Biology subjects

Smith, S. M.

Publications and source records attributed to Smith, S. M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

The developing Human Connectome Project fetal functional MRI release: Methods and data structures

Recent advances in fetal fMRI present a new opportunity for neuroscience to study functional human brain connectivity at the time of its emergence. Progress in the field however has been hampered by the lack of openly available datasets that can be exploited by researchers across disciplines to develop methods that would address the unique challenges associated with imaging and analysing functional brain in utero, such as unconstrained head motion, dynamically evolving geometric distortions, or inherently low signal-to-noise ratio. Here we describe the developing Human Connectome Projects release of the largest open access fetal fMRI dataset to date, containing 275 scans from 255 fetuses and spanning the period of 20.86 to 38.29 post-menstrual weeks. We present a systematic approach to its pre-processing, implementing multi-band soft SENSE reconstruction, dynamic distortion corrections via phase unwrapping method, slice-to-volume reconstruction and a tailored temporal filtering model, with attention to the prominent sources of structured noise in the in utero fMRI. The dataset is accompanied with an advanced registration infrastructure, enabling group-level data fusion, and contains outputs from the main intermediate processing steps. This allows for various levels of data exploration by the imaging and neuroscientific community, starting from the development of robust pipelines for anatomical and temporal corrections to methods for elucidating the development of functional connectivity in utero. By providing a high-quality template for further method development and benchmarking, the release of the dataset will help to advance fetal fMRI to its deserved and timely place at the forefront of the efforts to build a life-long connectome of the human brain.

neuroscience↗

bioRxiv2024

Multiscale Modes of Functional Brain Connectivity

Information processing in the brain spans from localised sensorimotor processes to higher-level cognition that integrates across multiple regions. Interactions between and within these subsystems enable multiscale information processing. Despite this multiscale characteristic, functional brain connectivity is often either estimated based on 10-30 distributed modes or parcellations with 100-1000 localised parcels, both missing across-scale functional interactions. We present Multiscale Probabilistic Functional Modes (mPFMs), a new mapping which comprises modes over various scales of granularity, thus enabling direct estimation of functional connectivity within- and across-scales. Crucially, mPFMs were not formulated, but emerged from data-driven multilevel Bayesian modelling of large functional MRI (fMRI) populations and every individual. We demonstrate that mPFMs capture both distributed brain modes and their co-existing subcomponents. In addition to validating mPFMs using simulations and real data, we show that mPFMs can predict [~]900 personalised traits from UK Biobank more accurately than current standard techniques. Therefore, mPFMs can offer a new basis for functional connectivity modelling and yield enhanced fMRI biomarkers for traits and diseases.

neuroscience↗

bioRxiv2024

HIV-1 controllers possess a unique CD8+ T-cell activation phenotype and loss of control is associated with increased expression of exhaustion markers

HIV-1 controllers are a rare population of individuals that exhibit spontaneous control of HIV-1 infection without antiretroviral therapy. These controllers can be categorized based on the level and mechanism of control. Understanding the mechanisms by which controllers maintain and eventually lose this ability would be highly valuable in HIV-1 cure or vaccine research. We explored whether CD8+ T cell exhaustion plays a role in the maintenance and loss of control by examining immune characteristics of HIV-1 controllers and controllers who lost control within the duration of the study. Previous work revealed the ability of CD8+ T-cells isolated from HIV-1 controllers to suppress HIV-1 replication in matched CD4+ T-cells ex vivo. Using flow cytometry, we analyzed exhaustion marker expression on CD8+ T-cells from these controllers and determined that they maintain a unique exhaustion profile as compared to HIV-negative individuals and standard progressors. The low level of T-cell exhaustion seen in controllers was reversed when these individuals lost control and showed increased viral loads. Immune checkpoint blockade targeting exhaustion markers was able to restore ex vivo control by CD8+ T-cells from former controllers. These results suggest that CD8+ T cell exhaustion compromises the ability to control viral replication in HIV-1 controllers. AUTHOR SUMMARYDespite the use of antiretroviral therapy, HIV continues to be a major public health issue that affects the lives of millions of people. Some infected people can control viral infection without therapy. The mechanism by which some people can control HIV infection at low, but detectable levels is unknown. In this study we examined the state of cytotoxic CD8+ T-cells in a group of HIV controllers and found that controllers maintain low levels of markers for a chronic state of activation called exhaustion. Loss of control correlated with increase in exhausted T-cells and for individuals who had recently lost control of infection we could restore protection in the cell culture dish by using immune checkpoint blockade drugs that affect exhaustion.

