Genomic Variation Affecting MPV and PLT Count in Association with Development of Ischemic Stroke and Its Subtypes

Platelets play a significant role in the pathophysiology of ischemic stroke since they are involved in the formation of intravascular thrombus after erosion or rupture of the atherosclerotic plaques. Platelet (PLT) count and mean platelet volume (MPV) are the two significant parameters that affect the functions of platelets. In the current study, MPV and PLT count was evaluated using flow cytometry and a cell counter. SonoClot analysis was carried out to evaluate activated clot timing (ACT), clot rate (CR), and platelet function (PF). Genotyping was carried out using GSA and Sanger sequencing, and expression analysis was performed using RT-PCR. In silico analysis was carried out using the GROMACS tool and UNAFold. The interaction of significant proteins with other proteins was predicted using the STRING database. Ninety-six genes were analyzed, and a significant association of THPO (rs6141) and ARHGEF3 (rs1354034) was observed with the disease and its subtypes. Altered genotypes were associated significantly with increased MPV, decreased PLT count, and CR. Expression analysis revealed a higher expression in patients bearing the variant genotypes of both genes. In silico analysis revealed that mutation in the THPO gene leads to the reduced compactness of protein structure. mRNA encoded by mutated ARHGEF3 gene increases the half-life of mRNA. The two significant proteins interact with many other proteins, especially the ones involved in platelet activation, aggregation, erythropoiesis, megakaryocyte maturation, and cytoskeleton rearrangements, suggesting that they could be important players in the determination of MPV values. In conclusion, the current study demonstrated the role of higher MPV affected by genetic variation in the development of IS and its subtypes. The results of the current study also indicate that higher MPV can be used as a biomarker for the disease and altered genotypes, and higher MPV can be targeted for better therapeutic outcomes.


Introduction
Stroke or 'brain attack' is one of the major causes of mortality and morbidity worldwide after myocardial infarction [1].Stroke is mainly divided into two types: ischemic and hemorrhagic stroke [2].Eighty-seven percent of the cases are of ischemic stroke (IS) type, 10% intracerebral hemorrhage (ICH), and 3% of subarachnoid hemorrhage (SAH) [3].IS occurs by an obstruction in the blood supply to the brain, which is usually caused by the formation of a thrombus leading to cell death in the brain [4].Various modifiable and non-modifiable risk factors are associated with the development of stroke.The modifiable risk factors, including hypertension, obesity, hyperglycemia, hyperlipidemia, atherosclerosis, thrombosis, renal dysfunction, and Sickle Cell Disease, contribute to an 87% risk of stroke.The non-modifiable risk factors include family history, age, and ethnicity.It has also been established that stroke has a strong genetic component [5][6][7].Genes involved in various pathways, including homocysteine metabolism, coagulation and hemostasis, rennin angiotensin aldosterone system, cAMP degradation pathway, inflammation, extracellular matrix, and lipid metabolism, are known to be associated with stroke susceptibility [7][8][9].
Platelet traits such as mean platelet volume (MPV) and platelet count (PLT) and pathways involved in the recruitment of platelets have also been implicated in the disease pathophysiology [10][11][12].Platelets are known to play an important role in the pathophysiology of IS by virtue of their capability in the formation of intravascular thrombus after the erosion or rupture of atherosclerotic plaques [13].We have already established the association of increased MPV with a degree of disability and rate of clot formation in IS patients [14].PLT count and MPV are markers of platelet function and activation and are positively associated with platelet reactivity and aggregation [15][16][17].An increase in MPV occurs when platelets become activated and swollen spheres instead of quiescent discs.Large platelets are more adhesive and likely to aggregate more than smaller ones [18].These traits and other platelet functions have been reported to be highly influenced by genetic variation.Various genome-wide association studies (GWAS) involving different populations have demonstrated that genomic alterations are associated with PLT count and MPV [19][20][21].Variation involved in the genes taking part in significant processes such as megakaryopoiesis, megakaryocyte/platelet adhesion, platelet formation, and cell cycle regulation has been reported to influence platelet physiology [10,22,23].PLT count and MPV altered by genetic profile have not been evaluated in association with the development of IS and its subtypes.Therefore, the current study has been carried out with an aim to explore the alterations in genes affecting MPV and PLT count and their functional implications associated with IS and its subtypes.

