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Turner, M. R.

Publications and source records attributed to Turner, M. R..

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Effects of age on resting-state cortical networks

Understanding how ageing affects brain function remains a central challenge in neuroscience. Electrophysiological brain imaging techniques provide a near-direct measure of neuronal activity, which is useful for characterising neurophysiological health. They offer us the ability to track large-scale networks of functional activity with high temporal precision. The effects of healthy ageing on these networks remain poorly understood, in part due to small sample sizes and limited control for confounding factors in previous studies. Here, we analysed resting-state source-reconstructed magnetoencephalography (MEG) data from a large cross-sectional cohort of healthy adults (N =612, 18-88 years old) to characterise the effect of age using not only time-averaged (static), but also transient (dynamic) network activity. We examined time-averaged power and coherence across canonical frequency bands ({delta}, {theta}, , {beta}, {gamma}), as well as transient network dynamics identified using Hidden Markov Modelling. We included many confounding variables known to be affected by age, such as brain volume, as well as head size and position, which have previously been overlooked. Ageing was associated with frequency-specific changes in oscillatory power, with decreases in low-frequency ({delta}, {theta}) power and increases in high-frequency ({beta}) power. Coherence increased across all frequency bands and was positively associated with cognitive performance. Transient network analyses additionally revealed that frontal network occurrences declined with age, with evidence suggesting a compensatory role in supporting cognition. These findings provide a more comprehensive electrophysiological signature for healthy ageing and establish a baseline for detecting pathological change. HighlightsO_LIUsing source reconstructed magnetoencephalography data, we studied cortical functional networks of oscillatory activity from a large healthy population (612 subjects, 18-88 years old). C_LIO_LITime-averaged (static) network analysis in canonical frequency bands ({delta}, {theta}, , {beta}, {gamma}) showed: {beta} power and coherence increased with age; {delta}/{theta} power decreased with age, but coherence increased. Coherence in all frequencies increased with cognitive performance. C_LIO_LITransient (dynamic) network analysis showed frontal networks decreased in occurrence with age and their relation to cognitive performance showed that these changes were compensatory. The other networks showed a decreased occurrence with age. C_LIO_LIIn testing age and cognitive performance effects for statistical significance, we included a comprehensive set of confounds, such as brain volumes, head size and position, which has previously been overlooked. C_LIO_LIWe provide a comprehensive electrophysiological signature for healthy ageing and establish a baseline for detecting pathological change. C_LI

neuroscience↗

Glutathione Oxidation in Cerebrospinal Fluid as a Biomarker of Oxidative Stress in Amyotrophic Lateral Sclerosis

BackgroundOxidative stress is a key feature of several neurodegenerative diseases, including Amyotrophic Lateral Sclerosis (ALS). Identification of reliable biomarkers of oxidative stress would be beneficial for drug-target engagement studies. MethodsWe performed unbiased quantitative mass spectrometry (MS)-based analysis to measure changes in protein abundance and oxidation in cerebrospinal fluid (CSF) from a cohort of ALS patients and healthy controls at two time points (approximately four months apart) to capture disease progression. In addition, we developed a sensitive and targeted quantitative MS method to measure glutathione oxidation state in the same sets of CSF samples. ResultsProteomic analysis of CSF revealed statistically significant changes in the abundance of several proteins, including CHIT1, CHI3L1, CHI3L2 and COL18A1 in ALS patients compared to healthy controls at both time points. Several sites of protein oxidation were significantly altered in ALS compared to healthy controls, and total levels of reversible protein oxidation were elevated in ALS patients. Given that glutathione oxidation could be a useful biomarker of oxidative stress, we also measured glutathione and its oxidation state in CSF in the same cohorts of samples. Total GSH (tGSH), GSSG levels and the GSSG/GSH ratio were significantly higher in the ALS than in the healthy control group for both time points. For the first visit, fold changes of tGSH, GSSG, and GSSG/GSH ratio in ALS compared to HC were 1.33 (p = 0.0215), 1.54 (p = 0.0041) and 1.80 (p = 0.0454), respectively. For the second visit, these values were 1.50 (p = 0.0143), 2.00 (p = 0.0018) and 2.14 (p = 0.0120), respectively. Furthermore, we found positive correlations between disease duration until the first visit and total glutathione (tGSH), GSSG and GSSG/GSH ratio. Finally, there was a strong positive correlation between the total intensity of reversibly oxidised proteins and the ratio of GSSG/GSH in ALS patients at both visits. ConclusionWe propose that measuring levels of glutathione oxidation in CSF could act as a stratification biomarker to select ALS patients for antioxidant therapy and an approach to monitor the treatment response to therapeutic agents targeting oxidative stress.

