GWAS-Supported CRP Gene Polymorphisms and Functional Outcome of Large Artery Atherosclerotic Stroke in Han Chinese

Genetics of ischemic stroke functional outcome

Ischemic stroke, which accounts for 87% of cerebrovascular accidents, is responsible for massive global burden both in terms of economic cost and personal hardship. Many stroke survivors face long-term disability-a phenotype associated with an increasing number of genetic variants. While clinical variables such as stroke severity greatly impact recovery, genetic polymorphisms linked to functional outcome may offer physicians a unique opportunity to deliver personalized care based on their patient's genetic makeup, leading to improved outcomes. A comprehensive catalogue of the variants at play is required for such an approach. In this review, we compile and describe the polymorphisms associated with outcome scores such as modified Rankin Scale and Barthel Index. Our search identified 74 known genetic polymorphisms spread across 48 features associated with various poststroke disability metrics. The known variants span diverse biological systems and are related to inflammation, vascular homeostasis, growth factors, metabolism, the p53 regulatory pathway, and mitochondrial variation. Understanding how these variants influence functional outcome may be helpful in maximizing poststroke recovery.

CRP as a potential predictor of outcome in acute ischemic stroke

Ischemic stroke is one of the major causes of death and long-term disability worldwide. C-reactive protein (CRP) as a potential biomarker for functional outcome after acute ischemic stroke remains controversial. The aim of the present study was to examine the association between the level of CRP and functional outcome of stroke. A total of 218 consecutive patients with acute ischemic stroke within 24 h after onset were recruited for the study. Poor functional outcome was defined as a modified Rankin scale score of >2 at 3 months after stroke. The retrospective analysis was performed to investigate whether CRP within 24 h after stroke is associated with poor functional outcome at 3 months. Multivariate logistic regression analysis indicated that the CRP level (odds ratio=1.146, 95%CI: 1.012-1.297, P=0.031) was an independent risk factor for poor outcome. The receiver operating characteristics curve analysis revealed that the optimal cut-off value of CRP to distinguish favorable from poor outcome was 6.34 (area under the curve=0.829, 95%CI: 0.772-0.887, P<0.001), with 68.2% sensitivity and 85.7% specificity. Spearman correlation analysis indicated that the CRP level was positively related to the baseline National Institutes of Health Stroke Scale (NIHSS) score (r=0.551, P<0.001), fasting glucose (r=0.301, P<0.001) and age (r=0.252, P<0.001). In conclusion, a high level of CRP within 24 h after onset was associated with a poor functional outcome after the acute ischemic event. The elevation of CRP may be correlated with the baseline NIHSS score, fasting glucose and age.

Stroke Genomics: Current Knowledge, Clinical Applications and Future Possibilities

The pathophysiology of stoke involves many complex pathways and risk factors. Though there are several ongoing studies on stroke, treatment options are limited, and the prevalence of stroke is continuing to increase. Understanding the genomic variants and biological pathways associated with stroke could offer novel therapeutic alternatives in terms of drug targets and receptor modulations for newer treatment methods. It is challenging to identify individual causative mutations in a single gene because many alleles are responsible for minor effects. Therefore, multiple factorial analyses using single nucleotide polymorphisms (SNPs) could be used to gain new insight by identifying potential genetic risk factors. There are many studies, such as Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) which have identified numerous independent loci associated with stroke, which could be instrumental in developing newer drug targets and novel therapies. Additionally, using analytical techniques, such as meta-analysis and Mendelian randomization could help in evaluating stroke risk factors and determining treatment priorities. Combining SNPs into polygenic risk scores and lifestyle risk factors could detect stroke risk at a very young age and help in administering preventive interventions.

