Gorski – Expectations in the Application of Systems Biology to the Study of Aging
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Abstract— The progress in the study of aging, resulting from technological advances of the human genome project, is occurring at a rapid pace. As one of the hardest problems facing biologists and geneticists, there is now hope that an effective solution to stop individual aging can be found. Current biological theories focus on genetic or biochemical effects, however, fail to study all the multifaceted processes in aging at the same time. It is proposed in this article that systems biology can provide a solution uniquely suited for the complexity of aging. This can be accomplished by using a model of aging based on the many mechanisms of aging within an organism, rather than merely the action of aging on cells. Hopefully in the future, the application of systems biology to the study of aging can offer insight into the interrelating mechanisms of aging resulting in effective treatment and prevention.
Index Terms—Biological aging, genetics of aging, model organisms, systems biology.
I.
I NTRODUCTION
T HE advance of the human genome project has resulted in many biological advances; of these the progress in the study of aging is most exciting. Aging is one of the hardest problems in biology and to date there are no effect restorative therapies [1]. Current medical practices only alleviate the ailments or consequences of aging, such as heart disease or cancer. These practices merely forestall death, with little effect on the aging process itself.
There is great hope that systems biology, with its use of high throughput technology and models [2], will be able to study all the complex processes of aging simultaneously
[3]. Modes of action of mutations that prolong life could, therefore, be simultaneously incorporated into complex
Manuscript received October 21, 2001. This work was supported in part by an Ontario Graduate Scholarship.
Susan M. Gorski is with the Institute of Biomaterials and Biomedical
Engineering at the University of Toronto (phone: 416-429-0830; email: susan.gorski@utoronto.ca). models, illustrating and hopefully predicting aging in an individual. Even so, researchers have not yet formally incorporated the process of systems biology in aging research. In fact, the study of aging is perched on the edge of systems biology. When the study of aging takes the plunge into systems biology, scientists predict its advantageous techniques will unlock the mysteries of aging
[1], [3]-[6].
II.
W HAT IS A GING ?
Before demonstrating the advantages of systems biology in the study of aging, the question of what aging is must be addressed first.
Most people in OECD countries will suffer from mortality and morbidity related to aging [1], however, there is common confusion between the aging process itself and its effects, causing disease or death. Aging is a process “that converts health adults into frail ones, with diminished reserves in most physiological systems and an exponentially increasing vulnerability to most diseases and to death” [5]. Aging takes place between middle and old age, not earlier in life, birth to maturation. From an evolutionary standpoint, before adulthood the force of natural selection usually regulates a population [1]. After adulthood, aging is the contributing cause of death. This being said, it is very difficult to identify aging in an individual, rather than a population, however, it would be of more use to applications in treatment and prevention of aging. A decrease in physiological reserves and increasing vulnerability to disease are typical outcomes observed in the changing chemistry and biology of aging individuals.
These transformations result in the view that aging is in fact a disorder of homeostasis [7]. How to prevent or treat aging is the current focus of study.
III.
C URRENT T HEORIES AND T HEIR F AILURE TO
C OMPREHENSIVELY E XPLAIN A GING
There has been a failure to find simple controls of aging in the 20 th century [1]. Indeed all current biological theories of aging cannot describe aging as an organismal function. Further, while genetic and biochemical work can identify changes in aged tissue, theories only speculate on
1

Gorski – Expectations in the Application of Systems Biology to the Study of Aging
TABLE I
B IOLOGICAL T HEORIES OF A GING a
Programmed theories of aging
The neuroendocrine theory
The immune theory
The cellular senescence theory
The stem cell theory
Wear and tear theories of aging
The free radical theory
The DNA damage theory
2 immune cells, such as T-cells, B-cells, macrophages and dendritic cells, deteriorate with age [3]. Altered T-cells cause a greater susceptibility to infection and B-cells cause autoimmune disease [5]. Although there is a link between immunity and age, declining immunity is perhaps a result of aging rather than a cause of it. Organisms with poor a
Adapted from [5]. the cause and effect of these changes [8]. The most popular immune systems still age, suggesting that a lesser participation of the immune system does not affect the aging process. Thus, the immune theory does not comprehensively explain aging.
The cellular senescence theory suggests that aging of the whole organism is built into regulators in the cells current biological theories are divided into programmed theories and wear and tear theories, as illustrated by Table
1.
A.
Programmed Theories
The intrinsic theories of aging suggest that aging is a themselves. It is acknowledged that cells, such as fibroblasts, can only divide a finite number of times [5].
