Evidence map›Paper›PMID 23418382›Full record

ArticleThe Journal of rheumatology2013

New centromere autoantigens identified in systemic sclerosis using centromere protein microarrays.

Guang Song, Chaojun Hu, Heng Zhu, Li Wang, Fengchun Zhang, Yongzhe Li, Lin Wu

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of rheumatology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
0.4field-weighted citation impact, top 34% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Systemic Sclerosis-Specific Antibodies: Novel and Classical Biomarkers.Clinical reviews in allergy & immunology · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 2 countries.

Guang SongBeijing Institute of Genomics, Chinese Academy of Sciences, Beijing, PR China.
Chaojun Hu
Heng Zhu
Li Wang
Fengchun Zhang
Yongzhe Li
Lin Wu
Peking Union Medical College Hospital · CNBeijing Institute of Genomics · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNHigh Throughput Biology (United States) · USUniversity of Chinese Academy of Sciences · CN

Funding

TCP5: ACTIVE SITE LABELING REAGENT FOR ACETYLTRANSFERASESU54RR020839 · NCRR · JOHNS HOPKINS UNIVERSITY · PI BOEKE, JEF D · 2004 to 2011
$27.4M
Monospecific monoclonal antibodies against human transcription factorsU54HG006434 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI BLACKSHAW, SETH, ZHU, HENG · 2011 to 2015
$13.8M
Proteome Characterization Center: A Genoproteomics Pipeline for Cance ResearchU24CA160036 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI, ZHANG, HUI · 2011 to 2016
$10.7M
Networks, Pathways and Dynamics of Lysine ModificationU54GM103520 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BADER, JOEL S. · 2012 to 2013
$7.0M
Visual Programming Tool for Integrated Gene/Protein Networks in Cancer ResearchR44CA125807 · NCI · INCOGEN, INC. · PI SASINOWSKI, MACIEK · 2008 to 2011
$3.4M
DNA-Binding Activity of Human Transcription FactorsR01GM076102 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI ZHU, HENG · 2006 to 2014
$2.6M
NCI NIH HHS R44 CA125807NCI NIH HHS U24 CA160036NCRR NIH HHS U54 RR020839NHGRI NIH HHS U54 HG006434NIGMS NIH HHS R01 GM076102NIGMS NIH HHS U54 GM103520
6 · The paper itself

Abstract

objectiveTo identify novel centromere protein (CENP) targets of anticentromere antibodies (ACA), and to investigate their association with clinical manifestations of systemic sclerosis (SSc).

methodsA CENP-focused protein microarray was fabricated by spotting 14 purified CENP. These microarrays were individually incubated with 35 ACA-positive SSc sera and 20 ACA-negative healthy control samples. Newly identified CENP autoantigens with high sensitivities were selected for validation and characterization.

resultsStatistical analysis revealed 11 CENP are potential target antigens of ACA in patients with SSc. Of them, 5 [CENP-P, CENP-Q, CENP-M (isoform I), CENP-J, and CENP-T] are novel, among which CENP-P and CENP-Q showed high sensitivities in ACA-positive SSc sera of 34.3% and 28.6%, respectively. Subsequently, 186 SSc sera (35 ACA-positives and 151 negatives), 69 ACA-positive sera from other various autoimmune diseases (primary Sjögren syndrome, systemic lupus erythematosus, rheumatoid arthritis, and primary biliary cirrhosis), and 31 healthy sera were assayed for the presence of anti-CENP-P and -Q autoantibodies by ELISA followed by Western blotting analysis. CENP-P and -Q autoantibodies were detected in ACA-positive sera of various disease groups; among them, SSc showed the highest detection rate. Anti-CENP-P was also found in 9 of the 151 ACA-negative sera. Analyses of the correlation with clinical information showed anti-CENP-P-positive patients had higher levels of IgG, IgA, and erythrocyte sedimentation rate among the ACA-positive cohort and were more vulnerable to renal disease in the ACA-negative patients with SSc. Regardless of ACA status, anti-CENP-P or Q-negative patients seem to be predominantly affected by interstitial lung disease.

conclusionCENP-P and CENP-Q were identified as novel ACA autoantigens by CENP microarray assays followed by validation of ELISA and Western blotting. Both of them have prognostic utility for interstitial lung disease. CENP-P was associated with renal disease in an ACA-negative cohort.

Indexed as

AdultArthritis, RheumatoidAutoantibodiesAutoantigensCentromereFemaleHumansLiver Cirrhosis, BiliaryLupus Erythematosus, SystemicMaleMiddle AgedScleroderma, SystemicSjogren's SyndromeTissue Array AnalysisAutoantibodiesAutoantigens

Identifiers

PMID23418382
PMCPMC3962773
OpenAlexW2096844390

What OpenQuestion holds

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LicenceTDM
Read underepoch 390

Registered trials

None linked

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.