In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution.
For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most whole-brain neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell-types’ contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell-types extensively predicts tissue damage in thirteen neurodegenerative conditions, including early- and late-onset Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and three clinical variants of frontotemporal lobar degeneration (behavioural variant, semantic and non-fluent primary progressive aphasia) along with associated 3-repeat and 4-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell-types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorders pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.
Abstract For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types’ contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in thirteen neurodegenerative conditions, including early-and late-onset Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and three clinical variants of frontotemporal lobar degeneration (behavioural variant, semantic and non-fluent primary progressive aphasia) along with associated 3-repeat and 4-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorders pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.
Abstract Genes associated with risk for brain disease exhibit characteristic expression patterns that reflect both anatomical and cell type relationships. Brain-wide transcriptomic patterns of disease risk genes provide a molecular based signature for identifying disease association, often differing from common phenotypic classification. Analysis of adult brain-wide transcriptomic patterns associated with 40 human brain diseases identified five major transcriptional patterns, represented by tumor-related, neurodegenerative, psychiatric and substance abuse, and two mixed groups of diseases. Brain disease risk genes exhibit unique anatomic transcriptomic signatures, based on differential co-expression, that often uniquely identify the disease. For cortical expressing diseases, single nucleus data in the middle temporal gyrus reveals cell type expression gradients separating neurodegenerative, psychiatric, and substance abuse diseases. By homology mapping of cell types across mouse and human, transcriptomic disease signatures are found largely conserved, but with psychiatric and substance abuse related diseases showing important specific species differences. These results describe the structural and cellular transcriptomic landscape of disease in the adult brain, highlighting significant homology with the mouse yet indicating where human data is needed to further refine our understanding of disease-associated genes.
Summary Vulnerability to obesity includes eating in response to food cues, which acquire incentive value through conditioning. The conditioning process is largely subserved by dopamine, theorized to encode the discrepancy between expected and actual rewards, known as the reward prediction error (RPE). Ghrelin is a gut-derived homeostatic hormone that triggers hunger and eating. Despite extensive evidence that ghrelin stimulates dopamine, it remains unknown in humans if ghrelin modulates food cue learning. Here we show using functional magnetic resonance imaging that intravenously administered ghrelin increased RPE-related activity in dopamine-responsive areas during food odor conditioning in healthy volunteers. Participants responded faster to food odor-associated cues and perceived them to be more pleasant following ghrelin injection. Ghrelin also increased functional connectivity between hippocampus and ventral striatum. Our work demonstrates that ghrelin promotes the ability of cues to acquire incentive salience, and has implications for the development of vulnerability to obesity.
ABSTRACT Background MRI studies show that obese adults have reduced grey (GM) and white matter (WM) tissue density as well as altered WM integrity. It remains to be examined if bariatric surgery induces structural brain changes. The aim of this study is to characterize GM and WM density changes in a longitudinal setting, comparing pre- and post-operation and to determine whether these changes are related to inflammation and cardiometabolic markers. Methods 29 severely obese participants (age: 45.9±7.8 years) scheduled to undergo sleeve gastrectomy (SG) were recruited. High-resolution T1-weighted anatomical images were acquired 1 month prior to as well as 4 and 12 months after surgery. GM and WM densities were quantified using voxel-based morphometry (VBM). Circulating lipid profile, glucose, insulin and inflammatory markers (interleukin (IL)-6, C-reactive protein (CRP) and lipopolysaccharide-binding protein (LBP) were measured at each time point. A linear mixed effect model was used to compare brain changes before and after SG, controlling for age, gender, initial BMI and diabetic status. To assess the associations between changes in adiposity, metabolism and inflammation and changes in GM or WM density, the mean GM and WM densities were extracted across all the participants using atlas, and linear mixed-effect models were used. Results As expected, weight, BMI, waist circumference and neck circumference significantly decreased after SG compared with baseline (p<0.001 for all). A widespread increase in WM density was observed after surgery, particularly in the cerebellum, brain stem, cerebellar peduncle, cingulum, corpus callosum and corona radiata (p<0.05, after FDR correction). Significant increases in GM density were observed 4 months after SG compared to baseline in several brain regions such as the bilateral occipital cortex, temporal cortex, precentral gyrus and cerebellum as well as right fusiform gyrus, right hippocampus and right insula. These GM and WM increases were more pronounced and widespread after 12 months and were significantly associated with post-operative weight loss and the improvement of metabolic alterations. Our linear mixed-effect models also showed strong associations between post-operative reductions in LBP, a marker of inflammation, and increased WM density. To confirm our results, we tested whether the peak of each significant region showed BMI-related differences in an independent dataset (Human Connectome Project). We matched a group of severely obese individuals with a group of lean individuals for age, gender and ethnicity. Severe obesity was associated with reduced WM density in the brain stem and cerebellar peduncle as well as reduced GM density in cerebellum, regions that significantly changed after surgery (p<0.01 for all clusters). Conclusions Bariatric surgery-induced weight loss and improvement in metabolic alterations is associated with widespread increases in WM and GM densities. These post-operative changes overlapped with baseline brain differences between severely obese and normal-weight individuals, which may suggest a recovery of WM and GM alterations after bariatric surgery.
Abstract Magnetic resonance imaging (MRI) is a valuable non-invasive tool that has been widely used for in vivo investigations of brain morphometry and microstructural characteristics. Postmortem MRIs can provide complementary anatomical and microstructural information to in vivo imaging and ex vivo neuropathological assessments without compromising the sample for future investigations. We have developed a postmortem MRI protocol for the brain specimens of the Douglas-Bell Canada Brain Bank (DBCBB), the largest brain bank in Canada housing over 3000 neurotypical and diseased brain specimens, that allows for acquisition of high-resolution 3T and 7T MRIs. Our protocol can be used to scan DBCBB specimens with minimal tissue manipulation, allowing for feasibly scanning large numbers of postmortem specimens while retaining the quality of the tissue for downstream histology and immunohistochemistry assessments. We demonstrate the robustness of this protocol in spite of the dependency of image quality on fixation by acquiring data on the first day of extraction and fixation, to over twenty years post fixation. The acquired images can be used to perform volumetric segmentations, cortical thickness measurements, and quantitative analyses which can be potentially used to link MRI-derived and ex vivo histological measures, assaying both the normative organization of the brain and ex vivo measures of pathology.
ABSTRACT Parkinson’s Disease (PD) is a progressive neurodegenerative disorder characterized by motor and cognitive deficits. The neurodegenerative process is thought to move stereotypically from the brainstem up to the cerebral cortex, possibly reflecting the spread of toxic alpha-synuclein molecules. Using a large, longitudinal, multi-center database of de novo PD patients, we tested whether focal reductions in cortical thickness could be explained by disease spread from a subcortical “disease reservoir” along the brain’s connectome. PD patients (n=105) and matched controls (n=57) underwent T1-MRI at entry and one year later. Over this period, PD patients demonstrated significantly greater loss of cortical thickness than healthy controls in parts of the left occipital and bilateral frontal lobes and right somatomotor-sensory cortex. Cortical regions with greater connectivity (measured functionally or structurally) to a “disease reservoir” evaluated via MRI at baseline demonstrated greater atrophy one year later. The atrophy pattern in the ventral frontal lobes resembled one described in certain cases of Alzheimer’s disease. Moreover, a multiple linear regression model suggested that cortical thinning was associated with impaired cognitive function at follow-up. Our findings suggest that disease propagation to the cortex in PD follows neural connectivity, and that disease spread to the cortex may herald the onset of cognitive impairment.
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