Study Population
Two hundred IS patients were recruited from Guru Gobind Singh Medical College and Hospital, Faridkot, Punjab, India.The study was approved by the ethical committee of the Central University of Punjab as well as the study hospital.Patients confirmed to have suffered an IS as diagnosed by a CT scan or MRI were included in this study.Patients having HS or TIA were excluded from this study.Patients with major secondary problems like renal, hepatic skeletal, and other neurological disorders were also excluded from the study.As a control group, 200 age and sex-matched healthy individuals without a history of any other medical condition, especially cardiovascular and neurological diseases, were also employed in the study.The present study involved patients between the age group of 27-94 years with a mean age of 61.8±13.3.The controls were between 24 and 72 years, with a mean age of 60.2±11.6.The male: female ratio of patients and controls was 156:44.Written informed consent was obtained from all the recruited subjects.Stroke subtypes were stratified as per TOAST classification [24].

Blood Sample Collection
A total of 5 ml of blood was collected in EDTA and sodium citrate-containing vacutainers with the written informed consent of the participants.

Measurements of Platelet Count and Mean Platelet Volume
MPV and PLT counts were evaluated using an automated cell counter (ABX Micros 60 Hematology System).The values were confirmed using BD Accuri C6 flow cytometer in 50% of the patients, as reported previously [14].

Sonoclot Signature Analysis
The assessment of clot timing in IS patients was carried out using Sonoclot Coagulation and Platelet Function Analyzer (Sienco Inc.: Model no.SCP1) as described in our previous study [14].

DNA Isolation
DNA isolation was carried out using the organic method (phenol-chloroform method) (Russell and Sambrook 2001).

Evaluation of Genomic Alterations Affecting MPV and PLT
The Screening for genetic variations affecting MPV and PLT count was carried out in 17% of IS patients to figure out the gene variants occurring at a higher frequency.This screening was carried out using Global Screening Array (GSA) v3.0 microchip (Illumina Inc.).After analyzing the GSA results, variants of three genes THPO (rs6141), WDR66 (rs7961894), and ARHGEF3 (rs1354034) were filtered out and all the samples; i.e., 200 patients and 200 controls were screened for these variants using Sanger Sequencing.

Expression Analysis
RNA was isolated from the platelets using the Trizol method.cDNA synthesis was carried out using a cDNA synthesis kit (iScript™ cDNA Synthesis Kit Bio-Rad) as per the manufacturer's instructions, with an equal amount of RNA from each sample.18s rRNA was used as a housekeeping gene.

Statistical Analysis
All significant variants were tested for Hardy-Weinberg equilibrium.The association of genotypes and alleles with IS (univariate analysis) was estimated by the odds ratio with a 95% confidence interval (CI) and χ 2 analysis using OpenEpi software (version 2.3.1;Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA).The association of gene variants with the disease was confirmed by Multiple Logistic Regression analysis (MLR).The independent variables were decided as the following dummy variables: MPV, 0 for standard and 1 for elevated; hypertension, 0 for normotension and 1 for hypertension; diabetes, 0 for normal and 1 for diabetic; tobacco use, 0 for no tobacco use and 1 for tobacco use; alcohol consumption, 0 for non-alcoholics and 1 for alcohol consumers; family history, 0 for no family history of IS and 1 for family history of IS.The dummy variables for gene variants were 0 for normal homozygous and 1 for heterozygous and mutant homozygote.All the statistical analysis was carried out using SPSS (Version: 28.0.1.1 (15)).Statistical significance was defined as p<0.05.

