Stroke genetics informs drug discovery and risk prediction across ancestries

LDL-c Lowering, Ischemic Stroke, and Small Vessel Disease Brain Imaging Biomarkers: A Mendelian Randomization Study

BACKGROUND

The effects of lipid-lowering drug targets on different ischemic stroke subtypes are not fully understood. We aimed to explore the mechanisms by which lipid-lowering drug targets differentially affect the risk of ischemic stroke subtypes and their underlying pathophysiology.

METHODS

Using a 2-sample Mendelian randomization approach, we assessed the effects of genetically proxied low-density lipoprotein cholesterol (LDL-c) and 3 clinically approved LDL-lowering drugs (HMGCR [3-hydroxy-3-methylglutaryl-CoA reductase], PCSK9 [proprotein convertase subtilisin/kexin type 9], and NPC1L1 [Niemann-Pick C1-Like 1]) on stroke subtypes and brain imaging biomarkers associated with small vessel stroke (SVS), including white matter hyperintensity volume and perivascular spaces.

RESULTS

In genome-wide Mendelian randomization analyses, lower genetically predicted LDL-c was significantly associated with a reduced risk of any stroke, ischemic stroke, and large artery stroke, supporting previous findings. Significant associations between genetically predicted LDL-c and cardioembolic stroke, SVS, and biomarkers, perivascular space and white matter hyperintensity volume, were not identified in this study. In drug-target Mendelian randomization analysis, genetically proxied reduced LDL-c through NPC1L1 inhibition was associated with lower odds of perivascular space (odds ratio per 1-mg/dL decrease, 0.79 [95% CI, 0.67-0.93]) and with lower odds of SVS (odds ratio, 0.29 [95% CI, 0.10-0.85]).

CONCLUSIONS

This study provides supporting evidence of a potentially protective effect of LDL-c lowering through NPC1L1 inhibition on perivascular space and SVS risk, highlighting novel therapeutic targets for SVS.

Risk Factors for Intracerebral Hemorrhage: Genome-Wide Association Study and Mendelian Randomization Analyses

BACKGROUND

The genetic and nongenetic causes of intracerebral hemorrhage (ICH) remain obscure. The present study aimed to uncover the genetic and modifiable risk factors for ICH.

METHODS

We meta-analyzed genome-wide association study data from 3 European biobanks, involving 7605 ICH cases and 711 818 noncases, to identify the genomic loci linked to ICH. To uncover the potential causal associations of cardiometabolic and lifestyle factors with ICH, we performed Mendelian randomization analyses using genetic instruments identified in previous genome-wide association studies of the exposures and ICH data from the present genome-wide association study meta-analysis. We performed multivariable Mendelian randomization analyses to examine the independent associations of the identified risk factors with ICH and evaluate potential mediating pathways.

RESULTS

We identified 1 ICH risk locus, located at the APOE genomic region. The lead variant in this locus was rs429358 (chr19:45411941), which was associated with an odds ratio of ICH of 1.17 (95% CI, 1.11-1.20; P=6.01×10-11) per C allele. Genetically predicted higher levels of body mass index, visceral adiposity, diastolic blood pressure, systolic blood pressure, and lifetime smoking index, as well as genetic liability to type 2 diabetes, were associated with higher odds of ICH after multiple testing corrections. Additionally, a genetic increase in waist-to-hip ratio and liability to smoking initiation were consistently associated with ICH, albeit at the nominal significance level (P<0.05). Multivariable Mendelian randomization analysis showed that the association between body mass index and ICH was attenuated on adjustment for type 2 diabetes and further that type 2 diabetes may be a mediator of the body mass index-ICH relationship.

CONCLUSIONS

Our findings indicate that the APOE locus contributes to ICH genetic susceptibility in European populations. Excess adiposity, elevated blood pressure, type 2 diabetes, and smoking were identified as the chief modifiable cardiometabolic and lifestyle factors for ICH.

Impact of loss-of-function in angiopoietin-like 4 on the human phenome

BACKGROUND

Carriers of the E40K loss-of-function variant in Angiopoietin-like 4 (ANGPTL4), have lower plasma triglyceride levels as well as lower rates of coronary artery disease (CAD) and type 2 diabetes (T2D). These genetic data suggest ANGPTL4 inhibition as a potential therapeutic target for cardiometabolic diseases. However, it is unknown whether the association between E40K and human diseases is due to linkage disequilibrium confounding. The broader impact of genetic ANGPTL4 inhibition is also unknown, raising uncertainties about the safety and validity of this target.

METHODS

To assess the impact of ANGPLT4 inhibition, we evaluated whether E40K and other loss-of-function variants in ANGPTL4 influenced a wide range of health markers and diseases using 29 publicly available genome-wide association meta-analyses of cardiometabolic traits and diseases, as well as 1589 diseases assessed in electronic health records within FinnGen (n = 309,154). To determine whether these relationships were likely causal, and not driven by other correlated variants, we used the Bayesian fine mapping algorithm CoPheScan.

RESULTS

The CoPheScan posterior probability of E40K being the causal variant for triglyceride levels was 99.99 %, validating the E40K to proxy lifelong lower activity of ANGPTL4. The E40K variant was associated with lower risk of CAD (odds ratio [OR] = 0.84, 95 % CI = 0.81 to 0.87, p=3.6e-21) and T2D (OR = 0.91, 95 % CI = 0.87 to 0.95, p=2.8e-05) in GWAS meta-analyses, with results replicated in FinnGen. These significant results were also replicated using other rare loss-of-function variants identified through whole exome sequencing in 488,278 participants of the UK Biobank. Using a Mendelian randomization study design, the E40K variant effect on cardiometabolic diseases was concordant with lipoprotein lipase enhancement (r = 0.82), but not hepatic lipase enhancement (r = -0.10), suggesting that ANGPTL4 effects on cardiometabolic diseases are potentially mainly mediated through lipoprotein lipase. After correction for multiple testing, the E40K variant did not significantly increase the risk of any of the 1589 diseases tested in FinnGen.

CONCLUSIONS

ANGPTL4 inhibition may represent a potentially safe and effective target for cardiometabolic diseases prevention or treatment.

Identification of pleiotropic and specific therapeutic targets for cardio-cerebral diseases: A large-scale proteome-wide mendelian randomization and colocalization study

BACKGROUND

The cardiac-brain connection has been identified as the basis for multiple cardio-cerebral diseases. However, effective therapeutic targets for these diseases are still limited. Therefore, this study aimed to identify pleiotropic and specific therapeutic targets for cardio-cerebral diseases using Mendelian randomization (MR) and colocalization analyses.

METHODS

This study included two large protein quantitative trait loci studies with over 4,000 plasma proteins were included in the discovery and replication cohorts, respectively. We initially used MR to estimate the associations between protein and 20 cardio-cerebral diseases. Subsequently, Colocalization analysis was employed to enhance the credibility of the results. Protein target prioritization was based solely on including highly robust significant results from both the discovery and replication phases. Lastly, the Drug-Gene Interaction Database was utilized to investigate protein-gene-drug interactions further.

RESULTS

A total of 46 target proteins for cardio-cerebral diseases were identified as robust in the discovery and replication phases by MR, comprising 7 pleiotropic therapeutic proteins and 39 specific target proteins. Followed by colocalization analysis and prioritization of evidence grades for target protein, 6 of these protein-disease pairs have achieved the highly recommended level. For instance, the PILRA protein presents a pleiotropic effect on sick sinus syndrome and Alzheimer's disease, whereas GRN exerts specific effects on the latter. APOL3, LRP4, and F11, on the other hand, have specific effects on cardiomyopathy and ischemic stroke, respectively.

CONCLUSIONS

This study successfully identified important therapeutic targets for cardio-cerebral diseases, which benefits the development of preventive or therapeutic drugs.

