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Cardiometabolic diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1–3. Polygenic scores (PGS) aggregate these into a metric representing an individual’s genetic predisposition to disease. PGS have shown promise for early risk prediction4–7 and there is an open question as to whether PGS can also be used to understand disease biology8. Here, we demonstrate that cardiometabolic disease PGS can be used to elucidate the proteins underlying disease pathogenesis. In 3,087 healthy individuals, we found that PGS for coronary artery disease, type 2 diabetes, chronic kidney disease and ischaemic stroke are associated with the levels of 49 plasma proteins. Associations were polygenic in architecture, largely independent of cis and trans protein quantitative trait loci and present for proteins without quantitative trait loci. Over a follow-up of 7.7 years, 28 of these proteins associated with future myocardial infarction or type 2 diabetes events, 16 of which were mediators between polygenic risk and incident disease. Twelve of these were druggable targets with therapeutic potential. Our results demonstrate the potential for PGS to uncover causal disease biology and targets with therapeutic potential, including those that may be missed by approaches utilizing information at a single locus., Ritchie et al. use polygenic scores to identify plasma proteins with causal roles in cardiometabolic disease.

Background Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. Methods and findings Using data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million individuals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703–0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009–0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40–75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 individuals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to, Luanluan Sun and colleagues investigate whether adding polygenic risk scores to conventional risk factors of cardiovascular disease helps predict disease risk., Author summary Why was this study done? Application of polygenic risk scores (PRSs) has opened opportunities to enhance risk stratification and prevention for common diseases. The clinical utility of PRSs in cardiovascular disease (CVD) risk prediction is, however, uncertain. Previous analyses have generally focused only on coronary heart disease (CHD) rather than the composite outcome of CHD and stroke, and have often lacked modelling of clinical implications of initiating guideline-recommended interventions (e.g., statin therapy). What did the researchers do and find? We quantified the incremental predictive gain with PRSs on top of conventional risk factors using data on 306,654 individuals from UK Biobank. We modelled the population health implications of initiating statin therapy as recommended by current guidelines using data from 2.1 million individuals from the Clinical Practice Research Datalink. Addition of information on PRSs to a conventional risk prediction model increased the C-index (a measure of risk discrimination) and improved risk classification of cases and non-cases. We estimated that targeted assessment of PRSs among people at intermediate (i.e., 5% to

IMPORTANCE: Acquisition of reliable randomized clinical trial evidence of the effects of cardiovascular interventions on cognitive decline is a priority. OBJECTIVES: To estimate the association of cognitive aging with the avoidance of vascular events in cardiovascular intervention trials and understand whether reports of nonsignificant results exclude worthwhile benefit. DESIGN, SETTING, AND PARTICIPANTS: This secondary analysis of 3 randomized clinical trials in participants with preexisting occlusive vascular disease or diabetes included survivors to final in-trial follow-up in the Heart Protection Study (HPS), Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine (SEARCH), and Treatment of HDL (High-Density Lipoprotein) to Reduce the Incidence of Vascular Events (HPS2-THRIVE) trials of lipid modification for prevention of cardiovascular events. Data were collected from February 1994 through January 2013 and analyzed from January 2015 through December 2018. EXPOSURES: Incident vascular events and diabetes and statin therapy. MAIN OUTCOMES AND MEASURES: Cognitive function was assessed at the end of a mean (SD) of 4.9 (1.5) years of follow-up using a 14-item verbal test. Associations of the incidence of vascular events and new-onset diabetes during the trials, with cognitive function at final in-trial follow-up were estimated and expressed as years of cognitive aging (using the association of the score with age >60 years). The benefit on cognitive aging mediated through the effects of lowering low-density lipoprotein cholesterol levels on events was estimated by applying these findings to nonfatal event differences observed with statin therapy in the HPS trial. RESULTS: Among 45 029 participants undergoing cognitive assessment, mean (SD) age was 67.9 (8.0) years; 80.7% were men. Incident stroke (n = 1197) was associated with 7.1 (95% CI, 5.7-8.5) years of cognitive aging; incident transient ischemic attack, myocardial infarction, heart failure, and new-onset diabetes were associated with 1 to 2 years of cognitive aging. In HPS, randomization to statin therapy for 5 years resulted in 2.0% of survivors avoiding a nonfatal stroke or transient ischemic attack and 2.4% avoiding a nonfatal cardiac event, which yielded an expected reduction in cognitive aging of 0.15 (95% CI, 0.11-0.19) years. With 15 926 participants undergoing cognitive assessment, HPS had 80% power to detect a 1-year (ie, 20% during the 5 years) difference in cognitive aging. CONCLUSIONS AND RELEVANCE: The expected cognitive benefits of the effects of preventive therapies on cardiovascular events during even the largest randomized clinical trials may have been too small to be detectable. Hence, nonsignificant findings may not provide good evidence of a lack of worthwhile benefit on cognitive function with prolonged use of such therapies. TRIAL REGISTRATION: isrctn.com and ClinicalTrials.gov Identifiers: ISRCTN48489393, ISRCTN74348595, and NCT00461630.

