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Several studies have shown white matter (WM) abnormalities in Alzheimer’s disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aβ-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aβ-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics. [ABSTRACT FROM AUTHOR]

Several studies have shown decreased cerebral blood flow (CBF) in Alzheimer's disease (AD). However, the role of hypoperfusion in the disease pathogenesis remains unclear. Combining arterial spin labeling MRI, PET, and CSF biomarkers, we investigated the associations between gray matter (GM)-CBF and the key mechanisms in AD including amyloid-β (Aβ) and tau pathology, synaptic and axonal degeneration. Further, we applied a disease progression modeling to characterize the temporal sequence of different AD biomarkers. Lower perfusion was observed in temporo-occipito-parietal cortex in the Aβ-positive cognitively impaired compared to both Aβ-negative and Aβ-positive cognitively unimpaired individuals. In participants along the AD spectrum, GM-CBF was associated with tau, synaptic and axonal dysfunction, but not Aβ in similar cortical regions. Axonal degeneration was further associated with hypoperfusion in cognitively unimpaired individuals. Disease progression modeling revealed that GM-CBF disruption Followed the abnormality of biomarkers of Aβ, tau and brain atrophy. These findings indicate that tau tangles and neurodegeneration are more closely connected with GM-CBF changes than Aβ pathology. Although subjected to the sensitivity of the employed neuroimaging techniques and the modeling approach, these findings suggest that hypoperfusion might not be an early event associated with the build-up of Aβ in preclinical phase of AD. [ABSTRACT FROM AUTHOR]

Background: The majority of individuals with dementia will suffer from behavioral and psychological symptoms of dementia (BPSD). These symptoms contribute to functional impairment and caregiver burden.Objective: To characterize BPSD in Alzheimer's disease (AD), vascular dementia (VaD), mixed (Mixed) dementia, Parkinson's disease dementia (PDD), dementia with Lewy bodies (DLB), frontotemporal dementia (FTD), and unspecified dementia in individuals residing in long-term care facilities.Methods: We included 10,405 individuals with dementia living in long-term care facilities from the Swedish registry for cognitive/dementia disorders (SveDem) and the Swedish BPSD registry. BPSD was assessed with the Neuropsychiatric Inventory - Nursing Home Version (NPI-NH). Multivariate logistic regression models were used to evaluate the associations between dementia diagnoses and different BPSDs.Results: The most common symptoms were aberrant motor behavior, agitation, and irritability. Compared to AD, we found a lower risk of delusions (in FTD, unspecified dementia), hallucinations (FTD), agitation (VaD, PDD, unspecified dementia), elation/euphoria (DLB), anxiety (Mixed, VaD, unspecified dementia), disinhibition (in PDD), irritability (in DLB, FTD, unspecified dementia), aberrant motor behavior (Mixed, VaD, unspecified dementia), and sleep and night-time behavior changes (unspecified dementia). Higher risk of delusions (DLB), hallucinations (DLB, PDD), apathy (VaD, FTD), disinhibition (FTD), and appetite and eating abnormalities (FTD) were also found in comparison to AD.Conclusion: Although individuals in our sample were diagnosed with different dementia disorders, they all exhibited aberrant motor behavior, agitation, and irritability. This suggests common underlying psychosocial or biological mechanisms. We recommend prioritizing these symptoms while planning interventions in long-term care facilities. [ABSTRACT FROM AUTHOR]

Although recent clinical trials targeting amyloid-β in Alzheimer's disease have shown promising results, there is increasing evidence suggesting that understanding alternative disease pathways that interact with amyloid-β metabolism and amyloid pathology might be important to halt the clinical deterioration. In particular, there is evidence supporting a critical role of astroglial activation and astrocytosis in Alzheimer's disease. However, so far, no studies have assessed whether astrocytosis is independently related to either amyloid-β or tau pathology in vivo. To address this question, we determined the levels of the astrocytic marker GFAP in plasma and CSF of 217 amyloid-β-negative cognitively unimpaired individuals, 71 amyloid-β-positive cognitively unimpaired individuals, 78 amyloid-β-positive cognitively impaired individuals, 63 amyloid-β-negative cognitively impaired individuals and 75 patients with a non-Alzheimer's disease neurodegenerative disorder from the Swedish BioFINDER-2 study. Participants underwent longitudinal amyloid-β (18F-flutemetamol) and tau (18F-RO948) PET as well as cognitive testing. We found that plasma GFAP concentration was significantly increased in all amyloid-β-positive groups compared with participants without amyloid-β pathology (P < 0.01). In addition, there were significant associations between plasma GFAP with higher amyloid-β-PET signal in all amyloid-β-positive groups, but also in cognitively normal individuals with normal amyloid-β values (P < 0.001), which remained significant after controlling for tau-PET signal. Furthermore, plasma GFAP could predict amyloid-β-PET positivity with an area under the curve of 0.76, which was greater than the performance achieved by CSF GFAP (0.69) and other glial markers (CSF YKL-40: 0.64, soluble TREM2: 0.71). Although correlations were also observed between tau-PET and plasma GFAP, these were no longer significant after controlling for amyloid-β-PET. In contrast to plasma GFAP, CSF GFAP concentration was significantly increased in non-Alzheimer's disease patients compared to other groups (P < 0.05) and correlated with amyloid-β-PET only in amyloid-β-positive cognitively impaired individuals (P = 0.005). Finally, plasma GFAP was associated with both longitudinal amyloid-β-PET and cognitive decline, and mediated the effect of amyloid-β-PET on tau-PET burden, suggesting that astrocytosis secondary to amyloid-β aggregation might promote tau accumulation. Altogether, these findings indicate that plasma GFAP is an early marker associated with brain amyloid-β pathology but not tau aggregation, even in cognitively normal individuals with a normal amyloid-β status. This suggests that plasma GFAP should be incorporated in current hypothetical models of Alzheimer's disease pathogenesis and be used as a non-invasive and accessible tool to detect early astrocytosis secondary to amyloid-β pathology. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) is characterized by motor deficits and brain alterations having a detrimental impact on balance, gait, and cognition. Intensive physical exercise can induce changes in the neural system, potentially counteracting neurodegeneration in PD and improving clinical symptoms. Objective: This randomized controlled trial investigated effects of a highly challenging, cognitively demanding, balance and gait training (HiBalance) program in participants with PD on brain structure. Methods: 95 participants were assigned to either the HiBalance or an active control speech training program. The group-based interventions were performed in 1-hour sessions, twice per week over a 10-week period. Participants underwent balance, gait, cognitive function, and structural magnetic resonance imaging assessments before and after the interventions. Voxel-based morphometry was analyzed in 34 HiBalance and 31 active controls. Additionally, structural covariance networks were assessed. Results: There was no significant time by group interaction between the HiBalance and control training in balance, gait, or brain volume. Within-HiBalance-group analyses showed higher left putamen volumes post-training. In repeated measures correlation a positive linear, non-significant relationship between gait speed and putamen volume was revealed. In the HiBalance group we found community structure changes and stronger thalamic-cerebellar connectivity in structural covariance networks. Neither brain volume changes nor topology changes were found for the active controls after the training. Conclusion: Thus, subtle structural brain changes occur after balance and gait training. Future studies need to determine whether training modifications or other assessment methods lead to stronger effects. [ABSTRACT FROM AUTHOR]

