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

Clinical use of polygenic risk scores for detection of peripheral artery disease and cardiovascular events

We have previously shown that polygenic risk scores (PRS) can improve risk stratification of peripheral artery disease (PAD) in a large, retrospective cohort. Here, we evaluate the potential of PRS in improving the detection of PAD and prediction of major adverse cardiovascular and cerebrovascular events (MACCE) and adverse events (AE) in an institutional patient cohort. We created a cohort of 278 patients (52 cases and 226 controls) and fit a PAD-specific PRS based on the weighted sum of risk alleles. We built traditional clinical risk models and machine learning (ML) models using clinical and genetic variables to detect PAD, MACCE, and AE. The models' performances were measured using the area under the curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), and Brier score. We also evaluated the clinical utility of our PAD model using decision curve analysis (DCA). We found a modest, but not statistically significant improvement in the PAD detection model's performance with the inclusion of PRS from 0.902 (95% CI: 0.846-0.957) (clinical variables only) to 0.909 (95% CI: 0.856-0.961) (clinical variables with PRS). The PRS inclusion significantly improved risk re-classification of PAD with an NRI of 0.07 (95% CI: 0.002-0.137), p = 0.04. For our ML model predicting MACCE, the addition of PRS did not significantly improve the AUC, however, NRI analysis demonstrated significant improvement in risk re-classification (p = 2e-05). Decision curve analysis showed higher net benefit of our combined PRS-clinical model across all thresholds of PAD detection. Including PRS to a clinical PAD-risk model was associated with improvement in risk stratification and clinical utility, although we did not see a significant change in AUC. This result underscores the potential clinical utility of incorporating PRS data into clinical risk models for prevalent PAD and the need for use of evaluation metrics that can discern the clinical impact of using new biomarkers in smaller populations.

European and US Guideline-Based Statin Eligibility, Genetically Predicted Coronary Artery Disease, and the Risk of Major Coronary Events

BACKGROUND

A study was designed to investigate whether the coronary artery disease polygenic risk score (CAD-PRS) may guide lipid-lowering treatment initiation as well as deferral in primary prevention beyond established clinical risk scores.

METHODS AND RESULTS

Participants were 311 799 individuals from the UK Biobank free of atherosclerotic cardiovascular disease, diabetes, chronic kidney disease, and lipid-lowering treatment at baseline. Participants were categorized as statin indicated, statin indication unclear, or statin not indicated as defined by the European and US guidelines on statin use. For a median of 11.9 (11.2-12.6) years, 8196 major coronary events developed. CAD-PRS added to European-Systematic Coronary Risk Evaluation 2 (European-SCORE2) and US-Pooled Cohort Equation (US-PCE) identified 18% and 12% of statin-indication-unclear individuals whose risk of major coronary events were the same as or higher than the average risk of statin-indicated individuals and 16% and 12% of statin-indicated individuals whose major coronary event risks were the same as or lower than the average risk of statin-indication-unclear individuals. For major coronary and atherosclerotic cardiovascular disease events, CAD-PRS improved C-statistics greater among statin-indicated or statin-indication-unclear than statin-not-indicated individuals. For atherosclerotic cardiovascular disease events, CAD-PRS added to the European evaluation and US equation resulted in a net reclassification improvement of 13.6% (95% CI, 11.8-15.5) and 14.7% (95% CI, 13.1-16.3) among statin-indicated, 10.8% (95% CI, 9.6-12.0) and 15.3% (95% CI, 13.2-17.5) among statin-indication-unclear, and 0.9% (95% CI, 0.6-1.3) and 3.6% (95% CI, 3.0-4.2) among statin-not-indicated individuals.

CONCLUSIONS

CAD-PRS may guide statin initiation as well as deferral among statin-indication-unclear or statin-indicated individuals as defined by the European and US guidelines. CAD-PRS had little clinical utility among statin-not-indicated individuals.

Stroke genetics and how it Informs novel drug discovery

INTRODUCTION

Stroke is one of the main causes of death and disability worldwide. Nevertheless, despite the global burden of this disease, our understanding is limited and there is still a lack of highly efficient etiopathology-based treatment. It is partly due to the complexity and heterogenicity of the disease. It is estimated that around one-third of ischemic stroke is heritable, emphasizing the importance of genetic factors identification and targeting for therapeutic purposes.

