Improving reporting standards for polygenic scores in risk prediction studies.

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

Polygenic risk scores for the prediction of cardiometabolic disease.

Cardiometabolic diseases contribute more to global morbidity and mortality than any other group of disorders. Polygenic risk scores (PRSs), the weighted summation of individually small-effect genetic variants, represent an advance in our ability to predict the development and complications of cardiometabolic diseases. This article reviews the evidence supporting the use of PRS in seven common cardiometabolic diseases: coronary artery disease (CAD), stroke, hypertension, heart failure and cardiomyopathies, obesity, atrial fibrillation (AF), and type 2 diabetes mellitus (T2DM). Data suggest that PRS for CAD, AF, and T2DM consistently improves prediction when incorporated into existing clinical risk tools. In other areas such as ischaemic stroke and hypertension, clinical application appears premature but emerging evidence suggests that the study of larger and more diverse populations coupled with more granular phenotyping will propel the translation of PRS into practical clinical prediction tools.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Practice variation in the use of tests in UK primary care: a retrospective analysis of 16 million tests performed over 3.3 million patient years in 2015/16.

BACKGROUND: The UK's National Health Service (NHS) is currently subject to unprecedented financial strain. The identification of unnecessary healthcare resource use has been suggested to reduce spending. However, there is little very research quantifying wasteful test use, despite the £3 billion annual expenditure. Geographical variation has been suggested as one metric in which to quantify inappropriate use. We set out to identify tests ordered from UK primary care that are subject to the greatest between-practice variation in their use. METHODS: We used data from 444 general practices within the Clinical Practice Research Datalink to calculate a coefficient of variation (CoV) for the ordering of 44 specific tests from UK general practices. The coefficient of variation was calculated after adjusting for differences between practice populations. We also determined the tests that had both a higher-than-average CoV and a higher-than-average rate of use. RESULTS: In total, 16,496,218 tests were ordered for 4,078,091 patients over 3,311,050 person-years from April 1, 2015, to March 31, 2016. The tests subject to the greatest variation were drug monitoring 158% (95%CI 153 to 163%), urine microalbumin (52% (95%CI 49.9 to 53.2%)), pelvic CT (51% (95%CI 50 to 53%)) and Pap smear (49% (95%CI 48 to 51%). Seven tests were classified as high variability and high rate (clotting, vitamin D, urine albumin, prostate-specific antigen (PSA), bone profile, urine MCS and C-reactive protein (CRP)). CONCLUSIONS: There are wide variations in the use of common tests, which is unlikely to be explained by clinical indications. Since £3 billion annually are spent on tests, this represents considerable variation in the use of resources and inefficient management in the NHS. Our results can be of value to policy makers, researchers, patients and clinicians as the NHS strives towards identifying overuse and underuse of tests.

Medications that reduce emergency hospital admissions: an overview of systematic reviews and prioritisation of treatments.

BACKGROUND: Rates of emergency hospitalisations are increasing in many countries, leading to disruption in the quality of care and increases in cost. Therefore, identifying strategies to reduce emergency admission rates is a key priority. There have been large-scale evidence reviews to address this issue; however, there have been no reviews of medication therapies, which have the potential to reduce the use of emergency health-care services. The objectives of this study were to review systematically the evidence to identify medications that affect emergency hospital admissions and prioritise therapies for quality measurement and improvement. METHODS: This was a systematic review of systematic reviews. We searched MEDLINE, PubMed, the Cochrane Database of Systematic Reviews & Database of Abstracts of Reviews of Effects, Google Scholar and the websites of ten major funding agencies and health charities, using broad search criteria. We included systematic reviews of randomised controlled trials that examined the effect of any medication on emergency hospital admissions among adults. We assessed the quality of reviews using AMSTAR. To prioritise therapies, we assessed the quality of trial evidence underpinning meta-analysed effect estimates and cross-referenced the evidence with clinical guidelines. RESULTS: We identified 140 systematic reviews, which included 1968 unique randomised controlled trials and 925,364 patients. Reviews contained 100 medications tested in 47 populations. We identified high-to moderate-quality evidence for 28 medications that reduced admissions. Of these medications, 11 were supported by clinical guidelines in the United States, the United Kingdom and Europe. These 11 therapies were for patients with heart failure (angiotensin-converting-enzyme inhibitors, angiotensin II receptor blockers, aldosterone receptor antagonists and digoxin), stable coronary artery disease (intensive statin therapy), asthma exacerbations (early inhaled corticosteroids in the emergency department and anticholinergics), chronic obstructive pulmonary disease (long-acting muscarinic antagonists and long-acting beta-2 adrenoceptor agonists) and schizophrenia (second-generation antipsychotics and depot/maintenance antipsychotics). CONCLUSIONS: We identified 11 medications supported by strong evidence and clinical guidelines that could be considered in quality monitoring and improvement strategies to help reduce emergency hospital admission rates. The findings are relevant to health systems with a large burden of chronic disease and those managing increasing pressures on acute health-care services.

