Evidence map›Paper›PMID 37903543›Full record

ArticleAnnals of the rheumatic diseases2024

Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases by cohort-wide immunophenotyping.

Hiroaki Tanaka, Yukinori Okada, Shingo Nakayamada, Yusuke Miyazaki, Kyuto Sonehara, Shinichi Namba, Suguru Honda, Yuya Shirai, Kenichi Yamamoto, Satoshi Kubo and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Annals of the rheumatic diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Review
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  5. Article
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  7. Review
  8. Observational
  9. Article
  10. Pursuing Precision Medicine in Managing Rheumatoid Arthritis.International journal of rheumatic diseases · 2025
    Review
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  12. Article
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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

14 authors at 4 institutions in 1 country.

Hiroaki Tanaka *First Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan.
Yukinori Okada *Department of Statistical Genetics, Osaka University School of Medicine Graduate School of Medicine, Suita, Osaka, Japan yuki-okada@m.u-tokyo.ac.jp tanaka@med.uoeh-u.ac.jp.ORCID http://orcid.org/0000-0002-0311-8472
Shingo NakayamadaFirst Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan.
Yusuke MiyazakiFirst Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan.ORCID http://orcid.org/0000-0001-5692-3881
Kyuto SoneharaDepartment of Statistical Genetics, Osaka University School of Medicine Graduate School of Medicine, Suita, Osaka, Japan.
Shinichi NambaDepartment of Statistical Genetics, Osaka University School of Medicine Graduate School of Medicine, Suita, Osaka, Japan.
Suguru HondaDepartment of Rheumatology, Department of Internal Medicine, Tokyo Women's Medical University, Shinjuku-ku, Tokyo, Japan.ORCID http://orcid.org/0000-0003-4846-3234
Yuya ShiraiDepartment of Statistical Genetics, Osaka University School of Medicine Graduate School of Medicine, Suita, Osaka, Japan.
Kenichi YamamotoDepartment of Statistical Genetics, Osaka University School of Medicine Graduate School of Medicine, Suita, Osaka, Japan.
Satoshi KuboFirst Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan.ORCID http://orcid.org/0000-0001-9693-9263
Katsunori IkariDepartment of Orthopedics, Tokyo Women's Medical University, Tokyo, Japan.
Masayoshi HarigaiDepartment of Rheumatology, Department of Internal Medicine, Tokyo Women's Medical University, Shinjuku-ku, Tokyo, Japan.ORCID http://orcid.org/0000-0002-6418-2603
Koshiro SonomotoFirst Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan.ORCID http://orcid.org/0000-0002-4003-8842
Yoshiya TanakaFirst Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan yuki-okada@m.u-tokyo.ac.jp tanaka@med.uoeh-u.ac.jp.ORCID http://orcid.org/0000-0002-0807-7139
University of Occupational and Environmental Health Japan · JPThe University of Osaka · JPTokyo Women's Medical University · JPRIKEN Center for Integrative Medical Sciences · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveExtracting immunological and clinical heterogeneity across autoimmune rheumatic diseases (AIRDs) is essential towards personalised medicine.

methodsWe conducted large-scale and cohort-wide immunophenotyping of 46 peripheral immune cells using Human Immunology Protocol of comprehensive 8-colour flow cytometric analysis. Dataset consisted of >1000 Japanese patients of 11 AIRDs with deep clinical information registered at the FLOW study, including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). In-depth clinical and immunological characterisation was conducted for the identified RA patient clusters, including associations of inborn human genetics represented by Polygenic Risk Score (PRS).

resultsMultimodal clustering of immunophenotypes deciphered underlying disease-cell type network in immune cell, disease and patient cluster resolutions. This provided immune cell type specificity shared or distinct across AIRDs, such as close immunological network between mixed connective tissue disease and SLE. Individual patient-level clustering dissected patients with AIRD into several clusters with different immunological features. Of these, RA-like or SLE-like clusters were exclusively dominant, showing immunological differentiation between RA and SLE across AIRDs. In-depth clinical analysis of RA revealed that such patient clusters differentially defined clinical heterogeneity in disease activity and treatment responses, such as treatment resistance in patients with RA with SLE-like immunophenotypes. PRS based on RA case-control and within-case stratified genome-wide association studies were associated with clinical and immunological characteristics. This pointed immune cell type implicated in disease biology such as dendritic cells for RA-interstitial lung disease.

conclusionCohort-wide and cross-disease immunophenotyping elucidate clinically heterogeneous patient subtypes existing within single disease in immune cell type-specific manner.

Indexed as

Arthritis, RheumatoidAutoimmune DiseasesLupus Erythematosus, SystemicRheumatic DiseasesGenome-Wide Association StudyHumansImmunophenotypingLupus Erythematosus, SystemicRheumatoid ArthritisScleroderma, SystemicSjogren's SyndromeSpondylitis, Ankylosing

Identifiers

PMID37903543
PMCPMC10850648
OpenAlexW4388034576

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.