Original title: Biolearn, an open-source library for biomarkers of aging
Authors: Kejun Ying,Seth Paulson,Martin Perez-Guevara,Mehrnoosh Emamifar,Maximiliano Casas Martinez,Dayoon Kwon,Jesse R. Poganik,Mahdi Moqri,Vadim N. Gladyshev
In this article, the authors highlight the importance of identifying and validating biomarkers of aging in order to better understand the aging process and test interventions for longevity. However, clinical validation of these biomarkers has been a challenge due to the lack of cross-population validation, caused by differences in biomarker designs and dataset structures. To address this issue, the authors introduce Biolearn, an open-source library designed to implement and apply aging biomarkers. Biolearn offers a framework for harmonizing existing biomarkers and creating new ones in standardized formats. It also unifies public datasets, making cross-population validation studies simpler. Additionally, Biolearn provides computational methods to evaluate harmonized biomarkers against unified datasets. By offering this community-driven platform, Biolearn improves the development, assessment, and validation of aging biomarkers, thereby enhancing their clinical validation and potential use in clinical trials. The Biolearn package is open-source and can be accessed for free.
Original article: https://www.biorxiv.org/content/10.1101/2023.12.02.569722v1