immunology↗

bioRxiv2024

Integrative genomic analysis identifies unique immune environments associated with immunotherapy response in diffuse large B cell lymphoma

Most diffuse large B-cell lymphoma (DLBCL) patients treated with bispecific antibodies (BsAb) or chimeric antigen receptor (CAR) T cells fail to achieve durable treatment responses, underscoring the need for a deeper understanding of mechanisms that regulate the immune environment and response to treatment. Here, an integrative, multi-omic approach was employed to characterize DLBCL immune environments, which effectively segregated DLBCLs into four quadrants - termed DLBCL-immune quadrants (IQ) - defined by cell-of-origin and immune-related gene set expression scores. Recurrent genomic alterations were enriched in each IQ, suggesting that lymphoma cell-intrinsic alterations contribute to orchestrating unique DLBCL immune environments. In relapsed/refractory DLBCL patients, DLBCL-IQ assignment correlated significantly with clinical benefit with the CD20 x CD3 BsAb, mosunetuzumab, but not with CD19-directed CAR T cells. DLBCL-IQ provides a new framework to conceptualize the DLBCL immune landscape and uncovers the differential impact of the endogenous immune environment on outcomes to BsAb and CAR T cell treatment.

cancer biology↗

bioRxiv2024

Automating the Human Connectome Project's Temporal ICA Pipeline

Functional magnetic resonance imaging (fMRI) data are dominated by noise and artifacts, with only a small fraction of the variance relating to neural activity. Temporal independent component analysis (tICA) is a recently developed method that enables selective denoising of fMRI artifacts related to physiology such as respiration. However, an automated and easy to use pipeline for tICA has not previously been available; instead, two manual steps have been necessary: 1) setting the group spatial ICA dimensionality after MELODICs Incremental Group-PCA (MIGP) and 2) labeling tICA components as artifacts versus signals. Moreover, guidance has been lacking as to how many subjects and timepoints are needed to adequately re-estimate the temporal ICA decomposition and what alternatives are available for smaller groups or even individual subjects. Here, we introduce a nine-step fully automated tICA pipeline which removes global artifacts from fMRI dense timeseries after sICA+FIX cleaning and MSMAll alignment driven by functionally relevant areal features. Additionally, we have developed an automated "reclean" Pipeline for improved spatial ICA (sICA) artifact removal. Two major automated components of the pipeline are 1) an automatic group spatial ICA (sICA) dimensionality selection for MIGP data enabled by fitting multiple Wishart distributions; 2) a hierarchical classifier to distinguish group tICA signal components from artifactual components, equipped with a combination of handcrafted features from domain expert knowledge and latent features obtained via self-supervised learning on spatial maps. We demonstrate that the dimensionality estimated for the MIGP data from HCP Young Adult 3T and 7T datasets is comparable to previous manual tICA estimates, and that the group sICA decomposition is highly reproducible. We also show that the tICA classifier achieved over 0.98 Precision-Recall Area Under Curve (PR-AUC) and that the correctly classified components account for over 95% of the tICA-represented variance on multiple held-out evaluation datasets including the HCP-Young Adult, HCP-Aging and HCP-Development datasets under various settings. Our automated tICA pipeline is now available as part of the HCP pipelines, providing a powerful and user-friendly tool for the neuroimaging community.