It is currently unclear whether plasma biomarkers can be used as independent prognostic tools to predict changes associated with early Alzheimer's disease. In this study, we sought to address this question by assessing whether plasma biomarkers can predict changes in amyloid load, tau accumulation, brain atrophy and cognition in non-demented individuals. To achieve this, plasma amyloid-β 42/40 (Aβ42/40), phosphorylated-tau181, phosphorylated-tau217 and neurofilament light were determined in 159 non-demented individuals, 123 patients with Alzheimer's disease dementia and 35 patients with a non-Alzheimer's dementia from the Swedish BioFINDER-2 study, who underwent longitudinal amyloid (18F-flutemetamol) and tau (18F-RO948) PET, structural MRI (T1-weighted) and cognitive testing. Our univariate linear mixed effect models showed there were several significant associations between the plasma biomarkers with imaging and cognitive measures. However, when all biomarkers were included in the same multivariate linear mixed effect models, we found that increased longitudinal amyloid-PET signals were independently predicted by low baseline plasma Aβ42/40 (P = 0.012), whereas increased tau-PET signals, brain atrophy and worse cognition were independently predicted by high plasma phosphorylated-tau217 (P < 0.004). These biomarkers performed equally well or better than the corresponding biomarkers measured in the CSF. In addition, they showed a similar performance to binary plasma biomarker values defined using the Youden index, which can be more easily implemented in the clinic. In addition, plasma Aβ42/40 and phosphorylated-tau217 did not predict longitudinal changes in patients with a non-Alzheimer's neurodegenerative disorder. In conclusion, our findings indicate that plasma Aβ42/40 and phosphorylated-tau217 could be useful in clinical practice, research and drug development as prognostic markers of future Alzheimer's disease pathology. [ABSTRACT FROM AUTHOR]

It is currently unclear how amyloid-β and tau deposition are linked to changes in synaptic function and axonal structure over the course of Alzheimer's disease. Here, we assessed these relationships by measuring presynaptic (synaptosomal-associated protein 25, SNAP25; growth-associated protein 43, GAP43), postsynaptic (neurogranin, NRGN) and axonal (neurofilament light chain) markers in the CSF of individuals with varying levels of amyloid-β and tau pathology based on 18F-flutemetamol PET and 18F-flortaucipir PET. In addition, we explored the relationships between synaptic and axonal markers with cognition as well as functional and anatomical brain connectivity markers derived from resting-state functional MRI and diffusion tensor imaging. We found that the presynaptic and postsynaptic markers SNAP25, GAP43 and NRGN are elevated in early Alzheimer's disease i.e. in amyloid-β-positive individuals without evidence of tau pathology. These markers were associated with greater amyloid-β pathology, worse memory and functional changes in the default mode network. In contrast, neurofilament light chain was abnormal in later disease stages, i.e. in individuals with both amyloid-β and tau pathology, and correlated with more tau and worse global cognition. Altogether, these findings support the hypothesis that amyloid-β and tau might have differential downstream effects on synaptic and axonal function in a stage-dependent manner, with amyloid-related synaptic changes occurring first, followed by tau-related axonal degeneration. [ABSTRACT FROM AUTHOR]

Background: Cognitive deficits arising in the course of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and Parkinson's disease with dementia (PDD) are directly linked to synaptic loss. Postmortem studies suggest that zinc transporter protein 3 (ZnT3), AMPA glutamate receptor 3 (GluA3), and Dynamin1 are associated with cognitive decline in AD and Lewy body dementia patients.Objective: We aimed to evaluate the diagnostic value of ZnT3, GluA3, and Dynamin 1 in the cerebrospinal fluid (CSF) of patients with dementia due to AD, DLB, and PDD compared to cognitively normal subjective cognitive decline (SCD) patients in a retrospective study. In addition, we assessed the relationship between synaptic markers and age, sex, cognitive impairment, and depressive symptoms as well as CSF amyloid, phosphorylated tau (p-tau), and total tau (T-tau).Methods: Commercially available ELISA immunoassay was used to measure the levels of proteins in a total of 97 CSF samples from AD (N = 24), PDD (N = 18), DLB (N = 27), and SCD (N = 28) patients. Cognitive impairment was assessed using the Mini-Mental State Examination (MMSE).Results: We found a significant increase in the concentrations of ZnT3, GluA3, and Dynamin1 in AD (p = 0.002) and of ZnT3 and Dynamin 1 in DLB (p = 0.001, p = 0.002) when compared to SCD patients. Changes in ZnT3 concentrations correlated with MMSE scores in AD (p = 0.011), and with depressive symptoms in SCD (p = 0.041).Conclusion: We found alteration of CSF levels of synaptic proteins in AD, PDD, and DLB. Our results reveal distinct changes in CSF concentrations of ZnT3 that could reflect cognitive impairment in AD with implications for future prognostic and diagnostic marker development. [ABSTRACT FROM AUTHOR]

Purpose: The abnormal deposition of tau begins before the onset of clinical symptoms and seems to target specific brain networks. The aim of this study is to identify the spatial patterns of tau deposition in cognitively normal older adults and assess whether they are related to amyloid-β (Aβ), APOE, sex, and longitudinal cognitive decline. Methods: We included 114 older adults with cross-sectional flortaucipir (FTP) and Pittsburgh Compound-B PET in addition to longitudinal cognitive testing. A voxel-wise independent component analysis was applied to FTP images to identify the spatial patterns of tau deposition. We then assessed whether tau within these patterns differed by Aβ status, APOE genotype, and sex. Linear mixed effects models were built to test whether tau in each component predicted cognitive decline. Finally, we ordered the spatial components based on the frequency of high tau deposition to model tau spread. Results: We found 10 biologically plausible tau patterns in the whole sample. There was greater tau in medial temporal, occipital, and orbitofrontal components in Aβ-positive compared with Aβ-negative individuals; in the parahippocampal component in ε3ε3 compared with ε2ε3 carriers; and in temporo-parietal and anterior frontal components in women compared with men. Higher tau in temporal and frontal components predicted longitudinal cognitive decline in memory and executive functions, respectively. Tau deposition was most frequently observed in medial temporal and ventral cortical areas, followed by lateral and primary areas. Conclusions: These findings suggest that the spatial patterns of tau in asymptomatic individuals are clinically meaningful and are associated with Aβ, APOE ε2ε3, sex and cognitive decline. These patterns could be used to predict the regional spread of tau and perform in vivo tau staging in older adults. [ABSTRACT FROM AUTHOR]

