Association between Phenotypic Age and Mortality in Patients with Multivessel Coronary Artery Disease

Author:

Ma Qiong12,Li Bo-Lin12,Yang Lei1,Zhang Miao3,Feng Xin-Xin4,Li Qian1,Liu Hui5,Gao Ya-Jie1,Ma Wen-Zhuo6,Shi Rui-Juan1,Xue Yan-Bo1,Zheng Xiao-Pu1,Gao Ke12ORCID,Mu Jian-Jun1ORCID

Affiliation:

1. Department of Cardiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

2. Key Laboratory of Molecular Cardiology of Shaanxi Province, Xi’an, Shaanxi, China

3. Department of Ultrasound, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

4. Department of Oncology Radiology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

5. Biobank, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

6. Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, College of Pharmacy, Rhode Island, USA

Abstract

Background. Chronological age (CA) is not a perfect proxy for the true biological aging status of the body. A new biological aging measure, phenotypic age (PhenoAge), has been shown to capture morbidity and mortality risk in the general US population and diverse subpopulations. This study was aimed at evaluating the association between PhenoAge and long-term outcome of patients with multivessel coronary artery disease (CAD). Methods. A total of 609 multivessel CAD patients who received PCI attempt and with follow-up were enrolled. The clinical outcome was all-cause mortality on follow-up. PhenoAge was calculated using an equation constructed from CA and 9 clinical biomarkers. Cox proportional hazards regression models and receiver operating characteristic (ROC) curves were performed to evaluate the association between PhenoAge and mortality. Results. Overall, patients with more diseases had older PhenoAge and phenotypic age acceleration (PhenoAgeAccel). After a median follow-up of 33.5 months, those with positive PhenoAgeAccel had a significantly higher incidence of all-cause mortality ( P = 0.001 ). After adjusting for CA, Cox proportional hazards models showed that both PhenoAge and PhenoAgeAccel were significantly associated with all-cause mortality. Even after further adjusting for confounding factors, each 10-year increase in PhenoAge was also associated with a 51% increased mortality risk. ROC curves revealed that PhenoAge, with an area under the curve of 0.705, significantly outperformed CA, the individual clinical chemistry measure, and other risk factors. When reexamining the ROC curves using various combinations of variables, we found that PhenoAge provides additional predictive power to all models. Conclusions. In conclusion, PhenoAge was strongly associated with all-cause mortality even after adjusting for CA. Our findings suggest that PhenoAge measure may be complementary in predicting mortality risk for patients with multivessel CAD.

Funder

Key Project of Research and Development Plan of Shaanxi Province, China

Publisher

Hindawi Limited

Subject

Biochemistry (medical),Clinical Biochemistry,Genetics,Molecular Biology,General Medicine

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