Dataset Information

Three-dimensional histology reveals dissociable human hippocampal long axis gradients of Alzheimer's pathology.

ABSTRACT:

Introduction

Three-dimensional (3D) histology analyses are essential to overcome sampling variability and understand pathological differences beyond the dissection axis. We present Path2MR, the first pipeline allowing 3D reconstruction of sparse human histology without an MRI reference. We implemented Path2MR with post-mortem hippocampal sections to explore pathology gradients in Alzheimer's Disease.

Methods

Blockface photographs of brain hemisphere slices are used for 3D reconstruction, from which an MRI-like image is generated using machine learning. Histology sections are aligned to the reconstructed hemisphere and subsequently to an atlas in standard space.

Results

Path2MR successfully registered histological sections to their anatomical position along the hippocampal longitudinal axis. Combined with histopathology quantification, we found an expected peak of tau pathology at the anterior end of the hippocampus, while amyloid-β displayed a quadratic anterior-posterior distribution.

Conclusion

Path2MR, which enables 3D histology using any brain bank dataset, revealed significant differences along the hippocampus between tau and amyloid-β.

SUBMITTER: Ortega-Cruz D

PROVIDER: S-EPMC10723286 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Three-dimensional histology reveals dissociable human hippocampal long axis gradients of Alzheimer's pathology.

Ortega-Cruz Diana D Bress Kimberly S KS Gazula Harshvardhan H Rabano Alberto A Iglesias Juan Eugenio JE Strange Bryan A BA

bioRxiv : the preprint server for biology 20231207

<h4>Introduction</h4>Three-dimensional (3D) histology analyses are essential to overcome sampling variability and understand pathological differences beyond the dissection axis. We present Path2MR, the first pipeline allowing 3D reconstruction of sparse human histology without an MRI reference. We implemented Path2MR with post-mortem hippocampal sections to explore pathology gradients in Alzheimer's Disease.<h4>Methods</h4>Blockface photographs of brain hemisphere slices are used for 3D reconstr ...[more]

PMID: 38105985

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Project description:Alzheimer's disease is the most common form of dementia, characterized by a persistent and progressive impairment of cognitive functions. Alzheimer's disease is typically associated with extracellular deposits of amyloid-β peptide and accumulation of abnormally phosphorylated tau protein inside neurons (amyloid-β and neurofibrillary pathologies). It has been proposed that these pathologies cause neuronal degeneration and synaptic alterations, which are thought to constitute the major neurobiological basis of cognitive dysfunction in Alzheimer's disease. The hippocampal formation is especially vulnerable in the early stages of Alzheimer's disease. However, the vast majority of electron microscopy studies have been performed in animal models. In the present study, we performed an extensive 3D study of the neuropil to investigate the synaptic organization in the stratum pyramidale and radiatum in the CA1 field of Alzheimer's disease cases with different stages of the disease, using focused ion beam/scanning electron microscopy (FIB/SEM). In cases with early stages of Alzheimer's disease, the synapse morphology looks normal and we observed no significant differences between control and Alzheimer's disease cases regarding the synaptic density, the ratio of excitatory and inhibitory synapses, or the spatial distribution of synapses. However, differences in the distribution of postsynaptic targets and synaptic shapes were found. Furthermore, a lower proportion of larger excitatory synapses in both strata were found in Alzheimer's disease cases. Individuals in late stages of the disease suffered the most severe synaptic alterations, including a decrease in synaptic density and morphological alterations of the remaining synapses. Since Alzheimer's disease cases show cortical atrophy, our data indicate a reduction in the total number (but not the density) of synapses at early stages of the disease, with this reduction being much more accentuated in subjects with late stages of Alzheimer's disease. The observed synaptic alterations may represent a structural basis for the progressive learning and memory dysfunctions seen in Alzheimer's disease cases.

Project description:Traditional histology is the gold standard for tissue studies, but it is intrinsically reliant on two-dimensional (2D) images. Study of volumetric tissue samples such as whole hearts produces a stack of misaligned and distorted 2D images that need to be reconstructed to recover a congruent volume with the original sample's shape. In this paper, we develop a mathematical framework called Transformation Diffusion (TD) for stack alignment refinement as a solution to the heat diffusion equation. This general framework does not require contour segmentation, is independent of the registration method used, and is trivially parallelizable. After the first stack sweep, we also replace registration operations by operations in the space of transformations, several orders of magnitude faster and less memory-consuming. Implementing TD with operations in the space of transformations produces our Transformation Diffusion Reconstruction (TDR) algorithm, applicable to general transformations that are closed under inversion and composition. In particular, we provide formulas for translation and affine transformations. We also propose an Approximated TDR (ATDR) algorithm that extends the same principles to tensor-product B-spline transformations. Using TDR and ATDR, we reconstruct a full mouse heart at pixel size 0.92µm×0.92µm, cut 10µm thick, spaced 20µm (84G). Our algorithms employ only local information from transformations between neighboring slices, but the TD framework allows theoretical analysis of the refinement as applying a global Gaussian low-pass filter to the unknown stack misalignments. We also show that reconstruction without an external reference produces large shape artifacts in a cardiac specimen while still optimizing slice-to-slice alignment. To overcome this problem, we use a pre-cutting blockface imaging process previously developed by our group that takes advantage of Brewster's angle and a polarizer to capture the outline of only the topmost layer of wax in the block containing embedded tissue for histological sectioning.

Dataset Information

Three-dimensional histology reveals dissociable human hippocampal long axis gradients of Alzheimer's pathology.

Introduction

Methods

Results

Conclusion

Publications

Three-dimensional histology reveals dissociable human hippocampal long axis gradients of Alzheimer's pathology.

Similar Datasets

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