355 research outputs found
Brain connectivity during Alzheimer's disease progression and its cognitive impact in a transgenic rat model
The research of Alzheimer's disease (AD) in its early stages and its progression till symptomatic onset is essential to understand the pathology and investigate new treatments. Animal models provide a helpful approach to this research, since they allow for controlled follow-up during the disease evolution. In this work, transgenic TgF344-AD rats were longitudinally evaluated starting at 6 months of age. Every 3 months, cognitive abilities were assessed by a memory-related task and magnetic resonance imaging (MRI) was acquired. Structural and functional brain networks were estimated and characterized by graph metrics to identify differences between the groups in connectivity, its evolution with age, and its influence on cognition. Structural networks of transgenic animals were altered since the earliest stage. Likewise, aging significantly affected network metrics in TgF344-AD, but not in the control group. In addition, while the structural brain network influenced cognitive outcome in transgenic animals, functional network impacted how control subjects performed. TgF344-AD brain network alterations were present from very early stages, difficult to identify in clinical research. Likewise, the characterization of aging in these animals, involving structural network reorganization and its effects on cognition, opens a window to evaluate new treatments for the disease
Spatio-temporal metabolic rewiring in the brain of TgF344-AD rat model of Alzheimer's disease
Brain damage associated with Alzheimer's disease (AD) occurs even decades before the symptomatic onset, raising the need to investigate its progression from prodromal stages. In this context, animal models that progressively display AD pathological hallmarks (e.g. TgF344-AD) become crucial. Translational technologies, such as magnetic resonance spectroscopy (MRS), enable the longitudinal metabolic characterization of this disease. However, an integrative approach is required to unravel the complex metabolic changes underlying AD progression, from early to advanced stages. TgF344-AD and wild-type (WT) rats were studied in vivo on a 7 Tesla MRI scanner, for longitudinal quantitative assessment of brain metabolic profile changes using MRS. Disease progression was investigated at 4 time points, from 9 to 18 months of age, and in 4 regions: cortex, hippocampus, striatum, and thalamus. Compared to WT, TgF344-AD rats replicated common findings in AD patients, including decreased N-acetylaspartate in the cortex, hippocampus and thalamus, and decreased glutamate in the thalamus and striatum. Different longitudinal evolution of metabolic concentration was observed between TgF344-AD and WT groups. Namely, age-dependent trajectories differed between groups for creatine in the cortex and thalamus and for taurine in cortex, with significant decreases in Tg344-AD animals; whereas myo-inositol in the thalamus and striatum showed greater increase along time in the WT group. Additional analysis revealed divergent intra- and inter-regional metabolic coupling in each group. Thus, in cortex, strong couplings of N-acetylaspartate and creatine with myo-inositol in WT, but with taurine in TgF344-AD rats were observed; whereas in the hippocampus, myo-inositol, taurine and choline compounds levels were highly correlated in WT but not in TgF344-AD animals. Furthermore, specific cortex-hippocampus-striatum metabolic crosstalks were found for taurine levels in the WT group but for myo-inositol levels in the TgF344-AD rats. With a systems biology perspective of metabolic changes in AD pathology, our results shed light into the complex spatio-temporal metabolic rewiring in this disease, reported here for the first time. Age- and tissue-dependent imbalances between myo-inositol, taurine and other metabolites, such as creatine, unveil their role in disease progression, while pointing to the inadequacy of the latter as an internal reference for quantification
Motor and cortico-striatal-thalamic connectivity alterations in intrauterine growth restriction
BACKGROUND: Intrauterine growth restriction is associated with short-and long-term neurodevelopmental problems. Structural brain changes underlying these alterations have been described with the use of different magnetic resonance-based methods that include changes in whole structural brain networks. However, evaluation of specific brain circuits and its correlation with related functions has not been investigated in intrauterine growth restriction.OBJECTIVES: In this study, we aimed to investigate differences in tractography-related metrics in cortico-striatal-thalamic and motor networks in intrauterine growth restricted children and whether these parameters were related with their specific function in order to explore its potential use as an imaging biomarker of altered neurodevelopment.METHODS: We included a group of 24 intrauterine growth