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Stroke Genomics
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This entry is adapted from the peer-reviewed paper 10.3390/brainsci12030302

The pathophysiology of stroke 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.

stroke genomics Mendelian inheritance

1. Introduction

Several risk factors and complex pathways are involved in the pathophysiology of stroke. Stroke is the second leading cause of death worldwide after heart attack [1]. The human genome project has helped in understanding many genetic factors that are associated with stroke [2][3][4]. Several studies have reported genetic predisposition to stroke in both human beings and animal models. However, the definition of genetic risk factors for stroke is not well established. Since no single specific gene has been responsible for stroke, it has been hypothesized to be a multifactorial polygenic disorder [5].

2. Genetic Factor Associated with Stroke (Non-Modifiable Factors in Stroke)

Several studies, such as the classical twin study which consisted of 15,924 twin pairs have been designed to assess the genetic factors associated with stroke [6]. Likewise, another twin study provided evidence for genetic factors that may increase the risk of stroke related events, such as death and hospitalization [7]. This study found greater concordance rates for these associations among monozygotic twins, compared to dizygotic twins [7]. These two studies were designed long before the human genome project. There could be different environmental effects affecting the results of these studies, which was a major limitation [8]. Previous studies have reported that first degree relatives are at an increased risk for stroke [9]. The preponderance of large and small vessel strokes, compared to cardioembolic strokes, is higher among subjects with a family history of stroke [9]. Sex is an important factor to influence stroke outcome indicating the possible role of the sex chromosome and associated genes; however, recently a review reported no association between sex and stroke [10]. Similarly, though ethnicity is not widely considered as an important factor affecting acute stroke outcome; it may influence the long-term outcome [10][11]. A recent study identified that levels of lipoprotein-A were significantly associated with adverse stroke outcomes, and were substantially higher in the Black, compared to the White population [12]. In addition, hematological disorders are responsible for nearly 1.3% of acute stroke. Some of the common hematological disorders associated with stroke include polycythemia vera, sickle-cell disease, Waldenström macroglobulinemia, multiple myeloma, essential thrombocythemia, thrombotic thrombocytopenic purpura, protein C deficiency, Protein S deficiency, antithrombin deficiency, and Factor V Leiden. A substantial number of these disorders have a genetic predisposition. For example, a large proportion of polycythemia vera patients have a mutation in the exon 14 of the JAK2 gene (JAK2V617F), whereas a smaller proportion has mutations in the JAK2 exon 12 [4].