AREAS COVERED

In this review, the authors provide an overview of the current knowledge of stroke genetics and its value in diagnostics, personalized treatment, and prognostication.

EXPERT OPINION

As the scale of genetic testing increases and the cost decreases, integration of genetic data into clinical practice is inevitable, enabling assessing individual risk, providing personalized prognostic models and identifying new therapeutic targets and biomarkers. Although expanding stroke genetics data provides different diagnostics and treatment perspectives, there are some limitations and challenges to face. One of them is the threat of health disparities as non-European populations are underrepresented in genetic datasets. Finally, a deeper understanding of underlying mechanisms of potential targets is still lacking, delaying the application of novel therapies into routine clinical practice.

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.

Assessing the individual risk of stroke in caregivers of patients with stroke

BACKGROUND

 Genetic factors influence the risk of developing stroke. Still, it is unclear whether this risk is intrinsically high in certain people or if nongenetic factors explain it entirely.

OBJECTIVE

 To compare the risk of stroke in kin and nonkin caregivers.

METHODS

 In a cross-sectional study using the Stroke Riskometer app (AUT Ventures Limited, Auckland, AUK, New Zealand), we determined the 5- and 10-year stroke risk (SR) among caregivers of stroke inpatients. The degree of kinship was rated with a score ranging from 0 to 50 points.

RESULTS

 We studied 278 caregivers (69.4% of them female) with a mean age of 47.5 ± 14.2 years. Kin caregivers represented 70.1% of the sample, and 49.6% of them were offspring. The median SR at 5 years was of 2.1 (range: 0.35-17.3) versus 1.73 (range: 0.04-29.9), and of 4.0 (range: 0.45-38.6) versus 2.94 (range: 0.05-59.35) at 10 years for the nonkin and kin caregivers respectively. In linear logistic regression controlled for the age of the caregivers, adding the kinship score did not increase the overall variability of the model for the risk at 5 years (R2 = 0.271; p = 0.858) nor the risk at 10 years (R2 = 0.376; p = 0.78).

CONCLUSION

 Caregivers of stroke patients carry a high SR regardless of their degree of kinship.

Associations of polygenic risk scores with risks of stroke and its subtypes in Chinese

BACKGROUND AND PURPOSE

Previous studies, mostly focusing on the European population, have reported polygenic risk scores (PRSs) might achieve risk stratification of stroke. We aimed to examine the association strengths of PRSs with risks of stroke and its subtypes in the Chinese population.

METHODS

Participants with genome-wide genotypic data in China Kadoorie Biobank were split into a potential training set (n=22 191) and a population-based testing set (n=72 150). Four previously developed PRSs were included, and new PRSs for stroke and its subtypes were developed. The PRSs showing the strongest association with risks of stroke or its subtypes in the training set were further evaluated in the testing set. Cox proportional hazards regression models were used to estimate the association strengths of different PRSs with risks of stroke and its subtypes (ischaemic stroke (IS), intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH)).

RESULTS

In the testing set, during 872 919 person-years of follow-up, 8514 incident stroke events were documented. The PRSs of any stroke (AS) and IS were both positively associated with risks of AS, IS and ICH (p<0.05). The HR for per SD increment (HRSD) of PRSAS was 1.10 (95% CI 1.07 to 1.12), 1.10 (95% CI 1.07 to 1.12) and 1.13 (95% CI 1.07 to 1.20) for AS, IS and ICH, respectively. The corresponding HRSD of PRSIS was 1.08 (95% CI 1.06 to 1.11), 1.08 (95% CI 1.06 to 1.11) and 1.09 (95% CI 1.03 to 1.15). PRSICH was positively associated with the risk of ICH (HRSD=1.07, 95% CI 1.01 to 1.14). PRSSAH was not associated with risks of stroke and its subtypes. The addition of current PRSs offered little to no improvement in stroke risk prediction and risk stratification.

