Tomoko Ito

Purpose: This study estimated an individual’s genetic liability to cardiometabolic risk factors by polygenic risk score (PRS) construction and examined whether high cardiorespiratory fitness (CRF) modifies the association between PRS and cardiometabolic risk factors. Methods: This cross-sectional study enrolled 1296 Japanese adults aged ≥40 yr. The PRS for each cardiometabolic trait (blood lipids, glucose, hypertension, and obesity) was calculated using the LDpred2 and clumping and thresholding methods. Participants were divided into low-, intermediate-, and high-PRS groups according to PRS tertiles for each trait. CRF was quantified as peak oxygen uptake (V̇O_2peak) per kilogram body weight. Participants were divided into low-, intermediate-, and high-CRF groups according to the tertile V̇O_2peak value. Results: Linear regression analysis revealed a significant interaction between PRS for triglyceride (PRS_TG) and CRF groups on serum TG levels regardless of the PRS calculation method, and the association between PRS_TG and TG levels was attenuated in the high-CRF group. Logistic regression analysis revealed a significant sub-additive interaction between LDpred2 PRS_TG and CRF on the prevalence of high TG, indicating that high CRF attenuated the genetic predisposition to high TG. Furthermore, a significant sub-additive interaction between PRS for body mass index and CRF on obesity was detected regardless of the PRS calculation method. These significant interaction effects on high TG and obesity were diminished in the sensitivity analysis using V̇O_2peak per kilogram fat-free mass as the CRF index. Effects of PRSs for other cardiometabolic traits were not significantly attenuated in the high-CRF group regardless of PRS calculation methods. Conclusions: The findings of the present study suggest that individuals with high CRF overcome the genetic predisposition to high TG levels and obesity.

Background: Although the negative relationship between cardiorespiratory fitness (CRF) or muscular fitness and diabetes mellitus were respectively observed in many previous studies, there is still a lack of studies that include CRF and muscular fitness simultaneously. Therefore, this study aimed to investigate the relationship between the combination of CRF and muscular fitness and diabetes through a cross-sectional study. Methods: This study was part of WASEDA'S Health Study, a cohort study launched in 2014. We used a part of the baseline data collected for this study. Maximal exercise test using a cycle ergometer and leg extension power (LEP) test were respectively used to evaluate CRF and muscular fitness. Since LEP is affected by body weight, relative LEP (rLEP) which is LEP per body weight, was used as an index of muscular fitness. 796 men (56.5 ± 10.4 years old) who completed a medical examination and fitness tests, were divided into two groups based on CRF and rLEP, respectively. The prevalence of diabetes was collected based on a self-reported questionnaire or blood test. Odds ratios and 95% confidence intervals (CIs) for the prevalence of diabetes were obtained using logistic regression models while adjusting for age, body mass index, exercise habits, family history of diabetes, smoking habits, and drinking habits. Results: 55 (7%) participants had diabetes. Compared to participants with lower CRF or rLEP, the odds ratio (95% CIs) of diabetes in those with higher CRF or rLEP was 0.46 (0.21–0.98) or 0.34 (0.16–0.74), respectively. Furthermore, using the lower CRF and lower rLEP group as the reference, the odds ratio (95% CIs) for the lower CRF and higher rLEP group was 0.32 (0.12–0.88), and higher CRF and higher rLEP group was 0.21 (0.07–0.63), after adjusting for potential confounding factors. Conclusions: CRF and rLEP have independent and joint inverse associations with diabetes prevalence. In addition, participants with high CRF and high rLEP had a lower prevalence of diabetes compared to those with only high CRF or only high rLEP.