Molecular Modelling and Simulation of ARHGEF3 (Q9NR81) and THPO (P40225)
The amino acid sequence of the proteins was retrieved from UniProt [25].The AlphaFold Protein Structure Database was used to predict the protein structures [26].GROMACS 2018.3 modules were used to simulate the system of proteins as well as for the analysis to identify the potential role of mutation on the structural integrity of the two proteins with accession numbers Q9NR81 (Rho guanine nucleotide exchange factor 3, ARHGEF3) and P40225 (Thrombopoietin, THPO).In order to identify any structural deviation and/or stability, we have calculated the RMSD (root mean squared deviation) for the wild and mutated proteins along with the Radius of Gyration (Rg) that again tell us about any changes in the folded structure of the protein or conformational jump during the course of the simulation.As far as the rs1354034 variant of the ARHGEF3 gene is concerned, it is an intronic variant; it was difficult to simulate the mutated ARHGEF3 protein as it does not show any change in the amino acid sequence.Therefore, we used UNAFold to predict the changes caused by this SNP at the mRNA level [27].

Protein-Protein Interaction Networks
The STRING web-based server was used to generate a protein-protein interaction network of THPO and ARHGEF3 proteins at the highest confidence score of 0.700 [28].

Results
In our recent study, we already established the association of various risk factors with IS and its subtypes [14].A total of 106 variants affecting MPV, PLT count, and platelet reactivity were screened using GSA in 17% of IS patients (Fig. 1a).Three genes ARHGEF3 (rs1354034, T>C), THPO (rs6141, C>T), and WDR66 (rs7961894, C>T) showed variation based on the results of GSA.These were further validated by subjecting all the samples (200 patients and 200 controls) to Sanger sequencing.No significant association of WDR66 (rs7961894) was found with the disease.In the case of THPO, rs6141 (C>T) polymorphism, a significant difference was observed in genotypic distribution between IS patients and controls [for TT vs CC, X 2 =37.09; p<0.001,OR=6.98 (95% CI; 3.60-13.22)](Fig. 1b and Tables 1 and  2).TT and CT genotypes showed a significant association with the disease (for TT vs CC+CT, X 2 =6.323; p<0.005,OR=1.89 (95% CI; 1.17-3.07)).However, we did not find any significant difference in the distribution of T and C alleles between IS patients and controls.Even after controlling all the confounding risk factors using MLR, a significant association of TT genotype with IS was found ((p = 0.008; adjusted odds ratio −3.834; 95% CI; 1.431-10.277))(Table 5).
Evaluating the association of these two variants with IS subtypes, a significant association of TT genotypes of the THPO gene, whereas for the ARHGEF3 gene, a significant association was observed with the C allele as well as CC genotypes (p<0.001)(Tables 6 and 7).
The association of variants of THPO (rs6141) and ARHGEF3 (rs1354034) genes with MPV and PLT count was also evaluated.The altered genotypes of THPO (rs6141) and ARHGEF3 (rs1354034) gene showed a significant association with increased MPV, whereas, for PLT count, an association of the variant genotypes with decreased PLT count was observed, although it did not reach statistical significance (Table 8 and Figs.2a and  b).This is also in consensus with our observation, where an inverse correlation was observed between these two variables [14].
The clotting parameters, including ACT, CR, and PF, were also compared among various genotypes of THPO (rs6141) and ARHGEF3 (rs1354034) genes.A significant   increase in CR was observed in the patients bearing the altered TT genotype of THPO and CC genotype of ARHGEF3 gene in comparison with normal genotypes of both these genes, CC and TT, respectively.However, we did not find significant differences in ACT and PF values among the variant genotypes of both genes (Tables 9 and  10 and Figs.3a and b).Expression analysis carried out by qPCR of THPO (rs6141) and ARHGEF3 (rs1354034) genes revealed higher expression of both genes in patients bearing altered genotypes.The altered genotypes showed significantly higher expression in comparison with heterozygous and normal genotypes (p<0.05).Furthermore, the heterozygous genotypes showed a significantly higher expression as compared to the normal genotypes (p<0.05).Similarly, the expression of the CC genotype of the ARHGEF3 (rs1354034) gene was significantly higher in comparison with the heterozygous and normal genotypes (p<0.05).After comparing the heterozygous genotype with the normal genotype, it showed significantly higher expression (p<0.05) (Fig. 4).The results were normalized against 18s rRNA, which was used as a housekeeping gene to evaluate the expression of both genes.The amino acid sequence of the proteins was retrieved from UniProt [1].The AlphaFold Protein Structure Database was used to predict the protein structures of both THPO and ARHGEF3 genes.RMSD for both the Proteins (wild and mutated) were calculated using the GROMACS module gmx rms module with respect to a crystal structure as a reference.The stability of a protein relative to the reference structure can be determined by measuring the deviation produced during the simulation.The smaller the deviations, the more stable the simulated structure.RMSD values for all atoms of the mentioned three proteins were calculated for 100ns simulation.It can be observed for P40225 (Thrombopoietin), the wildtype structure was stable around 2.0 nm (3.5 ns) with respect to its crystal structure, but the mutated (R38C) structure showed a sudden jump to a higher rmsd value (2.5 nm) at 4.0 ns and maintained a constant elevation of RMSD value during the course of its simulation (Fig. 5).A similar indication was observed in the case of the Radius of gyration calculation that suggests the P40225 wild-type protein structure is stable during the course of the simulation, whereas in the case of mutated structure, moderate fluctuations were observed.However, the mutated protein shows reduced compactness in the protein structure with respect to the wild variant till the end of the simulation (Figs. 6 and 7).
As far as the rs1354034 variant of the ARHGEF3 gene is concerned, it is an intronic variant; it was difficult to simulate UNAFold software package is used to create the simulations of folding, hybridization, and melting pathways for one or two single-stranded RNA or DNA molecules.It combines free energy minimization, partition function calculations, and stochastic sampling to predict the folding of single-stranded RNA or DNA.Further, for melting simulations, the package computes entire melting profiles, not just the melting temperatures [27].
The results showed that the mutant (rs1354034) variant RNA exhibits qualitatively greater stability wrt the free energy associated with the secondary structure.This increased stability manifests in the reduced decay rate of the mutant RNA and, as a consequence, it increased processing into mRNA and its translation into the protein.The examination of the secondary structure of the mutant variant clearly indicates a more organized structure (Fig. 8) with 54 helices as compared to the wild-type sequence (50 helices).The average stem-loop size is also less for the mutant variant vis-à-vis wild type.This reduces the probability of its decay by RNases.