CONCLUSIONS

In this Chinese population, the association strengths of current PRSs with risks of stroke and its subtypes were moderate, suggesting a limited value for improving risk prediction over traditional risk factors in the context of current genome-wide association study under-representing the East Asian population.

Association of genetic risk and outcomes in patients with atrial fibrillation: interactions with early rhythm control in the EAST-AFNET4 trial

AIMS

The randomized Early Treatment of Atrial Fibrillation for Stroke Prevention Trial found that early rhythm control reduces cardiovascular events in patients with recently diagnosed atrial fibrillation (AF) compared with usual care. How genetic predisposition to AF and stroke interacts with early rhythm-control therapy is not known.

METHODS AND RESULTS

Array genotyping and imputation for common genetic variants were performed. Polygenic risk scores (PRS) were calculated for AF (PRS-AF) and ischaemic stroke risk (PRS-stroke). The effects of PRS-AF and PRS-stroke on the primary outcome (composite of cardiovascular death, stroke, and hospitalization for acute coronary syndrome or worsening heart failure), its components, and recurrent AF were determined.A total of 1567 of the 2789 trial patients were analysed [793 randomized to early rhythm control; 774 to usual care, median age 71 years (65-75), 704 (44%) women]. Baseline characteristics were similar between randomized groups. Early rhythm control reduced the primary outcome compared with usual care [HR 0.67, 95% CI: (0.53, 0.84), P < 0.001]. The randomized intervention, early rhythm control, did not interact with PRS-AF (interaction P = 0.806) or PRS-stroke (interaction P = 0.765). PRS-AF was associated with recurrent AF [HR 1.08 (01.0, 1.16), P = 0.047]. PRS-stroke showed an association with the primary outcome [HR 1.13 (1.0, 1.27), P = 0.048], driven by more heart failure events [HR 1.23 (1.05-1.43), P = 0.010] without differences in stroke [HR 1.0 (0.75, 1.34), P = 0.973] in this well-anticoagulated cohort. In a replication analysis, PRS-stroke was associated with incident AF [HR 1.16 (1.14, 1.67), P < 0.001] and with incident heart failure in the UK Biobank [HR 1.08 (1.06, 1.10), P < 0.001]. The association with heart failure was weakened when excluding AF patients [HR 1.03 (1.01, 1.05), P = 0.001].

CONCLUSIONS

Early rhythm control is effective across the spectrum of genetic AF and stroke risk. The association between genetic stroke risk and heart failure calls for research to understand the interactions between polygenic risk and treatment.

REGISTRATION

ISRCTN04708680, NCT01288352, EudraCT2010-021258-20, www.easttrial.org.

Association of CASZ1 genetic variants with stroke risk in the Chinese population

BACKGROUND

Stroke is a heterogeneous disease with multiple etiologies, placing a heavy burden on the world. Our purpose was to clarify the association between CASZ1 genetic variants and stroke risk in the Chinese population.

METHODS

The Agena MassARRAY platform effectively genotyped three single nucleotide polymorphisms of CASZ1 in recruited 591 stroke patients and 553 healthy controls. Logistic regression genetic models were employed to evaluate the relationship between CASZ1 polymorphisms and stroke risk through odds ratios (ORs) and 95% confidence intervals (CIs). Then, the interaction between CASZ1 variants was detected by multifactor dimensionality reduction (MDR). Moreover, functional enrichment analyses of the CASZ1 gene were performed by Metascape.

RESULTS

In this study, CASZ1 rs4845941 and rs778228 were significantly associated with an increased risk of stroke. In particular, the gender-stratified analysis also showed that rs778228 of CASZ1 had an association with higher stroke risk in females. The relationship between stroke susceptibility and the interaction models of rs4845941, rs778228, and rs17035539 forecasted by MDR were analyzed to improve the ability to predict stroke risk. Furthermore, we found CASZ1 and related genes might facilitate the occurrence of stroke.

CONCLUSIONS

This study demonstrated that CASZ1 genetic variants (rs4845941 and rs778228) contribute to the occurrence of stroke in the Chinese population, and therefore has important implications for treating and preventing stroke.

