Biology subjects

Gauthier, S.

Publications and source records attributed to Gauthier, S..

17 recordsLinked to original sources

bioRxiv2026

Extracellular water withdrawal drives disease resistance in the phyllosphere

A central question in immunity is how hosts arrest pathogen growth. Diverse plant pathogens create a water-soaked niche in host tissue essential for pathogenesis, yet how water shapes infection outcome is unknown. Using genetics and hyperspectral imaging, we show that extracellular water status is rate-limiting for both compatible and incompatible interactions. We find that the hypersensitive response of effector-triggered immunity (ETI) is, mechanistically, a desiccation event. Water loss imposes osmotic stress that arrests bacterial division while the pathogen remains alive and metabolically active, rather than killing it. Restoring apoplastic water reverses this stasis and licenses growth despite intact immune signaling and cell death. Water status, not immune signaling per se, gates pathogen growth. This reframes ETI as a controlled desiccation mechanism and identifies hydration as a decisive lever on disease outcome.

plant biology↗

bioRxiv2026

Atypical immunity induced by extracellular water in plants

Microbial pathogens require nutrients and water to support their growth and proliferation. Pathogen-mediated resource acquisition is orchestrated by the secretion of virulence factors that have evolved a diversity of forms (from effector proteins to small toxins), but which have converged in function (resource acquisition). A key observable virulence mechanism employed by a large number of microbial pathogens to cause disease is to induce a water-rich niche in the extracellular space (i.e. the apoplast) of their host, known as water-soaked lesions. Given the ubiquity of this virulence mechanism, we asked whether plants respond to pathogen-induced extracellular water to activate immune programs. We find that inducing a water-soaked apoplast induces an atypical transcriptional response, yet results in a functional immune response that restricts pathogen growth as effectively as canonical pattern-triggered immunity. Genetic and functional analyses reveal a role for the immune phytohormone salicylic acid (SA) in mediating apoplastic water-induced immunity (AWII). These results suggest that plants engage in an immune-priming program in response to apoplastic water accumulation, suggesting that the pathogenic niches induced during infection may be perceived as danger signals.

plant biology↗

bioRxiv2026

The Role of Meningeal Lymphatic Vessels and Perivascular Cerebrospinal Fluid Flow in Age-Related Processing Speed Decline

Meningeal lymphatic vessels (mLV) play essential roles in draining cerebrospinal fluid (CSF) into peripheral blood. The mLVs are hypothesized to be supportive structures to the glymphatic system, which is thought to remove metabolic byproducts from brain parenchyma and has been most directly studied in rodent models. Previous rodent studies have indicated a correlation between mLV function and cognitive performance, but this relationship in humans remains unexplored. Age-related declines in glymphatic system efficiency in humans and cognitive performance have been observed separately. This study investigates age- and sex-related differences in CSF production via choroid plexus volumes, mLV characteristics, and glymphatic system efficiency, overall elucidating the implication of cerebral lymphatic function on cognition. We recruited 26 healthy adults from Dallas-Fort Worth and acquired magnetic resonance images. mLVs along the sagittal sinus were visualized and segmented from T2-FLAIR images. The glymphatic system was evaluated by measuring diffusivity along the perivascular space. Choroid plexus volume and brain volume were estimated from T1-MPRAGE. Neuropsychological tests were conducted to assess cognitive function. Our findings indicate that glymphatic function diminishes with age, while mLV and choroid plexus volumes increase. Males displayed greater mLV volume than females, yet no sex differences were found in glymphatic function or choroid plexus volume. Notably, mLV volume increased as glymphatic function declined, independent of age. Moreover, a glymphatic-mLV latent variable significantly predicted processing speed, underscoring the influence of cerebral lymphatics on cognition. In conclusion, this study highlights a decline in glymphatic function with age, accompanied by increased mLV volumes and altered processing speed. These lymphatic system changes may underlie or contribute to the cognitive declines observed in healthy and pathological aging. Significance StatementThe glymphatic system and meningeal lymphatic vessels play crucial roles in removing brain cell waste. The relationship between these systems and their effect on human cognition, particularly processing speed, is unknown. We demonstrate that these systems change with advancing age. Variations in cerebral lymphatic function contribute to differences in processing speed independent of age, ultimately affecting higher-order cognitive function. The findings presented have implications for cognitive function in both healthy and diseased states.

