The DOI matches its Crossref record; 269 of the 270 references it cites were found in a registry or an index.
The promise of the gut microbiome as part of individualized treatment strategies
Open accessAbstract
Variability in disease presentation, progression and treatment response has been a central challenge in medicine. Although variability in host factors and genetics are important, it has become evident that the gut microbiome, with its vast genetic and metabolic diversity, must be considered in moving towards individualized treatment. In this Review, we discuss six broad disease groups: infectious disease, cancer, metabolic disease, cardiovascular disease, autoimmune or inflammatory disease, and allergic and atopic diseases. We highlight current knowledge on the gut microbiome in disease pathogenesis and prognosis, efficacy, and treatment-related adverse events and its promise for stratifying existing treatments and as a source of novel therapies. The Review is not meant to be comprehensive for each disease state but rather highlights the potential implications of the microbiome as a tool to individualize treatment strategies in clinical practice. Although early, the outlook is optimistic but challenges need to be overcome before clinical implementation, including improved understanding of underlying mechanisms, longitudinal studies with multiple data layers reflecting gut microbiome and host response, standardized approaches to testing and reporting, and validation in larger cohorts. Given progress in the microbiome field with concurrent basic and clinical studies, the microbiome will likely become an integral part of clinical care within the next decade.
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“Clinical outcomes vary widely because host genetics, baseline microbiota, diet, medications, and comorbidities modulate response and susceptibility, which explains the heterogeneous results across studies [15,114,115].”
From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [115]
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An obesity-associated gut microbiome with increased capacity for energy harvest
Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006) · Nature · doi:10.1038/nature05414 · Cited by 12,444
Diet rapidly and reproducibly alters the human gut microbiome
David, L. A., Maurice, C. F., Carmody, R. N., Gootenberg, D. B., Button, J. E., Wolfe, B. E., Ling, A. V., Devlin, A. S., Varma, Y., Fischbach, M. A., et al. (2014) · Nature · doi:10.1038/nature12820 · Cited by 10,100
Hill (2014) · doi:10.1038/nrgastro.2014.66 · Cited by 9,592
Diversity of the Human Intestinal Microbial Flora
Eckburg, P. B., Bik, E. M., Bernstein, C. N., Purdom, E., Dethlefsen, L., Sargent, M., Gill, S. R., Nelson, K. E., & Relman, D. A. (2005) · Science · doi:10.1126/science.1110591 · Cited by 7,913
A core gut microbiome in obese and lean twins
Turnbaugh, P. J., Hamady, M., Yatsunenko, T., Cantarel, B. L., Duncan, A., Ley, R. E., Sogin, M. L., Jones, W. J., Roe, B. A., Affourtit, J. P., et al. (2009) · Nature · doi:10.1038/nature07540 · Cited by 7,823
Metabolic Endotoxemia Initiates Obesity and Insulin Resistance
Cani, P. D., Amar, J., Iglesias, M. A., Poggi, M., Knauf, C., Bastelica, D., Neyrinck, A. M., Fava, F., Tuohy, K. M., Chabo, C., et al. (2007) · Diabetes · doi:10.2337/db06-1491 · Cited by 6,638
Wang, H., Naghavi, M., Allen, C., Barber, R. M., Bhutta, Z. A., Carter, A., Casey, D. C., Charlson, F. J., Chen, A. Z., Coates, M. M., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(16)31012-1 · Cited by 6,596
The gut microbiota as an environmental factor that regulates fat storage
Bäckhed, F., Ding, H., Wang, T., Hooper, L. V., Koh, G. Y., Nagy, A., Semenkovich, C. F., & Gordon, J. I. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407076101 · Cited by 6,245
Obesity alters gut microbial ecology
Ley, R. E., Bäckhed, F., Turnbaugh, P., Lozupone, C. A., Knight, R. D., & Gordon, J. I. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504978102 · Cited by 6,176
Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors
Routy, B., Le Chatelier, E., Derosa, L., Duong, C. P. M., Alou, M. T., Daillère, R., Fluckiger, A., Messaoudene, M., Rauber, C., Roberti, M. P., et al. (2018) · Science · doi:10.1126/science.aan3706 · Cited by 5,671
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Ullah, M., Rizwan, M., Waheed, M. I., Alam, M. S., Jan, S. U., Raza, A., Shahid, M. F., Andoh, V., & Chen, Y. (2026) · World Journal of Microbiology and Biotechnology · doi:10.1007/s11274-026-05143-1
Shahidi, F., & Saeid, A. (2026) · Food Research International · doi:10.1016/j.foodres.2026.120092
Precision microbiome medicine and therapeutics: the enabling role of in vitro gut models
Huang, Z., Ng, S. C., Sokol, H., & Rolhion, N. (2026) · FEMS Microbiology Reviews · doi:10.1093/femsre/fuag038
Wali, A. F., Talath, S., Rangraze, I. R., El‐Tanani, M., & Khan, S. (2026) · BioMed Research International · doi:10.1155/bmri/8376859
Nesterova, E. Y., Gladkikh, M. I., Burakova, I. Y., Korneeva, O. S., Dmitrievna, M. P., & Syromyatnikov, M. (2026) · Diabetology · doi:10.3390/diabetology7080153
Gastrointestinal Microbiome Diversity
Singh, H., Bajaj, S., Jailabdin, S., & Hossain, K. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-3079-2.ch007
Zeng, J., Yang, K., Wu, H., Lin, Z., Liao, L., Dong, F., & Zhu, Y. (2026) · Journal of Clinical and Experimental Hepatology · doi:10.1016/j.jceh.2026.103637
Alhassan, L., Alrabadi, B., Batarseh, S. F., Alghzawi, Y., Bandak, N., Badwan, A., & Alkayed, H. A. (2026) · Immunotherapy · doi:10.1080/1750743x.2026.2717074
Saxena, S., Ahmed, I., Jha, R. K., Kumar, N., Saxena, M., Chakrabarty, S., Choudhary, R. K., Ahuja, D., Kumar, M. V., & Bhattacharjee, A. (2026) · Obesity Medicine · doi:10.1016/j.obmed.2026.100745
Le, Q. (2026) · Frontiers in Physiology · doi:10.3389/fphys.2026.1902756 · Cited by 1
Manrique, E., Sciglitano, L., & Ortega‐Santos, C. P. (2026) · Frontiers in Nutrition · doi:10.3389/fnut.2026.1989174
Farah, H., Kubaev, A., Hanumanthayya, M., Al-Hussein, M. A., Mutee, A. F., Axmedova, F., Бекзод, Б. Э., & Shefali (2026) · Frontiers in Microbiology · doi:10.3389/fmicb.2026.1955829
The Native Intra-articular Knee Microbiome: A Narrative Review of Emerging Clinical Evidence
Upadhyay, A., Ambade, R. E., Salwan, A., Khanduja, A., & Dhankhar, K. (2026) · International Journal of Medicine and Health Development · doi:10.4103/ijmh.ijmh_61_25
Benchmarking gut microbiome indices within and across populations
Sun, Y., Tang, Y., Ou, J., Wang, X., Yuan, Y., Fu, X., & Deng, Y. (2026) · iMetaOmics. · doi:10.1002/imo2.70148
Rathod, B., & Puri, S. (2026) · Journal of Drug Delivery Science and Technology · doi:10.1016/j.jddst.2026.108987
Maurya, Y., George, E., Roy, A., Menon, G. J., Harshitha, K. R., Priyadharshini, K., Ramaiah, S., & Anbarasu, A. (2026) · Biochemistry and Biophysics Reports · doi:10.1016/j.bbrep.2026.102827
Sun, J., Fan, Z., Bohn, R. C., Kim, S., & Park, H. J. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag545
Metadata
- Authors
- Schupack, D. A., Mars, R. A. T., Voelker, D. H., Abeykoon, J. P., & Kashyap, P. C.
- Affiliations
- Mayo Clinic (US)
- Corresponding author
- Kashyap, Purna C.
- Venue
- Nature Reviews Gastroenterology & Hepatology
- Published
- 2021-08-27
- Volume
- 19
- Issue
- 1
- Pages
- 7-25
- ISSN
- 1759-5045 (ISSN-L)
- 1759-5053
- PMC
- PMC8712374
- OpenAlex
- W3195493570
- Cited by
- 217
- References
- 270
- Citations by year
- 2026: 50 · 2025: 60 · 2024: 47 · 2023: 37 · 2022: 20 · 2021: 3
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature Reviews Gastroenterology & Hepatology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK114007)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Gastroenterology › Gastrointestinal motility and disorders
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- gut microbiota, personalized treatment, precision medicine, microbiota-based therapy, treatment response variability, infectious diseases, cancer, metabolic disorders, cardiovascular disease, autoimmune disease, pathogenesis, treatment-related adverse events
- MeSH terms
- Gastrointestinal Microbiome, Gastrointestinal Diseases, Humans, Liver Diseases, Precision Medicine
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