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bioRxiv · 10.1101/2023.11.07.565946

In-silico analysis of Myocardial Infarction-related missense SNPs to identify novel biomarkers to predict susceptibility.

Tarlochan, F. F.·Rasool, S.
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Abstract

Myocardial Infarction (MI), commonly known as a heart attack, stands as a formidable global health challenge, responsible for a substantial burden of morbidity and mortality. This study embarked on a comprehensive exploration of the genetic underpinnings of MI, recognizing the pivotal role of genetic factors in determining an individuals susceptibility to this life-threatening condition. The objective of our research was to investigate missense single nucleotide polymorphisms (SNP) associated with MI to determine whether the changes in amino acid sequences have potential implications for the risk of MI. Employing a multifaceted approach, we leveraged an array of computational tools and databases to scrutinize specific missense SNP and meticulously analyzed their potential effects on protein structure stability and function. Our analysis has confirmed a total of 4 missense SNP in ALDH2, APOE, IGFBP1, and PCSK1 genes to be damaging to protein structure and hence, the function. An extensive literature review was then performed to determine the functional roles of these genes in the regulation of the cardiac system-related pathways. Our analysis confirmed that all 2 of these genes are directly involved in pathways related to the cardiac system, while the other 2 genes play other roles. We have further analyzed their interactions and underlying biological processes to determine their potential role in the incidence of MI. These findings collectively offer a profound understanding of the intricate genetic landscape underlying MI. They not only enhance our comprehension of the multifaceted genetic factors influencing MI susceptibility but also set the stage for future experimental investigations. Importantly, these insights hold the potential to guide future research and the development of therapeutic strategies, to improve the prevention and management of this critical cardiovascular condition.

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Tarlochan, F. F., Rasool, S.. 2023-11-09. In-silico analysis of Myocardial Infarction-related missense SNPs to identify novel biomarkers to predict susceptibility.. https://doi.org/10.1101/2023.11.07.565946

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