Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome
We enrolled consecutive IBS-M patients (n = 25) according to Rome IV criteria. Fecal samples were obtained from all patients twice (pre-and post-intervention) and high-throughput 16S rRNA sequencing was performed. Six weeks of personalized nutrition diet (n = 14) for group 1 and a standard IBS diet...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Gut Microbes |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19490976.2022.2138672 |
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| author | Tarkan Karakan Aycan Gundogdu Hakan Alagözlü Nergiz Ekmen Seckin Ozgul Varol Tunali Mehmet Hora Damla Beyazgul O. Ufuk Nalbantoglu |
| author_facet | Tarkan Karakan Aycan Gundogdu Hakan Alagözlü Nergiz Ekmen Seckin Ozgul Varol Tunali Mehmet Hora Damla Beyazgul O. Ufuk Nalbantoglu |
| author_sort | Tarkan Karakan |
| collection | DOAJ |
| description | We enrolled consecutive IBS-M patients (n = 25) according to Rome IV criteria. Fecal samples were obtained from all patients twice (pre-and post-intervention) and high-throughput 16S rRNA sequencing was performed. Six weeks of personalized nutrition diet (n = 14) for group 1 and a standard IBS diet (n = 11) for group 2 were followed. AI-based diet was designed based on optimizing a personalized nutritional strategy by an algorithm regarding individual gut microbiome features. The IBS-SSS evaluation for pre- and post-intervention exhibited significant improvement (p < .02 and p < .001 for the standard IBS diet and personalized nutrition groups, respectively). While the IBS-SSS evaluation changed to moderate from severe in 78% (11 out of 14) of the personalized nutrition group, no such change was observed in the standard IBS diet group. A statistically significant increase in the Faecalibacterium genus was observed in the personalized nutrition group (p = .04). Bacteroides and putatively probiotic genus Propionibacterium were increased in the personalized nutrition group. The change (delta) values in IBS-SSS scores (before-after) in personalized nutrition and standard IBS diet groups are significantly higher in the personalized nutrition group. AI-based personalized microbiome modulation through diet significantly improves IBS-related symptoms in patients with IBS-M. Further large-scale, randomized placebo-controlled trials with long-term follow-up (durability) are needed. |
| format | Article |
| id | doaj-art-2971d8b4fb4e46d1bd7d552e8b75c498 |
| institution | DOAJ |
| issn | 1949-0976 1949-0984 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Gut Microbes |
| spelling | doaj-art-2971d8b4fb4e46d1bd7d552e8b75c4982025-08-20T03:05:25ZengTaylor & Francis GroupGut Microbes1949-09761949-09842022-12-0114110.1080/19490976.2022.2138672Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndromeTarkan Karakan0Aycan Gundogdu1Hakan Alagözlü2Nergiz Ekmen3Seckin Ozgul4Varol Tunali5Mehmet Hora6Damla Beyazgul7O. Ufuk Nalbantoglu8Department of Internal Medicine, Division of Gastroenterology, Faculty of Medicine, Gazi University, Ankara, TurkeyDepartment of Microbiology and Clinical Microbiology, Faculty of Medicine, Erciyes University, Kayseri, TurkeyYuksek Ihtisas University, Medical Faculty, Gastroenterology Department, TurkeyDepartment of Internal Medicine, Division of Gastroenterology, Faculty of Medicine, Gazi University, Ankara, TurkeyDepartment of Internal Medicine, Division of Gastroenterology, Faculty of Medicine, Gazi University, Ankara, TurkeyCelal Bayar University, Medical Faculty, Parasitology Department, Manisa, TurkeyEnbiosis Biotechnology, Istanbul, TurkeyEnbiosis Biotechnology, Istanbul, TurkeyEnbiosis Biotechnology, Istanbul, TurkeyWe enrolled consecutive IBS-M patients (n = 25) according to Rome IV criteria. Fecal samples were obtained from all patients twice (pre-and post-intervention) and high-throughput 16S rRNA sequencing was performed. Six weeks of personalized nutrition diet (n = 14) for group 1 and a standard IBS diet (n = 11) for group 2 were followed. AI-based diet was designed based on optimizing a personalized nutritional strategy by an algorithm regarding individual gut microbiome features. The IBS-SSS evaluation for pre- and post-intervention exhibited significant improvement (p < .02 and p < .001 for the standard IBS diet and personalized nutrition groups, respectively). While the IBS-SSS evaluation changed to moderate from severe in 78% (11 out of 14) of the personalized nutrition group, no such change was observed in the standard IBS diet group. A statistically significant increase in the Faecalibacterium genus was observed in the personalized nutrition group (p = .04). Bacteroides and putatively probiotic genus Propionibacterium were increased in the personalized nutrition group. The change (delta) values in IBS-SSS scores (before-after) in personalized nutrition and standard IBS diet groups are significantly higher in the personalized nutrition group. AI-based personalized microbiome modulation through diet significantly improves IBS-related symptoms in patients with IBS-M. Further large-scale, randomized placebo-controlled trials with long-term follow-up (durability) are needed.https://www.tandfonline.com/doi/10.1080/19490976.2022.2138672Irritable bowel syndromeFunctional GI diseasesMicrobiomeSymptom score or indexArtificial intelligencePersonalized medicine |
| spellingShingle | Tarkan Karakan Aycan Gundogdu Hakan Alagözlü Nergiz Ekmen Seckin Ozgul Varol Tunali Mehmet Hora Damla Beyazgul O. Ufuk Nalbantoglu Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome Gut Microbes Irritable bowel syndrome Functional GI diseases Microbiome Symptom score or index Artificial intelligence Personalized medicine |
| title | Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome |
| title_full | Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome |
| title_fullStr | Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome |
| title_full_unstemmed | Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome |
| title_short | Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome |
| title_sort | artificial intelligence based personalized diet a pilot clinical study for irritable bowel syndrome |
| topic | Irritable bowel syndrome Functional GI diseases Microbiome Symptom score or index Artificial intelligence Personalized medicine |
| url | https://www.tandfonline.com/doi/10.1080/19490976.2022.2138672 |
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