Publications by authors named "Zexi Rao"
Background: Biological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in white individuals, and they used proteomic measures from only one-time point. In this study, we created de novo PACs and compared their performance to published PACs at 2 different time points in the Atherosclerosis Risk in Communities (ARIC) study of white and black participants (around 75% white and 25% black).
View Article and Find Full Text PDFArticle Synopsis
- This study aims to create a predictive model for cardiovascular disease (CVD) in breast cancer survivors using diverse data from the All of Us Research Program, focusing on fairness across different demographics.
- The researchers developed a universal data pipeline to integrate various data types, such as electronic health records, patient surveys, and genomic information, and applied models like Adaptive Lasso and Random Forest to predict CVD outcomes over a 10-year span.
- Results show that the Adaptive Lasso model performed well overall, while the Random Forest model was particularly strong for predicting certain events; factors like age and prior heart issues were key predictors, highlighting the importance of social determinants of health in understanding patient outcomes.
Background: We constructed a new proteomic aging clock (PAC) and computed the published Lehallier's PAC to estimate biological age. We tested PACs' associations with mortality in longer-term cancer survivors and cancer-free participants.
Methods: ARIC measured 4,712 proteins using SomaScan in plasma samples collected at multiple visits, including Visit 5 (2011-13), from 806 cancer survivors and 3,699 cancer-free participants (aged 66-90).
Biological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in White individuals, and they used proteomic measures from only one-time point. In the Atherosclerosis Risk in Communities (ARIC) study of about 12,000 persons followed for 30 years (around 75% White, 25% Black), we created de novo PACs and compared their performance to published PACs at two different time points.
View Article and Find Full Text PDF