Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis
Abstract Background Rapid advances in the past decade have shown that dysbiosis of the gut microbiome is a key hallmark of rheumatoid arthritis (RA). Yet, the relationship between the gut microbiome and clinical improvement in RA disease activity remains unclear. In this study, we explored the gut m...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-09-01
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| Series: | Genome Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13073-021-00957-0 |
| _version_ | 1818358849542815744 |
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| author | Vinod K. Gupta Kevin Y. Cunningham Benjamin Hur Utpal Bakshi Harvey Huang Kenneth J. Warrington Veena Taneja Elena Myasoedova John M. Davis Jaeyun Sung |
| author_facet | Vinod K. Gupta Kevin Y. Cunningham Benjamin Hur Utpal Bakshi Harvey Huang Kenneth J. Warrington Veena Taneja Elena Myasoedova John M. Davis Jaeyun Sung |
| author_sort | Vinod K. Gupta |
| collection | DOAJ |
| description | Abstract Background Rapid advances in the past decade have shown that dysbiosis of the gut microbiome is a key hallmark of rheumatoid arthritis (RA). Yet, the relationship between the gut microbiome and clinical improvement in RA disease activity remains unclear. In this study, we explored the gut microbiome of patients with RA to identify features that are associated with, as well as predictive of, minimum clinically important improvement (MCII) in disease activity. Methods We conducted a retrospective, observational cohort study on patients diagnosed with RA between 1988 and 2014. Whole metagenome shotgun sequencing was performed on 64 stool samples, which were collected from 32 patients with RA at two separate time-points approximately 6–12 months apart. The Clinical Disease Activity Index (CDAI) of each patient was measured at both time-points to assess achievement of MCII; depending on this clinical status, patients were distinguished into two groups: MCII+ (who achieved MCII; n = 12) and MCII− (who did not achieve MCII; n = 20). Multiple linear regression models were used to identify microbial taxa and biochemical pathways associated with MCII while controlling for potentially confounding factors. Lastly, a deep-learning neural network was trained upon gut microbiome, clinical, and demographic data at baseline to classify patients according to MCII status, thereby enabling the prediction of whether a patient will achieve MCII at follow-up. Results We found age to be the largest determinant of the overall compositional variance in the gut microbiome (R 2 = 7.7%, P = 0.001, PERMANOVA). Interestingly, the next factor identified to explain the most variance in the gut microbiome was MCII status (R 2 = 3.8%, P = 0.005). Additionally, by looking at patients’ baseline gut microbiome profiles, we observed significantly different microbiome traits between patients who eventually showed MCII and those who did not. Taxonomic features include alpha- and beta-diversity measures, as well as several microbial taxa, such as Coprococcus, Bilophila sp. 4_1_30, and Eubacterium sp. 3_1_31. Notably, patients who achieved clinical improvement had higher alpha-diversity in their gut microbiomes at both baseline and follow-up visits. Functional profiling identified fifteen biochemical pathways, most of which were involved in the biosynthesis of L-arginine, L-methionine, and tetrahydrofolate, to be differentially abundant between the MCII patient groups. Moreover, MCII+ and MCII− groups showed significantly different fold-changes (from baseline to follow-up) in eight microbial taxa and in seven biochemical pathways. These results could suggest that, depending on the clinical course, gut microbiomes not only start at different ecological states, but also are on separate trajectories. Finally, the neural network proved to be highly effective in predicting which patients will achieve MCII (balanced accuracy = 90.0%, leave-one-out cross-validation), demonstrating potential clinical utility of gut microbiome profiles. Conclusions Our findings confirm the presence of taxonomic and functional signatures of the gut microbiome associated with MCII in RA patients. Ultimately, modifying the gut microbiome to enhance clinical outcome may hold promise as a future treatment for RA. |
| first_indexed | 2024-12-13T20:35:32Z |
| format | Article |
| id | doaj.art-fbd00a95259145969ce1d6e0669a5c9c |
| institution | Directory Open Access Journal |
| issn | 1756-994X |
| language | English |
| last_indexed | 2024-12-13T20:35:32Z |
| publishDate | 2021-09-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Medicine |
