Microarrays as a tool to investigate the biology of aging: a retrospective and a look to the future

The Systems Biology of Single-Cell Aging

Aging is a leading cause of human morbidity and mortality, but efforts to slow or reverse its effects are hampered by an incomplete understanding of its multi-faceted origins. Systems biology, the use of quantitative and computational methods to understand complex biological systems, offers a toolkit well suited to elucidating the root cause of aging. We describe the known components of the aging network and outline innovative techniques that open new avenues of investigation to the aging research community. We propose integration of the systems biology and aging fields, identifying areas of complementarity based on existing and impending technological capabilities.

Systems biology in aging: linking the old and the young

Aging can be defined as a process of progressive decline in the physiological capacity of an organism, manifested by accumulated alteration and destabilization at the whole system level. Systems biology approaches offer a promising new perspective to examine the old problem of aging. We begin this review by introducing the concepts of systems biology, and then illustrate the application of systems biology approaches to aging research, from gene expression profiling to network analysis. We then introduce the network that can be constructed using known lifespan and aging regulators, and conclude with a look forward to the future of systems biology in aging research. In summary, systems biology is not only a young field that may help us understand aging at a higher level, but also an important platform that can link different levels of knowledge on aging, moving us closer to a more comprehensive control of systematic decline during aging.

Genome-wide analysis of yeast aging

In the past several decades the budding yeast Saccharomyces cerevisiae has emerged as a prominent model for aging research. The creation of a single-gene deletion collection covering the majority of open reading frames in the yeast genome and advances in genomic technologies have opened yeast research to genome-scale screens for a variety of phenotypes. A number of screens have been performed looking for genes that modify secondary age-associated phenotypes such as stress resistance or growth rate. More recently, moderate-throughput methods for measuring replicative life span and high-throughput methods for measuring chronological life span have allowed for the first unbiased screens aimed at directly identifying genes involved in determining yeast longevity. In this chapter we discuss large-scale life span studies performed in yeast and their implications for research related to the basic biology of aging.

Age-related behaviors have distinct transcriptional profiles in Caenorhabditis elegans

There has been a great deal of interest in identifying potential biomarkers of aging. Biomarkers of aging would be useful to predict potential vulnerabilities in an individual that may arise well before they are chronologically expected, due to idiosyncratic aging rates that occur between individuals. Prior attempts to identify biomarkers of aging have often relied on the comparisons of long-lived animals to a wild-type control. However, the effect of interventions in model systems that prolong lifespan (such as single gene mutations or caloric restriction) can sometimes be difficult to interpret due to the manipulation itself having multiple unforeseen consequences on physiology, unrelated to aging itself. The search for predictive biomarkers of aging therefore is problematic, and the identification of metrics that can be used to predict either physiological or chronological age would be of great value. One methodology that has been used to identify biomarkers for numerous pathologies is gene expression profiling. Here, we report whole-genome expression profiles of individual wild-type Caenorhabditis elegans covering the entire wild-type nematode lifespan. Individual nematodes were scored for either age-related behavioral phenotypes, or survival, and then subsequently associated with their respective gene expression profiles. This facilitated the identification of transcriptional profiles that were highly associated with either physiological or chronological age. Overall, our approach serves as a paradigm for identifying potential biomarkers of aging in higher organisms that can be repeatedly sampled throughout their lifespan.

Transcriptional (dys)regulation and aging in Caenorhabditis elegans

New work could link laboratory-defined longevity pathways to the process of normal aging.

A circuit of transcription factors has been discovered in Caenorhabditis elegans that could provide a link between laboratory-defined intracellular 'longevity pathways', gene dysregulation and the process of normal aging.

