Partitioned polygenic scores show mechanistic heterogeneity in type 2 diabetes and hypertension comorbidity
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- Title
- Partitioned polygenic scores show mechanistic heterogeneity in type 2 diabetes and hypertension comorbidity
- Creators
- Vincent Pascat - Université de LilleLiudmila Zudina - University of Surrey, MedicineLucas Maurin - Université de LilleAnna Ulrich - Imperial College LondonJared G. Maina - Université de LilleAyse Demirkan - University of Surrey, School of BiosciencesZhanna Balkhiiarova (Author) - University of Surrey, School of BiosciencesIgor Pupko - University of SurreyYevheniya Sharhorodska - University of FerraraFrançois Pattou - European Genomic Institute for DiabetesB Staels - Université de LilleMarika Kaakinen - Imperial College LondonAmélie Bonnefond - Imperial College LondonPatricia Munroe - Queen Mary University of LondonPhilippe Froguel - Imperial College LondonInga Prokopenko (Corresponding Author) - University of Surrey, School of Biosciences
- Publication Details
- Nature Communications, Vol.17(1), 1446
- Publisher
- Nature
- Number of pages
- 14
- Publication Date
- 09/02/2026
- Grants
- PreciDIAB, ANR-18-IBHU-0001, Agence Nationale de la Recherche (France, Paris) - ANRDiabetes UK Research Grant, 20/0006307, Diabetes UK (United Kingdom, London)UKRI, EP/Z535072/1), UKRI Horizon Europe funding guaranteeBritish Academy, RaR\100084, British Academy (United Kingdom, London)
- Grant note
- Agence Nationale de la Recherche (French National Research Agency): ANR-18-IBHU-0001
This research has been conducted using the UK Biobank Resource under application number 236. This project was in part funded by the Agence Nationale de la Recherche under the Programme d'Investissement d'Avenir (PreciDIAB, ANR-18-IBHU-0001 and RHU PreciNASH ANR-16-RHUS-0006), by the European Union through the "Fonds Europeen de Developpement Regional" (FEDER), by the "Conseil Regional des Hauts-de-France" (Hauts-de-France Regional Council), by the "Metropole Europeenne de Lille" (MEL, European Metropolis of Lille), and by the European Research Council (ERC OpiO - 101043671, to A.B.). I.Pr. and Z.B. were in part funded by the Diabetes UK (BDA number: 20/0006307), UKRI (EP/Z535072/1), European Foundation for the Study of Diabetes (EFSD), and Novo Nordisk A/S Programme for Diabetes Research in Europe-2025. The research of Y.S. was funded by The British Academy (RaR\100084). The authors would like to thank all the investigators from different consortia that built and shared the GWAS meta-analysis, eQTLs, and scATAC-seq atlases used in this study, as well as the UK Biobank participants and dedicated staff.
- Identifiers
- 991095128702346; WOS:001685458900002
- Academic Unit
- Surrey Institute for People-Centred AI; School of Biosciences
- Language
- English
- Resource Type
- Journal article