Tract-based spatial statistics (TBSS): application to detecting white matter tract variation in mild hypoxic-ischemic neonates

The aim of this study is to employ tract-based spatial statistics (TBSS) to analyze the voxel-wise differences in DTI parameters between normal and mild hypoxic-ischemic (HI) neonatal brains. Forty-one full term neonates (24 normal controls and 17 with mild HI injury) and 31 preterm neonates (20 normal controls and 11 with mild HI injury) underwent T1 weighted imaging, T2 weighted imaging and diffusion tensor imaging (DTI) within 28 days after birth. The voxel differences of fractional anisotropy (FA), lambda1, lambda2, and lambda3 values between mild HI group and control group were analyzed in preterm and full term neonates respectively. The significantly decreased FA with increased lambda2, lambda3 in corticospinal tract, genu of corpus callosum (GCC), external capsule (EC) and splenium of the corpus callosum (SCC) in mild HI neonates suggested deficits or delays in both myelination and premyelination. Such impaired corticospinal tract, in both preterm and term neonates, may directly lead to the subsequent poor motor performance. Impaired EC and SCC, the additional injured sites observed in full term neonates with mild HI injury, may be causally responsible for the dysfunction in coordination and integration. In conclusion, TBSS provides an objective, independent and sensitive method for DTI data analysis of neonatal white matter alterations after mild HI injury.published_or_final_versio

Frontal-Subcortical Protein Expression following Prenatal Exposure to Maternal Inflammation

BACKGROUND: Maternal immune activation (MIA) during prenatal life is a risk factor for neurodevelopmental disorders including schizophrenia and autism. Such conditions are associated with alterations in fronto-subcortical circuits, but their molecular basis is far from clear. METHODOLOGY/PRINCIPAL FINDINGS: Using two-dimensional differential in-gel electrophoresis (2D-DIGE) and mass spectrometry, with targeted western blot analyses for confirmation, we investigated the impact of MIA on the prefrontal and striatal proteome from an established MIA mouse model generated in C57B6 mice, by administering the viral analogue PolyI:C or saline vehicle (control) intravenously on gestation day (GD) 9. In striatum, 11 proteins were up-regulated and 4 proteins were down-regulated in the PolyI:C mice, while 10 proteins were up-regulated and 7 proteins down-regulated in prefrontal cortex (PFC). These were proteins involved in the mitogen-activated protein kinase (MAPK) signaling pathway, oxidation and auto-immune targets, including dual specificity mitogen-activated protein kinase kinase 1 (MEK), eukaryotic initiation factor (eIF) 4A-II, creatine kinase (CK)-B, L-lactate dehydrogenase (LDH)-B, WD repeat-containing protein and NADH dehydrogenase in the striatum; and guanine nucleotide-binding protein (G-protein), 14-3-3 protein, alpha-enolase, olfactory maker protein and heat shock proteins (HSP) 60, and 90-beta in the PFC. CONCLUSIONS/SIGNIFICANCE: This data fits with emerging evidence for disruption of critical converging intracellular pathways involving MAPK pathways in neurodevelopmental conditions and it shows considerable overlap with protein pathways identified by genetic modeling and clinical post-mortem studies. This has implications for understanding causality and may offer potential biomarkers and novel treatment targets for neurodevelopmental conditions

DTIPrep: quality control of diffusion-weighted images

pre-printIn the last decade, diffusion MRI (dMRI) studies of the human and animal brain have been used to investigate a multitude of pathologies and drug-related effects in neuroscience research. Study after study identifies white matter (WM) degeneration as a crucial biomaker for all these diseases. The tool of choice for studying WM is dMRI however, dMRI has inherently low signal-to-noise ratio and its acquisition requires a relatively long scan time; in fact, the high loads required occasionally stress scanner hardware past the point of physical failure

Early Stage Alterations in White Matter and Decreased Functional Interhemispheric Hippocampal Connectivity in the 3xTg Mouse Model of Alzheimer’s Disease

