Blood Lipid Polygenic Risk Score Development and Application for Atherosclerosis Ultrasound Parameters

<b>Background:</b> The present study investigates the feasibility of using three previously published genome-wide association studies (GWAS) results on blood lipids to develop polygenic risk scores (PRS) for population samples from the European part of the Russian Federation. <b>Methods:</b> Two population samples were used in the study – one from the Ivanovo region (<i>n</i> = 1673) and one from the Vologda region (<i>n</i> = 817). We investigated three distinct approaches to PRS development: using the straightforward PRS approach with original effect sizes and fine-tuning with PRSice-2 and LDpred2. <b>Results:</b> In total, we constructed 56 PRS scales related to four lipid phenotypes: low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, total cholesterol, and triglyceride levels. Compared with previous results for the Russian population, we achieved an additional R² increase of 2–4%, depending on the approach and lipid phenotype studied. Overall, the R² PRS estimates approached those described for other populations. We also evaluated the clinical utility of blood lipid PRS for predicting carotid and femoral artery atherosclerosis. Specifically, we found that PRS for total cholesterol, low-density lipoprotein cholesterol, and triglycerides were positively correlated with ultrasound parameters of carotid and femoral artery atherosclerosis (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ρ</mi></semantics></math></inline-formula> = 0.09–0.13, <i>p</i> < 0.001), whereas PRS for high-density lipoprotein cholesterol were inversely correlated with the number of plaques in the femoral arteries (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ρ</mi></semantics></math></inline-formula> = −0.08, <i>p</i> = 8.71 × <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mn>10</mn><mrow><mo>−</mo><mn>3</mn></mrow></msup></mrow></semantics></math></inline-formula>). <b>Conclusions:</b> PRS fine-tuning using PRSice-2 add LDpred2 improves the performance of blood lipid PRS. Our study demonstrates the potential for further use of blood lipid PRS for prediction of atherosclerosis risk.