A Genome-Wide Association Study of Genetic Variants of Apolipoprotein A1 Levels and Their Association with Vitamin D in Korean Cohorts.
Young LeeJi Won YoonYe An KimHyuk Jin ChoiByung-Woo YoonJe-Hyun SeoPublished in: Genes (2022)
Dyslipidemia is an important independent risk factor for cardiovascular disease (CVD). Specifically, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and the ApoB/A1 ratio have been linked to CVD. We conducted a genome-wide association study meta-analysis of two Korean cohorts containing a total of 12,924 patients to identify novel single nucleotide polymorphisms (SNPs) associated with ApoA1 and ApoB levels and the ApoB/A1 ratio. Additionally, an expression quantitative trait locus (eQTL) and differentially expressed genes (DEGs) analysis were performed. The statistically significant eQTL, DEG, and Gene Ontology (GO) results were used to explore the predicted interaction networks and retrieve the interacting genes and proteins. We identified three novel SNPs (rs11066280, p = 3.46 × 10-21; rs1227162, p = 2.98 × 10-15; rs73216931, p = 5.62 × 10-9) associated with ApoA1. SNP rs73216931 was an eQTL for KMT5A in the pancreas and whole blood. The network analysis revealed that HECTD4 and MYL2:LINC1405 are associated with AKT1 . Our in silico analysis of ApoA1 genetic variants revealed heart muscle-related signals. ApoA1 also correlated positively with vitamin D, and genes associated with ApoA1 and vitamin D were found. Our data imply that more research into ApoA1 is needed to understand the links between dyslipidemia and CVD and vitamin D and CVD.
Keyphrases
- genome wide association study
- genome wide
- protein kinase
- cardiovascular disease
- network analysis
- dna methylation
- end stage renal disease
- cell proliferation
- chronic kidney disease
- heart failure
- ejection fraction
- copy number
- poor prognosis
- single cell
- newly diagnosed
- type diabetes
- long non coding rna
- machine learning
- signaling pathway
- gene expression
- patient reported outcomes
- atrial fibrillation
- big data