@article {129, title = {Genome-Wide Polygenic Score, Clinical Risk Factors, and Long-Term Trajectories of Coronary Artery Disease.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {40}, year = {2020}, month = {2020 11}, pages = {2738-2746}, abstract = {

OBJECTIVE: To determine the relationship of a genome-wide polygenic score for coronary artery disease (GPS) with lifetime trajectories of CAD risk, directly compare its predictive capacity to traditional risk factors, and assess its interplay with the Pooled Cohort Equations (PCE) clinical risk estimator. Approach and Results: We studied GPS in 28 556 middle-aged participants of the Malm{\"o} Diet and Cancer Study, of whom 4122 (14.4\%) developed CAD over a median follow-up of 21.3 years. A pronounced gradient in lifetime risk of CAD was observed-16\% for those in the lowest GPS decile to 48\% in the highest. We evaluated the discriminative capacity of the GPS-as assessed by change in the C-statistic from a baseline model including age and sex-among 5685 individuals with PCE risk estimates available. The increment for the GPS (+0.045, <0.001) was higher than for any of 11 traditional risk factors (range +0.007 to +0.032). Minimal correlation was observed between GPS and 10-year risk defined by the PCE (=0.03), and addition of GPS improved the C-statistic of the PCE model by 0.026. A significant gradient in lifetime risk was observed for the GPS, even among individuals within a given PCE clinical risk stratum. We replicated key findings-noting strikingly consistent results-in 325 003 participants of the UK Biobank.

CONCLUSIONS: GPS-a risk estimator available from birth-stratifies individuals into varying trajectories of clinical risk for CAD. Implementation of GPS may enable identification of high-risk individuals early in life, decades in advance of manifest risk factors or disease.

}, keywords = {Adult, Aged, Coronary Artery Disease, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Disease Risk Factors, Heredity, Humans, Incidence, Male, Middle Aged, Multifactorial Inheritance, Phenotype, Prognosis, Risk Assessment, Sweden, Time Factors, United Kingdom}, issn = {1524-4636}, doi = {10.1161/ATVBAHA.120.314856}, author = {Hindy, George and Aragam, Krishna G and Ng, Kenney and Chaffin, Mark and Lotta, Luca A and Baras, Aris and Drake, Isabel and Orho-Melander, Marju and Melander, Olle and Kathiresan, Sekar and Khera, Amit V} } @article {43, title = {Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.}, journal = {Nat Genet}, volume = {50}, year = {2018}, month = {2018 Sep}, pages = {1219-1224}, abstract = {

A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation. Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature, it has not yet been possible to use polygenic predictors to identify individuals at risk comparable to monogenic mutations. Here, we develop and validate genome-wide polygenic scores for five common diseases. The approach identifies 8.0, 6.1, 3.5, 3.2, and 1.5\% of the population at greater than threefold increased risk for coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively. For coronary artery disease, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk. We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care, and discuss relevant issues.

}, issn = {1546-1718}, doi = {10.1038/s41588-018-0183-z}, author = {Khera, Amit V and Chaffin, Mark and Aragam, Krishna G and Haas, Mary E and Roselli, Carolina and Choi, Seung Hoan and Natarajan, Pradeep and Lander, Eric S and Lubitz, Steven A and Ellinor, Patrick T and Kathiresan, Sekar} } @article {33, title = {Genetics of coronary artery disease: discovery, biology and clinical translation.}, journal = {Nat Rev Genet}, volume = {18}, year = {2017}, month = {2017 Jun}, pages = {331-344}, abstract = {

Coronary artery disease is the leading global cause of mortality. Long recognized to be heritable, recent advances have started to unravel the genetic architecture of the disease. Common variant association studies have linked approximately 60 genetic loci to coronary risk. Large-scale gene sequencing efforts and functional studies have facilitated a better understanding of causal risk factors, elucidated underlying biology and informed the development of new therapeutics. Moving forwards, genetic testing could enable precision medicine approaches by identifying subgroups of patients at increased risk of coronary artery disease or those with a specific driving pathophysiology in whom a therapeutic or preventive approach would be most useful.

}, keywords = {Animals, Coronary Artery Disease, Humans, Precision Medicine, Translational Research, Biomedical}, issn = {1471-0064}, doi = {10.1038/nrg.2016.160}, author = {Khera, Amit V and Kathiresan, Sekar} } @article {8, title = {Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease.}, journal = {N Engl J Med}, volume = {375}, year = {2016}, month = {2016 Dec 15}, pages = {2349-2358}, abstract = {

BACKGROUND: Both genetic and lifestyle factors contribute to individual-level risk of coronary artery disease. The extent to which increased genetic risk can be offset by a healthy lifestyle is unknown.

METHODS: Using a polygenic score of DNA sequence polymorphisms, we quantified genetic risk for coronary artery disease in three prospective cohorts - 7814 participants in the Atherosclerosis Risk in Communities (ARIC) study, 21,222 in the Women{\textquoteright}s Genome Health Study (WGHS), and 22,389 in the Malm{\"o} Diet and Cancer Study (MDCS) - and in 4260 participants in the cross-sectional BioImage Study for whom genotype and covariate data were available. We also determined adherence to a healthy lifestyle among the participants using a scoring system consisting of four factors: no current smoking, no obesity, regular physical activity, and a healthy diet.

RESULTS: The relative risk of incident coronary events was 91\% higher among participants at high genetic risk (top quintile of polygenic scores) than among those at low genetic risk (bottom quintile of polygenic scores) (hazard ratio, 1.91; 95\% confidence interval [CI], 1.75 to 2.09). A favorable lifestyle (defined as at least three of the four healthy lifestyle factors) was associated with a substantially lower risk of coronary events than an unfavorable lifestyle (defined as no or only one healthy lifestyle factor), regardless of the genetic risk category. Among participants at high genetic risk, a favorable lifestyle was associated with a 46\% lower relative risk of coronary events than an unfavorable lifestyle (hazard ratio, 0.54; 95\% CI, 0.47 to 0.63). This finding corresponded to a reduction in the standardized 10-year incidence of coronary events from 10.7\% for an unfavorable lifestyle to 5.1\% for a favorable lifestyle in ARIC, from 4.6\% to 2.0\% in WGHS, and from 8.2\% to 5.3\% in MDCS. In the BioImage Study, a favorable lifestyle was associated with significantly less coronary-artery calcification within each genetic risk category.

CONCLUSIONS: Across four studies involving 55,685 participants, genetic and lifestyle factors were independently associated with susceptibility to coronary artery disease. Among participants at high genetic risk, a favorable lifestyle was associated with a nearly 50\% lower relative risk of coronary artery disease than was an unfavorable lifestyle. (Funded by the National Institutes of Health and others.).

}, keywords = {Aged, Cohort Studies, Coronary Disease, Cross-Sectional Studies, Female, Genetic Predisposition to Disease, Healthy Lifestyle, Humans, Incidence, Male, Middle Aged, Multifactorial Inheritance, Patient Compliance, Polymorphism, Genetic, Risk}, issn = {1533-4406}, doi = {10.1056/NEJMoa1605086}, author = {Khera, Amit V and Emdin, Connor A and Drake, Isabel and Natarajan, Pradeep and Bick, Alexander G and Cook, Nancy R and Chasman, Daniel I and Baber, Usman and Mehran, Roxana and Rader, Daniel J and Fuster, Valentin and Boerwinkle, Eric and Melander, Olle and Orho-Melander, Marju and Ridker, Paul M and Kathiresan, Sekar} }