The brain works as a large-scale complex network, known as the connectome. The strength of the connections between two brain regions in the connectome is commonly estimated by calculating the correlations between their patterns of activation. This approach relies on the assumption that the activation of connected regions occurs together and at the same time. However, there are delays between the activation of connected regions due to excitatory and inhibitory connections. Here, we propose a method to harvest this additional information and reconstruct the structural brain connectome using delayed correlations. This delayed-correlation method correctly identifies 70% to 80% of connections of simulated brain networks, compared to only 5% to 25% of connections detected by the standard methods; this result is robust against changes in the network parameters (small-worldness, excitatory vs. inhibitory connection ratio, weight distribution) and network activation dynamics. The delayed-correlation method predicts more accurately both the global network properties (characteristic path length, global efficiency, clustering coefficient, transitivity) and the nodal network properties (nodal degree, nodal clustering, nodal global efficiency), particularly at lower network densities. We obtain similar results in networks derived from animal and human data. These results suggest that the use of delayed correlations improves the reconstruction of the structural brain connectome and open new possibilities for the analysis of the brain connectome, as well as for other types of networks. [ABSTRACT FROM AUTHOR]

• Women with past conduct disorder showed cortical structure abnormalities relative to healthy women. • Abnormalities included reduced cortical thickness in left fusiform gyrus. • Reduced surface area in the right superior parietal lobe. • Increased surface area in left superior temporal gyrus and right precentral gyrus. • All abnormalities survived correction for maltreatment and comorbid disorders. Among females, conduct disorder (CD) before age 15 is associated with multiple adverse outcomes in adulthood. The few existing structural neuroimaging studies of females with CD report abnormalities of gray matter volumes. The present study compared cortical thickness and surface area of young women with childhood/adolescent CD and healthy women to determine whether cortical abnormalities were present in adulthood and whether they were related to prior CD. Structural brain images from 31 women with CD and 25 healthy women were analyzed using FreeSurfer. Group differences between cortical thickness and surface area were assessed using cluster-wise corrections with Monte Carlo simulations. Women with prior CD, relative to healthy women, showed: (1) reduced cortical thickness in left fusiform gyrus extending up to entorhinal cortex and lingual gyrus; (2) reduced surface area in right superior parietal cortex; (3) increased surface area in left superior temporal gyrus, and right precentral gyrus. These differences remained significant after adjusting for past comorbid disorders, current symptoms of anxiety and depression, current substance use as well as maltreatment. The study suggests that among females, CD prior to age 15 is associated with cortical structure abnormalities in brain regions involved in emotion processing and social interaction. [ABSTRACT FROM AUTHOR]

We conducted the first systematic omics study of the oncocytic phenotype in 488 papillary thyroid carcinomas (PTC) from The Cancer Genome Atlas. Oncocytic phenotype is secondary to PTC, being unrelated to several pathologic scores. The nuclear genome had low impact on this phenotype (except in specific copy number variation), which was mostly driven by the significant accumulation of mitochondrial DNA non-synonymous and frameshift mutations at high heteroplasmy levels. Energy and mitochondrial-related pathways were significantly enriched in oncocytic tumors that also displayed increased levels of expression for genes involved in autophagy and fusion of mitochondria. Our in vitro tests confirmed that autophagy is increased and functional while mitophagy is decreased in these tumors. [ABSTRACT FROM AUTHOR]

There is increasing evidence showing that brain atrophy varies between patients with Alzheimer's disease (AD), suggesting that different anatomical patterns might exist within the same disorder. We investigated AD heterogeneity based on cortical and subcortical atrophy patterns in 299 AD subjects from 2 multicenter cohorts. Clusters of patients and important discriminative features were determined using random forest pairwise similarity, multidimensional scaling, and distance-based hierarchical clustering. We discovered 2 typical (72.2%) and 3 atypical (28.8%) subtypes with significantly different demographic, clinical, and cognitive characteristics, and different rates of cognitive decline. In contrast to previous studies, our unsupervised random forest approach based on cortical and subcortical volume measures and their linear and nonlinear interactions revealed more typical AD subtypes with important anatomically discriminative features, while the prevalence of atypical cases was lower. The hippocampal-sparing and typical AD subtypes exhibited worse clinical progression in visuospatial, memory, and executive cognitive functions. Our findings suggest there is substantial heterogeneity in AD that has an impact on how patients function and progress over time. [ABSTRACT FROM AUTHOR]

Recent findings show that structural network topology is disrupted in Alzheimer's disease (AD), with changes occurring already at the prodromal disease stages. Amyloid accumulation, a hallmark of AD, begins several decades before symptom onset, and its effects on brain connectivity at the earliest disease stages are not fully known. We studied global and local network changes in a large cohort of cognitively healthy individuals (N = 299, Swedish BioFINDER study) with and without amyloid-β (Aβ) pathology (based on cerebrospinal fluid Aβ42/Aβ40 levels). Structural correlation matrices were constructed based on magnetic resonance imaging cortical thickness data. Despite the fact that no significant regional cortical atrophy was found in the Aβ-positive group, this group exhibited an altered global network organization, including decreased global efficiency and modularity. At the local level, Aβ-positive individuals displayed fewer and more disorganized modules as well as a loss of hubs. Our findings suggest that changes in network topology occur already at the presymptomatic (preclinical) stage of AD and may precede detectable cortical thinning. [ABSTRACT FROM AUTHOR]

The aggregation and deposition of amyloid-β (Aβ) peptides into plaques is an early event in Alzheimer's disease (AD), which is followed by different aspects of neurodegeneration that can be measured in the cerebrospinal fluid (CSF) or plasma using neurofilament light (NFL), neurogranin (Ng), total Tau (T-Tau), and phosphorylated tau (P-Tau) levels. The relationship between these biomarkers and regional brain atrophy across the different stages of AD remains largely unexplored. In this study, we assessed whether NFL, Ng, T-Tau, and P-Tau levels in CSF and NFL in plasma are associated with cortical thinning and subcortical volume loss in cognitively normal, mild cognitive impairment, and AD subjects with and without Aβ pathology. Our main findings showed that CSF NFL levels were associated with brain atrophy in all groups, but plasma NFL only correlated with atrophy in symptomatic cases. In contrast, Ng was associated with regional brain atrophy only in individuals with Aβ pathology. Altogether, our main findings suggest that Ng is strongly associated with Aβ pathology, whereas NFL is more unspecific. [ABSTRACT FROM AUTHOR]

