Fig. 2: Evaluation of the performance of the proteomics aging clock.
From: Decoding sexually dimorphic proteomic landscapes in the context of aging and mortality
a, b Scatter plots and correlations between ProteAge and CA for the female (R = 0.936, P < 0.001, MAE = 2.225) and male (R = 0.928, P < 0.001, MAE = 2.448) cohorts. c Scatter plots and correlations between KDM BA and CA for females (red, R = 0.904, P < 0.05, MAE = 3.606) and males (blue, R = 0.845, P < 0.05, MAE = 4.169). d Scatter plots and correlations between PhenoAge and CA for females (orange, R = 0.795, P < 0.05, MAE = 7.696) and males (blue, R = 0.822, P < 0.05, MAE = 6.476). Scatter plots and correlations between KDM (R = 0.787, P < 0.001, MAE = 4.714, e)/PhenoAge (R = 0.761, P < 0.001, MAE = 6.371, f) and ProteAge in the male cohort. g, h Scatter plots and correlations between KDM (R = 0.851, P < 0.001, MAE = 3.666, g)/PhenoAge (R = 0.719, P < 0.001, MAE = 7.869, h) and ProteAge in the female cohort. LOESS fitting plots showing the relationship between ProteAge residuals and CA for females (red, i) and males (blue, j). k Bar plot demonstrating the mean absolute error of different aging clock models.
