| Literature DB >> 32143424 |
Amir Mari1, Fadi Abu Baker2, Mahmud Mahamid1,3, Wisam Sbeit4, Tawfik Khoury1,4.
Abstract
The intestinal microbiota is one of the most rapidly evolving areas in biology and medicine. Extensive research in the last decade has escalated our understanding of the role of the microbiota in the pathogenesis of several intestinal and extra-intestinal disorders. Marked by high prevalence, substantial morbidity, and enormous costs, irritable bowel syndrome (IBS) is an important chronic gastrointestinal disorder that is widely encountered by gastroenterologists. Despite advances in our understanding of its pathophysiology, curative interventions have yet to be discovered, and therapeutic approaches remain symptom-driven. Recently, accumulating evidence has enlightened the possible impact of an imbalanced gut microbiome in the pathogenesis of IBS. In fact, several studies have documented altered microbiota in patients, while others have shown that IBS severity was associated with a distinct microbiota signature. These findings may pave the way for the use of microbiota manipulation strategies as an attractive option for IBS management, and may have an essential role in efforts to reduce the societal and economic effects of this ever-growing disorder. In this review, we have outlined the results of the latest research on the association between microbiota and IBS and their implications for the clinical management of affected patients.Entities:
Keywords: IBS; gut; microbiome
Year: 2020 PMID: 32143424 PMCID: PMC7141230 DOI: 10.3390/jcm9030685
Source DB: PubMed Journal: J Clin Med ISSN: 2077-0383 Impact factor: 4.241
Figure 1Role of the microbiome in irritable bowel syndrome (IBS).
Figure 2Treatments of irritable bowel syndrome (IBS) by targeting the gut microbiome.
Summary of the meta-analysis studies reporting efficacy of therapeutic interventions in irritable bowel syndrome (IBS) based on overall global IBS symptoms.
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| Didari T., 2015 [ | 15 | 1793 | 2.43 ± 1.13–5.21 | - | 0.02 |
| Zhang Y., 2016 [ | 21 | 1639 | 1.82 ± 1.27–2.6 | - | <0.001 |
| Liang D., 2019 [ | 14 | 1695 | 1.27 ± 1.13–1.44 | - | <0.001 |
| McFarland L.V., 2008 [ | 23 | 1404 | 0.77 pooled ± 0.62–0.94 | - | <0.001 |
| Connell M., 2018 [ | 5 | 243 | 1.39 ± 0.99–1.98 | - | 0.06 |
| Ford A.C., 2014 [ | 23 | 2575 | - | 0.79 ± 0.7–0.89 | <0.0001 |
| Tiequn B., 2015 [ | 6 | 273 | 17.62 pooled ± 5.12–60.65 for adults | - | <0.00001 |
| Ritchie M.L., 2012 [ | 16 | - | 0.77 ± 0.65–0.92 | - | - |
| Horvath A., 2011 [ | 3 | 167 | 1.7 ± 1.27–2.27 | - | 0.0004 |
| Hoveyda N., 2009 [ | 7 | 425 | 1.6 ± 1.2–2.2 | - | 0.0007 |
| Moayyedi P., 2010 [ | 10 | 918 | - | 0.71 ± 0.57–0.88 | 0.002 |
| Nikfar S., 2008 [ | 8 | 1011 | 1.22 ± 1.07–1.4 | - | 0.004 |
| McFarland L.V., 2008 [ | 20 | 1404 | 0.77 pooled ± 0.62–0.94 | - | <0.001 |
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| Wilson B., 2019 [ | 11 | 729 | OR 0.62 ± 0.07–5.69 | - | 0.67 |
| Ford A.C., 2018 [ | Trials for prebiotics were sparse and no definite conclusions could be drawn | ||||
| Ford A.C., 2014 [ | |||||
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| Myneedu K., 2019 [ | 5 | 262 | 0.93 ± 0.5–1.75 | - | 0.83 |
| Xu D., 2019 [ | 4 | 254 | 0.93 ± 0.48–1.79 | - | 0.83 |
| Laniro G., 2019 [ | 5 | 267 | - | 0.98 ± 0.58–1.66 | 0.94 |
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| Ford A.C., 2018 [ | 5 | 3610 | - | 0.84 ± 0.79–0.9 | 0.0002 |
| Li J., 2016 [ | 4 | 1803 | 1.19 ± 1.08–1.32 | - | 0.0008 |
| Menees S.B., 2012 [ | 5 | 1803 | 1.57 ± 1.22–2.01 | - | <0.001 |
RCT: Randomized Controlled Trials; CI: Confidence Interval; pooled: Pooled RR.