Missense Variants in Hypoxia-Induced VEGFA/VEGFR2 Signaling Predict the Outcome of Large Artery Atherosclerotic Stroke

Collateral density variations are a major determinant of stroke outcome. Here, we explored the association of missense variants in hypoxia-induced VEGFA/VEGFR2 signaling and stroke outcome. We recruited 683 large artery atherosclerotic (LAA) stroke patients as the training set from Nanjing Stroke Registry Program between August 2013 and January 2016. To validate the findings from the training set, we recruited an additional 333 LAA stroke patients between February 2016 and January 2017 as the validation set. Genotyping of target SNPs (rs11549465 [HIF-1α], rs11549467 [HIF-1α], rs1870377 [VEGFR2], and rs2305948 [VEGFR2]) was conducted using a SNPscan method. Unfavorable outcome was defined as a modified Rankin Scale (mRS) score > 2 at three months after index event. In the training set, the AA genotype of rs1870377 led to a decreased risk of unfavorable outcomes in the recessive model (AA vs. TA + TT, OR 0.60, 95% CI 0.38-0.95, P = 0.031). This was confirmed in the validation set (OR 0.43, 95% CI 0.21-0.86, P = 0.017) and the combined set (OR 0.54, 95% CI 0.36-0.79, P = 0.002). We also found that A allele was a protective factor for stroke outcome in both validation set and combined set (OR 0.70, 95% CI 0.49-0.99, P = 0.044 and OR 0.77, 95% CI 0.63-0.94, P = 0.012, respectively). In silico analysis indicated that the rs1870377 variant led to structural alterations in VEGFR2 that may influence its activity. Our findings demonstrate that the rs1870377 in the hypoxia-induced VEGFA/VEGFR2 axis predicts the 3-month outcome of patients with LAA stroke.

Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

Stroke ranks the second leading cause of death among people over the age of 60 in the world. Stroke is widely regarded as a complex disease that is affected by genetic and environmental factors. Evidence from twin and family studies suggests that genetic factors may play an important role in its pathogenesis. Therefore, research on the genetic association of susceptibility genes can help understand the mechanism of stroke. Genome-wide association study (GWAS) has found a large number of stroke-related loci, but their mechanism is unknown. In order to explore the function of single-nucleotide polymorphisms (SNPs) at the molecular level, in this paper, we integrated 8 GWAS datasets with brain expression quantitative trait loci (eQTL) dataset to identify SNPs and genes which are related to four types of stroke (ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke). Thirty-eight SNPs which can affect 14 genes expression are found to be associated with stroke. Among these 14 genes, 10 genes expression are associated with ischemic stroke, one gene for large artery stroke, six genes for cardioembolic stroke and eight genes for small vessel stroke. To explore the effects of environmental factors on stroke, we identified methylation susceptibility loci associated with stroke using methylation quantitative trait loci (MQTL). Thirty-one of these 38 SNPs are at greater risk of methylation and can significantly change gene expression level. Overall, the genetic pathogenesis of stroke is explored from locus to gene, gene to gene expression and gene expression to phenotype.

Sex-specific and opposite modulatory aspects revealed by PPI network and pathway analysis of ischemic stroke in humans

Background

Ischemic Stroke (IS) is a major disease which greatly threatens human health. Recent studies showed sex-specific outcomes and mechanisms of cerebral ischemic stroke. This study aimed to identify the key changes of gene expression between male and female IS in humans.

Methods

Gene expression dataset GSE22255, including peripheral blood samples, was downloaded from the Gene Expression Omnibus (GEO) dataset. Differentially Expressed Genes (DEGs) with a LogFC>1, and a P-value <0.05 were screened by BioConductor R package and grouped in female, male and overlap DEGs for further bioinformatic analysis. Gene Ontology (GO) functional annotation, Protein-Protein Interaction (PPI) network, “Molecular Complex Detection” (MCODE) modules, CytoNCA (cytoscape network centrality analysis) essential genes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway interrelation analysis were performed.

Results

In a total of 54,665 genes, 185 (73 ups and 112 downs) DEGs in the female dataset, 461 DEGs (297 ups and 164 downs) in the male dataset, within which 118 DEGs overlapped (7 similar changes in female and male, 111 opposite changes in female and male) were obtained from the GSE22255 dataset. Female, male and overlapping DEGs enriched for similar cellular components and molecular function. Male DEGs enriched for divergent biological processes from female and overlapping DEGs. Sex-specific and overlapping DEGs were put into the PPI network. Overlapping genes such as IL6, presented opposite changes and were mainly involved in cytokine-cytokine receptor interactions, the TNF-signalling pathway, etc.

Conclusion

The analysis of sex-specific DEGs from GEO human blood samples showed that not only specific but also opposite DEG alterations in the female and male stroke genome wide dataset. The results provided an overview of sex-specific mechanisms, which might provide insight into stroke and its biomarkers and lead to sex-specific prognosis and treatment strategies in future clinical practice.