neuroscience↗

bioRxiv2023

Internally-consistent and fully-unbiased multimodal MRI brain template construction from UK Biobank: Oxford-MM

Anatomical MRI templates of the brain are essential to group-level analyses and image processing pipelines, as they provide a reference space for spatial normalisation. While it has become common for studies to acquire multimodal MRI data, many templates are still limited to one type of modality, usually either scalar or tensor-based. Aligning each modality in isolation does not take full advantage of the available complementary information, such as strong contrast between tissue types in structural images, or axonal organisation in the white matter in diffusion tensor images. Most existing strategies for multimodal template construction either do not use all modalities of interest to inform the template construction process, or do not use them in a unified framework. Here, we present multimodal, cross-sectional templates constructed from UK Biobank data: the OMM-1 template, and age-dependent templates for each year of life between 45 to 81. All templates are fully unbiased to represent the average shape of the populations they were constructed from, and internally consistent through jointly informing the template construction process with T1, T2-FLAIR and DTI data. The OMM-1 template was constructed with a multi-resolution, iterative approach using 240 individuals in the 50-55 year age range. The age-dependent templates were estimated using a Gaussian Process, which describes the change in average brain shape with age in 37,330 individuals. All templates show excellent contrast and alignment within and between modalities. The global brain shape and size is not preconditioned on existing templates, although maximal possible compatibility with MNI-152 space was maintained through rigid alignment. We showed benefits in registration accuracy across two datasets (UK Biobank and HCP), when using the OMM-1 as the template compared with FSLs MNI-152 template, and found that the use of age-dependent templates further improved accuracy to a small but detectable extent. All templates are publicly available and can be used as a new reference space for uni- or multimodal spatial alignment.

neuroscience↗

bioRxiv2023

MMORF - FSL's MultiMOdal Registration Framework

We present MMORF--FSLs MultiMOdal Registration Framework--a newly released nonlinear image registration tool designed primarily for application to MRI images of the brain. MMORF is capable of simultaneously optimising both displacement and rotational transformations within a single registration framework by leveraging rich information from multiple scalar and tensor modalities. The regularisation employed in MMORF promotes local rigidity in the deformation, and we have previously demonstrated how this effectively controls both shape and size distortion, and leads to more biologically plausible warps. The performance of MMORF is benchmarked against three established nonlinear registration methods--FNIRT, ANTs and DR-TAMAS--across four domains: FreeSurfer label overlap, DTI similarity, task-fMRI cluster mass, and distortion. Results show that MMORF performs as well as or better than all other methods across every domain--both in terms of accuracy and levels of distortion. MMORF is available as part of FSL, and its inputs and outputs are fully compatible with existing workflows. We believe that MMORF will be a valuable tool for the neuroimaging community, regardless of the domain of any downstream analysis, providing state-of-the-art registration performance that integrates into the rich and widely adopted suite of analysis tools in FSL.

neuroscience↗

bioRxiv2023

Evaluating functional brain organization in individuals and identifying contributions to network overlap

Individual differences in the spatial organization of resting state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting state networks can be derived using high quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that network overlap is indicative of linear additive coupling. These results suggest that regions of network overlap concurrently process information from all contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.

neuroscience↗

bioRxiv2023

Single-cell transcriptomic analysis of pea shoot development and cell-type-specific responses to boron deficiency

