Evidence map›Paper›PMID 39171755›Full record

ArticleJournal of diabetes investigation2025

Validation of GenProb-T1D and its clinical utility for differentiating types of diabetes in a biobank from a US healthcare system.

Liana K Billings, Zhuqing Shi, Ashley J Mulford, Jun Wei, Huy Tran, Annabelle Ashworth, S Lilly Zheng, Henry M Dunnenberger, Peter J Hulick, Alan R Sanders and 1 more

Abstract readValidation Study
In one paragraph

Article in Journal of diabetes investigation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Liana K BillingsEndeavor Health, Evanston, IL, USA.
Zhuqing ShiEndeavor Health, Evanston, IL, USA.
Ashley J MulfordEndeavor Health, Evanston, IL, USA.
Jun WeiEndeavor Health, Evanston, IL, USA.
Huy TranEndeavor Health, Evanston, IL, USA.
Annabelle AshworthEndeavor Health, Evanston, IL, USA.
S Lilly ZhengEndeavor Health, Evanston, IL, USA.
Henry M DunnenbergerEndeavor Health, Evanston, IL, USA.
Peter J HulickEndeavor Health, Evanston, IL, USA.
Alan R SandersEndeavor Health, Evanston, IL, USA.
Jianfeng XuEndeavor Health, Evanston, IL, USA.ORCID https://orcid.org/0000-0002-1343-8752

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atypical diabetes with overlapping clinical features of type 1 (T1D) and type 2 (T2D) is common and challenging diagnostically and for implementing effective treatment. Here, we validate a recently reported genetic probability of type 1 diabetes (GenProb-T1D) from the UK Biobank (UKB) for differentiating type 1 diabetes and type 2 diabetes in a diabetes patient cohort from a healthcare system-based biobank in the USA. Among 3,363 diabetes patients, we confirmed the performance of GenProb-T1D in differentiating typical type 1 diabetes vs type 2 diabetes. Furthermore, for 359 atypical diabetes patients, those with GenProb-T1D higher than the pre-defined cutoff derived from the UKB had clinical presentations more consistent with that of typical type 1 diabetes. Similar findings were found in participants of European and non-European ancestries. This study provides necessary validation to translate GenProb-T1D into genetic testing in a multi-ancestry cohort. Measuring underlying genetic susceptibility of type 1 diabetes and type 2 diabetes can supplement current clinical tools for earlier and more accurate diagnoses of diabetes.

Indexed as

Biological Specimen BanksDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2AdultAgedCohort StudiesDiagnosis, DifferentialFemaleGenetic Predisposition to DiseaseGenetic TestingHumansMaleMiddle AgedUnited Statesdiabetes mellitispolygenic

Identifiers

PMID39171755
PMCPMC11693536

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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.