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定量神经病理学:自动化方法的最新进展及其对大规模队列研究的影响

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

作者信息

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

机构信息

Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK.

出版信息

J Neural Transm (Vienna). 2017 Jun;124(6):671-683. doi: 10.1007/s00702-017-1702-2. Epub 2017 Mar 6.

Abstract

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-), 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- 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- 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.

摘要

先前已开发出一种组织微阵列(TMA)用于评估神经退行性疾病。我们研究了半定量评分类别中病理负荷的变化以及病理负荷与疾病进展的关系。使用了146例病例的尸检组织;阿尔茨海默病(AD)(n = 36)、路易体病(LBD)(n = 56)、AD/路易体混合性痴呆(n = 14)和对照组(n = 40)。TMA块(每个病例一个)由来自15个脑区(包括皮质和皮质下区域)的组织芯构建而成。TMA组织切片用高磷酸化tau蛋白(HP-)、β淀粉样蛋白和α-突触核蛋白(αsyn)进行染色,并使用自动图像分析系统进行定量。分类为Braak VI期的病例在内嗅皮质中HP-病理表现出广泛的变化(四分位间距为4.13 - 44.03%)。分类为Thal 5期的病例额叶皮质中β淀粉样蛋白的四分位间距为6.75 - 17.03%,分类为McKeith新皮质LBD的病例扣带回中αsyn的四分位间距为0.04 - 0.58%。在AD和对照病例中,HP-负荷可预测Braak分期(p < 0.001),β淀粉样蛋白负荷可预测Thal分期(p < 0.001),LBD病例中的αsyn负荷可预测McKeith类型的LBD(p < 0.001)。TMA评估的定量数据突出了分类为“严重”病理的病例中病理负荷的范围,有助于进一步阐明神经退行性疾病的异质性。对多个脑区的病理进行定量分析可能有助于识别新的临床病理表型以改善临床队列根据潜在病理进行的生前分层。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8378/5446847/3d2c3158c281/702_2017_1702_Fig1_HTML.jpg

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