Interplay between polygenic variants related immune response and lifestyle factors mitigate the chances of stroke in a genome-wide association study

We aimed to investigate the intricate interplay between genetic predisposition and lifestyle factors on stroke. We conducted a comprehensive genome-wide association study to identify the genetic variants linked to stroke in the participants who experienced a stroke event (cases; n 672) and those with no stroke history (non-stroke; n 58 029) in a large hospital-based cohort. Using generalised multifactor dimensionality reduction, we identified genetic variants with interactive effects and constructed polygenic risk scores (PRS) by summing up the risk alleles from the genetic variants. Food intake was measured with a validated semi-quantitative FFQ. No significant differences in stroke incidence were seen in demographic variables between the two groups. Among the metabolic indicators, only serum TAG levels were higher in males with stroke than those without stroke. The daily nutrient intake, dietary inflammation index, glycaemic index, dietary patterns, alcohol consumption, exercise and smoking did not display associations with the OR for stroke. The stroke-linked genetic variants were related to the IL-18 pathway. After accounting for covariates, the PRS derived from the 5-, 6- and 7-SNP models were positively associated with stroke chance with 2·5-, 2·9- and 2·8-fold. Furthermore, interactions between genetic predisposition and dietary components, including energy, carbohydrates, n-3 fatty acids and branched-chain amino acids (BCAA), that affected OR for stroke were observed. A high intake of energy, carbohydrates and BCAA and a low intake of n-3 fatty acids were positively associated with the chances of stroke occurrence. In conclusion, understanding the interaction between genetic variants and lifestyle factors can assist in developing stroke prevention and management strategies.

The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses

Decline in cognitive function is the most feared aspect of ageing. Poorer midlife cognitive function is associated with increased dementia and stroke risk. The mechanisms underlying variation in cognitive function are uncertain. Here, we assessed associations between 1160 proteins' plasma levels and two measures of cognitive function, the digit symbol substitution test (DSST) and the Montreal Cognitive Assessment in 1198 PURE-MIND participants. We identified five DSST performance-associated proteins (NCAN, BCAN, CA14, MOG, CDCP1), with NCAN and CDCP1 showing replicated association in an independent cohort, GS (N = 1053). MRI-assessed structural brain phenotypes partially mediated (8-19%) associations between NCAN, BCAN, and MOG, and DSST performance. Mendelian randomisation analyses suggested higher CA14 levels might cause larger hippocampal volume and increased stroke risk, whilst higher CDCP1 levels might increase intracranial aneurysm risk. Our findings highlight candidates for further study and the potential for drug repurposing to reduce the risk of stroke and cognitive decline.

A combined observational and Mendelian randomization investigation reveals NMR-measured analytes to be risk factors of major cardiovascular diseases

Dyslipidaemias is the leading risk factor of several major cardiovascular diseases (CVDs), but there is still a lack of sufficient evidence supporting a causal role of lipoprotein subspecies in CVDs. In this study, we comprehensively investigated several lipoproteins and their subspecies, as well as other metabolites, in relation to coronary heart disease (CHD), heart failure (HF) and ischemic stroke (IS) longitudinally and by Mendelian randomization (MR) leveraging NMR-measured metabolomic data from 118,012 UK Biobank participants. We found that 123, 110 and 36 analytes were longitudinally associated with myocardial infarction, HF and IS (FDR < 0.05), respectively, and 25 of those were associated with all three outcomes. MR analysis suggested that genetically predicted levels of 70, 58 and 7 analytes were associated with CHD, HF and IS (FDR < 0.05), respectively. Two analytes, ApoB/ApoA1 and M-HDL-C were associated with all three CVD outcomes in the MR analyses, and the results for M-HDL-C were concordant in both observational and MR analyses. Our results implied that the apoB/apoA1 ratio and cholesterol in medium size HDL were particularly of importance to understand the shared pathophysiology of CHD, HF and IS and thus should be further investigated for the prevention of all three CVDs.

SGLT1 and SGLT2 inhibition, circulating metabolites, and cerebral small vessel disease: a mediation Mendelian Randomization study

BACKGROUND

Sodium-glucose cotransporter 2 (SGLT2) and SGLT1 inhibitors may have additional beneficial metabolic effects on circulating metabolites beyond glucose regulation, which could contribute to a reduction in the burden of cerebral small vessel disease (CSVD). Accordingly, we used Mendelian Randomization (MR) to examine the role of circulating metabolites in mediating SGLT2 and SGLT1 inhibition in CSVD.

METHODS

Genetic instruments for SGLT1/2 inhibition were identified as genetic variants, which were both associated with the expression of encoding genes of SGLT1/2 inhibitors and glycated hemoglobin A1c (HbA1c) level. A two-sample two-step MR was used to determine the causal effects of SGLT1/2 inhibition on CSVD manifestations and the mediating effects of 1400 circulating metabolites linking SGLT1/2 inhibition with CSVD manifestations.

RESULTS

A lower risk of deep cerebral microbleeds (CMBs) and small vessel stroke (SVS) was linked to genetically predicted SGLT2 inhibition. Better white matter structure integrity was also achieved, as evidenced by decreased mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), as well as lower deep (DWMH) and periventrivular white matter hyperintensity (PWMH) volume. Inhibiting SGLT2 could also lessen the incidence of severe enlarged perivascular spaces (EPVS) located at white matter, basal ganglia (BG) and hippocampus (HIP). SGLT1 inhibition could preserve white matter integrity, shown as decreased MD of white matter and DWMH volume. The effect of SGLT2 inhibition on SVS and MD of white matter through the concentration of 4-acetamidobutanoate and the cholesterol to oleoyl-linoleoyl-glycerol (18:1 to 18:2) ratio, with a mediated proportion of 30.3% and 35.5% of the total effect, respectively.

CONCLUSIONS

SGLT2 and SGLT1 inhibition play protective roles in CSVD development. The SGLT2 inhibition could lower the risk of SVS and improve the integrity of white matter microstructure via modulating the level of 4-acetamidobutanoate and cholesterol metabolism. Further mechanistic and clinical studies research are needed to validate our findings.

Genetic assessment of efficacy and safety profiles of coagulation cascade proteins identifies Factors II and XI as actionable anticoagulant targets

Aims

Anticoagulants are routinely used by millions of patients worldwide to prevent blood clots. Yet, problems with anticoagulant therapy remain, including a persistent and cumulative bleeding risk in patients undergoing prolonged anticoagulation. New safer anticoagulant targets are needed.

Methods and results

To prioritize anticoagulant targets with the strongest efficacy [venous thromboembolism (VTE) prevention] and safety (low bleeding risk) profiles, we performed two-sample Mendelian randomization and genetic colocalization. We leveraged three large-scale plasma protein data sets (deCODE as discovery data set and Fenland and Atherosclerosis Risk in Communities as replication data sets] and one liver gene expression data set (Institut Universitaire de Cardiologie et de Pneumologie de Québec bariatric biobank) to evaluate evidence for a causal effect of 26 coagulation cascade proteins on VTE from a new genome-wide association meta-analysis of 44 232 VTE cases and 847 152 controls, stroke subtypes, bleeding outcomes, and parental lifespan as an overall measure of efficacy/safety ratio. A 1 SD genetically predicted reduction in F2 blood levels was associated with lower risk of VTE [odds ratio (OR) = 0.44, 95% confidence interval (CI) = 0.38-0.51, P = 2.6e-28] and cardioembolic stroke risk (OR = 0.55, 95% CI = 0.39-0.76, P = 4.2e-04) but not with bleeding (OR = 1.13, 95% CI = 0.93-1.36, P = 2.2e-01). Genetically predicted F11 reduction was associated with lower risk of VTE (OR = 0.61, 95% CI = 0.58-0.64, P = 4.1e-85) and cardioembolic stroke (OR = 0.77, 95% CI = 0.69-0.86, P = 4.1e-06) but not with bleeding (OR = 1.01, 95% CI = 0.95-1.08, P = 7.5e-01). These Mendelian randomization associations were concordant across the three blood protein data sets and the hepatic gene expression data set as well as colocalization analyses.

Conclusion

These results provide strong genetic evidence that F2 and F11 may represent safe and efficacious therapeutic targets to prevent VTE and cardioembolic strokes without substantially increasing bleeding risk.

Using machine learning to identify proteomic and metabolomic signatures of stroke in atrial fibrillation

Atrial fibrillation (AF) is a common cardiac arrhythmia, with stroke being its most detrimental comorbidity. The exact mechanism of AF related stroke (AFS) still needs to be explored. In this study, we integrated proteomics and metabolomics platform to explore disordered plasma proteins and metabolites between AF patients and AFS patients. There were 22 up-regulated and 31 down-regulated differentially expressed proteins (DEPs) in AFS plasma samples. Moreover, 63 up-regulated and 51 down-regulated differentially expressed metabolites (DEMs) were discovered in AFS plasma samples. We integrated proteomics and metabolomics based on the topological interactions of DEPs and DEMs, which yielded revealed several related pathways such as arachidonic acid metabolism, serotonergic synapse, purine metabolism, tyrosine metabolism and steroid hormone biosynthesis. We then performed a machine learning model to identify potential biomarkers of stroke in AF. Finally, we selected 6 proteins and 6 metabolites as candidate biomarkers for predicting stroke in AF by random forest, the area under the curve being 0.976. In conclusion, this study provides new perspectives for understanding the progressive mechanisms of AF related stroke and discovering innovative biomarkers for determining the prognosis of stroke in AF.

