Plasma proteomics identify novel biomarkers and dynamic patterns of biological aging.

INTRODUCTION: Plasma proteomics examines levels of thousands of proteins and has the potential to identify clinical biomarkers for healthy aging. OBJECTIVES: This large proteomics study aims to identify clinical biomarkers for healthy aging and further explore potential mechanisms involved in aging. METHODS: This study analyzed data from 51,904 UK Biobank participants to explore the association between 2,923 plasma proteins and nine aging-related phenotypes, including PhenoAge, KDM-Biological Age, healthspan, parental lifespan, frailty, and longevity. Protein levels were measured using proteomics, and associations were assessed with a significance threshold of P < 1.90E-06. We utilized the DE-SWAN method to detect and measure the nonlinear alterations in plasma proteome during the process of biological aging. Mendelian randomization was applied to assess causal relationships, and a PheWAS explored the broader health impacts of these proteins. RESULTS: We identified 227 proteins significantly associated with aging (P CONCLUSION: These significant discoveries underscore the importance of monitoring and intervening in the aging process at critical periods, alongside identifying potential biomarkers and therapeutic targets for age-related disorders within the plasma proteomic landscape, thus offering valuable insights into healthy aging.