Common aging pathways in worms, flies, mice and humans

Development of functional genomics tools has made it possible to define the aging process by performing genome-wide scans for transcriptional differences between the young and the old. Global screens for age regulation have been performed for worms and flies, as well as many tissues in mice and humans. Recent work has begun to analyze the similarities and differences in transcriptional changes in aging among different species. Most age-related expression changes are specific for a given species, but genes in one pathway (the electron transport chain pathway) show common age regulation in species from worms to humans. Evolutionary theories of aging provide a basis to understand how age regulation of a genetic pathway might be preserved between distantly related species.

Temporal and spatial transcriptional profiles of aging in Drosophila melanogaster

Temporal and tissue-specific alterations in gene expression have profound effects on aging of multicellular organisms. However, much remains unknown about the patterns of molecular changes in different tissues and how different tissues interact with each other during aging. Previous genomic studies on invertebrate aging mostly utilized the whole body or body parts and limited age-points, and failed to address tissue-specific aging. Here we measured genome-wide expression profiles of aging in Drosophila melanogaster for seven tissues representing nervous, muscular, digestive, renal, reproductive, and storage systems at six adult ages. In each tissue, we identified hundreds of age-related genes exhibiting significant changes of transcript levels with age. The age-related genes showed clear tissue-specific patterns: <10% of them in each tissue were in common with any other tissue; <20% of the biological processes enriched with the age-related genes were in common between any two tissues. A significant portion of the age-related genes were those involved in physiological functions regulated by the corresponding tissue. Nevertheless, we identified some overlaps of the age-related functional groups among tissues, suggesting certain common molecular mechanisms that regulate aging in different tissues. This study is one of the first that defined global, temporal, and spatial changes associated with aging from multiple tissues at multiple ages, showing that different tissues age in different patterns in an organism. The spatial and temporal transcriptome data presented in this study provide a basis and a valuable resource for further genetic and genomic investigation of tissue-specific regulation of aging.

Resistance exercise reverses aging in human skeletal muscle

Human aging is associated with skeletal muscle atrophy and functional impairment (sarcopenia). Multiple lines of evidence suggest that mitochondrial dysfunction is a major contributor to sarcopenia. We evaluated whether healthy aging was associated with a transcriptional profile reflecting mitochondrial impairment and whether resistance exercise could reverse this signature to that approximating a younger physiological age. Skeletal muscle biopsies from healthy older (N = 25) and younger (N = 26) adult men and women were compared using gene expression profiling, and a subset of these were related to measurements of muscle strength. 14 of the older adults had muscle samples taken before and after a six-month resistance exercise-training program. Before exercise training, older adults were 59% weaker than younger, but after six months of training in older adults, strength improved significantly (P<0.001) such that they were only 38% lower than young adults. As a consequence of age, we found 596 genes differentially expressed using a false discovery rate cut-off of 5%. Prior to the exercise training, the transcriptome profile showed a dramatic enrichment of genes associated with mitochondrial function with age. However, following exercise training the transcriptional signature of aging was markedly reversed back to that of younger levels for most genes that were affected by both age and exercise. We conclude that healthy older adults show evidence of mitochondrial impairment and muscle weakness, but that this can be partially reversed at the phenotypic level, and substantially reversed at the transcriptome level, following six months of resistance exercise training.

Transcriptome analysis of age-, gender- and diet-associated changes in murine thymus

The loss of thymic function with age may be due to diminished numbers of T-cell progenitors and the loss of critical mediators within the thymic microenvironment. To assess the molecular changes associated with this loss, we examined transcriptomes of progressively aging mouse thymi, of different sexes and on caloric-restricted (CR) vs. ad libitum (AL) diets. Genes involved in various biological and molecular processes including transcriptional regulators, stress response, inflammation and immune function significantly changed during thymic aging. These differences depended on variables such as sex and diet. Interestingly, many changes associated with thymic aging are either muted or almost completely reversed in mice on caloric-restricted diets. These studies provide valuable insight into the molecular mechanisms associated with thymic aging and emphasize the need to account for biological variables such as sex and diet when elucidating the genomic correlates that influence the molecular pathways responsible for thymic involution.

