A Study of Metabolite Profiles in Healthy Individuals Across Age Groups
In today's open access paper, researchers report on a study of age-related changes in metabolite profiles in blood, muscle, and urine, with samples taken from healthy members of age groups spanning the 20s to 80s. As might be expected, the results point to many of the usual suspects in aging, such as senescent cell burden and mitochondrial dysfunction.
It is certainly possible to use metabolomic data to construct aging clocks in much the same way as for epigenetic data, and some researchers have done just that in recent years. There are indeed characteristic changes in a range of metabolite levels that appear to reflect biological age, the burden of damage and dysfunction, rather than chronological age.
Human studies make use of biomarker changes in fluids and tissues, such as blood, skeletal muscle, and urine, that occur during the aging process to infer biological changes due to aging per se. These studies are made even more complex by the difficulty in distinguishing between changes compensatory to the emergence of pathology and those that simply reflect aging itself. In addition, findings from studies that investigated age-related changes in the metabolome that occurred in just one compartment, such as plasma or serum, may not necessarily translate to other biological fluids or tissues.
We hypothesized that simultaneously investigating age-related differences in various fluid and tissue compartments may shed more light on the underlying mechanisms that drive changes in the metabolome with age and that ultimately contribute to the phenotypic manifestations of aging. Here, we report the results of a comprehensive profiling of age-related metabolomic changes across three compartments simultaneously: the circulatory system (plasma), the excretory system (urine), and a solid organ (skeletal muscle). To minimize the interference of changes in metabolites reactive to pathology, we enrolled in this study individuals that were healthy based on a comprehensive clinical evaluation performed by trained health professionals. To reduce variability that can result from different quantification methods, the same targeted metabolomic platform was used for all compartments. Herein, we carry out a cross-sectional analysis of 'healthy' individuals who were free from disease to formulate hypotheses based on the metabolic exchanges that occur between different compartments with aging.
Here, we summarize the metabolic pathways that emerged from our analysis of metabolites in plasma, muscle, and urine. These pathways include inflammation and cellular senescence, microbial metabolism, mitochondrial health, sphingolipid metabolism, lysosomal membrane permeabilization, vascular aging, and kidney function. It is important to underline that while these biological mechanisms are far from being a comprehensive list of the biological processes at play over human life spans, they provide insight into some of the basic metabolomic age signatures of cross compartmental, interconnected changes.