restriction subjects and 27 control subjects that were scanned at 1 year old; we acquired T1-weighted and 30 directions diffusion magnetic resonance images. Each subject brain was segmented in 93 regions with the use of anatomical automatic labeling atlas, and deterministic tractography was performed. Brain regions included in motor and cortico-striatal-thalamic networks were defined based in functional and anatomic criteria. Within the streamlines that resulted from the whole brain tractography, those belonging to each specific circuit were selected and tractography-related metrics that included number of streamlines, fractional anisotropy, and integrity were calculated for each network. We evaluated differences between both groups and further explored the correlation of these parameters with the results of socioemotional, cognitive, and motor scales from Bayley Scale at 2 years of age.RESULTS: Reduced fractional anisotropy (cortico-striatal-thalamic, 0.319 +/- 0.018 vs 0.315 +/- 0.015; P =.010; motor, 0.322 +/- 0.019 vs 0.319 +/- 0.020; P =.019) and integrity cortico-striatal-thalamic (0.407 +/- 0.040 vs 0.399 +/- 0.034; P =.018; motor, 0.417 +/- 0.044 vs 0.409 +/- 0.046; P =.016) in both networks were observed in the intrauterine growth restriction group, with no differences in number of streamlines. More importantly, strong specific correlation was found between tractography-related metrics and its relative function in both networks in intrauterine growth restricted children. Motor network metrics were correlated specifically with motor scale results (fractional anisotropy: rho = 0.857; integrity: rho = 0.740); cortico-striatal-thalamic network metrics were correlated with cognitive (fractional anisotropy: rho = 0.793; integrity, rho = 0.762) and socioemotional scale (fractional anisotropy: rho = 0.850; integrity: rho = 0.877).CONCLUSIONS: These results support the existence of altered brain connectivity in intrauterine growth restriction demonstrated by altered connectivity in motor and cortico-striatal-thalamic networks, with reduced fractional anisotropy and integrity. The specific correlation between tractography-related metrics and neurodevelopmental outcomes in intrauterine growth restriction shows the potential to use this approach to develop imaging biomarkers to predict specific neurodevelopmental outcome in infants who are at risk because of intrauterine growth restriction and other prenatal diseases
Early brain connectivity alterations and cognitive impairment in a rat model of Alzheimer's disease
Background: Animal models of Alzheimer's disease (AD) are essential to understanding the disease progression and to development of early biomarkers. Because AD has been described as a disconnection syndrome, magnetic resonance imaging (MRI)-based connectomics provides a highly translational approach to characterizing the disruption in connectivity associated with the disease. In this study, a transgenic rat model of AD (TgF344-AD) was analyzed to describe both cognitive performance and brain connectivity at an early stage (5 months of age) before a significant concentration of β-amyloid plaques is present. Methods: Cognitive abilities were assessed by a delayed nonmatch-to-sample (DNMS) task preceded by a training phase where the animals learned the task. The number of training sessions required to achieve a learning criterion was recorded and evaluated. After DNMS, MRI acquisition was performed, including diffusion-weighted MRI and resting-state functional MRI, which were processed to obtain the structural and functional connectomes, respectively. Global and regional graph metrics were computed to evaluate network organization in both transgenic and control rats. Results: The results pointed to a delay in learning the working memory-related task in the AD rats, which also completed a lower number of trials in the DNMS task. Regarding connectivity properties, less efficient organization of the structural brain networks of the transgenic rats with respect to controls was observed. Specific regional differences in connectivity were identified in both structural and functional networks. In addition, a strong correlation was observed between cognitive performance and brain networks, including whole-brain structural connectivity as well as functional and structural network metrics of regions related to memory and reward processes. Conclusions: In this study, connectivity and neurocognitive impairments were identified in TgF344-AD rats at a very early stage of the disease when most of the pathological hallmarks have not yet been detected. Structural and functional network metrics of regions related to reward, memory, and sensory performance were strongly correlated with the cognitive outcome. The use of animal models is essential for the early identification of these alterations and can contribute to the development of early biomarkers of the disease based on MRI connectomics