neuroscience↗

bioRxiv2025

Amyloid-β 42-carrying extracellular vesicles are associated with neurodegeneration and neuroinflammation in Alzheimer's disease

Alzheimers disease (AD) is the most common form of dementia, characterized by progressive amyloid-{beta} (A{beta}) accumulation and neurodegeneration. Extracellular vesicles (EVs) have been implicated in AD pathology, but their relationship to disease progression and the cerebrospinal fluid (CSF) proteome remains poorly understood. In this study, we analysed plasma-derived A{beta}42-containing EVs from participants of the Alzheimers Disease Neuroimaging Initiative (ADNI) and calculated the ratio between the percentage of A{beta}42-positive peripheral EVs and CSF A{beta}42 (rA{beta}42). This ratio was elevated in AD and positively correlated with amyloid pathology as measured by PET. Longitudinal analyses revealed that higher rA{beta}42 values predicted accelerated hippocampal atrophy and cognitive decline, independent of CSF A{beta}42 concentrations. Proteomic profiling of CSF using the SomaScan platform showed that rA{beta}42 was associated with an inflammatory signature characterized by myeloid activation and type II interferon-related signalling pathways. Together, these findings indicate that A{beta}42-carrying EVs reflect an active and inflammatory component of AD pathology and may represent a novel class of biomarkers for disease progression. Understanding the mechanisms that link A{beta}42-positive EVs to neuroinflammatory signalling could open new avenues for pathway-specific diagnostics and therapeutic strategies in AD.

neuroscience↗

bioRxiv2025

High-severity fires undermine resilience of black spruce-dominated boreal forests in eastern North America

Climate-induced fire regime shifts may reduce post-fire resilience of black spruce-dominated (BS; Picea mariana) North American boreal forests. While post-fire vulnerability of immature BS stands has been extensively studied, no study has evaluated simultaneous effects of fire severity and seasonality on the post-fire regeneration of mature (> 60-year-old) BS stands. This study aims to quantify post-fire regeneration levels of BS and co-occurring tree species to assess ecosystem recovery and possible loss of resilience due to regeneration failure. We analyzed effects of seed bank conditions, fire regime characteristics (fire severity and seasonality), and seedbed conditions on BS post-fire regeneration in mature forests in Quebec, Canada. Post-fire regeneration density was extensively surveyed across [~]50 400 km2 through a network of 536 plots that were distributed in 21 fires, which burned between 1995 and 2016. One-third of plots failed to regenerate (< 1750 conifer seedlings/ha) at levels adequate to produce closed-crown forest, whereas one-fifth experienced compositional changes, mainly towards jack pine (JP; Pinus banksiana) dominance. Pre-fire basal area of BS and living Sphagnum ground cover increased BS post-fire regeneration, whereas high-severity crown fires and spring fires reduced it. These findings suggest that mature BS-dominated forests may lose resilience in response to high-severity and spring fires. Given the projected increase in fire severity, and the extension towards an early-fire season in response to climate change, our study suggests that post-fire regeneration failure may become more frequent over the coming decades, with potential negative consequences on ecosystem services that are provided by BS-dominated boreal forests.