Background Lean body mass has been identified as a key determinant of left ventricular mass and wall thickness. However, the importance of lean body mass or other body‐size measures as normative determinants of carotid intima‐media thickness ( cIMT ), a widely used early indicator of atherosclerosis, has not been well established. Methods and Results Carotid artery ultrasound measurements of cIMT and carotid artery plaque burden (derived from plaque number and maximum size) and measurements of body size, including height, body mass index, weight, body fat proportion, and lean body mass ([1−body fat proportion]×weight), were recorded in 25 020 participants from 10 regions of China. Analyses were restricted to a healthy younger subset (n=6617) defined as never or long‐term ex‐regular smokers aged cIMT , but was not associated with plaque burden: overall, each 10 kg higher lean body mass was associated with a 0.03 (95% CI , 0.03–0.04) mm higher cIMT ( P =5×10 −33 ). Fat mass, height, and other body‐size measures were more weakly associated with cIMT . Conclusions The strong association of lean body mass with cIMT, but not with plaque burden, in healthy adults suggests a normative relationship rather than reflecting atherosclerotic pathology. Common mechanisms may underlie the associations of lean body mass with cIMT and with nonatherosclerotic vascular traits.

IMPORTANCE: A better understanding of the role of atherosclerosis in the development of ischemic stroke subtypes could help to improve strategies for prevention of stroke worldwide. OBJECTIVE: To assess the role of carotid atherosclerosis in the association between major cardiovascular risk factors and ischemic stroke subtypes. DESIGN, SETTING, AND PARTICIPANTS: The prospective China Kadoorie Biobank cohort study was conducted in the general population of 5 urban and 5 rural areas in China, with a baseline survey obtained between June 2004 and July 2008. A random sample of 23 973 participants with no history of cardiovascular disease at enrollment who had carotid artery ultrasonographic measurements recorded at a resurvey from September 2013 to June 2014 were included. Data analysis was performed from July 1, 2016, to April 10, 2019. EXPOSURES: Major cardiovascular risk factors (ie, blood pressure [BP], blood lipid levels, smoking, and diabetes). MAIN OUTCOMES AND MEASURES: Carotid ultrasonographic measures of plaque burden (derived from number and maximum size of carotid artery plaques at resurvey) and first ischemic stroke during follow-up (n = 952), with subtyping (data release, August 2018) as lacunar (n = 263), probable large artery (n = 193), probable cardioembolic (n = 66), or unconfirmed (n = 430). Associations between cardiovascular risk factors, carotid plaque burden, and ischemic stroke subtypes were adjusted for age, sex, and geographic area. RESULTS: The 23 973 participants in the study had a mean (SD) age of 50.6 (10.0) years, and 14 833 (61.9%) were women. Systolic BP had a stronger association (odds ratio [OR] per SD, 1.51; 95% CI, 1.42-1.61) than plaque burden (OR per SD, 1.34; 95% CI, 1.26-1.44) with ischemic stroke, and the associations of systolic BP with each subtype of ischemic stroke were modestly attenuated by adjustment for plaque burden. After adjustment for BP, plaque burden had a stronger association with probable large artery stroke (OR, 1.43; 95% CI, 1.24-1.63) than with lacunar stroke (OR, 1.25; 95% CI, 1.10-1.43) but was not associated with probable cardioembolic stroke (OR, 1.06; 95% CI, 0.83-1.36). CONCLUSIONS AND RELEVANCE: Although BP was an important risk factor for all ischemic stroke subtypes, carotid atherosclerosis was an important risk factor only for large artery and lacunar strokes, suggesting that drug treatments targeting atherosclerosis may reduce the risk of stroke subtypes to different extents.