Biology subjects

Torok, J.

Publications and source records attributed to Torok, J..

9 recordsLinked to original sources

bioRxiv2025

Distinguish risk genes functioning at presynaptic or postsynaptic regions and key connectomes associated with pathological α-synuclein spreading

Previous studies have suggested that pathological -synuclein (-Syn) mainly transmits along the neuronal network, but several key questions remain unanswered: (1) How many and which connections in the connectome are necessary for predicting the progression of pathological -Syn? (2) How to identify risk gene that affects pathology spreading functioning at presynaptic or postsynaptic regions, and are these genes enriched in different cell types? Here, we addressed these key questions with novel mathematical models. Strikingly, the spreading of pathological -Syn is predominantly determined by the key subnetworks composed of only 2% of the strongest connections in the connectome. We further explored the genes that are responsible for the selective vulnerability of different brain regions to transmission to distinguish the genes that play roles in presynaptic from those in postsynaptic regions. Those risk genes were significantly enriched in microglial cells of presynaptic regions and neurons of postsynaptic regions. Gene regulatory network analyses were then conducted to identify key drivers of genes responsible for selective vulnerability and overlapping with Parkinsons disease risk genes. By identifying and discriminating between key gene mediators of transmission operating at presynaptic and postsynaptic regions, our study has demonstrated for the first time that these are functionally distinct processes.

neuroscience↗

bioRxiv2024

Directionality bias is necessary to explain spatiotemporal progression of pathology in mouse models of tauopathy

Mounting evidence implicates trans-synaptic connectome-based spread as a shared mechanism behind different tauopathic conditions, yet also suggests there is divergent spatiotemporal progression between them. A potential parsimonious explanation for this apparent contradiction could be that different conditions incur differential rates and directional biases in tau transmission along fiber tracts. In this meta-analysis we closely examined this hypothesis and quantitatively tested it using spatiotemporal tau pathology patterns from 11 distinct models across 4 experimental studies. For this purpose, we extended a network-based spread model by incorporating net directionality along the connectome. Our data unambiguously supports the directional transmission hypothesis. First, retrograde bias is an unambiguously better predictor of tau progression than anterograde bias. Second, while spread exhibits retrograde character, our best-fitting biophysical models incorporate the mixed effects of both retrograde- and anterograde-directed spread, with notable tau-strain-specific differences. We also found a nontrivial association between directionality bias and tau strain aggressiveness, with more virulent strains exhibiting less retrograde character. Taken together, our study implicates directional transmission bias in tau transmission along fiber tracts as a general feature of tauopathy spread and a strong candidate explanation for the diversity of spatiotemporal tau progression between conditions. This simple and parsimonious mechanism may potentially fill a critical gap in our knowledge of the spatiotemporal ramification of divergent tauopathies.

neuroscience↗

bioRxiv2024

Understanding the complex interplay between tau, amyloid and the network in the spatiotemporal progression of Alzheimer's Disease

INTRODUCTIONThe interaction of amyloid and tau in neurodegenerative diseases is a central feature of AD pathophysiology. While experimental studies point to various interaction mechanisms, their causal direction and mode (local, remote or network-mediated) remain unknown in human subjects. The aim of this study was to compare mathematical reaction-diffusion models encoding distinct cross-species couplings to identify which interactions were key to model success. METHODSWe tested competing mathematical models of network spread, aggregation, and amyloid-tau interactions on publicly available data from ADNI. RESULTSAlthough network spread models captured the spatiotemporal evolution of tau and amyloid in human subjects, the model including a one-way amyloid-to-tau aggregation interaction performed best. DISCUSSIONThis mathematical exposition of the "pas de deux" of co-evolving proteins provides quantitative, whole-brain support to the concept of amyloid-facilitated-tauopathy rather than the classic amyloid-cascade or pure-tau hypotheses, and helps explain certain known but poorly understood aspects of AD.

neuroscience↗

bioRxiv2024

Selective vulnerability and resilience to Alzheimer's disease tauopathy as a function of genes and the connectome

