Evidence map›Paper›PMID 41630906›Full record

ArticleiScience2026

Exploration of immune phenotypes in self-sampling citizens.

Leo Dahl, Annika Bendes, María Bueno Álvez, Vincent Albrecht, Hooman Aghelpasand, Sophia Björkander, Simon Kebede Merid, Anja Mezger, Max Käller, Claudia Fredolini and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

17 authors.

Leo DahlSciLifeLab, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden.
Annika BendesSciLifeLab, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden.
María Bueno ÁlvezSciLifeLab, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden.
Vincent AlbrechtSciLifeLab, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden.
Hooman AghelpasandSciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden.
Sophia BjörkanderDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
Simon Kebede MeridDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
Anja MezgerSciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden.
Max KällerSciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden.
Claudia FredoliniSciLifeLab, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden.
Åsa Torinsson NaluaiInstitute of Biomedicine, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
Olof BeckDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Erik MelénDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
Stefan BauerTUM Technical University of Munich, Munich, Germany.
Magnus GisslénDepartment of Infectious Diseases, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.
Niclas RoxhedDepartment of Micro and Nanosystems, KTH Royal Institute of Technology Stockholm, Stockholm, Sweden.
Jochen M SchwenkSciLifeLab, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blood proteins have provided essential insights into how humans responded to the recent pandemic. To expand our understanding beyond patients seeking medical care, we conducted a citizen-centric survey with 2,000 random residents (age: 18-69 years) from Sweden's two largest cities in 2021. With self-sampled dried blood spots (DBS) and health information from 437 (22%) volunteers, we performed multi-analyte COVID-19 serology, measured autoantibodies (AAbs) against 22 interferons, and quantified 502 circulating low-abundant immune-related blood proteins. Antibody assays confirmed self-reported infections (26%) and vaccinations (40%), showed timing-dependent discrepancies in the immune response, and revealed anti-type I interferon AAbs co-occurring frequently alongside natural infections. Proteomics data added plausible mechanistic insights into cell-mediated processes: data-driven analyses revealed 24% of participants presented deviating immune phenotypes linked to infections, immunity, respiratory effects, and age. Multi-molecular DBS analysis of random layperson samples captured the broader spectrum of immune system states, adding relevant insights for clinical and public health investigations.

Indexed as

Health sciences

Identifiers

PMID41630906
PMCPMC12860695

What OpenQuestion holds

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LicenceCC BY
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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.