Important gaps remain in our understanding of the spread of farming into Europe, due partly to apparent contradictions between studies of contemporary genetic variation and ancient DNA. It seems clear that farming was introduced into central, northern, and eastern Europe from the south by pioneer colonization. It is often argued that these dispersals originated in the Near East, where the potential source genetic pool resembles that of the early European farmers, but clear ancient DNA evidence from Mediterranean Europe is lacking, and there are suggestions that Mediterranean Europe may have resembled the Near East more than the rest of Europe in the Mesolithic. Here, we test this proposal by dating mitogenome founder lineages from the Near East in different regions of Europe. We find that whereas the lineages date mainly to the Neolithic in central Europe and Iberia, they largely date to the Late Glacial period in central/eastern Mediterranean Europe. This supports a scenario in which the genetic pool of Mediterranean Europe was partly a result of Late Glacial expansions from a Near Eastern refuge, and that this formed an important source pool for subsequent Neolithic expansions into the rest of Europe. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess whether mild cognitive impairment (MCI) is associated with disruption in large-scale structural networks in newly diagnosed, drug-naïve patients with Parkinson's disease (PD). Graph theoretical analyses were applied to 3T MRI data from 123 PD patients and 56 controls from the Parkinson's progression markers initiative (PPMI). Thirty-three patients were classified as having Parkinson's disease with mild cognitive impairment (PD-MCI) using the Movement Disorders Society Task Force criteria, while the remaining 90 PD patients were classified as cognitively normal (PD-CN). Global measures (clustering coefficient, characteristic path length, global efficiency, small-worldness) and regional measures (regional clustering coefficient, regional efficiency, hubs) were assessed in the structural networks that were constructed based on cortical thickness and subcortical volume data. PD-MCI patients showed a marked reduction in the average correlation strength between cortical and subcortical regions compared with controls. These patients had a larger characteristic path length and reduced global efficiency in addition to a lower regional efficiency in frontal and parietal regions compared with PD-CN patients and controls. A reorganization of the highly connected regions in the network was observed in both groups of patients. This study shows that the earliest stages of cognitive decline in PD are associated with a disruption in the large-scale coordination of the brain network and with a decrease of the efficiency of parallel information processing. These changes are likely to signal further cognitive decline and provide support to the role of aberrant network topology in cognitive impairment in patients with early PD. Hum Brain Mapp 36:2980-2995, 2015. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

In the past few years, there has been an increasing awareness of the regional vulnerability of the hippocampus to age-related processes. However, to date, no studies have assessed the effects of age on different structural magnetic resonance parameters in the specific hippocampal subfields. In this study, we measured volume, mean diffusivity (MD) and fractional anisotropy (FA) in the presubiculum, subiculum, fimbria, cornu ammonis (CA) 1,2-3,4-DG and the whole hippocampus in fifty cognitively intact elder adults between 50 and 75 years of age (20 men, 30 women). Segmentation of hippocampal subfields was performed using FreeSurfer. Individual MD and FA images were coregistered to T1-weighted volumes using FLIRT of FSL. Linear regression analyses were performed to assess the effects of age on the anatomical measures of each subfield. In addition, multiple regression analyses were also carried out to assess which of the anatomical measures that showed a correlation with age in the previous analyses, were the best age predictors in the hippocampus. In agreement with previous studies, our results showed a significant association between age and volume ( P < 0.001) as well as MD ( P < 0.001) in the whole hippocampus. Regarding the specific hippocampal subfields, we found that age had a significant negative effect on volume in CA2-3 ( P < 0.001) and CA4-DG ( P < 0.001). Importantly, we found a positive effect of age on MD in CA2-3 ( P < 0.001) and fimbria ( P < 0.001) as well as a negative age effect on FA in the subiculum ( P < 0.001). Multiple regression analyses revealed that the best overall predictors of age in the hippocampus were MD in the fimbria and volume of CA2-3, which explained 73.8% of the age variance. These results indicate that age has an effect both on volume and diffusion tensor imaging measures in different subfields, suggesting they provide complementary information on age-related processes in the hippocampus. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

ABSTRACT Neuropathological studies show the hippocampus is affected in Parkinson's disease (PD), with the second subfield of the cornu armonis (CA2) being the most involved. Our aims were to assess in vivo volumes of different hippocampal subfields in patients with PD with and without visual hallucinations using MRI and test their association with verbal learning and long-term recall. A total of 18 nondemented PD patients, 18 nondemented PD patients with visual hallucinations and 18 neurologically unimpaired elderly controls matched by age and gender were enrolled in this study. We assessed the volumes of seven hippocampal subfields on MRI, including the cornu armonis (CA) sectors, subiculum, presubiculum, and the dentate gyrus (DG) using a novel technique that enables automated volumetry. The CA2-3 and CA4-DG subfields were significantly smaller in both groups of patients, while the subiculum was only reduced in PD patients with visual hallucinations, compared to controls. Significant correlations were found between learning performance and CA2-3 as well as CA4-DG volumes in the whole patient sample. These data show there is regional atrophy of specific hippocampal subfields in PD, which is more severe and further extends to the subiculum in patients with visual hallucinations. Our findings indicate that learning deficits are associated with volume loss in subfields that act as input regions in the hippocampal circuit, suggesting that degeneration in these regions could be responsible for cognitive dysfunction in PD. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: Neuropsychological (mostly posterior-cortical) deficits, quantitative magnetic resonance imaging (MRI) atrophy patterns, and low cerebrospinal fluid (CSF) levels of amyloid-β have been separately related to worsening cognition in Parkinson's disease (PD). However, these biomarkers have not been longitudinally assessed in combination as PD-dementia predictors. In this prospective longitudinal study, 27 non-demented PD patients underwent CSF, neuropsychological and 3-T brain-MRI studies at baseline and were re-assessed 18 months later in terms of progression to dementia (primary outcome) and longitudinal neuropsychological and cortical thickness changes (secondary outcomes). At follow-up 11 patients (41%) had progressed to dementia. Lower CSF amyloid-β, worse verbal learning, semantic fluency and visuoperceptual scores, and thinner superior-frontal/anterior cingulate and precentral regions were significant baseline dementia predictors in binary logistic regressions as quantitative and/or dichotomised traits. All participants without baseline biomarker abnormalities remained non-demented whereas all with abnormalities in each biomarker type progressed to dementia, with intermediate risk for those showing abnormalities in a single to two biomarker types (p = 0.006). Both the dementia-outcome and low baseline CSF amyloid-β were prospectively associated with limbic and posterior-cortical neuropsychological decline and frontal, limbic and posterior-cortical thinning from baseline to follow-up. These findings suggest that the combination of CSF amyloid-β, neuropsychological and cortical thickness biomarkers might provide a basis for dementia-risk stratification and progression monitoring in PD. [Copyright &y& Elsevier]