Association between genetic predisposition and disease burden of stroke in China: a genetic epidemiological study

Background

Stroke ranks second worldwide and first in China as a leading cause of death and disability. It has a polygenic architecture and is influenced by environmental and lifestyle factors. However, it remains unknown as to whether and how much the genetic predisposition of stroke is associated with disease burden.

Methods

Allele frequency from the whole genome sequencing data in the Chinese Millionome Database of 141,418 individuals and trait-specific polygenic risk score models were applied to estimate the provincial genetic predisposition to stroke, stroke-related risk factors and stroke-related drug response. Disease burden including mortality, disability-adjusted life years (DALYs), years of life lost(YLLs), years lived with disability (YLDs) and prevalence in China was collected from the Global Burden Disease study. The association between stroke genetic predisposition and the epidemiological burden was assessed and then quantified in both regression-based models and machine learning-based models at a provincial resolution.

Findings

Among the 30 administrative divisions in China, the genetic predisposition of stroke was characterized by a north-higher-than-south gradient (p < 0.0001). Genetic predisposition to stroke, blood pressure, body mass index, and alcohol use were strongly intercorrelated (rho >0.6; p < 0.05 after Bonferroni correction for each comparison). Genetic risk imposed an independent effect of approximately 1-6% on mortality, DALYs and YLLs.

Interpretation

The distribution pattern of stroke genetic predisposition is different at a macroscopic level, and it subtly but significantly impacts the epidemiological burden. Further research is warranted to identify the detailed aetiology and potential translation into public health measures.

Funding

Beijing Municipal Science and Technology Commission (Z191100006619106), CAMS Innovation Fund for Medical Sciences (CAMS-I2M, 2023-I2M-1-001), the National High Level Hospital Clinical Research Funding (2022-GSP-GG-17), National Natural Science Foundation of China (32000398, 32171441 to X.J.), Natural Science Foundation of Guangdong Province, China (2017A030306026 to X.J.), and National Key R&D Program of China (2022YFC2502402).

Induction Mechanism of Ferroptosis, Necroptosis, and Pyroptosis: A Novel Therapeutic Target in Nervous System Diseases

In recent years, three emerging cell deaths, ferroptosis, necroptosis and pyroptosis, have gradually attracted everyone's attention, and they also play an important role in the occurrence and development of various diseases. Ferroptosis is an idiographic iron-dependent form regulated cell death with the hallmark of accumulation of the intracellular reactive oxygen species (ROS). Necroptosis is a form of regulated necrotic cell death mediated by the receptor-interacting protein kinase 1(RIPK1) and receptor-interacting protein kinase 3RIPK3. Pyroptosis, also known as cell inflammatory necrosis, is a programmed cell necrosis mediated by Gasdermin D (GSDMD). It is manifested by the continuous swelling of the cells until the cell membrane ruptures, resulting in the release of the cell contents and the activation of a strong inflammatory response. Neurological disorders remain a clinical challenge and patients do not respond well to conventional treatments. Nerve cell death can aggravate the occurrence and development of neurological diseases. This article reviews the specific mechanisms of these three types of cell death and their relationship with neurological diseases and the evidence for the role of the three types of cell death in neurological diseases; understanding these pathways and their mechanisms is helpful for the treatment of neurological diseases.

A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage

BACKGROUND

Intracerebral hemorrhage (ICH) has an estimated heritability of 29%. We developed a genomic risk score for ICH and determined its predictive power in comparison to standard clinical risk factors.

METHODS

We combined genome-wide association data from individuals of European ancestry for ICH and related traits in a meta-genomic risk score ([metaGRS]; 2.6 million variants). We tested associations with ICH and its predictive performance in addition to clinical risk factors in a held-out validation dataset (842 cases and 796 controls). We tested associations with risk of incident ICH in the population-based UK Biobank cohort (486 784 individuals, 1526 events, median follow-up 11.3 years).