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.

Drug-target Mendelian randomization analysis supports lowering plasma ANGPTL3, ANGPTL4, and APOC3 levels as strategies for reducing cardiovascular disease risk

Aims

APOC3, ANGPTL3, and ANGPTL4 are circulating proteins that are actively pursued as pharmacological targets to treat dyslipidaemia and reduce the risk of atherosclerotic cardiovascular disease. Here, we used human genetic data to compare the predicted therapeutic and adverse effects of APOC3, ANGPTL3, and ANGPTL4 inactivation.

Methods and results

We conducted drug-target Mendelian randomization analyses using variants in proximity to the genes associated with circulating protein levels to compare APOC3, ANGPTL3, and ANGPTL4 as drug targets. We obtained exposure and outcome data from large-scale genome-wide association studies and used generalized least squares to correct for linkage disequilibrium-related correlation. We evaluated five primary cardiometabolic endpoints and screened for potential side effects across 694 disease-related endpoints, 43 clinical laboratory tests, and 11 internal organ MRI measurements. Genetically lowering circulating ANGPTL4 levels reduced the odds of coronary artery disease (CAD) [odds ratio, 0.57 per s.d. protein (95% CI 0.47-0.70)] and Type 2 diabetes (T2D) [odds ratio, 0.73 per s.d. protein (95% CI 0.57-0.94)]. Genetically lowering circulating APOC3 levels also reduced the odds of CAD [odds ratio, 0.90 per s.d. protein (95% CI 0.82-0.99)]. Genetically lowered ANGPTL3 levels via common variants were not associated with CAD. However, meta-analysis of protein-truncating variants revealed that ANGPTL3 inactivation protected against CAD (odds ratio, 0.71 per allele [95%CI, 0.58-0.85]). Analysis of lowered ANGPTL3, ANGPTL4, and APOC3 levels did not identify important safety concerns.

Conclusion

Human genetic evidence suggests that therapies aimed at reducing circulating levels of ANGPTL3, ANGPTL4, and APOC3 reduce the risk of CAD. ANGPTL4 lowering may also reduce the risk of T2D.

Causal role of myeloid cells in Parkinson's disease: Mendelian randomization study

BACKGROUND

Previous studies have observed elevated myeloid cells in the peripheral blood of patients with Parkinson's disease (PD), but the causal relationship between them remains to be elucidated. We investigated whether there is a causal relationship between different subtypes of peripheral blood myeloid cells and PD using Mendelian randomization (MR) combined with bioinformatics analysis. Exploring the etiology of PD from the perspective of genetics can remove confounding factors and provide a more reliable theoretical basis for elucidating the pathogenesis of PD.

METHODS

Comprehensive two-sample MR analysis and sensitivity analyses were conducted to explore the causal associations between 64 myeloid cell signatures and PD risk. The Venn diagram and protein-protein interaction network analysis of instrumental variables (IV) corresponding genes were used to further investigate the potential mechanism of myeloid cells influencing the pathogenesis of PD.

RESULTS

We investigated the impact of four immunophenotypes on the risk of PD, including Im MDSC% CD33dim HLA DR- CD66b- (relative count), CD33dim HLA DR+ CD11b+% CD33dim HLA DR+ (relative count), and CD11b on Mo MDSC (MFI) and CD11b on CD33br HLA DR+ CD14dim (MFI), while an immunophenotype's protective effect on PD was observed CD45 on Im MDSC (MFI). The results of bioinformatics analysis showed that CD33, NTRK2, PLD2, GRIK2 and RELN had protein interactions with the risk genes of PD.

CONCLUSIONS

Our study has demonstrated a close genetic correlation between different subtypes of myeloid cells and PD, providing guidance for early identification and immunotherapeutic development in patients with PD.

Causal effect of serum 25 hydroxyvitamin D concentration on cardioembolic stroke: Evidence from two-sample Mendelian randomization

BACKGROUND AND AIMS

The putative association between serum 25-hydroxyvitamin D concentration [25(OH)D] and the risk of cardioembolic stroke (CES) has been examined in observational studies, which indicate controversial findings. We performed Mendelian randomization (MR) analysis to determine the causal relationship of serum 25(OH)D with the risk of CES.

METHODS AND RESULTS

The summary statistics dataset on the genetic variants related to 25(OH)D was used from the published GWAS of European descent participants in the UK Biobank, including 417,580 subjects, yielding 143 independent loci in 112 1-Mb regions. GWAS summary data of CES was obtained from GIGASTROKE Consortium, which included European individuals (10,804 cases, 1,234,808 controls). Our results unveiled a causal relationship between 25(OH)D and CES using IVW [OR = 0.82, 95% CI: 0.67-0.98, p = 0.037]. Horizontal pleiotropy was not seen [MR-Egger intercept = 0.001; p = 0.792], suggesting an absence of horizontal pleiotropy. Cochrane's Q [Q = 78.71, p-value = 0.924], Rucker's Q [Q = 78.64, p-value = 0.913], and I2 = 0.0% (95% CI: 0.0%, 24.6%) statistic suggested no heterogeneity. This result remained consistent using different MR methods and sensitivity analyses, including Maximum likelihood [OR = 0.82, 95%CI: 0.67-0.98, p-value = 0.036], Constrained maximum likelihood [OR = 0.76, 95%CI: 0.64-0.90, p-value = 0.002], Debiased inverse-variance weighted [OR = 0.82, 95%CI: 0.68-0.99, p-value = 0.002], MR-PRESSO [OR = 0.82, 95%CI 0.77-0.87, p-value = 0.022], RAPS [OR = 0.82, 95%CI 0.67-0.98, p-value = 0.038], MR-Lasso [OR = 0.82, 95%CI 0.68-0.99, p-value = 0.037].

CONCLUSION

Our MR analysis provides suggestive evidence that increased 25(OH)D levels may play a protective role in the development of cardioembolic stroke. Determining the role of 25(OH)D in stroke subtypes has important clinical and public health implications.

An ensemble penalized regression method for multi-ancestry polygenic risk prediction

Great efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER). PROSPER integrates genome-wide association studies (GWAS) summary statistics from diverse populations to develop ancestry-specific PRS with improved predictive power for minority populations. The method uses a combination ofL 1 (lasso) andL 2 (ridge) penalty functions, a parsimonious specification of the penalty parameters across populations, and an ensemble step to combine PRS generated across different penalty parameters. We evaluate the performance of PROSPER and other existing methods on large-scale simulated and real datasets, including those from 23andMe Inc., the Global Lipids Genetics Consortium, and All of Us. Results show that PROSPER can substantially improve multi-ancestry polygenic prediction compared to alternative methods across a wide variety of genetic architectures. In real data analyses, for example, PROSPER increased out-of-sample prediction R2 for continuous traits by an average of 70% compared to a state-of-the-art Bayesian method (PRS-CSx) in the African ancestry population. Further, PROSPER is computationally highly scalable for the analysis of large SNP contents and many diverse populations.

An Ensemble Penalized Regression Method for Multi-ancestry Polygenic Risk Prediction

Great efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER). PROSPER integrates genome-wide association studies (GWAS) summary statistics from diverse populations to develop ancestry-specific PRS with improved predictive power for minority populations. The method uses a combination of ℒ 1 (lasso) and ℒ 2 (ridge) penalty functions, a parsimonious specification of the penalty parameters across populations, and an ensemble step to combine PRS generated across different penalty parameters. We evaluate the performance of PROSPER and other existing methods on large-scale simulated and real datasets, including those from 23andMe Inc., the Global Lipids Genetics Consortium, and All of Us. Results show that PROSPER can substantially improve multi-ancestry polygenic prediction compared to alternative methods across a wide variety of genetic architectures. In real data analyses, for example, PROSPER increased out-of-sample prediction R2 for continuous traits by an average of 70% compared to a state-of-the-art Bayesian method (PRS-CSx) in the African ancestry population. Further, PROSPER is computationally highly scalable for the analysis of large SNP contents and many diverse populations.

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.

Does Thrombosis Play a Causal Role in Lacunar Stroke and Cerebral Small Vessel Disease?

