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Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions — familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background — the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant. Genetic variation predisposes to disease via monogenic and polygenic risk variants. Here, the authors assess the interplay between these types of variation on disease penetrance in 80,928 individuals. In carriers of monogenic variants, they show that disease risk is a gradient influenced by polygenic background.

Identification of individuals at highest risk of coronary artery disease (CAD)—ideally before onset—remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPS Mult , that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPS Mult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10–2.19, P  < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPS Mult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70–1.76, P  < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPS Mult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPS Mult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction. A polygenic risk score for coronary artery disease developed using data from individuals of five different ancestries has increased accuracy across diverse populations.

Preliminary reports suggest that the Coronavirus Disease 2019 (COVID− 19) pandemic has led to disproportionate morbidity and mortality among historically disadvantaged populations. We investigate the racial and socioeconomic associations of COVID− 19 hospitalization among 418,794 participants of the UK Biobank, of whom 549 (0.13%) had been hospitalized. Both Black participants (odds ratio 3.7; 95%CI 2.5–5.3) and Asian participants (odds ratio 2.2; 95%CI 1.5–3.2) were at substantially increased risk as compared to White participants. We further observed a striking gradient in COVID− 19 hospitalization rates according to the Townsend Deprivation Index − a composite measure of socioeconomic deprivation − and household income. Adjusting for socioeconomic factors and cardiorespiratory comorbidities led to only modest attenuation of the increased risk in Black participants, adjusted odds ratio 2.4 (95%CI 1.5–3.7). These observations confirm and extend earlier preliminary and lay press reports of higher morbidity in non-White individuals in the context of a large population of participants in a national biobank. The extent to which this increased risk relates to variation in pre-existing comorbidities, differences in testing or hospitalization patterns, or additional disparities in social determinants of health warrants further study.

Polygenic risk scores (PRS) continue to improve with novel methods and expanding genome-wide association studies. Healthcare and commercial laboratories are increasingly deploying PRS reports to patients, but it is unknown how the classification of high polygenic risk changes across individual PRS. Here, we assess the association and classification performance of cataloged PRS for three complex traits. We chronologically order all trait-related publications (Pub n ) and identify the single PRS Best(Pub n ) for each Pub n that has the strongest association with the target outcome. While each Best(Pub n ) demonstrates generally consistent population-level strengths of associations, the classification of individuals in the top 10% of each Best(Pub n ) distribution varies widely. Using the PRSmix framework, which integrates information across several PRS to improve prediction, we generate corresponding ChronoAdd(Pub n ) scores for each Pub n that combine all polygenic scores from all publications up to and including Pub n . When compared with Best(Pub n ), ChronoAdd(Pub n ) scores demonstrate more consistent high-risk classification amongst themselves. This integrative scoring approach provides stable and reliable classification of high-risk individuals and is an adaptable framework into which new scores can be incorporated as they are introduced, integrating easily with current PRS implementation strategies. Variability exists in classifying high-risk individuals across polygenic scores for complex diseases. Here the authors show that an integrative scoring approach improves high-risk classification consistency and overall performance toward more reliable clinical applications.

Several forms of pulmonary hypertension (PH) disproportionately affect women. Animal and human studies suggest that estradiol exerts mixed effects on the pulmonary vasculature. Whether premature menopause represents a risk factor for PH is unknown. In this cohort study, women in the UK Biobank aged 40-69 years who were postmenopausal and had complete data available on reproductive history were included. Premature menopause, defined as menopause occurring before age 40 years. Postmenopausal women without premature menopause served as the reference group. The primary outcome was incident PH, ascertained by appearance of a qualifying ICD code in the participant's UK Biobank study record. Of 136,715 postmenopausal women included, 5,201 (3.8%) had premature menopause. Participants were followed up for a median of 11.1 (interquartile range 10.5-11.8) years. The primary outcome occurred in 38 women (0.73%) with premature menopause and 409 (0.31%) without. After adjustment for age, race, ever-smoking, body-mass index, systolic blood pressure, antihypertensive medication use, non-high-density lipoprotein cholesterol, cholesterol-lowering medication use, C-reactive protein, prevalent type 2 diabetes, obstructive sleep apnea, heart failure, mitral regurgitation, aortic stenosis, venous thromboembolism, forced vital capacity (FVC), the forced expiratory volume in 1 second-to-FVC ratio, use of menopausal hormone therapy, and hysterectomy status, premature menopause was independently associated with PH (hazard ratio 2.13, 95% CI 1.31-3.23, P<0.001). In analyses of alternate menopausal age thresholds, risk of PH appeared to increase progressively with younger age at menopause (Ptrend <0.001), with 4.8-fold risk in women with menopause before age 30 years (95% CI 1.82-12.74, P = 0.002). Use of menopausal hormone therapy did not modify the association of premature menopause with PH. Premature menopause may represent an independent risk factor for PH in women. Further investigation of the role of sex hormones in PH is needed in animal and human studies to elucidate pathobiology and identify novel therapeutic targets.

