@article{Inouye2018b,
title = {Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention},
author = {Michael Inouye and Gad Abraham and Christopher P. Nelson and Angela M. Wood and Michael J. Sweeting and Frank Dudbridge and Florence Y. Lai and Stephen Kaptoge and Marta Brozynska and Tingting Wang and Shu Ye and Thomas R. Webb and Martin K. Rutter and Ioanna Tzoulaki and Riyaz S. Patel and Ruth J.F. Loos and Bernard Keavney and Harry Hemingway and John Thompson and Hugh Watkins and Panos Deloukas and Emanuele Di Angelantonio and Adam S. Butterworth and John Danesh and Nilesh J. Samani and for the UK Biobank CardioMetabolic Consortium CHD Working Group},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176870/},
year = {2018},
date = {2018-10-16},
journal = {Journal of the American College of Cardiology},
abstract = {Background

Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes.
Objectives

This study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention.
Methods

Using a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank.
Results

The hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age.
Conclusions

The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.},
keywords = {9922, coronary artery disease, genetics},
pubstate = {published},
tppubtype = {article}
}

@article{Sjaarda2018,
title = {Blood CSF1 and CXCL12 as Causal Mediators of Coronary Artery Disease},
author = {J Sjaarda and H Gerstein and M Chong and S Yusuf and D Meyre and SS Anand and S Hess and G Paré},
url = {https://www.ncbi.nlm.nih.gov/pubmed/30012324},
year = {2018},
date = {2018-07-17},
journal = {Journal of the American College of Cardiology},
abstract = {BACKGROUND:

Identification of biomarkers that cause coronary artery disease (CAD) has led to important advances in prevention and treatment. Epidemiological analyses have identified many biomarker-CAD relationships; however, these associations may arise from reverse causation and/or confounding and therefore may not represent true causal associations. Mendelian randomization (MR) analyses overcome these limitations.

OBJECTIVES:

This study sought to identify causal mediators of CAD through a comprehensive screen of 237 biomarkers using MR.

METHODS:

MR was performed by identifying genetic determinants of 227 biomarkers in ORIGIN (Outcome Reduction With Initial Glargine Intervention) trial participants (N = 4,147) and combining these with genetic effects on CAD from the CARDIoGRAM consortium (60,801 cases and 123,504 controls). Blood concentrations of novel biomarkers identified by MR were then tested for association with incident major adverse cardiovascular events in ORIGIN.

RESULTS:

Six biomarkers were found to be causally linked to CAD after adjustment for multiple hypothesis testing. The causal role of 4 of these is well documented, whereas macrophage colony-stimulating factor 1 (CSF1) and stromal cell-derived factor 1 (CXCL12) have not previously been reported, to the best of our knowledge. MR analysis predicted an 18% higher risk of CAD per SD increase in CSF1 (odds ratio: 1.18; 95% confidence interval: 1.08 to 1.30; p = 2.1 × 10-4) and epidemiological analysis identified a 16% higher risk of major adverse cardiovascular events per SD (hazard ratio: 1.16; 95% confidence interval: 1.09 to 1.23; p < 0.001). Elevated CXCL12 levels were also identified as a causal risk factor for CAD with consistent epidemiological results. Furthermore, genetically predicted CSF1 and CXCL12 levels were associated with CAD in the UK Biobank (n = 343,735).

CONCLUSIONS:

The study identified CSF1 and CXCL12 as causal mediators of CAD in humans. Understanding the mechanism by which these markers mediate CAD will provide novel insights into CAD and could lead to new approaches to prevention. These results support targeting inflammatory processes and macrophages, in particular, to prevent CAD, consistent with the recent CANTOS (Canakinumab Antiinflammatory Thrombosis Outcome Study). (Outcome Reduction With Initial Glargine Intervention [ORIGIN]; NCT00069784).},
keywords = {15255, blood, coronary artery disease},
pubstate = {published},
tppubtype = {article}
}

@article{Thériault2018b,
title = {Polygenic Contribution in Individuals With Early-Onset Coronary Artery Disease},
author = {S Thériault and R Lali and M Chong and JL Velianou and MK Natarajan and G Paré},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29874178},
year = {2018},
date = {2018-01-11},
journal = {Circulation, Genomic and Precision Medicine},
abstract = {BACKGROUND:

Despite evidence of high heritability, monogenic disorders are identified in a minor fraction of individuals with early-onset coronary artery disease (EOCAD). We hypothesized that some individuals with EOCAD carry a high number of common genetic risk variants, with a combined effect similar to Mendelian forms of coronary artery disease, such as familial hypercholesterolemia.

