Evidence map›Paper›PMID 39227502›Full record

ArticleActa neuropathologica2024

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

Amanda E Denning, Ranjit Ittyerah, Lisa M Levorse, Niyousha Sadeghpour, Chinmayee Athalye, Eunice Chung, Sadhana Ravikumar, Mengjin Dong, Michael Tran Duong, Yue Li and 28 more

Abstract read
In one paragraph

Article in Acta neuropathologica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Review
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  11. Tau burden is best captured by magnitude and extent: Tau-MaX as a measure of global tau.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  12. Article
  13. Review
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  15. Article
  16. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

38 authors.

Amanda E DenningDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA. amanda.denning@pennmedicine.upenn.edu.ORCID 0009-0005-2531-9346
Ranjit IttyerahDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Lisa M LevorseDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Niyousha SadeghpourDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Chinmayee AthalyeDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
Eunice ChungDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Sadhana RavikumarDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Mengjin DongDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Michael Tran DuongDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
Yue LiDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Ademola IlesanmiDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Lasya P SreepadaDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
Philip SabatiniDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
MaKayla LoweDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Alejandra BahenaDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Jamila ZablahDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Barbara E SpencerDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Ryohei WatanabeDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Boram KimDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Maja Højvang SørensenDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Pulkit KhandelwalDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
Christopher BrownDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Stanislau HrybouskiDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Sharon X XieDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
Robin de FloresUMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, INSERM, Caen-Normandie University, GIP Cyceron, Caen, France.
John L RobinsonDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Theresa SchuckDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Daniel T OhmDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Sanaz ArezoumandanDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Sílvia PortaDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
John A DetreDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Ricardo InsaustiHuman Neuroanatomy Lab, University of Castilla La Mancha, Albacete, Spain.
Laura E M WisseDepartment of Clinical Sciences Lund, Lund University, Lund, Sweden.
Sandhitsu R DasDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
David J IrwinDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Edward B LeeDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
David A WolkDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Paul A YushkevichDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.

Funding

Research Education ComponentP30AG072979 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Corey T McMillan · 2021 to 2026
$24.8M
Understanding Environmental Contributions to Heterogeneity in bvFTD.P01AG066597 · NIA · UNIVERSITY OF PENNSYLVANIA · PI David John Irwin, Corey T McMillan · 2020 to 2026
$18.8M
Project IV "Tackling Heterogeneity of Cognitive Trajectory in LBD"U19AG062418 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LEE, VIRGINIA M · 2019 to 2023
$18.1M
Project IV: In Vivo Dissection of Genetic Modifiers on Different Stages of SynucleinopathyP01AG084497 · NIA · UNIVERSITY OF PENNSYLVANIA · PI ALICE S CHEN-PLOTKIN · 2024 to 2026
$15.2M
Ex Vivo Imaging of the Aging Brain to Discover Morphology/Pathology AssociationsR01AG056014 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Paul A. Yushkevich · 2017 to 2026
$4.5M
Characterization of relationship between tau pathology and neurodegeneration in Alzheimer's disease using multimodal imagingR01AG072796 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Sandhitsu Das, DAVID A WOLK · 2022 to 2026
$4.0M
Microscopic and Large-Scale Networks of Molecular Pathology in Frontotemporal Lobar DegenerationR01NS109260 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI IRWIN, DAVID JOHN · 2019 to 2023
$3.8M
A harmonized medial temporal lobe subregion segmentation protocol: an essential element for dementia researchR01AG070592 · NIA · WAYNE STATE UNIVERSITY · PI Ana Marie Daugherty, Rosanna Kathleen Olsen · 2022 to 2026
$3.5M
Biochemical and molecular heterogeneity of human TDP-43 proteinopathies in age-related dementiasR01AG075276 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Silvia Porta Antolinez · 2022 to 2026
$3.0M
Research Training Program in Disease Oriented Neuroscience (R25)R25NS065745 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DETRE, JOHN A · 2009 to 2023
$3.0M
Improving the sensitivity and specificity of MRI-based biomarkers in Alzheimer's diseaseRF1AG069474 · NIA · UNIVERSITY OF PENNSYLVANIA · PI WOLK, DAVID A, YUSHKEVICH, PAUL A. · 2021 to 2021
$2.1M
Ex Vivo Imaging of the Aging Brain to Discover Morphology/Pathology AssociationsRF1AG056014 · NIA · UNIVERSITY OF PENNSYLVANIA · PI YUSHKEVICH, PAUL A. · 2023 to 2023
$2.1M
Alzheimer's Association AACSF-23-1152241Alzheimer's Association AARF-21- 48972NIA NIH HHS P01 AG066597NIA NIH HHS P01 AG084497NIA NIH HHS P30 AG072979NIA NIH HHS R01 AG056014NIA NIH HHS R01 AG069474NIA NIH HHS R01 AG070592NIA NIH HHS R01 AG072796NIA NIH HHS R01 AG075276NIA NIH HHS RF1 AG056014NIA NIH HHS RF1 AG069474NIA NIH HHS T32 AG076411NIA NIH HHS U19 AG062418NINDS NIH HHS R01 NS109260NINDS NIH HHS R01-NS109260NINDS NIH HHS R25 NS065745NINDS NIH HHS R25-NS065745
6 · The paper itself

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.

Indexed as

Alzheimer Diseasetau ProteinsTemporal LobeAgedAged, 80 and overAtrophyDeep LearningDNA-Binding ProteinsFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedDNA-Binding ProteinsMAPT protein, humanTARDBP protein, humantau ProteinsAlzheimer’s diseaseQuantitative neuropathologyTauTDP-43

Identifiers

PMID39227502
PMCPMC11371872

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.