ecology↗

bioRxiv2024

Chloroplastic ROS bursts initiate salicylic acid biosynthesis in plant immunity

Chloroplasts are essential centers of signal integration and transduction in plants. They are involved in the biosynthesis of primary and specialized metabolites, including salicylic acid (SA), a key defense phytohormone synthesized via the conserved chorismate biosynthetic pathway. However, the identity of the signal(s) that ultimately triggers SA induction in chloroplasts upon perception of a biotic threat has remained elusive. Here, we provide evidence of a functional link between chloroplast-derived reactive oxygen species (cROS) and SA production. We observe that inhibiting ROS bursts generated from photosystem II during plant immune activation completely abrogates the induction of SA synthesis in response to immunity-inducing signals, without affecting SA-independent immune responses. Indeed, time course analyses show that the induction of SA marker genes parallels that of cROS production during an immune response. Consistent with this, preventing cROS induction is sufficient to nullify the immune protection normally conferred by activating immunity prior to an infection. Analyses of transcriptomes and photosynthetic efficiency show that two conserved effectors from the phytopathogen Pseudomonas syringae, HopM1 and AvrE1, redundantly disrupt photosynthesis and cROS bursts. These effects reduce SA accumulation and are mediated via the impact of HopM1 and AvrE1 in inducting host abscisic acid signaling. Our results suggest that a change in chloroplastic redox homeostasis induced by biotic stressors acts as an initiator of plant immunity through the production of SA, and that this response is targeted by conserved pathogen effector proteins.

plant biology↗

bioRxiv2023

The sequence of regional structural disconnectivity due to multiple sclerosis lesions

ObjectivePrediction of disease progression is challenging in multiple sclerosis (MS) as the sequence of lesion development and retention of inflammation within a subset of chronic lesions is heterogeneous among patients. We investigated the sequence of lesion-related regional structural disconnectivity across the spectrum of disability and cognitive impairment in MS. MethodsIn a full cohort of 482 patients, the Expanded Disability Status Scale was used to classify patients into (i) no or mild vs (ii) moderate or severe disability groups. In 363 out of 482 patients, Quantitative Susceptibility Mapping was used to identify paramagnetic rim lesions (PRL), which are maintained by a rim of iron-laden innate immune cells. In 171 out of 482 patients, Brief International Cognitive Assessment was used to identify subjects with cognitive impairment. Network Modification Tool was used to estimate the regional structural disconnectivity due to MS lesions. Discriminative event-based modeling was applied to investigate the sequence of regional structural disconnectivity due to all representative lesions across the spectrum of disability and cognitive impairment. ResultsStructural disconnection in the ventral attention and subcortical networks was an early biomarker of moderate or severe disability. The earliest biomarkers of disability progression were structural disconnections due to PRL in the motor-related regions. Subcortical structural disconnection was an early biomarker of cognitive impairment. InterpretationMS lesion-related structural disconnections in the subcortex is an early biomarker for both disability and cognitive impairment in MS. PRL-related structural disconnection in the motor cortex may identify the patients at risk for moderate or severe disability in MS.

neuroscience↗

bioRxiv2022

Proteome dynamics of COVID-19 severity learnt by a graph convolutional network of multi-scale topology

Many efforts have been recently done to characterise the molecular mechanisms of COVID-19 disease. These efforts resulted in a full structural identification of ACE2 as principal receptor of the Sars-CoV-2 spike protein in the cell. However, there are still important open questions related to other proteins involved in the progression of the disease. To this end, we have modelled the plasma proteome of 384 COVID patients. The model calibrated proteins measures at three time tags and make also use of the detailed clinical evaluation outcome of each patient after their hospital stay at day 28. Our analysis is able to discriminate severity of the disease by means of a metric based on available WHO scores of disease progression. Then, we identify by topological vectorisation those proteins shifting the most in their expression depending on that severity classification. Finally, the extracted topological invariants respect the protein expression at different times were used as base of a graph convolutional network. This model enabled the dynamical learning of the molecular interactions produced between the identified proteins.

systems biology↗

bioRxiv2022

Stage dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum

BackgroundLarge-scale neuronal network breakdown underlies memory impairment in Alzheimers disease (AD). However, the differential trajectories of the relationships between network organization and memory across pathology and cognitive stages in AD remain elusive. We determined whether and how the influences of individual-level structural and metabolic covariance network integrity on memory varied with amyloid pathology across clinical stages without assuming a constant relationship. Methods708 participants from the Alzheimers Disease Neuroimaging Initiative were studied. Individual-level structural and metabolic covariance scores in higher-level cognitive and hippocampal networks were derived from magnetic resonance imaging and [18F]fluorodeoxyglucose positron emission tomography using seed-based partial least square analyses. The non-linear associations between network scores and memory across cognitive stages in each pathology group were examined using sparse varying coefficient modelling. ResultsWe showed that the associations of memory with structural and metabolic networks in the hippocampal and default mode regions exhibited pathology-dependent differential trajectories across cognitive stages using sparse varying coefficient modelling. In amyloid pathology group, there was an early influence of hippocampal structural network deterioration on memory impairment in the preclinical stage, and a biphasic influence of the angular gyrus-seeded default mode network metabolism on memory in both preclinical and dementia stages. In non-amyloid pathology groups, in contrast, the trajectory of the hippocampus-memory association was opposite and weaker overall, while no metabolism covariance networks were related to memory. Key findings were replicated in a larger cohort of 1280 participants. ConclusionsOur findings highlight potential windows of early intervention targeting network breakdown at the preclinical AD stage.

