Stroke genetics informs drug discovery and risk prediction across ancestries

Novel insight into the etiology of ischemic stroke gained by integrative transcriptome-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 mRNA, splicing, enhancer RNA (eRNA) and protein expression data (N=11,588) from 50 tissues. We identify 136 genes/eRNA/proteins associated with IS risk across 54 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.

Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke

Stroke is the second largest cause of mortality in the world. Genome-wide association studies (GWAS) have identified some genetic variants associated with stroke risk, but their putative functional causal genes are unknown. Hence, we aimed to identify putative functional causal gene biomarkers of stroke risk. We used a summary-based Mendelian randomisation (SMR) approach to identify the pleiotropic associations of genetically regulated traits (i.e., gene expression and DNA methylation) with stroke risk. Using SMR approach, we integrated cis-expression quantitative loci (cis-eQTLs) and cis-methylation quantitative loci (cis-mQTLs) data with GWAS summary statistics of stroke. We also utilised heterogeneity in dependent instruments (HEIDI) test to distinguish pleiotropy from linkage from the observed associations identified through SMR analysis. Our integrative SMR analyses and HEIDI test revealed 45 candidate biomarker genes (FDR < 0.05; P_HEIDI>0.01) that were pleiotropically or potentially causally associated with stroke risk. Of those candidate biomarker genes, 10 genes (HTRA1, PMF1, FBN2, C9orf84, COL4A1, BAG4, NEK6, SH2B3, SH3PXD2A, ACAD10) were differentially expressed in genome-wide blood transcriptomics data from stroke and healthy individuals (FDR<0.05). Functional enrichment analysis of the identified candidate biomarker genes revealed gene ontologies and pathways involved in stroke, including "cell aging", "metal ion binding" and "oxidative damage". Based on the evidence of genetically regulated expression of genes through SMR and directly measured expression of genes in blood, our integrative analysis suggests ten genes as blood biomarkers of stroke risk. Furthermore, our study provides a better understanding of the influence of DNA methylation on the expression of genes linked to stroke risk.

Genetic Risk Score Improves Risk Stratification for Anticoagulation-Related Intracerebral Hemorrhage

BACKGROUND

Intracerebral hemorrhage (ICH) is the most devastating adverse outcome for patients on anticoagulants. Clinical risk scores that quantify bleeding risk can guide decision-making in situations when indication or duration for anticoagulation is uncertain. We investigated whether integration of a genetic risk score into an existing risk factor-based CRS could improve risk stratification for anticoagulation-related ICH.

METHODS

We constructed 153 genetic risk scores from genome-wide association data of 1545 ICH cases and 1481 controls and validated them in 431 ICH cases and 431 matched controls from the population-based UK Biobank. The score that explained the largest variance in ICH risk was selected and tested for prediction of incident ICH in an independent cohort of 5530 anticoagulant users. A CRS for major anticoagulation-related hemorrhage, based on 8/9 components of the HAS-BLED score, was compared with a combined clinical and genetic risk score incorporating an additional point for high genetic risk for ICH.

RESULTS

Among anticoagulated individuals, 94 ICH occurred over a mean follow-up of 11.9 years. Compared with the lowest genetic risk score tertile, being in the highest tertile was associated with a two-fold increased risk for incident ICH (hazard ratio, 2.08 [95% CI, 1.22-3.56]). Although the CRS predicted incident ICH with a hazard ratio of 1.24 per 1-point increase (95% CI [1.01-1.53]), adding a point for high genetic ICH risk led to a stronger association (hazard ratio of 1.33 per 1-point increase [95% CI, 1.11-1.59]) with improved risk stratification (C index 0.57 versus 0.53) and maintained calibration (integrated calibration index 0.001 for both). The new clinical and genetic risk score showed 19% improvement in high-risk classification among individuals with ICH and a net reclassification improvement of 0.10.

CONCLUSIONS

Among anticoagulant users, a prediction score incorporating genomic information is superior to a clinical risk score alone for ICH risk stratification and could serve in clinical decision-making.

Impact of miR-200b and miR-495 variants on the risk of large-artery atherosclerosis stroke

Single-nucleotide polymorphisms (SNPs) of microRNAs (miRNAs) may alter miRNA transcription, maturation and target specificity, thus affecting stroke susceptibility. We aimed to investigate whether miR-200b and miR-495 SNPs may be associated with ischemic stroke (IS) risk and further explore underlying mechanisms including related genes and pathways. MiR-200b rs7549819 and miR-495 rs2281611 polymorphisms were genotyped among 712 large-artery atherosclerosis (LAA) stroke patients and 1,076 controls in a case-control study. Bioinformatic analyses were performed to explore potential association of miR-200b/495 with IS and to examine the effects of these two SNPs on miR-200b/495. Furthermore, we evaluated the association between these two SNPs and stroke using the public GWAS datasets. In our case-control study, rs7549819 was significantly associated with a decreased risk of LAA stroke (OR = 0.73, 95% CI = 0.58-0.92; p = 0.007), while rs2281611 had no significant association with LAA stroke risk. These results were consistent with the findings in East Asians from the GIGASTROKE study. Combined effects analysis revealed that individuals with 2-4 protective alleles (miR-200bC and miR-495 T) exhibited lower risk of LAA stroke than those with 0-1 variants (OR = 0.76, 95% CI = 0.61-0.96; p = 0.021). Bioinformatic analyses showed that miR-200b and miR-495 were significantly associated with genes and pathways related to IS pathogenesis, and rs7549819 and rs2281611 markedly influenced miRNA expression and structure. MiR-200b rs7549819 polymorphism and the combined genotypes of miR-200b rs7549819 and miR-495 rs2281611 polymorphisms were associated with decreased risk of LAA stroke in Chinese population.

