Evidence map›Paper›PMID 35559025›Full record

ArticleFrontiers in genetics2022

A Polygenic Score for Type 2 Diabetes Improves Risk Stratification Beyond Current Clinical Screening Factors in an Ancestrally Diverse Sample.

James R Ashenhurst, Olga V Sazonova, Olivia Svrchek, Stacey Detweiler, Ryosuke Kita, Liz Babalola, Matthew McIntyre, Stella Aslibekyan, Pierre Fontanillas, Suyash Shringarpure and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

18 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Integrating Polygenic Risk Scores (PRS) for Personalized Diabetes Care: Advancing Clinical Practice with Tailored Pharmacological Approaches.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Review
  10. Article
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  18. Observational
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

13 authors at 1 institution in 1 country.

James R Ashenhurst23andMe, Inc., Sunnyvale, CA, United States.
Olga V Sazonova23andMe, Inc., Sunnyvale, CA, United States.
Olivia Svrchek23andMe, Inc., Sunnyvale, CA, United States.
Stacey Detweiler23andMe, Inc., Sunnyvale, CA, United States.
Ryosuke Kita23andMe, Inc., Sunnyvale, CA, United States.
Liz Babalola23andMe, Inc., Sunnyvale, CA, United States.
Matthew McIntyre23andMe, Inc., Sunnyvale, CA, United States.
Stella Aslibekyan23andMe, Inc., Sunnyvale, CA, United States.
Pierre Fontanillas23andMe, Inc., Sunnyvale, CA, United States.
Suyash Shringarpure23andMe, Inc., Sunnyvale, CA, United States.
23andMe Research Team
Jeffrey D Pollard23andMe, Inc., Sunnyvale, CA, United States.
Bertram L Koelsch23andMe, Inc., Sunnyvale, CA, United States.
23andMe (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A substantial proportion of the adult United States population with type 2 diabetes (T2D) are undiagnosed, calling into question the comprehensiveness of current screening practices, which primarily rely on age, family history, and body mass index (BMI). We hypothesized that a polygenic score (PGS) may serve as a complementary tool to identify high-risk individuals. The T2D polygenic score maintained predictive utility after adjusting for family history and combining genetics with family history led to even more improved disease risk prediction. We observed that the PGS was meaningfully related to age of onset with implications for screening practices: there was a linear and statistically significant relationship between the PGS and T2D onset (-1.3 years per standard deviation of the PGS). Evaluation of U.S. Preventive Task Force and a simplified version of American Diabetes Association screening guidelines showed that addition of a screening criterion for those above the 90th percentile of the PGS provided a small increase the sensitivity of the screening algorithm. Among T2D-negative individuals, the T2D PGS was associated with prediabetes, where each standard deviation increase of the PGS was associated with a 23% increase in the odds of prediabetes diagnosis. Additionally, each standard deviation increase in the PGS corresponded to a 43% increase in the odds of incident T2D at one-year follow-up. Using complications and forms of clinical intervention (i.e., lifestyle modification, metformin treatment, or insulin treatment) as proxies for advanced illness we also found statistically significant associations between the T2D PGS and insulin treatment and diabetic neuropathy. Importantly, we were able to replicate many findings in a Hispanic/Latino cohort from our database, highlighting the value of the T2D PGS as a clinical tool for individuals with ancestry other than European. In this group, the T2D PGS provided additional disease risk information beyond that offered by traditional screening methodologies. The T2D PGS also had predictive value for the age of onset and for prediabetes among T2D-negative Hispanic/Latino participants. These findings strengthen the notion that a T2D PGS could play a role in the clinical setting across multiple ancestries, potentially improving T2D screening practices, risk stratification, and disease management.

Indexed as

consumer genomicsdiabetes screeninggenetic riskpolygenic scoretype 2 diabees

Identifiers

PMID35559025
PMCPMC9086969
OpenAlexW4224981747

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.