Frontiers in Aging Neuroscience (Jan 2018)

Ventricular and Periventricular Anomalies in the Aging and Cognitively Impaired Brain

  • Krysti L. Todd,
  • Tessa Brighton,
  • Emily S. Norton,
  • Samuel Schick,
  • Wendy Elkins,
  • Olga Pletnikova,
  • Richard H. Fortinsky,
  • Juan C. Troncoso,
  • Peter J. Molfese,
  • Susan M. Resnick,
  • Joanne C. Conover,
  • for the Alzheimer’s Disease Neuroimaging Initiative

DOI
https://doi.org/10.3389/fnagi.2017.00445
Journal volume & issue
Vol. 9

Abstract

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Ventriculomegaly (expansion of the brain’s fluid-filled ventricles), a condition commonly found in the aging brain, results in areas of gliosis where the ependymal cells are replaced with dense astrocytic patches. Loss of ependymal cells would compromise trans-ependymal bulk flow mechanisms required for clearance of proteins and metabolites from the brain parenchyma. However, little is known about the interplay between age-related ventricle expansion, the decline in ependymal integrity, altered periventricular fluid homeostasis, abnormal protein accumulation and cognitive impairment. In collaboration with the Baltimore Longitudinal Study of Aging (BLSA) and Alzheimer’s Disease Neuroimaging Initiative (ADNI), we analyzed longitudinal structural magnetic resonance imaging (MRI) and subject-matched fluid-attenuated inversion recovery (FLAIR) MRI and periventricular biospecimens to map spatiotemporally the progression of ventricle expansion and associated periventricular edema and loss of transependymal exchange functions in healthy aging individuals and those with varying degrees of cognitive impairment. We found that the trajectory of ventricle expansion and periventricular edema progression correlated with degree of cognitive impairment in both speed and severity, and confirmed that areas of expansion showed ventricle surface gliosis accompanied by edema and periventricular accumulation of protein aggregates, suggesting impaired clearance mechanisms in these regions. These findings reveal pathophysiological outcomes associated with normal brain aging and cognitive impairment, and indicate that a multifactorial analysis is best suited to predict and monitor cognitive decline.

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