Numerous genetic loci influence systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans 1-3. We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N=74,064) and follow-up studies (N=48,607), we identified at genome-wide significance (P= 2.7×10-8 to P=2.3×10-13) four novel PP loci (at 4q12 near CHIC2/PDGFRAI, 7q22.3 near PIK3CG, 8q24.12 in NOV, 11q24.3 near ADAMTS-8), two novel MAP loci (3p21.31 in MAP4, 10q25.3 near ADRB1) and one locus associated with both traits (2q24.3 near FIGN) which has recently been associated with SBP in east Asians. For three of the novel PP signals, the estimated effect for SBP was opposite to that for DBP, in contrast to the majority of common SBP- and DBP-associated variants which show concordant effects on both traits. These findings indicate novel genetic mechanisms underlying blood pressure variation, including pathways that may differentially influence SBP and DBP.

IMPORTANCE Polygenic risk scores comprising millions of single-nucleotide polymorphisms (SNPs) could be useful for population-wide coronary heart disease (CHD) screening.OBJECTIVE To determine whether a polygenic risk score improves prediction of CHD compared with a guideline-recommended clinical risk equation. DESIGN, SETTING, AND PARTICIPANTSA retrospective cohort study of the predictive accuracy of a previously validated polygenic risk score was assessed among 4847 adults of white European ancestry, aged 45 through 79 years, participating in the Atherosclerosis Risk in Communities (ARIC) study and 2390 participating in the Multi-Ethnic Study of Atherosclerosis (MESA) from 1996 through December 31, 2015, the final day of follow-up. The performance of the polygenic risk score was compared with that of the 2013 American College of Cardiology and American Heart Association pooled cohort equations.EXPOSURES Genetic risk was computed for each participant by summing the product of the weights and allele dosage across 6 630 149 SNPs. Weights were based on an international genome-wide association study.MAIN OUTCOMES AND MEASURES Prediction of 10-year first CHD events (including myocardial infarctions, fatal coronary events, silent infarctions, revascularization procedures, or resuscitated cardiac arrest) assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI). RESULTSThe study population included 4847 adults from the ARIC study (mean [SD] age, 62.9 [5.6] years; 56.4% women) and 2390 adults from the MESA cohort (mean [SD] age, 61.8 [9.6] years; 52.2% women). Incident CHD events occurred in 696 participants (14.4%) and 227 participants (9.5%), respectively, over median follow-up of 15.5 years (interquartile range [IQR], 6.3 years) and 14.2 (IQR, 2.5 years) years. The polygenic risk score was significantly associated with 10-year CHD incidence in ARIC with hazard ratios per SD increment of 1.24 (95% CI, 1.15 to 1.34) and in MESA, 1.38 (95% CI, 1.21 to 1.58). Addition of the polygenic risk score to the pooled cohort equations did not significantly increase the C statistic in either cohort (ARIC, change in C statistic, −0.001; 95% CI, −0.009 to 0.006; MESA, 0.021; 95% CI, −0.0004 to 0.043). At the 10-year risk threshold of 7.5%, the addition of the polygenic risk score to the pooled cohort equations did not provide significant improvement in reclassification in either ARIC (NRI, 0.018, 95% CI, −0.012 to 0.036) or MESA (NRI, 0.001, 95% CI, −0.038 to 0.076). The polygenic risk score did not significantly improve calibration in either cohort. CONCLUSIONS AND RELEVANCEIn this analysis of 2 cohorts of US adults, the polygenic risk score was associated with incident coronary heart disease events but did not significantly improve discrimination, calibration, or risk reclassification compared with conventional predictors. These findings suggest that a polygenic risk score may not enhance risk prediction in a general, white middle-aged population.

