Fig. 1

Overview of discovery cohort for chemical modifications in urinary proteomics. A Experimental flow chart, schematic representation of analysis of the urinary proteome. Discovery cohorts contained 38 samples from 1 to 81 years, and validation cohorts contained 29 samples from 21 to 72 years. First, we use D open-search to find out modifications of aging signature, next we used refined-search to retrieve these modifications for verification. B Conjectures about the relationship between aging and post-translational modification of proteins. Changes in the structure of some proteins are not only the cause of aging but also the phenomenon accompanying aging, and these changes in the structure of proteins damage their functions and are even harmful to the body, they are excreted in the urine. C Median modification abundance distribution as calculated from MS intensities of quantified sites of each modification. D Intersections between waves of aging global modifications in discovery cohorts. E Venn diagram of significantly changed modifications. The overlap between waves of aging modifications (n=242; p-value<0.05, fold change>2 or <0.5), significance was tested using the t-test. F and G, PCA of total modifications (R:0.994, P:0.001) and PCA of significantly changed modifications (R:1, P:0.001). H Statistics on the number and proportion of various amino acid site modifications (In order to better display the data, Carbamidomethyl [C] and Oxidation [M] were removed because they accounted for almost 60% of the total number of artefacts.) between the three age groups. The abscissa is the ratio of the number of various amino acid modification sites to the sum of the total modifications’ sites identified. The pie chart shows the proportion of the same amino acid modification between different age groups, the detailed content of each part has been placed in the schedule