Alzheimer’s disease (AD) is characterized in the late stages by amyloid-β (Aβ) plaques and neurofibrillary tangles. Nevertheless, recent evidence has indicated that early changes in cerebral connectivity could compromise cognitive functions even before the appearance of the classical neuropathological features. Diffusion tensor imaging (DTI), resting-state functional magnetic resonance imaging (rs-fMRI) and volumetry were performed in the triple transgenic mouse model of AD (3xTg-AD) at 2 months of age, prior to the development of intraneuronal plaque accumulation. We found the 3xTg-AD had significant fractional anisotropy (FA) increase and radial diffusivity (RD) decrease in the cortex compared with wild-type controls, while axial diffusivity (AD) and mean diffusivity (MD) were similar. Interhemispheric hippocampal connectivity was decreased in the 3xTg-AD while connectivity in the caudate putamen (CPu) was similar to controls. Most surprising, ventricular volume in the 3xTg-AD was four times larger than controls. The results obtained in this study characterize the early stage changes in interhemispheric hippocampal connectivity in the 3xTg-AD mouse that could represent a translational biomarker to human models in preclinical stages of the AD

Brain in flames - animal models of psychosis: utility and limitations

The neurodevelopmental hypothesis of schizophrenia posits that schizophrenia is a psychopathological condition resulting from aberrations in neurodevelopmental processes caused by a combination of environmental and genetic factors which proceed long before the onset of clinical symptoms. Many studies discuss an immunological component in the onset and progression of schizophrenia. We here review studies utilizing animal models of schizophrenia with manipulations of genetic, pharmacologic, and immunological origin. We focus on the immunological component to bridge the studies in terms of evaluation and treatment options of negative, positive, and cognitive symptoms. Throughout the review we link certain aspects of each model to the situation in human schizophrenic patients. In conclusion we suggest a combination of existing models to better represent the human situation. Moreover, we emphasize that animal models represent defined single or multiple symptoms or hallmarks of a given disease

Voxel-based analysis of postnatal white matter microstructure in mice exposed to immune challenge in early or late pregnancy

Maternal infection during prenatal life is a risk factor for neurodevelopmental disorders, including schizophrenia and autism, in the offspring We and others have reported white mater microstructure abnormalities in prefrontal-striato-temporal networks in these disorders In addition we have shown that early rather than late maternal immune challenge in the mouse model precipitates ventricular volume change and impairs sensorimotor gating similar to that found in schizophrenia However, it is not known whether the timing of maternal infection has a differential impact upon white matter microstructural indices Therefore this study directly tested the effect of early or late gestation maternal immune activation on post-natal white matter microstructure in the mouse The viral mimic PolyI C was administered on day 9 or day 17 of gestation In-vivo diffusion tensor imaging (DTI) was carried out when the offspring reached adulthood We describe a novel application of voxel-based analysis to evaluate fractional anisotrophy (FA) In addition we conducted a preliminary immunohistochemical exploration of the oligodendrocyte marker, 2',3'-cyclic nucleotide 3'-phosphodiesterase (CNPase), to determine whether differences in myelination might contribute to any changes in FA observed Our results provide experimental evidence that prenatal exposure to inflammation elicits widespread differences in FA throughout fronto-striatal-limbic circuits compared to control saline exposure. Moreover, FA changes were more extensive in the group exposed earliest in gestation (C) 2010 Elsevier Inc All rights reserve

Automatisation et optimisation de l’analyse de données de résonance magnétique pour les cerveaux de rongeur en développement