neuroscience↗

bioRxiv2022

Larger lesion volume in people with multiple sclerosis is associated with increased transition energies between brain states and decreased entropy of brain activity

BackgroundNeuronal loss, demyelination, and inflammation in the brains of people with multiple sclerosis (pwMS) can cause impairment or disability across a range of domains. However, the mapping between severity or location of this brain tissue damage and an individuals impairment remains challenging. Advanced neuroimaging techniques may enable us to better understand the neuropathological or compensatory mechanisms in MS and quantify the link between the brains functional activity and its structural backbone. One recently developed approach uses network control theory to characterize the brains energetic landscape using an individuals structural connectome and brain activity dynamics. While brain activity dynamics have previously been analyzed in MS cohorts, investigating how structural network damage, one of the hallmarks of MS, relates to shifts in activity dynamics has not yet been performed. AimsWe apply brain activity dynamics analysis and network control theory (NCT) to functional time series and structural connectomes in healthy controls (HC) and pwMS with and without disability and compare the three groups resulting metrics. We also assessed the entropy of the three groups brain activity time series. Our hypotheses were that pwMS with disability would have increased brain state transition energies compared to pwMS without disability and controls, and that greater energies would be related to greater lesion burden and decreased entropy of brain activity. Materials and MethodsNinety-nine pwMS and 19 HC were included in our study; individuals underwent MRI, including anatomical, diffusion and resting-state functional scans. Expanded Disability Status Scale (EDSS) was used to assess disability; 66 pwMS with EDSS<2 were considered as not having disability. Commonly recurring brain states were identified using k-means clustering of the regional brain activity time series. NCT was used to compute the energy required to transition between each pair of states or to remain in the same state, taking into account an individuals structural connectome. The entropy of brain activity time series was quantified and correlated with overall transition energy and lesion volume. Finally, logistic regression with ridge regularization was used to classify the groups using transition energies and demographics/clinical information and the models feature importance assessed. ResultsSix brain states were identified, including pairs of states with high and low visual (VIS+/-), ventral attention (VAN)+/- and somatomotor (SOM+/-) network activity. Global entropy was negatively correlated with lesion volume (r=-0.20, p=0.03) as was global transition energy (r=-0.18, p=0.04) in pwMS. Smaller transition energies were associated with pwMS without disability, while larger transition energies were associated with pwMS with disability. DiscussionWe conjecture that functional compensation of brain activity in pwMS without disability results in decreased transition energies between states compared to controls, but, as this mechanism diminishes, transition energies increase and disability occurs. We also conjecture that larger volumes of MS-related lesions result in greater energetic demands to transition between brain states which then leads to lower overall entropy of brain activity.

neuroscience↗

bioRxiv2021

Differentiating amyloid beta spread in autosomal dominant and sporadic Alzheimer's disease

Amyloid-beta (A{beta}) deposition is one of the hallmark pathologies in both sporadic Alzheimers disease (sAD) and autosomal dominant Alzheimers disease (ADAD), the latter of which is caused by mutations in genes involved in A{beta} processing. Despite A{beta} deposition being a centerpiece to both sAD and ADAD, some differences between these AD subtypes have been observed with respect to the spatial pattern of A{beta}. Previous work has shown that the spatial pattern of A{beta} in individuals spanning the sAD spectrum can be reproduced with high accuracy using an epidemic spreading model (ESM), which simulates the diffusion of A{beta} across neuronal connections and is constrained by individual rates of A{beta} production and clearance. However, it has not been investigated whether A{beta} deposition in the rarer ADAD can be modeled in the same way, and if so, how congruent the spreading patterns of A{beta} across sAD and ADAD are. We leverage the ESM as a data-driven approach to probe individual-level variation in the spreading patterns of A{beta} across three different large-scale imaging datasets (2 SAD, 1 ADAD). We applied the ESM separately to the Alzheimers Disease Neuroimaging initiative (N=737), the Open Access Series of Imaging Studies (N=510), and the Dominantly Inherited Alzheimers Network (N=249), the latter two of which were processed using an identical pipeline. We assessed inter- and intra-individual model performance in each dataset separately, and further identified the most likely epicenter of A{beta} spread for each individual. Using epicenters defined in previous work in sAD, the ESM provided moderate prediction of the regional pattern of A{beta} deposition across all three datasets. We further find that, while the most likely epicenter for most A{beta}-positive subjects overlaps with the default mode network, 13% of ADAD individuals were best characterized by a striatal origin of A{beta} spread. These subjects were also distinguished by being younger than ADAD subjects with a DMN A{beta} origin, despite having a similar estimated age of symptom onset. Together, our results suggest that most ADAD patients express A{beta} spreading patters similar to those of sAD, but that there may be a subset of ADAD patients with a separate, striatal phenotype.

neuroscience↗

bioRxiv2021

Estimated connectivity networks outperform observed connectivity networks when classifying people with multiple sclerosis into disability groups

BackgroundMultiple Sclerosis (MS), a neurodegenerative and neuroinflammatory disease, causing lesions that disrupt the brains anatomical and physiological connectivity networks, resulting in cognitive, visual and/or motor disabilities. Advanced imaging techniques like diffusion and functional MRI allow measurement of the brains structural connectivity (SC) and functional connectivity (FC) networks, and can enable a better understanding of how their disruptions cause disability in people with MS (pwMS). However, advanced MRI techniques are used mainly for research purposes as they are expensive, time-consuming and require high-level expertise to acquire and process. As an alternative, the Network Modification (NeMo) Tool can be used to estimate SC and FC using lesion masks derived from pwMS and a reference set of controls connectivity networks. ObjectiveHere, we test the hypothesis that estimated SC and FC (eSC and eFC) from the NeMo Tool, based only on an individuals lesion masks, can be used to classify pwMS into disability categories just as well as SC and FC extracted from advanced MRI directly in pwMS. We also aim to find the connections most important for differentiating between no disability vs evidence of disability groups. Materials and MethodsOne hundred pwMS (age:45.5 {+/-} 11.4 years, 66% female, disease duration: 12.97 8.07 years) were included in this study. Expanded Disability Status Scale (EDSS) was used to assess disability, 67 pwMS had no disability (EDSS < 2). Observed SC and FC were extracted from diffusion and functional MRI directly in pwMS, respectively. The NeMo Tool was used to estimate the remaining structural connectome (eSC), by removing streamlines in a reference set of tractograms that intersected the lesion mask. The NeMo Tools eSC was used then as input to a deep neural network to estimate the corresponding FC (eFC). Logistic regression with ridge regularization was used to classify pwMS into disability categories (no disability vs evidence of disability), based on demographics/clinical information (sex, age, race, disease duration, clinical phenotype, and spinal lesion burden) and either pairwise entries or regional summaries from one of the following matrices: SC, FC, eSC, and eFC. The area under the ROC curve (AUC) was used to assess the classification performance. Both univariate statistics and parameter coefficients from the classification models were used to identify features important to differentiating between the groups. ResultsThe regional eSC and eFC models outperformed their observed FC and SC counterparts (p-value<0.05), while the pairwise eSC and SC performed similarly (p=0.10). Regional eSC and eFC models had higher AUC (0.66-0.68) than the pairwise models (0.60-0.65), with regional eFC having highest classification accuracy across all models. Ridge regression coefficients for the regional eFC and regional observed FC models were significantly correlated (Pearsons r = 0.52, p-value < 10e-7). Decreased estimated SC node strength in default mode and ventral attention networks and increased eFC node strength in visual networks was associated with evidence of disability. DiscussionHere, for the first time, we use clinically-acquired lesion masks to estimate both structural and functional connectomes in patient populations to better understand brain lesion-dysfunction mapping in pwMS. Models based on the NeMo Tools estimates of SC and FC better classified pwMS by disability level than SC and FC observed directly in the individual using advanced MRI. This work provides a viable alternative to performing high-cost, advanced MRI in patient populations, bringing the connectome one step closer to the clinic. HighlightsO_LIWe compared the accuracy of models based on observed functional connectivity (FC) and structural connectivity (SC) networks extracted from advanced MRI and estimated FC and SC networks derived using only lesion masks from conventional MRI in classifying people with multiple sclerosis (pwMS) into disability groups. C_LIO_LIEstimated SC and FC generally outperformed observed SC and FC in classifying pwMS into no disability vs evidence of disability groups, with regional estimated SC and FC having the best performance. C_LIO_LIIncreased estimated FC node strength of regions in the visual network was associated with disability. C_LIO_LIDecreased estimated SC node strength of regions in the default mode and ventral attention networks was associated with disability. C_LIO_LIDespite their varied sources of origin, feature weights for the regional estimated FC and the regional observed FC classification models was significantly correlated (Pearsons r = 0.52, p-value < 10e-7). C_LI

