ArticleClinical and translational science2015
Quantitative Proteomic Analysis of Peripheral Blood Mononuclear Cells in Ankylosing Spondylitis by iTRAQ.
Article in Clinical and translational science, 2015. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 23 citations in OpenAlex.
- From advanced imaging to molecular insights: the state of the art in omics for axial spondyloarthritis.Therapeutic advances in musculoskeletal disease · 2025Review
- Global Proteomic Analyses Reveals Abnormal Immune Regulation in Patients With New Onset Ankylosing Spondylitis.Frontiers in immunology · 2022Article
- Serum Antigenome Profiling Reveals Diagnostic Models for Rheumatoid Arthritis.Frontiers in immunology · 2022Article
- Biomarker development for axial spondyloarthritis.Nature reviews. Rheumatology · 2020Review
- Molecular Biology Approaches to Understanding Spondyloarthritis.Rheumatic diseases clinics of North America · 2020Review
- Article
- Proteomic analysis of human synovial fluid reveals potential diagnostic biomarkers for ankylosing spondylitis.Clinical proteomics · 2020Article
- Biomarkers for Diagnosis of Axial Spondyloarthritis, Disease Activity, Prognosis, and Prediction of Response to Therapy.Frontiers in immunology · 2019Review
- Expression and Metabolomic Profiling in Axial Spondyloarthritis.Current rheumatology reports · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study was designed to identify and quantify the different proteins expression levels in ankylosing spondylitis (AS) and to explore the pathogenesis of AS. We performed isobaric tags for relative and absolute quantitation (iTRAQ) coupled with multiple chromatographic fractionation and tandem mass spectrometry to detect the proteins profiling in peripheral blood mononuclear cells (PBMCs) from AS patients and healthy controls. Mascot software and the International Protein Index and the Gene Ontology (GO) database were used to conduct the bioinformatics analysis. The differentially expressed proteins were validated by enzyme-linked immunosorbent assay (ELISA). A total of 1,232 proteins were identified by iTRAQ, of which 183 showed differential expression and 18 differentially expressed proteins were acute phase reactants. Upon mapping of the differentially expressed proteins to GO database, we found four differentially expressed proteins involved in the biological process of cell killing, including up-regulated cathepsin G (CTSG), neutrophil defensin3 (DEFA3), protein tyrosine phosphatase receptor type C (PTPRC), and down-regulated peroxiredoxin-1(PRDX1),which were consistent with the verified results of ELISA. Our proteomic analyses suggested that the proteins involved in the biological process of cell killing might play an important role in the pathogenesis of AS.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.