Genome-wide approaches to understanding human ageing

The use of genomic technologies in biogerontology has the potential to greatly enhance our understanding of human ageing. High-throughput screens for alleles correlated with survival in long-lived people have uncovered novel genes involved in age-associated disease. Genome-wide longevity studies in simple eukaryotes are identifying evolutionarily conserved pathways that determine longevity. It is hoped that validation of these 'public' aspects of ageing in mice, along with analyses of variation in candidate human ageing genes, will provide targets for future interventions to slow the ageing process and retard the onset of age-associated pathologies.

Expression profiling in the aging brain: a perspective

To evaluate molecular events associated with the aging process in animal models and human tissues, microarray analysis is performed at the regional and cellular levels to define transcriptional patterns or mosaics that may lead to better understanding of the mechanism(s) that drive senescence. In this review, we outline the experimental and analytical issues associated with high-throughput genomic analyses in aging brain and other tissues for a comprehensive evaluation of the current state of microarray analysis in aging paradigms. Ultimately, the goal of these studies is to apply functional genomics and proteomics approaches to aging research to develop new tools to assess age in cell- and tissue-specific manners in order to develop aging biomarkers for pharmacotherapeutic interventions and disease prevention.

Gene expression and DNA repair in progeroid syndromes and human aging

Human progeroid syndromes are caused by mutations in single genes accelerating some but not all features of normal aging. Most progeroid disorders are linked to defects in genome maintenance, and while it remains unknown if similar processes underlie normal and premature aging, they provide useful models for the study of aging. Altered transcription is speculated to play a causative role in aging, and is involved in the pathology of most if not all progeroid syndromes. Previous studies demonstrate that there is a similar pattern of gene expression changes in primary cells from old and Werner syndrome compared to young suggesting a presence of common cellular aging mechanisms in old and progeria. Here we review the role of transcription in progeroid syndromes and discuss the implications of similar transcription aberrations in normal and premature aging.

Harnessing the power of gene microarrays for the study of brain aging and Alzheimer's disease: statistical reliability and functional correlation

During normal brain aging, numerous alterations develop in the physiology, biochemistry and structure of neurons and glia. Aging changes occur in most brain regions and, in the hippocampus, have been linked to declining cognitive performance in both humans and animals. Age-related changes in hippocampal regions also may be harbingers of more severe decrements to come from neurodegenerative disorders such as Alzheimer's disease (AD). However, unraveling the mechanisms underlying brain aging, AD and impaired function has been difficult because of the complexity of the networks that drive these aging-related changes. Gene microarray technology allows massively parallel analysis of most genes expressed in a tissue, and therefore is an important new research tool that potentially can provide the investigative power needed to address the complexity of brain aging/neurodegenerative processes. However, along with this new analytic power, microarrays bring several major bioinformatics and resource problems that frequently hinder the optimal application of this technology. In particular, microarray analyses generate extremely large and unwieldy data sets and are subject to high false positive and false negative rates. Concerns also have been raised regarding their accuracy and uniformity. Furthermore, microarray analyses can result in long lists of altered genes, most of which may be difficult to evaluate for functional relevance. These and other problems have led to some skepticism regarding the reliability and functional usefulness of microarray data and to a general view that microarray data should be validated by an independent method. Given recent progress, however, we suggest that the major problem for current microarray research is no longer validity of expression measurements, but rather, the reliability of inferences from the data, an issue more appropriately redressed by statistical approaches than by validation with a separate method. If tested using statistically defined criteria for reliability/significance, microarray data do not appear a priori to require more independent validation than data obtained by any other method. In fact, because of added confidence from co-regulation, they may require less. In this article we also discuss our strategy of statistically correlating individual gene expression with biologically important endpoints designed to address the problem of evaluating functional relevance. We also review how work by ourselves and others with this powerful technology is leading to new insights into the complex processes of brain aging and AD, and to novel, more comprehensive models of aging-related brain change.