Evidence map›Paper›PMID 41360390›Full record

ArticleDiabetes & metabolism journal2026

Evaluation of Sex-Stratified Polygenic Risk Scores for Type 2 Diabetes Mellitus and Glycemic Traits in the Framingham Heart Study.

Ningyuan Wang, Yixin Zhang, Philip Schroeder, Alicia Huerta-Chagoya, Ravi Mandla, James B Meigs, Alisa K Manning, Ching-Ti Liu, Josée Dupuis, Josep M Mercader

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetes & metabolism journal, 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
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Ningyuan WangDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Yixin ZhangDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Philip SchroederPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Alicia Huerta-ChagoyaPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Ravi MandlaPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
James B MeigsPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Alisa K ManningPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Ching-Ti LiuDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA. ctliu@bu.edu.
Josée DupuisDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA. josee.dupuis3@mcgill.ca.
Josep M MercaderPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. mercader@broadinstitute.org.

Funding

TOPMed Omics of Type 2 Diabetes and Quantitative TraitsUM1DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · 2022 to 2025
$3.1M
GEneration and assessment of Multi-omic informed Subtypes of Type 2 Diabetes in Diverse Populations (GEMS-T2D)U01DK140757 · MASSACHUSETTS GENERAL HOSPITAL · 2025 to 2025
$784k
Cataloging multi-ancestry 'omic readouts of the environmental and genetic determinants of type 2 diabetesR01DK137993 · HARVARD MEDICAL SCHOOL · 2025 to 2025
$670k
American Diabetes Association 11-22-ICTSPM-16Foundation for the National Institutes of HealthMedical University of BialystokMinistry of Science and Higher EducationNIDDK NIH HHS R01DK137993NIDDK NIH HHS U01 DK140757NIDDK NIH HHS UM1DK078616Novo Nordisk Foundation NNF21SA0072102
6 · The paper itself

Abstract

backgruoundDiabetes is a multifactorial disease with significant genetic predisposition. Polygenic risk scores (PRS) have been developed to estimate an individual's genetic risk of a disease. Traditionally, PRS utilize sex-combined genome-wide association studies (GWAS) due to the limited availability of sex-stratified summary statistics. This study explores sex-dimorphic genetic effects and evaluates the potential benefits of incorporating sex-stratified effects in PRS for type 2 diabetes mellitus (T2DM) and glycemic traits by comparing PRS performance derived from sex-combined versus sex-stratified GWAS.

methodsWe performed a sex-heterogeneity test across sex-specific GWAS and identified nine signals with sex-dimorphic effects for T2DM. PRS[sex-combined] and PRS[sex-stratified] were developed using sex-combined and sex-stratified GWAS results for T2DM (41,444 cases and 354,539 controls), fasting glucose (n=120,595) and fasting insulin (n=98,210). We evaluated these PRS models in 8,379 participants (1,303 cases and 7,076 controls) from the Framingham Heart Study not included in the PRS derivation.

resultsOur findings suggest that sex-combined PRS currently offer better predictive performance for T2DM and glycemic traits.

conclusionThese results highlight the need for larger sex-stratified studies and the optimization of sex-stratified risk models for clinical practice.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 2Multifactorial InheritanceAgedFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreGenome-Wide Association StudyHumansInsulinMaleMiddle AgedPolymorphism, Single NucleotideRisk FactorsSex FactorsBlood GlucoseInsulinBlood glucoseDiabetes mellitus, type 2Genetic predisposition to diseaseGenetic risk scoreInsulin resistanceSex factors

Identifiers

PMID41360390
PMCPMC13366129

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.