Stroke genetics informs drug discovery and risk prediction across ancestries.

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

A polygenic risk score predicts atrial fibrillation in cardiovascular disease.

AIMS: Interest in targeted screening programmes for atrial fibrillation (AF) has increased, yet the role of genetics in identifying patients at highest risk of developing AF is unclear. METHODS AND RESULTS: A total of 36,662 subjects without prior AF were analyzed from four TIMI trials. Subjects were divided into quintiles using a validated polygenic risk score (PRS) for AF. Clinical risk for AF was calculated using the CHARGE-AF model. Kaplan-Meier event rates, adjusted hazard ratios (HRs), C-indices, and net reclassification improvement were used to determine if the addition of the PRS improved prediction compared with clinical risk and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Over 2.3 years, 1018 new AF cases developed. AF PRS predicted a significant risk gradient for AF with a 40% increased risk per 1-SD increase in PRS [HR: 1.40 (1.32-1.49); P < 0.001]. Those with high AF PRS (top 20%) were more than two-fold more likely to develop AF [HR 2.45 (1.99-3.03), P < 0.001] compared with low PRS (bottom 20%). Furthermore, PRS provided an additional gradient of risk stratification on top of the CHARGE-AF clinical risk score, ranging from a 3-year incidence of 1.3% in patients with low clinical and genetic risk to 8.7% in patients with high clinical and genetic risk. The subgroup of patients with high clinical risk, high PRS, and elevated NT-proBNP had an AF risk of 16.7% over 3 years. The C-index with the CHARGE-AF clinical risk score alone was 0.65, which improved to 0.67 (P < 0.001) with the addition of NT-proBNP, and increased further to 0.70 (P < 0.001) with the addition of the PRS. CONCLUSION: In patients with cardiovascular conditions, AF PRS is a strong independent predictor of incident AF that provides complementary predictive value when added to a validated clinical risk score and NT-proBNP.

Clinical Application of a Novel Genetic Risk Score for Ischemic Stroke in Patients With Cardiometabolic Disease.

BACKGROUND: Genome-wide association studies have identified single-nucleotide polymorphisms that are associated with an increased risk of stroke. We sought to determine whether a genetic risk score (GRS) could identify subjects at higher risk for ischemic stroke after accounting for traditional clinical risk factors in 5 trials across the spectrum of cardiometabolic disease. METHODS: Subjects who had consented for genetic testing and who were of European ancestry from the ENGAGE AF-TIMI 48 (Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation), SOLID-TIMI 52 (Stabilization of Plaques Using Darapladib), SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus), PEGASUS-TIMI 54 (Prevention of Cardiovascular Events in Patients With Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin), and FOURIER (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Patients With Elevated Risk) trials were included in this analysis. A set of 32 single-nucleotide polymorphisms associated with ischemic stroke was used to calculate a GRS in each patient and identify tertiles of genetic risk. A Cox model was used to calculate hazard ratios for ischemic stroke across genetic risk groups, adjusted for clinical risk factors. RESULTS: In 51 288 subjects across the 5 trials, a total of 960 subjects had an ischemic stroke over a median follow-up period of 2.5 years. After adjusting for clinical risk factors, a higher GRS was strongly and independently associated with increased risk for ischemic stroke (P trend=0.009). In comparison with individuals in the lowest third of the GRS, individuals in the middle and top tertiles of the GRS had adjusted hazard ratios of 1.15 (95% CI, 0.98-1.36) and 1.24 (95% CI 1.05-1.45) for ischemic stroke, respectively. Stratification into subgroups revealed that the performance of the GRS appeared stronger in the primary prevention cohort with an adjusted hazard ratio for the top versus lowest tertile of 1.27 (95% CI, 1.04-1.53), in comparison with an adjusted hazard ratio of 1.06 (95% CI, 0.81-1.41) in subjects with previous stroke. In an exploratory analysis of patients with atrial fibrillation and CHA2DS2-VASc score of 2, high genetic risk conferred a 4-fold higher risk of stroke and an absolute risk equivalent to those with CHA2DS2-VASc score of 3. CONCLUSIONS: Across a broad spectrum of subjects with cardiometabolic disease, a 32-single-nucleotide polymorphism GRS was a strong, independent predictor of ischemic stroke. In patients with atrial fibrillation but lower CHA2DS2-VASc scores, the GRS identified patients with risk comparable to those with higher CHA2DS2-VASc scores.