RESULTS

One SD increment in the metaGRS was significantly associated with 31% higher odds for ICH (95% CI, 1.16-1.48) in age-, sex- and clinical risk factor-adjusted models. The metaGRS identified individuals with almost 5-fold higher odds for ICH in the top score percentile (odds ratio, 4.83 [95% CI, 1.56-21.2]). Predictive models for ICH incorporating the metaGRS in addition to clinical predictors showed superior performance compared to the clinical risk factors alone (c-index, 0.695 versus 0.686). The metaGRS showed similar associations for lobar and nonlobar ICH, independent of the known APOE risk locus for lobar ICH. In the UK Biobank, the metaGRS was associated with higher risk of incident ICH (hazard ratio, 1.15 [95% CI, 1.09-1.21]). The associations were significant within both a relatively high-risk population of antithrombotic medications users, as well as among a relatively low-risk population with a good control of vascular risk factors and no use of anticoagulants.

CONCLUSIONS

We developed and validated a genomic risk score that predicts lifetime risk of ICH beyond established clinical risk factors among individuals of European ancestry. Whether implementation of the score in risk prognostication models for high-risk populations, such as patients under antithrombotic treatment, could improve clinical decision making should be explored in future studies.

Integrating polygenic and clinical risks to improve stroke risk stratification in prospective Chinese cohorts

The utility of the polygenic risk score (PRS) to identify individuals at higher risk of stroke beyond clinical risk remains unclear, and we clarified this using Chinese population-based prospective cohorts. Cox proportional hazards models were used to estimate the 10-year risk, and Fine and Gray's models were used for hazard ratios (HRs), their 95% confidence intervals (CIs), and the lifetime risk according to PRS and clinical risk categories. A total of 41,006 individuals aged 30-75 years with a mean follow-up of 9.0 years were included. Comparing the top versus bottom 5% of the PRS, the HR was 3.01 (95%CI 2.03-4.45) in the total population, and similar findings were observed within clinical risk strata. Marked gradients in the 10-year and lifetime risk across PRS categories were also found within clinical risk categories. Notably, among individuals with intermediate clinical risk, the 10-year risk for those in the top 5% of the PRS (7.3%, 95%CI 7.1%-7.5%) reached the threshold of high clinical risk (⩾7.0%) for initiating preventive treatment, and this effect of the PRS on refining risk stratification was evident for ischemic stroke. Even among those in the top 10% and 20% of the PRS, the 10-year risk would also exceed this level when aged ⩾50 and ⩾60 years, respectively. Overall, the combination of the PRS with the clinical risk score improved the risk stratification within clinical risk strata and distinguished actual high-risk individuals with intermediate clinical risk.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

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.

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.

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.

Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine

Ischemic stroke (IS), the leading cause of death and disability worldwide, is caused by many modifiable and non-modifiable risk factors. This complex disease is also known for its multiple etiologies with moderate heritability. Polygenic risk scores (PRSs), which have been used to establish a common genetic basis for IS, may contribute to IS risk stratification for disease/outcome prediction and personalized management. Statistical modeling and machine learning algorithms have contributed significantly to this field. For instance, multiple algorithms have been successfully applied to PRS construction and integration of genetic and non-genetic features for outcome prediction to aid in risk stratification for personalized management and prevention measures. PRS derived from variants with effect size estimated based on the summary statistics of a specific subtype shows a stronger association with the matched subtype. The disruption of the extracellular matrix and amyloidosis account for the pathogenesis of cerebral small vessel disease (CSVD). Pathway-specific PRS analyses confirm known and identify novel etiologies related to IS. Some of these specific PRSs (e.g., derived from endothelial cell apoptosis pathway) individually contribute to post-IS mortality and, together with clinical risk factors, better predict post-IS mortality. In this review, we summarize the genetic basis of IS, emphasizing the application of methodologies and algorithms used to construct PRSs and integrate genetics into risk models.

Stroke and Etiopathogenesis: What Is Known?

