Genetic study of cardiovascular disease subtypes defined by International Classification of Diseases.
- Author:
Zi Ning GUO
1
;
Zhi Sheng LIANG
1
;
Yi ZHOU
1
;
Na ZHANG
1
;
Jie HUANG
1
Author Information
1. Department of Global Health, School of Public Health, Peking University 100191, China.
- Publication Type:Journal Article
- Keywords:
Cardiovascular diseases;
Genetic correlation;
Genome-wide association studies;
International classification of diseases;
Mendelian randomization
- MeSH:
Adult;
Aged;
Cardiovascular Diseases/genetics*;
Genome-Wide Association Study;
Humans;
International Classification of Diseases;
Mendelian Randomization Analysis;
Middle Aged;
Polymorphism, Single Nucleotide
- From:
Journal of Peking University(Health Sciences)
2021;53(3):453-459
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To study the molecular connection among cardiovascular diseases (CVD) subtypes defined by the International Classification of Diseases (ICD) version 10 (ICD-10).
METHODS:Both phenotypic data and genotypic data used in this study were obtained from the UK Biobank. A total of 380 083 participants aged between 40 and 69 years were included. Those without any cardiovascular disease (either no ICD-10 code at all or no ICD-10 code containing letter I) were assigned to the control group. The five CVD subtypes were: ischaemic heart diseases (IHD), pulmonary heart disease and diseases of pulmonary circulation (PHD), cerebrovascular diseases (CRB), diseases of arteries, arterioles and capillaries (AAC), diseases of veins, lymphatic vessels and lymph nodes, and diseases not elsewhere classified (VLL). We first performed a genome-wide association study (GWAS) for each of the five subtypes. We summarized novel loci using genome-wide significance threshold P=5×10-8. Next, we used linkage disequilibrium score regression (LDSC) method to assess genetic correlation among the five subtypes. Lastly, we applied mendelian randomization (MR) approach to assess the causal relationship among the subtypes. The particular software that we used was generalised summary-data-based mendelian randomisation (GSMR).
RESULTS:Through GWAS, we identified hundreds of genome-wide significant SNPs: 672 for IHD, 241 for PHD, 31 for CRB, 48 for AAC, and 193 for VLL. By comparing with published literature, we found 28 novel loci, for PHD (n=14), CRB (n =7) and AAC (n =7). Eight of these 28 loci were rare, where the lead SNP had minor allele frequency (MAF) less than 1%. LDSC analyses indicated IHD had significant genetic correlation with VLL (P=2.52×10-7), PHD (P=3.77×10-3) and AAC (P=4.90×10-3), respectively. Bidrectional GSMR analyses showed that IHD had a positive causal relationship with VLL (P=7.40×10-5) and AAC (P=1.50×10-3), while reverse causality was not supported.
CONCLUSION:This study adopted an innovative approach to study the molecular connection among CVD subtypes that are defined by ICD. We identified potentially positive genetic correlation and causal effects among some of these subtypes. Research along this line will provide scientific insights and serve as a guidance for future ICD standards.
