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Richardson, J. C.

Publications and source records attributed to Richardson, J. C..

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Modelling ferroptosis in a human microglial line by sequential exposure to iron and GPX4 inhibition

Excessive iron accumulation is a pathological feature of several neurodegenerative diseases (NDDs) and a growing body of evidence suggests that ferroptosis, an iron-dependent form of regulated cell death (RCD) driven by lipid peroxidation, is implicated in their pathogenesis. Microglia, the brains resident immune cells, buffer iron overload but become susceptible to ferroptotic death, exacerbating neuroinflammation and neuronal loss. To uncover the molecular events leading to microglial ferroptosis, we established a human microglial ferroptosis model using the HMC3 cell line. This model recapitulates core features of ferroptosis, including increased reactive oxygen species (ROS) and peroxidation of lipids at the membrane, both rescued by Ferrostatin-1 (Fer-1). We used this model to perform integrated multi-omics profiling and identified significant dysregulation in lipid species, notably an accumulation of sterols, including oxysterols such as the 7-oxo-cholesterol, alongside the oxidation of polyunsaturated fatty acid (PUFA) characteristic of ferroptosis. Transcriptomic and proteomic analyses corroborated these findings, revealing the upregulation of genes and proteins involved in the mevalonate pathway and cholesterol metabolism. Importantly, the increased expression of some of these key metabolic genes was also reversed by Fer-1 treatment, indicating their role in a pre-ferroptotic signature. Our model provides a novel platform for investigating early molecular events in microglia ferroptosis. Integrating these findings into future investigations could uncover new protective mechanisms against microglia ferroptosis at the crossroad between ROS level mitigation and sterol metabolism.

neuroscience↗

Epilepsy-linked kinase CDKL5 phosphorylates voltage-gated calcium channel Cav2.3, altering inactivation kinetics and neuronal excitability

Developmental and epileptic encephalopathies (DEEs) are a group of rare childhood disorders characterized by severe epilepsy and cognitive deficits. Numerous DEE genes have been discovered thanks to advances in genomic diagnosis, yet putative molecular links between these disorders are unknown. CDKL5 deficiency disorder (CDD, DEE2), one of the most common genetic epilepsies, is caused by loss-of-function mutations in the brain-enriched kinase CDKL5. To elucidate CDKL5 function, we looked for CDKL5 substrates using a SILAC-based phosphoproteomic screen. We identified the voltage-gated Ca2+ channel Cav2.3 (encoded by CACNA1E) as a novel physiological target of CDKL5 in mice and humans. Recombinant channel electrophysiology and interdisciplinary characterization of Cav2.3 phosphomutant mice revealed that loss of Cav2.3 phosphorylation leads to channel gain-of-function via slower inactivation and enhanced cholinergic stimulation, resulting in increased neuronal excitability. Our results thus show that CDD is partly a channelopathy. The properties of unphosphorylated Cav2.3 closely resemble those described for CACNA1E gain-of-function mutations causing DEE69, a disorder sharing clinical features with CDD. We show that these two single-gene diseases are mechanistically related and could be ameliorated with Cav2.3 inhibitors.

neuroscience↗

TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

BackgroundNeurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimers disease (AD), to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Here we performed genome-wide association study (GWAS) analyses using all three biomarkers as outcome. MethodsDNA and cerebrospinal fluid (CSF) samples originated from the European Medical Information Framework AD Multimodal Biomarker Discovery (EMIF-AD MBD) study. Overlapping genotype/phenotype data were available for n=671 (NF-L), 677 (YKL-40), and 672 (Ng) individuals. GWAS analyses applied linear regression models adjusting for relevant covariates. FindingsWe identify novel genome-wide significant associations with markers in TMEM106B and CSF levels of NF-L. Additional novel signals were observed with DNA variants in CPOX and CSF levels of YKL-40. Lastly, we confirmed previous work suggesting that YKL-40 levels are regulated by cis protein quantitative trait loci (pQTL) in CHI3L1. InterpretationOur study provides important new insights into the genetic architecture underlying inter-individual variation in all three tested AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

genomics↗

Modular slowing of resting-state dynamic Functional Connectivity as a marker of cognitive dysfunction induced by sleep deprivation

Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks -including Rapid Visual Processing (RVP, assessing sustained visual attention)- and dFC speed quantified at the level of functional subnetworks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module. HighlightsO_LISleep Deprivation (SD) slows down the random walk in FC space implemented by Dynamic Functional Connectivity (dFC) at rest. C_LIO_LIWhole-brain level slowing of dFC speed does not selectively correlate with fine and taskspecific changes in performance C_LIO_LIWe quantify dFC speed separately for different link-based modules coordinated by distinct regional "meta-hubs" C_LIO_LIModular dFC speed variations capture subtle and task-specific variations of cognitive performance induced by SD. C_LI Author summaryWe interpreted dynamic Functional Connectivity (dFC) as a random walk in the space of possible FC networks performed with a quantifiable "speed". Here, we analyze a fMRI dataset in which subjects are scanned and cognitively tested both before and after Sleep Deprivation (SD), used as a reversible model of cognitive dysfunction. While global dFC speed slows down after a sleepless night, it is not a sufficiently sensitive metric to correlate with fine and specific cognitive performance changes. To boost the capacity of dFC speed analyses to account for fine and specific cognitive decline, we introduce the notion of modular dFC speed. Capitalizing on an edge-centric measure of functional connectivity, which we call Meta-Connectivity, we isolate subgraphs of FC describing relatively independent random walks (dFC modules) and controlled by distinct "puppet masters" (meta-hubs). We then find that variations of the random walk speed of distinct dFC modules now selectively correlate with SD-induced variations of performance in the different tasks. This is in agreement with the fact that different subsystems - distributed but functionally distinct- oversee different tasks. The high sensitivity of modular dFC analyses bear promise of future applications to the early detection and longitudinal characterization of pathologies such as Alzheimers disease.

neuroscience↗

Genome-wide association study of Alzheimer’s disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

Alzheimers disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimers Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures of amyloid-beta (A{beta}) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to A{beta}42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A{beta}38 and CSF-A{beta}40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-A{beta} and -tau related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

genomics↗

Effects of rising amyloidβ on hippocampal synaptic transmission, microglial response and cognition in APPSwe/PSEN1M146V transgenic mice

BackgroundProgression of Alzheimers disease is thought initially to depend on rising amyloid{beta} and its synaptic interactions. Transgenic mice (TASTPM; APPSwe/PSEN1M146V) show altered synaptic transmission, compatible with increased physiological function of amyloid{beta}, before plaques are detected. Recently, the importance of microglia has become apparent in the human disease. Similarly, TASTPM show a close association of plaque load with upregulated microglial genes.\n\nMethodsCA1 Synaptic transmission and plasticity were investigated using in vitro electrophysiology. Migroglial relationship to plaques was examined with immunohistochemistry. Behaviour was assessed with a forced-alternation T-maze, open field, light/dark box and elevated plus maze.\n\nFindingsThe most striking finding is the increase in microglial numbers in TASTPM, which, like synaptic changes, begins before plaques are detected. Further increases and a reactive phenotype occur later, concurrent with development of larger plaques. Long-term potentiation is initially enhanced at pre-plaque stages but decrements with the initial appearance of plaques. Finally, despite altered plasticity, TASTPM have little cognitive deficit, even with a heavy plaque load, although they show altered non-cognitive behaviours.\n\nInterpretationThe pre-plaque synaptic changes and microglial proliferation are presumably related to low, non-toxic amyloid{beta} levels in the general neuropil and not directly associated with plaques. However, as plaques grow, microglia proliferate further, clustering around plaques and becoming phagocytic. Like in humans, even when plaque load is heavy, without development of neurofibrillary tangles and neurodegeneration, these alterations do not result in cognitive deficits. Behaviours are seen that could be consistent with pre-diagnosis changes in the human condition.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThere is a large body of research examining many aspects of phenotypes associated with mouse models of Alzheimers disease - a PubMed search for the terms Alzheimer* AND mouse returns in excess of 21000 articles. However, there are few systematic articles pulling together pathological, functional (electrophysiological), and behavioural analyses across the life-span of such models. There is also a number of conflicting outcomes, for example reports of impaired versus enhanced synaptic plasticity; cognitive impairments or not.\n\nRecently, the importance of microglia in Alzheimers disease has come to the fore in human Genome Wide Association Studies (GWAS), with variants of a number of microglial genes identified as risk-factors for developing the disease. Interestingly, we have recently reported that Trem2 and other genes identified as risk-factors in humans are strongly up regulated in close association to plaque development in the mouse model used in this study. Moreover, this previous study predicted two of the most recently identified genes that were identified in GWAS since the publication of our paper.\n\nWe have previously used this model to identify the earliest synaptic changes and shown changes in release of glutamate, the primary excitatory neurotransmitter in the brain, to occur even before plaques are detectable.\n\nAdded value of this studyBy studying this transgenic mouse model of Alzheimers disease, throughout the development of plaques, from prior to detection through to heavy plaque loads, we have been able to identify a clear time course of key phenotypic changes associated with early disease. In particular, this study identifies the very early changes in microglia and can separate the time course of the microglial phenotype. In addition, we detail the changes in synaptic plasticity over time and importantly identify that, like in humans in the absence of Tau tangles or neurodegeneration, considerable synaptic changes can occur and a heavy plaque load without resulting in substantial cognitive loss.\n\nImplications of all the available evidenceOur data indicate that rising amyloid beta prior to detectable plaque deposition results in changes in synaptic function that likely reflects an enhanced physiological effect of amyloid beta. At this stage, microglia proliferate but do not activate. Once plaques begin to appear, microglia migrate to surround the plaque and become phagocytic, likely targeting dystrophic synapses and neurites caused by the cloud of highly-toxic amyloid beta around the plaque. Similarly to humans, who have plaques but no tangles and have yet to develop substantial neurodegeneration, cognitive deficits are not seen, even with a heavy plaque load; behavioural changes are limited to anxiety-like effects.\n\nThis investigation of the parallel time-course of events highlights the probability that, if progression of disease can be reversed or slowed early enough, before Tau tangles and substantial neurodegeneration occur, the symptoms of cognitive decline could be very largely avoided. Moreover, it suggests that the substantial increases in microglia number and upregulation of their specific gene expression in association with plaques, is not associated with cognitive loss and may indeed be protective.