neuroscience↗

Tensor Image Registration Library: Automated Deformable Registration of Stand-Alone Histology Images to Whole-Brain Post-Mortem MRI Data

BackgroundAccurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to automate the registration of stand-alone histology sections to whole-brain MRI data. MethodsOur pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slice photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline. ResultsAll 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks. ConclusionsOur open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies. HighlightsO_LINew software framework for prototyping bespoke image registration pipelines C_LIO_LIAutomated pipeline to register stand-alone histology sections to whole-brain MRI C_LIO_LINovel deformable slice-to-volume registration algorithm C_LIO_LINo strict necessity for serial histological sectioning for MRI-histology registration C_LI

neuroscience↗

The Digital Brain Bank: an open access platform for post-mortem datasets

Post-mortem MRI provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy, and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes - Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank release includes twenty one distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen non-human primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our labs investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides crossscale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.

neuroscience↗

Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T

Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology. Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices. Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex. Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS.

neuroscience↗

Correction of amyotrophic lateral sclerosis related phenotypes in induced pluripotent stem cell-derived motor neurons carrying a hexanucleotide expansion mutation in C9orf72 by CRISPR/Cas9 genome editing using homology-directed repair

The G4C2 hexanucleotide repeat expansion (HRE) in C9orf72 is the commonest cause of familial amyotrophic lateral sclerosis (ALS). A number of different methods have been used to generate isogenic control lines using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 and non-homologous end-joining (NHEJ) by deleting the repeat region with the risk of creating indels and genomic instability. In this study we demonstrate complete correction of an induced pluripotent stem cell (iPSC) line derived from a C9orf72-HRE positive ALS/FTD patient using CRISPR/Cas9 genome editing and homology directed repair (HDR), resulting in replacement of the excised region with a donor template carrying the wild-type repeat size to maintain the genetic architecture of the locus. The isogenic correction of the C9orf72 HRE restored normal expression and methylation at the C9orf72 locus, reduced intron retention in the edited lines, and abolished pathological phenotypes associated with the C9orf72 HRE expansion in iPSC derived motor neurons (iPSMNs). RNA sequencing of the mutant line identified 2220 differentially expressed genes compared to its isogenic control. Enrichment analysis demonstrated an over-representation of ALS relevant pathways, including calcium ion dependent exocytosis, synaptic transport and the KEGG ALS pathway, as well as new targets of potential relevance to ALS pathophysiology. Complete correction of the C9orf72 HRE in iPSMNs by CRISPR/Cas9 mediated HDR provides an ideal model to study the earliest effects of the hexanucleotide expansion on cellular homeostasis and the key pathways implicated in ALS pathophysiology.

neuroscience↗

Tensor Image Registration Library: Automated Non-Linear Registration of Sparsely Sampled Histological Specimens to Post-Mortem MRI of the Whole Human Brain

There is a need to understand the histopathological basis of MRI signal characteristics in complex biological matter. Microstructural imaging holds promise for sensitive and specific indicators of the early stages of human neurodegeneration but requires validation against traditional histological markers before it can be reliably applied in the clinical setting. Validation relies on a precise and preferably automatic method to align MRI and histological images of the same tissue, which poses unique challenges compared to more conventional MRI-to-MRI registration. A customisable open-source platform, Tensor Image Registration Library (TIRL) is presented. Based on TIRL, a fully automated pipeline was implemented to align small stained histological images with dissection photographs of corresponding tissue blocks and coronal brain slices, and further with high-resolution (0.5 mm) whole-brain post-mortem MRI data. The pipeline performed three separate deformable registrations to achieve accurate mapping between whole-brain MRI and small-slide histology coordinates. The robustness and accuracy of the individual registration steps were evaluated using both simulated data and real-life images from 6 different anatomical locations of one post-mortem human brain. The automated registration method demonstrated sub-millimetre accuracy in all steps, robustness against tissue damage, and good reproducibility between experiments. The method also outperformed manual landmark-based slice-to-volume registration, also correcting for curvatures in the slicing plane. Due to the customisability of TIRL, the pipeline can be conveniently adapted for other research needs and is therefore suitable for the large-scale comparison of routinely collected histology and MRI data. HighlightsO_LITIRL: new framework for prototyping bespoke image registration pipelines C_LIO_LIPipeline for automated registration of small-slide histology to whole-brain MRI C_LIO_LISlice-to-volume registration accounting for through-plane deformations C_LIO_LINo need for serial histological sampling C_LI

neuroscience↗