To define the C. elegans aging process at the molecular level, we used DNA microarray experiments to identify a set of 1294 age-regulated genes, and found that the GATA transcription factors ELT-3, ELT-5 and ELT-6 are responsible for age-regulation of a large fraction of these genes. Expression of elt-5 and elt-6 increases during normal aging and both of these GATA factors repress expression of elt-3, which shows a corresponding decrease in expression in old worms. elt-3 regulates a large number of downstream genes that change expression in old age including ugt-9, col-144 and sod-3. elt-5(RNAi) and elt-6(RNAi) worms have extended longevity indicating that elt-3, elt-5 and elt-6 play an important functional role in the aging process. These results identify a novel transcriptional circuit that guides the rapid aging process in C. elegans, and indicates that this circuit is driven by drift of developmental pathways rather than accumulation of damage.
Budovskaya, Y. V., Wu, K., Southworth, L. K., Jiang, M., Tedesco, P., Johnson, T. E., & Kim, S. K. (2008). An elt-3/elt-5/elt-6 GATA transcription circuit guides aging in C. elegans. Cell, 134, 291-303.
Aging is characterized by a plethora of progressive changes to the molecular, cellular and tissue structure of the body. These changes form a network linked by cause-effect relationships that are supported by experimental data. Similarly, existing and proposed interventions in aging modulate those changes and relationships, and again there is experimental evidence supporting their efficacy. My work, and that of the Methuselah Foundation, focuses on a divide-and-conquer, repair-and-maintenance approach to combating aging in which individual therapies address parts of this network and the goal is a panel of interventions that, in unison, is sufficiently comprehensive to confer full-blown rejuvenation. A formal (computable-on) representation of the above evidence would be a highly valuable tool in determining the efficacy of such a panel, identifying possible gaps in it, etc. Accordingly, we are in the early stages of implementing such a knowledge base, and I will present our current design for its structure.
In higher vertebrates, aging is generally characterized by complex changes affecting multiple systems at different (and often overlapping) organizational levels. Amid the apparently chaotic nature of aging, many have sought simple underlying causes. In this talk, I will discuss these different theoretical frameworks devised to explain aging. Drawing from the many genes that have been related to aging in model organisms, one hypothesis is that aging is a genetically-regulated process. It is now necessary, however, to investigate how these genes relate to human biology and how they exert their influence as an aggregate or as a hierarchy to modulate the aging process. I will present our studies of aging-associated protein networks using GenAge (http://genomics.senescence.info/genes/), a database of genes related to aging in humans and model organisms, as well as our work on finding conserved gene expression signatures of aging. While identifying conserved aging genes is important, one striking observation in biogerontology is the variety of aging rates among similar species, such as mammals. In fact, many mechanistic explanations for aging are based on correlations between a given trait and longevity. I will present and discuss our work testing these hypotheses and studying genome evolution to gather new clues about aging. Finally, I will discuss how to integrate these different approaches into new models of aging and to derive testable hypotheses.
de Magalhes, J. P., & Toussaint, O. (2004). GenAge: a genomic and proteomic network map of human ageing. FEBS Letters, 571,243-247.
de Magalhes, J. P., & Church, G. M. (2005). Genomes optimize reproduction: aging as a consequence of the developmental program. Physiology, 20,252-259.
de Magalhes, J. P., & Church, G. M. (2007). Analyses of human-chimpanzee orthologous gene pairs to explore evolutionary hypotheses of aging. Mechanisms of Ageing and Development, 128,355-364.
During normative aging of humans and other mammals, oxidative and inflammatory changes are accumulated progressively throughout the lifespan in most if not all cells and tissues. Long-lived molecules accumulate damage from oxidizing sugars and free radicals. Concurrently, immune system cells show increased inflammatory gene expression, while blood inflammatory proteins tend to be elevated and predict degenerative diseases. I propose that aging processes central to premature aging and shortened longevity are driven by recursive oxidative-inflammatory interactions, such that oxidant damage induces local tissue inflammatory responses, while inflammatory responses cause further by-stander oxidative damage. These mechanisms are revealed by the opposite effects of caloric restriction vs. diabetes-obesity in laboratory and clinical settings for cancer, vascular disease, and Alzheimer disease. A major frontier in prolongevity research is to identify interfaces of local and systemic oxidative and inflammatory processes that are open to homeostatic and pharmacologic manipulation.
Finch, C. E. (2007). The Biology of Human Longevity: Inflammation, Nutrition, and Aging in the Evolution of Lifespans. Amsterdam: Academic Press.