The effect of grapefruits (Citrus paradisi) on body weight and cardiovascular risk factors: A systematic review and meta-analysis of randomized clinical trials.

The aim of this systematic review was to evaluate the evidence for or against the effectiveness of grapefruits (Citrus paradisi) on body weight, blood pressure, and lipid profile. Electronic searches were conducted in MEDLINE, EMBASE, AMED, and the Cochrane Clinical Trials databases to identify relevant human randomized clinical trials (RCTs). Hand searches of bibliographies were also conducted. Only overweight and obese subjects were included. The reporting quality was assessed using the CONSORT checklist, and the strength of the overall body of evidence was rated based on the GRADE criteria. One hundred and fifty four citations were identified and three RCTs with a total of 250 participants were included. The RCTs were of moderate quality. A meta-analysis for change in body weight failed to reveal a significant difference between grapefruits and controls, MD: -0.45 kg (95% CI: -1.06 to 0.16; I2 = 53%, but analysis revealed a significant decrease in systolic blood pressure, MD: -2.43 mmHg (95% CI: -4.77 to -0.09; I2 = 0%). Paucity in the number of RCTs, short durations of interventions, and lack of an established minimum effective dose limit the conclusions that can be drawn about the effects of grapefruit on body weight and metabolic parameters. Further clinical trials evaluating the effects of grapefruit are warranted.

GaitKeeper: A System for Measuring Canine Gait.

It is understood gait has the potential to be used as a window into neurodegenerative disorders, identify markers of subclinical pathology, inform diagnostic algorithms of disease progression and measure the efficacy of interventions. Dogs' gaits are frequently assessed in a veterinary setting to detect signs of lameness. Despite this, a reliable, affordable and objective method to assess lameness in dogs is lacking. Most described canine lameness assessments are subjective, unvalidated and at high risk of bias. This means reliable, early detection of canine gait abnormalities is challenging, which may have detrimental implications for dogs' welfare. In this paper, we draw from approaches and technologies used in human movement science and describe a system for objectively measuring temporal gait characteristics in dogs (step-time, swing-time, stance-time). Asymmetries and variabilities in these characteristics are of known clinical significance when assessing lameness but presently may only be assessed on coarse scales or under highly instrumented environments. The system consists an inertial measurement unit, containing a 3-axis accelerometer and gyroscope coupled with a standardized walking course. The measurement unit is attached to each leg of the dog under assessment before it is walked around the course. The data by the measurement unit is then processed to identify steps and subsequently, micro-gait characteristics. This method has been tested on a cohort of 19 healthy dogs of various breeds ranging in height from 34.2 cm to 84.9 cm. We report the system as capable of making precise step delineations with detections of initial and final contact times of foot-to-floor to a mean precision of 0.011 s and 0.048 s, respectively. Results are based on analysis of 12,678 foot falls and we report a sensitivity, positive predictive value and F-score of 0.81, 0.83 and 0.82 respectively. To investigate the effect of gait on system performance, the approach was tested in both walking and trotting with no significant performance deviation with 7249 steps reported for a walking gait and 4977 for a trotting gait. The number of steps reported for each leg were approximately equal and this consistency was true in both walking and trotting gaits. In the walking gait 1965, 1790, 1726 and 1768 steps were reported for the front left, front right, hind left and hind right legs respectively. 1361, 1250, 1176 and 1190 steps were reported for each of the four legs in the trotting gait. The proposed system is a pragmatic and precise solution for obtaining objective measurements of canine gait. With further development, it promises potential for a wide range of applications in both research and clinical practice.

Ten essential papers for the practice of evidence-based medicine.

In this article we signpost readers to 10 papers we consider essential reading for anyone starting out on an evidence-based medicine journey. We have considered papers consisting a mix of old and new, seminal and cutting-edge that offer insight into what evidence-based medicine is, where it came from, why it matters and what it has achieved. This is balanced against some of the common criticisms of evidence-based medicine and efforts to tackle them. We have also highlighted papers acknowledging the importance of teaching and learning of the principles of evidence-based medicine and how health professionals can better use evidence in clinical decisions with patients.

