AmiAge Clock
Biological age reflects the combined influence of genetic, environmental, and lifestyle factors on growth, development, and aging. AmiAge estimates biological age from serum amino-acid profiles using machine-learning models trained across demographically diverse datasets including the Atlas Project and UK Biobank.
Use the AmiAge Clock to enter amino-acid concentrations, estimate AmiAge, view percentile distributions, and receive educational interpretation from the health assistant.
Support
Center for Translational Medicine and Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.
The quickest way of reaching us is by contacting us directly by e-mail: chentianlu@sjtu.edu.cn or dingkeke@sjtu.edu.cn.
We appreciate your questions and feedback.
Latest Update
The health assistant was upgraded with streaming responses and a clearer interpretation prompt.
Support for both 8-amino-acid and 18-amino-acid prediction workflows was refined.
References
[1] AmiAge Clock publication in Nature Communications. Nature Communications article
[2] Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779.
[3] Argentieri MA, Xiao S, Bennett D, Winchester L, Nevado-Holgado AJ, Ghose U, et al. Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations. Nat Med. 2024;30(9):2450-60.