Brain regions in Alzheimers (AD) exhibit distinct vulnerability to the diseases hallmark pathology, with the entorhinal cortex and hippocampus succumbing early to tau tangles while others like primary sensory cortices remain resilient. The quest to understand how local/regional genetic factors, pathogenesis, and network-mediated spread of pathology together govern this selective vulnerability (SV) or resilience (SR) is ongoing. Although many risk genes in AD are known from gene association and transgenic studies, it is still not known whether and how their baseline expression signatures confer SV or SR to brain structures. Prior analyses have yielded conflicting results, pointing to a disconnect between the location of genetic risk factors and downstream tau pathology. We hypothesize that a full accounting of genes role in mediating SV/SR would require the modeling of network-based vulnerability, whereby tau misfolds, aggregates, and propagates along fiber projections. We therefore employed an extended network diffusion model (eNDM) and tested it on tau pathology PET data from 196 AD patients from the Alzheimers Disease Neuroimaging Initiative (ADNI). Thus the fitted eNDM model becomes a reference process from which to assess the role of innate genetic factors. Using the residual (observed - model-predicted) tau as a novel target outcome, we obtained its association with 100 top AD risk-genes, whose baseline spatial transcriptional profiles were obtained from the Allen Human Brain Atlas (AHBA). We found that while many risk genes at baseline showed a strong association with regional tau, many more showed a stronger association with residual tau. This suggests that both direct vulnerability, related to the network, as well as network-independent vulnerability, are conferred by risk genes. We then classified risk genes into four classes: network-related SV (SV-NR), network-independent SV (SV-NI), network-related SR (SR-NR), and network-independent SR (SR-NI). Each class has a distinct spatial signature and associated vulnerability to tau. Remarkably, we found from gene-ontology analyses, that genes in these classes were enriched in distinct functional processes and encompassed different functional networks. These findings offer new insights into the factors governing innate vulnerability or resilience in AD pathophysiology and may prove helpful in identifying potential intervention targets.

neuroscience↗

bioRxiv2023

A meta-analysis of mouse models of tauopathy reveals the cellular underpinnings of selective regional vulnerability

Neurodegenerative diseases such as Alzheimers disease (AD) exhibit pathological changes in the brain that proceed in a stereotyped and regionally specific fashion, but the cellular and molecular underpinnings of regional vulnerability are currently poorly understood. Recent work has identified certain subpopulations of neurons in a few focal regions of interest, such as the entorhinal cortex, that are selectively vulnerable to tau pathology in AD. However, the cellular underpinnings of regional susceptibility to tau pathology are currently unknown, primarily because whole-brain maps of a comprehensive collection of cell types have been inaccessible. Here, we deployed a recent cell-type mapping pipeline, Matrix Inversion and Subset Selection (MISS), to determine the brain-wide distributions of pan-hippocampal and neocortical neuronal and non-neuronal cells in the mouse using recently available single-cell RNA sequencing (scRNAseq) data. We then performed a robust set of analyses to identify general principles of cell-type-based selective vulnerability using these cell-type distributions, utilizing 5 transgenic mouse studies that quantified regional tau in 12 distinct PS19 mouse models. Using our approach, which constitutes the broadest exploration of whole-brain selective vulnerability to date, we were able to discover cell types and cell-type classes that conferred vulnerability and resilience to tau pathology. Hippocampal glutamatergic neurons as a whole were strongly positively associated with regional tau deposition, suggesting vulnerability, while cortical glutamatergic and GABAergic neurons were negatively associated. Among glia, we identified oligodendrocytes as the single-most strongly negatively associated cell type, whereas microglia were consistently positively correlated. Strikingly, we found that there was no association between the gene expression relationships between cell types and their vulnerability or resilience to tau pathology. When we looked at the explanatory power of cell types versus GWAS-identified AD risk genes, cell type distributions were consistently more predictive of end-timepoint tau pathology than regional gene expression. To understand the functional enrichment patterns of the genes that were markers of the identified vulnerable or resilient cell types, we performed gene ontology analysis. We found that the genes that are directly correlated to tau pathology are functionally distinct from those that constitutively embody the vulnerable cells. In short, we have demonstrated that regional cell-type composition is a compelling explanation for the selective vulnerability observed in tauopathic diseases at a whole-brain level and is distinct from that conferred by risk genes. These findings may have implications in identifying cell-type-based therapeutic targets.

