| Title: | Partitioned polygenic scores show mechanistic heterogeneity in type 2 diabetes and hypertension comorbidity |
| Journal: | Nature Communications |
| Published: | 9 Feb 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41663376/ |
| DOI: | https://doi.org/10.1038/s41467-025-67449-2 |
| URL: | https://www.nature.com/articles/s41467-025-67449-2.pdf |
Publication 18335
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Type 2 diabetes and hypertension are common health conditions that often occur together, suggesting shared biological mechanisms. To explore this relationship, we analyse large-scale multiomic data to uncover genetic factors underlying type 2 diabetes and blood pressure comorbidity. We curate 1304 independent single-nucleotide variants associated with type 2 diabetes and blood pressure, grouping them into five clusters related to metabolic syndrome, inverse type 2 diabetes/blood pressure risk, impaired pancreatic beta-cell function, higher adiposity, and vascular dysfunction. Colocalization with tissue-specific gene expression highlights significant enrichment in pathways related to thyroid function and fetal development. Partitioned polygenic scores derived from these clusters improve risk prediction for type 2 diabetes/hypertension comorbidity, identifying individuals with more than twice the usual susceptibility. These results reveal a mechanistically heterogeneous genetic architecture shared between type 2 diabetes and blood pressure, enhancing comorbidity risk prediction. Partitioned polygenic risk scores offer a promising approach for early risk stratification, personalised prevention, and improved management of these interconnected conditions.</p>
13 Keywords
- Blood Pressure
- Comorbidity
- Diabetes Mellitus, Type 2
- Female
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Humans
- Hypertension
- Male
- Metabolic Syndrome
- Multifactorial Inheritance
- Polymorphism, Single Nucleotide
- Risk Factors
17 Authors
- Vincent Pascat
- Liudmila Zudina
- Lucas Maurin
- Anna Ulrich
- Jared G. Maina
- Ayse Demirkan
- Zhanna Balkhiyarova
- Igor Pupko
- Yevheniya Sharhorodska
- François Pattou
- Bart Staels
- Marika Kaakinen
- Amna Khamis
- Amélie Bonnefond
- Patricia Munroe
- Philippe Froguel
- Inga Prokopenko
1 Application
| Application ID | Title |
|---|---|
| 236 | Genome-wide association study of blood pressure. |
Enabling scientific discoveries that improve human health