Genetic testing for early prediction of cardiovascular diseases: genome-wide association studies and polygenic score

Authors: Jaroslav A. Hubáček
Authors‘ workplace: III. interní klinika – klinika endokrinologie a metabolismu 1. LF UK a VFN v Praze ;  Centrum experimentální medicíny, Institut klinické a experimentální medicíny, Praha
Published in: AtheroRev 2020; 5(2): 88-92


Despite the important shifts in both knowledge and technological possibilities in the field of molecular genetics, there are still considerable reserves in their use in clinical practice. Whole-genome association studies detected a high number of previously unknown variants associated with cardiovascular disease and its risk factors. Some of them pointed to new important points in the metabolic pathways. The strongest risk variants increase CVD by approximately 40% (most by 5–25% “only”) and a similar effect is observed for genetic variants associated with CVD risk factors. The maximum individual SNP effect on cholesterol levels is about 0.3 mmol/l and for triglycerides about 0.25 mmol/l, for obesity usually 300–500 grams of body weight per risk allele, and in the case of smoking the risk for becoming a smoker increases by about 40%. Recently, the research is focused on simultaneous analysis of number of genetic variants to subsequently produce polygenic genetic risk scores that should be more precise in early (at 18–25 years of age?) disease prediction. These scores either use a simple sum of the risk alleles present (unweighted score) or take into account the relative risks (weighted gene score), usually based on OR, HR or β coefficients.


CVD – genetic – genome wide association studies – prediction

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