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Escape from homeostasis.

Publication ,  Journal Article
Nijhout, HF; Best, J; Reed, MC
Published in: Mathematical biosciences
November 2014

Many physiological systems, from gene networks to biochemistry to whole organism physiology, exhibit homeostatic mechanisms that keep certain variables within a fairly narrow range. Because homeostatic mechanisms buffer traits against environmental and genetic variation they allow the accumulation of cryptic genetic variation. Homeostatic mechanisms are never perfect and can be destabilized by mutations in genes that alter the kinetics of the underlying mechanism. We use mathematical models to study five diverse mechanisms of homeostasis: thermoregulation; maintenance of homocysteine concentration; neural control by a feed forward circuit; the myogenic response in the kidney; and regulation of extracellular dopamine levels in the brain. In all these cases there are homeostatic regions where the trait is relatively insensitive to genetic or environmental variation, flanked by regions where it is sensitive. Moreover, mutations or environmental changes can place an individual closer to the edge of the homeostatic region, thus predisposing that individual to deleterious effects caused by additional mutations or environmental changes. Mutations and environmental variables can also reduce the size of the homeostatic region, thus releasing potentially deleterious cryptic genetic variation. These considerations of mutations, environment, homeostasis, and escape from homeostasis help to explain why the etiology of so many diseases is complex.

Duke Scholars

Published In

Mathematical biosciences

DOI

EISSN

1879-3134

ISSN

0025-5564

Publication Date

November 2014

Volume

257

Start / End Page

104 / 110

Related Subject Headings

  • Models, Biological
  • Humans
  • Homeostasis
  • Genetic Variation
  • Environment
  • Bioinformatics
  • 49 Mathematical sciences
  • 31 Biological sciences
  • 06 Biological Sciences
  • 01 Mathematical Sciences
 

Citation

APA
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ICMJE
MLA
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Nijhout, H. F., Best, J., & Reed, M. C. (2014). Escape from homeostasis. Mathematical Biosciences, 257, 104–110. https://doi.org/10.1016/j.mbs.2014.08.015
Nijhout, H Frederik, Janet Best, and Michael C. Reed. “Escape from homeostasis.Mathematical Biosciences 257 (November 2014): 104–10. https://doi.org/10.1016/j.mbs.2014.08.015.
Nijhout HF, Best J, Reed MC. Escape from homeostasis. Mathematical biosciences. 2014 Nov;257:104–10.
Nijhout, H. Frederik, et al. “Escape from homeostasis.Mathematical Biosciences, vol. 257, Nov. 2014, pp. 104–10. Epmc, doi:10.1016/j.mbs.2014.08.015.
Nijhout HF, Best J, Reed MC. Escape from homeostasis. Mathematical biosciences. 2014 Nov;257:104–110.
Journal cover image

Published In

Mathematical biosciences

DOI

EISSN

1879-3134

ISSN

0025-5564

Publication Date

November 2014

Volume

257

Start / End Page

104 / 110

Related Subject Headings

  • Models, Biological
  • Humans
  • Homeostasis
  • Genetic Variation
  • Environment
  • Bioinformatics
  • 49 Mathematical sciences
  • 31 Biological sciences
  • 06 Biological Sciences
  • 01 Mathematical Sciences