ArticleOncotarget2018
Comprehensive analysis of gene expression and DNA methylation datasets identify valuable biomarkers for rheumatoid arthritis progression.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Hypomethylation of the HumanArchives of Iranian medicine · 2026Article
- Multidimensional regulatory mechanisms and translational potential of epigenetic networks in the rheumatoid arthritis disease course.Frontiers in immunology · 2026Review
- High Throughput Genetic Characterisation of Caucasian Patients Affected by Multi-Drug Resistant Rheumatoid or Psoriatic Arthritis.Journal of personalized medicine · 2022Article
- Identification of a Prognostic Model Based on Fatty Acid Metabolism-Related Genes of Head and Neck Squamous Cell Carcinoma.Frontiers in genetics · 2022Article
- Potential clinical biomarkers in rheumatoid arthritis with an omic approach.Auto- immunity highlights · 2021Review
- Comprehensive analysis of gene expression and DNA methylation for preeclampsia progression.Journal of the Chinese Medical Association : JCMA · 2021Article
- IDO and Kynurenine Metabolites in Peripheral and CNS Disorders.Frontiers in immunology · 2020Review
- Review
- Polyamine Metabolism and Gene Methylation in Conjunction with One-Carbon Metabolism.International journal of molecular sciences · 2018Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rheumatoid arthritis (RA) represents a common systemic autoimmune disease which lays chronic and persistent pain on patients. The purpose of our study is to identify novel RA-related genes and biological processes/pathways. All the datasets of this study, including gene expression and DNA methylation datasets of RA and OA samples, were obtained from the free available database, i.e. Gene Expression Omnibus (GEO). We firstly identified the differentially expressed genes (DEGs) between RA and OA samples through the limma package of R programming software followed by the functional enrichment analysis in the Database for Annotation, Visualization and Integrated Discovery (DAVID) for the exploring of potential involved biological processes/pathways of DEGs. For DNA methylation datasets, we used the IMA package for their normalization and identification of differential methylation genes (DMGs) in RA compared with OA samples. Comprehensive analysis of DEGs and DMGs was also conducted for the identification of valuable RA-related biomarkers. As a result, we obtained 394 DEGs and 363 DMGs in RA samples with the thresholds of |log2fold change|> 1 and
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.