METHODS AND RESULTS:

To confirm the polygenic contribution to EOCAD (age of ≤40 years for men and ≤45 years for women), we calculated in 111 418 British participants from the UK Biobank cohort a genetic risk score (GRS) based on the presence of 182 independent variants associated with coronary artery disease (GRS182). Participants with a diagnosis of EOCAD who underwent a revascularization procedure (n=96) had a significantly higher GRS182 (P=3.21×10-9) than those without EOCAD. An increase of 1 SD in GRS182 corresponded to an odds ratio of 1.84 (1.52-2.24) for EOCAD. The prevalence of a polygenic contribution that increased EOCAD risk similar to what is observed in heterozygous familial hypercholesterolemia was estimated at 1 in 53. In a local cohort of individuals with EOCAD (n=30), GRS182 was significantly increased compared with UK Biobank controls (P=0.001). Seven participants (23%) had a GRS182 corresponding to an estimated 2-fold increase in EOCAD risk; none had a rare mutation involved in monogenic dyslipidemia or EOCAD.

CONCLUSIONS:

These results suggest a significant polygenic contribution in individuals presenting with EOCAD, which could be more prevalent than familial hypercholesterolemia. Determination of the polygenic risk component could be included in the diagnostic workup of patients with EOCAD.},
keywords = {15255, coronary artery disease, genetics},
pubstate = {published},
tppubtype = {article}
}

@article{Nelson2017,
title = {Association analyses based on false discovery rate implicate 243 susceptibility loci for coronary artery disease},
author = {CP Nelson, A Goel, A Butterworth},
url = {http://eprints.whiterose.ac.uk/116865/},
year = {2017},
date = {2017-05-25},
abstract = {Genome-wide association studies (GWAS) in coronary artery disease (CAD) have identified 66 loci at ‘genome-wide significance’ (p < 5 × 10-8) but a much larger number of putative loci at a false discovery rate (FDR) of 5%1-4. Here, we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; Ncases=10,801) as well as a stricter definition without it (HARD; Ncases=6,482) and selected the former for conducting a meta-analysis with the two most recent CAD GWASs2-3. This approach identified 13 new loci at genome-wide significance, 12 of which were in our previous 5% FDR list2, and provided strong support that the remaining FDR loci represent genuine signals. The set of 304 independent variants at 5% FDR in this study explain 21.2% of CAD heritability and identified 243 loci that implicate pathways in blood vessel morphogenesis as well as lipid metabolism, nitric oxide signaling and inflammation.},
keywords = {11223, coronary artery disease, genetics},
pubstate = {published},
tppubtype = {article}
}

@article{Hagenaars2016b,
title = {Polygenic risk for coronary artery disease is associated with cognitive ability in older adults},
author = {Saskia P. Hagenaars, Sarah E. Harris, Toni-Kim Clarke, Lynsey Hall, Michelle Luciano, Ana Maria Fernandez-Pujals, Gail Davies, Caroline Hayward, Generation Scotland, John M. Starr, David J. Porteous, Andrew M. McIntosh, Ian J. Deary },
url = {http://ije.oxfordjournals.org/content/early/2016/01/28/ije.dyv354.abstract},
year = {2016},
date = {2016-01-28},
journal = {International Journal of Epidemiology},
abstract = {Background: Coronary artery disease (CAD) is associated with cognitive decrements and risk of later dementia, but it is not known if shared genetic factors underlie this association. We tested whether polygenic risk for CAD was associated with cognitive ability in community-dwelling cohorts of middle-aged and older adults.

