Nikpay M, et al. Cureus. J Hum Genet. 2020 Jan 7.
Nikpay M, et al., conducted a study to perform an extensive search to identify traits that basically linked with the risk of Coronary Artery Disease (CAD). Later, the relevant signals to additional analysis were also subjected to examine link between traits.
The collection of data comprised of 6194 cases and 4287 controls of European ancestry with available postimputed autosomal genotype data for 4,680,676 genome-wide single nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥ 0.01, Hardy–Weinberg equilibrium (HWE) ≥ 0.0001, missingness < 0.01, and info > 0.9. This sample was utilized to estimate linkage disequilibrium (LD) and to assess the individual-level polygenic risk scores. To determine correlation between CAD and a phenotype and to distinguish between causation and reverse causation, multi-SNP summary based Mendelian randomization (MR) analysis which is also known as two-sample MR were conducted. Further, to validate that genetic susceptibility to a given trait positively alter the risk of CAD, polygenic risk score (PRS) analysis were conducted.
By utilizing both MR and PRS analysis, almost 46 traits were identified which offers basic impact on CAD. Twenty-five traits were favourably linked with CAD (enhanced the risk of CAD) and the remaining unfavourably linked with the risk of CAD (Figure 1).
Figure 1: Phenotypes that have causal effect on coronary artery disease. These risk factors were grouped into seven categories, including cardiovascular, CNS, diabetes, lipids, immune, anthropometry, and life style features. Each point represents a risk factor. Y-axis represents the Z-scores from forward MR analysis and has been capped to |Z-score| = 12 for better visualization. Phenotypes that are below the dashed cyan line decrease the risk of CAD (e.g., height); whereas, those above the line increase the risk of CAD (e.g., LDL level). For better visualization side-by-side categories are colored differently.
Multiple occurrences of positive genetic association were identified between traits from several groups after conducting pairwise-MR analysis (a) genetic correlation analysis (b) between the 46 CAD-risk factors (Figure 2A). Multiple evidences of positive genetic association between traits that do not adhere to the same category were identified (Figure 2B).
Figure 2: Evidences of genetic relatedness between trait categories. (A) Proportion of casual associations between risk factors in each category (rows) with risk factors in other categories (columns). The numbers in parenthesis represent the total number of causal associations identified for each category (rows). Each orange circle represents a proportion and the sum of the proportions in each row equals 1. (B) The genetic correlations (X-axis) are plotted versus the −Log10 of the P values (Y-axis). Each point represents a pair of traits. Thresholds are shown as dot-dashed lines at | rg| = 0.5 and the Bonferroni-corrected P value = 4.7e−5. Trait pairs with P value < 4.7e−5 and |rg| ≥ 0.5 are colored in red, those with P value < 4.7e−5 and |rg| < 0.5 are displayed in blue and the remaining in dark gray. Pairs of traits that do not belong to the same category are displayed as triangles and the remaining as circles.
Genetic variants linked with raised cognition are correlated with life-style characteristics that reduce the risk of CAD such as walking for pleasures, choosing muesli for breakfast, and exercising were identified. Importantly, time spent watching television (TV) do not link with the risk of CAD per se, rather it was observed that it is a substitute for lower cognition because, another form of screen time such as time spent using computer is significantly linked with higher intelligence (rg = 0.53, p value = 3.5e−184) and also shows reduced risk of CAD (Figure 3).
Figure 3: Pairs of phenotypes. The identified risk factors were grouped into seven major categories, including cardiovascular, lung, CNS, diabetes, lipids, immune, anthropometry, and life style features. Each color represents a category. Dashed red lines indicate negative genetic correlations and solid lines indicate positive genetic correlations. CAD shares a significant positive genetic correlation with pulmonary embolism.
Thus, outcomes from this study showed applications in personalized medicine of CAD as well as PRS for the 46 risk factors observed in this study can be measured to figure out certain risk factors that a subject is sensitive to and requires preventive medicine.