• We developed a method for automatic brain tissue classification on CT images. • Used appropriately, the method may obviate the clinical need for MRI to quantify brain atrophy. • A U-Net-based deep learning model was trained on CT images with labels generated by segmenting paired MR images. • High overlap scores indicate strong agreement of the model predictions with segmentations. • High volumetric correlations with low volumetric errors were observed for grey matter, white matter, and intracranial volume, indicating that model-derived tissue volumes were similar to MRI-derived volumes. • We provide extensive benchmarking of the label agreement result against MRI-based segmentation methods. Automatic methods for feature extraction, volumetry, and morphometric analysis in clinical neuroscience typically operate on images obtained with magnetic resonance (MR) imaging equipment. Although CT scans are less expensive to acquire and more widely available than MR scans, their application is currently limited to the visual assessment of brain integrity and the exclusion of co-pathologies. CT has rarely been used for tissue classification because the contrast between grey matter and white matter was considered insufficient. In this study, we propose an automatic method for segmenting grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and intracranial volume (ICV) from head CT images. A U-Net deep learning model was trained and validated on CT images with MRI-derived segmentation labels. We used data from 744 participants of the Gothenburg H70 Birth Cohort Studies for whom CT and T1-weighted MR images had been acquired on the same day. Our proposed model predicted brain tissue classes accurately from unseen CT images (Dice coefficients of 0.79, 0.82, 0.75, 0.93 and 0.98 for GM, WM, CSF, brain volume and ICV, respectively). To contextualize these results, we generated benchmarks based on established MR-based methods and intentional image degradation. Our findings demonstrate that CT-derived segmentations can be used to delineate and quantify brain tissues, opening new possibilities for the use of CT in clinical practice and research. [Display omitted] [ABSTRACT FROM AUTHOR]

ABSTRACT This study describes the synthesis of three new tetra- and octa-thio-pyridinium phthalocyanine derivatives. PSs 3a and 4a were prepared from the tetramerization of phthalonitriles 1 and 2, respectively, whereas PS 5 was prepared from the nucleophilic substitution of the 8 beta fluor atoms of hexadecafluorophthalocyaninatozinc(II) by mercaptopyridine, followed by cationization. The recombinant bioluminescent Escherichia coli strain was used to assess, in real time, the photoinactivation efficiency of these cationic phthalocyanines, under white and red light. The cellular localization and uptake were also determined to assess the potential of the new phthalocyanines as antibacterial agents. Derivative 3a was the most effective PS, causing a 5 logs reduction in bioluminescence after 30 min of irradiation under white or red lights. The photoinactivation efficiency of the phthalocyanine 4a was similar (5 logs reduction in bioluminescence) to that of 3a when irradiated with white light, but the efficiency of inactivation was reduced (2.1 logs reduction in bioluminescence) under red light. The tetra-substituted phthalocyanine 3a also generates high amounts of singlet oxygen, does not aggregate in PBS and is highly fluorescent, which makes it an effective PS and a promising fluorescent labeling. [ABSTRACT FROM AUTHOR]

To determine magnetic resonance imaging patterns of gray matter (GM) atrophy underlying visuospatial and visuoperceptual impairment in Parkinson's disease (PD), we applied voxel-based morphometry to 36 nondemented PD patients and correlated their whole brain GM density with performance on three visuospatial and visuoperceptual tests. In addition, group comparisons between patients and 20 healthy controls were also performed. Correlations between visuospatial performance and GM density were found in the superior parietal lobules and the superior occipital gyrus of PD patients. Poor performance on visuoperceptual tests was also found to be significantly associated with GM decreases in the fusiform, the parahippocampus, and the middle occipital gyrus. Finally, group comparisons between controls and patients showed widespread GM cortical reductions in PD, involving posterior temporal and parietal regions. Taken together, these findings suggest that visuospatial and visuoperceptual dysfunctions reflect structural GM changes in temporo-parietal cortical regions of PD patients. © 2009 Movement Disorder Society [ABSTRACT FROM AUTHOR]

AbstractBackground: Cognitive impairment is observed in up to 50% of patients with amyotrophic lateral sclerosis (ALS). The Edinburgh Cognitive and Behavioral ALS Screen (ECAS) is an ALS-specific multi-domain screening tool. Few studies have examined the relationship between ECAS scores and [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) findings. Objective: To assess the relationship between ECAS scores and glucose metabolism patterns on [18F]FDG -PET images in ALS. Methods: We collected [18F]FDG-PET images from 65 patients with ALS and 39 healthy controls. ECAS scores were collected on all patients and we calculated the correlation to [18F]FDG-PET in order to investigate the potential links between cognition and glucose metabolism. Results: We observed hypometabolism in the frontal cortex, insula, and limbic system, together with hypermetabolism in the cerebellum in patients with ALS compared to controls. A lower ECAS total score was associated with lower glucose metabolism in the right orbitofrontal gyrus and higher glucose metabolism in lateral occipital, medial occipital, and cerebellar regions, among patients with ALS. Similar results, although less widespread, were observed in the analyses of ECAS ALS-specific scores. Conclusions: The metabolic patterns in [18F]FDG -PET show that changes in the glucose metabolism of corresponding areas are related to cognitive dysfunction in ALS, and can be detected using the ECAS. [ABSTRACT FROM AUTHOR]