Background: A substantial portion of stroke risk remains unexplained, and a contribution from genetic factors is supported by recent findings. In most cases, genetic risk factors contribute to stroke risk as part of a multifactorial predisposition. A major challenge in identifying the genetic determinants of stroke is fully understanding the complexity of the phenotype. Aims: Our narrative review is needed to improve our understanding of the biological pathways underlying the disease and, through this understanding, to accelerate the identification of new drug targets. Methods: We report, the research in the literature until February 2022 in this narrative review. The keywords are stroke, causes, etiopathogenesis, genetic, epigenetic, ischemic stroke. Results: While better risk prediction also remains a long-term goal, its implementation is still complex given the small effect-size of genetic risk variants. Some authors encourage the use of stroke genetic panels for stroke risk assessment and further stroke research. In addition, new biomarkers for the genetic causes of stroke and new targets for gene therapy are on the horizon. Conclusion: We summarize the latest evidence and perspectives of ischemic stroke genetics that may be of interest to the physician and useful for day-to-day clinical work in terms of both prevention and treatment of ischemic stroke.

Relationship of cumulative exposure to the triglyceride-glucose index with ischemic stroke: a 9-year prospective study in the Kailuan cohort

BACKGROUND

A single measurement of the triglyceride-glucose (TyG) index, a simple and reliable surrogate marker of insulin resistance, is associated with ischemic stroke. However, evidence for an effect of a long-term elevation in TyG index on ischemic stroke is limited. Therefore, we evaluated the relationship between cumulative TyG index exposure and the risk of ischemic stroke.

METHODS

A total of 54,098 participants in the Kailuan study who had not experienced ischemic stroke underwent three measurements of fasting blood glucose and triglycerides during 2006-2007, 2008-2009, and 2010-2011. Cumulative exposure to TyG index was calculated as the weighted sum of the mean TyG index value for each time interval (value × time). Participants were placed into four groups according to the quartile of the weighted mean: Q1 group, < 32.01; Q2 group, 32.01-34.45; Q3 group, 34.45-37.47; and Q4 group, ≥ 37.47. Cox proportional hazard models were used to assess the relationships of the cumulative TyG index with incident ischemic stroke by calculating hazard ratios (HRs) and 95% confidence intervals (95% CIs).

RESULTS

There were 2083 incident ischemic stroke events over the 9 years of follow-up. The risk of ischemic stroke increased with the quartile of cumulative TyG index. After adjustment for multiple potential confounders, participants in groups Q4, Q3, and Q2 had significantly higher risks of ischemic stroke, with HRs (95% CIs) of 1.30 (1.12-1.52), 1.26 (1.09-1.45), and 1.09 (0.94-1.27), respectively (P_trend < 0.05), compared with the Q1 group. The longer duration of high TyG index exposure was significantly associated with increased ischemic stroke.

CONCLUSIONS

High cumulative TyG index is associated with a higher risk of ischemic stroke. This finding implies that monitoring and the maintenance of an appropriate TyG index may be useful for the prevention of ischemic stroke.

“Big Data” Approaches for Prevention of the Metabolic Syndrome

Metabolic syndrome (MetS) is characterized by the concurrence of multiple metabolic disorders resulting in the increased risk of a variety of diseases related to disrupted metabolism homeostasis. The prevalence of MetS has reached a pandemic level worldwide. In recent years, extensive amount of data have been generated throughout the research targeted or related to the condition with techniques including high-throughput screening and artificial intelligence, and with these “big data”, the prevention of MetS could be pushed to an earlier stage with different data source, data mining tools and analytic tools at different levels. In this review we briefly summarize the recent advances in the study of “big data” applications in the three-level disease prevention for MetS, and illustrate how these technologies could contribute tobetter preventive strategies.

Stroke Genetics: Discovery, Insight Into Mechanisms, and Clinical Perspectives

Stroke is the second leading cause of death worldwide and a complex, heterogeneous condition. In this review, we provide an overview of the current knowledge on monogenic and multifactorial forms of stroke, highlighting recent insight into the continuum between these. We describe how, in recent years, large-scale genome-wide association studies have enabled major progress in deciphering the genetic basis for stroke and its subtypes, although more research is needed to interpret these findings. We cover the potential of stroke genetics to reveal novel pathophysiological processes underlying stroke, to accelerate the discovery of new therapeutic approaches, and to identify individuals in the population who are at high risk of stroke and could be targeted for tailored preventative interventions.

A Family and a Genome-Wide Polygenic Risk Score Are Independently Associated With Stroke in a Population-Based Study

BACKGROUND

Positive family history and genetic risk scores have been shown to independently capture those individuals with high risk for stroke. The aim of our study was to evaluate the amount of shared information between family history and genetic risk and to investigate their combined effect on the association with prevalent and incident stroke cases.

