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Research article
Tsutomu Takeuchi
Keio University School of Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0003-1111-8218
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background. While numerous disease-modifying anti-rheumatic drugs (DMARDs) has brought about a dramatic paradigm shift in the management of rheumatoid arthritis (RA), unmet needs remain such as small proportion of achievement drug-free patients. The aim of this study is to explore key molecules for remission at T cell level, which is known to involve the pathogenesis of RA deeply, and investigate disease course of patients who achieved molecular remission (MR).
Methods. We enrolled a total of 46 patients with RA and 10 healthy controls (HCs). We performed gene expression profiling and selected remission signature genes in CD4+ T cells and CD8+ T cells of patients with RA using machine learning methods. In addition, we investigated the benefit of achieving MR on disease control thereafter.
Results. We identified 9 and 23 genes that were associated with clinical remission in CD4+ and CD8+ T cells. Principal component analysis (PCA) demonstrated expression profiling of them was similar with HCs. As to remission signature genes in CD4+ T cells, PCA result was reproduced using validation cohort, indicating their robustness. There was a trend towards better disease control during 12 months follow-up in patients treated with tocilizumab in deep MR than those in non-deep MR, although it was not significant.
Conclusion. We identified robust genes which represented remission status in CD4+ T cells using machine learning techniques. The current study will promote our understandings about molecular mechanism to achieve deep remission in the management of RA.
Trial registration: Not required.
Keywords
Rheumatoid arthritis, T cells, molecular remission
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research article
Tsutomu Takeuchi
Keio University School of Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0003-1111-8218
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
View the published article at Scientific Reports.
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Rheumatology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Scientific Reports.
Background. While numerous disease-modifying anti-rheumatic drugs (DMARDs) has brought about a dramatic paradigm shift in the management of rheumatoid arthritis (RA), unmet needs remain such as small proportion of achievement drug-free patients. The aim of this study is to explore key molecules for remission at T cell level, which is known to involve the pathogenesis of RA deeply, and investigate disease course of patients who achieved molecular remission (MR).
Methods. We enrolled a total of 46 patients with RA and 10 healthy controls (HCs). We performed gene expression profiling and selected remission signature genes in CD4+ T cells and CD8+ T cells of patients with RA using machine learning methods. In addition, we investigated the benefit of achieving MR on disease control thereafter.
Results. We identified 9 and 23 genes that were associated with clinical remission in CD4+ and CD8+ T cells. Principal component analysis (PCA) demonstrated expression profiling of them was similar with HCs. As to remission signature genes in CD4+ T cells, PCA result was reproduced using validation cohort, indicating their robustness. There was a trend towards better disease control during 12 months follow-up in patients treated with tocilizumab in deep MR than those in non-deep MR, although it was not significant.
Conclusion. We identified robust genes which represented remission status in CD4+ T cells using machine learning techniques. The current study will promote our understandings about molecular mechanism to achieve deep remission in the management of RA.
Trial registration: Not required.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
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