| spelling | doaj.art-fbd00a95259145969ce1d6e0669a5c9c2022-12-21T23:32:19ZengBMCGenome Medicine1756-994X2021-09-0113112010.1186/s13073-021-00957-0Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritisVinod K. Gupta0Kevin Y. Cunningham1Benjamin Hur2Utpal Bakshi3Harvey Huang4Kenneth J. Warrington5Veena Taneja6Elena Myasoedova7John M. Davis8Jaeyun Sung9Microbiome Program, Center for Individualized Medicine, Mayo ClinicBioinformatics and Computational Biology Program, University of MinnesotaMicrobiome Program, Center for Individualized Medicine, Mayo ClinicMicrobiome Program, Center for Individualized Medicine, Mayo ClinicMayo Clinic Medical Scientist Training Program, Mayo ClinicDivision of Rheumatology, Department of Medicine, Mayo ClinicDepartment of Immunology, Mayo ClinicDivision of Rheumatology, Department of Medicine, Mayo ClinicDivision of Rheumatology, Department of Medicine, Mayo ClinicMicrobiome Program, Center for Individualized Medicine, Mayo ClinicAbstract Background Rapid advances in the past decade have shown that dysbiosis of the gut microbiome is a key hallmark of rheumatoid arthritis (RA). Yet, the relationship between the gut microbiome and clinical improvement in RA disease activity remains unclear. In this study, we explored the gut microbiome of patients with RA to identify features that are associated with, as well as predictive of, minimum clinically important improvement (MCII) in disease activity. Methods We conducted a retrospective, observational cohort study on patients diagnosed with RA between 1988 and 2014. Whole metagenome shotgun sequencing was performed on 64 stool samples, which were collected from 32 patients with RA at two separate time-points approximately 6–12 months apart. The Clinical Disease Activity Index (CDAI) of each patient was measured at both time-points to assess achievement of MCII; depending on this clinical status, patients were distinguished into two groups: MCII+ (who achieved MCII; n = 12) and MCII− (who did not achieve MCII; n = 20). Multiple linear regression models were used to identify microbial taxa and biochemical pathways associated with MCII while controlling for potentially confounding factors. Lastly, a deep-learning neural network was trained upon gut microbiome, clinical, and demographic data at baseline to classify patients according to MCII status, thereby enabling the prediction of whether a patient will achieve MCII at follow-up. Results We found age to be the largest determinant of the overall compositional variance in the gut microbiome (R 2 = 7.7%, P = 0.001, PERMANOVA). Interestingly, the next factor identified to explain the most variance in the gut microbiome was MCII status (R 2 = 3.8%, P = 0.005). Additionally, by looking at patients’ baseline gut microbiome profiles, we observed significantly different microbiome traits between patients who eventually showed MCII and those who did not. Taxonomic features include alpha- and beta-diversity measures, as well as several microbial taxa, such as Coprococcus, Bilophila sp. 4_1_30, and Eubacterium sp. 3_1_31. Notably, patients who achieved clinical improvement had higher alpha-diversity in their gut microbiomes at both baseline and follow-up visits. Functional profiling identified fifteen biochemical pathways, most of which were involved in the biosynthesis of L-arginine, L-methionine, and tetrahydrofolate, to be differentially abundant between the MCII patient groups. Moreover, MCII+ and MCII− groups showed significantly different fold-changes (from baseline to follow-up) in eight microbial taxa and in seven biochemical pathways. These results could suggest that, depending on the clinical course, gut microbiomes not only start at different ecological states, but also are on separate trajectories. Finally, the neural network proved to be highly effective in predicting which patients will achieve MCII (balanced accuracy = 90.0%, leave-one-out cross-validation), demonstrating potential clinical utility of gut microbiome profiles. Conclusions Our findings confirm the presence of taxonomic and functional signatures of the gut microbiome associated with MCII in RA patients. Ultimately, modifying the gut microbiome to enhance clinical outcome may hold promise as a future treatment for RA.https://doi.org/10.1186/s13073-021-00957-0Rheumatoid arthritisGut microbiomeClinical disease activity indexMinimum clinically important improvementShotgun metagenomic sequencingMachine-learning |
| spellingShingle | Vinod K. Gupta Kevin Y. Cunningham Benjamin Hur Utpal Bakshi Harvey Huang Kenneth J. Warrington Veena Taneja Elena Myasoedova John M. Davis Jaeyun Sung Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis Genome Medicine Rheumatoid arthritis Gut microbiome Clinical disease activity index Minimum clinically important improvement Shotgun metagenomic sequencing Machine-learning |
| title | Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis |
| title_full | Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis |
| title_fullStr | Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis |
| title_full_unstemmed | Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis |
| title_short | Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis |
| title_sort | gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis |
| topic | Rheumatoid arthritis Gut microbiome Clinical disease activity index Minimum clinically important improvement Shotgun metagenomic sequencing Machine-learning |
| url | https://doi.org/10.1186/s13073-021-00957-0 |
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