How many variants were highly powered to detect an OR 1.3?

in terms of total coverage of low-frequency variation, only 15.3% of the 9.3 million low-frequency variants (0.005 90%) to detect an OR ≥3.15.

How many variants were indels in the meta-analysis?

Twenty of the 202 FDR variants (9.9%) were indels (4–14 bp in size) as compared to 8.8% of all the variants in the meta-analysis (P = 0.60).

How is the GCTA method used to assess the correlation between LD and ances?

The accuracy of this analysis depends on appropriate ancestry matching as well as the sample size of the reference genotype panel to ensure that estimated LD correlations are unbiased and acceptably precise69.

What are the cell types that are relevant to the CAD phenotype?

Cell types were grouped into CAD-relevant types and others (Supplementary Table 12) on the basis of their potential roles in CAD pathophysiology; hepatocytes (for example, lipid metabolism80), vascular endothelial cells (atherosclerosis81) and myoblasts (injury and repair82) were selected as being the most relevant to the CAD phenotype.

How many variants were able to detect an OR 1.3?

The number of variants with power of ≥90% to detect associations varied systematically with allele frequency and imputation quality (results for OR = 1.3 shown in Supplementary Fig. 4); 1.5 million of the 2.7 million (55%) low-frequency variants (0.005 < MAF < 0.05) in the meta-analysis were adequately powered to detect an OR ≥1.3, as most of these variants were accurately imputed (median imputation quality = 0.94, interquartile range = 0.88–0.98).

What is the association between MC4R and obesity?

MC4R is a well-studied obesity-related locus, and the variant (and corresponding proxy variants) that were associated with higher CAD risk are also associated with body mass index (BMI) (P = 6 × 10−42) and obesity-associated risk factors, including higher triglyceride and lower high-density lipoprotein (HDL) concentrations and type 2 diabetes37–41.

What is the eQTL and ENCODE data for SWAP70?

Although this CAD-associated locus includes 33 genes, the eQTL and ENCODE data implicate SWAP70 as a plausible causal gene and suggest putative causal SNPs.

(PDF) A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease (2015) | Majid Nikpay

Q: What are the contributions mentioned in the paper "University of dundee a comprehensive 1000 genomes-based genome-wide association meta-analysis of coronary artery disease nikpay," ?

Nikpay et al. this paper presented a comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease.

Q: What are the future works in "University of dundee a comprehensive 1000 genomes-based genome-wide association meta-analysis of coronary artery disease nikpay," ?

This phenomenon has previously been reported for other diseases and traits48 and can guide candidate gene nomination and the design of future functional studies. The authors found few suggestions of overlap with risk factor QTLs or eQTLs in available data sets ; this may in part reflect that the use of proxy variants can be limiting in cross-referencing the 1000 Genomes Project and HapMap association databases. The authors confirmed that ABO is particularly associated with risk of myocardial infarction50, suggesting that this locus may specifically increase the risk of plaque rupture and/or thrombosis. In contrast, HDAC9 showed a stronger association with CAD than with myocardial infarction, suggesting that it might predispose to atherosclerosis but not the precipitant events leading to a myocardial infarction.

Q: What are the genes implicated in CAD susceptibility?

Several of the genes implicated thus far in large-scale analyses of CAD susceptibility encode proteins with a known role in the biology of risk factors for CAD, notably circulating lipid levels and the metabolism of lipoproteins; other susceptibility genes are related to other known atherosclerosis risk factors, including genes implicated in systemic inflammation and hypertension.

Q: What is the role of NOS3 in CAD?

NOS3 is involved in the production of nitric oxide (NO), a potent vascular smooth muscle relaxant, and is a wellstudied candidate gene for CAD.

Q: What is the association between MC4R and obesity?

MC4R is a well-studied obesity-related locus, and the variant (and corresponding proxy variants) that were associated with higher CAD risk are also associated with body mass index (BMI) (P = 6 × 10−42) and obesity-associated risk factors, including higher triglyceride and lower high-density lipoprotein (HDL) concentrations and type 2 diabetes37–41.

Most frequently asked questions

1. What are the contributions mentioned in the paper "University of dundee a comprehensive 1000 genomes-based genome-wide association meta-analysis of coronary artery disease nikpay," ?

Nikpay et al. this paper presented a comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease.

2. What are the future works in "University of dundee a comprehensive 1000 genomes-based genome-wide association meta-analysis of coronary artery disease nikpay," ?

This phenomenon has previously been reported for other diseases and traits48 and can guide candidate gene nomination and the design of future functional studies.. The authors found few suggestions of overlap with risk factor QTLs or eQTLs in available data sets ; this may in part reflect that the use of proxy variants can be limiting in cross-referencing the 1000 Genomes Project and HapMap association databases.. The authors confirmed that ABO is particularly associated with risk of myocardial infarction50, suggesting that this locus may specifically increase the risk of plaque rupture and/or thrombosis.. In contrast, HDAC9 showed a stronger association with CAD than with myocardial infarction, suggesting that it might predispose to atherosclerosis but not the precipitant events leading to a myocardial infarction.

3. What are the genes implicated in CAD susceptibility?

Several of the genes implicated thus far in large-scale analyses of CAD susceptibility encode proteins with a known role in the biology of risk factors for CAD, notably circulating lipid levels and the metabolism of lipoproteins; other susceptibility genes are related to other known atherosclerosis risk factors, including genes implicated in systemic inflammation and hypertension.

4. What is the role of NOS3 in CAD?

NOS3 is involved in the production of nitric oxide (NO), a potent vascular smooth muscle relaxant, and is a wellstudied candidate gene for CAD.

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A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease

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Most frequently asked questions

1. What are the contributions mentioned in the paper "University of dundee a comprehensive 1000 genomes-based genome-wide association meta-analysis of coronary artery disease nikpay," ?

2. What are the future works in "University of dundee a comprehensive 1000 genomes-based genome-wide association meta-analysis of coronary artery disease nikpay," ?

3. What are the genes implicated in CAD susceptibility?

4. What is the role of NOS3 in CAD?

5. How many variants were highly powered to detect an OR 1.3?

6. How many variants were indels in the meta-analysis?

7. How is the GCTA method used to assess the correlation between LD and ances?

8. What are the cell types that are relevant to the CAD phenotype?

9. How many variants were able to detect an OR 1.3?

10. What is the association between MC4R and obesity?

11. What is the eQTL and ENCODE data for SWAP70?

Citations

Distinct metabolic features of genetic liability to type 2 diabetes and coronary artery disease: a reverse Mendelian randomization study

The association of clinical phenotypes to known AD/FTD genetic risk loci and their inter-relationship.

Genetic Analysis for Coronary Artery Disease Toward Diverse Populations

Gene-Environment Interactions for Cardiovascular Disease.

Proteogenomic Data Integration Reveals CXCL10 as a Potentially Downstream Causal Mediator for IL-6 Signaling on Atherosclerosis.

References

Meta-Analysis in Clinical Trials*

Quantifying heterogeneity in a meta‐analysis

An integrated encyclopedia of DNA elements in the human genome

ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

The control of the false discovery rate in multiple testing under dependency

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