Effects of Orientation and Anisometry of Magnetic Resonance Imaging Acquisitions on Diffusion Tensor Imaging and Structural Connectomes
Diffusion-weighted imaging (DWI) quantifies water molecule diffusion within tissues and is becoming an increasingly used technique. However, it is very challenging as correct quantification depends on many different factors, ranging from acquisition parameters to a long pipeline of image processing. In this work, we investigated the influence of voxel geometry on diffusion analysis, comparing different acquisition orientations as well as isometric and anisometric voxels. Diffusion-weighted images of one rat brain were acquired with four different voxel geometries (one isometric and three anisometric in different directions) and three different encoding orientations (coronal, axial and sagittal). Diffusion tensor scalar measurements, tractography and the brain structural connectome were analyzed for each of the 12 acquisitions. The acquisition direction with respect to the main magnetic field orientation affected the diffusion results. When the acquisition slice-encoding direction was not aligned with the main magnetic field, there were more artifacts and a lower signal-to-noise ratio that led to less anisotropic tensors (lower fractional anisotropic values), producing poorer quality results. The use of anisometric voxels generated statistically significant differences in the values of diffusion metrics in specific regions. It also elicited differences in tract reconstruction and in different graph metric values describing the brain networks. Our results highlight the importance of taking into account the geometric aspects of acquisitions, especially when comparing diffusion data acquired using different geometries
Midbrain and pons MRI shape analysis and its clinical and CSF correlates in degenerative parkinsonisms: a pilot study
Multiple system atrophy; Neurofilament protein; Parkinsonian disordersAtròfia de sistemes mĂşltiples; ProteĂŻna del neurofilament; Trastorns de ParkinsonAtrofia multisistĂ©mica; ProteĂna de neurofilamento; Trastornos parkinsonianosObjectives: To conduct brainstem MRI shape analysis across neurodegenerative parkinsonisms and control subjects (CS), along with its association with clinical and cerebrospinal fluid (CSF) correlates.
Methodology: We collected demographic and clinical variables, performed planimetric and shape MRI analyses, and determined CSF neurofilament-light chain (NfL) levels in 84 participants: 11 CS, 12 with Parkinson's disease (PD), 26 with multiple system atrophy (MSA), 21 with progressive supranuclear palsy (PSP), and 14 with corticobasal degeneration (CBD).
Results: MSA featured the most extensive and significant brainstem shape narrowing (that is, atrophy), mostly in the pons. CBD presented local atrophy in several small areas in the pons and midbrain compared to PD and CS. PSP presented local atrophy in small areas in the posterior and upper midbrain as well as the rostral pons compared to MSA. Our findings of planimetric MRI measurements and CSF NfL levels replicated those from previous literature. Brainstem shape atrophy correlated with worse motor state in all parkinsonisms and with higher NfL levels in MSA, PSP, and PD.
Conclusion: Atypical parkinsonisms present different brainstem shape patterns which correlate with clinical severity and neuronal degeneration. In MSA, shape analysis could be further explored as a potential diagnostic biomarker. By contrast, shape analysis appears to have a rather limited discriminant value in PSP
Neonatal Neurobehavior and Diffusion MRI Changes in Brain Reorganization Due to Intrauterine Growth Restriction in a Rabbit Model
Background: Intrauterine growth restriction (IUGR) affects 5–10 % of all newborns and is associated with a high risk of abnormal neurodevelopment. The timing and patterns of brain reorganization underlying IUGR are poorly documented. We developed a rabbit model of IUGR allowing neonatal neurobehavioral assessment and high resolution brain diffusion magnetic resonance imaging (MRI). The aim of the study was to describe the pattern and functional correlates of fetal brain reorganization induced by IUGR. Methodology/Principal Findings: IUGR was induced in 10 New Zealand fetal rabbits by ligation of 40–50 % of uteroplacental vessels in one horn at 25 days of gestation. Ten contralateral horn fetuses were used as controls. Cesarean section was performed at 30 days (term 31 days). At postnatal day +1, neonates were assessed by validated neurobehavioral tests including evaluation of tone, spontaneous locomotion, reflex motor activity, motor responses to olfactory stimuli, and coordination of suck and swallow. Subsequently, brains were collected and fixed and MRI was performed using a high resolution acquisition scheme. Global and regional (manual delineation and voxel based analysis) diffusion tensor imaging parameters were analyzed. IUGR was associated with significantly poorer neurobehavioral performance in most domains. Voxel based analysis revealed fractional anisotropy (FA) differences in multiple brain regions of gray and white matter, including frontal, insular, occipital and temporal cortex, hippocampus, putamen, thalamus, claustrum, medial septa