The effects of the cellular and infectious prion protein on the neuronal adaptor protein X11α.

BACKGROUND: The neuronal adaptor protein X11α is a multidomain protein with a phosphotyrosine binding (PTB) domain, two PDZ (PSD_95, Drosophila disks-large, ZO-1) domains, a Munc Interacting (MI) domain and a CASK interacting region. Amongst its functions is a role in the regulation of the abnormal processing of the amyloid precursor protein (APP). It also regulates the activity of Cu/Zn Superoxide dismutase (SOD1) through binding with its chaperone the copper chaperone for SOD1. How X11α production is controlled has remained unclear. METHODS: Using the neuroblastoma cell line, N2a, and knockdown studies, the effect of the cellular and infectious prion protein, PrP(C) and PrP(Sc), on X11α is examined. RESULTS: We show that X11α expression is directly proportional to the expression of PrP(C), whereas its levels are reduced by PrP(Sc). We also show PrP(Sc) to affect X11α at a functional level. One of the effects of prion infection is lowered cellular SOD1 levels, here by knockdown of X11α we identify that the effect of PrP(Sc) on SOD1 can be reversed indicating that X11α is involved in prion disease pathogenesis. CONCLUSIONS: A role for the cellular and infectious prion protein, PrP(C) and PrP(Sc), respectively, in regulating X11α is identified in this work. GENERAL SIGNIFICANCE: Due to the multiple interacting partners of X11α, dysfunction or alteration in X11α will have a significant cellular effect. This work highlights the role of PrP(C) and PrP(Sc) in the regulation of X11α, and provides a new target pathway to control X11α and its related functions.

Development of a heat-mediated protein blotting method.

Western blotting is a significant tool employed for the detection of cell proteins. High-molecular-weight proteins have proven a challenge to detect by western blotting, but proteins even of 100 KDa can still present difficulties in detection. This work reports the development of a heat transfer method that is suitable for both low- and high-molecular-weight proteins. The procedure involves the use of a constant temperature at 78 °C in a dedicated heat transfer module. Through the use of this protocol the neuronal adaptor protein X11α (120 KDa), which prior to this methodology was undetectable endogenously in the neuroblastoma cell line (N2a), was successfully detected in the N2a cell line. The procedure provides a reproducible protocol that can be adapted for other high-molecular-weight proteins, and it provides the advantage that low-molecular-weight proteins are not sacrificed by the methodology.

Written information for patients (or parents of child patients) to reduce the use of antibiotics for acute upper respiratory tract infections in primary care.