BACKGROUND

The importance of thromboembolism in the pathogenesis of lacunar stroke (LS), resulting from cerebral small vessel disease (cSVD), is debated, and although antiplatelets are widely used in secondary prevention after LS, there is limited trial evidence from well-subtyped patients to support this approach. We sought to evaluate whether altered anticoagulation plays a causal role in LS and cSVD using 2-sample Mendelian randomization.

METHODS

From a recent genome-wide association study (n=81 190), we used 119 genetic variants associated with venous thrombosis at genome-wide significance (P<5*10-8) and with a linkage disequilibrium r2<0.001 as instrumental variables. We also used genetic associations with stroke from the GIGASTROKE consortium (62 100 ischemic stroke cases: 10 804 cardioembolic stroke, 6399 large-artery stroke, and 6811 LS). In view of the lower specificity for LS with the CT-based phenotyping mainly used in GIGASTROKE, we also used data from patients with magnetic resonance imaging-confirmed LS (n=3199). We also investigated associations with more chronic magnetic resonance imaging features of cSVD, namely, white matter hyperintensities (n=37 355) and diffusion tensor imaging metrics (n=36 533).

RESULTS

Mendelian randomization analyses showed that genetic predisposition to venous thrombosis was associated with an increased odds of any ischemic stroke (odds ratio [OR], 1.19 [95% CI, 1.13-1.26]), cardioembolic stroke (OR, 1.32 [95% CI, 1.21-1.45]), and large-artery stroke (OR, 1.41 [95% CI, 1.26-1.57]) but not with LS (OR, 1.07 [95% CI, 0.99-1.17]) in GIGASTROKE. Similar results were found for magnetic resonance imaging-confirmed LS (OR, 0.94 [95% CI, 0.81-1.09]). Genetically predicted risk of venous thrombosis was not associated with imaging markers of cSVD.

CONCLUSIONS

These findings suggest that altered thrombosis plays a role in the risk of cardioembolic and large-artery stroke but is not a causal risk factor for LS or imaging markers of cSVD. This raises the possibility that antithrombotic medication may be less effective in cSVD and underscores the necessity for further trials in well-subtyped cohorts with LS to evaluate the efficacy of different antithrombotic regimens in LS.

A multitrait genetic study of hemostatic factors and hemorrhagic transformation after stroke treatment

BACKGROUND

Thrombolytic recombinant tissue plasminogen activator (r-tPA) treatment is the only pharmacologic intervention available in the ischemic stroke acute phase. This treatment is associated with an increased risk of intracerebral hemorrhages, known as hemorrhagic transformations (HTs), which worsen the patient's prognosis.

OBJECTIVES

To investigate the association between genetically determined natural hemostatic factors' levels and increased risk of HT after r-tPA treatment.

METHODS

Using data from genome-wide association studies on the risk of HT after r-tPA treatment and data on 7 hemostatic factors (factor [F]VII, FVIII, von Willebrand factor [VWF], FXI, fibrinogen, plasminogen activator inhibitor-1, and tissue plasminogen activator), we performed local and global genetic correlation estimation multitrait analyses and colocalization and 2-sample Mendelian randomization analyses between hemostatic factors and HT.

RESULTS

Local correlations identified a genomic region on chromosome 16 with shared covariance: fibrinogen-HT, P = 2.45 × 10-11. Multitrait analysis between fibrinogen-HT revealed 3 loci that simultaneously regulate circulating levels of fibrinogen and risk of HT: rs56026866 (PLXND1), P = 8.80 × 10-10; rs1421067 (CHD9), P = 1.81 × 10-14; and rs34780449, near ROBO1 gene, P = 1.64 × 10-8. Multitrait analysis between VWF-HT showed a novel common association regulating VWF and risk of HT after r-tPA at rs10942300 (ZNF366), P = 1.81 × 10-14. Mendelian randomization analysis did not find significant causal associations, although a nominal association was observed for FXI-HT (inverse-variance weighted estimate [SE], 0.07 [-0.29 to 0.00]; odds ratio, 0.87; 95% CI, 0.75-1.00; raw P = .05).

CONCLUSION

We identified 4 shared loci between hemostatic factors and HT after r-tPA treatment, suggesting common regulatory mechanisms between fibrinogen and VWF levels and HT. Further research to determine a possible mediating effect of fibrinogen on HT risk is needed.

Longer and better lives for patients with atrial fibrillation: the 9th AFNET/EHRA consensus conference

AIMS

Recent trial data demonstrate beneficial effects of active rhythm management in patients with atrial fibrillation (AF) and support the concept that a low arrhythmia burden is associated with a low risk of AF-related complications. The aim of this document is to summarize the key outcomes of the 9th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA).

METHODS AND RESULTS

Eighty-three international experts met in Münster for 2 days in September 2023. Key findings are as follows: (i) Active rhythm management should be part of the default initial treatment for all suitable patients with AF. (ii) Patients with device-detected AF have a low burden of AF and a low risk of stroke. Anticoagulation prevents some strokes and also increases major but non-lethal bleeding. (iii) More research is needed to improve stroke risk prediction in patients with AF, especially in those with a low AF burden. Biomolecules, genetics, and imaging can support this. (iv) The presence of AF should trigger systematic workup and comprehensive treatment of concomitant cardiovascular conditions. (v) Machine learning algorithms have been used to improve detection or likely development of AF. Cooperation between clinicians and data scientists is needed to leverage the potential of data science applications for patients with AF.

CONCLUSIONS

Patients with AF and a low arrhythmia burden have a lower risk of stroke and other cardiovascular events than those with a high arrhythmia burden. Combining active rhythm control, anticoagulation, rate control, and therapy of concomitant cardiovascular conditions can improve the lives of patients with AF.

Sleep Characteristics and Risk of Stroke and Dementia: An Observational and Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Sleep disturbances are implicated as risk factors of both stroke and dementia. However, whether these associations are causal and whether treatment of sleep disorders could reduce stroke and dementia risk remain uncertain. We aimed to evaluate associations and ascertain causal relationships between sleep characteristics and stroke/dementia risk and MRI markers of small vessel disease (SVD).

METHODS

We used data sets from a multicenter population-based study and summary statistics from genome-wide association studies (GWASs) of sleep characteristics and outcomes. We analyzed 502,383 UK Biobank participants with self-reported sleep measurements, including sleep duration, insomnia, chronotype, napping, daytime dozing, and snoring. In observational analyses, the primary outcomes were incident stroke, dementia, and their subtypes, alongside SVD markers. Hazard ratios (HRs) and odds ratios (ORs) were adjusted for age, sex, and ethnicity, and additional vascular risk factors. In Mendelian randomization (MR) analyses, ORs or risk ratios are reported for the association of each genetic score with clinical or MRI end points.

RESULTS

Among 502,383 participants (mean [SD] age, 56.5 [8.1] years; 54.4% female), there were 7,668 cases of all-cause dementia and 10,334 strokes. In longitudinal analyses, after controlling for cardiovascular risk factors, participants with insomnia, daytime napping, and dozing were associated with increased risk of any stroke (HR 1.05, 95% CI 1.01-1.11, p = 8.53 × 10-3; HR 1.09, 95% CI 1.05-1.14, p = 3.20 × 10-5; HR 1.19, 95% CI 1.08-1.32, p = 4.89 × 10-4, respectively). Almost all sleep measures were associated with dementia risk (all p < 0.001, except insomnia). Cross-sectional analyses identified associations between napping, snoring, and MRI markers of SVD (all p < 0.001). MR analyses supported a causal link between genetically predicted insomnia and increased stroke risk (OR 1.31, 95% CI 1.13-1.51, p = 0.00072), but not with dementia or SVD markers.

DISCUSSION

We found that multiple sleep measures predicted future risk of stroke and dementia, but these associations were attenuated after controlling for cardiovascular risk factors and were absent in MR analyses for Alzheimer disease. This suggests possible confounding or reverse causation, implying caution before proposing sleep disorder modifications for dementia treatment.