Long-term functional outcomes and correlation with regional brain connectivity by MRI diffusion tractography metrics in a near-term rabbit model of intrauterine growth restriction
Background: Intrauterine growth restriction (IUGR) affects 5-10% of all newborns and is associated with increased risk of memory, attention and anxiety problems in late childhood and adolescence. The neurostructural correlates of long-term abnormal neurodevelopment associated with IUGR are unknown. Thus, the aim of this study was to provide a comprehensive description of the long-term functional and neurostructural correlates of abnormal neurodevelopment associated with IUGR in a near-term rabbit model (delivered at 30 days of gestation) and evaluate the development of quantitative imaging biomarkers of abnormal neurodevelopment based on diffusion magnetic resonance imaging (MRI) parameters and connectivity. Methodology: At +70 postnatal days, 10 cases and 11 controls were functionally evaluated with the Open Field Behavioral Test which evaluates anxiety and attention and the Object Recognition Task that evaluates short-term memory and attention. Subsequently, brains were collected, fixed and a high resolution MRI was performed. Differences in diffusion parameters were analyzed by means of voxel-based and connectivity analysis measuring the number of fibers reconstructed within anxiety, attention and short-term memory networks over the total fibers. Principal Findings: The results of the neurobehavioral and cognitive assessment showed a significant higher degree of anxiety, attention and memory problems in cases compared to controls in most of the variables explored. Voxel-based analysis (VBA) revealed significant differences between groups in multiple brain regions mainly in grey matter structures, whereas connectivity analysis demonstrated lower ratios of fibers within the networks in cases, reaching the statistical significance only in the left hemisphere for both networks. Finally, VBA and connectivity results were also correlated with functional outcome. Conclusions: The rabbit model used reproduced long-term functional impairments and their neurostructural correlates of abnormal neurodevelopment associated with IUGR. The description of the pattern of microstructural changes underlying functional defects may help to develop biomarkers based in diffusion MRI and connectivity analysis
Long-term reorganization of structural brain networks in a rabbit model of intrauterine growth restriction
Characterization of brain changes produced by intrauterine growth restriction (IUGR) is among the main challenges of modern fetal medicine and pediatrics. This condition affects 5-10% of all pregnancies and is associated with a wide range of neurodevelopmental disorders. Better understanding of the brain reorganization produced by IUGR opens a window of opportunity to find potential imaging biomarkers in order to identify the infants with a high risk of having neurodevelopmental problems and apply therapies to improve their outcomes. Structural brain networks obtained from diffusion magnetic resonance imaging (MRI) is a promising tool to study brain reorganization and to be used as a biomarker of neurodevelopmental alterations. In the present study this technique is applied to a rabbit animal model of IUGR, which presents some advantages including a controlled environment and the possibility to obtain high quality MRI with long acquisition times. Using a Q-Ball diffusion model, and a previously published rabbit brain MRI atlas, structural brain networks of 15 IUGR and 14 control rabbits at 70 days of age (equivalent to pre-adolescence human age) were obtained. The analysis of graph theory features showed a decreased network infrastructure (degree and binary global efficiency) associated with IUGR condition and a set of generalized fractional anisotropy (GFA) weighted measures associated with abnormal neurobehavior. Interestingly, when assessing the brain network organization independently of network infrastructure by means of normalized networks, IUGR showed increased global and local efficiencies. We hypothesize that this effect could reflect a compensatory response to reduced infrastructure in IUGR. These results present new evidence on the long-term persistence of the brain reorganization produced by IUGR that could underlie behavioral and developmental alterations previously described. The described changes in network organization have the potential to be used as biomarkers to monitor brain changes produced by experimental therapies in IUGR animal model
Competencias y habilidades transversales en AdministraciĂłn de Empresas. PropĂłsitos y realidades
Memoria ID-056. Ayudas de la Universidad de Salamanca para la innovaciĂłn docente, curso 2013-2014
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