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

Lauren Walker, Kirsty E. McAleese, Mary Johnson, Ahmad Khundakar, Daniel Erskine, Alan J. Thomas, Ian G. McKeith, Johannes Attems

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    A tissue microarray (TMA) has previously been developed for use in assessment of neurodegenerative diseases. We investigated the variation of pathology loads in semi-quantitative score categories and how pathology load related to disease progression. Post-mortem tissue from 146 cases were used; Alzheimer’s disease (AD) (n = 36), Lewy body disease (LBD) (n = 56), mixed AD/dementia with Lewy bodies (n = 14) and controls (n = 40). TMA blocks (one per case) were constructed using tissue cores from 15 brain regions including cortical and subcortical regions. TMA tissue sections were stained for hyperphosphorylated tau (HP-T), β amyloid and α-synuclein (αsyn), and quantified using an automated image analysis system. Cases classified as Braak stage VI displayed a wide variation in HP-T pathology in the entorhinal cortex (interquartile range 4.13–44.03%). The interquartile range for β amyloid in frontal cortex in cases classified as Thal phase 5 was 6.75–17.03% and for αsyn in the cingulate in cases classified as McKeith neocortical LBD was 0.04–0.58%. In AD and control cases, HP-T load predicted the Braak stage (p < 0.001), β amyloid load predicted Thal phase (p < 0.001) and αsyn load in LBD cases predicted McKeith 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 the heterogeneity of neurodegenerative diseases. Quantifying pathology in multiple brain regions may allow identification of novel clinico-pathological phenotypes for the improvement of intra vitam stratification of clinical cohorts according to underlying pathologies.

    Original languageEnglish
    Pages (from-to)671-683
    Number of pages13
    JournalJournal of Neural Transmission
    Issue number6
    Early online date6 Mar 2017
    Publication statusPublished - 30 Jun 2017


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