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Quantitative neuropathology: an update on automated methodologies and implicationsfor large scale cohorts

Lookup NU author(s): Dr Lauren WalkerORCiD, Dr Kirsty McAleese, Mary Johnson, Dr Ahmad Khundakar, Dr Daniel ErskineORCiD, Professor Alan ThomasORCiD, Professor Ian McKeith, Professor Johannes Attems

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

A tissue microarray (TMA) has previously been developed for use in assessment ofneurodegenerative diseases. We investigated the variation of pathology loads in semiquantitativescore categories and how pathology load related to disease progression.Post-mortem tissue from 146 cases were used; Alzheimer's disease (AD) (n=36), Lewybody disease (LBD) (n=56), Mixed AD/dementia with Lewy bodies (n = 14) andcontrols (n=40). TMA blocks (one per case) were constructed using tissue cores from15 brain regions including cortical and subcortical regions. TMA tissue sections werestained for hyperphosphorylated tau (HP-T), β amyloid and α-synuclein (αsyn), andquantified using an automated image analysis system.Cases classified as Braak stage VI displayed a wide variation in HP-T pathology in theentorhinal cortex (interquartile range, 4.13%-44.03%). The interquartile range for βamyloid in frontal cortex in cases classified as Thal phase 5 was 6.75%-17.03% andfor αsyn in the cingulate in cases classified as McKeith neocortical LBD was 0.2%-0.58%. In AD and control cases, HP-T load predicted the Braak stage (p<0.001), βamyloid load predicted Thal phase (p<0.001) and αsyn load in LBD cases predictedMcKeith type of LBD (p<0.001). Quantitative data from TMA assessment highlight the range in pathological load across cases classified with 'severe' pathology and is beneficial to further elucidate theheterogeneity of neurodegenerative diseases. Quantifying pathology in multiple brainregions may allow identification of novel clinico-pathological phenotypes for theimprovement of intra vitam stratification of clinical cohorts according to underlyingpathologies.


Publication metadata

Author(s): Walker L, McAleese KE, Johnson M, Khundakar AA, Erskine D, Thomas AJ, McKeith IG, Attems J

Publication type: Article

Publication status: Published

Journal: Journal of Neural Transmission

Year: 2017

Volume: 124

Issue: 6

Pages: 671-683

Print publication date: 01/06/2017

Online publication date: 06/03/2017

Acceptance date: 24/02/2017

Date deposited: 27/03/2017

ISSN (electronic): 1435-1463

Publisher: Springer

URL: http://dx.doi.org/10.1007/s00702-017-1702-2

DOI: 10.1007/s00702-017-1702-2


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Funding

Funder referenceFunder name
G0400074
MRC

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