ArticleBioMed research international2020
RNA Sequencing for Gene Expression Profiles in Peripheral Blood Mononuclear Cells with Ankylosing Spondylitis RNA.
Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Identification of potential biomarkers and therapeutic targets for osteoarthritis associated with arginine and proline metabolism based on transcriptome sequencing and bioinformatics.Frontiers in genetics · 2026Article
- From advanced imaging to molecular insights: the state of the art in omics for axial spondyloarthritis.Therapeutic advances in musculoskeletal disease · 2025Review
- RNA sequencing and bioinformatics analysis of differentially expressed genes in the peripheral serum of ankylosing spondylitis patients.Journal of orthopaedic surgery and research · 2023Article
- Exploring the diagnostic markers of essential tremor: A study based on machine learning algorithms.Open life sciences · 2023Article
- Multimerin-1 and cancer: a review.Bioscience reports · 2022Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Several previous studies have attempted to investigate the regulatory mechanisms underlying gene expression in ankylosing spondylitis (AS). However, the specific molecular pathways underlying this condition remain unclear. Previous research used next-generation RNA sequencing to identify a series of differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMCs) when compared between patients with AS and healthy controls, thus implying that these DEGs may be related to AS. Furthermore, by screening these DEGS, it may be possible to facilitate clinical diagnosis and optimize treatment strategies. In order to test this hypothesis, we recruited 15 patients with AS and 15 healthy controls. We randomly selected five subjects from each group of patients for RNA sequencing analysis. Sequence reads were generated by an Illumina HiSeq2500 platform and mapped on to the human reference genome using HISAT2. We successfully identified 973 significant DEGs (
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Registered trials
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