Investigation on cardiovascular risk prediction using genetic information.
Cardiovascular disease (CVD) has become the primary killer worldwide and is expected to cause more deaths in the future. Prediction and prevention of CVD have therefore become important social problems. Many groups have developed prediction models for asymptomatic CVD by classifying its risk based on established risk factors (e.g., age, sex, etc.). More recently, studies have uncovered that many genetic variants are associated with CVD outcomes/traits. If treated as single or multiple risk factors, the genetic information could improve the performance of prediction models as well as promote the development of individually tailored risk models. In this paper, eligible genome-wide association studies for CVD outcomes/traits will be overviewed. Clinical trials on CVD prediction using genetic information will be summarized from overall aspects. As yet, most of the single or multiple genetic markers, which have been evaluated in the follow-up clinical studies, did not significantly improve discrimination of CVD. However, the potential clinical utility of genetic information has been uncovered initially and is expected for further development.
Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China. ln.pu@siat.ac.cn
Li-Na
LN
Pu
Ze
Z
Zhao
Yuan-Ting
YT
Zhang
D000328:Adult; D000368:Aged; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000235:genetics* / Q000503:physiopathology; D005260:Female; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical