O.4.2-9 Shared genetic factors may partly explain the associations between physical activity and cardiometabolic diseases

• Published in: European Journal of Public Health
• Main Authors: Sillanpää, Elina, Tynkkynen, Niko, Törmäkangas, Timo, Palviainen, Teemu, Hyvärinen, Matti, Joensuu, Laura, Klevjer, Marie, Bye, Anja, Paula, Pesonen, Katja, Waller, Maarit, Kangas, Minna, Männikkö, Henri, Vähä-Ypyä, Harri, Sievänen, Raija, Korpelainen, Timo, Jämsä, Maisa, Niemelä, Samuli, Ripatti, Urho, Kujala, Jaakko, Kaprio
• Format: Text
• Language: English
• Published: Oxford University Press 2023
• Subjects: Parallel sessions; Northern Finland
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493917/; https://doi.org/10.1093/eurpub/ckad133.184

Shared genetic factors may contribute to the associations between higher levels of physical activity (PA) and lower risk for cardiometabolic diseases (CMDs), and may partially explain these associations observed in cohort studies. To explore this, we used novel methodology to calculate PA genotypes (polygenic risk score, PRS) and validated them against measured or reported PA in three independent cohorts. We then investigated the associations between polygenic inheritance of PA and cardiometabolic risk factors and diseases in two large population-based biobank datasets, and examined whether selected associations were independent of self-reported PA. Our study utilized the UK Biobank as a base dataset (N = 400,124) and constructed genomewide PRSs for both self-reported and device-measured PA using single nucleotide polymorphism (SNP)-specific weights and SBayesR methodology. Both PRSs for PA included over one million SNPs. PRSs were constructed in the Finnish Twin cohort (N = 759–11,528), the Northern Finland Birth Cohort 1966 (N = 3,263–4,061), the Trøndelag Health Study cohort (HUNT, N = 47,148), and the FinnGen (N = 218,792). Cardiometabolic risk factors were measured in laboratory conditions, and CMD outcomes were derived from national health registers (ICD codes). We utilized linear, logistic, and cox regression methods for analysis. Our results showed that genotypes predisposing to higher PA were associated with higher levels of PA in independent datasets, but PRSs accounted for only a limited amount of variation (0.13-1.44%). Genotypes supporting higher PA were associated with lower body mass index [B=-0.002 in HUNT and B=-0.025 in FinnGen] and favorable cardiometabolic health in HUNT (waist circumference [B=-0.003] and HDL cholesterol [B = 0.004]). Genotypes supporting higher PA volumes were associated with lower incidence of CMDs in both HUNT and FinnGen. The strongest associations were found in hypertensive diseases and Type 2 Diabetes. In HUNT, the observed associations were not materially changed ...