Understanding how nutrient stress impacts plant growth is fundamentally important to the development of approaches to improve crop production under nutrient limitation. Here we applied single-cell RNA sequencing to shoot apices of Pisum sativum grown under boron (B) deficiency. We identified up to fifteen cell clusters based on the clustering of gene expression profiles and verified cell identity with cell-type-specific marker gene expression. Different cell types responded differently to B deficiency. Specifically, the expression of photosynthetic genes in mesophyll cells (MCs) was down-regulated by B deficiency, consistent with impaired photosynthetic rate. Furthermore, the down-regulation of stomatal development genes in guard cells (GCs), including homologs of MUTE and TOO MANY MOUTHS, correlated with a decrease in stomatal density under B deficiency. We also constructed the developmental trajectory of the shoot apical meristem (SAM) cells and a transcription factor (TF) interaction network. The developmental progression of SAM to MC was characterized by up-regulation of genes encoding histones and chromatin assembly and remodeling proteins including homologs of FASCIATA1 (FAS1) and SWITCH DEFECTIVE/SUCROSE NON-FERMENTABLE (SWI/SNF) complex. However, B deficiency suppressed their expression, which helps to explain impaired SAM development under B deficiency. These results represent a major advance over bulk-tissue RNA-seq analysis in which cell-type-specific responses are lost and hence important physiological responses to B deficiency are missed. The reported approach and resources have potential applications well beyond P. sativum species and could be applied to various legumes to improve their adaptability to multiple nutrient or abiotic stresses.

plant biology↗

bioRxiv2023

Time-resolved molecular measurements reveal changes in astronauts during spaceflight

From the early days of spaceflight to current missions, astronauts continue to be exposed to multiple hazards that affect human health, including low gravity, high radiation, isolation during long-duration missions, a closed environment and distance from Earth. Their effects can lead to adverse physiological changes and necessitate countermeasure development and/or longitudinal monitoring. A time-resolved analysis of biological signals can detect and better characterize potential adverse events during spaceflight, ideally preventing them and maintaining astronauts wellness. Here we provide a time-resolved assessment of the impact of spaceflight on multiple astronauts (n=27) by studying multiple biochemical and immune measurements before, during, and after long-duration orbital spaceflight. We reveal space-associated changes of astronauts physiology on both the individual level and across astronauts, including associations with bone resorption and kidney function, as well as immune-system dysregulation.

molecular biology↗

bioRxiv2023

Geneneralising the HCP multimodal cortical parcellation to UK Biobank

The Human Connectome Project Multimodal Parcellation (HCP_MMP1.0) provides a robust in vivo map of the cerebral cortex, which demonstrates variability in structure and function that cannot be captured through diffeomorphic image registration alone. The HCP successfully employed a fully-connected neural network architecture to capture this variation, however it is unclear whether this approach generalises to other datasets with less rich imaging protocols. In this paper we propose and validate a novel geometric deep learning framework for generating individualised HCP_MMP1.0 parcellations in UK Biobank (UKB), an extremely rich resource that has led to numerous breakthroughs in neuroscience. To address substantial differences in image acquisition (for example, 6 minutes of resting-state fMRI per subject for UKB vs. 60 minutes per subject for HCP), we introduce a multi-step learning procedure including pretraining with a convolutional autoencoder. Compared to a fully-connected baseline, our proposed framework improved average detection rate across all areas by 10.4% (99.1% vs 88.7%), and detection of the worst performing area by 51.0% (80.9% vs. 29.9%). Importantly, this was not a result of the framework predicting one consistent parcellation across subjects, as visual inspection indicated that our method was sensitive to atypical cortical topographies. Code and trained models will be made available at https://www.github.com.

neuroscience↗

bioRxiv2023

Functional traits of young seedlings predict trade-offs in seedling performance in three neotropical forests.