Functional Roles of Furin in Cardio-Cerebrovascular Diseases

Furin plays a major role in post-translational modification of several biomolecules, including endogenous hormones, growth factors, and cytokines. Recent reports have demonstrated the association of furin and cardio-cerebrovascular diseases (CVDs) in humans. This review describes the possible pathogenic contribution of furin and its substrates in CVDs. Early-stage hypertension and diabetes mellitus show a negative correlation with furin. A reduction in furin might promote hypertension by decreasing maturation of B-type natriuretic peptide (BNP) or by decreasing shedding of membrane (pro)renin receptor (PRR), which facilitates activation of the renin-angiotensin-aldosterone system (RAAS). In diabetes, furin downregulation potentially leads to insulin resistance by reducing maturation of the insulin receptor. In contrast, the progression of other CVDs is associated with an increase in furin, including dyslipidemia, atherosclerosis, ischemic stroke, myocardial infarction (MI), and heart failure. Upregulation of furin might promote maturation of membrane type 1-matrix metalloproteinase (MT1-MMP), which cleaves low-density lipoprotein receptor (LDLR), contributing to dyslipidemia. In atherosclerosis, elevated levels of furin possibly enhance maturation of several substrates related to inflammation, cell proliferation, and extracellular matrix (ECM) deposition and degradation. Neuronal cell death following ischemic stroke has also been shown to involve furin substrates (e.g., MT1-MMP, hepcidin, and hemojuvelin). Moreover, furin and its substrates, including tumor necrosis factor-α (TNF-α), endothelin-1 (ET-1), and transforming growth factor-β1 (TGF-β1), are capable of mediating inflammation, hypertrophy, and fibrosis in MI and heart failure. Taken together, this evidence provides functional significance of furin in CVDs and might suggest a potential novel therapeutic modality for the management of CVDs.

Genetic architecture of the structural connectome

Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.

Sex-specific genetic architecture of blood pressure

The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.

Joint Exposure to Ambient Air Pollutants, Genetic Risk, and Ischemic Stroke: A Prospective Analysis in UK Biobank

BACKGROUND

Our primary objective was to assess the association between joint exposure to various air pollutants and the risk of ischemic stroke (IS) and the modification of the genetic susceptibility.

METHODS

This observational cohort study included 307 304 British participants from the United Kingdom Biobank, who were stroke-free and possessed comprehensive baseline data on genetics, air pollutant exposure, alcohol consumption, and dietary habits. All participants were initially enrolled between 2006 and 2010 and were followed up until 2022. An air pollution score was calculated to assess joint exposure to 5 ambient air pollutants, namely particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, as well as nitrogen oxide and nitrogen dioxide. To evaluate individual genetic risk, a polygenic risk score for IS was calculated for each participant. We adjusted for demographic, social, economic, and health covariates. Cox regression models were utilized to estimate the associations between air pollution exposure, polygenic risk score, and the incidence of IS.

RESULTS

Over a median follow-up duration of 13.67 years, a total of 2476 initial IS events were detected. The hazard ratios (95% CI) of IS for per 10 µg/m3 increase in particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, nitrogen dioxide, and nitrogen oxide were 1.73 (1.33-2.14), 1.24 (0.88-1.70), 1.13 (0.89-1.33), 1.03 (0.98-1.08), and 1.04 (1.02-1.07), respectively. Furthermore, individuals in the highest quintile of the air pollution score exhibited a 29% to 66% higher risk of IS compared with those in the lowest quintile. Notably, participants with both high polygenic risk score and air pollution score had a 131% (95% CI, 85%-189%) greater risk of IS than participants with low polygenic risk score and air pollution score.

CONCLUSIONS

Our findings suggested that prolonged joint exposure to air pollutants may contribute to an increased risk of IS, particularly among individuals with elevated genetic susceptibility to IS.

High-Performance Hydrogel Sensors Enabled Multimodal and Accurate Human-Machine Interaction System for Active Rehabilitation

Human-machine interaction (HMI) technology shows an important application prospect in rehabilitation medicine, but it is greatly limited by the unsatisfactory recognition accuracy and wearing comfort. Here, this work develops a fully flexible, conformable, and functionalized multimodal HMI interface consisting of hydrogel-based sensors and a self-designed flexible printed circuit board. Thanks to the component regulation and structural design of the hydrogel, both electromyogram (EMG) and forcemyography (FMG) signals can be collected accurately and stably, so that they are later decoded with the assistance of artificial intelligence (AI). Compared with traditional multichannel EMG signals, the multimodal human-machine interaction method based on the combination of EMG and FMG signals significantly improves the efficiency of human-machine interaction by increasing the information entropy of the interaction signals. The decoding accuracy of the interaction signals from only two channels for different gestures reaches 91.28%. The resulting AI-powered active rehabilitation system can control a pneumatic robotic glove to assist stroke patients in completing movements according to the recognized human motion intention. Moreover, this HMI interface is further generalized and applied to other remote sensing platforms, such as manipulators, intelligent cars, and drones, paving the way for the design of future intelligent robot systems.

Mendelian Randomization Applied to Neurology: Promises and Challenges

The Mendelian randomization (MR) paradigm allows for causal inferences to be drawn using genetic data. In recent years, the expansion of well-powered publicly available genetic association data related to phenotypes such as brain tissue gene expression, brain imaging, and neurologic diseases offers exciting opportunities for the application of MR in the field of neurology. In this review, we discuss the basic principles of MR, its myriad applications to research in neurology, and potential pitfalls of injudicious applications. Throughout, we provide examples where MR-informed findings have shed light on long-standing epidemiologic controversies, provided insights into the pathophysiology of neurologic conditions, prioritized drug targets, and informed drug repurposing opportunities. With the ever-expanding availability of genome-wide association data, we project MR to become a key driver of progress in the field of neurology. It is therefore paramount that academics and clinicians within the field are familiar with the approach.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), 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, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA 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 global data, 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.

Genome-Wide Association Studies of 3 Distinct Recovery Phenotypes in Mild Ischemic Stroke

BACKGROUND AND OBJECTIVES

Stroke genetic research has made substantial progress in the past decade. Its recovery application, however, remains behind, in part due to its reliance on the modified Rankin Scale (mRS) score as a measure of poststroke outcome. The mRS does not map well to biological processes because numerous psychosocial factors drive much of what the mRS captures. Second, the mRS contains multiple disparate biological events into a single measure further limiting its use for biological discovery. This led us to investigate the effect of distinct stroke recovery phenotypes on genetic variation associations with Genome-Wide Association Studies (GWASs) by repurposing the NIH Stroke Scale (NIHSS) and its subscores.

METHODS

In the Vitamin Intervention for Stroke Prevention cohort, we estimated changes in cognition, motor, and global impairments over 2 years using specific measures. We included genotyped participants with a total NIHSS score greater than zero at randomization and excluded those with recurrent stroke during the trial. A GWAS linear mixed-effects model predicted score changes, with participant as a random effect, and included initial score, age, sex, treatment group, and the first 5 ancestry principal components.

RESULTS

In total, 1,270 participants (64% male) were included with a median NIHSS score of 2 (interquartile range [IQR] 1-3) and median age 68 (IQR 59-75) years. At randomization, 20% had cognitive deficits (NIHSS Cog-4 score >0) and 70% had ≥1 motor deficits (impairment score >1). At 2 years, these percentages improved to 7.2% with cognitive deficits and 30% with motor deficits. GWAS identified novel suggestive gene-impairment associations (p < 5e-6) for cognition (CAMK2D, EVX2, LINC0143, PTPRM, SGMS1, and SMAD2), motor (ACBD6, KDM4B, MARK4, PTPRS, ROBO1, and ROBO2), and global (MSR1 and ROBO2) impairments.

DISCUSSION

Defining domain-specific stroke recovery phenotypes and using longitudinal clinical trial designs can help detect novel genes associated with chronic recovery. These data support the use of granular endpoints to identify genetic associations related to stroke recovery.

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

BACKGROUND

African ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans.

METHODS

Cases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation.

RESULTS

We observed genome-wide significant (P-value < 5.0E-8) SNPs associations near AADACL2 and miRNA (MIR5186) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA (MIR4458) gene in chromosome 5 were also associated with stroke (P-value < 1.0E-6). The putative genes near AADACL2, MIR5186, and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 (P-value < 1.0E-6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) (P-value < 1.0E-6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping.

CONCLUSIONS

Our findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke's risk prediction and development of new targeted interventions to prevent or treat stroke.