BACKGROUND: Acute upper respiratory tract infections (URTIs) are frequently managed in primary care settings. Although many are viral, and there is an increasing problem with antibiotic resistance, antibiotics continue to be prescribed for URTIs. Written patient information may be a simple way to reduce antibiotic use for acute URTIs. OBJECTIVES: To assess if written information for patients (or parents of child patients) reduces the use of antibiotics for acute URTIs in primary care. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, CINAHL, LILACS, Web of Science, clinical trials.gov, and the World Health Organization (WHO) trials registry up to July 2016 without language or publication restrictions. SELECTION CRITERIA: We included randomised controlled trials (RCTs) involving patients (or parents of child patients) with acute URTIs, that compared written patient information delivered immediately before or during prescribing, with no information. RCTs needed to have measured our primary outcome (antibiotic use) to be included. DATA COLLECTION AND ANALYSIS: Two review authors screened studies, extracted data, and assessed study quality. We could not meta-analyse included studies due to significant methodological and statistical heterogeneity; we summarised the data narratively. MAIN RESULTS: Two RCTs met our inclusion criteria, involving a total of 827 participants. Both studies only recruited children with acute URTIs (adults were not involved in either study): 558 children from 61 general practices in England and Wales; and 269 primary care doctors who provided data on 33,792 patient-doctor consultations in Kentucky, USA. The UK study had a high risk of bias due to lack of blinding and the US cluster-randomised study had a high risk of bias because the methods to allocate participants to treatment groups was not clear, and there was evidence of baseline imbalance.In both studies, clinicians provided written information to parents of child patients during primary care consultations: one trained general practitioners (GPs) to discuss an eight-page booklet with parents; the other conducted a factorial trial with two comparison groups (written information compared to usual care and written information plus prescribing feedback to clinicians compared to prescribing feedback alone). Doctors in the written information arms received 25 copies of two-page government-sponsored pamphlets to distribute to parents.Compared to usual care, we found moderate quality evidence (one study) that written information significantly reduced the number of antibiotics used by patients (RR 0.53, 95% CI 0.35 to 0.80; absolute risk reduction (ARR) 20% (22% versus 42%)) and had no significant effect on reconsultation rates (RR 0.79, 95% CI 0.47 to 1.32), or parent satisfaction with consultation (RR 0.95, 95% CI 0.87 to 1.03). Low quality evidence (two studies) demonstrated that written information also reduced antibiotics prescribed by clinicians (RR 0.47, 95% CI 0.28 to 0.78; ARR 21% (20% versus 41%); and RR 0.84, 95% CI 0.81 to 0.86; 9% ARR (45% versus 54%)). Neither study measured resolution of symptoms, patient knowledge about antibiotics for acute URTIs, or complications for this comparison.Compared to prescribing feedback, we found low quality evidence that written information plus prescribing feedback significantly increased the number of antibiotics prescribed by clinicians (RR 1.13, 95% CI 1.09 to 1.17; absolute risk increase 6% (50% versus 44%)). Neither study measured reconsultation rate, resolution of symptoms, patient knowledge about antibiotics for acute URTIs, patient satisfaction with consultation or complications for this comparison. AUTHORS' CONCLUSIONS: Compared to usual care, moderate quality evidence from one study showed that trained GPs providing written information to parents of children with acute URTIs in primary care can reduce the number of antibiotics used by patients without any negative impact on reconsultation rates or parental satisfaction with consultation. Low quality evidence from two studies shows that, compared to usual care, GPs prescribe fewer antibiotics for acute URTIs but prescribe more antibiotics when written information is provided alongside prescribing feedback (compared to prescribing feedback alone). There was no evidence addressing resolution of patients' symptoms, patient knowledge about antibiotics for acute URTIs, or frequency of complications.To fill evidence gaps, future studies should consider testing written information on antibiotic use for adults with acute URTIs in high- and low-income settings provided without clinician training and presented in different formats (such as electronic). Future study designs should endeavour to ensure blinded outcome assessors. Study aims should include measurement of the effect of written information on the number of antibiotics used by patients and prescribed by clinicians, patient satisfaction, reconsultation, patients' knowledge about antibiotics, resolution of symptoms, and complications.

Genetic architecture of cardiac dynamic flow volumes.

Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.

Personalized digital behaviour interventions increase short-term physical activity: a randomized control crossover trial substudy of the MyHeart Counts Cardiovascular Health Study.

Aims: Physical activity is associated with decreased incidence of the chronic diseases associated with aging. We previously demonstrated that digital interventions delivered through a smartphone app can increase short-term physical activity. Methods and results: We offered enrolment to community-living iPhone-using adults aged ≥18 years in the USA, UK, and Hong Kong who downloaded the MyHeart Counts app. After completion of a 1-week baseline period, e-consented participants were randomized to four 7-day interventions. Interventions consisted of: (i) daily personalized e-coaching based on the individual's baseline activity patterns, (ii) daily prompts to complete 10 000 steps, (iii) hourly prompts to stand following inactivity, and (iv) daily instructions to read guidelines from the American Heart Association (AHA) website. After completion of one 7-day intervention, participants subsequently randomized to the next intervention of the crossover trial. The trial was completed in a free-living setting, where neither the participants nor investigators were blinded to the intervention. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in a modified intention-to-treat analysis (modified in that participants had to complete 7 days of baseline monitoring and at least 1 day of an intervention to be included in analyses). This trial is registered with ClinicalTrials.gov, NCT03090321. Conclusion: Between 1 January 2017 and 1 April 2022, 4500 participants consented to enrol in the trial (a subset of the approximately 50 000 participants in the larger MyHeart Counts study), of whom 2458 completed 7 days of baseline monitoring (mean daily steps 4232 ± 73) and at least 1 day of one of the four interventions. Personalized e-coaching prompts, tailored to an individual based on their baseline activity, increased step count significantly (+402 ± 71 steps from baseline, P = 7.1⨯10-8). Hourly stand prompts (+292 steps from baseline, P = 0.00029) and a daily prompt to read AHA guidelines (+215 steps from baseline, P = 0.021) were significantly associated with increased mean daily step count, while a daily reminder to complete 10 000 steps was not (+170 steps from baseline, P = 0.11). Digital studies have a significant advantage over traditional clinical trials in that they can continuously recruit participants in a cost-effective manner, allowing for new insights provided by increased statistical power and refinement of prior signals. Here, we present a novel finding that digital interventions tailored to an individual are effective in increasing short-term physical activity in a free-living cohort. These data suggest that participants are more likely to react positively and increase their physical activity when prompts are personalized. Further studies are needed to determine the effects of digital interventions on long-term outcomes.

