In one paragraphArticle in medRxiv : the preprint server for health sciences, 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
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
21 authors.
Stella NamDiabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-9049-2680 Raymond J KreienkampDiabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-1683-323X Ravi MandlaGraduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-0782-0138 Huy TranEndeavor Health, Evanston, IL, USA.
Katherine TaylorPrograms in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.
Alicia Huerta-ChagoyaDiabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0001-6218-3904 Jun WeiEndeavor Health, Evanston, IL, USA.
Jianfeng XuEndeavor Health, Evanston, IL, USA.
Bogdan PasaniucDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Jose C FlorezDiabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-1730-9325 Alisa K ManningPrograms in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.ORCID 0000-0003-0247-902X Josep M MercaderDiabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0001-8494-3660 Miriam S UdlerDiabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0003-3824-9162 Aaron J DeutschDiabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0001-6750-5335 Funding
Diabetes-Docs: Physician-Scientist Career Development Program (DiabDocs)K12DK133995 · NIDDK · STANFORD UNIVERSITY · PI LINDA A DIMEGLIO, David Matthew Maahs · 2022 to 2026
$16.0MDevelopment of Polygenic Risk Scores for Diabetes and Complications across the Life-Span in Populations of Multiple AncestriesU01HG011723 · NHGRI · BROAD INSTITUTE, INC. · PI Alisa Knodle Manning, Josep Maria Mercader · 2021 to 2026
$5.7MMulti-Ancestry Genetic Analysis of Type 1 Diabetes and Related ConditionsK23DK140643 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Aaron Jonathan Deutsch · 2024 to 2026
$576kNHGRI NIH HHS U01 HG011723NIDDK NIH HHS K12 DK133995NIDDK NIH HHS K23 DK140643
6 · The paper itselfAbstract
Most polygenic scores (PS) for type 1 diabetes were developed using European (EUR) ancestry datasets, limiting performance in non-European (non-EUR) populations. We evaluated novel type 1 diabetes PS across diverse populations to assess whether newer models improve prediction in underrepresented populations. Seven type 1 diabetes PS (T1D GRS2, T1D GRS2', T1D GRS
Identifiers
PMID42818433
PMCPMC13622736
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