Prediction of biological age by morphological staging of sarcopenia in Caenorhabditis elegans

Abstract

Sarcopenia encompasses a progressive decline in allover muscle quantity and quality. Given its close association with aging, it may represent a valuable healthspan marker. Given the strong commonalities with human muscle structure and the facile visualization possibilities, C. elegans represents an attractive model for studying the relationship between sarcopenia and healthspan. However, classical assessment relies on visual scoring of muscle architecture, which is subjective and inaccurate. To resolve this, we have developed an automated image analysis pipeline for the detailed quantification and classification of muscle integrity in confocal microscopy images from a cohort of aging myosin::GFP reporter strains. We then extracted a variety of morphological descriptors and found a subset to scale linearly with age. This allowed us to establish a general linear model that predicts biological age from a morphological muscle signature. To validate the model, we evaluated muscle architecture in long-lived worms that are known to experience delayed sarcopenia by targeted RNAi-mediated knockdown of the daf-2 gene. We conclude that quantitative microscopy allows for staging sarcopenia in C. elegans and will be of use for systematic screening for pharmacological or genetic modulators that mitigate age-related muscle frailty and thus improve healthspan in C. elegans.