METHODS

We obtained a family risk score (FamRS), weighted for disease onset and family size as well as genome-wide polygenic risk score (PGS) including over 3.2 million single-nucleotide polymorphisms in the population-based prospective KORA F3 (Cooperative Health Research in the Region of Augsburg) study (n=3071) from Southern Germany. FamRS and PGS were evaluated separately and combined. The measures were once treated as continuous variables but also divided in the highest 20%, 10%, 5%, and 1% percentiles. Odds ratios via logistic regression and hazard ratios via Cox regression were estimated. A stroke event was defined as a hospitalization for stroke that was self-reported in a standardized interview by certified and supervised personnel.

RESULTS

The FamRS outperformed other simplified family measures such as affected parents or number of affected family members. FamRS and PGS were not correlated, and no individuals were observed with both very high FamRS and very high PGS (top 1% percentile). In a combined model, both FamRS and PGS were independently from each other associated with risk of stroke, also independent of other traditional risk factors (p [FamRS]=0.02, p [PGS]=0.005). Individuals in the top 1% of either FamRS or PGS were found to have >5-fold risk for stroke (odds ratios, 5.82 [95% CI, 2.08-14]; P=0.0002). The results for incident stroke events showed the same trend but were not significant.

CONCLUSIONS

Our study shows that a family risk score and PGS capture different information concerning individual stroke risk. Combining the risk measures FamRS and PGS increases predictive power, as demonstrated in a population-based study.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Ischemic Stroke Genetics: What Is New and How to Apply It in Clinical Practice?

The etiology of ischemic stroke is multifactorial. Although receiving less emphasis, genetic causes make a significant contribution to ischemic stroke genesis, especially in early-onset stroke. Several stroke classification systems based on genetic information corresponding to various stroke phenotypes were proposed. Twin and family history studies, as well as candidate gene approach, are common methods to discover genetic causes of stroke, however, both have their own limitations. Genome-wide association studies and next generation sequencing are more efficient, promising and increasingly used for daily diagnostics. Some monogenic disorders, despite covering only about 7% of stroke etiology, may cause well-known clinical manifestations that include stroke. Polygenic disorders are more frequent, causing about 38% of all ischemic strokes, and their identification is a rapidly developing field of modern stroke genetics. Current advances in human genetics provide opportunity for personalized prevention of stroke and novel treatment possibilities. Genetic risk scores (GRS) and extended polygenic risk scores (PRS) estimate cumulative contribution of known genetic factors to a specific outcome of stroke. Combining those scores with clinical information and risk factor profiles might result in better primary stroke prevention. Some authors encourage the use of stroke gene panels for stroke risk evaluation and further stroke research. Moreover, new biomarkers for stroke genetic causes and novel targets for gene therapy are on the horizon. In this article, we summarize the latest evidence and perspectives of ischemic stroke genetics that could be of interest to the practitioner and useful for day-to-day clinical work.

Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases

Early prediction of risk of cardiovascular disease (CVD), including stroke, is a cornerstone of disease prevention. Clinical risk scores have been widely used for predicting CVD risk from known risk factors. Most CVDs have a substantial genetic component, which also has been confirmed for stroke in recent gene discovery efforts. However, the role of genetics in prediction of risk of CVD, including stroke, has been limited to testing for highly penetrant monogenic disorders. In contrast, the importance of polygenic variation, the aggregated effect of many common genetic variants across the genome with individually small effects, has become more apparent in the last 5 to 10 years, and powerful polygenic risk scores for CVD have been developed. Here we review the current state of the field of polygenic risk scores for CVD including stroke, and their potential to improve CVD risk prediction. We present findings and lessons from diseases such as coronary artery disease as these will likely be useful to inform future research in stroke polygenic risk prediction.