neuroscience↗

bioRxiv2021

Emergence of directional bias in tau deposition from axonal transport dynamics

Defects in axonal transport may partly underpin the differences between the observed pathophysiology of Alzheimers disease (AD) and that of other non-amyloidogenic tauopathies. Particularly, pathological tau variants may have molecular properties that dysregulate motor proteins responsible for the anterograde-directed transport of tau in a disease-specific fashion. Here we develop the first computational model of tau-modified axonal transport that produces directional biases in the spread of tau pathology. We simulated the spatiotemporal profiles of soluble and insoluble tau species in a multicompartment, two-neuron system using biologically plausible parameters and time scales. Changes in the balance of tau transport feedback parameters can elicit anterograde and retrograde biases in the distributions of soluble and insoluble tau between compartments in the system. Aggregation and fragmentation parameters can also perturb this balance, suggesting a complex interplay between these distinct molecular processes. Critically, we show that the model faithfully recreates the characteristic network spread biases in both AD-like and non-AD-like mouse tauopathy models. Tau transport feedback may therefore help link microscopic differences in tau conformational states and the resulting variety in clinical presentations. Author SummaryThe misfolding and spread of the axonal protein tau is a hallmark of the pathology of many neurodegenerative disorders, including Alzheimers disease and frontotemporal lobar dementia. How tau misfolding causes disorders with distinct neuropathology and clinical presentations is the subject of ongoing research. Although current evidence suggests that the specific conformations tau adopts affect where it spreads throughout the brain, a mechanistic explanation has remained elusive. Here we propose that the conformer-specific dysregulation of axonal transport can lead to directionally biased spread, and we employ a mathematical model to explore how tau spreads between neurons in the context of this transport feedback mechanism. We find that conformation-specific feedback is flexible enough to explain bias in either direction and thoroughly explore how this bias emerges as a function of the models key parameters. Further, the model reproduces the temporal evolution of directionality observed in two classes of in vivo tauopathy models, demonstrating that transport feedback is sufficient to explain differential tau spread as a function of conformation.

neuroscience↗

bioRxiv2020

Bird populations most exposed to climate change are less responsive to climatic variation

The phenology of many species shows strong sensitivity to climate change; however, with few large scale intra-specific studies it is unclear how such sensitivity varies over a species range. We document large intra-specific variation in phenological sensitivity to temperature using laying date information from 67 populations of two European songbirds covering a large part of their breeding range. Populations inhabiting deciduous habitats showed stronger phenological sensitivity compared with those in evergreen and mixed habitats. Strikingly, however, the lowest sensitivity was seen in populations that had experienced the greatest change in climate. Therefore, we predict that the strongest phenological advancement will not occur in those populations with the highest sensitivity. Our results show that to effectively assess the impact of climate change on phenology across a species range it will be necessary to account for intra-specific variation in phenological sensitivity, climate change exposure, and the ecological characteristics of a population.

ecology↗

bioRxiv2019

Matrix Inversion and Subset Selection (MISS): A novel pipeline for quantitative mapping of diverse cell types across the murine brain

The advent of increasingly sophisticated imaging platforms has allowed for the visualization of the murine nervous system at single-cell resolution. However, current experimental approaches have not yet produced whole-brain maps of a comprehensive set of neuronal and nonneuronal types that approaches the cellular diversity of the mammalian cortex. Here we aim to fill in this gap in knowledge with an open-source computational pipeline, Matrix Inversion with Subset Selection (MISS), that can infer quantitatively validated distributions of diverse collections of neural cell types at 200m resolution using a combination of single-cell RNAseq and in situ hybridization datasets. We rigorously demonstrate the accuracy of MISS against literature expectations. Importantly, we show that gene subset selection, a procedure by which we filter out low-information genes prior to performing deconvolution, is a critical pre-processing step that distinguishes MISS from its predecessors and facilitates the production of cell type maps with significantly higher accuracy. We also show that MISS is generalizable by generating high-quality cell type maps from a second, independently curated single-cell RNAseq dataset. Together, our results illustrate the viability of computational approaches for determining the spatial distributions of a wide variety of cell types from genetic data alone.

neuroscience↗

bioRxiv2018

Heterogeneity of Incipient Atrophy Patterns in Parkinsons Disease

Parkinsons Disease (PD) is a the second most common neurodegenerative disorder after Alzheimers disease and is characterized by cell death in the amygdala and in substructures of the basal ganglia such as the substantia nigra. Since neuronal loss in PD leads to measurable atrophy patterns in the brain, there is clinical value in understanding where exactly the pathology emerges in each patient and how incipient atrophy relates to the future spread of disease. A recent seed-inference algorithm combining an established network-diffusion model with an L1-penalized optimization routine led to new insights regarding the non-stereotypical origins of Alzheimers pathologies across individual subjects. Here, we leverage the same technique to PD patients, demonstrating that the high variability in their atrophy patterns also translates into heterogeneous seed locations. Our individualized seeds are significantly more predictive of future atrophy than a single seed placed at the substantia nigra or the amygdala. We also found a clear distinction in seeding patterns between two PD subgroups - one characterized by predominant involvement of brainstem and ventral nuclei, and the other by more widespread frontal and striatal cortices. This might be indicative of two distinct etiological mechanisms operative in PD. Ultimately, our methods demonstrate that the early stages of the disease may exhibit incipient atrophy patterns that are more complex and variable than generally appreciated.

neuroscience↗