Polygenic Risk Score Simulation: A case study of sudden cardiovascular diseas derived from literature insights

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00843989%3A_____%2F24%3AE0111548" target="_blank" >RIV/00843989:_____/24:E0111548 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1109/BIBM62325.2024.10821852" target="_blank" >http://dx.doi.org/10.1109/BIBM62325.2024.10821852</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/BIBM62325.2024.10821852" target="_blank" >10.1109/BIBM62325.2024.10821852</a>

Result language

angličtina

Original language name

Polygenic Risk Score Simulation: A case study of sudden cardiovascular diseas derived from literature insights

Original language description

Sudden cardiovascular diseases, including sudden cardiac arrest (SCA) and myocardial infarction (MI), remain among the leading causes of mortality worldwide. This study employs synthetic data simulations to develop polygenic risk scores (PRS) for improved identification of individuals at elevated risk. Leveraging genetic and phenotypic information from established literature, we modeled associations between multiple single nucleotide polymorphisms (SNPs) and the risk of sudden cardiovascular diseases. Our case study demonstrated that individuals with higher PRS values have a significantly increased risk of SCA and MI, with SNPs such as LTA (252A>G) identified as notable contributors. Additionally, combining PRS with traditional cardiovascular risk factors, such as smoking and diabetes, improved predictive accuracy, underscoring the value of integrating genetic data with clinical variables. These findings highlight the cumulative effect of genetic predispositions in determining cardiovascular risk and suggest potential applications of PRS models in personalized medicine to enhance preventive strategiesWhile promising, the study recognizes limitations related to the use of synthetic data and the need for validation in diverse, real-world populations. Future research should focus on refining these models and exploring additional genetic markers to further improve prediction capabilities.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

30101 - Human genetics

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIB 2024

ISBN

979-8-3503-8622-6

ISSN

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e-ISSN

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Number of pages

8

Pages from-to

5081-5088

Publisher name

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Place of publication

Lisbon: IEEE Xplore, 2024

Event location

Lisbon, Portugal

Event date

Dec 3, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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