Predicting Benefit From Evolocumab Therapy in Patients With Atherosclerotic Disease Using a Genetic Risk Score: Results From the FOURIER Trial.

BACKGROUND: The ability of a genetic risk score to predict risk in established cardiovascular disease and identify individuals who derive greater benefit from PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibition has not been established. METHODS: We studied 14 298 patients with atherosclerotic cardiovascular disease from the FOURIER trial (Further Cardiovascular Outcomes Researh With PCSK9 Inhibition in Subjects With Elevated Risk). A 27-single-nucleotide polymorphism genetic risk score defined low (quintile 1), intermediate (quintiles 2-4), and high (quintile 5) genetic risk. Patients were also categorized by major atherosclerotic risk factors including diabetes mellitus, hypertension, low-density lipoprotein cholesterol ≥100 mg/dl, and smoking; multiple (≥2) risk factors was considered high clinical risk. Outcomes consisted of major coronary events (coronary heart death, myocardial infarction, or coronary revascularization) and major vascular events (major coronary events and ischemic stroke). Median follow-up was 2.3 years. RESULTS: After we adjusted for clinical factors, the genetic risk score was associated with risk for both major vascular events (Ptrend=0.005) and major coronary events (Ptrend<0.0001). Individuals with intermediate and high genetic risk scores had 1.23- and 1.65-fold increased hazard for major coronary events, respectively. Elevated genetic risk was additive to major atherosclerotic risk factors and identified patients more likely to benefit from evolocumab. There was no benefit for major vascular events in patients without multiple clinical risk factors or high genetic risk (hazard ratio [HR], 1.02; absolute risk reduction [ARR], -0.2%, P=0.86). In contrast, there was a 13% relative risk reduction (HR, 0.87 [0.75-0.998], P=0.047) and a 1.4% ARR in patients with multiple clinical risk factors but without high genetic risk and a 31% relative risk reduction (HR, 0.69 [0.55-0.86], P=0.0012), and 4.0% ARR in patients with high genetic risk, irrespective of clinical risk (Ptrend for HR=0.017, ARR Ptrend=0.004). Patients with high genetic risk who received evolocumab had event rates similar to patients with a low burden of both genetic and clinical risk. CONCLUSION: Patients without multiple clinical risk factors or high genetic risk had a low event rate and did not appear to derive benefit from evolocumab over 2.3 years. Conversely, patients with multiple clinical risk factors but without high genetic risk had intermediate risk and intermediate risk reduction. Patients with high genetic risk, regardless of clinical risk, had a high event rate and derived the greatest relative and absolute benefit from evolocumab, which mitigated this risk.

Interactions between the colonic transcriptome, metabolome, and microbiome in mouse models of obesity-induced intestinal cancer.

Obesity is a significant risk factor for colorectal cancer (CRC); however, the relative contribution of high-fat (HF) consumption and excess adiposity remains unclear. It is becoming apparent that obesity perturbs both the intestinal microbiome and metabolome, and each has the potential to induce protumorigenic changes in the epithelial transcriptome. The physiological consequences and the degree to which these different biologic systems interact remain poorly defined. To understand the mechanisms by which obesity drives colonic tumorigenesis, we profiled the colonic epithelial transcriptome of HF-fed and genetically obese (DbDb) mice with a genetic predisposition to intestinal tumorigenesis (Apc(1638N)); 266 and 584 genes were differentially expressed in the colonic mucosa of HF and DbDb mice, respectively. These genes mapped to pathways involved in immune function, and cellular proliferation and cancer. Furthermore, Akt was central within the networks of interacting genes identified in both gene sets. Regression analyses of coexpressed genes with the abundance of bacterial taxa identified three taxa, previously correlated with tumor burden, to be significantly correlated with a gene module enriched for Akt-related genes. Similarly, regression of coexpressed genes with metabolites found that adenosine, which was negatively associated with inflammatory markers and tumor burden, was also correlated with a gene module enriched with Akt regulators. Our findings provide evidence that HF consumption and excess adiposity result in changes in the colonic transcriptome that, although distinct, both appear to converge on Akt signaling. Such changes could be mediated by alterations in the colonic microbiome and metabolome.

Novel Polygenic Risk Score and Established Clinical Risk Factors for Risk Estimation of Aortic Stenosis.

Importance: Polygenic risk scores (PRSs) have proven to be as strong as or stronger than established clinical risk factors for many cardiovascular phenotypes. Whether this is true for aortic stenosis remains unknown. Objective: To develop a novel aortic stenosis PRS and compare its aortic stenosis risk estimation to established clinical risk factors. Design, Setting, and Participants: This was a longitudinal cohort study using data from the Million Veteran Program (MVP; 2011-2020), UK Biobank (2006-2010), and 6 Thrombolysis in Myocardial Infarction (TIMI) trials, including DECLARE-TIMI 58 (2013-2018), FOURIER (TIMI 59; 2013-2017), PEGASUS-TIMI 54 (2010-2014), SAVOR-TIMI 53 (2010-2013), SOLID-TIMI 52 (2009-2014), and ENGAGE AF-TIMI 48 (2008-2013), which were a mix of population-based and randomized clinical trials. Individuals from UK Biobank and the MVP meeting a previously validated case/control definition for aortic stenosis were included. All individuals from TIMI trials were included unless they had a documented preexisting aortic valve replacement. Analysis took place from January 2022 to December 2023. Exposures: PRS for aortic stenosis (developed using data from MVP and validated in UK Biobank) and other previously validated cardiovascular PRSs, defined either as a continuous variable or as low (bottom 20%), intermediate, and high (top 20%), and clinical risk factors. Main Outcomes: Aortic stenosis (defined using International Classification of Diseases or Current Procedural Terminology codes in UK Biobank and MVP or safety event data in the TIMI trials). Results: The median (IQR) age in MVP was 67 (57-73) years, and 135 140 of 147 104 participants (92%) were male. The median (IQR) age in the TIMI trials was 66 (54-78) years, and 45 524 of 59 866 participants (71%) were male. The best aortic stenosis PRS incorporated 5 170 041 single-nucleotide variants and was associated with aortic stenosis in both the MVP testing sample (odds ratio, 1.41; 95% CI, 1.37-1.45 per 1 SD PRS; P = 4.6 × 10-116) and TIMI trials (hazard ratio, 1.44; 95% CI, 1.27-1.62 per 1 SD PRS; P = 3.2 × 10-9). Among genetic and clinical risk factors, the aortic stenosis PRS performed comparably to most risk factors besides age, and within a given age range, the combination of clinical and genetic risk factors was additive, providing a 3- to 4-fold increased gradient of risk of aortic stenosis. However, the addition of the aortic stenosis PRS to a model including clinical risk factors only improved risk discrimination of aortic stenosis by 0.01 to 0.02 (C index in MVP: 0.78 with clinical risk factors, 0.79 with risk factors and aortic stenosis PRS; C index in TIMI: 0.71 with clinical risk factors, 0.73 with risk factors and aortic stenosis PRS). Conclusions: This study developed and validated 1 of the first aortic stenosis PRSs. While aortic stenosis genetic risk was independent from clinical risk factors and performed comparably to all other risk factors besides age, genetic risk resulted in only a small improvement in overall aortic stenosis risk discrimination beyond age and clinical risk factors. This work sets the stage for further development of an aortic stenosis PRS.

Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention.

Importance: The clinical utility of polygenic risk scores (PRS) for coronary artery disease (CAD) has not yet been established. Objective: To investigate the ability of a CAD PRS to potentially guide statin initiation in primary prevention after accounting for age and clinical risk. Design, Setting, and Participants: This was a longitudinal cohort study with enrollment starting on January 1, 2006, and ending on December 31, 2010, with data updated to mid-2021, using data from the UK Biobank, a long-term population study of UK citizens. A replication analysis was performed in Biobank Japan. The analysis included all patients without a history of CAD and who were not taking lipid-lowering therapy. Data were analyzed from January 1 to June 30, 2022. Exposures: Polygenic risk for CAD was defined as low (bottom 20%), intermediate, and high (top 20%) using a CAD PRS including 241 genome-wide significant single-nucleotide variations (SNVs). The pooled cohort equations were used to estimate 10-year atherosclerotic cardiovascular disease (ASCVD) risk and classify individuals as low (<5%), borderline (5-<7.5%), intermediate (7.5-<20%), or high risk (≥20%). Main Outcomes and Measures: Myocardial infarction (MI) and ASCVD events (defined as incident clinical CAD [including MI], stroke, or CV death). Results: A total of 330 201 patients (median [IQR] age, 57 [40-74] years; 189 107 female individuals [57%]) were included from the UK Biobank. Over the 10-year follow-up, 4454 individuals had an MI. The CAD PRS was significantly associated with the risk of MI in all age groups but had significantly stronger risk prediction at younger ages (age <50 years: hazard ratio [HR] per 1 SD of PRS, 1.72; 95% CI, 1.56-1.89; age 50-60 years: HR, 1.46; 95% CI, 1.38-1.53; age >60 years: HR, 1.42; 95% CI, 1.37-1.48; P for interaction <.001). In patients younger than 50 years, those with high PRS had a 3- to 4-fold increased associated risk of MI compared with those in the low PRS category. A significant interaction between CAD PRS and age was replicated in Biobank Japan. When CAD PRS testing was added to the clinical ASCVD risk score in individuals younger than 50 years, 591 of 4373 patients (20%) with borderline risk were risk stratified into intermediate risk, warranting initiation of statin therapy and 3198 of 7477 patients (20%) with both borderline or intermediate risk were stratified as low risk, thus not warranting therapy. Conclusions and Relevance: Results of this cohort study suggest that the predictive ability of a CAD PRS was greater in younger individuals and can be used to better identify patients with borderline and intermediate clinical risk who should initiate statin therapy.

