Evidence map›Paper›PMID 38714671›Full record

ArticleNature communications2024

Distinct cellular immune responses in children en route to type 1 diabetes with different first-appearing autoantibodies.

Inna Starskaia, Milla Valta, Sami Pietilä, Tomi Suomi, Sirpa Pahkuri, Ubaid Ullah Kalim, Omid Rasool, Emilie Rydgren, Heikki Hyöty, Mikael Knip and 6 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
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  5. Article
  6. Article
  7. Review
  8. Article
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  10. Review
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

16 authors.

Inna Starskaia *Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID http://orcid.org/0000-0003-4349-439X
Milla Valta *Turku Doctoral Programme of Molecular Medicine, University of Turku, Turku, Finland.ORCID http://orcid.org/0000-0001-6674-4182
Sami Pietilä *Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID http://orcid.org/0000-0002-3825-0967
Tomi Suomi *Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID http://orcid.org/0000-0003-3639-979X
Sirpa PahkuriTurku Doctoral Programme of Molecular Medicine, University of Turku, Turku, Finland.ORCID http://orcid.org/0000-0003-0234-060X
Ubaid Ullah KalimTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID http://orcid.org/0000-0002-2539-2296
Omid RasoolTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID http://orcid.org/0000-0002-1286-4725
Emilie RydgrenTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.
Heikki HyötyFaculty of Medicine and Health Technology, Tampere University, and Fimlab Laboratories, Tampere, Finland.
Mikael KnipResearch Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.ORCID http://orcid.org/0000-0003-0474-0033
Riitta VeijolaDepartment of Pediatrics, Research Unit of Clinical Medicine, Medical Research Centre, Oulu University Hospital and University of Oulu, Oulu, Finland.ORCID http://orcid.org/0000-0002-6557-270X
Jorma IlonenImmunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland.
Jorma ToppariInFLAMES Research Flagship Center, University of Turku, Turku, Finland.
Johanna LempainenImmunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland. johanna.lempainen@utu.fi.ORCID http://orcid.org/0000-0001-9893-1468
Laura L EloTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland. laura.elo@utu.fi.ORCID http://orcid.org/0000-0001-5648-4532
Riitta LahesmaaTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland. rilahes@utu.fi.ORCID http://orcid.org/0000-0002-4782-9567

Funding

European Commission (EC) BMH4-CT98-3314JDRF 1-SRA-2016-342-M-R, 1-SRA-2019-732-M-B, 3-SRA-2020-955-S-B
6 · The paper itself

Abstract

Previous studies have revealed heterogeneity in the progression to clinical type 1 diabetes in children who develop islet-specific antibodies either to insulin (IAA) or glutamic acid decarboxylase (GADA) as the first autoantibodies. Here, we test the hypothesis that children who later develop clinical disease have different early immune responses, depending on the type of the first autoantibody to appear (GADA-first or IAA-first). We use mass cytometry for deep immune profiling of peripheral blood mononuclear cell samples longitudinally collected from children who later progressed to clinical disease (IAA-first, GADA-first, ≥2 autoantibodies first groups) and matched for age, sex, and HLA controls who did not, as part of the Type 1 Diabetes Prediction and Prevention study. We identify differences in immune cell composition of children who later develop disease depending on the type of autoantibodies that appear first. Notably, we observe an increase in CD161 expression in natural killer cells of children with ≥2 autoantibodies and validate this in an independent cohort. The results highlight the importance of endotype-specific analyses and are likely to contribute to our understanding of pathogenic mechanisms underlying type 1 diabetes development.

Indexed as

AutoantibodiesDiabetes Mellitus, Type 1Glutamate DecarboxylaseImmunity, CellularAdolescentChildChild, PreschoolDisease ProgressionFemaleHumansInsulinIslets of LangerhansKiller Cells, NaturalLeukocytes, MononuclearMaleAutoantibodiesGlutamate DecarboxylaseInsulin

Identifiers

PMID38714671
PMCPMC11076468

What OpenQuestion holds

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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.