Abstract Background Cardiorespiratory fitness (CRF) has a strong genetic component estimated to be up to 60%. Further, CRF is a major risk factor for cardiovascular morbidity and mortality. However, the specific genetic architecture of CRF and how this relates to cardiovascular disease (CVD) risk is poorly understood. There is a clinical need for improved risk prediction accuracy as many patients free from traditional risk factors still experience different CVDs. Aim To develop and validate a polygenic score (PGS) for CRF (CRFPGS) and assess its associations with CVD. Methods The Bayesian approach PRS-CS was applied to construct a genome-wide PGS for CRF. Genetic effect estimates from a genome-wide association study on directly measured V̇O2peak in the Trøndelag Health Study (HUNT; n = 4 525) was used as the base data and an independent cohort from the UK Biobank (n = 65 674) with estimated CRF from a submaximal bicycle test was used as the tuning cohort. The top performing score was identified and applied in the independent target cohort in HUNT (n = 82 109) with estimated CRF (eCRF) from clinical measurements, to test for associations with different CVD outcomes. Results The correlation between the CRFPGS and the CRF measurements varied between the cohorts and accuracy of the phenotype. There was a clinically meaningful difference of 1.5 mL·kg-1·min-1 in the eCRF between the bottom and top decile of the CRFPGS. Moreover, the CRFPGS demonstrated cardioprotective effects, where a high CRFPGS was associated with reduced risk for all-cause mortality, CVD, myocardial infarction, hypertension, heart failure, and hypertrophic cardiomyopathy. When considering women and men separately, the association between the CRFPGS and risk of heart failure and hypertrophic cardiomyopathy disappeared in men, suggesting sex-specific effects. The CRFPGS appeared to be more suited to identify individuals with a genetic susceptibility to slightly higher lifelong levels of CRF, in part driven by lower BMI, rather than individuals with a potential for supraphysiological levels. Conclusion We developed the first PGS for CRF using gold standard phenotypes as the base data and independent tuning and validation cohorts. A genetic susceptibility to a high CRF had a clinically meaningful impact on the phenotype and associated disease risk. The CRFPGS was better to identify individuals with slightly higher lifelong levels of CRF which seems to protect against cardiovascular morbidity and mortality. These results suggest that a CRFPGS could be used in clinic to identify individuals with excessive genetic risk for different CVDs in the future.
Klevjer et al. (Sat,) studied this question.