Research Paper Volume 10, Issue 10 pp 2973—2990

Figure 2. Principle Component Analysis (PCA) reveals low-dimensional aging trajectory. (A) The graphical representation of the PCA for 5−85-year-old NHANES 2003−2006 participants follows a winding aging trajectory. Samples were plotted in the first three PCs in 3D space along with 2D projections. To simplify the visualization, the PC scores are shown for the age-matched averages for men (squares) and women (diamonds) and color-coded by age. The Roman numerals and corresponding arrows illustrate the approximately linear dynamics of PC scores over sequential stages of human life: I) age<16; II) age 16−35; III) age 35−65; and IV) age >65. (B) Age-dependence of PCA scores along chronological age for NHANES 2003-2006 cohort aged 35+ is shown by age-cohort average values. Human physiological state dynamics has a low intrinsic dimensionality: only the principal component score, PC₁, which corresponds to the largest variance in data, showed a notable correlation with age (Pearson's r = 0.62 for PC₁ and r < 0.2 for other PCs) and therefore could be used as a natural biomarker of age. Shaded regions illustrate the spread corresponding to one standard deviation in each age-matched cohort for PC₁. The inset shows the increase of variance in biological age (PC₁) in the age- and sex-matched cohorts along the chronological age.