Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.

Background Cardiovascular diseases are the leading cause of death in the United States, yet a significant proportion of adults at high risk remain undetected by standard screening practices. Polygenic risk score for coronary artery disease (CAD‐PRS) improves precision in determining the 10‐year risk of atherosclerotic cardiovascular disease but health benefits and health care costs associated with CAD‐PRS are unknown. We examined the cost‐effectiveness of including CAD‐PRS as a risk‐enhancing factor in the pooled cohort equation (PCE)—the standard of care for determining the risk of atherosclerotic cardiovascular disease—versus PCE alone. Methods and Results We applied a Markov model on a cohort of 40‐year‐old individuals with borderline or intermediate 10‐year risk (5% to <20%) for atherosclerotic cardiovascular disease to identify those in the top quintile of the CAD‐PRS distribution who are at high risk and eligible for statin prevention therapy. Health outcomes examined included coronary artery disease (CAD; ie, myocardial infarction) and ischemic stroke. The model projected medical costs (2019 US$) of screening for CAD, statin prevention therapy, treatment, and monitoring patients living with CAD or ischemic stroke and quality‐adjusted life‐years for PCE+CAD‐PRS versus PCE alone. Deterministic and probabilistic sensitivity analyses and scenario analyses were performed to examine uncertainty in parameter inputs. PCE+CAD‐PRS was dominant compared with PCE alone in the 5‐ and 10‐year time horizons. We found that, respectively, PCE+CAD‐PRS had 0.003 and 0.011 higher mean quality‐adjusted life‐years and $40 and $181 lower mean costs per person screened, with 29 and 50 fewer events of CAD and ischemic stroke in a cohort of 10 000 individuals compared with PCE alone. The risk of developing CAD, the effectiveness of statin prevention therapy, and the cost of treating CAD had the largest impact on the cost per quality‐adjusted life‐year gained. However, this cost remained below the $50 000 willingness‐to‐pay threshold except when the annual risk of developing CAD was <0.006 in the 5‐year time horizon. Results from Monte Carlo simulation indicated that PCE+CAD‐PRS would be cost‐effective. with the probability of 94% and 99% at $50 000 willingness‐to‐pay threshold in the 5‐ and 10‐year time horizon, respectively. Conclusions Implementing CAD‐PRS as a risk‐enhancing factor in the PCE to determine the risk of atherosclerotic cardiovascular disease reduced the mean cost per individual, improved quality‐adjusted life‐years, and averted future events of CAD and ischemic stroke when compared with PCE alone.

No abstract

In the last decade the scientific community witnessed a large increase in Genome-Wide Association Study sample size, in the availability of large Biobanks and in the improvements of statistical methods to model genomes features. This have paved the way for the development of new prediction medicine tools that use genomic data to estimate disease risk. One of these tools is the Polygenic Risk Score (PRS), a metric that estimates the genetic risk of an individual to develop a disease, based on a combination of a large number of genetic variants.Using the largest prospective genotyped cohort available to date, the UK Biobank, we built a new PRS for Coronary Artery Disease (CAD) and assessed its predictive performances along with two additional PRS for Breast Cancer (BC), and Prostate Cancer (PC). When compared with previously published PRS, the newly developed PRS for CAD displayed higher AUC and positive predictive value. PRSs were able to stratify disease risks from 1.34% to 25.7% (CAD in men), from 0.26% to 8.62% (CAD in women), from 1.6% to 24.6% (BC), and from 1.4% to 24.3% (PC) in the lowest and highest percentiles, respectively. Additionally, the three PRSs were able to identify the 5% of the UK Biobank population with a relative risk for the diseases at least 3 times higher than the average. Family history is a well recognised risk factor of CAD, BC, and PC and it is currently used to identify individuals at high risk of developing the diseases. We show that individuals with

An individual's lifetime risk of Coronary Artery Disease (CAD) is determined by a combination of genetic and lifestyle factors. Whilst adherence to a healthy lifestyle can help individuals with high genetic risk reduce their lifetime risk of CAD, the extent to which blood lipid levels affect CAD risk in individuals with varying genetic risk remains unknown. To explore how genetics, blood lipids and CAD risk interact, we derived a novel genome-wide polygenic risk score (PRS) for CAD. We then applied the PRS to individuals from the UK Biobank and divided them into Low PRS (bottom 10 percentiles of PRS distribution), Intermediate PRS (PRS in the 10th-90th percentiles), and High PRS (top 10 percentiles), and further stratified individuals by blood lipid levels. We found that the elevated CAD risk conferred by high low-density lipoprotein cholesterol (LDL-C) was modified by the interaction with PRS (P-value interaction: <0.005). Individuals with High PRS and whose LDL-C was Borderline (between 130 and 160 mg/dL) had higher CAD relative risk (HR 3.10; 95% CI, 2.55-3.76) than those at Intermediate PRS whose LDL-C were Very High (>190 mg/dL; HR 2.77; 95% CI, 2.33-3.28). Furthermore, individuals with High PRS but whose lipid levels were below the following thresholds did not have a significantly increased risk for incident CAD: LDL-C <130 mg/dL, total Cholesterol (TC) <200 mg/dL, LDL-C:HDL <2.0 and TC:HDL <3.0. In addition, individuals with Low PRS and Very High LDL-C (>190 mg/dl) did not have increased CAD risk, which was comparable to individuals with Intermediate PRS and Optimal LDL-C (<130 mg/dL). Our results have important implications for the primary prevention of coronary artery disease. Currently, healthy individuals with Borderline LDL-C (130-159 mg/dL) are not considered to be at high risk of CAD. Here we demonstrate that the combination of Borderline LDL-C and High PRS results in CAD relative risk which is greater than individuals without high polygenic risk, but whose LDL-C levels are high enough for statins to be recommended (>190 mg/dL). This analysis therefore demonstrates that PRS can identify a proportion of the population who are at high-risk of CAD but who are invisible to current approaches for assessing CAD risk. Moreover, of perhaps greater significance is the evidence that individuals who have a combination of High PRS and Optimal blood lipid levels do not have greater risk of CAD than individuals without high polygenic risk and the same Optimal blood lipid levels. Our results suggest that high polygenic risk for CAD could be overcome by controlling blood lipid levels. We propose that incorporating PRS into CAD risk assessment early in life could allow individuals at high polygenic risk to benefit from tailored blood lipid guidelines and avoid lifetime exposure to potentially damaging PRS-dependent LDL-C levels.