Influences of genetic variants on stroke recovery: a meta-analysis of the 31,895 cases

Background

The influences of genetic variants on functional clinical outcomes following stroke are unclear. In order to reliably quantify these influences, we undertook a comprehensive meta-analysis of outcomes after acute intracerebral haemorrhage (ICH) or ischaemic stroke (AIS) in relation to different genetic variants.

Methods

PubMed, PsycInfo, Embase and Medline electronic databases were searched up to January 2019. Outcomes, defined as favourable or poor, were assessed by validated scales (Barthel index, modified Rankin scale, Glasgow outcome scale and National Institutes of Health stroke scale).

Results

Ninety-two publications comprising 31,895 cases met our inclusion criteria. Poor outcome was observed in patients with ICH who possessed the APOE4 allele: OR =2.60 (95% CI = 1.25–5.41, p = 0.01) and in AIS patients with the GA or AA variant at the BDNF-196 locus: OR = 2.60 (95% CI = 1.25–5.41, p = 0.01) or a loss of function allele of CYP2C19: OR = 2.36 (95% CI = 1.56–3.55, p < 0.0001). Poor outcome was not associated with APOE4: OR = 1.02 (95% CI = 0.81–1.27, p = 0.90) or IL6-174 G/C: OR = 2.21 (95% CI = 0.55–8.86, p = 0.26) in patients with AIS.

Conclusions

We demonstrate that recovery of AIS was unfavourably associated with variants of BDNF and CYP2C19 genes whilst recovery of ICH was unfavourably associated with APOE4 gene.

Electronic supplementary material

The online version of this article (10.1007/s10072-019-04024-w) contains supplementary material, which is available to authorized users.

Association of G-protein coupled purinergic receptor P2Y2 with ischemic stroke in a Han Chinese population of North China

The G-protein-coupled purinergic receptor P2Y2 (P2RY2) plays an important role in the mechanism of atherosclerosis, which is relevant to ischemic stroke. This retrospective case-control study aimed to assess the relationship between P2RY2 gene polymorphisms and ischemic stroke risk in the northern Han Chinese population. In this study, clinical data and peripheral blood specimens were collected from 378 ischemic stroke patients and 344 controls. The ischemic stroke participants were recruited from the First Affiliated Hospital of China Medical University and the First Affiliated Hospital of Liaoning Medical University. The controls were recruited from the Health Check Center at the First Affiliated Hospital of China Medical University. Ischemic stroke patients were divided into two subgroups according to the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification: large-artery atherosclerosis (n = 178) and small-artery occlusion (n = 200) strokes. All subjects were genotyped for three single nucleotide polymorphisms (rs4944831, rs1783596, and rs4944832) in the P2RY2 gene using peripheral venous blood samples. The distribution of the dominant rs4944832 phenotype (GG vs. GA+AA) differed significantly between small-artery occlusion patients and control subjects (odds ratio (OR) = 1.720, 95% confidence interval (CI): 1.203–2.458, P < 0.01). Multivariable logistic regression analysis revealed that the GG genotype of rs4944832 was significantly more prevalent in small-artery occlusion patients than in control subjects (OR = 1.807, 95% CI: 1.215–2.687, P < 0.01). The overall distribution of the haplotype established by rs4944831-rs1783596-rs4944832 was significantly different between ischemic stroke patients and controls (P < 0.01). In ischemic stroke patients, the frequency of the G-C-G haplotype was significantly higher than in control subjects (P = 0.028), whereas the frequency of the T-C-A haplotype was lower than in control subjects (P = 0.047). These results indicate that the G-C-G haplotype of P2RY2 is a susceptibility haplotype for ischemic stroke. In addition, the GG genotype of rs4944832 may be associated with the development of small-artery occlusion in the northern Han Chinese population. The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of China Medical University on February 20, 2012 (No. 2012-38-1) and the First Affiliated Hospital of Liaoning Medical University, China, on March 1, 2013 (No. 2013-03-1). All participants gave their informed consent. This trial was registered with the ISRCTN Registry (ISRCTN11439124) on October 24, 2018. Protocol version (1.0).