The many observable signs of human senescence have been hypothesized by various researchers to result from several primary causes. Close inspection of the biochemical and physiological pathways associated with age-related changes and with the hypothesized causes reveals several parallel cascades of events that involve multiple interactions and feedback loops. We present a network diagram to aid in conceptualizing the many processes and interactions among them, including promising intervention points for therapy development. This network model includes both intracellular and extracellular processes. It ranges in scale from the molecular to the whole-body level. Symbols are introduced to indicate changes over time and flows of materials. This diagram is maintained on the Web as a reference for researchers and students, with the content updated as new information comes to light.
Furber, J. D. (2008). Network model of systems biology of aging. http://www.LegendaryPharma.com/chartbg.html
Vijg, J., & Campisi, J. (2008). Puzzles, promises and a cure for ageing. Nature, 454, 1065-1071.
The cellular system is very complex, arising from the interaction of many components and processes. Understanding how these processes support the robust maintenance of life is a prominent goal of systems biology, as is producing formal models that are detailed enough to predict how altering the components affects the processes. Achieving this goal requires choosing a modeling framework that can represent biological behavior, creating a parameterized model based on the studied behavior (possibly learned from data), evaluating the model's behavior using extensive computer simulations, and finally validating its predictions through biological experiments. Many engineers within the systems biology movement adapt strategies that have been successful for understanding complex, man-made systems. Since both man-made and natural systems achieve their complexity by combining simple, modular components that have a limited range of capabilities, they should ultimately be bound by the same operational constraints, ensuring that, at the appropriate level of abstraction, engineering approaches should work for both types of system. This talk will illustrate such similarities, along with examples of their application to systems biology and their implications for the study of aging mechanisms.
Different schools of thought, model systems and experimental approaches have generated a comprehensive list of factors characterizing the aging process, which challenges integrative computer modeling. Our approach is focused on deciphering defense mechanisms in human cells in response to cellular aging, which includes the activation of the transcription factor NF-kB (Kriete et al., 2008). Our findings suggest that low-grade inflammation, a hallmark of aging and many age-associated diseases, is a cell-autonomous phenomenon and part of a cellular survival process. We have investigated possible functional mechanisms related to NF-κB activation, using a correlative approach to genomewide expression data (Kriete, 2006). Our experimental work is accompanied by the development of computational models of the aging process, which further elucidate survival and robustness in a multiscale framework (Kriete et al, 2006). We are using computational approaches that allow exploration of semi-quantitative data to integrate a variety of organelle function descriptors, pathways and gene regulation, accompanied by multiscale modeling across scales including tissues and organs. The main purpose is to establish conceptual models and generate new hypotheses suitable for further experimental investigation.
Kriete, A., Mayo, K. L., Yalamanchili, N., Beggs, W., Bender, P., Kari, C., & Rodeck, U. (2008). Cell autonomous expression of inflammatory genes in biologically aged fibroblasts associated with elevated NF-kappaB activity. Immunity & Aging, 5:5.
Kriete, A. (2006). Biomarkers of aging: combinatorial or systems model? Science of Aging Knowledge Environment, pe1.
Kriete, A., Sokhansanj, B. A., Coppock, D. L., West, G. B. (2006). Systems approaches to the networks of aging. Aging Research Reviews, 5, 434-48.
The growing body of results on senescence has made possible a systems biology of aging. However, combining, tracking, and reasoning over these findings poses challenges for both individual researchers and the broader scientific community. In this talk, I describe an interactive, Web-based assistant that we are constructing to address these challenges. This software environment incorporates techniques from artificial intelligence, computational biology, and human-computer interaction to represent existing knowledge about entities and processes involved in aging, let users visualize this knowledge and its implications, and help them reason about hypothetical changes to the processes and identify therapeutic targets. Our approach differs from most earlier work in its interactive character, its reliance on qualitative process-based representations, and its ability to reason over these structures. Our initial knowledge base borrows heavily from Furber's (2008) network diagram of aging, but we expect it to evolve over time as the biological research community begins to use and extend its content.
Bridewell, W., Sanchez, J. N., Langley, P., & Billman, D. (2006). An interactive environment for the modeling and discovery of scientific knowledge. International Journal of Human-Computer Studies, 64, 1099-1114.