O_LIUnderstanding the mechanisms that promote the coexistence of hundreds of species over small areas in tropical forest remains a challenge. Many tropical tree species are presumed to be functionally equivalent shade tolerant species that differ in performance trade-offs between survival in shade and the ability to quickly grow in sunlight. C_LIO_LIVariation in plant functional traits related to resource acquisition is thought to predict variation in performance among species, perhaps explaining community assembly across habitats with gradients in resource availability. Many studies have found low predictive power, however, when linking trait measurements to species demographic rates. C_LIO_LISeedlings face different challenges recruiting on the forest floor and may exhibit different traits and/or performance trade-offs than older individuals face in the eventual adult niche. Seed mass is the typical proxy for seedling success, but species also differ in cotyledon strategy (reserve vs photosynthetic) or other seedling traits. These can cause species with the same average seed mass to have divergent performance in the same habitat. C_LIO_LIWe combined long-term studies of seedling dynamics with functional trait data collected at a standard developmental stage in three diverse neotropical forests to ask whether variation in coordinated suites of traits predicts variation among species in demographic performance. C_LIO_LIAcross hundreds of species in Ecuador, Panama, and Puerto Rico, we found seedlings displayed correlated suites of leaf, stem, and root traits, which strongly correlated with seed mass and cotyledon strategy. Variation among species in seedling functional traits, seed mass, and cotyledon strategy were strong predictors of trade-offs in seedling growth and survival. C_LIO_LIOur findings highlight the importance of cotyledon strategy in addition to seed mass as a key component of seed and seedling biology. These results also underscore the importance of matching the ontogenetic stage of the trait measurement to the stage of demographic dynamics. C_LIO_LISynthesis: With strikingly consistent patterns across three tropical forests, we find strong evidence for the promise of functional traits to provide mechanistic links between seedling form and demographic performance. C_LI

ecology↗

bioRxiv2022

Inactivated voltage-gated sodium channels are preferentially targeted in cinacalcet block of mouse neocortical action potentials

Voltage-gated sodium channel (VGSC) activation is essential for action potential generation in the brain. Allosteric calcium-sensing receptor (CaSR) agonist, cinacalcet, strongly and ubiquitously inhibits VGSC currents in neocortical neurons via an unidentified, G-protein-dependent blocking molecule. The mechanisms by which VGSC characteristics influence cinacalcet-mediated inhibition are not well understood. Here, using whole-cell patch clamp methods, we investigated the voltage-dependence of cinacalcet-mediated inhibition of VGSCs and the channel state preference of cinacalcet. The rate of inhibition of VGSC currents was accelerated at more depolarized holding potentials. Cinacalcet shifted the voltage-dependence of both fast and slow inactivation of VGSCs in the hyperpolarizing direction. Utilizing a simple model, the voltage-dependence of VGSC current inhibition may be explained if the affinity of the blocking molecule to the channel states follows the sequence: fast-inactivated > slow-inactivated > resting. The state dependence of block contributes to the non-linearity of action potential block by cinacalcet. This dynamic and abundant signaling pathway by which G-proteins regulate VGSC currents provides an important voltage-dependent mechanism for modulating central neuronal excitability. Key points summaryVoltage-gated sodium channels are essential for the action potential generation and propagation that is central to physiological function in excitable cells. VGSC inhibitors are useful therapies to treat epilepsy, pain, and cardiac arrhythmias. Cinacalcet inhibits VGSC currents strongly and the underlying G-protein dependent signaling pathway occurs in the vast majority of neocortical and hippocampal neurons. Here we demonstrate that cinacalcet inhibits the VGSC current by activating a downstream blocking molecule that preferentially binds to the fast-inactivated state, that the blocking molecule stabilizes the inactivated states, and that cinacalcet impacts neuronal excitability in a non-linear manner. Characterization of the mechanism by which cinacalcet operates will facilitate the determination of its role in regulating neocortical excitability and the identification of new therapeutic targets for epilepsy, pain, and arrythmias.

neuroscience↗

bioRxiv2022

Anandamide reduces excitability by preferentially targeting somatic VGSCs via CB1

