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Discrete Changes in Glucose Metabolism Define Aging.

ABSTRACT: Aging is a physiological process in which multifactorial processes determine a progressive decline. Several alterations contribute to the aging process, including telomere shortening, oxidative stress, deregulated autophagy and epigenetic modifications. In some cases, these alterations are so linked with the aging process that it is possible predict the age of a person on the basis of the modification of one specific pathway, as proposed by Horwath and his aging clock based on DNA methylation. Because the energy metabolism changes are involved in the aging process, in this work, we propose a new aging clock based on the modifications of glucose catabolism. The biochemical analyses were performed on mononuclear cells isolated from peripheral blood, obtained from a healthy population with an age between 5 and 106 years. In particular, we have evaluated the oxidative phosphorylation function and efficiency, the ATP/AMP ratio, the lactate dehydrogenase activity and the malondialdehyde content. Further, based on these biochemical markers, we developed a machine learning-based mathematical model able to predict the age of an individual with a mean absolute error of approximately 9.7 years. This mathematical model represents a new non-invasive tool to evaluate and define the age of individuals and could be used to evaluate the effects of drugs or other treatments on the early aging or the rejuvenation.

SUBMITTER: Ravera S

PROVIDER: S-EPMC6637183 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Discrete Changes in Glucose Metabolism Define Aging.

Ravera Silvia S Podestà Marina M Sabatini Federica F Dagnino Monica M Cilloni Daniela D Fiorini Samuele S Barla Annalisa A Frassoni Francesco F

Scientific reports 20190717 1

Aging is a physiological process in which multifactorial processes determine a progressive decline. Several alterations contribute to the aging process, including telomere shortening, oxidative stress, deregulated autophagy and epigenetic modifications. In some cases, these alterations are so linked with the aging process that it is possible predict the age of a person on the basis of the modification of one specific pathway, as proposed by Horwath and his aging clock based on DNA methylation. B ...[more]

PMID: 31316102

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Project description:BACKGROUND:Exercise promotes metabolic remodeling in the heart, which is associated with physiological cardiac growth; however, it is not known whether or how physical activity-induced changes in cardiac metabolism cause myocardial remodeling. In this study, we tested whether exercise-mediated changes in cardiomyocyte glucose metabolism are important for physiological cardiac growth. METHODS:We used radiometric, immunologic, metabolomic, and biochemical assays to measure changes in myocardial glucose metabolism in mice subjected to acute and chronic treadmill exercise. To assess the relevance of changes in glycolytic activity, we determined how cardiac-specific expression of mutant forms of 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase affect cardiac structure, function, metabolism, and gene programs relevant to cardiac remodeling. Metabolomic and transcriptomic screenings were used to identify metabolic pathways and gene sets regulated by glycolytic activity in the heart. RESULTS:Exercise acutely decreased glucose utilization via glycolysis by modulating circulating substrates and reducing phosphofructokinase activity; however, in the recovered state following exercise adaptation, there was an increase in myocardial phosphofructokinase activity and glycolysis. In mice, cardiac-specific expression of a kinase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase transgene (GlycoLo mice) lowered glycolytic rate and regulated the expression of genes known to promote cardiac growth. Hearts of GlycoLo mice had larger myocytes, enhanced cardiac function, and higher capillary-to-myocyte ratios. Expression of phosphatase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase in the heart (GlycoHi mice) increased glucose utilization and promoted a more pathological form of hypertrophy devoid of transcriptional activation of the physiological cardiac growth program. Modulation of phosphofructokinase activity was sufficient to regulate the glucose-fatty acid cycle in the heart; however, metabolic inflexibility caused by invariantly low or high phosphofructokinase activity caused modest mitochondrial damage. Transcriptomic analyses showed that glycolysis regulates the expression of key genes involved in cardiac metabolism and remodeling. CONCLUSIONS:Exercise-induced decreases in glycolytic activity stimulate physiological cardiac remodeling, and metabolic flexibility is important for maintaining mitochondrial health in the heart.

Project description:Separation of B cells into different subsets has been useful to understand their different functions in various immune scenarios. In some instances, the subsets defined by phenotypic FACS separation are relatively homogeneous and so establishing the functions associated with them is straightforward. Other subsets, such as the "Double negative" (DN, CD19+CD27-IgD-) population, are more complex with reports of differing functionality which could indicate a heterogeneous population. Recent advances in single-cell techniques enable an alternative route to characterize cells based on their transcriptome. To maximize immunological insight, we need to match prior data from phenotype-based studies with the finer granularity of the single-cell transcriptomic signatures. We also need to be able to define meaningful B cell subsets from single cell analyses performed on PBMCs, where the relative paucity of a B cell signature means that defining B cell subsets within the whole is challenging. Here we provide a reference single-cell dataset based on phenotypically sorted B cells and an unbiased procedure to better classify functional B cell subsets in the peripheral blood, particularly useful in establishing a baseline cellular landscape and in extracting significant changes with respect to this baseline from single-cell datasets. We find 10 different clusters of B cells and applied a novel, geometry-inspired, method to RNA velocity estimates in order to evaluate the dynamic transitions between B cell clusters. This indicated the presence of two main developmental branches of memory B cells. A T-independent branch that involves IgM memory cells and two DN subpopulations, culminating in a population thought to be associated with Age related B cells and the extrafollicular response. The other, T-dependent, branch involves a third DN cluster which appears to be a precursor of classical memory cells. In addition, we identify a novel DN4 population, which is IgE rich and closely linked to the classical/precursor memory branch suggesting an IgE specific T-dependent cell population.

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Discrete Changes in Glucose Metabolism Define Aging.

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Discrete Changes in Glucose Metabolism Define Aging.

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