We shall discuss three classes of progressive somatic variegation that should be considered in the development of a systems analysis of biological aging. The first is the issue of systematic age-related shifts in population heterogeneity within complex tissues, particularly in mammals, where losses of proliferative homeostasis are widespread. A cogent example is the gradual increase in interstitial fibrosis and the associated loss of parenchyma in multiple tissues. The second is somatic mutation, both nuclear and mitochondrial. These can sometimes reach surprisingly high levels. The third involves stochastic epigenetic changes in gene expression, a phenomenon that is sometimes referred to as epigenetic drift. The latter may well prove to be the dominant explanation for the substantial variations in health span and life span that are universally observed among individual members of a cohort, including those for whom genetic and environmental variables have been tightly controlled. I will argue that such stochastic variations have evolved as a form of group selection.
Martin, G. M. (2005). Epigenetic drift in aging identical twins. Proceedings of the National Academy of Sciences, 102, 10413-10414.
Martin, G. M. (2007). Keynote lecture: The genetics and epigenetics of altered proliferative homeostasis in ageing and cancer. Mechanisms of Ageing and Development, 128, 9-12.
Martin, G. M., Ogburn, C. E., Colgin, L. M., Gown, A. M., Edland, S. D., & Monnat, R. J. (1996). Somatic mutations are frequent and increase with age in human kidney epithelial cells. Human Molecular Genetics, 5, 215-221
Theories for the evolution of aging are based on the recognition that the strength of selection declines with age. This notion lies at the heart of the two classic evolutionary models of aging-mutation accumulation and antagonistic pleiotropy. For the most part, both theoretical and empirical evolutionary biologists have been working with the same two evolutionary theories for the past half-century. I will discuss how more recent ideas about gene interactions and gene networks may provide a new and more predictive theoretical framework to understand the biology of aging. In addition, I will describe ways in which network theory may inform our understanding of age-related morbidity, based on some recent studies in dogs.
Promislow, D. E. L. (2004). Protein networks, pleiotropy and the evolution of senescence. Proceedings of the Royal Society, 271, 1225-1234.
Promislow, D. E. L. (2005). A regulatory network analysis of phenotypic plasticity in yeast. American Naturalist, 165, 515-523.
Proulx, S. R., Nuzhdin, S., & Promislow, D. E. L. (2007). Direct selection on genetic robustness revealed in the yeast transcriptome. PLoS One, 2, e911.
Like many biomedical areas of inquiry, the volume and complexity of data that need to be integrated is complex within the realm of the biology of aging. We have been developing an informatics infrastructure to identify relevant biology of aging knowledge from literature and gene sources, such as PubMed and GenBank. Working with collaborators, we are beginning to harness natural language processing techniques to identify semantic relationships that may be of relevance to the biology of aging. Even with the limited volume of data collected, we have created interactive Web-based interfaces that enable one to browse through the semantic space of the biology of aging, anchoring one according to longevity data, geo-location, and gene annotation. This presentation will provide an overview of the underpinning technologies working towards a conclusion that includes a demonstration of the current interfaces that enable one to browse through the knowledge space of the biology of aging.
Older individuals who present with cancer have increased metastasis, and this could be due to factors such as decreased immunity, or changes in the microenvironment. Metastasis is dependent on the coordinated regulation of a number of genes. We have previously shown that one of these genes, Wnt5A, a non-canonical member of the Wnt signaling pathway, is associated with increased aggressiveness, and plays a critical role in melanoma metastasis and escape from immune surveillance. Using melanoma cells and both young and old normal skin fibroblasts as a model, we are trying to unravel just what these changes may be, and how they affect tumor progression. We are currently using gene expression profiling analysis in conjunction with cellular analyses to determine if co-culturing melanoma cells with young vs. old fibroblasts has differing effects on their metastatic ability. We are inducing senescence in young fibroblasts to determine if senescing fibroblasts make melanoma cells more invasive. We are also asking if oncogene-induced senescence in tumor cells can influence surrounding cells in a co-culture system, make them senesce and in turn, release factors that then cause tumor cells to invade. Our current analyses implicate chemokines and Wnts, as well as aging-associated genes such as Klotho.
Dissanayake, S. K. et al. (2007). The Wnt5A/protein kinase C pathway mediates motility in melanoma cells via the inhibition of metastasis suppressors and initiation of an epithelial to mesenchymal transition. Journal of Biological Chemistry, 282, 17259-17271.
Weeraratna, A. T. (2005). A Wnt-er Wonderland - The complexity of Wnt signaling in melanoma. Cancer and Metastasis Review, 24, 237-50.