2.1. Heritability Genes in Stroke (Monogenic and Polygenic Inheritance in Stroke Etiology)

Several animal model studies were conducted to identify potential candidate genes associated with stroke outcome. These studies analyzed the association of single nucleotide polymorphisms (SNPs) in targeted genes. The SNP of COX-2 and rs20417 genes were associated with early neurological deterioration [13][14]. However, these studies are not supported with further replicational studies and hence warrant further in-depth research. A study reported that several single-gene disorders might influence stroke, such as sickle cell disease, Fabry’s disease, homocystinuria, mitochondrial myopathy, and encephalopathy [15]. A rare stroke case caused by mutations in the Notch 3 gene (OMIM*600276) showed heritable patterns [16], which was also reported as a single-gene disorder. Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) caused by different types of mutations of Notch 3 gene are associated with extensive cerebral small vessel damage, marked by the accumulation of granular osmiophilic material (GOM) [17]. Molecular evaluation of the vascular smooth muscles in CADASIL patients showed increased oxidation of soluble guanyl cyclase associated with decreased cyclic GMP levels, which impaired vasorelaxation of the cerebral vasculature [17]. A number of molecular pathways associated with cell adhesion, extracellular matrix components, misfolding control, autophagy, angiogenesis, and transforming growth factor β (TGFβ) signaling pathway are altered in CADASIL. Metabolic impairment, such as diabetes mellitus further expedites the pathological damage to the cerebral small blood vessels in Notch 3 mutation, resulting in endothelium mitochondrial dysfunction and vascular basement membrane injuries [18]. This suggests that the heritability of Notch 3 mutation increases the risk for ischemic stroke from small vessel diseases, such as CADASIL (Table 1).
Table 1. Studies showing stroke related events and clinical or pathological outcomes.
Table
Author, Year Stroke Related or Associated Events Outcome (Clinical or Pathological)
Bak et al., 2002 Higher stroke death and hospitalization in MZ compared to DZ twins Potential role of genetic factors in stroke etiology
Flossmann et al., 2004 Large and small vessel stroke in comparison to cardioembolic stroke Positive family history enhances the risk of large and small vessel stroke
Neves et al., 2021 CADASIL with gain of function mutation of notch 3 Enhanced cerebral small vessel disease marked by GOM
Neves et al., 2021 CADASIL and impaired cerebral vasorelaxation Augmented soluble guanyl cyclase oxidation and reduced cGMP
Felczak et al., 2021 Diabetes mellitus and cerebral small blood vessel injury in notch 3 mutation Associated with mitochondrial dysfunction in endothelial cells and vascular basement membrane injury
Mola-Caminal et al., 2019 PATJ variants Poor functional outcome post-stroke
Helgadottir et al., 2004 Vascular inflammation triggered by 5-lipoxygenase activating protein gene variants Increase the risk for myocardial infarction and stroke
Smith et al., 2009 Genetic determinants for ischemic stroke on chromosome 9p21 shared with coronary artery disease 2 common variants, rs2383207 and rs10757274 associated with modest increase in ischemic stroke risk
Ikram et al., 2009 SNPs (rs11833579 and rs12425791) in chromosome 12p13 Increased risk for ischemic stroke
Gretarsdottir et al., 2008 Atrial fibrillation associated cardioembolic events Increased risk for ischemic stroke associated with markers rs2200733 and rs10033464 located on chromosome 4q25
Malik et al., 2018 32 loci associated with ischemic stroke and its subtypes Shared traits with blood pressure, cardiac abnormalities, LDL cholesterol, atrial fibrillation and venous thromboembolism
Mola-Caminal et al., 2018 Top variant rs76221407 in PATJ gene Associated with poor functional outcome in ischemic stroke
Zhang et al., 2017 Downregulation of MALAT1 expression in in vitro and in vivo stroke model Enhanced pro-apoptotic bim and pro-inflammatory cytokines (MCP-1, IL-6, and E-selectin) in vitro. Post-stroke functional deterioration in vivo.
Yan et al., 2017 OGD-reperfusion induced neuronal injury in vitro LncRNA MEG3 induced neuronal death by downregulating miR-21/PDAC pathway
Long et al., 2018 LncRNA SNHG12 overexpression following neuronal ischemia Suppress neuronal death by downregulating miR-199a
Yin et al., 2019 LncRNA SNHG12 salvages ischemia injured neurons Upregulated Sirtuin-1 and activated AMPK pathway in vitro
Abbreviations: MZ, monozygotic; DZ, dizygotic; CADASIL, cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy; GOM, granular osmiophilic material; cGMP, cyclic guanosine monophosphate; PATJ, pals1-associated tight junction; SNP, single nucleotide polymorphism; LDL, low density lipoprotein; MALAT1, metastasis-associated lung adenocarcinoma transcript 1; MCP-1, monocyte chemoattractant protein-1; IL-6, interleukin-6; OGD, oxygen-glucose deprivation; LncRNA, long non-coding RNA; MEG3, maternally expressed gene 3; miR-21/PDAC, micro ribonucleic acid-21/pancreatic ductal adenocarcinoma; SNHG12, small nucleolar RNA host gene 12; miR-199a, micro ribonucleic acid-199a; AMPK, adenosine monophosphate-activated protein kinase.
Heterozygous mutations in the 3ʹuntranslated region (UTR) of the collagen 4A1 encoding gene may also influence ischemic stroke [19]. A glycine substitution mutation in the triple-helical domains of COL4A1 and COL4A2 may develop neurological and non-neurological manifestations, including hemorrhagic stroke [20]. The genomic data enables accurate analysis of heterozygous mutations. Another study identified heterozygous mutations in High-Temperature Requirement Serine protease A1 (HTRA1) encoding gene that manifest as stroke and cognitive decline in people aged more than 45 years [21]. Other mutations were also identified in the HTRA1 gene that may cause cerebral autosomal recessive arteriopathy in younger people who are between 10 to 30 years of age [22]. Similarly, mutations in adenosine deaminase 2 (ADA2), cathepsin A (CTSA) and forkhead-box C1 (FOXC1) genes were also found to be associated with autosomal dominant small vessel disease [23][24][25]. In addition, there are several other candidate genes under investigation for a possible association with stroke.

2.2. Multifactorial Stroke and SNPs

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 SNPs were used to gain newer insight by identifying potential genetic risk factors. For example, a study by Mola-Caminal et al. identified a locus located within a candidate gene [26], which can help in understanding the genetic mechanisms involved in stroke. Newer variants in the gene pals1-associated tight junction (PATJ) were linked to poor functional outcomes at 3-month post-stroke [26]. rs76221407 was the major SNP variant of the PATJ gene, which was associated with poor outcomes in stroke subjects after 3 months. The locus STRK1 was mapped to identify a susceptible gene for stroke for the first time [27]. Another study identified a strong association between the phosphodiesterase 4D gene (PDE4D; OMIM 600129*) and two major subtypes of stroke, cardiogenic and carotid stroke. Among 260 PDE4D gene SNPs, six were found to be significantly associated with stroke. Some of the SNPs were from UTR; therefore, these SNPs may affect the transcription of PDE4D [28]. The 5-lipoxygenase activating protein gene (ALOX5AP; OMIM 603700*) was also associated with an increased risk of stroke [29]. ALOX5AP SNP haplotypes increase the production of leukotriene B4 in stimulated neutrophils, thereby contributing to vascular inflammation in myocardial infarction and stroke [29]. The main limitation of studying candidate genes for SNPs and their association with stroke is that they are time consuming and require significant resources [30][31], and could be associated with false positive results.

