Evidence map›Paper›PMID 34162665›Full record

ArticleDiabetes care2021

Islet Autoimmunity and HLA Markers of Presymptomatic and Clinical Type 1 Diabetes: Joint Analyses of Prospective Cohort Studies in Finland, Germany, Sweden, and the U.S.

Vibha Anand, Ying Li, Bin Liu, Mohamed Ghalwash, Eileen Koski, Kenney Ng, Jessica L Dunne, Josefine Jönsson, Christiane Winkler, Mikael Knip and 10 more

Open access · bronzeAbstract read
In one paragraph

Article in Diabetes care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 3 pooled it
8.5field-weighted citation impact, top 2% 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

45 citing papers in PubMed, 3 syntheses or guidelines pooled it, 71 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

20 authors at 10 institutions in 5 countries.

Vibha AnandCenter for Computational Health, IBM T.J. Watson Research Center, Cambridge, MA, and Yorktown Heights, NY anand@us.ibm.com.ORCID https://orcid.org/0000-0001-8605-5712
Ying LiCenter for Computational Health, IBM T.J. Watson Research Center, Cambridge, MA, and Yorktown Heights, NY.
Bin LiuCenter for Computational Health, IBM T.J. Watson Research Center, Cambridge, MA, and Yorktown Heights, NY.
Mohamed GhalwashCenter for Computational Health, IBM T.J. Watson Research Center, Cambridge, MA, and Yorktown Heights, NY.
Eileen KoskiCenter for Computational Health, IBM T.J. Watson Research Center, Cambridge, MA, and Yorktown Heights, NY.
Kenney NgCenter for Computational Health, IBM T.J. Watson Research Center, Cambridge, MA, and Yorktown Heights, NY.
Jessica L DunneJDRF, New York, NY.
Josefine JönssonDepartment of Clinical Sciences Malmö, Lund University/CRC, Skåne University Hospital, Malmö.
Christiane WinklerInstitute of Diabetes Research, Helmholtz Zentrum München German Research Center for Environmental Health, Munich-Neuherberg, Germany.
Mikael KnipTampere Center for Child Health Research, Tampere University Hospital, Tampere, Finland.ORCID https://orcid.org/0000-0003-0474-0033
Jorma ToppariInstitute of Biomedicine and Population Research Centre, University of Turku, and Department of Pediatrics, Turku University Hospital, Turku, Finland.
Jorma IlonenImmunogenetics Laboratory, Institute of Biomedicine, University of Turku, and Clinical Microbiology, Turku University Hospital, Turku, Finland.
Michael B KillianPacific Northwest Research Institute, Seattle, WA.
Brigitte I FrohnertBarbara Davis Center for Diabetes, University of Colorado, Denver, CO.ORCID https://orcid.org/0000-0002-6636-4048
Markus LundgrenInstitute of Diabetes Research, Helmholtz Zentrum München German Research Center for Environmental Health, Munich-Neuherberg, Germany.
Anette-Gabriele ZieglerInstitute of Diabetes Research, Helmholtz Zentrum München German Research Center for Environmental Health, Munich-Neuherberg, Germany.ORCID https://orcid.org/0000-0002-6290-5548
William HagopianPacific Northwest Research Institute, Seattle, WA.ORCID https://orcid.org/0000-0003-2979-0475
Riitta VeijolaPEDEGO Research Unit, Department of Pediatrics, University of Oulu and Oulu University Hospital, Oulu, Finland.
Marian Rewers
T1DI Study Group
IBM (United States) · USHelmholtz Zentrum München · DEPacific Northwest Diabetes Research Institute · USUniversity of Colorado Denver · USUniversity of Turku · FIAin Shams University · EGBreakthrough T1D · USLund University · SEOulu University Hospital · FIUniversity of Helsinki · FI

Funding

University of Colorado Anschutz Medical Campus DRCP30DK116073 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LORI SUSSEL · 2020 to 2026
$10.8M
Natural History of Pre-Diabetic Autoimmunity (DAISY)R01DK032493 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI REWERS, MARIAN J · 1986 to 2024
$9.3M
Natural History of Pre-diabetic Autoimmunity (DAISY)R37DK032493 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI REWERS, MARIAN J · 2001 to 2010
$8.0M
Multiple Autoantigens/Multiple Epitopes of Type 1DMR01DK032083 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI MICHELS, AARON W · 1986 to 2025
$6.9M
ISLET CELL MEMBRANE ANTIBODIES IN DIABTESR01DK026190 · NIDDK · UNIVERSITY OF WASHINGTON · PI HAMPE, CHRISTIANE S · 1986 to 2016
$4.9M
Nutrigenetics & -genomics of Vitamin D and Omega-3 Fatty Acids in Type 1 DiabetesR01DK104351 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI NORRIS, JILL M · 2014 to 2018
$2.9M
MULTIPLE AUTOANTIGENS OF PRETYPE I DMR37DK032083 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI EISENBARTH, GEORGE S · 1992 to 1999
–
NIDDK NIH HHS P30 DK116073NIDDK NIH HHS R01 DK026190NIDDK NIH HHS R01 DK032083NIDDK NIH HHS R01 DK032493NIDDK NIH HHS R01 DK104351NIDDK NIH HHS R37 DK032083NIDDK NIH HHS R37 DK032493
6 · The paper itself

Abstract

objectiveTo combine prospective cohort studies, by including HLA harmonization, and estimate risk of islet autoimmunity and progression to clinical diabetes. RESEARCH DESIGN AND

methodsFor prospective cohorts in Finland, Germany, Sweden, and the U.S., 24,662 children at increased genetic risk for development of islet autoantibodies and type 1 diabetes have been followed. Following harmonization, the outcomes were analyzed in 16,709 infants-toddlers enrolled by age 2.5 years.

resultsIn the infant-toddler cohort, 1,413 (8.5%) developed at least one autoantibody confirmed at two or more consecutive visits (seroconversion), 865 (5%) developed multiple autoantibodies, and 655 (4%) progressed to diabetes. The 15-year cumulative incidence of diabetes varied in children with one, two, or three autoantibodies at seroconversion: 45% (95% CI 40-52), 85% (78-90), and 92% (85-97), respectively. Among those with a single autoantibody, status 2 years after seroconversion predicted diabetes risk: 12% (10-25) if reverting to autoantibody negative, 30% (20-40) if retaining a single autoantibody, and 82% (80-95) if developing multiple autoantibodies. HLA-DR-DQ affected the risk of confirmed seroconversion and progression to diabetes in children with stable single-autoantibody status. Their 15-year diabetes incidence for higher- versus lower-risk genotypes was 40% (28-50) vs. 12% (5-38). The rate of progression to diabetes was inversely related to age at development of multiple autoantibodies, ranging from 20% per year to 6% per year in children developing multipositivity in ≤2 years or >7.4 years, respectively.

conclusionsThe number of islet autoantibodies at seroconversion reliably predicts 15-year type 1 diabetes risk. In children retaining a single autoantibody, HLA-DR-DQ genotypes can further refine risk of progression.

Identifiers

PMID34162665
PMCPMC8929180
OpenAlexW3173682566

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.