The Rotterdam Study. Design update and major findings between 2020 and 2024

The Rotterdam Study is a population-based cohort study, started in 1990 in the district of Ommoord in the city of Rotterdam, the Netherlands, with the aim to describe the prevalence and incidence, unravel the etiology, and identify targets for prediction, prevention or intervention of multifactorial diseases in mid-life and elderly. The study currently includes 17,931 participants (overall response rate 65%), aged 40 years and over, who are examined in-person every 3 to 5 years in a dedicated research facility, and who are followed-up continuously through automated linkage with health care providers, both regionally and nationally. Research within the Rotterdam Study is carried out along two axes. First, research lines are oriented around diseases and clinical conditions, which are reflective of medical specializations. Second, cross-cutting research lines transverse these clinical demarcations allowing for inter- and multidisciplinary research. These research lines generally reflect subdomains within epidemiology. This paper describes recent methodological updates and main findings from each of these research lines. Also, future perspective for coming years highlighted.

Cardiovascular diseases consequences of type 1, type 2 diabetes mellitus and glycemic traits: A Mendelian randomization study

OBJECTIVE

This Mendelian randomization (MR) study aimed to investigate the relationships between type 1 diabetes (T1D), type 2 diabetes (T2D), and glycemic traits, including fasting insulin, fasting glucose, and HbA1c, with cardiovascular diseases (CVDs).

METHODS

We selected genetic instruments for predisposition to T1D, T2D, fasting insulin, fasting glucose, and HbA1c based on published genome-wide association studies. Using a 2-Sample MR approach, we assessed associations with 12 common CVDs sourced from the FinnGen and UK Biobank studies, along with stroke subtypes obtained from the GIGASTROKE and MEGASTROKE Consortium.

RESULTS

T1D was associated with SVS. T2D showed associations with AIS, LAA, CES, SVS, coronary heart disease, myocardial infarction, pulmonary embolism, DVT of lower extremities, peripheral vascular diseases. Genetically predicted higher HbA1c levels were associated with eight CVDs. The results of MVMR aligned with the primary findings for T1D and T2D.

CONCLUSIONS

T1D and T2D exhibit different genetic predisposition to CVDs. BMI, LDL, and HDL play intermediary roles in connecting TID and T2D to specific types of CVDs, providing insights into the potential underlying pathways and mechanisms involved in these relationships. Strategies aimed at achieving sustained reductions in HbA1c levels may offer potential for reducing the risk of various CVDs.

A terminal metabolite of niacin promotes vascular inflammation and contributes to cardiovascular disease risk

Despite intensive preventive cardiovascular disease (CVD) efforts, substantial residual CVD risk remains even for individuals receiving all guideline-recommended interventions. Niacin is an essential micronutrient fortified in food staples, but its role in CVD is not well understood. In this study, untargeted metabolomics analysis of fasting plasma from stable cardiac patients in a prospective discovery cohort (n = 1,162 total, n = 422 females) suggested that niacin metabolism was associated with incident major adverse cardiovascular events (MACE). Serum levels of the terminal metabolites of excess niacin, N1-methyl-2-pyridone-5-carboxamide (2PY) and N1-methyl-4-pyridone-3-carboxamide (4PY), were associated with increased 3-year MACE risk in two validation cohorts (US n = 2,331 total, n = 774 females; European n = 832 total, n = 249 females) (adjusted hazard ratio (HR) (95% confidence interval) for 2PY: 1.64 (1.10-2.42) and 2.02 (1.29-3.18), respectively; for 4PY: 1.89 (1.26-2.84) and 1.99 (1.26-3.14), respectively). Phenome-wide association analysis of the genetic variant rs10496731, which was significantly associated with both 2PY and 4PY levels, revealed an association of this variant with levels of soluble vascular adhesion molecule 1 (sVCAM-1). Further meta-analysis confirmed association of rs10496731 with sVCAM-1 (n = 106,000 total, n = 53,075 females, P = 3.6 × 10-18). Moreover, sVCAM-1 levels were significantly correlated with both 2PY and 4PY in a validation cohort (n = 974 total, n = 333 females) (2PY: rho = 0.13, P = 7.7 × 10-5; 4PY: rho = 0.18, P = 1.1 × 10-8). Lastly, treatment with physiological levels of 4PY, but not its structural isomer 2PY, induced expression of VCAM-1 and leukocyte adherence to vascular endothelium in mice. Collectively, these results indicate that the terminal breakdown products of excess niacin, 2PY and 4PY, are both associated with residual CVD risk. They also suggest an inflammation-dependent mechanism underlying the clinical association between 4PY and MACE.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

Breakfast skipping and traits of cardiometabolic health: A mendelian randomization study

BACKGROUND

Breakfast skipping has been linked to poor cardiometabolic health in observational studies, but the causality remains unknown. Herein, we used Mendelian randomization (MR) approach to elucidate the potential causal effects of breakfast skipping on cardiometabolic traits.

METHODS

Genetic association estimates for breakfast skipping, cardiometabolic diseases, and cardiometabolic risk factors were extracted from the UK Biobank and several large genome-wide association studies. Two-sample MR analyses were performed primarily using the inverse variance weighted method, followed by sensitivity analysis to test the reliability of results.

RESULTS

MR results indicated no causal relationship between breakfast shipping with coronary heart disease (odds ratio [OR]: 1.079, 95 % confidence interval [CI]: 0.817-1.426; p = 0.591), stroke (OR: 0.877, 95 % CI: 0.680-1.131; p = 0.311), and type 2 diabetes mellitus (OR: 1.114, 95 % CI: 0.631-1.970; p = 0.709). However, genetically predicted breakfast skipping was significantly associated with increased body mass index (β: 0.250, standard error [SE]: 0.079; p = 0.001), waist-to-hip ratio (β: 0.177, SE: 0.076; p = 0.019), and low-density lipoprotein cholesterol (β: 0.260, SE: 0.115; p = 0.024). We found no evidence of association of genetic liability to breakfast skipping with blood pressure, glycemic traits, and other blood lipids. Sensitivity analysis supported the above results.

CONCLUSION

Our study suggested that breakfast skipping is causally linked to weight gain and higher serum low-density lipoprotein cholesterol, which may mediate the increased risk of cardiometabolic diseases reported in epidemiological studies.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Biospecimens and Biomarkers

BACKGROUND

In patients with disorders of consciousness (DoC), laboratory and molecular biomarkers may help define endotypes, identify therapeutic targets, prognosticate outcomes, and guide patient selection in clinical trials. We performed a systematic review to identify common data elements (CDEs) and key design elements (KDEs) for future coma and DoC research.

METHODS

The Curing Coma Campaign Biospecimens and Biomarkers work group, composed of seven invited members, reviewed existing biomarker and biospecimens CDEs and conducted a systematic literature review for laboratory and molecular biomarkers using predetermined search words and standardized methodology. Identified CDEs and KDEs were adjudicated into core, basic, supplemental, or experimental CDEs per National Institutes of Health classification based on level of evidence, reproducibility, and generalizability across different diseases through a consensus process.

RESULTS

Among existing National Institutes of Health CDEs, those developed for ischemic stroke, traumatic brain injury, and subarachnoid hemorrhage were most relevant to DoC and included. KDEs were common to all disease states and included biospecimen collection time points, baseline indicator, biological source, anatomical location of collection, collection method, and processing and storage methodology. Additionally, two disease core, nine basic, 24 supplemental, and 59 exploratory biomarker CDEs were identified. Results were summarized and generated into a Laboratory Data and Biospecimens Case Report Form (CRF) and underwent public review. A final CRF version 1.0 is reported here.

CONCLUSIONS

Exponential growth in biomarkers development has generated a growing number of potential experimental biomarkers associated with DoC, but few meet the quality, reproducibility, and generalizability criteria to be classified as core and basic biomarker and biospecimen CDEs. Identification and adaptation of KDEs, however, contribute to standardizing methodology to promote harmonization of future biomarker and biospecimens studies in DoC. Development of this CRF serves as a basic building block for future DoC studies.

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease

Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genomic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying their comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and atherosclerotic CVD (ASCVD) revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial/lifestyle risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and demonstrated that the causal effects were partly explained by metabolic and psychosocial/lifestyle factors. The distinct signature of MDD-ASCVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.

A novel nomogram predicting early neurological deterioration after intravenous thrombolysis for acute ischemic stroke

Objectives

Intravenous thrombolysis therapy (IVT) with recombinant tissue plasminogen activator has proven to be a beneficial treatment for acute ischemic stroke (AIS) patients when administered within 4.5 h after a stroke. This study aimed to investigate an available and inexpensive predictive tool for early neurological deterioration in AIS.

Methods

Patients admitted to our department with acute stroke who were given IVT with recombinant tissue plasminogen activator within 4.5 h of stroke onset were included in the study. The NIH stroke scale (NIHSS) was used to assess patients' neurological state prior to IVT and for 24 h after. Early neurological deterioration was defined as occurring if the NIHSS total score increased by ≥ 4 or the NIHSS individual score increased by ≥ 2 compared to baseline. Patients were randomly assigned to training or validation cohorts.