Constrictive Pericarditis Revealing Rare Case of ALH Amyloidosis With Underlying Lymphoplasmacytic Lymphoma (Waldenstrom Macroglobulinemia).

We present a case of pericardial amyloidosis with associated lymphoplasmacytic lymphoma in a patient with chronic worsening shortness of breath and cough. This case highlights the wide variation in the presentation of cardiac amyloidosis, and the rare occurrence of clinically significant light-chain and heavy-chain amyloidosis in the pericardium. (Level of Difficulty: Advanced.).

Interactions of physical activity, muscular fitness, adiposity, and genetic risk for NAFLD.

Genetic predisposition and unhealthy lifestyle are risk factors for nonalcoholic fatty liver disease (NAFLD). We investigated whether the genetic risk of NAFLD is modified by physical activity, muscular fitness, and/or adiposity. In up to 242,524 UK Biobank participants without excessive alcohol intake or known liver disease, we examined cross-sectional interactions and joint associations of physical activity, muscular fitness, body mass index (BMI), and a genetic risk score (GRS) with alanine aminotransferase (ALT) levels and the proxy definition for suspected NAFLD of ALT levels > 30 U/L in women and >40 U/L in men. Genetic predisposition to NAFLD was quantified using a GRS consisting of 68 loci known to be associated with chronically elevated ALT. Physical activity was assessed using accelerometry, and muscular fitness was estimated by measuring handgrip strength. We found that increased physical activity and grip strength modestly attenuate genetic predisposition to elevation in ALT levels, whereas higher BMI markedly amplifies it (all p values < 0.001). Among those with normal weight and high level of physical activity, the odds of suspected NAFLD were 1.6-fold higher in those with high versus low genetic risk (reference group). In those with high genetic risk, the odds of suspected NAFLD were 12-fold higher in obese participants with low physical activity versus those with normal weight and high physical activity (odds ratio for NAFLD = 19.2 and 1.6, respectively, vs. reference group). Conclusion: In individuals with high genetic predisposition for NAFLD, maintaining a normal body weight and increased physical activity may reduce the risk of NAFLD.

Reproducibility in the UK biobank of genome-wide significant signals discovered in earlier genome-wide association studies.

With the establishment of large biobanks, discovery of single nucleotide variants (SNVs, also known as single nucleotide polymorphisms (SNVs)) associated with various phenotypes has accelerated. An open question is whether genome-wide significant SNVs identified in earlier genome-wide association studies (GWAS) are replicated in later GWAS conducted in biobanks. To address this, we examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, "discovery" GWAS and a later, "replication" GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNVs (of which 6289 reached P < 5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0%; although lower for binary than quantitative phenotypes (58.1% versus 94.8% respectively). There was a 18.0% decrease in SNV effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNV effect size, phenotype trait (binary or quantitative), and discovery P value, we built and validated a model that predicted SNV replication with area under the Receiver Operator Curve = 0.90. While non-replication may reflect lack of power rather than genuine false-positives, these results provide insights about which discovered associations are likely to be replicated across subsequent GWAS.

Combining Clinical and Polygenic Risk Improves Stroke Prediction Among Individuals With Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable; however, current risk stratification tools (CHA2DS2-VASc) do not include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS). METHODS: Using data from the largest available genome-wide association study in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank, both independently and integrated with clinical risk factors. The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. RESULTS: Compared with the currently recommended risk tool (CHA2DS2-VASc), the integrated tool significantly improved Net Reclassification Index (2.3% [95% CI, 1.3%-3.0%]) and fit (χ2P=0.002). Using this improved tool, >115 000 people with AF would have improved risk classification in the United States. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (hazard ratio, 1.13 per 1 SD [95% CI, 1.06-1.23]). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson correlation coefficient, -0.018). CONCLUSIONS: In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors; however, the prediction of stroke remains challenging.