Objective To evaluate whether early initiation of prophylactic anticoagulation compared with no anticoagulation was associated with decreased risk of death among patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United States. Design Observational cohort study. Setting Nationwide cohort of patients receiving care in the Department of Veterans Affairs, a large integrated national healthcare system. Participants All 4297 patients admitted to hospital from 1 March to 31 July 2020 with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and without a history of anticoagulation. Main outcome measures The main outcome was 30 day mortality. Secondary outcomes were inpatient mortality, initiating therapeutic anticoagulation (a proxy for clinical deterioration, including thromboembolic events), and bleeding that required transfusion. Results Of 4297 patients admitted to hospital with covid-19, 3627 (84.4%) received prophylactic anticoagulation within 24 hours of admission. More than 99% (n=3600) of treated patients received subcutaneous heparin or enoxaparin. 622 deaths occurred within 30 days of hospital admission, 513 among those who received prophylactic anticoagulation. Most deaths (510/622, 82%) occurred during hospital stay. Using inverse probability of treatment weighted analyses, the cumulative incidence of mortality at 30 days was 14.3% (95% confidence interval 13.1% to 15.5%) among those who received prophylactic anticoagulation and 18.7% (15.1% to 22.9%) among those who did not. Compared with patients who did not receive prophylactic anticoagulation, those who did had a 27% decreased risk for 30 day mortality (hazard ratio 0.73, 95% confidence interval 0.66 to 0.81). Similar associations were found for inpatient mortality and initiation of therapeutic anticoagulation. Receipt of prophylactic anticoagulation was not associated with increased risk of bleeding that required transfusion (hazard ratio 0.87, 0.71 to 1.05). Quantitative bias analysis showed that results were robust to unmeasured confounding (e-value lower 95% confidence interval 1.77 for 30 day mortality). Results persisted in several sensitivity analyses. Conclusions Early initiation of prophylactic anticoagulation compared with no anticoagulation among patients admitted to hospital with covid-19 was associated with a decreased risk of 30 day mortality and no increased risk of serious bleeding events. These findings provide strong real world evidence to support guidelines recommending the use of prophylactic anticoagulation as initial treatment for patients with covid-19 on hospital admission.

The time course of cardiovascular disease (CVD) risk after smoking cessation is unclear. Risk calculators consider former smokers to be at risk for only 5 years. OBJECTIVE To evaluate the association between years since quitting smoking and incident CVD. DESIGN, SETTING, AND PARTICIPANTS Retrospective analysis of prospectively collected data from Framingham Heart Study participants without baseline CVD (original cohort: attending their fourth examination in 1954-1958; offspring cohort: attending their first examination in 1971-1975) who were followed up through December 2015. EXPOSURES Time-updated self-reported smoking status, years since quitting, and cumulative pack-years. MAIN OUTCOMES AND MEASURES Incident CVD (myocardial infarction, stroke, heart failure, or cardiovascular death). Primary analyses included both cohorts (pooled) and were restricted to heavy ever smokers (Ն20 pack-years). RESULTS The study population included 8770 individuals (original cohort: n = 3805; offspring cohort: n = 4965) with a mean age of 42.2 (SD, 11.8) years and 45% male. There were 5308 ever smokers with a median 17.2 (interquartile range, 7-30) baseline pack-years, including 2371 heavy ever smokers (406 [17%] former and 1965 [83%] current). Over 26.4 median follow-up years, 2435 first CVD events occurred (original cohort: n = 1612 [n = 665 among heavy smokers]; offspring cohort: n = 823 [n = 430 among heavy smokers]). In the pooled cohort, compared with current smoking, quitting within 5 years was associated with significantly lower rates of incident CVD (incidence rates per 1000 person-years: current smoking, 11.56 [95% CI, 10.30-12.98]; quitting within 5 years, 6.94 [95% CI, 5.61-8.59]; difference, −4.51 [95% CI, −5.90 to −2.77]) and lower risk of incident CVD (hazard ratio, 0.61; 95% CI, 0.49-0.76). Compared with never smoking, quitting smoking ceased to be significantly associated with greater CVD risk between 10 and 15 years after cessation in the pooled cohort (incidence rates per 1000 person-years: never smoking, 5.09 [95% CI, 4.52-5.74]; quitting within 10 to <15 years, 6.31 [95% CI, 4.93-8.09]; difference, 1.27 [95% CI, −0.10 to 3.05]; hazard ratio, 1.25 [95% CI, 0.98-1.60]). CONCLUSIONS AND RELEVANCE Among heavy smokers, smoking cessation was associated with significantly lower risk of CVD within 5 years relative to current smokers. However, relative to never smokers, former smokers' CVD risk remained significantly elevated beyond 5 years after smoking cessation.

The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL (http://www.genabel.org) and CRAN (http://cran.r-project.org/).