Endogenous cannabinoid signaling is vital for important brain functions and can be modified pharmacologically to treat pain, epilepsy, and posttraumatic stress disorder. Endocannabinoid mediated changes to excitability are predominantly attributed to 2-arachidonoylglycerol at synapses. Here we identify a pathway in the neocortex by which anandamide, the other major endocannabinoid, powerfully inhibits sodium conductances in the soma resulting in a loss of neuronal excitability. This pathway is mediated by the cannabinoid receptor, and its activation results in a decrease of recurrent action potential generation. The synthetic cannabinoid, WIN 55,212-2, also inhibits VGSC currents indicating this pathway is positioned to mediate the actions of exogenous cannabinoids. HighlightsAnandamide (AEA), a major endocannabinoid, indirectly inhibits VGSC currents in neocortical neurons. This prevalent signaling pathway involves AEA activation of CB1 and other G-protein-coupled receptors localized to the intracellular compartment of neurons. CB1 activation by AEA reduces VGSC availability at the soma but not at the axonal compartment suggesting tighter functional coupling between VGSCs and CB1 at the cell body. Cannabinoid action on somatic CB1 inhibits VGSCs with high efficacy, providing a parallel pathway outside of nerve terminals, by which these ligands reduce neuronal excitability in the neocortex.

neuroscience↗

bioRxiv2022

Reduced affinity of calcium sensing-receptor heterodimers and reduced mutant homodimer trafficking combine to impair function in a mouse model of Familial Hypocalciuric Hypercalcemia Type 1

Heterozygous loss-of-function mutation of the calcium sensing-receptor (CaSR), causes familial hypocalciuric hypercalcemia type 1 (FHH1), a typically benign condition characterized by mild hypercalcemia. In contrast, homozygous mutation of this dimer-forming G-protein coupled receptor manifests as the lethal neonatal severe hyperparathyroidism (NSHPT). To investigate the mechanisms by which CaSR mutations lead to these distinct disease states, we engineered wild-type (WT) and an exon 5-deficient disease-causing mutation, and transfected expression constructs into human embryonic kidney (HEK) cells. WT protein was mainly membrane-expressed whereas the mutant CaSR protein (mCaSR) was confined to the cytoplasm. Co-expression of WT CaSR directed mCaSR to the cell membrane. In assays of CaSR function, increases in extracellular [Ca2+] ([Ca2+]o) increased intracellular [Ca2+] ([Ca2+]i) in cells expressing WT CaSR while the response was reduced in cells coexpressingmutant and WT receptor. Untransfected cells or those expressing mCaSR alone, showed minimal, equivalent responses to increased [Ca2+]o. Immunoprecipitation experiments confirmed an association between mutant and wild-type CaSR. The affinity of the WT CaSR for calcium was three times greater than that of the heterodimer. The maximal functional response to [Ca]o was dependent on localization of CaSR to the membrane level and independent of homo- or heterodimerizations. In summary, these results suggest that heterodimerization of WT and mCaSR receptors, rescues the trafficking defect of the mutant receptors and also reduces the affinity of the WT-mutant heterodimer for [Ca]o. In contrast, the homozygous mutants do not produce functional receptors on cell membrane. These data indicate how substantial differences between signaling of hetero- and homodimeric mutants lead to profound differences in the severity of disease in heterozygous and homozygous carriers of these mutations.

cell biology↗

bioRxiv2022

Paired Associates Learning is Disrupted After Unilateral Parietal Lobe Controlled Cortical Impact in Rats: A Trial-by-Trial Behavioral Analysis

Approximately 60-70 million people suffer from a traumatic brain injury (TBI) each year. As animal models continue to be paramount in understanding and treating cognitive impairment following TBI, the necessity of testing intervention strategies in clinically relevant settings cannot be ignored. This study used a unilateral parietal lobe controlled cortical impact (CCI) model of TBI and tested rats on a touchscreen-based associative learning task, Paired Associates Learning (PAL). In humans, PAL has been used to assess cognitive deficits in stimulus-location association in a multitude of disease states, including TBI. To date, the extent to which a rat model of TBI produces deficits in PAL has not yet been reported, although the usage of PAL will be important for understanding the clinical consequences of cognitive impairment post-injury and throughout intervention treatment. This study details the behavioral and histological consequences of the CCI injury model and closes a translational research gap between basic and clinical TBI research. HIGHLIGHTSO_LIPAL performance declines in a rat model of TBI. C_LIO_LIResponse-driven bias in PAL becomes elevated after TBI. C_LIO_LIInflammatory microglial response in the thalamus correlates with PAL deficit. C_LI

animal behavior and cognition↗

bioRxiv2022

Neuronopathic GBA1 L444P mutation accelerates glucosylsphingosine levels and formation of hippocampal alpha-synuclein inclusions

