence of NAFLD on abdominal imaging. Results: Of the 372 eligible patients, 141 (37.9%) were tested positive for SIBO (study group) and 231 (62.1%) were negative for it (control group). NAFLD occurred in 45.4% (64/141) of the study group compared to 17.3% (40/231) of the control group (p<0.001). Patients in the study group were found to have higher rates of elevated aspartate aminotransferase (AST) (20.6% vs. 11.3%; p=0.034) and alanine aminotransferase (ALT) levels (56.0% vs. 40.7%; p= 0.039), type 2 diabetes (23.4% vs. 13.9%; p=0.041), hypertension (54.6% vs. 40.3%; p=0.046) and metabolic syndrome (78.0% vs. 60.2%; p=0.020). In the multivariate analysis, SIBO (odds ratio [OR]: 1.95; 95% confidence interval [CI]: 1.14-3.31; p=0.014), type 2 DM (OR: 3.04; 95%CI: 1.57-5.90; p=0.001) and obesity (OR: 3.58; 95%CI: 1.70-7.54; p=0.001) remained associated with NAFLD.Conclusion: Patients with SIBO have an increased risk for hepatic steatosis and may benefit from aggressive control of the risk factors for NAFLD including metabolic syndrome. Abbreviations: ALT: alanine aminotransferase; AST: aspartate aminotransferase; BMI: body mass index; CTE: computed tomography enterography; DM: diabetes mellitus; ETOH: ethanol; IL: interleukin; LPS: lipopolysaccharide; NAFLD: non-alcoholic fatty liver disease; NASH: non-alcoholic steatohepatitis; PPI: proton pump inhibitor; SIBO: small intestinal bacterial overgrowth; TLR-4: toll-like receptor 4; TMAO: trimethylamine-N-oxide (TMAO); TNF-α: tumor necrosis factor alpha.

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