Results

Of the 266 AIS patients receiving IVT who were screened, 217 were deemed eligible for the study. Multivariate logistic regression analysis identified smoking history, NIHSS score, homocysteine level, and neutrophil to lymphocyte ratio as independent factors for predicting early neurological deterioration. ROC analysis was used to assess the quality of the resulting nomogram. The AUC for the training dataset was 0.826 (95 % CI, 0.719-0.932), and for the validation dataset was 0.887 (95 % CI, 0.763-1.000).

Conclusion

The robustness of this nomogram suggests that it may be a reliable tool for evaluating the progression of AIS after IVT.

Antioxidants and the risk of stroke: results from NHANES and two-sample Mendelian randomization study

BACKGROUND

Stroke is the second leading cause of death worldwide, and observational studies have suggested a correlation between antioxidants and reduced stroke risk. However, it remains unclear whether causal relationships exist.

METHODS

This study first performed a cross-sectional study of the association between the Composite Dietary Antioxidant Index (CDAI) and stroke using data from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. Second, a two-sample univariable Mendelian Randomization (MR) was performed to analyze the causal effect of circulating levels of antioxidants on different subtypes of stroke.

RESULTS

The cross-sectional study included a total of 24,892 participants representing more than 200 million US non-institutionalized residents, a multivariable logistic regression model revealed that the risk of stroke decreased by 3.4% for each unit increase in CDAI (P = 0.017), with a non-linear association found, indicating a reduction in stroke risk before an inflection point of 3.078. MR analysis revealed that genetically determined levels of retinol had a suggestive protective effect on subarachnoid hemorrhage (SAH) (OR = 0.348, P = 0.025), and genetically determined levels of selenium had a suggestive protective effect against SAH (OR = 0.826, P = 0.007). However, no causal relationship was found between antioxidants and ischemic stroke or intracranial hemorrhage risk.

CONCLUSIONS

Evidence suggests that diet-derived antioxidants may reduce the risk of stroke, as indicated by the protective effects of retinol and selenium against SAH. However, more research is needed to fully understand how antioxidants prevent stroke.

Novel insight into the etiology of ischemic stroke gained by integrative multiome-wide association study

Stroke, characterized by sudden neurological deficits, is the second leading cause of death worldwide. Although genome-wide association studies (GWAS) have successfully identified many genomic regions associated with ischemic stroke (IS), the genes underlying risk and their regulatory mechanisms remain elusive. Here, we integrate a large-scale GWAS (N = 1 296 908) for IS together with molecular QTLs data, including mRNA, splicing, enhancer RNA (eRNA), and protein expression data from up to 50 tissues (total N = 11 588). We identify 136 genes/eRNA/proteins associated with IS risk across 60 independent genomic regions and find IS risk is most enriched for eQTLs in arterial and brain-related tissues. Focusing on IS-relevant tissues, we prioritize 9 genes/proteins using probabilistic fine-mapping TWAS analyses. In addition, we discover that blood cell traits, particularly reticulocyte cells, have shared genetic contributions with IS using TWAS-based pheWAS and genetic correlation analysis. Lastly, we integrate our findings with a large-scale pharmacological database and identify a secondary bile acid, deoxycholic acid, as a potential therapeutic component. Our work highlights IS risk genes/splicing-sites/enhancer activity/proteins with their phenotypic consequences using relevant tissues as well as identify potential therapeutic candidates for IS.

AGIDB: a versatile database for genotype imputation and variant decoding across species

The high cost of large-scale, high-coverage whole-genome sequencing has limited its application in genomics and genetics research. The common approach has been to impute whole-genome sequence variants obtained from a few individuals for a larger population of interest individually genotyped using SNP chip. An alternative involves low-coverage whole-genome sequencing (lcWGS) of all individuals in the larger population, followed by imputation to sequence resolution. To overcome limitations of processing lcWGS data and meeting specific genotype imputation requirements, we developed AGIDB (https://agidb.pro), a website comprising tools and database with an unprecedented sample size and comprehensive variant decoding for animals. AGIDB integrates whole-genome sequencing and chip data from 17 360 and 174 945 individuals, respectively, across 89 species to identify over one billion variants, totaling a massive 688.57 TB of processed data. AGIDB focuses on integrating multiple genotype imputation scenarios. It also provides user-friendly searching and data analysis modules that enable comprehensive annotation of genetic variants for specific populations. To meet a wide range of research requirements, AGIDB offers downloadable reference panels for each species in addition to its extensive dataset, variant decoding and utility tools. We hope that AGIDB will become a key foundational resource in genetics and breeding, providing robust support to researchers.

Genotypes of Stim1 and the proximal region on chromosome 1 exert opposite effects on stroke susceptibility in stroke-prone spontaneously hypertensive rat

BACKGROUND

The stroke-prone spontaneously hypertensive rat (SHRSP) is a genetic model for cerebral stroke. Although a recent study on a congenic SHRSP suggested that a nonsense mutation in stromal interaction molecule 1 ( Stim1 ) encoding a major component of store-operated Ca 2+ entry was a causal variant for stroke in SHRSP, this was not conclusive because the congenic region including Stim1 in that rat was too wide. On the other hand, we demonstrated that the Wistar-Kyoto (WKY)-derived congenic fragment adjacent to Stim1 exacerbated stroke susceptibility in a congenic SHRSP called SPwch1.71. In the present study, we directly examined the effects of the Stim1 genotype on stroke susceptibility using SHRSP in which wild-type Stim1 was knocked in (called Stim1 -KI SHRSP). The combined effects of Stim1 and the congenic fragment of SPwch1.71 were also investigated.

METHODS

Stroke susceptibility was assessed by the stroke symptom-free and survival periods based on observations of behavioral symptoms and reductions in body weight.

RESULTS

Stim1 -KI SHRSP was more resistant to, while SPwch1.71 was more susceptible to stroke than the original SHRSP. Introgression of the wild-type Stim1 of Stim1 -KI SHRSP into SPwch1.71 by the generation of F1 rats ameliorated stroke susceptibility in SPwch1.71. Gene expression, whole-genome sequencing, and biochemical analyses identified Art2b , Folr1 , and Pde2a as possible candidate genes accelerating stroke in SPwch1.71.

CONCLUSION

The substitution of SHRSP-type Stim1 to wild-type Stim1 ameliorated stroke susceptibility in both SHRSP and SPwch1.71, indicating that the nonsense mutation in Stim1 is causally related to stroke susceptibility in SHRSP.

CNS Drug Delivery in Stroke: Improving Therapeutic Translation From the Bench to the Bedside

Drug development for ischemic stroke is challenging as evidenced by the paucity of therapeutics that have advanced beyond a phase III trial. There are many reasons for this lack of clinical translation including factors related to the experimental design of preclinical studies. Often overlooked in therapeutic development for ischemic stroke is the requirement of effective drug delivery to the brain, which is critical for neuroprotective efficacy of several small and large molecule drugs. Advancing central nervous system drug delivery technologies implies a need for detailed comprehension of the blood-brain barrier (BBB) and neurovascular unit. Such knowledge will permit the innate biology of the BBB/neurovascular unit to be leveraged for improved bench-to-bedside translation of novel stroke therapeutics. In this review, we will highlight key aspects of BBB/neurovascular unit pathophysiology and describe state-of-the-art approaches for optimization of central nervous system drug delivery (ie, passive diffusion, mechanical opening of the BBB, liposomes/nanoparticles, transcytosis, intranasal drug administration). Additionally, we will discuss how endogenous BBB transporters represent the next frontier of drug delivery strategies for stroke. Overall, this review will provide cutting edge perspective on how central nervous system drug delivery must be considered for the advancement of new stroke drugs toward human trials.

Fine Particulate Matter Exposure, Genetic Susceptibility, and the Risk of Incident Stroke: A Prospective Cohort Study

BACKGROUND

Both genetic factors and environmental air pollution contribute to the risk of stroke. However, it is unknown whether the association between air pollution and stroke risk is influenced by the genetic susceptibilities of stroke and its risk factors.