Privacy-aware multi-institutional time-to-event studies.

Clinical time-to-event studies are dependent on large sample sizes, often not available at a single institution. However, this is countered by the fact that, particularly in the medical field, individual institutions are often legally unable to share their data, as medical data is subject to strong privacy protection due to its particular sensitivity. But the collection, and especially aggregation into centralized datasets, is also fraught with substantial legal risks and often outright unlawful. Existing solutions using federated learning have already demonstrated considerable potential as an alternative for central data collection. Unfortunately, current approaches are incomplete or not easily applicable in clinical studies owing to the complexity of federated infrastructures. This work presents privacy-aware and federated implementations of the most used time-to-event algorithms (survival curve, cumulative hazard rate, log-rank test, and Cox proportional hazards model) in clinical trials, based on a hybrid approach of federated learning, additive secret sharing, and differential privacy. On several benchmark datasets, we show that all algorithms produce highly similar, or in some cases, even identical results compared to traditional centralized time-to-event algorithms. Furthermore, we were able to reproduce the results of a previous clinical time-to-event study in various federated scenarios. All algorithms are accessible through the intuitive web-app Partea (https://partea.zbh.uni-hamburg.de), offering a graphical user interface for clinicians and non-computational researchers without programming knowledge. Partea removes the high infrastructural hurdles derived from existing federated learning approaches and removes the complexity of execution. Therefore, it is an easy-to-use alternative to central data collection, reducing bureaucratic efforts but also the legal risks associated with the processing of personal data to a minimum.

Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Genetic Risk Score to Identify Risk of Venous Thromboembolism in Patients With Cardiometabolic Disease.

BACKGROUND: Venous thromboembolism (VTE) is a major cause of cardiovascular morbidity and mortality and has a known genetic contribution. We tested the performance of a genetic risk score for its ability to predict VTE in 3 cohorts of patients with cardiometabolic disease. METHODS: We included patients from the FOURIER (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Patients With Elevated Risk), PEGASUS-TIMI 54 (Prevention of Cardiovascular Events in Patients With Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin), and SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus) trials (history of a major atherosclerotic cardiovascular event, myocardial infarction, and diabetes, respectively) who consented for genetic testing and were not on baseline anticoagulation. We calculated a VTE genetic risk score based on 297 single nucleotide polymorphisms with established genome-wide significance. Patients were divided into tertiles of genetic risk. Cox proportional hazards models were used to calculate hazard ratios for VTE across genetic risk groups. The polygenic risk score was compared with available clinical risk factors (age, obesity, smoking, history of heart failure, and diabetes) and common monogenic mutations. RESULTS: A total of 29 663 patients were included in the analysis with a median follow-up of 2.4 years, of whom 174 had a VTE event. There was a significantly increased gradient of risk across VTE genetic risk tertiles (P-trend <0.0001). After adjustment for clinical risk factors, patients in the intermediate and high genetic risk groups had a 1.88-fold (95% CI, 1.23-2.89; P=0.004) and 2.70-fold (95% CI, 1.81-4.06; P<0.0001) higher risk of VTE compared with patients with low genetic risk. In a continuous model adjusted for clinical risk factors, each standard deviation increase in the genetic risk score was associated with a 47% (95% CI, 29-68) increased risk of VTE (P<0.0001). CONCLUSIONS: In a broad spectrum of patients with cardiometabolic disease, a polygenic risk score is a strong, independent predictor of VTE after accounting for available clinical risk factors, identifying 1/3 of patients who have a risk of VTE comparable to that seen with established monogenic thrombophilia.