The most common genetic risk factor for Parkinsons disease (PD) is heterozygous mutations in the GBA1 gene which encodes for the lysosomal enzyme, glucocerebrosidase (GCase). GCase impairments are associated with an accumulation of abnormal -synuclein (-syn) called Lewy pathology, which characterizes PD. PD patients heterozygous for the GBA1 L444P mutation (GBA1+/L444P) have a 5.6-fold increased risk of cognitive impairments. In this study, we used GBA1+/L444P mice to determine the effects of this severe GBA1 mutation on lipid metabolism, expression of synaptic proteins, behavior, and -syn inclusion formation. GBA1+/L444P mice showed reduced GCase activity in limbic brain regions and expressed lower levels of hippocampal vGLUT1 compared to wildtype (GBA1+/+) mice. GBA+/L444P mice also demonstrated impaired fear conditioning, but no motor deficits. We show, using mass spectrometry, that mutant GCase and age increased levels of glucosylsphingosine (GlcSph), but not glucosylceramide (GlcCer), in the brains and serum of GBA1+/L444P mice. Aged GBA1+/+ mice also showed increased levels of GlcSph, and decreased GlcCer. To model disease pathology, templated -syn pathology was used. -Syn inclusions were increased in the hippocampus of GBA1+/L444P mice compared to GBA1+/+ mice, but not in the cortex, or substantia nigra pars compacta (SNc). Pathologic -syn did not cause a loss of dopamine neurons in the SNc. Treatment with a GlcCer synthase inhibitor prevented loss of cortical -syn inclusions, but not loss of dopamine neurons. Overall, these data suggest the critical importance to evaluate the contribution of hippocampal pathologic -syn and brain and serum glucosylsphingosine in synucleinopathies. SIGNIFICANCE STATEMENTSynucleinopathies, such as Parkinsons disease (PD) and Dementia with Lewy bodies (DLB), are both pathologically characterized by abnormal -synuclein (-syn). Mutant GBA1 is a risk factor for both PD and DLB where a reduction of glucocerebrosidase (GCase) activity is seen. Collectively, this indicates the significance of evaluating mutant GCase in synucleinopathies. Our data suggest the critical importance to evaluate the contribution of hippocampal pathologic -syn and brain and serum glucosylsphingosine (GlcSph) accumulation in synucleinopathies. Moreover, these pathologic outcomes may contribute to the nonmotor symptoms clinically observed in PD and DLB. Our findings highlight the importance of GlcSph as a relevant biomarker for future therapeutics.

neuroscience↗

bioRxiv2022

Causal Inference on Neuroimaging Data with Mendelian Randomisation

While population-scale neuroimaging studies offer the promise of discovery and characterisation of subtle risk factors, massive sample sizes increase the power for both meaningful associations and those attributable to confounds. This motivates the need for causal modelling of observational data that goes beyond statements of association and towards deeper understanding of complex relationships between individual traits and phenotypes, clinical biomarkers, genetic variation, and brain-related measures of health. Mendelian randomisation (MR) presents a way to obtain causal inference on the basis of genetic data and explicit assumptions about the relationship between genetic variables, exposure and outcome. In this work, we provide an introduction to and overview of causal inference methods based on Mendelian randomisation, with examples involving imaging-derived phenotypes from UK Biobank to make these methods accessible to neuroimaging researchers. We motivate the use of MR techniques, lay out the underlying assumptions, introduce common MR methods and focus on several scenarios in which modelling assumptions are potentially violated, resulting in biased effect estimates. Importantly, we give a detailed account of necessary steps to increase the reliability of MR results with rigorous sensitivity analyses.

neuroscience↗