Evaluation of the Role of Nutrition Intake in Coronary Artery Disease Using Mendelian Randomization Restricted; Files Only
Ren, Jiyuan (Spring 2023)
Abstract
Background: Previous observational studies showed inconsistent evidence supporting the role of nutrient intake in coronary artery disease (CAD). It is inconclusive if observed associations are caused by nutrient intake or by confounders such as other lifestyle factors. Mendelian Randomization (MR) uses genetic variants as instrumental variables (IVs) to estimate the association between the exposure and the outcome with the control of confounders. This study aims to use two-sample MR to investigate the potential causal relationship between several common nutrients and CAD utilizing data from the UK Biobank and summary statistics of Genome-wide association studies (GWAS) of CAD.
Methods: The study population consisted of 201,245 white participants from the UK Biobank. Genome-wide association studies (GWAS) of the nutrient intake were performed with adjustments for age, sex, and top 10 principal components to identify independent significant SNPs (linkage disequilibrium r2 < 0.1 ) as IVs. CAD GWAS results were derived from CARDIoGRAMplusC4D 1000 Genomes-based study. MR analysis was conducted using inverse-variance weighted MR method and MR-Egger regression.
Results: Animal fat, fat, magnesium, trans fatty acids, and Vitamin C were significantly associated with incident CAD after adjusting for CAD risk factors. We identified IVs from the GWAS of 13 nutrients to conduct two-sample MR analyses. Alcohol, fat, lactose, and Vitamin C were significantly associated with CAD risk. A one SD increase in alcohol intake increased the risk of CAD by 1.24-fold (95% CI: 1.02-1.50, P = 0.029). Conversely, the corresponding odds ratio of CAD for one SD increase intake of fat, free sugar, lactose and vitamin C were 0.622 (95%CI: 0.400 - 0.968, P = 0.035), 0.647 (95%CI: 0.431 - 0.970, P = 0.035), 0.805 (95%CI: 0.676 - 0.959, P = 0.015) and 0.372 (95%CI: 0.160 - 0.865, P = 0.022), respectively.
Conclusion: Significant GWAS findings showed the important role of genetic factors in nutrients intake. The MR results supported that nutrients intake may have potential causal effect on CAD.
Table of Contents
Table of Contents
Introduction. 1
Methods. 3
Study Population and data sources. 3
GWAS of the Nutrition data. 4
CAD GWAS data source. 5
Statistical Analyses. 5
Results. 6
Descriptive statistics. 6
Associations between nutrient intake and incidence CAD.. 6
GWAS of nutrient intake. 7
Two-sample MR.. 7
Discussion. 8
Conclusion. 10
References. 12
Tables and Figures. 14
Table 1. Baseline characteristics : Categorized by CAD status. 14
Figure 1. Univariate associations between nutrients (per SD increase) and CAD incidence (unadjusted) 16
Figure 2. Univariate associations between nutrients (per SD increase) and the risk of CAD (adjusted) 17
Figure 3. Mendelian Randomization Associations between nutrients (per SD increase) and CAD incidence . 18
Supplemental Table 1. Comparison of baseline characteristics among subjects based on availability of nutrition data. 19
Supplemental Table 2. Univariate associations between nutrients (per SD increase) and the CAD incidence. 20
Supplemental Table 3. Summary of GWAS of nutrient intake. 21
Supplemental Table 4. Mendelian Randomization Associations between nutrients (per SD increase) and CAD incidence . 22
About this Master's Thesis
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File download under embargo until 18 May 2025 | 2023-04-18 19:41:52 -0400 | File download under embargo until 18 May 2025 |
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