Discussion
IS affects a large number of individuals.In spite of the availability of various treatment modalities, the disease causes significant morbidity and mortality among patients.Therefore, there is a need to explore new biomarkers that can be used as diagnostic and prognostic markers and also targeted for better therapeutic approaches.Platelets are significant players in the formation of thrombus.Although the patients are prescribed various anti-platelet agents like aspirin and clopidogrel to prevent a stroke in individuals with a strong family history and also to prevent a recurrent stroke [13].Platelet parameters like MPV and PLT count are considered significant determinants of platelet function [29].There is evidence that increased platelet size and count reflect increased platelet activity and are useful predictive and prognostic biomarkers for cerebrovascular events.There is no study available on MPV and PLT count affected by a specific genetic alteration in association with the development of IS and its subtypes.Therefore, the current study is a novel approach to evaluate these parameters as potential diagnostic and prognostic markers in IS.In a recent study published by our lab, an elevated MPV was found to be significantly associated with an increased risk of IS, and also higher clot rate, and a higher degree of disability based on mRS.[14].These results are in accordance with previous studies where an increase in MPV has been associated significantly with an increased risk of IS [11,[29][30][31].In the current study, we screened the genetic variants involved in PLT count, MPV, and platelet reactivity in IS patients.Based on the previous reports, a total of 106 variants in 96 genes involved in PLT count, MPV and Platelet reactivity were initially screened using GSA in 17% of patients.Out of these, 62 variants have been reported to affect PLT count; 33 were found to affect MPV and 11 variants reported to affect platelet reactivity (Tables 11, 12, and 13).Most of these genes were found to be Fig.7 Ribbon model of mutant protein of Thrombopoietin (Accession number: P40225) during the course of a 100 ns simulation either normal homozygous or showed very minor frequency of heterozygosity except for variants of two genes ARHGEF3 (rs1354034, T>C) and THPO (rs6141, C>T).Therefore, these were evaluated further by Sanger Sequencing after amplifying the specific regions of these genes bearing the variation in all the subjects.Thrombopoietin (also known as THPO, TPO) is a major cytokine that plays a crucial role in platelet production.This humoral substance controls MK proliferation and differentiation to maintain normal thrombopoiesis [32].The SNP rs6141 (C>T) situated at the 3'-UTR region of the THPO gene is reported to be involved in the posttranscriptional control of the gene expression, mainly affecting mRNA splicing [33].Studies have also shown that microdeletions involving this SNP in the THPO gene cause mild congenital thrombocytopenia [34,35].Furthermore, two gain-of-function mutations in THPO gene G>C transversion and a G>T transversion have been reported to produce mRNAs with shortened 5′-untranslated regions (UTR) that are more efficiently translated in comparison with transcripts produced by wild-type THPO.These transcripts with a gain of function mutation result in elevated PLT count, which might lead to thrombosis and bleeding [36,37].THPO variants with bi-allelic loss-of-function cause multilineage bone marrow failure and severely reduced platelet counts [38][39][40].Another study identified a one-base deletion in the 5′-untranslated region of the THPO gene.In vitro experiments showed that this mutation increased TPO production and suggested that this region of the THPO gene may play a crucial role in regulating THPO expression [41].Based on the results of different GWAS studies, it has been established that rs6141 of the THPO gene is a significant determinant of MPV and PLT count [33,42,43].As far as the role of THPO in IS is concerned, it has been reported that elevated levels of TPO are associated with increased MPV and PLT counts in these patients [44][45][46].
In the current study evaluating the association of rs6141 (THPO) with IS, we found a significant association of TT genotype with the disease, which was confirmed by MLR analysis showing an independent association of TT genotype   with the disease (p<0.05).However, we did not find a significant difference in the distribution of T and C alleles between patients and controls.As far as the association of this variant with IS subtypes is concerned, the T allele showed a significant association with LAA, small artery occlusion, and cardioembolism.We also evaluated the association of variant genotype with MPV, Clot rate, and PLT count.The TT and CT genotypes showed a significant association with elevated MPV, higher clot rate, and reduced PLT count in comparison with the CC genotype-bearing patients.This association was also confirmed by MLR controlling all other confounding factors.
Since the focus of the current study was on platelet parameters, therefore, the expression analysis of THPO (rs6141) was carried out using mRNA isolated from platelets of IS patients.Patients bearing TT genotype showed the highest expression, followed by CT and CC genotypes.Aged platelets induce the production of TPO in the hepatocytes.TPO increases the number of circulating platelets once released into the bloodstream.Most of the studies have linked higher TPO levels with increased platelet activity [46].A study carried out by Balcik et al. (2013) reported that patients with IS have higher TPO and MPV levels and concluded that increased TPO levels elevate both PLT count and MPV resulting in a higher thrombotic capacity of platelets [44].Another study carried out in acute myocardial infarction (AMI) patients and unstable angina pectoris also reported that increased TPO and MPV levels are positively associated with each other in AMI patients [47].Yang et al. (2008) evaluated the role of Severe Acute Respiratory Syndrome (SARS) in affecting the normal functions of hematopoietic stem cells and megakaryocytic cells.They found that increased TPO levels in the plasma of these patients lead to thrombocytosis and hyperactive platelets [48].Recently a study demonstrated that platelets in COVID-19 patients aggregate faster and showed increased spreading of both fibrinogen and collagen during clot retraction.It was also found that TPO levels were elevated in the serum of SARS-CoV-2 patients [49].
