• Maciej Banach, Martyna Fronczek, Tadeusz Osadnik, Agnieszka Gach, Dominik Strapagiel, Marcin Słomka, Mateusz Lejawa, Anna Goc, Ewa Boniewska-Bernacka, Anna Pańczyszyn, LipGregory Y HGYHLiverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University, and Liverpool Heart and Chest Hospital, Liverpool, UK.Department of Clinical Medicine, Aalborg University, Aalborg, Denmark., Dimitri P Mikhailidis, Peter P Toth, Peter E Penson, and Jacek Jóźwiak.
• Department of Cardiology and Adult Congenital Heart Diseases, Polish Mother's Memorial Hospital Research Institute (PMMHRI), Lodz, Poland.
• Arch Med Sci. 2024 Jan 1; 20 (5): 145214601452-1460.

IntroductionClassical risk factors such as hypertension, hypercholesterolemia, pre-diabetes, diabetes and obesity can predict adverse cardiovascular events, but they are less prognostic in patients aged < 60 years. Polygenic risk scores (PRS) can be effective in predicting adverse coronary events in younger and middle-aged patients. Our main aim is to assess the utility of a new PRS created for the Polish population in predicting mortality during an 8-year follow-up in the nationwide LIPIDOGEN2015 population.Material And MethodsAll DNA samples of 1779 patients were genotyped using Infinium Global Screening Array-24+ v3.0 Kit microarrays. The samples were amplified, fragmented, and hybridized to BeadChips. The BeadChips were scanned using iScan and converted to genotypes using Genome Studio 2.0.ResultsWe will develop a PRS based on the identified single nucleotide polymorphisms (SNPs) in the LIPIDOGEN2015 project's studied population and determine the analyzed group's risk of death due to cardiovascular diseases (CVD) based on data obtained from 8 years of patient-follow-up. Using the developed PRS scale and biochemical analyses, we will assess the effectiveness of lipid-lowering therapy with statins in patients with high and low genetic risk of sudden CVD events (secondary endpoints).ConclusionsThe developed PRS scale, combined with clinical covariates, will facilitate the creation of an algorithm to predict long-term mortality. This will enable us to stratify CVD risk more precisely, which may result in earlier implementation of lifestyle changes and dietary adjustments and potentially initiate earlier pharmacotherapy for at-risk individuals.Copyright: © 2024 Termedia & Banach.

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