Chiyoko Usui
Research Subjects
Research Interests
Chiyoko Usui has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Hiroki Tabata
Sportology Center Juntendo University Graduate School of Medicine Tokyo Japan
1 shared publication - Isao Muraoka
Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan
1 shared publication - Kaori Ishii
Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan
1 shared publication - Katsuhiko Suzuki
Faculty of Sport Sciences, Waseda University, Tokorozawa 359-1192, Japan
1 shared publication - Koichiro Oka
Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan
1 shared publication - Kumpei Tanisawa
Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan
1 shared publication
Latest Publications
- Open Access
- 15 May 2024
- Published by Wolters Kluwer Health in Medicine & Science in Sports & Exercise
- Vol. 56 (10) , 2026-2038
Polygenic Risk Score, Cardiorespiratory Fitness, and Cardiometabolic Risk Factors: WASEDA’S Health Study
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 (V̇O2peak) per kilogram body weight. Participants were divided into low-, intermediate-, and high-CRF groups according to the tertile V̇O2peak value. Results: Linear regression analysis revealed a significant interaction between PRS for triglyceride (PRSTG) and CRF groups on serum TG levels regardless of the PRS calculation method, and the association between PRSTG and TG levels was attenuated in the high-CRF group. Logistic regression analysis revealed a significant sub-additive interaction between LDpred2 PRSTG 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 V̇O2peak 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.
- 15 May 2024
- Published by Wolters Kluwer Health in Medicine & Science in Sports & Exercise
- Vol. 56 (10) , 2026-2038
Open AccessPolygenic Risk Score, Cardiorespiratory Fitness, and Cardiometabolic Risk Factors: WASEDA’S Health Study
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 (V̇O2peak) per kilogram body weight. Participants were divided into low-, intermediate-, and high-CRF groups according to the tertile V̇O2peak value. Results: Linear regression analysis revealed a significant interaction between PRS for triglyceride (PRSTG) and CRF groups on serum TG levels regardless of the PRS calculation method, and the association between PRSTG and TG levels was attenuated in the high-CRF group. Logistic regression analysis revealed a significant sub-additive interaction between LDpred2 PRSTG 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 V̇O2peak 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.