Stroke Genetics: Turning Discoveries into Clinical Applications

The field of medical and population genetics in stroke is moving at a rapid pace and has led to unanticipated opportunities for discovery and clinical applications. Genome-wide association studies have highlighted the role of specific pathways relevant to etiologically defined subtypes of stroke and to stroke as a whole. They have further offered starting points for the exploration of novel pathways and pharmacological strategies in experimental systems. Mendelian randomization studies continue to provide insights in the causal relationships between exposures and outcomes and have become a useful tool for predicting the efficacy and side effects of drugs. Additional applications that have emerged from recent discoveries include risk prediction based on polygenic risk scores and pharmacogenomics. Among the topics currently moving into focus is the genetics of stroke outcome. While still at its infancy, this field is expected to boost the development of neuroprotective agents. We provide a brief overview on recent progress in these areas.

Stroke risk factors and outcomes among hospitalized women with atrial fibrillation

Observational cohort analyses suggest that women with atrial fibrillation (AF) endure a greater burden of stroke. We conducted an analysis of an observational cohort study completed at our tertiary care medical center to assess sex-related differences in cardiovascular risk factors, prescription of antithrombotic therapy, and 90-day outcomes. We analyzed 5000 hospitalized patients with AF: 1888 women and 3112 men. Clinical characteristics of AF, risk of stroke and bleeding, prescription of antithrombotic therapy, and 90-day clinical outcomes, including stroke and all-cause mortality, were compared. We observed a 50% higher relative frequency of stroke in hospitalized women with AF compared with men. While the frequencies of prescription of antithrombotic therapy at discharge were similar, anticoagulation was omitted in 40% of women with AF. The 90-day frequencies of major adverse events and mortality were increased in hospitalized women with AF not prescribed antithrombotic therapy at discharge. Prescription of anticoagulation in women with AF at hospital discharge was associated with a 60% and 40% relative reduction in the odds of mortality and major adverse events at 90 days. In conclusion, women hospitalized with AF have a higher risk of stroke at 90 days compared with men. Anticoagulation at hospital discharge was omitted in 40% of women with AF, but when prescribed, was associated with a reduction in mortality and major adverse events at 90 days, respectively. We analyzed 5000 hospitalized patients with atrial fibrillation (AF) (1888 women and 3112 men) in an observational cohort study completed at our tertiary care medical center to assess sex-related differences in cardiovascular risk factors, prescription of antithrombotic therapy, and 90-day outcomes. We observed a 50% higher relative frequency of stroke in hospitalized women with AF compared with men. The 90-day frequencies of major adverse events and mortality were increased in hospitalized women with AF not prescribed antithrombotic therapy at discharge. Prescription of anticoagulation in women with AF at hospital discharge was associated with a 60% and 40% relative reduction in the odds of mortality and major adverse events at 90 days.

Genetics of atrial fibrillation-practical applications for clinical management: if not now, when and how?

The prevalence and economic burden of atrial fibrillation (AF) are predicted to more than double over the next few decades. In addition to anticoagulation and treatment of concomitant cardiovascular conditions, early and standardized rhythm control therapy reduces cardiovascular outcomes as compared with a rate control approach, favouring the restoration, and maintenance of sinus rhythm safely. Current therapies for rhythm control of AF include antiarrhythmic drugs (AADs) and catheter ablation (CA). However, response in an individual patient is highly variable with some remaining free of AF for long periods on antiarrhythmic therapy, while others require repeat AF ablation within weeks. The limited success of rhythm control therapy for AF is in part related to incomplete understanding of the pathophysiological mechanisms and our inability to predict responses in individual patients. Thus, a major knowledge gap is predicting which patients with AF are likely to respond to rhythm control approach. Over the last decade, tremendous progress has been made in defining the genetic architecture of AF with the identification of rare mutations in cardiac ion channels, signalling molecules, and myocardial structural proteins associated with familial (early-onset) AF. Conversely, genome-wide association studies have identified common variants at over 100 genetic loci and the development of polygenic risk scores has identified high-risk individuals. Although retrospective studies suggest that response to AADs and CA is modulated in part by common genetic variation, the development of a comprehensive clinical and genetic risk score may enable the translation of genetic data to the bedside care of AF patients. Given the economic impact of the AF epidemic, even small changes in therapeutic efficacy may lead to substantial improvements for patients and health care systems.