The intrinsic limit of the dividing cells in turn regulates the maximal lifespan by causing tissue, organ and then organ system death. In fact, the number of times a cell can divide is linked to the age of the donor [5]. The stem cell depletion theory mirrors the cellular senescence theory by proposing that aging is dependent on the body’s ability to result of evolutionary, genetically programmed internal changes [7]. This innate genetic program or a “primary clock” in turn determines the maximal lifespan and the rate of aging [5]. These theories are firmly grounded on the evidence that maximal lifespan of a species is relatively fixed so that lifespan is a phenotypical trait. Indeed, twin replenish cells [7]. An inability of this causes death in a hieratical manner, through cell death to system death. The stem cell depletion theory, however, attributes the inability to replace cells of the body to the depletion of a stem cell pool in both quality and quantity. Indeed stem cell therapies can increase longevity and the depletion of stem studies in humans have shown that maximal lifespan is genetically regulated [5]. As well, the predictable acceleration in mortality rates during adulthood suggests a cells has been linked to diseases of aging, such as diabetes or cataracts [7]. Both theories, however, cannot account for aging in non-dividing cells, such as brain cells [5]. programmed process [1].
B.
Wear and Tear Theories Genes have long been used as an explanation of the rate of aging. Genes are known to predispose an individual to disease. For example, a woman with a defect copy of the
BRCA1 gene has a 70% chance of getting breast cancer by the time she is 60 years of age [3]. Expanding this theory to aging, a single mutation of a gene can result in premature aging syndrome in humans [5]. For this reason, genes or an individual’s innate resistance to forms of stress are suggested as the reason for a programmed rate of aging.
The neuroendocrine theory suggests that the programmed aging response of an individual is due to regulation of the neuroendocrine system [5]. This system is important for homeostasis, as well as response to stress.
However, like the decline in these functions in elderly people, major hormones of the endocrine system are also
Unlike programmed theories of biological aging, with their predetermined blueprints, “wear and tear” or extrinsic theories propose that aging is a result of random events or a random “stochastic” process [5]. An organism is subject to continuous stresses, such as oxidation, which can cause an accumulation of molecular and biochemical changes producing cellular damage to key cellular components, such as DNA, proteins and lipids [7]. Resistance or efficient repair of the chronic accumulation of chemical modifications to structural or functional components of the cells results in the longevity of an individual [9]. These theories are supported by knowledge of metabolism rates.
A decrease in metabolism rate or in core temperature has been shown to increase lifespan of Drosophila known to diminish with age. Estrogen amounts decrease in post-menopausal women, testosterone in men (andropause) and growth hormone and insulin like growth factor I (IGF
I) with both sexes [5]. However, even though these changes are well documented, it is not clear what effect hormones have on the aging process. For example, hormone replacement theories are not known to directly increase lifespan.
In the immune theory, it is proposed that the immune system regulates aging. The number and function of the melanogaster and Caenorhabditis elegans (fruit flies and nematode worms) [6]. Caloric restriction in rodents and yeast also increases longevity [4]. Furthermore, sleep is known to have a restorative role that could be linked to a decrease in metabolism and extension of life properties [6].
One of the popular theories of aging is the free radical theory [5]. It hypothesizes that free radicals in the body cause oxidation. Increased oxidative damage is noted with age in proteins, DNA and lipids. The free radicals can

Gorski – Expectations in the Application of Systems Biology to the Study of Aging 3
Fig. 1.
Unified theory of aging. Solid boxes indicate the mechanisms proposed by the wear and tear theory of aging and dashed boxes indicate programmed theory mechanisms. [5] come from external sources, like ionizing radiation or pollutants, or internal cellular reactions, such as oxidative phosphorylation in the mitochondria [5]. Oxidation, or the
Maillard reaction, chronically damages the cellular components of an organism, altering cellular function and tissue and organ function, resulting in a limited lifespan
[9]. Indeed, fruit flies genetically engineered to have high antioxidant defenses live longer [5]. Further, the free radical theory suggests that a higher metabolic rate results in more free radicals, explaining the shortened lifespan observed. Higher caloric intake also results in more free radicals, again suggesting free radicals are to blame for increased rates of aging. The differences in aging between individuals are explained as a difference in the ability of an individual to resist free radical damage.
Another theory, the DNA damage theory, suggests that free radical damage to DNA exclusively cases aging
[5]. Damage to the DNA, in strand breaks, covalent modifications and chromosomal rearrangements, results in a gradual lose of integrity of the genome [9]. A decrease in the efficiency of the repair of DNA causes the accumulated mutations. Altered cells affect tissues, organs, organ systems and finally the entire organism, resulting in aging
[5].
Wear and tear theories, however, fail to account for the known effects of genes on maximal lifespan.
C.