METHODS

This prospective cohort study included 40 827 Chinese adults without stroke history. Satellite-based monthly fine particulate matter (PM2.5) estimation at 1-km resolution was used for exposure assessment. Based on 534 identified genetic variants from genome-wide association studies in East Asians, we constructed 6 polygenic risk scores for stroke and its risk factors, including atrial fibrillation, blood pressure, type 2 diabetes, body mass index, and triglyceride. The Cox proportional hazards model was applied to evaluate the hazard ratios and 95% CIs for the associations of PM2.5 and polygenic risk score with incident stroke and the potential effect modifications.

RESULTS

Over a median follow-up of 12.06 years, 3147 incident stroke cases were documented. Compared with the lowest quartile of PM2.5 exposure, the hazard ratio (95% CI) for stroke in the highest quartile group was 2.72 (2.42-3.06). Among individuals at high genetic risk, the relative risk of stroke was 57% (1.57; 1.40-1.76) higher than those at low genetic risk. Although no statistically significant interaction was found, participants with both the highest PM2.5 and high genetic risk showed the highest risk of stroke, with ≈4× that of the lowest PM2.5 and low genetic risk group (hazard ratio, 3.55 [95% CI, 2.84-4.44]). Similar upward gradients were observed in the risk of stroke when assessing the joint effects of PM2.5 and genetic risks of blood pressure, type 2 diabetes, body mass index, atrial fibrillation, and triglyceride.

CONCLUSIONS

Long-term exposure to PM2.5 was associated with a higher risk of incident stroke across different genetic susceptibilities. Our findings highlighted the great importance of comprehensive assessment of air pollution and genetic risk in the prevention of stroke.

Genetic variation supports a causal role for valproate in prevention of ischemic stroke

BACKGROUND

Valproate is a candidate for ischemic stroke prevention due to its anti-atherosclerotic effects in vivo. Although valproate use is associated with decreased ischemic stroke risk in observational studies, confounding by indication precludes causal conclusions.

AIMS

We applied Mendelian randomization to determine whether genetic variants that influence seizure response among valproate users associate with ischemic stroke.

METHODS

We derived a genetic score for valproate response using genome-wide association data of seizure response after valproate intake from the Epilepsy Pharmacogenomics Consortium. We then tested this score among valproate users of the UK Biobank for association with incident and recurrent ischemic stroke using Cox proportional hazard models. As replication, we tested found associations in an independent cohort of valproate users of the Mass General Brigham Biobank.

RESULTS

Among 2150 valproate users (mean 56 years, 54% females), 82 ischemic strokes occurred over a mean 12 year follow-up. Higher valproate response genetic score was associated with higher serum valproate levels (+5.78 µg/ml per 1 standard deviation (SD), 95% confidence interval (CI) (3.45, 8.11)). After adjusting for age and sex, higher valproate response genetic score was associated with lower ischemic stroke risk (hazard ratio (HR) per 1 SD 0.73, 95% CI (0.58, 0.91)) with a halving of absolute risk in the highest compared to the lowest score tertile (4.8% vs 2.5%, p trend = 0.027). Among 194 valproate users with prevalent stroke at baseline, a higher valproate response genetic score was associated with lower recurrent ischemic stroke risk (HR per 1 SD 0.53, 95% CI (0.32, 0.86)) with reduced absolute risk in the highest compared to the lowest score tertile (3/51, 5.9% vs 13/71, 18.3%, p trend = 0.026). The valproate response genetic score was not associated with ischemic stroke among the 427,997 valproate non-users (p = 0.61), suggesting minimal pleiotropy. In 1241 valproate users of the Mass General Brigham Biobank with 99 ischemic stroke events over 6.5 years follow-up, we replicated our observed associations between the valproate response genetic score and ischemic stroke (HR per 1 SD 0.77, 95% CI (0.61, 0.97)).

CONCLUSION

These results demonstrate that a genetically predicted favorable seizure response to valproate is associated with higher serum valproate levels and reduced ischemic stroke risk among valproate users, providing causal support for valproate effectiveness in ischemic stroke prevention. The strongest effect was found for recurrent ischemic stroke, suggesting potential dual-use benefits of valproate for post-stroke epilepsy. Clinical trials will be required in order to identify populations that may benefit most from valproate for stroke prevention.

DATA ACCESS STATEMENT

UK Biobank participant data are available after approval of a research proposal. The weights of the used genetic scores are available in the Supplemental Tables.

Genetic Susceptibility Modifies Relationships Between Air Pollutants and Stroke Risk: A Large Cohort Study

BACKGROUND

The extent to which genetic susceptibility modifies the associations between air pollutants and the risk of incident stroke is still unclear. This study was designed to investigate the separate and joint associations of long-term exposure to air pollutants and genetic susceptibility on stroke risk.

METHODS

The participants of this study were recruited by the UK Biobank between 2006 and 2010. These participants were followed up from the enrollment until the occurrence of stroke events or censoring of data. Hazard ratios (HRs) and 95% CIs for stroke events associated with long-term exposure to air pollutants were estimated by fitting both crude and adjusted Cox proportional hazards models. Additionally, the polygenic risk score was calculated to estimate whether the polygenic risk score modifies the associations between exposure to air pollutants and incident stroke.

RESULTS

A total of 502 480 subjects were included in this study. After exclusion, 452 196 participants were taken into the final analysis. During a median follow-up time of 11.7 years, 11 334 stroke events were observed, with a mean age of 61.60 years, and men accounted for 56.2% of the total cases. Long-term exposures to particulate matter with an aerodynamic diameter smaller than 2.5 µm (adjusted HR, 1.70 [95% CI, 1.43-2.03]) or particulate matter with an aerodynamic diameter smaller than 10 µm (adjusted HR, 1.50 [95% CI, 1.36-1.66]), nitrogen dioxide (adjusted HR, 1.10 [95% CI, 1.07-1.12]), and nitrogen oxide (adjusted HR, 1.04 [95% CI, 1.02-1.05]) were pronouncedly associated with increased risk of stroke. Meanwhile, participants with high genetic risk and exposure to high air pollutants had ≈45% (31%, 61%; particulate matter with an aerodynamic diameter smaller than 2.5 µm), 48% (33%, 65%; particulate matter with an aerodynamic diameter smaller than 10 µm), 51% (35%, 69%; nitrogen dioxide), and 39% (25%, 55%; nitrogen oxide) higher risk of stroke compared with those with low genetic risk and exposure to low air pollutants, respectively. Of note, we observed additive and multiplicative interactions between genetic susceptibility and air pollutants on stroke events.

CONCLUSIONS

Chronic exposure to air pollutants was associated with an increased risk of stroke, especially in populations at high genetic risk.

Genetic Architecture of Neurological Disorders and Their Endophenotypes: Insights from Genetic Association Studies

Population-scale genetic association studies of complex neurologic diseases have identified the underlying genetic architecture as multifactorial. Despite the study sample sizes reaching the millions, the identified disease-related genes explain only a small fraction of the phenotypic variance. Notable advancements in statistical methods now enable researchers to gain insights even from genomic regions where genotype-phenotype associations do not reach statistical significance. Such studies confirm a highly interconnected molecular network comprising a core group of genes directly involved in the disease process, alongside an expanded peripheral network, each contributing a small but potentially important (modulatory) effect. Additionally, causal inference methods, utilizing genetic instruments, have shed light on putative causal links between risk factors and clinical endpoints. In light of the pervasive genetic overlap or pleiotropy, however, caution is warranted in interpreting causal relationships inferred from these analyses. In this chapter, I will introduce the genetic association model, provide insights into the current state of genetic association studies, and discuss potential future directions.

Mendelian randomization study supports the causal effects of air pollution on longevity via multiple age-related diseases

Growing evidence suggests that exposure to fine particulate matter (PM2.5) may reduce life expectancy; however, the causal pathways of PM2.5 exposure affecting life expectancy remain unknown. Here, we assess the causal effects of genetically predicted PM2.5 concentration on common chronic diseases and longevity using a Mendelian randomization (MR) statistical framework based on large-scale genome-wide association studies (GWAS) (>400,000 participants). After adjusting for other types of air pollution and smoking, we find significant causal relationships between PM2.5 concentration and angina pectoris, hypercholesterolaemia and hypothyroidism, but no causal relationship with longevity. Mediation analysis shows that although the association between PM2.5 concentration and longevity is not significant, PM2.5 exposure indirectly affects longevity via diastolic blood pressure (DBP), hypertension, angina pectoris, hypercholesterolaemia and Alzheimer's disease, with a mediated proportion of 31.5, 70.9, 2.5, 100, and 24.7%, respectively. Our findings indicate that public health policies to control air pollution may help improve life expectancy.