Les lésions de la matière blanche parfois observées chez les enfants prématurés peuvent avoir des conséquences lourdes sur le développement cognitif, comportemental et social de l’enfant. Il est important de réagir tôt pour éviter des conséquences irrémédiables. Malheureusement, à l’heure actuelle, la capacité d’un traitement à protéger les habilités cognitives ou comportementales ne peut être évaluée qu’à un stade développemental avancé, et il est alors généralement trop tard pour un traitement alternatif. L’établissement de biomarqueurs qui corrèlent avec l’issue neuro¬développementale et qui permettent d’évaluer en phase aiguë l’effet du traitement serait très bénéfique. À cet effet, l’imagerie par résonance magnétique (IRM) est un outil de choix. Son caractère non-invasif permet d’étudier sans risques additionnels cette population sensible. Le présent mémoire évalue la capacité des technologies de résonance magnétique à détecter les lésions diffuses de la matière blanche dans un modèle animal. Ce modèle animal reproduit les lésions observées chez l’humain prématuré en induisant une réaction inflammatoire par l’injection de lipopolysaccharides (LPS) directement dans le cerveau au troisième jour postnatal (P3). L’objectif principal du travail présenté est le développement d’outils opérateur-indépendants et optimaux pour l’analyse des données de résonance magnétique du raton. En particulier, ces outils sont conçus pour l’analyse des données d’imagerie du tenseur de diffusion (DTI) et pour l’analyse de données de spectroscopie (MRS). Ces outils sont ensuite appliqués à la caractérisation du modèle animal via l’analyse de deux jeux de données. Le premier est constitué de données DTI acquises à P24 ex vivo sur deux groupes, un sham (témoin) et un ayant subi une injection de LPS. Le second comprend des données MRS et DTI acquises en phase aiguë de la réaction inflammatoire (P4) in vivo dans trois groupes : sham, LPS et un troisième ayant reçu l’injection de LPS et un traitement neuroprotecteur par l’injection de l’antagoniste recombinant de l’IL1-ß (IL1-Ra), une cytokine pro-inflammatoire. Il existe différentes approches à l’analyse des données DTI : par région d’intérêt, par histogrammes, par tractographie et par comparaisons voxel-par-voxel. Principalement, dans ce mémoire, deux méthodes voxel-par-voxel ont été étudiées : "Voxel-Based Analysis" ou VBA et "Tract-Based Spatial Statistics" ou TBSS. VBA compare les populations en calculant une statistique pour chaque point de l’espace. TBSS, développé pour répondre à certaines limitations de VBA, compare les deux groupes en conduisant les tests sur un sous-ensemble des voxels de la matière blanche, le squelette de matière blanche. Ces deux méthodes reposent sur une étape préliminaire majeure : la normalisation spatiale. La normalisation permet de s’assurer, jusqu’à un certain degré, que pour l’ensemble de la population les voxels comparés correspondent à une même région anatomique. Pour ce projet, trois méthodes de normalisation spatiale utilisant chacune un algorithme de recalage différent ont été implémentées : Symmetric Group-Wise Normalization avec l’algorithme Symmetric Normalization (SyN, de la suite Advanced Normalization Tools ou ANTs), la normalisation spatiale non-biaisée du module Diffusion Tensor Toolkit (DTI-TK) et une normalisation spatiale sur base du sujet le plus représentatif de la population avec l’algorithme FMRIB Non-linear Image Registration Tool (FNIRT, de la suite FMRIB Software Library ou FSL). L’analyse automatique des données de diffusion peut donc se faire via différentes combinaisons de normalisation spatiale (ANTs, DTI-TK, FSL) et d’analyse voxel-par-voxel (VBA, TBSS). Il est généralement difficile de déterminer la meilleure combinaison et il n’y a pas de principes établis pour guider ce choix. Ceci est étudié dans l’article « Near equivalence of three automated diffusion tensor analysis pipelines in a neonate rat model of periventricular leukomalacia » où chacune des normalisations spatiales implémentées est testée en combinaison avec VBA et TBSS. L’étude démontre que les résultats sont très cohérents entre les différentes approches mais met en évidence des limitations de VBA et TBSS. Les résultats suggèrent qu’appliquer la normalisation DTI-TK en combinaison avec TBSS permet une analyse plus robuste, du moins pour les ratons et dans le cadre de ce modèle animal. Des modules d’analyse par histogramme et de parcellisation automatique de la matière blanche sous-corticale ont également été implémentés et testés. L’analyse des données de spectroscopie est plus directe, dans le sens où les paramètres de l’analyse sont moins influents sur le résultat. De ce fait, un pipeline unique et opérateur¬indépendant a été implémenté, incorporant le prétraitement des données et la quantification des métabolites à l’aide du Linear Combination Model (LCModel). Ces pipelines DTI/MRS ont été appliqués à l’étude du modèle animal et ont permis de démontrer la sensibilité des technologies de résonance magnétique à ce type de lésion. En effet, l’analyse des données de diffusion ex vivo a souligné une lésion persistante et diffuse de la matière blanche sous-corticale du côté ipsilatéral. En phase aiguë de l’inflammation, les données de diffusion in vivo indiquent une forte diminution de la diffusivité radiale et axiale. La spectroscopie a également permis de mettre en évidence des changements métaboliques avec notamment une réduction de N-acetylaspartate, glutamate, phosphorylethanolamine et une augmentation de lipides et de macromolécules. Le traitement à l’IL1-Ra a permis de modérer les changements observés en DTI et en MRS. En conclusion, différents outils « état-de-l’art » relatifs à l’analyse de données DTI et MRS ont été développés et appliqués avec succès à l’étude d’un modèle animal des lésions de la matière blanche de l’enfant prématuré. Les résultats permettent de considérer la DTI et la MRS comme technologies prometteuses pour la caractérisation et le suivi de ce type de lésion, celles-ci étant sensibles à la lésion en phase aiguë de la réaction inflammatoire ainsi qu’à un stade développemental plus avancé. Cependant, afin de permettre une interprétation solide des changements observés, il est nécessaire de confronter les observations IRM à d’autres méthodes d’imagerie telles que l’immuno-histologie, la microscopie électronique ou encore l’optique par cohérence tomographique.