Cognitive changes are common in corticobasal syndrome (CBS) and significantly impact quality of life and caregiver burden. However, relatively few studies have investigated the neural substrates of cognitive changes in CBS, and reliable predictors of cognitive impairment are currently lacking. The nucleus basalis of Meynert (NbM), which serves as the primary source of cortical cholinergic innervation, has been functionally associated with cognition. This study aimed to explore whether patients with CBS exhibit reduced NbM volumes compared with healthy control participants and whether NbM degeneration can serve as a predictor of cognitive impairment in patients with CBS. In this study, we investigated in vivo volumetric changes of the NbM in 38 patients with CBS and 84 healthy control participants. Next, we assessed whether gray matter degeneration of the NbM evaluated at baseline could predict cognitive impairment during a 12-month follow-up period in patients with CBS. All volumetric analyses were performed using 3T T1-weighted images obtained from the 4-Repeat Tauopathy Neuroimaging Initiative. Patients with CBS displayed significantly lower NbM volumes than control participants (p <.001). Structural damage of the NbM also predicted the development of cognitive impairment in patients with CBS as assessed by longitudinal measurements of the Clinical Dementia Rating Sum of Boxes (p <.001) and Mini-Mental State Examination (p =.035). Our findings suggest that NbM atrophy may represent a promising noninvasive in vivo marker of cognitive decline in CBS and provide new insights into the neural mechanisms that underlie cognitive impairment in CBS. [ABSTRACT FROM AUTHOR]

Cholinergic dysfunction plays a prominent role in cognitive impairment in Parkinson's disease (PD). The aim of this study was to assess the relationship of baseline and longitudinal basal forebrain atrophy with cognitive decline and dementia in PD. We included 106 non-demented PD patients, 19 PD dementia (PDD) patients and 42 controls with longitudinal structural MRI and cognitive testing. After 4.2 ± 1.8 years, 20 non-demented PD patients were diagnosed with dementia (PD-dementia converters), whereas the rest of PD patients remained non-demented (stable-PD). We compared MRI volumes of the medial septum/diagonal band (Ch1/Ch2) and nucleus basalis of Meynert (Ch4) between groups. Cox regression analyses were applied to test whether Ch1/Ch2 or Ch4 atrophy could predict future dementia and linear mixed models assessed their association with cognitive decline. Compared to controls, we found reduced Ch4 baseline volumes in PD-dementia converters (p =.003) and those who already had PDD (p <.001) but not in stable-PD. Over time, there was a greater loss in Ch1/Ch2 volumes in PD-dementia converters and PDD compared to the other groups (p =.004). Baseline and longitudinal Ch4 volumes were associated with cognition (p <.002) and longitudinal Ch4 atrophy predicted future dementia (p =.009). Atrophy of Ch4 precedes and predicts future dementia in PD and is followed by changes in Ch1/Ch2, reflecting a posterior-anterior pattern of basal forebrain atrophy. This pattern could be used to track the spread of cholinergic degeneration and identify patients at risk of developing dementia. • Ch4 atrophy precedes and predicts future dementia in PD. • These changes are followed by Ch1/Ch2 longitudinal atrophy. • The basal forebrain shows an anterior-posterior pattern of atrophy over time in PD. [ABSTRACT FROM AUTHOR]

Brain gray- and white matter changes is well described in alcohol-dependent elderly subjects; however, the effect of lower levels of alcohol consumption on the brain is poorly understood. We investigated the impact of different amounts of weekly alcohol consumption on brain structure in a population-based sample of 70-year-olds living in Gothenburg, Sweden. Cross-sectional data from 676 participants from The Gothenburg H70 Birth Cohort Study 2014–16 were included. Current alcohol consumers were divided into seven groups based on self-reported weekly amounts of alcohol consumption in grams (g) (0–50 g/week, used as reference group, 51–100 g/week, 101–150 g/week, 151–200 g/week, 201–250 g/week, 251–300 g/week, and > 300 g/week). Subcortical volumes and cortical thickness were assessed on T1-weighted structural magnetic resonance images using FreeSurfer 5.3, and white matter integrity assessed on diffusion tensor images, using tract-based statistics in FSL. General linear models were carried out to estimate associations between alcohol consumption and gray- and white matter changes in the brain. Self-reported consumption above 250 g/week was associated with thinning in the bilateral superior frontal gyrus, the right precentral gyrus, and the right lateral occipital cortex, in addition to reduced fractional anisotropy (FA) and increased mean diffusivity (MD) diffusively spread in many tracts all over the brain. No changes were found in subcortical gray matter structures. These results suggest that there is a non-linear relationship between alcohol consumption and structural brain changes, in which loss of cortical thickness only occur in non-demented 70-year-olds who consume more than 250 g/week. [ABSTRACT FROM AUTHOR]

Graph analysis has become a popular approach to study structural brain networks in neurodegenerative disorders such as Alzheimer’s disease (AD). However, reported results across similar studies are often not consistent. In this paper we investigated the stability of the graph analysis measures clustering, path length, global efficiency and transitivity in a cohort of AD (N = 293) and control subjects (N = 293). More specifically, we studied the effect that group size and composition, choice of neuroanatomical atlas, and choice of cortical measure (thickness or volume) have on binary and weighted network properties and relate them to the magnitude of the differences between groups of AD and control subjects. Our results showed that specific group composition heavily influenced the network properties, particularly for groups with less than 150 subjects. Weighted measures generally required fewer subjects to stabilize and all assessed measures showed robust significant differences, consistent across atlases and cortical measures. However, all these measures were driven by the average correlation strength, which implies a limitation of capturing more complex features in weighted networks. In binary graphs, significant differences were only found in the global efficiency and transitivity measures when using cortical thickness measures to define edges. The findings were consistent across the two atlases, but no differences were found when using cortical volumes. Our findings merits future investigations of weighted brain networks and suggest that cortical thickness measures should be preferred in future AD studies if using binary networks. Further, studying cortical networks in small cohorts should be complemented by analyzing smaller, subsampled groups to reduce the risk that findings are spurious. [ABSTRACT FROM AUTHOR]

Background: Disturbances in brain cholesterol homeostasis may be involved in the pathogenesis of Alzheimer's disease (AD). Lipid-lowering medications could interfere with neurodegenerative processes in AD through cholesterol metabolism or other mechanisms. Objective: To explore the association between the use of lipid-lowering medications and cognitive decline over time in a cohort of patients with AD or mixed dementia with indication for lipid-lowering treatment. Methods: A longitudinal cohort study using the Swedish Registry for Cognitive/Dementia Disorders, linked with other Swedish national registries. Cognitive trajectories evaluated with mini-mental state examination (MMSE) were compared between statin users and non-users, individual statin users, groups of statins and non-statin lipid-lowering medications using mixed-effect regression models with inverse probability of drop out weighting. A dose-response analysis included statin users compared to non-users. Results: Our cohort consisted of 15,586 patients with mean age of 79.5 years at diagnosis and a majority of women (59.2 %). A dose-response effect was demonstrated: taking one defined daily dose of statins on average was associated with 0.63 more MMSE points after 3 years compared to no use of statins (95% CI: 0.33;0.94). Simvastatin users showed 1.01 more MMSE points (95% CI: 0.06;1.97) after 3 years compared to atorvastatin users. Younger (< 79.5 years at index date) simvastatin users had 0.80 more MMSE points compared to younger atorvastatin users (95% CI: 0.05;1.55) after 3 years. Simvastatin users had 1.03 more MMSE points (95% CI: 0.26;1.80) compared to rosuvastatin users after 3 years. No differences regarding statin lipophilicity were observed. The results of sensitivity analysis restricted to incident users were not consistent. Conclusions: Some patients with AD or mixed dementia with indication for lipid-lowering medication may benefit cognitively from statin treatment; however, further research is needed to clarify the findings of sensitivity analyses. [ABSTRACT FROM AUTHOR]