Previous studies have mostly explored the association of THPO with PLT count.However, its role in MPV has not been studied much.Since MPV and PLT count is inversely correlated, therefore, it is obvious that studies showing its association with increased PLT count might not have observed its impact on MPV [50].
The proposed mechanism by which TT genotype (rs6141) might lead to the higher expression of the THPO gene in bone marrow producing hyperactive platelets, has been depicted in Fig. 10a.TPO binds to the megakaryocytes or platelets and controls their production through a feedback mechanism.During normal hemostasis, TPO concentrations remain normal.Platelets experience mechanical stress that shortens their life span under the conditions like atherosclerosis which indirectly activates platelet biogenesis [44,51].In vivo, the injection of recombinant adenoviral vectors, or transgenes, resulted in variable thrombocytosis [52][53][54][55].In addition, studies have also demonstrated that patients bearing gain of function mutations in the THPO gene enhance TPO mRNA translation which elevates its expression inducing lineage-selective effects in patients affected with thrombocytosis and polyclonal hematopoiesis.TPO levels were also observed to be higher in the serum [37,41,56,57].It has been reported that around 1000 to 3000 platelets are produced from a single MK [58].The mechanism leading to the production of platelets through MKs involves a lot of reorganization of cytoskeletal components like actin and tubulin.THPO is the major watchdog of this process [59,60].Although the process of thrombopoiesis is understood well, there are still many unanswered questions as to how some transcription factors like GATA and FOG1 affect the size of the platelets [61].
The impact of rs6141 of the THPO gene on protein structure was evaluated by protein dynamics studies using GROMACS.It showed that the wild-type structure of THPO was stable around 2.0 nm (3.5 ns) with respect to its crystal structure.On the other hand, mutated (R38C) structure showed a sudden jump to a higher RMSD value (2.5 nm) at 4.0 ns and maintained a constant higher RMSD value during the course of its simulation.The mutant protein encoded by THPO (rs6141) gene also showed reduced compactness in structure in comparison with the wild-type protein.This suggested that a minor deviation between the wild and mutated RMSD values affects the original protein structure.
ARHGEF3, also known as XPLN, is an exchange factor found in platelets, leukemics, and neuronal tissues [62].It was first identified as RhoGEF (Rho guanine nucleotide exchange factor) for Rho GTPases through an expressed sequence tag database search using the diffused B-cell lymphoma (Dbl) homology (DH) domain query in the BLASTN system [62].Skeletal muscles and the brain have the highest levels of ARHGEF3 protein expression, followed by the heart, kidneys, platelets, and macrophages [63].It plays a non-canonical role by inhibiting mTORC2 kinase activity through Akt signaling [63,64].It is also involved in various primary cellular functions, including cell adhesion, motility, polarity, growth, cell differentiation, and cytoskeleton rearrangements [63,65].
GWAS studies have identified newer roles of the ARH-GEF3 gene in modulating bone mineral density (BMD), platelet differentiation, and Hirschsprung disease [22,66].Another GWAS carried out to evaluate the association of significant variants with platelet traits reported the association of rs1354034 with MPV in association with other genes, including WDR66, TAOK1, and Phospatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit gamma [22].A metaanalysis including the results of various GWAS studies on 66 867 European individuals also demonstrated that rs1354034, located at 3p14.3, is associated significantly with PLT count and MPV [50].Zou et al. (2017) found that this SNP is present in the regulatory region (non-coding region upstream of the transcription start site) of the ARHGEF3 gene and proposed that it may influence the binding of certain transcription factors like RUNX1, MEIS1, and GATA2, GATA1, and FLI1 during MK maturation (Fig10b).However, it is not clear if this SNP is directly involved in influencing the binding sites of these transcription factors [66].The C allele of rs1354034 has been associated with lower ARHGEF3 mRNA expression, higher PLT count and lower MPV in humans [66].In a very recent report, researchers tried to investigate the genetic overlap of platelet parameters with an endophenotype of Parkinson's disease.They found that various genes, including ARHGEF3, are associated with MPV as well as the age of onset and Parkinson's disease susceptibility [67].
In the current study evaluating the association of rs1354034 (ARHGEF3) with IS and its subtypes, we found a significant association of CC genotype and C allele with the disease, which was confirmed by MLR analysis showing an independent association of CC genotype and C allele with the disease.As far as the association of this variant with IS subtypes is concerned, the CC genotype and C allele were found to be associated significantly with LAA, cardioembolism, small artery occlusion, and stroke of undetermined etiology.
We also evaluated the association of variant genotypes of the ARHGEF3 gene with MPV, Clot rate, and PLT count.The variants CC and TC genotypes showed a significant association with elevated MPV, higher clot rate, and reduced PLT count in comparison with the TT genotype.This association was also confirmed by MLR.A GWAS reported that the same SNP (rs1354034) is associated in trans with the expression of vWF, which is an important factor in the blood coagulation pathway in humans [68].
