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

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Abstract

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.

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Data Availability

The data generated or analysed during this study has been included in this article. The data relating to MPV, PLT count, and demographic profile of the study participants have already been published.

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Acknowledgements

Financial assistance from the Council for Scientific and Industrial Research (CSIR), India, and DST-FIST is highly acknowledged.

Funding

Financial assistance from DST-FIST (SR/FST/LS-I/2017/49) is acknowledged with thanks. Financial support to Mr. Abhilash Ludhiadch (Award No-09/ 1051(0029)/2 019-EMR-1) from the Council for Scientific and Industrial Research (CSIR) India is highly acknowledged.

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Authors and Affiliations

  1. Complex Disease Genomics and Precision Medicine Laboratory, Department of Human Genetics and Molecular Medicine, Central University of Punjab, Ghudda, Bathinda, Punjab, 151401, India

    Abhilash Ludhiadch & Anjana Munshi

  2. Department of Neurology, Guru Gobind Singh Medical College and Hospital, Sadiq Road, Faridkot, Punjab, 151203, India

    Sulena

  3. MD Anderson Cancer Center, Houston, TX, USA

    Sandeep Singh

  4. Department of Computational Sciences, School of Basic and Applied Sciences, Central University of Punjab, Ghudda, Bathinda, Punjab, 151401, India

    Sudip Chakraborty

  5. Department of Animal Sciences, School of Life Sciences, Central University of Himachal Pradesh, Kangra, Himachal Pradesh, 176206, India

    Dixit Sharma

  6. Centre for Computational Biology and Bioinformatics, School of Life Sciences, Central University of Himachal Pradesh, Kangra, Himachal Pradesh, 176206, India

    Mahesh Kulharia

  7. Department of Radiodiagnosis, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India

    Paramdeep Singh

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  1. Abhilash Ludhiadch
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  2. Sulena
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  8. Anjana Munshi
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Contributions

Anjana Munshi (AM) and Abhilash Ludhiadch (AL) conceived and planned the experiments. Sandeep Singh (SS) helped in mRNA expression analysis. AL carried out the experiments. Sudip Chakraborty (SC), and Mahesh Kulharia (MK) planned and carried out the protein and mRNA simulations. Sulena (S) and Paramdeep Singh (PS) helped in the sample collection and identification of patients. Dixit Sharma (DS) helped in protein-protein interaction studies. AM, AL, and SS contributed to the interpretation of the results. AL and AM took the lead in writing the manuscript. Overall the manuscript was shaped with invaluable and critical feedback from all the authors.

Corresponding author

Correspondence to Anjana Munshi.

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The study was approved by the Institutional ethics committee of the University (CUPB/CC/RO/18/2316) as well as the study hospital (GGS/IEC/56).

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Ludhiadch, A., Sulena, Singh, S. et al. Genomic Variation Affecting MPV and PLT Count in Association with Development of Ischemic Stroke and Its Subtypes. Mol Neurobiol 60, 6424–6440 (2023). https://doi.org/10.1007/s12035-023-03460-2

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