Prediction models are commonly used to estimate risk for cardiovascular diseases, to inform diagnosis and management. However, performance may vary substantially across relevant subgroups of the population. Here we investigated heterogeneity of accuracy and fairness metrics across a variety of subgroups for risk prediction of two common diseases: atrial fibrillation (AF) and atherosclerotic cardiovascular disease (ASCVD). We calculated the Cohorts for Heart and Aging in Genomic Epidemiology Atrial Fibrillation (CHARGE-AF) score for AF and the Pooled Cohort Equations (PCE) score for ASCVD in three large datasets: Explorys Life Sciences Dataset (Explorys, n = 21,809,334), Mass General Brigham (MGB, n = 520,868), and the UK Biobank (UKBB, n = 502,521). Our results demonstrate important performance heterogeneity across subpopulations defined by age, sex, and presence of preexisting disease, with fairly consistent patterns across both scores. For example, using CHARGE-AF, discrimination declined with increasing age, with a concordance index of 0.72 [95% CI 0.72–0.73] for the youngest (45–54 years) subgroup to 0.57 [0.56–0.58] for the oldest (85–90 years) subgroup in Explorys. Even though sex is not included in CHARGE-AF, the statistical parity difference (i.e., likelihood of being classified as high risk) was considerable between males and females within the 65–74 years subgroup with a value of − 0.33 [95% CI − 0.33 to − 0.33]. We also observed weak discrimination (i.e., < 0.7) and suboptimal calibration (i.e., calibration slope outside of 0.7–1.3) in large subsets of the population; for example, all individuals aged 75 years or older in Explorys (17.4%). Our findings highlight the need to characterize and quantify the behavior of clinical risk models within specific subpopulations so they can be used appropriately to facilitate more accurate, consistent, and equitable assessment of disease risk.

Preeclampsia and gestational hypertension are common pregnancy complications associated with adverse maternal and child outcomes. Current tools for prediction, prevention and treatment are limited. Here we tested the association of maternal DNA sequence variants with preeclampsia in 20,064 cases and 703,117 control individuals and with gestational hypertension in 11,027 cases and 412,788 control individuals across discovery and follow-up cohorts using multi-ancestry meta-analysis. Altogether, we identified 18 independent loci associated with preeclampsia/eclampsia and/or gestational hypertension, 12 of which are new (for example, MTHFR – CLCN6 , WNT3A , NPR3 , PGR and RGL3 ), including two loci ( PLCE1 and FURIN ) identified in the multitrait analysis. Identified loci highlight the role of natriuretic peptide signaling, angiogenesis, renal glomerular function, trophoblast development and immune dysregulation. We derived genome-wide polygenic risk scores that predicted preeclampsia/eclampsia and gestational hypertension in external cohorts, independent of clinical risk factors, and reclassified eligibility for low-dose aspirin to prevent preeclampsia. Collectively, these findings provide mechanistic insights into the hypertensive disorders of pregnancy and have the potential to advance pregnancy risk stratification. A multi-ancestry genetic meta-analysis identifies 12 new loci associated with preeclampsia and gestational hypertension and proposes the integration of polygenic scores and clinical factors for disease prediction

Pathogenic DNA variants associated with familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and Lynch syndrome are widely recognized as clinically important and actionable when identified, leading some clinicians to recommend population-wide genomic screening. To assess the prevalence and clinical importance of pathogenic or likely pathogenic variants associated with each of 3 genomic conditions (familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and Lynch syndrome) within the context of contemporary clinical care. This cohort study used gene-sequencing data from 49 738 participants in the UK Biobank who were recruited from 22 sites across the UK between March 21, 2006, and October 1, 2010. Inpatient hospital data date back to 1977; cancer registry data, to 1957; and death registry data, to 2006. Statistical analysis was performed from July 22, 2019, to November 15, 2019. Pathogenic or likely pathogenic DNA variants classified by a clinical laboratory geneticist. Composite end point specific to each genomic condition based on atherosclerotic cardiovascular disease events for familial hypercholesterolemia, breast or ovarian cancer for hereditary breast and ovarian cancer syndrome, and colorectal or uterine cancer for Lynch syndrome. Among 49 738 participants (mean [SD] age, 57 [8] years; 27 144 female [55%]), 441 (0.9%) harbored a pathogenic or likely pathogenic variant associated with any of 3 genomic conditions, including 131 (0.3%) for familial hypercholesterolemia, 235 (0.5%) for hereditary breast and ovarian cancer syndrome, and 76 (0.2%) for Lynch syndrome. Presence of these variants was associated with increased risk of disease: for familial hypercholesterolemia, 28 of 131 carriers (21.4%) vs 4663 of 49 607 noncarriers (9.4%) developed atherosclerotic cardiovascular disease; for hereditary breast and ovarian cancer syndrome, 32 of 116 female carriers (27.6%) vs 2080 of 27 028 female noncarriers (7.7%) developed associated cancers; and for Lynch syndrome, 17 of 76 carriers (22.4%) vs 929 of 49 662 noncarriers (1.9%) developed colorectal or uterine cancer. The predicted probability of disease at age 75 years despite contemporary clinical care was 45.3% for carriers of familial hypercholesterolemia, 41.1% for hereditary breast and ovarian cancer syndrome, and 38.3% for Lynch syndrome. Across the 3 conditions, 39.7% (175 of 441) of the carriers reported a family history of disease vs 23.2% (34 517 of 148 772) of noncarriers. The findings suggest that approximately 1% of the middle-aged adult population in the UK Biobank harbored a pathogenic variant associated with any of 3 genomic conditions. These variants were associated with an increased risk of disease despite contemporary clinical care and were not reliably detected by family history.