Expression analysis revealed that patients bearing the CC genotype of the ARHGEF3 gene showed the highest expression, followed by the TC genotype in comparison with the TT genotype in platelets.
Since this variant is an intronic variant, its impact on ARHGEF3 mRNA was evaluated using UNAFold.This analysis revealed that the mRNA encoded by the CC genotype of the ARHGEF3 gene (rs1354034) leads to qualitatively greater stability with respect to the free energy associated with the secondary structure as compared to the mRNA encoded by the normal genotype.
This SNP present upstream to the ARHGEF3 gene has been associated significantly with higher expression of ARHGEF3 during MK maturation both in murine and humans [66,69,70].Based on previous studies, it has been reported that ARHGEF3 is involved in platelet shape change and function.It has also been demonstrated that ARHGEF3 might be a missing link between ADP-mediated platelet shape change and activation via P2Y1 and P2Y2 receptors [66].The proposed mechanism by which CC genotype (rs1354034) might lead to the higher expression of the ARHGEF3 gene activating the MK maturation in bone marrow producing enlarged platelets, has been depicted in Fig. 11.Studies on mice lacking P2Y1 receptors do not show shape change of platelets in response to ADP, suggesting that the ADP signaling is associated with shape change mechanisms in these blood cells [71].This observation was further aided by another study that reported platelet shape change occurs through Rho signaling and actin reorganization [70,72].
As mentioned previously, THPO is a glycoprotein produced primarily in the liver that stimulates the formation of megakaryocytes and platelets.THPO protein was found to interact with 10 other proteins mainly involved in platelet activation (c-MPL, IL3), platelet aggregation (IL3), erythropoiesis (EPO, STAT5B), megakaryocyte development (c-MPL, JAK2, STAT3), cytoskeleton organization (CSF3), cell survival and proliferation (KITLG, STAT5A) [73][74][75].For the production of platelets, MKs undergo a series of remodeling events that result in thousands of platelets being released from a single cell [76].All the proteins found to interact with THPO protein are known to regulate platelet formation and functions [77][78][79].The interaction of THPO protein with other proteins suggested that there might be potential alternate mechanisms that could affect platelet production, morphology, and function.The THPO, along with other interacting proteins, might be explored as a significant biomarker affecting platelet parameters and functions and thereby a potential therapeutic target.
ARHGEF3 activates two members of the Rho family GTPases, RHOA and RHOB, which are involved in osteoblast maintenance [70].Various other cellular processes, including cytoskeleton reorganization, are activated and inactivated by Rho-like GTPases, as discussed previously [80,81].By catalyzing the release of bound GDP, guanine nucleotide exchange factors (GEFs) accelerate Rho GTPase activity.ARHGEF3 inhibits mTORC2 kinase activity, primarily for Akt, by binding the mTORC2 complex.ARHGEF3 protein has been found to interact with five other proteins involved in cytoskeleton organization (RHOA, RHOC), cell adhesion, migration (RHOA, RHOC, AHOB, and CTNNB1), apoptosis (RHOB), and cholesterol homeostasis (RNF145).Many physiological and pathological functions of platelets are mediated by Rho GTPase proteins [80].Actin cytoskeleton regulation is one of the main functions of Rho GTPases, although they also participate in several other biochemical pathways [82].When platelets interact with vWF and collagen via the cell-surface receptors GpIb-IX-V and GPVI, respectively, a dramatic change in shape occurs due to the reorganization of the actin cytoskeleton.When platelet morphology is altered, more surface area is available for interactions with the ECM and other cells [83,84].Initial shape changes include discoid loss, sphering, and filopodia extension.The interaction of ARHGEF3 and THPO with other proteins significantly involved in various platelet parameters and functions suggests that the Fig. 11 Mutated TPHO leads to an over expressed TPO cytokine, which activates the JAK-STAT pathway through its receptor (c-MPL) in Megakaryocytes.This pathway leads to the formation of platelets and also controls this formation as a feedback loop.Overexpression of THPO hampers this feedback loop and thereby results in the continuous formation of enlarged platelets.Overexpression of ARH-GEF3 activates RAS-GTP through Rho GEF after the activation of platelet receptor (P2Y1).RAS pathway in turn leads to the changes in cytoskeleton of platelets and thereby controls the platelet shape genotype-phenotype correlation should not be based on one protein but rather than a complete network should be analysed to explore their role as biomarkers or therapeutic targets.The current study is highly relevant as it sheds light on the underlying genetic mechanisms affecting platelet parameters contributing to the development of IS and its subtypes.This study is the first of its kind, focusing on these parameters.Overall the study is a step forward in the field of stroke, providing important insights into platelet parameters, especially MPV, altered by variation in significant genes and thereby highlighting the role of platelet markers in the development of IS.However, the limitation of the study is that the entire genomic landscape has not been explored.NGS approaches should be used to find out the association of variants, including novel ones in other genes employing a larger cohort and replicating the study in populations of different ethnicities.In addition, a more robust functional study needs to be conducted in order to interpret the potential impact of the significant genetic alterations observed in this study and understand the mechanisms involved.Knock-in and knock-out animal models can be used to determine the functional implication of significant variants observed in the current study as well as the ones that will be delineated by future omics studies.

Conclusion
We observed an association of ARHGEF3 (rs1354034) and THPO (rs6141) genes with higher MPV, higher rate of clot formation, and risk of developing IS.Further, we also observed that MPV and PLT count showed an inverse relationship with mutant alleles of both genes.Expression analysis of both THPO and ARHGEF3 genes revealed a higher expression of variant genotypes in the platelets.In silico analysis carried out for THPO (rs6141) gene showed that the mutated protein has reduced compactness in the protein structure in comparison with the wild type, which might be resulting in the higher expression of the THPO gene in the platelets.We used UNAFold to predict the changes caused by the variant ARHGEF3 (rs1354034) at the mRNA level because it is difficult to simulate the mutated ARHGEF3 (rs1354034) since it is an intronic variant.It showed that the mutant (rs1354034) variant RNA exhibits qualitatively greater stability with respect to the free energy associated with the secondary structure as compared to normal ARHGEF3 (rs1354034), which might lead to a higher expression in the platelets.Based on the STRING analysis, it was observed that these two significant proteins interact with other proteins which are involved in various pathways such as platelet activation, aggregation, erythropoiesis, megakaryocyte development, cytoskeleton organization, and cell adhesion.Cell migration, vascular development, apoptosis, cell proliferation, and cholesterol homeostasis.The current study is a step forward to establish MPV as a diagnostic or prognostic marker for IS.There is a need to develop specific treatment strategies that can particularly reduce MPV.Furthermore, establishing the specific genotype-phenotype correlation of markers affecting MPV in a particular population might help in devising better or specific treatment strategies.