Early peripheral blood gene expression associated with good and poor 90-day ischemic stroke outcomes

BACKGROUND

This study identified early immune gene responses in peripheral blood associated with 90-day ischemic stroke (IS) outcomes.

METHODS

Peripheral blood samples from the CLEAR trial IS patients at ≤ 3 h, 5 h, and 24 h after stroke were compared to vascular risk factor matched controls. Whole-transcriptome analyses identified genes and networks associated with 90-day IS outcome assessed using the modified Rankin Scale (mRS) and the NIH Stroke Scale (NIHSS).

RESULTS

The expression of 467, 526, and 571 genes measured at ≤ 3, 5 and 24 h after IS, respectively, were associated with poor 90-day mRS outcome (mRS ≥ 3), while 49, 100 and 35 genes at ≤ 3, 5 and 24 h after IS were associated with good mRS 90-day outcome (mRS ≤ 2). Poor outcomes were associated with up-regulated genes or pathways such as IL-6, IL-7, IL-1, STAT3, S100A12, acute phase response, P38/MAPK, FGF, TGFA, MMP9, NF-kB, Toll-like receptor, iNOS, and PI3K/AKT. There were 94 probe sets shared for poor outcomes vs. controls at all three time-points that correlated with 90-day mRS; 13 probe sets were shared for good outcomes vs. controls at all three time-points; and 46 probe sets were shared for poor vs. good outcomes at all three time-points that correlated with 90-day mRS. Weighted Gene Co-Expression Network Analysis (WGCNA) revealed modules significantly associated with 90-day outcome for mRS and NIHSS. Poor outcome modules were enriched with up-regulated neutrophil genes and with down-regulated T cell, B cell and monocyte-specific genes; and good outcome modules were associated with erythroblasts and megakaryocytes. Finally, genes identified by genome-wide association studies (GWAS) to contain significant stroke risk loci or loci associated with stroke outcome including ATP2B, GRK5, SH3PXD2A, CENPQ, HOXC4, HDAC9, BNC2, PTPN11, PIK3CG, CDK6, and PDE4DIP were significantly differentially expressed as a function of stroke outcome in the current study.

CONCLUSIONS

This study suggests the immune response after stroke may impact functional outcomes and that some of the early post-stroke gene expression markers associated with outcome could be useful for predicting outcomes and could be targets for improving outcomes.

Genetic considerations in cerebral small vessel diseases

Cerebral small vessel disease (CSVD) encompasses a broad clinical spectrum united by pathology of the small vessels of the brain. CSVD is commonly identified using brain magnetic resonance imaging with well characterized markers including covert infarcts, white matter hyperintensities, enlarged perivascular spaces, and cerebral microbleeds. The pathophysiology of CSVD is complex involving genetic determinants, environmental factors, and their interactions. While the role of vascular risk factors in CSVD is well known and its management is pivotal in mitigating the clinical effects, recent research has identified novel genetic factors involved in CSVD. Delineating genetic determinants can promote the understanding of the disease and suggest effective treatments and preventive measures of CSVD at the individual level. Here we review CSVD focusing on recent advances in the genetics of CSVD. The knowledge gained has advanced understanding of the pathophysiology of CSVD, offered promising early results that may improve subtype identification of small vessel strokes, has led to additional identification of mendelian forms of small vessel strokes, and is getting closer to influencing clinical care through pharmacogenetic studies.

Exome Array Analysis of 9721 Ischemic Stroke Cases from the SiGN Consortium

Recent genome wide association studies have identified 89 common genetic variants robustly associated with ischemic stroke and primarily located in non-coding regions. To evaluate the contribution of coding variants, which are mostly rare, we performed an exome array analysis on 106,101 SNPs for 9721 ischemic stroke cases from the SiGN Consortium, and 12,345 subjects with no history of stroke from the Health Retirement Study and SiGN consortium. We identified 15 coding variants significantly associated with all ischemic stroke at array-wide threshold (i.e., p < 4.7 × 10-7), including two common SNPs in ABO that have previously been associated with stroke. Twelve of the remaining 13 variants were extremely rare in European Caucasians (MAF < 0.1%) and the associations were driven by African American samples. There was no evidence for replication of these associations in either TOPMed Stroke samples (n = 5613 cases) or UK Biobank (n = 5874 stroke cases), although power to replicate was very low given the low allele frequencies of the associated variants and a shortage of samples from diverse ancestries. Our study highlights the need for acquiring large, well-powered diverse cohorts to study rare variants, and the technical challenges using array-based genotyping technologies for rare variant genotyping.