| Title: | Exploring the Genetic Relationship Between Type 2 Diabetes and Cardiovascular Disease: A Large-Scale Genetic Association and Polygenic Risk Score Study |
| Journal: | Biomolecules |
| Published: | 18 Nov 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39595643/ |
| DOI: | https://doi.org/10.3390/biom14111467 |
| URL: | https://www.mdpi.com/2218-273X/14/11/1467/pdf?version=1731938641 |
Publication 14100
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Abstract
Type 2 diabetes (T2D) is often comorbid with cardiovascular diseases (CVDs). The direction of causation between T2D and CVD is difficult to determine; however, there may be a common underlying pathway attributable to shared genetic factors. We aimed to determine whether there is a shared genetic susceptibility to T2D and CVD. This study utilizes large-scale datasets from the UK Biobank (UKB) and DIAGRAM consortium to investigate the genetic association between T2D and CVD through phenotypic association analyses, linkage disequilibrium score (LDSC) analysis, and polygenic risk score (PRS) analysis. LDSC analysis demonstrates significant genetic associations between T2D and various CVD subtypes, including angina, heart failure (HF), myocardial infarction (MI), peripheral vascular disease (PVD), and stroke. Although the genetic association between T2D and atrial fibrillation (AF) was not significant, individuals in the high-T2D PRS group had a significantly increased risk of CVD. These findings suggest a common genetic basis and suggest that genetic susceptibility to T2D may be a potential predictor of CVD risk.</p>
13 Keywords
- Cardiovascular Diseases
- Diabetes Mellitus, Type 2
- Female
- Genetic Predisposition to Disease
- Genetic Risk Score
- Genome-Wide Association Study
- Humans
- Linkage Disequilibrium
- Male
- Middle Aged
- Multifactorial Inheritance
- Polymorphism, Single Nucleotide
- Risk Factors
7 Authors
- Ziwei Yao
- Xiaomai Zhang
- Liufei Deng
- Jiayu Zhang
- Yalu Wen
- Deqiang Zheng
- Long Liu
1 Application
| Application ID | Title |
|---|---|
| 95259 | The role of dynamic environmental factors, genetic information, and gene-environment interactions in non-communicable chronic diseases and the development and validation of prediction models for risks |
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