| Autor: |
Song SY; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing100191, China., Wu ZY; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing100191, China., Sun DJY; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing100191, China., Yu CQ; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing100191, China., Lyu J; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing100191, China State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing100191, China., Li LM; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing100191, China., Pang YJ; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing100191, China. |
| Abstrakt: |
Biological age (BA) is a marker to accurately assess aging, facilitating the prediction of age-related diseases and promoting healthy aging. In recent years, first- and second-generation organ-system-specific BA has been developed using chronological age (CA) or aging-related outcomes (mortality) as training phenotypes and data from questionnaires, physical examinations, clinical biochemistry, imaging, and multi-omics to investigate the specificity of organ systems aging. Here, we review the methodologies for constructing BA, current efforts to assess organ system-specific BA, and related genome-wide association studies (GWAS). Previous studies predominantly used the first-generation BA method, using CA as training phenotypes. Organ-system-specific BA can accurately predict the disease risk of corresponding organ systems. We propose the development of organ system-specific BA through second-generation BA models and conducting GWAS and Mendelian randomization studies to explore organ system-specific aging processes, which will provide a theoretical foundation for the clinical application of organ system-specific BA. |