neuroscience↗

bioRxiv2020

A disynaptic circuit in the globus pallidus controls locomotion inhibition

Basal ganglia (BG) inhibit movement through two independent pathways, the indirect- and the hyperdirect-pathways. The globus pallidus (GP) has always been viewed as a simple relay within these two pathways, but its importance has changed drastically with the discovery of two functionally-distinct cell types, namely the prototypic and the arkypallidal neurons. Classic BG models suggest that all GP neurons receive GABAergic inputs from striato-pallidal indirect spiny projection neurons and glutamatergic inputs from subthalamic neurons. However, whether this synaptic connectivity scheme applies to both GP cell-types is currently unknown. Here, we optogenetically dissect the input organization of prototypic and arkypallidal neurons and further define the circuit mechanism underlying action inhibition in BG. Our results highlight that an increased activity of arkypallidal neurons is required to inhibit locomotion. Finally, this work supports the view that arkypallidal neurons are part of a novel disynaptic feedback loop that broadcast inhibitory control on movement execution.

neuroscience↗

bioRxiv2020

Functional brain age prediction suggests accelerated aging in preclinical familial Alzheimer's disease, irrespective of fibrillar amyloid-beta pathology

We aimed at developing a model able to predict brain aging from resting state functional connectivity (rs-fMRI) and assessing whether genetic risk/determinants of Alzheimers disease (AD) and amyloid (A{beta}) pathology contributes to accelerated brain aging. Using data collected in 1340 cognitively unimpaired participants from 18 to 94 years old selected across multi-site cohorts, we showed that chronological age can be predicted across the whole lifespan from topological properties of graphs constructed from rs-fMRI. We subsequently used the difference between the model-predicted age and the chronological age in pre-symptomatic autosomal dominant AD (ADAD) mutation carriers and asymptomatic individuals at risk of sporadic AD and assessed the influence of genetics and A{beta} pathology on brain age. Applying our predictive model in the context of preclinical AD revealed that the pre-symptomatic phase of ADAD is characterized by accelerated functional brain aging. This phenomenon is independent from, and might precede, detectable fibrillar A{beta} deposition.

