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Taurine 7 pp 199-206 | Cite as

Functional Implication of Taurine in Aging

  • Abdeslem El Idrissi
  • Latifa Boukarrou
  • Khrystyna Splavnyk
  • Ekaterina Zavyalova
  • Edward F. Meehan
  • William L’Amoreaux
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 643)

Abstract

Age-related impairment of central functions is though to result from alterations of neurochemical indices of synaptic function. These neurochemical modifications involve structural proteins, neurotransmitters, neuropeptides and related receptors. Several studies demonstrated that GABA receptors, glutamic acid decarboxylase (GAD65&67), and different subpopulations of GABAergic neurons are markedly decreased in experimental animal brains during aging. Thus, the age-related decline in cognitive functions could be attributable, at least in part, to decrements in the function of the GABAergic inhibitory neurotransmitter system. In this study we show that chronic supplementation of taurine to aged mice significantly ameliorated the age-dependent decline in memory acquisition and retention, and caused alterations in the GABAergic system. These changes include increased levels of the neurotransmitters GABA and glutamate, increased expression of glutamic acid decarboxylase and the neuropeptide somatostatin and increased in the number of somatostatin-positive neurons. These specific alterations of the inhibitory system caused by taurine treatment oppose those naturally-occurring during aging, and suggest a protective role of taurine in this process.

Increased understanding of age-related neurochemical changes in the GABAergic system will be important in elucidating the underpinnings of the functional changes of aging. Taurine might help forestall the age-related decline in cognitive functions through interaction with the GABAergic system.

Keywords

Aged Mouse Inferior Colliculus GABAergic Neuron Glutamic Acid Decarboxylase Dark Compartment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Abdeslem El Idrissi
    • 1
  • Latifa Boukarrou
  • Khrystyna Splavnyk
  • Ekaterina Zavyalova
  • Edward F. Meehan
  • William L’Amoreaux
  1. 1.Department of BiologyCity University of New York Graduate SchoolNewYork

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