Association of quantitative histopathology measurements with antemortem medial temporal lobe cortical thickness in the Alzheimer’s disease continuum

The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms using deep learning to measure phosphorylated tau (p-tau) and TDP-43 (pTDP-43) pathology, which are both known to accumulate in the MTL and are associated with MTL neurodegeneration. We focus on these pathologies in the context of Alzheimer's disease (AD) and limbic predominant age-related TDP-43 encephalopathy (LATE) and apply our deep learning algorithms to distinct histology sections, on which MTL subregions were digitally annotated. We demonstrate that both quantitative pathology measures show high agreement with expert visual ratings of pathology and discriminate well between pathology stages. In 140 cases with antemortem MR imaging, we compare the association of semi-quantitative and quantitative postmortem measures of these pathologies in the hippocampus with in vivo structural measures of the MTL and its subregions. We find widespread associations of p-tau pathology with MTL subregional structural measures, whereas pTDP-43 pathology had more limited associations with the hippocampus and entorhinal cortex. Quantitative measurements of p-tau pathology resulted in a significantly better model of antemortem structural measures than semi-quantitative ratings and showed strong associations with cortical thickness and volume. By providing a more granular measure of pathology, the quantitative p-tau measures also showed a significant negative association with structure in a severe AD subgroup where semi-quantitative ratings displayed a ceiling effect. Our findings demonstrate the advantages of using quantitative neuropathology to understand the relationship of pathology to structure, particularly for p-tau, and motivate the use of quantitative pathology measurements in future studies.

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Publication Details

Journal
Acta Neuropathologica
Published
2024-09-03
DOI
https://doi.org/10.1007/s00401-024-02789-9
Citations
16
Primary Topic
Alzheimer's disease research and treatments
Type
article
Field-Weighted Citation Impact
5.22

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article

Association of quantitative histopathology measurements with antemortem medial temporal lobe cortical thickness in the Alzheimer’s disease continuum

Alejandra Bahena, Amanda E Denning, Sílvia Porta, Ricardo Insausti et al.
16 citations
Acta Neuropathologica
Alzheimer's disease research and treatments
5.22
article

Association of quantitative histopathology measurements with antemortem medial temporal lobe cortical thickness in the Alzheimer’s disease continuum

Alejandra Bahena, Amanda E Denning, Sílvia Porta, Ricardo Insausti, Ranjit Ittyerah, Daniel T. Ohm, Theresa Schuck, Eunice Chung, Stanislau Hrybouski, Pulkit Khandelwal, Niyousha Sadeghpour, Lasya P Sreepada, David A. Wolk, Ryohei Watanabe, Mengjin Dong, Sharon Xiangwen Xie, Robin de Florès, Sandhitsu R. Das, MaKayla Lowe, Laura E.M. Wisse, John A. Detre, Paul A. Yushkevich, John Robinson, Edward B. Lee, Sanaz Arezoumandan, Boram Kim, Michael Tran Duong, David J. Irwin, Sadhana Ravikumar, Christopher D. Brown, Jamila Zablah, Lisa M Levorse, Chinmayee Athalye, Yue Li, Barbara E. Spencer, Maja Højvang Sørensen, Ademola Ilesanmi, Philip Sabatini
article en
16 citations

Abstract

The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms using deep learning to measure phosphorylated tau (p-tau) and TDP-43 (pTDP-43) pathology, which are both known to accumulate in the MTL and are associated with MTL neurodegeneration. We focus on these pathologies in the context of Alzheimer's disease (AD) and limbic predominant age-related TDP-43 encephalopathy (LATE) and apply our deep learning algorithms to distinct histology sections, on which MTL subregions were digitally annotated. We demonstrate that both quantitative pathology measures show high agreement with expert visual ratings of pathology and discriminate well between pathology stages. In 140 cases with antemortem MR imaging, we compare the association of semi-quantitative and quantitative postmortem measures of these pathologies in the hippocampus with in vivo structural measures of the MTL and its subregions. We find widespread associations of p-tau pathology with MTL subregional structural measures, whereas pTDP-43 pathology had more limited associations with the hippocampus and entorhinal cortex. Quantitative measurements of p-tau pathology resulted in a significantly better model of antemortem structural measures than semi-quantitative ratings and showed strong associations with cortical thickness and volume. By providing a more granular measure of pathology, the quantitative p-tau measures also showed a significant negative association with structure in a severe AD subgroup where semi-quantitative ratings displayed a ceiling effect. Our findings demonstrate the advantages of using quantitative neuropathology to understand the relationship of pathology to structure, particularly for p-tau, and motivate the use of quantitative pathology measurements in future studies.

Acta NeuropathologicaVol. 148(1)
Inserm (FR), Lund University (SE), Normandie Université (FR), Institute for Neurodegenerative Disorders (US), Cyceron (FR), University of Castilla-La Mancha (ES), University of Pennsylvania (US)
Alzheimer's Association, Lunds Universitet, National Institute on Aging, National Institute of Neurological Disorders and Stroke
Reduced inequalities
Openalex Percentile: Top 4%
Alzheimer's disease research and treatments
5.22
DOIOpen Access PDFOpenAlex
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