3. Genomic Evaluation in Stroke

Several studies were designed during the 1990s to observe the effect of Mendelian genetics and candidate genes on stroke [32]. Subsequently, the human genome project enabled accurate SNP analysis by using the Genome-Wide Association Study (GWAS) [33].

Genome-Wide Association Study (GWAS) in Stroke

The first GWAS in stroke, Ischemic Stroke Genetics Study (ISGS) which included 250 patients and controls, was published in 2007 [34]. This study failed to identify any genetic locus, which was explicitly associated with stroke. Subsequently, studies focused on a specific region of chromosome 9 (9p21.3) and found an association with stroke [35]. This region was associated with coronary heart disease [36], and hence it was suggested that heart disease and ischemic stroke share similar polymorphisms. Another research group also studied chromosome 9 and found modest associations between ischemic stroke and variants (rs2383207 and rs10757274) of the 9p21 region [37]. Finally, six SNPs were identified, including rs2383207 in the 9p21 region, which were independently associated with the ischemic stroke (large artery atherosclerotic subtype) [38]. This suggests that chromosome 9p21 is an important risk locus that shares SNP variants that are common for both ischemic stroke and coronary artery disease.
A case-control study found a significant association between the 4q25 region and the cardioembolic subtype of ischemic stroke [39]. This region was also associated with all types of ischemic stroke, though to a lesser degree [39]. This study found that markers of atrial fibrillation, such as rs2200733 and rs10033464, have a strong association with ischemic stroke by increasing the risk for cardioembolic events. Another locus, the 16q22 was also found to be associated with cardioembolic stroke [40]. GWAS also found robust associations between intracranial aneurysms and loci on 2q, 8q, and 9p21 regions [41][42] The first prospective GWAS on stroke was the Heart and Aging Research in Genomic Epidemiology (CHARGE) study, which included 19,600 participants with 1544 strokes incidence [43]. This study identified two SNPs (rs11833579 and rs12425791) in the 12p13 region of chromosome 12 and within 11 kb upstream of the gene NINJ2 (Ninjurin 2), all of which were significantly associated with stroke.
The GWAS projects for ischemic stroke have identified many SNPs that are associated with stroke [44][45][46][47][48][49][50][51][52][53][54]. Among them, one study identified variants associated with different subtypes of stroke. This study showed that variants close to PITX2 (paired like homeodomain 2) and ZFHX3 (zinc finger homeobox 3) were linked to cardioembolic stroke. Variants on chromosome 9p21 locus and a novel variant on chromosome 7p21.1 within the histone deacetylase 9 (HDAC9) gene were associated with large vessel stroke [53]. This study suggested that genetic heterogeneity was associated with different stroke subtypes and would further demand subtype-specific studies for understanding genetic alterations in ischemic stroke.
Several GWAS consortia have been using and analyzing extensive datasets from major national and international projects. For example, SiGN project contains 14,549 cases from 24 genetic research centers located in the United States (n = 13) and Europe (n = 11) [55]. The MEGASTROKE consortium analyzed multi-ancestry GWAS data from more than 67,000 stroke cases and 454,000 controls and identified 32 significant loci to be associated with stroke [56]. Among them, two loci were independently associated with large artery stroke, and one with cardioembolic stroke. However, GWAS data has provided different associations between genes and stroke among different population and ethnic groups. For example, variants of the apelin receptor gene (APLNR, rs9943582) were associated with increased risk of ischemic stroke among the Japanese population, while these variants had no association with stroke among the Chinese Han Population [57]. Similarly, GWAS identified that rs2107595 SNP in the HDAC9 gene was associated with large-vessel ischemic stroke among the European population, while not among the Chinese Han population [58]. Another GWAS identified an SNP locus on region 10q25.3 of chromosome 10 (rs11196288) to be associated with the risk of early-onset ischemic stroke among the European population [59]. However, this SNP locus showed different susceptibility levels among the Chinese Han population.

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Subjects: Cardiac & Cardiovascular Systems
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Peter McGranaghan
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Update Date: 09 Mar 2022
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