Tsuyoshi Kayo

A Low Dose of Dietary Resveratrol Partially Mimics Caloric Restriction and Retards Aging Parameters in Mice

Resveratrol in high doses has been shown to extend lifespan in some studies in invertebrates and to prevent early mortality in mice fed a high-fat diet. We fed mice from middle age (14-months) to old age (30-months) either a control diet, a low dose of resveratrol (4.9 mg kg−1 day−1), or a calorie restricted (CR) diet and examined genome-wide transcriptional profiles. We report a striking transcriptional overlap of CR and resveratrol in heart, skeletal muscle and brain. Both dietary interventions inhibit gene expression profiles associated with cardiac and skeletal muscle aging, and prevent age-related cardiac dysfunction. Dietary resveratrol also mimics the effects of CR in insulin mediated glucose uptake in muscle. Gene expression profiling suggests that both CR and resveratrol may retard some aspects of aging through alterations in chromatin structure and transcription. Resveratrol, at doses that can be readily achieved in humans, fulfills the definition of a dietary compound that mimics some aspects of CR.

Influences of aging and caloric restriction on the transcriptional profile of skeletal muscle from rhesus monkeys

In laboratory rodents, caloric restriction (CR) retards several age-dependent physiological and biochemical changes in skeletal muscle, including increased steady-state levels of oxidative damage to lipids, DNA, and proteins. We have previously used high-density oligonucleotide arrays to show that CR can prevent or delay most of the major age-related transcriptional alterations in the gastrocnemius muscle of C57BL/6 mice. Here we report the effects of aging and adult-onset CR on the gene expression profile of 7,070 genes in the vastus lateralis muscle from rhesus monkeys. Gene expression analysis of aged rhesus monkeys (mean age of 26 years) was compared with that of young animals (mean age of 8 years). Aging resulted in a selective up-regulation of transcripts involved in inflammation and oxidative stress, and a down-regulation of genes involved in mitochondrial electron transport and oxidative phosphorylation. Middle-aged monkeys (mean age of 20 years) subjected to CR since early adulthood (mean age of 11 years) were studied to determine the gene expression profile induced by CR. CR resulted in an up-regulation of cytoskeletal protein-encoding genes, and also a decrease in the expression of genes involved in mitochondrial bioenergetics. Surprisingly, we did not observe any evidence for an inhibitory effect of adult-onset CR on age-related changes in gene expression. These results indicate that the induction of an oxidative stress-induced transcriptional response may be a common feature of aging in skeletal muscle of rodents and primates, but the extent to which CR modifies these responses may be species-specific.

Gene expression profiling of aging using DNA microarrays.

We have previously employed high density oligonucleotide arrays representing thousands of genes to determine the gene expression profile of the aging process in skeletal muscle (gastrocnemius) and brain (cerebellum and neocortex) of male C57BL/6 mice. Specific gene expression profiles are associated with the aging process of individual organs, and caloric restriction can prevent or retard the establishment of these gene expression alterations. The use of DNA microarrays may provide a new tool to measure biological age on a tissue-specific basis and to evaluate at the molecular level the efficacy of interventions designed to retard the aging process.

Short-term consumption of a resveratrol-containing nutraceutical mixture mimics gene expression of long-term caloric restriction in mouse heart.

An active area of aging research is focused on identifying compounds having the ability to mimic the effects of caloric restriction (CR). From 2 to 5 months of age, we fed male B6C3F(1) mice either a 40% CR diet, a control diet supplemented with a commercially available nutraceutical mixture (NCM) containing resveratrol, quercetin and inositol hexaphosphate, or a diet supplemented with an equivalent dose of chemical-grade resveratrol (RES; 1.25 mg resveratrol kg(-1) day(-1)) from 2 to 5 months of age. Cardiac gene expression profiles were generated for the three groups of treated mice and compared to age-matched control (CO) mice. All three treatments were associated with changes in several cytoskeletal maintenance pathways, suggesting that RES and NCM are able to mimic short-term CR. CR uniquely affected several immune function pathways while RES uniquely affected multiple stress response pathways. Pathway analysis revealed that NCM (but not CR or RES) regulated multiple metabolic pathways that were also changed by long-term CR, including glucose and lipid metabolism, oxidative phosphorylation and chromatin assembly. Examination of key genes and pathways affected by NCM suggests that Foxo1 is a critical upstream mediator of its actions.

Power and sample size estimation in high dimensional biology

Genomic scientists often test thousands of hypotheses in a single experiment. One example is a microarray experiment that seeks to determine differential gene expression among experimental groups. Planning such experiments involves a determination of sample size that will allow meaningful interpretations. Traditional power analysis methods may not be well suited to this task when thousands of hypotheses are tested in a discovery oriented basic research. We introduce the concept of expected discovery rate (EDR) and an approach that combines parametric mixture modelling with parametric bootstrapping to estimate the sample size needed for a desired accuracy of results. While the examples included are derived from microarray studies, the methods, herein, are ‘extraparadigmatic’ in the approach to study design and are applicable to most high dimensional biological situations. Pilot data from three different microarray experiments are used to extrapolate EDR as well as the related false discovery rate at different sample sizes and thresholds.

Effects of caloric restriction on gene expression.

Caloric restriction (CR) retards the aging process in laboratory rodents as characterized by a delayed occurrence or complete prevention of a broad spectrum of age-associated pathophysiological changes and a 30–50% increase in maximum lifespan [1]. The maximum lifespan of fish, rotifers, spiders and other non-mammals is also extended by CR [1]. An active area of research in biological gerontology concerns the mechanisms by which CR retards the aging process. There are five classes of interrelated and non-exclusive explanations for CR’s mechanism: (i) decreases in oxidative stress [2]; (ii) decreases glycation or glycoxidation [3]; (iii) decreases in body temperature and circulating thyroid hormone levels associated with a hypometabolic state [4], (iv) alterations in gene expression and protein degradation [5], and (v) neuroendocrine changes [6]. We have used oligonucleotide microarrays to examine the influences of aging and CR on gene expression and herein review our studies in mice and rhesus monkeys.

Empirical Bayes estimation of gene-specific effects in micro-array research

Micro-array technology allows investigators the opportunity to measure expression levels of thousands of genes simultaneously. However, investigators are also faced with the challenge of simultaneous estimation of gene expression differences for thousands of genes with very small sample sizes. Traditional estimators of differences between treatment means (ordinary least squares estimators or OLS) are not the best estimators if interest is in estimation of gene expression differences for an ensemble of genes. In the case that gene expression differences are regarded as exchangeable samples from a common population, estimators are available that result in much smaller average mean-square error across the population of gene expression difference estimates. We have simulated the application of such an estimator, namely an empirical Bayes (EB) estimator of random effects in a hierarchical linear model (normal-normal). Simulation results revealed mean-square error as low as 0.05 times the mean-square error of OLS estimators (i.e., the difference between treatment means). We applied the analysis to an example dataset as a demonstration of the shrinkage of EB estimators and of the reduction in mean-square error, i.e., increase in precision, associated with EB estimators in this analysis. The method described here is available in software that is available at http://www.soph.uab.edu/ssg.asp?id=1087.