Aging and Genes 4
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Aging and Genes 4

Aging is likely to be the result of the interaction between numerous processes in the body. Due to this complexity, systems biology seems to be an important appraoch to elucidate the aging process.

Many Processes

When a gene is found that influences age, such as the ApoE gene, it is very alluring to think that this one gene could play a decisive role in the aging process. But, previous aging research has taught scientists to be careful with such assertions. The tendency to reduce aging to the result of one single process or system, such as the telomeres, or the antioxidants, for example, does not seem to work and this mentality has actually slowed down aging research. It seems likely that such a singular mechanism that is responsible for aging is not present, and thus will not be found.

Aging is very likely the product of several distinct processes in our body. The gene daf-16 (see Aging and Genes 2), for example, influences thousands of other genes, which, in turn influence several different physiological mechanisms. This, however, does not mean that paying attention to the details of the aging process is not useful, it just means that aging as a whole is likely to be a very complex consequence of a myriad of bodily mechanisms.

Systems Biology

This complex interaction that lies at the root of the aging process is a great example of potential benefits of the relatively new field of systems biology, which attempts to put the known knowledge of all relevant processes into complicated computer models, which can, hopefully, elucidate how these different mechanisms interact, and possibly provide us with ne knowledge about the process as a whole.

Looking for the interactions between all these different mechanisms is very hard (and expensive) to do experimentally, which is why computer models appear to be the better option. The predictions of these models allow researchers to design more appropriate experiments, which have a higher probability of yielding relevant results and, in turn, help in improving future computer models by adding extra knowledge input. This step-by-step process may slowly begin to accumulate in an integrated picture of the complex interactions between numerous physiological mechanisms that contribute to the process of aging.


  • Crimmins, E.; Vasunilashorn, S.; Kim, J.K. & Alley, D. (2008). Biomarkers Related to Aging in Human Populations. Advances in Clinical Chemistry. 46, pp. 161 – 216.
  • Hood, L. (2003). Systems biology: integrating technology, biology and computation. Mechanisms of Aging and Development. 124(1), pp. 9 – 16.
  • Takahashi, Y.; Kuro-o, M. & Ishikawa, F. (2000). Aging Mechanisms. Proceedings of the National Academy of Sciences of the United States of America. 97(23), pp. 12407 – 12408.

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Comments (2)

Another interesting article in the same series......Thanks Vernon for this very informative post

I am enjoying this series very much