Familial hypercholesterolemia variants impair clearance of cholesterol from the circulation and increase risk of coronary artery disease (CAD). The extent to which adherence to a healthy lifestyle is associated with a lower risk of CAD in carriers and noncarriers of variants warrants further study. To assess the association of the interaction between familial hypercholesterolemia variants and adherence to a healthy lifestyle with risk of CAD. This cross-sectional study used 2 independent data sets with gene sequencing and lifestyle data from the UK Biobank: a case-control study of 4896 cases and 5279 controls and a cohort study of 39 920 participants. Participants were recruited from 22 sites across the UK between March 21, 2006, and October 1, 2010. The case-control study included participants with CAD and controls at enrollment. The cohort study used a convenience sample of individuals with available gene sequencing data. Statistical analysis was performed from April 2, 2019, to January 20, 2022. Pathogenic or likely pathogenic DNA variants classified by a clinical laboratory geneticist and adherence to a healthy lifestyle based on a 4-point scoring system (1 point for each of the following: healthy diet, regular exercise, not smoking, and absence of obesity). Coronary artery disease, defined as myocardial infarction in the case-control study, and myocardial infarction, ischemic heart disease, or coronary revascularization procedure in the cohort study. The case-control study included 10 175 participants (6828 men [67.1%]; mean [SD] age, 58.6 [7.2] years), and the cohort study included 39 920 participants (18 802 men [47.1%]; mean [SD] age at the end of follow-up, 66.4 [8.0] years). A variant was identified in 35 of 4896 cases (0.7%) and 12 of 5279 controls (0.2%), corresponding to an odds ratio of 3.0 (95% CI, 1.6-5.9), and a variant was identified in 108 individuals (0.3%) in the cohort study, in which the hazard ratio for CAD was 3.8 (95% CI, 2.5-5.8). However, this risk appeared to vary according to lifestyle categories in both carriers and noncarriers of familial hypercholesterolemia variants, without a significant interaction between carrier status and lifestyle (odds ratio, 1.2 [95% CI, 0.6-2.5]; P = .62). Among carriers, a favorable lifestyle conferred 86% lower risk of CAD compared with an unfavorable lifestyle (hazard ratio, 0.14 [95% CI, 0.04-0.41]). The estimated risk of CAD by the age of 75 years varied according to lifestyle, ranging from 10.2% among noncarriers with a favorable lifestyle to 24.0% among noncarriers with an unfavorable lifestyle and ranging from 34.5% among carriers with a favorable lifestyle to 66.2% among carriers with an unfavorable lifestyle. This study suggests that, among carriers and noncarriers of a familial hypercholesterolemia variant, significant gradients in risk of CAD are noted according to adherence to a healthy lifestyle pattern. Similar to the general population, individuals who carry familial hypercholesterolemia variants are likely to benefit from lifestyle interventions to reduce their risk of CAD.

Aims Recent aspirin primary prevention trials failed to identify a net benefit of aspirin for preventing cardiovascular disease vs. the harms of bleeding. This study aimed to investigate whether a high-risk subgroup, individuals with elevated genetic predisposition to coronary artery disease (CAD), might derive more benefit than harm with aspirin, compared to those with lower genetic risk. Methods and results We performed genetic risk stratification of the Aspirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial using a CAD polygenic risk score (GPSMult). For 12 031 genotyped participants (5974 aspirin, 6057 placebo) overall, we stratified them by GPSMult quintiles (q1–5), then examined risk of CAD (composite of myocardial infarction and coronary heart disease death) and bleeding events using Cox models. During a median 4.6 years of follow-up with randomization to 100 mg/day aspirin vs. placebo, 234 (1.9%) participants had CAD and 373 (3.1%) had bleeding events. In the overall cohort, aspirin resulted in higher bleeding risk [adjusted Hazard ratio (aHR) = 1.30 (1.06–1.61), P = 0.01] but no significant CAD reduction [aHR = 0.84 (0.64–1.09), P = 0.19]. However, among the highest quintile of polygenic risk (q5, top 20% of the GPSMult distribution), there was a 47% reduction in risk of CAD events with aspirin [aHR = 0.53 (0.31–0.90), P = 0.02] without increased bleeding risk [aHR = 1.05 (0.60–1.82), P = 0.88]. Interaction between the GPSMult and aspirin was significant for CAD (q5 vs. q1, P = 0.02) but not bleeding (P = 0.80). Conclusion The balance between net benefit and harm on aspirin in the primary prevention setting shifts favourably in individuals with an elevated genetic predisposition.