Evidence map›Paper›PMID 42443500›Full record

ArticleCommunications medicine2026

Pan-disease blood protein profiles of rheumatic autoimmune diseases.

Josefin Kenrick, Charlotta Preger, María Bueno Álvez, Maria Alejandra Ulloa, Göran Bergström, Antonella Notarnicola, Begum Horuluoglu, Angeles S Galindo-Feria, Anna Smed-Sörensen, Anna Färnert and 16 more

Abstract read
In one paragraph

Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

26 authors.

Josefin KenrickDepartment of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-0110-5192
Charlotta PregerDepartment of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-1342-9135
María Bueno ÁlvezDepartment of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-2669-7796
Maria Alejandra UlloaDepartment of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0009-0005-0009-9340
Göran BergströmDepartment of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.ORCID http://orcid.org/0000-0003-4289-5722
Antonella NotarnicolaDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Begum HoruluogluDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Angeles S Galindo-FeriaDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Anna Smed-SörensenCenter for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-6966-7039
Anna FärnertDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Anna Norrby-TeglundDepartment of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-9372-1795
Iva GunnarssonDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Marie Wahren-HerleniusDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-0915-7245
Marie HolmqvistDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Leonid PadyukovDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-2950-5670
Karine CheminDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-2597-7809
Lina Marcela Diaz-GalloDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Ingrid E LundbergDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Elisabet SvenungssonDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-3396-3244
Vivianne MalmströmDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-9251-8082
Lars KlareskogDivision of Rheumatology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-9601-6186
Sofia BergströmDepartment of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-2910-4754
Mathias UhlénDepartment of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-4858-8056
Peter NilssonDepartment of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-4657-8532
Fredrik Edfors *Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-0017-7987
Elisa Pin *Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden. elisa.pin@scilifelab.se.ORCID http://orcid.org/0000-0002-2158-2674

Funding

Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation) KAW2022.0318
6 · The paper itself

Abstract

backgroundSystemic autoimmune rheumatic diseases (SARDs) are a heterogeneous group of autoimmune conditions characterized by immune system dysregulation leading to chronic inflammation and tissue damage. The overlapping clinical manifestations make differential diagnosis challenging, highlighting the need for novel biomarkers to facilitate early diagnosis, stratification, and personalized treatment.

methodsFive SARDs including idiopathic inflammatory myopathies (n = 210), rheumatoid arthritis (n = 84), systemic sclerosis (n = 100), Sjögren disease (n = 99), and systemic lupus erythematosus (n = 99), as well as healthy controls (n = 400) and controls with acute infectious diseases (n = 218) were selected for plasma protein profiling using Olink Explore 1536. Differential abundance analysis and machine learning were used to identify proteins with both known and novel association to SARDs.

resultsThe five SARDs share hundreds of proteins with consistently altered abundance compared to both healthy and infectious controls, reflecting common underlying molecular dysregulation. Despite the overlap, we identify multiple proteins with higher abundance specific to individual SARDs. Machine learning further enables accurate classification of the five SARDs, identifying a panel of 48 proteins with high discriminatory performance, several of which are also supported by differential abundance analysis.

conclusionsAltogether, this explorative cross-sectional study demonstrates the importance of a pan-disease approach, including also infectious and healthy controls, to identify robust and disease-informative protein panels for improved classification of SARDs. Protein levels from this study are available open access through the Human Protein Atlas, facilitating further plasma proteome research on autoimmune disease.

Identifiers

PMID42443500
PMCPMC13365237

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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.