A mathematical model of aging-related and cortisol induced hippocampal dysfunction

McAuley, Mark T; Kenny, Rose Anne; Kirkwood, Thomas BL; Wilkinson, Darren J; Jones, Janette JL; Miller, Veronica M

Abstract

Background

The hippocampus is essential for declarative memory synthesis and is a core pathological substrate for Alzheimer's disease (AD), the most common aging-related dementing disease. Acute increases in plasma cortisol are associated with transient hippocampal inhibition and retrograde amnesia, while chronic cortisol elevation is associated with hippocampal atrophy. Thus, cortisol levels could be monitored and managed in older people, to decrease their risk of AD type hippocampal dysfunction. We generated an in silicomodel of the chronic effects of elevated plasma cortisol on hippocampal activity and atrophy, using the systems biology mark-up language (SBML). We further challenged the model with biologically based interventions to ascertain if cortisol associated hippocampal dysfunction could be abrogated.
Results

The in silicoSBML model reflected the in vivoaging of the hippocampus and increased plasma cortisol and negative feedback to the hypothalamic pituitary axis. Aging induced a 12% decrease in hippocampus activity (HA), increased to 30% by acute and 40% by chronic elevations in cortisol. The biological intervention attenuated the cortisol associated decrease in HA by 2% in the acute cortisol simulation and by 8% in the chronic simulation.
Conclusion

Both acute and chronic elevations in cortisol secretion increased aging-associated hippocampal atrophy and a loss of HA in the model. We suggest that this first SMBL model, in tandem with in vitroand in vivostudies, may provide a backbone to further frame computational cortisol and brain aging models, which may help predict aging-related brain changes in vulnerable older people.

• Journal Article Type: Article
• Online Publication Date: Mar 25, 2009
• Publication Date: 2009-12
• Deposit Date: Feb 19, 2025
• Publicly Available Date: Feb 24, 2025
• Journal: BMC Neuroscience
• Electronic ISSN: 1471-2202
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 1
• DOI: https://doi.org/10.1186/1471-2202-10-26