In-depth Mendelian randomization analysis of causal factors for coronary artery disease.

Scientific Reports
Yuan-De TanChittibabu Guda

Abstract

Selecting a set of valid genetic variants is critical for Mendelian randomization (MR) to correctly infer risk factors causing a disease. We here developed a method for selecting genetic variants as valid instrumental variables for inferring risk factors causing coronary artery disease (CAD). Using this method, we selected two sets of single-nucleotide-polymorphism (SNP) genetic variants (SNP338 and SNP363) associated with each of the three potential risk factors for CAD including low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c) and triglycerides (TG) from two independent GWAS datasets. We performed in-depth multivariate MR (MVMR) analyses and the results from both datasets consistently showed that LDL-c was strongly associated with increased risk for CAD (β = 0.396,OR = 1.486 per 1 SD (equivalent to 38 mg/dL), 95CI = (1.38, 1.59) in SNP338; and β = 0.424, OR = 1.528 per 1 SD, 95%CI = (1.42, 1.65) in SNP363); HDL-c was strongly associated with reduced risk for CAD (β = -0.315, OR = 0.729 per 1 SD (equivalent to 16 mg/dL), 95CI = (0.68, 0.78) in SNP338; and β = -0.319, OR = 0.726 per 1 SD, 95%CI = (0.66, 0.80), in SNP363). In case of TG, when using the full datasets, an increased risk for...Continue Reading

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Citations

Jan 9, 2021·Journal of the American College of Cardiology·Gordon S Huggins, Eli Simsolo
May 28, 2021·Frontiers in Cardiovascular Medicine·Dara VakiliDeepak L Bhatt
Jan 21, 2022·European Heart Journal·Lale Tokgözoğlu, Peter Libby

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Software Mentioned

gride
MRPRESSO
Bioconductor
Forestplot
R
remeta
R package
R package , MendelianRandomization
MVMR
MR

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