----------ABSTRACT White matter injuries observed in the preterm infant may have heavy consequences on the cognitive, behavioral and social development of the child and it is imperative to act early in order to avoid definitive repercussions. Unfortunately, for now, the efficacy of neuroprotective treatments can only be assessed at an advanced developmental stage when it is already too late to experiment with an alternative treatment. Finding biomarkers that correlate with the neuro¬developmental outcome and allow to assess the efficacy of the treatment at an early stage would be greatly beneficial. Magnetic resonance imaging (MRI) is a prominent technology with potential for establishing quantitative biomarkers. Moreover, its non-invasive nature allows to study this sensitive population without additional risks. This thesis assesses the use of MRI technologies for the study of diffuse white matter injury in an animal model. This animal model reproduces the lesions observed in human preterms by inducing an inflammatory reaction in the neonate rat brain by an injection of lipopolysaccharides (LPS) at postnatal day 3 (P3). The main goal of this project is to develop user-independent and optimal tools for the analysis of magnetic resonance data of the rat pup brain. Specifically, these tools are designed for the analysis of diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) data. The secondary goal is to apply these tools to the study of the animal model of white matter injury. The data are made up of two different sets. The first one is constituted of DTI data only acquired ex vivo at P24 on two different groups: one sham and one that underwent an LPS injection. The second set of data comprises both DTI and MRS data. Data were acquired in vivo at the acute phase of injury (P4) on three different groups: sham, LPS and a third group that was injected with LPS and received a neuroprotective treatment by administration of the recombinant antagonist of IL1¬ß (IL1-Ra), a pro-inflammatory cytokine. There are several ways to conduct the analysis of DTI data: by region of interest, by histograms, by tractography or by conducting voxelwise comparisons. Primarily, in this thesis, two voxelwise methods were studied: “Voxel-Based Analysis” or VBA and “Tract-Based Spatial Statistics” or TBSS. VBA compares populations by computing a statistic at every voxel of the image. TBSS, which has been developed to alleviate some limitations of VBA, runs the statistical tests on a subset of voxels in the white matter, the white matter skeleton. Both these methods strongly rely on a specific image processing step: the spatial normalization. The normalization ensures, to a certain extent, that the voxels correspond to a same anatomical region across the subjects. Here, three normalization approaches, each using a different registration algorithm, were implemented: Symmetric Group-Wise Normalization using the Symmetric Normalization (SyN) algorithm of the Advanced Normalization Tools (ANTs) toolbox; the unbiased normalization of the Diffusion Tensor Toolkit (DTI-TK); and a normalization based on the population most representative subject using FMRIB Non-linear Image Registration Tool (FNIRT) algorithm of the FMRIB Software Library (FSL). Automatic diffusion data analysis can therefore be performed using combinations of a certain spatial normalization (ANTs, DTI-TK, FSL) and a voxelwise analysis (VBA, TBSS). Determining the best combination is not straight-forward and there are no principled ways to choose one combination over another. This was studied in the submitted paper “Near equivalence of three automated diffusion tensor analysis pipelines in a neonate rat model of periventricular leukomalacia” in which each of the implemented normalization methods were tested in combination with VBA and TBSS. Results demonstrate great coherence among the tested pipelines but also underlines both VBA and TBSS limitations. The study also suggests that, for the rat pup data of this animal model, combining DTI-TK normalization with TBSS might yield a more robust analysis. Other analysis modules implemented for the study of DTI data include analysis by histogram and by automatic parcelling of sub-cortical white matter. Magnetic spectroscopy data analysis does not depend as strongly to the processing pipeline as diffusion data. Therefore, a unique and user-independent pipeline was implemented. This pipeline incorporates data preprocessing operations and automatic metabolites quantification using the Linear Combination Model (LCModel). These pipelines were applied to the study of the animal model and the results demonstrated that magnetic resonance technologies are sensitive to these injuries. The ex vivo diffusion data exhibited a persistent and diffuse injury of the sub-cortical white matter on the ipsilateral side. At the acute phase, the in vivo diffusion data showed a strong decrease of axial and radial diffusivities. The spectroscopy data also underlined metabolic perturbations with essentially a decrease of N-acetylaspartate, glutamate, phosphorylethanolamine and an increase of lipids and macromolecules. The IL1-Ra neuroprotective treatment seemed effective and moderated the amplitude of these changes in both DTI and MRS. In conclusion, various state-of-the-art analysis tools for DTI and MRS data were developed and successfully applied to the study of an animal model of diffuse white matter injury of the preterm baby. Results indicate that DTI and MRS are potential tools for the characterisation and monitoring of this pathology, these being sensitive to the injury in the acute and chronic stages. However, in order to further strengthen the interpretation of these results, it is necessary that these be supported by other imaging technologies such as immuno-histology, electronic microscopy or optical coherence tomography