Fig. 1 a
Fig. 1 a Genes involved in MPV, PLT Count, and Platelet Reactivity analysed by GSA.b Chromatogram showing CC TT and CT genotypes of THPO gene (rs6141).c Chromatogram showing TT, TC and CC genotypes of ARHGEF3 gene (rs1354034)

Fig. 3 aFig. 4
Fig. 3 a ACT, CR and PF values in patients bearing CC, CT and TT genotypes of THPO gene.b ACT, CR, and PF values in patients bearing TT TC and CC genotypes of ARHGEF3

Fig. 6
Fig. 6 Ribbon model of wild type protein of Thrombopoietin (Accession number: P40225) during the course of a 100 ns simulation

Fig. 8 Fig. 9
Fig. 8 Simulations of folding, hybridization, and melting pathways of a rs1354034 wild type and b rs1354034 (mutant) at 37 O C

Fig. 10 a
Fig. 10 a Desialylated platelets from circulation activates the JAK-STAT cascade in the hepatocytes leading to the activation og THPO gene, which further induces the MKs to produce platelets through c-mpl receptor in the

Table 5
Independent association of genotypes with IS

Table 6
Chi-square (X 2 ), odds ratio, and p-value for THPO (rs6141) gene variant in IS subtypes

Table 11
SNPs associated with PLT count

Table 12
SNPs associated with MPV