PT  - JOURNAL ARTICLE
AU  - Gabriel Sturm
AU  - Anna S Monzel
AU  - Kalpita R Karan
AU  - Jeremy Michelson
AU  - Sarah A. Ware
AU  - Andres Cardenas
AU  - Jue Lin
AU  - Céline Bris
AU  - Balaji Santhanam
AU  - Michael P Murphy
AU  - Morgan E Levine
AU  - Steve Horvath
AU  - Daniel W Belsky
AU  - Shuang Wang
AU  - Vincent Procaccio
AU  - Brett A. Kaufman
AU  - Michio Hirano
AU  - Martin Picard
TI  - A Multi-Omics and Bioenergetics Longitudinal Aging Dataset in Primary Human Fibroblasts with Mitochondrial Perturbations
AID  - 10.1101/2021.11.12.468448
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.11.12.468448
4099  - http://biorxiv.org/content/early/2021/11/15/2021.11.12.468448.1.short
4100  - http://biorxiv.org/content/early/2021/11/15/2021.11.12.468448.1.full
AB  - Aging is a process of progressive change. In order to develop biological models of aging, longitudinal datasets with high temporal resolution are needed. Here we report a multi-omic longitudinal dataset for cultured primary human fibroblasts measured across their replicative lifespans. Based on the accelerated nature of epigenetic aging in vitro, these longitudinal data are equivalent to ~40 years of follow-up sampling at a frequency of every ~3 years. Fibroblasts were sourced from both healthy donors (n=6) and individuals with lifespan-shortening mitochondrial disease (n=3). The dataset includes cytological (cell size, morphology), bioenergetic (energy expenditure, derived ATP synthesis rates), epigenetic (DNA methylation), gene expression (RNA sequencing), secreted proteins, mitochondrial DNA (mtDNA) copy number and mutations, cell-free DNA, telomere length, and whole-genome sequencing data. This dataset enables the bridging of mechanistic processes of aging as outlined by the “hallmarks of aging”, with the descriptive characterization of aging provided by epigenetic clocks and other metrics. Here we focus on bridging the gap for the hallmark mitochondrial metabolism. Our dataset includes measurement of healthy cells replicating through senescence without intervention, as well as cells subjected to over a dozen experimental manipulations targeting oxidative phosphorylation (OxPhos), glycolysis, and glucocorticoid signaling, among others. These experiments provide opportunities to test how cellular energetics affect the biology of cellular aging. All data are publicly available at our webtool: https://columbia-picard.shinyapps.io/shinyapp-Lifespan_Study/Competing Interest StatementThe authors have declared no competing interest.