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. Author manuscript; available in PMC: 2020 Jun 18.
Published in final edited form as: Nat Med. 2020 Jan 13;26(1):83–90. doi: 10.1038/s41591-019-0719-5

Fig. 1 |. integrative Personal Omics Profiling (iPOP) cohort sampling and data collection for aging analyses.

Fig. 1 |

a, Study design. A total of 106 participants were profiled by multiomic assays at their quarterly healthy visits over the course of up to 48 months. The numbers in green boxes indicate the number of months since enrollment for the quarterly visits. b, Graphical illustration of sample collection, multiomic assays and data generation for participants, including 35 participants who were Ir, 31 participants who were IS and 40 participants with an unclassified insulin status. Data from a total of 624 healthy visits were analyzed. Omic assays included proteomics using sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS), metabolomics using untargeted liquid chromatography mass spectrometry (LC–MS) and transcriptomics and microbial profiling using next-generation sequencing. c, Plot of the collection dates for all participants (left), participant characteristics (middle) and participant age (right). red, Ir; green, IS; dark gray, unknown insulin status; blue, the participant was included in the longitudinal study and was analyzed for personal aging trends (ageotyped); light gray, the participant was not included in the longitudinal cohort owing to insufficient sampling for ageotyping analysis.