Biology subjects

Holton, J.

Publications and source records attributed to Holton, J..

6 recordsLinked to original sources

bioRxiv2025

Fast segmentation with the NextBrain histological atlas

Structural brain analysis at the subregion level offers critical insights into healthy aging and neurodegenerative diseases. The NextBrain histological atlas was recently introduced to support such fine-grained investigations, but its existing Bayesian segmentation framework remains computationally prohibitive, particularly for large-scale studies. We present a new, open-source tool that dramatically accelerates segmentation using a hybrid approach combining: machine learning, contrast-adaptive segmentation; target-specific image synthesis; and fast diffeomorphic registration (all three with GPU support). Our method enables highly granular segmentation of brain MRI scans of any resolution and contrast (in vivo or ex vivo) at a fraction of the computational cost of the original method (<5 minutes on a GPU). We validate our tool on four different modalities (in vivo MRI, ex vivo MRI, HiP-CT, and photography) across a total of approximately 4,000 brain scans. Our results demonstrate that the accelerated approach achieves comparable accuracy to the original method in terms of Dice scores, while reducing runtime by over an order of magnitude. This work enables high-resolution anatomical analysis at unprecedented scale and flexibility, providing a practical solution for large neuroimaging studies. Our tool is publicly available in FreeSurfer (https://surfer.nmr.mgh.harvard.edu/fswiki/HistoAtlasSegmentation).

neuroscience↗

bioRxiv2024

Dissecting the differential role of C-terminal truncations in the regulation of aSyn pathology formation and the biogenesis of Lewy bodies

Alpha-synuclein (aSyn) post-translational modifications (PTMs), particularly phosphorylation at serine 129 and C-terminal truncations, are highly enriched in Lewy bodies (LBs), Lewy neurites, and other types of aSyn pathological aggregates in the brain of patients with Parkinsons disease (PD) and other synucleinopathies. However, our knowledge about the precise role of PTMs in regulating the different stages of pathology formation, neurodegeneration, and aSyn pathology spreading remains incomplete. In this work, we applied a systematic approach to address this knowledge gap with an emphasis on mapping and elucidating the role of post-fibrillization C-terminal aSyn truncations in regulating the uptake, processing, seeding activity, and formation of LB-like inclusions and maturations in a well-established neuronal seeding model that recapitulates all the stages leading to LB formation and neurodegeneration. Our work shows that C-terminal cleavage of aSyn fibrils at multiple sites is a conserved process that occurs rapidly after and during the formation of intracellular LB-like aSyn inclusions in all neuronal seeding models. Interestingly, blocking the cleavage of internalized fibrils does not influence their seeding activity, whereas inhibiting the enzymes that regulate the cleavage of newly formed fibrils (e.g., calpains 1 and 2) significantly alters the formation of LB-like inclusions. We also show that C-terminal truncations, in combination with other PTMs, play a crucial role in regulating the interactome and remodeling of newly formed aSyn fibrils, including their shortening, lateral association, and packing during LB formation and maturation. Altogether, our results demonstrate that post-fibrillization C-terminal truncations have a differential role at different stages of aSyn aggregation and pathology formation. These insights, combined with the abundance of truncated aSyn species in LBs, have significant implications in understanding aSyn pathological diversity and developing therapeutic strategies targeting the C-terminus of aSyn or its proteolytic processing.

neuroscience↗

bioRxiv2024

A next-generation, histological atlas of the human brain and its application to automated brain MRI segmentation

Magnetic resonance imaging (MRI) is the standard tool to image the human brain in vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we present NextBrain, a next - generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct [~]10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to build the first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in any in vivo or ex vivo brain MRI scan using the NextBrain atlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimers disease and healthy brain ageing based on [~]4,000 publicly available in vivo MRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 m isotropic ex vivo hemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge, NextBrain holds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease.

neuroscience↗

bioRxiv2020

Transcriptional profiling of Multiple System Atrophy cerebellar tissue highlights differences between the parkinsonian and cerebellar sub-types of the disease

Multiple system atrophy (MSA) is a rare adult-onset neurodegenerative disease of unknown cause, with no effective therapeutic options, and no cure. Limited work to date has attempted to characterize the transcriptional changes associated with the disease, which presents as either predominating parkinsonian (MSA-P) or cerebellar (MSC-C) symptoms. We report here the results of RNA expression profiling of cerebellar white matter (CWM) tissue from two independent cohorts of MSA patients (n=66) and healthy controls (HC; n=66). RNA samples from bulk brain tissue and from oligodendrocytes obtained by laser capture microdissection (LCM) were sequenced. Differentially expressed genes (DEGs) were obtained and were examined before and after stratifying by MSA clinical sub-type. We detected the highest number of DEGs in the MSA-C group (n = 747) while only one gene was noted in MSA-P, highlighting the larger dysregulation of the transcriptome in the MSA-C CWM. Results from both bulk tissue and LCM analysis of MSA-C showed a downregulation of oligodendrocyte genes and an enrichment for myelination processes with a key role noted for the QKI gene. Additionally, we observed a significant upregulation of neuron-specific gene expression in MSA-C and an enrichment for synaptic processes. A third cluster of genes was associated with the upregulation of astrocyte and endothelial genes, two cell types with a key role in inflammation processes. Finally, network analysis in MSA-C showed enrichment for {beta}-amyloid related functional classes, including the known Alzheimers disease (AD) genes, APP and PSEN1. This is the largest RNA profiling study ever conducted on post-mortem brain tissue from MSA patients. We were able to define specific gene expression signatures for MSA-C highlighting the different stages of the complex neurodegenerative cascade of the disease that included alterations in several cell-specific transcriptional programs. Finally, several results suggest a common transcriptional dysregulation between MSA and AD-related genes despite the clinical and neuropathological distinctions between the two diseases.

genomics↗

bioRxiv2018

The making of a Lewy body: the role of alpha-synuclein post-fibrillization modifications in regulating the formation and the maturation of pathological inclusions.

Although converging evidence point to alpha-synuclein (a-syn) aggregation and Lewy body (LB) formation as central events in Parkinson's disease (PD), the molecular mechanisms that regulate these processes and their role in disease pathogenesis remain poorly understood. Herein, we applied an integrative biochemical, structural and imaging approach to elucidate the sequence, molecular and cellular mechanisms that regulate LB formation in primary neurons. Our results establish that post-fibrillization C-terminal truncation mediated by calpains 1 and 2 and potentially other enzymes, plays critical roles in regulating a-syn seeding, fibrillization and orchestrates many of the events associated with LB formation and maturation. These findings combined with the abundance of a-syn truncated species in LBs and pathological a-syn aggregates have significant implications for ongoing efforts to develop therapeutic strategies based on targeting the C-terminus of a-syn or proteolytic processing of this region.

neuroscience↗

bioRxiv2018

Heritability and genetic variance of dementia with Lewy bodies

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinsons disease (PD) or Alzheimers disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.

neuroscience↗