Dataset Information

Prediction of Self-Perception of Patient in Rheumatoid Arthritis With the Key RNAs Expression Profiles.

ABSTRACT: Self-perception in patients is their self-response to sensory stimuli. It is an important aspect of the existence and quality of life among patients. However, the inherent relationship between self-perception and the cellular activity at the molecular level is elusive. In this study, we aimed to explore the association of self-perception with RNA expression profile in patients with rheumatoid arthritis (RA) through computational analysis. We recruited 30 patients clinically diagnosed with RA and to age- and sex-matched controls without previous clinical history. In total, 5 self-perception measures and 30 RNA expression measures were derived from RA patients and control groups. A correlation analysis based on Spearman correlation and Logistic-regression methods was adopted to assess the correlation between self-perception and RNA expression. Quantitative analysis revealed that RA patients with poor self-perception were closely associated with RNAs expression, In addition, 3 key molecules including AC019117.2, LINC00638, and hsa_circ_0003972 could be used to predict self-perception changes in RA patients. Herein, our results will provide new insights in RA diagnosis however, the underlying mechanisms need to be further explored.

SUBMITTER: Wen J

PROVIDER: S-EPMC7530568 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Prediction of Self-Perception of Patient in Rheumatoid Arthritis With the Key RNAs Expression Profiles.

Wen Jianting J Liu Jian J Wang Bing B Jiang Hui H Wan Lei L Xin Ling L Sun Yue Y Sun Yanqiu Y Zhang Ying Y Du Xinlei X Wang Xin X Wang Jie J

Frontiers in medicine 20200918

Self-perception in patients is their self-response to sensory stimuli. It is an important aspect of the existence and quality of life among patients. However, the inherent relationship between self-perception and the cellular activity at the molecular level is elusive. In this study, we aimed to explore the association of self-perception with RNA expression profile in patients with rheumatoid arthritis (RA) through computational analysis. We recruited 30 patients clinically diagnosed with RA and ...[more]

PMID: 33072778

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Project description:We examined the gene expression profiles in arthroscopic biopsies retrieved from 10 rheumatoid arthritis patients before and after anti-TNF treatment with infliximab to investigate whether such profiles can be used to predict responses to the therapy, and to study effects of the therapy on the profiles. Responses to treatment were assessed using European League Against Rheumatism response criteria. Three patients were found to be good responders, five patients to be moderate responders and two patients to be nonresponders. The TNF-alpha status of the biopsies from each of the patients before treatment was also investigated immunohistochemically, and it was detected in biopsies from four of the patients, including all three of the good responders. The gene expression data demonstrate that all patients had unique gene expression signatures, with low intrapatient variability between biopsies. The data also revealed significant differences between the good responding and nonresponding patients (279 differentially expressed genes were detected, with a false discovery rate < 0.025). Among the identified genes we found that MMP-3 was significantly upregulated in good responders (log2 fold change, 2.95) compared with nonresponders, providing further support for the potential of MMP-3 as a marker for good responses to therapy. An even more extensive list of 685 significantly differentially expressed genes was found between patients in whom TNF-alpha was found and nonresponders, indicating that TNF-alpha could be an important biomarker for successful infliximab treatment. Significant differences were also observed between biopsies taken before and after anti-TNF treatment, including 115 differentially expressed genes in the good responding group. Interestingly, the effect was even stronger in the group in which TNF-alpha was immunohistochemically detected before therapy. Here, 1,058 genes were differentially expressed, including many that were novel in this context (for example, CXCL3 and CXCL14). Subsequent Gene Ontology analysis revealed that several 'themes' were significantly over-represented that are known to be affected by anti-TNF treatment in inflammatory tissue; for example, immune response (GO:0006955), cell communication (GO:0007154), signal transduction (GO:0007165) and chemotaxis (GO:0006935). No genes reached statistical significance in the moderately responding or nonresponding groups. In conclusion, this pilot study suggests that further investigation is warranted on the usefulness of gene expression profiling of synovial tissue to predict and monitor the outcome of rheumatoid arthritis therapies.

Dataset Information

Prediction of Self-Perception of Patient in Rheumatoid Arthritis With the Key RNAs Expression Profiles.

Publications

Prediction of Self-Perception of Patient in Rheumatoid Arthritis With the Key RNAs Expression Profiles.

Similar Datasets

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