• Data driven inflammatory subgroups show connectivity differences in psychosis. • High inflammation subgroup has lower DMNa activity vs the low inflammation group. • High inflammation subgroup has lower DMNa functional connectivity vs the low group. • High inflammation subgroup has lower multiplex participation vs the low group. • Network findings in high inflammation subgroups correlate with worse cognition. High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders. Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R. Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition. These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them. [ABSTRACT FROM AUTHOR]

Cognitive and behavioral impairment is observed in up to 50% of patients with amyotrophic lateral sclerosis (ALS). The Edinburgh Cognitive and Behavioral ALS Screen (ECAS) is a 5-domain screening tool customized for quick cognitive screening in patients with ALS. Although the ECAS is available in Swedish at the Karolinska University Hospital (SK-ECAS), it has not yet been validated in Sweden stressing the need to assess validity and reliability of the SK-ECAS Version A. The study included 176 patients with ALS or other motor neuron disease diagnosed between September 2017 and October 2021 at the Karolinska ALS Clinical Research Center in Stockholm, Sweden, and 35 age-matched healthy control subjects. SK-ECAS was validated against the Montreal Cognitive Assessment (MoCA) and optimal cutoffs, receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated. We identified an optimal cutoff of 108 for the SK-ECAS total score and 82 for the SK-ECAS ALS-specific score to detect cognitive impairment. The SK-ECAS showed good performance in indicating abnormal cognition with an AUC of 0.73 for SK-ECAS ALS-specific score and 0.77 for SK-ECAS total score. There was good internal consistency with a Cronbach's alpha of 0.79. This study demonstrates good validity and reliability indices for SK-ECAS Version A for the detection of cognitive impairment in newly diagnosed ALS patients. [ABSTRACT FROM AUTHOR]

Progranulin plays an important role in neuroinflammation in Alzheimer's disease (AD) pathophysiology, being upregulated by activated microglia. This study assessed whether cerebrospinal fluid levels of progranulin correlated with structural neuroimaging measures and cognition in 122 cognitively normal individuals, 81 mild cognitive impairment, and 70 AD patients from the Alzheimer's Disease Neuroimaging Initiative. Cognitively normal subjects were classified into 3 groups using the AT(N) system, whereas all mild cognitive impairment and AD patients were A+/TN+. Correlations between progranulin with neuroanatomical measures and cognitive decline were performed within each group. Progranulin was associated with cortical thickening in parietal, occipital, and frontal regions in cognitively normal individuals with amyloid pathology. These subjects also showed cortical thickening compared with A−/TN− subjects, an effect that was partially mediated by progranulin. In addition, higher progranulin correlated with longitudinal cognitive decline. The association between progranulin and cortical thickening, together with regional "brain swelling" in A+/TN− subjects, suggests progranulin contributes to the neuroinflammatory structural changes in preclinical AD. • Progranulin correlates with cortical thickening in early Alzheimer's disease. • Early Alzheimer's disease stages are characterized by cortical thickening or brain swelling. • Progranulin is a mediator of brain swelling in these early disease stages. • Progranulin predicts cognitive decline across the Alzheimer's continuum. [ABSTRACT FROM AUTHOR]

The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging, and whether it is associated with cognition and mood. Here, we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years of age (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project [HCP] 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory, and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography, and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale (HADS) ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease is a neurodegenerative disorder associated with the abnormal deposition of pathological processes, such as amyloid-ß and tau, which produces nonlinear changes in the functional connectivity patterns between different brain regions across the Alzheimer's disease continuum. However, the mechanisms underlying these nonlinear changes remain largely unknown. Here, we address this question using a novel method based on temporal or delayed correlations and calculate new whole-brain functional networks to tackle these mechanisms. Methods: To assess our method, we evaluated 166 individuals from the ADNI database, including amyloid-beta negative and positive cognitively normal subjects, patients with mild cognitive impairment, and patients with Alzheimer's disease dementia. We used the clustering coefficient and the global efficiency to measure the functional network topology and assessed their relationship with amyloid and tau pathology measured by positron emission tomography, as well as cognitive performance using tests measuring memory, executive function, attention, and global cognition. Results: Our study found nonlinear changes in the global efficiency, but not in the clustering coefficient, showing that the nonlinear changes in functional connectivity are due to an altered ability of brain regions to communicate with each other through direct paths. These changes in global efficiency were most prominent in early disease stages. However, later stages of Alzheimer's disease were associated with widespread network disruptions characterized by changes in both network measures. The temporal delays required for the detection of these changes varied across the Alzheimer's disease continuum, with shorter delays necessary to detect changes in early stages and longer delays necessary to detect changes in late stages. Both global efficiency and clustering coefficient showed quadratic associations with pathological amyloid and tau burden as well as cognitive decline. Conclusions: This study suggests that global efficiency is a more sensitive indicator of network changes in Alzheimer's disease when compared to clustering coefficient. Both network properties were associated with pathology and cognitive performance, demonstrating their relevance in clinical settings. Our findings provide an insight into the mechanisms underlying nonlinear changes in functional network organization in Alzheimer's disease, suggesting that it is the lack of direct connections that drives these functional changes. [ABSTRACT FROM AUTHOR]

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. [ABSTRACT FROM AUTHOR]