neuroscience↗

bioRxiv2020

Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia

Fronto-temporal dementia (FTD) is a neurodegenerative disease characterized by focal atrophy of the gray matter (GM), especially in the frontal and temporal regions. Recent studies suggest a framework where white matter (WM) atrophy plays an important role in FTD pathophysiology. However, these studies often overlook the fact that WM tracts bridging different brain regions may have different vulnerabilities to the disease and the relative contribution of GM atrophy to this WM model, resulting in a less comprehensive understanding of the relationship between clinical symptoms and pathology. Here, by leveraging the sensitivity of advanced diffusion MRI modelling and metrics to precise white matter microstructural properties, we aim to clarify the relative contributions of WM fibers and GM atrophy to the cognitive symptoms typically found in FTD. A total of 155 participant from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) were analysed, including 68 normal elderly controls (CN), 28 behavioral variants (BV), 26 sematic variants (SV) and 30 progressive non fluent aphasia variants (PNFA) of FTD. Diffusion MRI analysis was performed using two complementary techniques: whole brain fixel-based analysis (FBA) and structural connectivity based on probabilistic tractography. Whole brain GM atrophy was assessed using voxel-based morphometry (VBM). Using a common factor analysis to extract a semantic and an executive factor, we aim to test the relative contribution of WM and GM of specific tracts in predicting cognition. We found that semantic symptoms were mainly dependent on short-range WM fiber disruption, while damage to long-range WM fibers was preferentially associated to executive dysfunction with the GM contribution to cognition being predominant for local processing. Our results support the importance of the disruption of specific WM tracts to the core cognitive symptoms associated with FTD. As large-scale WM tracts, which are particularly vulnerable to vascular disease, were highly associated with executive dysfunction, our findings highlight the importance of controlling for risk factors associated with deep white matter disease, such as vascular risk factors, in patients with FTD in order not to potentiate underlying executive dysfunction.

neuroscience↗

bioRxiv2020

Creation of an Open Science Dataset from PREVENT-AD, a Longitudinal Cohort Study of Pre-symptomatic Alzheimer's Disease.

To move Alzheimer Disease (AD) research forward it is essential to collect data from large cohorts, but also make such data available to the global research community. We describe the creation of an open science dataset from the PREVENT-AD (PResymptomatic EValuation of Experimental or Novel Treatments for AD) cohort, composed of cognitively unimpaired older individuals with a parental or multiple-sibling history of AD. From 2011 to 2017, 386 participants were enrolled (mean age 63 years old {+/-} 5) for sustained investigation among whom 349 have retrospectively agreed to share their data openly. Repositories are findable through the unified interface of the Canadian Open Neuroscience Platform (https://portal.conp.ca/) and contain up to five years of longitudinal imaging data, cerebral fluid biochemistry, neurosensory capacities, cognitive, genetic, and medical information. Imaging data can be accessed openly at https://openpreventad.loris.ca while most of the other information, sensitive by nature, is accessible by qualified researchers at https://registeredpreventad.loris.ca. In addition to being a living resource for continued data acquisition, PREVENT-AD offers opportunities to facilitate understanding of AD pathogenesis.

neuroscience↗

bioRxiv2017

Family history and APOE4 risk for Alzheimer’s Disease impact the neural correlates of episodic memory by early midlife

Episodic memory impairment is a consistent, pronounced deficit in pre-clinical stages of late-onset Alzheimers disease (AD). Individuals with risk factors for AD exhibit altered brain function several decades prior to the onset of AD-related symptoms. In the current event-related fMRI study of spatial context memory we tested the hypothesis that middle-aged adults (MA; 40-58yrs) with a family history of late onset AD (MA+FH), or a combined +FH and apolipoprotein E {varepsilon}4 allele risk factors for AD (MA+FH+APOE4), will exhibit differences in encoding and retrieval-related brain activity, compared to - FH-APOE4 MA controls. We also hypothesized that the two at-risk MA groups will exhibit distinct patterns of correlation between brain activity and memory performance, compared to controls. To test these hypotheses we conducted multivariate task, and behavior, partial least squares analysis of fMRI data obtained during successful context encoding and retrieval. Our results indicate that even though there were no significant group differences in context memory performance, there were significant differences in brain activity and brain-behavior correlations involving hippocampus, left angular gyrus, cingulate, and precuneus in MA with AD risk factors, compared to controls. In addition, we observed that brain activity and brain-behavior correlations in anterior-medial PFC and in ventral visual cortex differentiated the two MA risk groups from each other, and from MAcontrols. This is the first study to show that there are differences in the brain areas engaged during context memory encoding and retrieval in middle-aged adults with +FH and +APOE-4 risk factors for late onset AD, compared to controls.

neuroscience↗