Genome-wide DNA methylation changes in a mouse model of infection-mediated neurodevelopmental disorders

Background Prenatal exposure to infectious or inflammatory insults increases the risk of neurodevelopmental disorders. Using a well-established mouse model of prenatal viral-like immune activation, we examined whether this pathological association involves genome-wide DNA methylation differences at single nucleotide resolution. Methods Prenatal immune activation was induced by maternal treatment with the viral mimetic polyriboinosinic-polyribocytidylic acid in middle or late gestation. Following behavioral and cognitive characterization of the adult offspring (n = 12 per group), unbiased capture array bisulfite sequencing was combined with subsequent matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and quantitative real-time polymerase chain reaction analyses to quantify DNA methylation changes and transcriptional abnormalities in the medial prefrontal cortex of immune-challenged and control offspring. Gene ontology term enrichment analysis was used to explore shared functional pathways of genes with differential DNA methylation. Results Adult offspring of immune-challenged mothers displayed hyper- and hypomethylated CpGs at numerous loci and at distinct genomic regions, including genes relevant for gamma-aminobutyric acidergic differentiation and signaling (e.g., Dlx1, Lhx5, Lhx8), Wnt signaling (Wnt3, Wnt8a, Wnt7b), and neural development (e.g., Efnb3, Mid1, Nlgn1, Nrxn2). Altered DNA methylation was associated with transcriptional changes of the corresponding genes. The epigenetic and transcriptional effects were dependent on the offspring\u2019s age and were markedly influenced by the precise timing of prenatal immune activation. Conclusions Prenatal viral-like immune activation is capable of inducing stable DNA methylation changes in the medial prefrontal cortex. These long-term epigenetic modifications are a plausible mechanism underlying the disruption of prefrontal gene transcription and behavioral functions in subjects with prenatal infectious histories