neuroscience↗

A TauP301L mouse model of dementia; development of pathology, synaptic transmission, microglial response and cognition throughout life

BackgroundLate stage Alzheimers disease and other dementias are associated with neurofibrillary tangles and neurodegeneration. Here we describe a mouse (TauD35) carrying human Tau with the P301L mutation that results in Tau hyperphosphorylation and tangles. Previously we have compared gene expression in TauD35 mice to mice which develop plaques but no tangles. A similar comparison of other pathological features throughout disease progression is made here between amyloid{beta} and Tau mice described in Parts I and II of this study.\n\nMethodsIn vitro CA1 patch clamp and field recordings were used to investigate synaptic transmission and plasticity. Plaque load and microglia were investigated with immunohistochemistry. Cognition, locomotor activity and anxiety-related behaviours were assessed with a forced-alternation T-maze, open field and light/dark box.\n\nResultsTransgene copy number in TauD35 mice fell into two groups (HighTAU and LowTAU), allowing assessment of dose-dependent effects of overexpression and resulting in tangle load increasing 100-fold for a 2-fold change in protein levels. Tangles were first detected at 8 (HighTAU) or 13 months (LowTAU) but the effects on synaptic transmission and plasticity and behaviour were subtle. However severe neurodegeneration occurred in HighTAU mice at around 17 months preceded by considerable proliferation but little additional activation of microglia. Proliferation only started as neurodegeneration began at 13 months. Similarly to HighTau mice at 13 months of age, LowTAU mice at 24 months of age showed a comparable tangle load and microglial proliferation. However, LowTAU mice showed no neurodegeneration at this stage and considerable microglial activation, stressing the dependence of these effects on overexpression and/or age.\n\nConclusionsComparison of the effects of amyloid{beta} and plaques without tangles in a model of preclinical Alzheimers disease to the effects of tangles without amyloid{beta} plaques in the late stage model described here may clarify the progressive stages of Alzheimers disease. While Tau hyperphosphorylation and neurofibrillary tangles are eventually sufficient to cause severe neurodegeneration, initial effects on synaptic transmission and the immune response are subtle. In contrast while even with a heavy plaque load little if any neurodegeneration occurs, considerable effects on synaptic transmission and the immune system result, even before plaques are detectable.

neuroscience↗

Genetic and real-world clinical data, combined with empirical validation, nominate JAK-STAT signalling as a target for Alzheimer’s Disease therapeutic development

As Genome Wide Association Studies (GWAS) have grown in size, the number of genetic variants that have been nominated for an increasing number of diseases has correspondingly increased. Despite this increase in the number of associated SNPs per disease, their biological interpretation has in many cases remained elusive. To address this, we have combined GWAS results with an orthogonal source of evidence, namely real-world, routinely collected clinical data from more than 6 million patients in order to drive target nomination. First we show that when examined at a pathway level, analysis of all GWAS studies groups Alzheimers disease (AD) in a cluster with disorders of immunity and inflammation. Using clinical data we show that the degree of comorbidity of these diseases with AD correlates with the strength of their genetic association with molecular participants in the JAK-STAT pathway. Using four independent open-science datasets we then find evidence for altered regulation of JAK-STAT pathway genes in AD. Finally, we use both in vitro and in vivo rodent models to demonstrate that A{beta} induces gene expression of key drivers of this pathway, providing experimental evidence validating these data-driven observations. These results therefore nominate JAK-STAT anomalies as a prominent aetiopathological event in AD and hence potential target for therapeutic development, and moreover demonstrate a de-novo multi-modal approach to derive information from rapidly increasing genomic datasets.\n\nOne Sentence SummaryCombining evidence from genome wide association studies, real-world clinical and cohort molecular data together with experimental studies in rodent model systems nominates JAK-STAT signaling as an aetiopathological event in Alzheimers disease

bioinformatics↗