United Theories
The obvious next step in attempting to explain aging is a combined theory incorporating both programming and wear and tear concepts. One proposed theory suggests that oxidation, from free radicals generated by cellular metabolism or environmental sources, damages the cells of the body. At the same time the ability of the body to cope with this stress is regulated by repair systems, which differ between individuals by genetics [5]. Together the two determine the rate of aging in an individual. This theory is illustrated in Figure 1.
Even so, there is linear thinking in all of the theories proposed, including the united theory. With the goal of curing aging, there is more promise in the systems study of an organism than in an isolated process as described in both the programmed and wear and tear theories. Indeed, linear thinking may be a limiting factor to the progression of aging research [4]. If aging is in reality a highly interactive process, as current research would suggest, a wider, more complex model needs to be developed.
Systems biology can give aging research the organization to achieve a comprehensive and complete model of the causes and cures of individual aging.
IV.
A PPLICATION OF S YSTEMS
A GING
B IOLOGY IN THE S TUDY OF
Systems biology is organized into discrete steps [2],
[3], [10], the first of which is to formulate a simple model.
The current studies and theories of aging could easily be used to formulate a simple model. As discussed, descriptive theories exist, and without doubt could be expanded into graphical or mathematical models or developed into computer models.
The advances in high throughput technologies facilitate the next step of systems biology; defining all the components of the system. The improvements of genetic discovery technology with the human genome project have allowed thousands of genes to be identified in relatively

Gorski – Expectations in the Application of Systems Biology to the Study of Aging short periods of time. This allows genetic variability to be
4 model should be able to fully explain and predict the studied in an aging perspective. These technologies causes and indicators of aging. include the automated DNA sequencer, simultaneous sequencing or DNA array technology, photolithography to
Although current work is centered on stages to generate a preliminary model, it is clear that this method synthesize oligonucleotide arrays and high speed sorting
[3]. These technologies generate expression profiles and extensive gene disruption data from model organisms [10].
However, two barriers stop scientists from identifying all the components of an aging system: differences between humans and these model organisms and the complexity of the mechanisms involved in aging. could be useful to refine generated models. Further, with readily available technologies, like knockout mutagensis, coupled with high throughput analyses of the resulting effects, these steps can also be easily integrated.
Systems biology clearly can be advantageous to the study of aging, not only in understanding the currently known processes, but also by providing insight their interactions and by predicating new processes. Studies of model organisms used in aging studies to date have centered on D. melanogaster and C. elegans , as both are easily handled and can be bred in large numbers
[8]. While many genes are similar between these organisms and humans, by no means all are, resulting in different cellular mechanisms. Indeed fruit flies and nematode worms have simpler circulatory systems, immune responses, cognitive abilities and skeletal organization. Further, humans often have two or more copies of genes, whereas the fly or worm would only have one [8]. It is unethical to experiment on humans, not to mention inefficient for aging study with the long human lifespan. Therefore to effectively identify all components of cellular and molecular mechanisms of human aging, differences between the model organisms and humans must be resolved. Perhaps voluntary, noninvasive experiments, such as sequencing genes in blood, could be one method of achieving an applicable human model.
V.
C ONCLUSION
Linear thinking could be disastrous when applied to a potentially complex biological problem, such as aging.
Systems biology could provide the key solution to this problem by simultaneously incorporating all modes of action into a comprehensive computer model. This points to promise in the future of medical intervention, not only in the treatment of aging, but, more excitingly, in the prevention to some degree of aging not only in a population, but also in an individual.
It should be noted however, that there is a potential that pinpointing a limiting factor for aging, although possible for a population, such as caloric restriction, might be impossible for an individual. Indeed, for an individual, barring disease, aging might be the biogerontologic equivalent of the uncertainty principle [4].
The mechanisms of aging are extremely complex.
Model organisms actually help in this regard, by simplifying processes for better comprehension [6]. Even so, geneticists have estimated that around 14,000 genes are involved in D. melanogaster aging [1]. In a complex organism like a human this translates into to a huge number of interactions, which could possibly contribute to aging. While a problem in identifying all components of a linear aging model, this complexity indicates the usefulness of a systems biology approach. Where linear understanding of the mechanisms of aging may not lead to total comprehension of processes, a computer simulation may be able to predict aging.
The next steps in systems biology would be to work with and refine the generated theoretical model [2], [3],
[10]. The model is perturbed by the removal of part of the system and relationships of the elements in the perturbed and normal systems. The model is tested against experimental data of genetic and biochemical tests, such as knockout mutagensis or surgical oblation [1]. These data are integrated and compared for reformulation of the model. These steps are then continued until the model and experimental data match. At this point a comprehensive
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