Extended Data Fig. 7: Permutation Tests and LASSO Optimized Lambda Values.
From: The secretome of senescent monocytes predicts age-related clinical outcomes in humans
a, Principal-Component Analysis was used to condense the high-impact panel into a composite senescence burden score in the BLSA. Principal Component 1 was used to represent an eigengene for the high-impact panel. With the InCHIANTI cohort ranked from low to moderate to high senescence burden, linear trait trends reveal that positive traits HDL and Walking Pace show a negative trend, while negative traits BMI and CRP show a positive trend. b, Permutation tests comparing the predictive potential is shown for LSPs compared with randomly selected proteins. Linear models for each trait were created either using LSPs or randomly selected proteins of the same size. Models were trained on 80% of the data and used to predict the clinical traits for the remaining 20%. Randomly selected proteins models were trained and tested 100,000 times per trait and compared with the accuracy of the LSP-only model. Red dotted lines show where the Spearman’s correlation of the LSP-only model lies in relation to the bell curve for the randomly selected protein models.
