Identification of RNA modification-associated single-nucleotide polymorphisms in genomic loci for low-density lipoprotein cholesterol concentrations.
Fan TangChengcheng DuanRu LiHuan ZhangXing-Bo MoPublished in: Pharmacogenomics (2022)
Introduction: Genome-wide association studies have identified approximately 1000 lipid-associated loci, but functional variants are less known. Materials & methods: The authors identified RNA modification-related single-nucleotide polymorphisms (RNAm-SNPs) in summary data from a genome-wide association study. By applying Mendelian randomization analysis, the authors identified gene expression levels involved in the regulation of RNAm-SNPs on low-density lipoprotein cholesterol (LDL-C) levels. Results: The authors identified 391 RNAm-SNPs that were significantly associated with LDL-C levels. RNAm-SNPs in NPC1L1 , LDLR , APOB , MYLIP , LDLRAP1 and ABCA6 were identified. The RNAm-SNPs were associated with gene expression. The expression levels of 112 genes were associated with LDL-C levels, and some of them (e.g., APOB , SMARCA4 and SH2B3 ) were associated with coronary artery disease. Conclusion: This study identified many RNAm-SNPs in LDL-C loci and elucidated the relationship among the SNPs, gene expression and LDL-C.
Keyphrases
- genome wide association
- genome wide
- gene expression
- dna methylation
- genome wide association study
- copy number
- coronary artery disease
- low density lipoprotein
- poor prognosis
- big data
- machine learning
- type diabetes
- acute coronary syndrome
- left ventricular
- aortic valve
- long non coding rna
- deep learning
- transcatheter aortic valve replacement