TY - JOUR

T1 - Clinical- and omics-based models of subclinical atherosclerosis in healthy Chinese adults: a cross-sectional exploratory study

AU - Valsesia, Armand

AU - Egli, Leonie

AU - Bosco, Nabil

AU - Magkos, Faidon

AU - Kong, Siew Ching

AU - Sun, Lijuan

AU - Goh, Hui Jen

AU - Weiting, Huang

AU - Arigoni, Fabrizio

AU - Leow, Melvin Khee-Shing

AU - Yeo, Khung Keong

AU - Actis-Goretta, Lucas

N1 - © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.

PY - 2021

Y1 - 2021

N2 - Background: Classical risk factors, such as fasting cholesterol, blood pressure (BP), and diabetes status are used today to predict the risk of developing cardiovascular disease (CVD). However, accurate prediction remains limited, particularly in low-risk groups such as women and younger individuals. Growing evidence suggests that biomarker concentrations following consumption of a meal challenge are better and earlier predictors of disease development than biomarker concentrations.Objective: To test the hypothesis that postprandial responses of circulating biomarkers differ between healthy subjects with and without subclinical atherosclerosis (SA) in an Asian population at low risk of coronary artery disease (CAD).Methods: One hundred healthy Chinese subjects (46 women, 54 men) completed the study. Subjects consumed a mixed-meal test and 164 blood biomarkers were analyzed over 6 h by using a combination of chemical and NMR techniques. Models were trained using different methodologies (including logistic regression, elastic net, random forest, sparse partial least square) on a random 75% subset of the data, and their performance was evaluated on the remaining 25%.Results: We found that models based on baseline clinical parameters or fasting biomarkers could not reliably predict SA. By contrast, an omics model based on magnitude and timing of postprandial biomarkers achieved high performance [receiving operating characteristic (ROC) AUC: 91%; 95% CI: 77, 100). Investigation of key features of this model enabled derivation of a considerably simpler model, solely based on postprandial BP and age, with excellent performance (AUC: 91%; 95% CI: 78, 100).Conclusion: We report a novel model to detect SA based on postprandial BP and age in a population of Asian subjects at low risk of CAD. The use of this model in large-scale CVD prevention programs should be explored. This trial was registered at ClinicalTrials.gov as NCT03531879.

AB - Background: Classical risk factors, such as fasting cholesterol, blood pressure (BP), and diabetes status are used today to predict the risk of developing cardiovascular disease (CVD). However, accurate prediction remains limited, particularly in low-risk groups such as women and younger individuals. Growing evidence suggests that biomarker concentrations following consumption of a meal challenge are better and earlier predictors of disease development than biomarker concentrations.Objective: To test the hypothesis that postprandial responses of circulating biomarkers differ between healthy subjects with and without subclinical atherosclerosis (SA) in an Asian population at low risk of coronary artery disease (CAD).Methods: One hundred healthy Chinese subjects (46 women, 54 men) completed the study. Subjects consumed a mixed-meal test and 164 blood biomarkers were analyzed over 6 h by using a combination of chemical and NMR techniques. Models were trained using different methodologies (including logistic regression, elastic net, random forest, sparse partial least square) on a random 75% subset of the data, and their performance was evaluated on the remaining 25%.Results: We found that models based on baseline clinical parameters or fasting biomarkers could not reliably predict SA. By contrast, an omics model based on magnitude and timing of postprandial biomarkers achieved high performance [receiving operating characteristic (ROC) AUC: 91%; 95% CI: 77, 100). Investigation of key features of this model enabled derivation of a considerably simpler model, solely based on postprandial BP and age, with excellent performance (AUC: 91%; 95% CI: 78, 100).Conclusion: We report a novel model to detect SA based on postprandial BP and age in a population of Asian subjects at low risk of CAD. The use of this model in large-scale CVD prevention programs should be explored. This trial was registered at ClinicalTrials.gov as NCT03531879.

KW - Faculty of Science

KW - Cardiovascular disease

KW - Subclinical atherosclerosis

KW - Post-prandial

KW - Blood pressure

KW - Predictive models

U2 - 10.1093/ajcn/nqab269

DO - 10.1093/ajcn/nqab269

M3 - Journal article

C2 - 34476468

VL - 114

SP - 1752

EP - 1762

JO - American Journal of Clinical Nutrition

JF - American Journal of Clinical Nutrition

SN - 0002-9165

IS - 5

ER -