Methods: Individuals from Generation Scotland: Scottish Family Health Study (GS:SFHS, N = 9865) and from the Lothian Birth Cohorts of 1921 (LBC1921, N = 517) and 1936 (LBC1936, N = 1005) provided cognitive data and genome-wide genotype data. Polygenic risk profile scores for CAD were calculated for all of the cohorts using the largest available genome-wide association studies (GWAS) data set, the CARDIoGRAM consortium (22 233 cases and 64 762 controls). Polygenic risk profile scores for CAD were then tested for their association with cognitive abilities in the presence and absence of manifest cardiovascular disease.

Results: A meta-analysis of all three cohorts showed a negative association between CAD polygenic risk and fluid cognitive ability (β = −0.022, P = 0.016), verbal intelligence (β = −0.024, P = 0.011) and memory (β = −0.021, P = 0.028).

Conclusions: Increased polygenic risk for CAD is associated with lower cognitive ability in older adults. Common genetic variants may underlie some of the association between age-related cognitive decrements and the risk for CAD. },
keywords = {7898, coronary artery disease, genetics},
pubstate = {published},
tppubtype = {article}
}

@misc{Yaghootkar2015,
title = {GENETIC VARIANTS ASSOCIATED WITH LOWER BMI AND LOWER BODY FAT PERCENTAGE INCREASE THE RISK OF TYPE 2 DIABETES, HYPERTENSION AND CORONARY ARTERY DISEASE IN THE UK BIOBANK STUDY.},
author = {Hanieh Yaghootkar, Robin Beaumont, Jessica Tyrrell, Samuel Jones, Andrew Wood, Marcus Tuke, Katherine Ruth, Rachel Freathy, Anna Murray, Michael Weedon, Timothy Frayling},
year = {2015},
date = {2015-09-04},
abstract = {The UK Biobank study was designed to understand the role of genes, environment and their interaction in disease. Previous smaller studies have shown that many obese individuals are metabolically healthy whilst many normal weight individuals can have an elevated risk of metabolic diseases such as type 2 diabetes, coronary artery disease and hypertension. Further studies are needed to investigate the potential role of a shared genetic etiology between these diseases that is independent from obesity. We aimed to use the initial release of genetic data from 120,000 ancestrally British UK Biobank individuals to test the hypothesis that some individuals are genetically predisposed to metabolic disease independently of higher BMI.

We selected 11 common genetic variants previously associated with insulin resistance and metabolic diseases from previously published GWAS data. We tested these variants individually and as a genetic risk score in the 120,000 UK Biobank individuals.

Alleles in or near the LYPLAL1, GRB14, IRS1, PPARG, FAM13A, PDGFC, PEPD and ANKRD55 genes, previously associated with higher insulin resistance, were associated with reduced body fat percentage in UK Biobank (N=118,012, p-values ranging from 0.05 to 9E-11). An insulin resistance genetic risk score consisting of all 11 variants was associated with lower BMI (-0.05kg/m2 per weighted allele [-0.06,-0.03], p=2E-7), lower body fat percentage (-0.13% [-0.15,-0.1], p=2E-27) but only nominally with fat free mass (0.03Kg [0.01,0.05], p=0.01).

Despite this association with lower adiposity the insulin resistance genetic risk score was associated with higher systolic (0.26mmHg [0.18,0.33], p=2E-10) and diastolic blood pressure(0.10 mmHg [0.05,0.14], p=6E-5), and greater risk of hypertension(OR 1.02 [1.01,1.03], p=3E-6, 65,976 cases), type 2 diabetes (OR 1.06 [1.04,1.08], p=2E-8, 4,040 cases) and coronary artery disease(OR 1.03 [1.02,1.05], p=1E-4, 5,807 cases).

The UK Biobank data provide evidence for shared genetic factors that predispose to type 2 diabetes, hypertension and coronary artery disease independently of obesity and suggest that reduced adipose tissue capacity is a likely contributory mechanism.},
keywords = {9055, 9072, coronary artery disease, diabetes, hypertension},
pubstate = {published},
tppubtype = {presentation}
}