Transcriptome States Reflect Imaging of Aging States

In this study, we describe a morphological biomarker that detects multiple discrete subpopulations (or "age-states") at several chronological ages in a population of nematodes (Caenorhabditis elegans). We determined the frequencies of three healthy adult states and the timing of the transitions between them across the lifespan. We used short-lived and long-lived strains to confirm the general applicability of the state classifier and to monitor state progression. This exploration revealed healthy and unhealthy states, the former being favored in long-lived strains and the latter showing delayed onset. Short-lived strains rapidly transitioned through the putative healthy state. We previously found that age-matched animals in different age-states have distinct transcriptome profiles. We isolated animals at the beginning and end of each identified state and performed microarray analysis (principal component analysis, relative sample to sample distance measurements, and gene set enrichment analysis). In some comparisons, chronologically identical individuals were farther apart than morphologically identical individuals isolated on different days. The age-state biomarker allowed assessment of aging in a novel manner, complementary to chronological age progression. We found hsp70 and some small heat shock protein genes are expressed later in adulthood, consistent with the proteostasis collapse model.