Identification of Novel Loci Associated With Hip Shape: A Meta-Analysis of Genomewide Association Studies.

We aimed to report the first genomewide association study (GWAS) meta-analysis of dual-energy X-ray absorptiometry (DXA)-derived hip shape, which is thought to be related to the risk of both hip osteoarthritis and hip fracture. Ten hip shape modes (HSMs) were derived by statistical shape modeling using SHAPE software, from hip DXA scans in the Avon Longitudinal Study of Parents and Children (ALSPAC; adult females), TwinsUK (mixed sex), Framingham Osteoporosis Study (FOS; mixed), Osteoporotic Fractures in Men study (MrOS), and Study of Osteoporotic Fractures (SOF; females) (total N = 15,934). Associations were adjusted for age, sex, and ancestry. Five genomewide significant (p < 5 × 10-9 , adjusted for 10 independent outcomes) single-nucleotide polymorphisms (SNPs) were associated with HSM1, and three SNPs with HSM2. One SNP, in high linkage disequilibrium with rs2158915 associated with HSM1, was associated with HSM5 at genomewide significance. In a look-up of previous GWASs, three of the identified SNPs were associated with hip osteoarthritis, one with hip fracture, and five with height. Seven SNPs were within 200 kb of genes involved in endochondral bone formation, namely SOX9, PTHrP, RUNX1, NKX3-2, FGFR4, DICER1, and HHIP. The SNP adjacent to DICER1 also showed osteoblast cis-regulatory activity of GSC, in which mutations have previously been reported to cause hip dysplasia. For three of the lead SNPs, SNPs in high LD (r2 > 0.5) were identified, which intersected with open chromatin sites as detected by ATAC-seq performed on embryonic mouse proximal femora. In conclusion, we identified eight SNPs independently associated with hip shape, most of which were associated with height and/or mapped close to endochondral bone formation genes, consistent with a contribution of processes involved in limb growth to hip shape and pathological sequelae. These findings raise the possibility that genetic studies of hip shape might help in understanding potential pathways involved in hip osteoarthritis and hip fracture. © 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals, Inc.

Incremental Elevations in TNFα and IL6 in the Human Colon and Procancerous Changes in the Mucosal Transcriptome Accompany Adiposity.

BACKGROUND: Obesity, a risk factor for colorectal cancer, raises systemic levels of proinflammatory mediators. Whether increased levels also reside in the colons of obese individuals and are accompanied by procancerous alterations in the mucosal transcriptome is unknown. METHODS: Concentrations of TNFα, IL1ß, and IL6 in blood and colonic mucosa of 16 lean and 26 obese individuals were examined. Differences in the mucosal transcriptome between the two groups were defined. RESULTS: Plasma IL6 and TNFα were 1.4- to 3-fold elevated in obese subjects [body mass index (BMI) ≥ 34 kg/m2] compared with the lean controls (P < 0.01). Among individuals with BMI ≥ 34 kg/m2 colonic concentrations of IL6 and TNFα were 2- to 3-fold greater than in lean subjects (P < 0.03). In a general linear model, adjusted for NSAID use, colonic IL6 (partial r = 0.41; P < 0.01) and TNFα (partial r = 0.41; P = 0.01) increased incrementally over the entire range of BMIs (18.1-45.7). Regular use of nonsteroidal anti-inflammatory drugs (NSAIDs) was associated with a reduction in colonic IL6 (ß = -0.65, P < 0.02). RNA sequencing (NSAID users excluded) identified 182 genes expressed differentially between lean and obese subjects. The two gene networks most strongly linked to changes in expression included several differentially expressed genes known to regulate the procarcinogenic signaling pathways, NFκB and ERK 1/2, in a pattern consistent with upregulation of each in the obese subjects. CONCLUSIONS: Incremental increases in two major proinflammatory colonic cytokines are associated with increasing BMI, and in the obese state are accompanied by procancerous changes in the transcriptome. IMPACT: These observations delineate means by which an inflammatory milieu may contribute to obesity-promoted colon cancer.