Reduction in metabolic noise reveals rejuvenation following transient severe caloric restriction.

Among land vertebrates, the laying hen stands out due to its great reproductive efficiency: producing an egg daily all year long. This production rate makes the laying hen a special model animal to study the general process of reproduction and aging. One unique aspect of hens is their ability to undergo reproductive plasticity and to rejuvenate their reproductive tract during molting, a standard industrial feed restriction protocol for transiently pausing reproduction, followed by improved laying efficiency almost to peak production. Here we use longitudinal metabolomics, immunology, and physiological assays to show that molting promotes reproduction, compresses morbidity, and restores youthfulness when applied to old hens. We identified circulating metabolic biomarkers that quantitatively predict the reproduction and age of individuals. Lastly, we introduce metabolic noise, a robust, unitless, and quantifiable measure for heterogeneity of the complete metabolome as a general marker that can indicate the rate of aging of a population. Indeed, metabolic noise increased with age in control hens, whereas molted hens exhibited reduced noise following molting, indicating systemic rejuvenation. Our results suggest that metabolic noise can be used as a quick and universal proxy for assessing successful aging treatments, accelerating the timeline for drug development.

A decline in avian cytokine expression with age revealed by commercially available cytokine array.

Cytokines are secreted immunomodulators that are key regulators of the avian immune response. Currently, the most commonly used method to follow cytokine expression is qPCR, which measures cellular levels of mRNA, rather their extracellular circulating levels. Here we present a commercially available cytokine array designed to assay circulating expression levels of multiple cytokines and immunomodulators simultaneously. Upon minor modifications to the manufacturer protocol, background noise was reduced, leading to a significant increase in the sensitivity of the device. Our data indicate that the array is reliable and produce consistent data between biological repeats. We tested the reproducibility of the array in a biologically relevant context by assessing age-related changes in circulating cytokines. While individual features did not show a consistent pattern, our data revealed a consistent decline in the median of all cytokine values, supporting the validity of the array in studying biological processes.

Metabolomic Changes Are Predictive of Aging in Laying Hens.

Aging in vertebrates is an extremely complex process that is still poorly understood. One confining factor to studying vertebrate aging is the lack of appropriate models. The laying hen is a good model to study vertebrate aging, as it can be maintained under standard housing conditions, its breeds are genetically well defined and it exhibits significant aging phenotypes at around 18 months of age. Furthermore, laying hens are maintained in a challenging realistic environment and possess a fully functional immune system. Here we used, for the first time, metabolomic profiling of laying hens' blood for identifying biomarkers of aging. Random forest classifier was used to quantify the quality of the markers and found that the markers can predict the correct age group of individuals with 90% accuracy. Animals under time-restricted feeding, a condition known to increase health span, appeared younger under the markers, indicating that the aging biomarkers can also predict the effectiveness of environmental treatments. Additionally, we found that noise, defined as the ratio between the standard deviation and the mean, is an exceptionally robust and universal biomarker of aging, as metabolomic noise increases significantly with age in laying hens, humans, and mice. Our study suggests the laying hen as a useful model to study aging in vertebrates and establishes metabolomic noise as a novel, universal biomarker of aging.