Age-related sympathetic ganglionic neuropathology: Human pathology and animal models

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Abstract

Systematic studies of the autonomic nervous system of human subjects and development of well-defined animal models have begun to substantially improve our understanding of the pathogenesis of autonomic dysfunction in aging and may eventually provide strategies for intervention. Neuropathological studies of the sympathetic ganglia of aged human subjects and rodent models have demonstrated that neuroaxonal dystrophy involving intraganglionic terminal axons and synapses is a robust, unequivocal and consistent neuropathological finding in the aged sympathetic nervous system of man and animals. Quantitative studies have demonstrated that markedly swollen argyrophilic dystrophic axon terminals develop in the prevertebral superior mesenteric (SMG) and coeliac, but to a much lesser degree in the superior cervical ganglia (SCG) as a function of age, sex (males more than females) and diabetes. Dystrophic axons were immunoreactive for neuropeptide Y, tyrosine hydroxylase, dopamine-β-hydroxylase, trkA and p75NTR, an immunophenotype consistent with their origin from postganglionic sympathetic neurons, and contained large numbers of highly phosphorylated neurofilaments or tubulovesicular elements. The sympathetic ganglia of aged rodents also showed the hallmark changes of neuroaxonal dystrophy as a function of age and location (many more in the SMG than in the SCG). Plasticity-related synaptic remodeling could represent a highly vulnerable target of the aging process. The fidelity of animal models to the neuropathology of aged humans suggests that similar pathogenetic mechanisms may be involved in both and that therapeutic advances in animal studies may have human application.

Original languageEnglish
Pages (from-to)63-72
Number of pages10
JournalAutonomic Neuroscience: Basic and Clinical
Volume96
Issue number1
DOIs
StatePublished - Feb 28 2002

Keywords

  • Animal model
  • Human pathology
  • Sympathetic ganglionic neuropathology

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