Evidence map›Paper›PMID 35603173›Full record

ArticleFrontiers in immunology2022

Autoantibody Landscape Revealed by Wet Protein Array: Sum of Autoantibody Levels Reflects Disease Status.

Kazuki M Matsuda, Ayumi Yoshizaki, Kei Yamaguchi, Eriko Fukuda, Taishi Okumura, Koji Ogawa, Chihiro Ono, Yuta Norimatsu, Hirohito Kotani, Teruyoshi Hisamoto and 8 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

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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

18 authors at 2 institutions in 1 country.

Kazuki M MatsudaDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Ayumi YoshizakiDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Kei YamaguchiMolecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
Eriko FukudaCellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
Taishi OkumuraMolecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
Koji OgawaMolecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
Chihiro OnoMolecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
Yuta NorimatsuDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Hirohito KotaniDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Teruyoshi HisamotoDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Ruriko KawanabeDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Ai KuzumiDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Takemichi FukasawaDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Satoshi EbataDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Takuya MiyagawaDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Asako Yoshizaki-OgawaDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Naoki GoshimaMolecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
Shinichi SatoDepartment of Dermatology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
The University of Tokyo · JPNational Institute of Advanced Industrial Science and Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autoantibodies are found in various pathological conditions such as autoimmune diseases, infectious diseases, and malignant tumors. However their clinical implications have not yet been fully elucidated. Herein, we conducted proteome-wide autoantibody screening and quantification with wet protein arrays consisting of proteins synthesized from proteome-wide human cDNA library (HuPEX) maintaining their three-dimensional structure. A total of 565 autoantibodies were identified from the sera of three representative inflammatory disorders (systemic sclerosis, psoriasis, and cutaneous arteritis). Each autoantibody level either positively or negatively correlated with serum levels of C-reactive protein, the best-recognized indicator of inflammation. In particular, we discovered total levels of a subset of autoantibodies correlates with the severity of clinical symptoms. From the sera of malignant melanoma, 488 autoantibodies were detected. Notably, patients with metastases had increased overall autoantibody production compared to those with tumors limiting to the primary site. Collectively, proteome-wide screening of autoantibodies using the

Indexed as

Autoimmune DiseasesProtein Array AnalysisAutoantibodiesBiomarkersHumansProteomeAutoantibodiesBiomarkersProteomeautoantibodyautoimmunityinflammatory diseasemalignancyprotein array

Identifiers

PMID35603173
PMCPMC9114879
OpenAlexW4225383425

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.