Literature DB >> 18835409

High-throughput quantification of Alzheimer's disease pathological markers in the post-mortem human brain.

Ursula T E Byrne1, Jacqueline M Ross, Richard L M Faull, Michael Dragunow.   

Abstract

Quantitative analysis of amyloid plaques and neurofibrillary tangles is central to many Alzheimer's disease studies. A novel approach for quantitative immunohistochemistry of plaques and tangles has arisen from the need to account for the heterogeneous expression pattern of these markers in the human brain. This approach aims to overcome the human bias inherent to many sampling strategies, to account for the effects of tissue shrinkage resulting from antigen-retrieval procedures, and to accelerate the analysis of large sample sets by using a high-throughput quantification system. The procedure entailed three coordinated steps: acquisition of montaged images of entire tissue sections, randomised sampling across the cortex, and automated quantification of the selected samples with morphometric image analysis software. Two-dimensional estimates of plaque and tangle densities were obtained from the superior temporal gyrus and middle temporal gyrus of Alzheimer's disease and normal human brains. Results showed a robust correlation between the numbers of plaques and tangles quantified by automated image analysis and those acquired by manual counting. Correction for antigen-retrieval tissue shrinkage ensured that density measurements were not over-estimated. The value and applicability of this assay was demonstrated by the statistically significant differences observed between the averaged densities of plaques and tangles within different investigational groups. We report an accurate and objective approach to the quantification of plaques and tangles in human brain tissue. Implementation of a randomised sampling strategy coupled with a reproducible automated quantification system will facilitate more rigorous comparison of quantitative data derived from different immunohistochemical studies.

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Year:  2008        PMID: 18835409     DOI: 10.1016/j.jneumeth.2008.09.008

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  4 in total

1.  Mosaic aging.

Authors:  Lary C Walker; James G Herndon
Journal:  Med Hypotheses       Date:  2010-01-27       Impact factor: 1.538

2.  Digital pathology and image analysis for robust high-throughput quantitative assessment of Alzheimer disease neuropathologic changes.

Authors:  Janna Hackett Neltner; Erin Lynn Abner; Frederick A Schmitt; Stephanie Kay Denison; Sonya Anderson; Ela Patel; Peter T Nelson
Journal:  J Neuropathol Exp Neurol       Date:  2012-12       Impact factor: 3.685

3.  ℮-conome: an automated tissue counting platform of cone photoreceptors for rodent models of retinitis pigmentosa.

Authors:  Emmanuelle Clérin; Nicolas Wicker; Saddek Mohand-Saïd; Olivier Poch; José-Alain Sahel; Thierry Léveillard
Journal:  BMC Ophthalmol       Date:  2011-12-20       Impact factor: 2.209

4.  Semi-Automated Digital Image Analysis of Pick's Disease and TDP-43 Proteinopathy.

Authors:  David J Irwin; Matthew D Byrne; Corey T McMillan; Felicia Cooper; Steven E Arnold; Edward B Lee; Vivianna M Van Deerlin; Sharon X Xie; Virginia M-Y Lee; Murray Grossman; John Q Trojanowski
Journal:  J Histochem Cytochem       Date:  2015-11-04       Impact factor: 2.479

  4 in total

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