Background: The medial parietal cortex is an early site of pathological protein deposition in Alzheimer's disease (AD). Previous studies have identified different subregions within this area; however, these subregions are often heterogeneous and disregard individual differences or subtle pathological alterations in the underlying functional architecture. To address this limitation, here we measured the continuous connectivity gradients of the medial parietal cortex and assessed their relationship with cerebrospinal fluid (CSF) biomarkers, ApoE ε4 carriership and memory in asymptomatic individuals at risk to develop AD. Methods: Two hundred sixty-three cognitively normal participants with a family history of sporadic AD who underwent resting-state and task-based functional MRI using encoding and retrieval tasks were included from the PREVENT-AD cohort. A novel method for characterizing spatially continuous patterns of functional connectivity was applied to estimate functional gradients in the medial parietal cortex during the resting-state and task-based conditions. This resulted in a set of nine parameters that described the appearance of the gradient across different spatial directions. We performed correlation analyses to assess whether these parameters were associated with CSF biomarkers of phosphorylated tau181 (p-tau), total tau (t-tau), and amyloid-ß1-42 (Aß). Then, we compared the spatial parameters between ApoE ε4 carriers and noncarriers, and evaluated the relationship between these parameters and memory. Results: Alterations involving the superior part of the medial parietal cortex, which was connected to regions of the default mode network, were associated with higher p-tau, t-tau levels as well as lower Aß/p-tau levels during the resting-state condition (p < 0.01). Similar alterations were found in ApoE ε4 carriers compared to non-carriers (p < 0.003). In contrast, lower immediate memory scores were associated with changes in the middle part of the medial parietal cortex, which was connected to inferior temporal and posterior parietal regions, during the encoding task (p = 0.001). No results were found when using conventional connectivity measures. Conclusions: Functional alterations in the medial parietal gradients are associated with CSF AD biomarkers, ApoE ε4 carriership, and lower memory in an asymptomatic cohort with a family history of sporadic AD, suggesting that functional gradients are sensitive to subtle changes associated with early AD stages. [ABSTRACT FROM AUTHOR]

The number of molecular imaging studies in the field of brain connectivity is steadily increasing. Molecular imaging is not yet widely used by the MRI-predominant neuroimaging community as tool of choice for studying brain connectomics. Because chemical synapses are essential to signal transduction, targeting the molecular level of brain communication is indispensable for our understanding of the brain connectome. PET as major molecular imaging tool provides various established markers of neural activity, neurotransmitter systems, and proteinopathies. Integration of connectomes produced with different neurophysiological methods, including molecular imaging, might be key for advancing the field of neuroscience. In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific community to take an integrative approach whereby MRI-based, electrophysiological techniques, and molecular imaging contribute to our understanding of the brain connectome. [ABSTRACT FROM AUTHOR]

Several studies have shown that amyloid-β (Aβ) deposition below the clinically relevant cut-off levels is associated with subtle changes in cognitive function and increases the risk of developing future Alzheimer's disease (AD). Although functional MRI is sensitive to early alterations occurring during AD, sub-threshold changes in Aβ levels have not been linked to functional connectivity measures. This study aimed to apply directed functional connectivity to identify early changes in network function in cognitively unimpaired participants who, at baseline, exhibit Aβ accumulation below the clinically relevant threshold. To this end, we analyzed baseline functional MRI data from 113 cognitively unimpaired participants of the Alzheimer's Disease Neuroimaging Initiative cohort who underwent at least one 18F-florbetapir-PET after the baseline scan. Using the longitudinal PET data, we classified these participants as Aβ negative (Aβ−) non-accumulators (n = 46) and Aβ− accumulators (n = 31). We also included 36 individuals who were amyloid-positive (Aβ+) at baseline and continued to accumulate Aβ (Aβ+ accumulators). For each participant, we calculated whole-brain directed functional connectivity networks using our own anti-symmetric correlation method and evaluated their global and nodal properties using measures of network segregation (clustering coefficient) and integration (global efficiency). When compared to Aβ− non-accumulators, the Aβ− accumulators showed lower global clustering coefficient. Moreover, the Aβ+ accumulator group exhibited reduced global efficiency and clustering coefficient, which at the nodal level mainly affected the superior frontal gyrus, anterior cingulate cortex, and caudate nucleus. In Aβ− accumulators, global measures were associated with lower baseline regional PET uptake values, as well as higher scores on the Modified Preclinical Alzheimer Cognitive Composite. Our findings indicate that directed connectivity network properties are sensitive to subtle changes occurring in individuals who have not yet reached the threshold for Aβ positivity, which makes them a potentially viable marker to detect negative downstream effects of very early Aβ pathology. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) is a clinically and neuroanatomically heterogeneous neurodegenerative disease characterized by different subtypes. To this date, no studies have used multimodal data that combines clinical, motor, cognitive and neuroimaging assessments to identify these subtypes, which may provide complementary, clinically relevant information. To address this limitation, we subtyped participants with mild-moderate PD based on a rich, multimodal dataset of clinical, cognitive, motor, and neuroimaging variables.Methods: Cross-sectional data from 95 PD participants from our randomized EXPANd (EXercise in PArkinson's disease and Neuroplasticity) controlled trial were included. Participants were subtyped using clinical, motor, and cognitive assessments as well as structural and resting-state MRI data. Subtyping was done by random forest clustering. We extracted information about the subtypes by inspecting their neuroimaging profiles and descriptive statistics.Results: Our multimodal subtyping analysis yielded three PD subtypes: a motor-cognitive subtype characterized by widespread alterations in brain structure and function as well as impairment in motor and cognitive abilities; a cognitive dominant subtype mainly impaired in cognitive function that showed frontoparietal structural and functional changes; and a motor dominant subtype impaired in motor variables without any brain alterations. Motor variables were most important for the subtyping, followed by gray matter volume in the right medial postcentral gyrus.Conclusions: Three distinct PD subtypes were identified in our multimodal dataset. The most important features to subtype PD participants were motor variables in addition to structural MRI in the sensorimotor region. These findings have the potential to improve our understanding of PD heterogeneity, which in turn can lead to personalized interventions and rehabilitation. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment and dementia are common, clinically important features of Parkinson's disease (PD). The underlying disease pathology is heterogeneous and not yet well characterized. Biomarkers for cognitive impairment in PD could aid in diagnostic and prognostic evaluation and in the development of new cognitive enhancing treatments. Objective:To examine the relationship betweenCSFmarkers and cognition in a large, multicenter, cohort study of early, untreated PD, and compare marker concentrations between PD patients with and without MCI and healthy, age-matched controls. Methods: 414 early, untreated PD (34% with mild cognitive impairment) and 189 healthy, cognitively intact controls with baseline neuropsychological testing and CSF abeta42, t-tau, p-tau181 and α-synuclein results were included. Multiple linear regression models were constructed with a composite cognition factor, or memory-, or visuospatial- or executive-attention domains as dependent variables, and CSF markers, demographic characteristics and MDS-UPDRS III score as predictors. Results: Lower α-synuclein was associated with reduced performance on the executive-attention domain and the composite cognition factor in the whole PD-group. Abeta42 was significantly decreased in PD with mild cognitive impairment compared with controls after adjusting for covariates, while values in PD without MCI were identical to healthy controls. Conclusions: The association between reduced CSF α-synuclein concentrations and cognition suggests that α-synuclein pathology contributes to early cognitive impairment in PD, in particular to executive-attentional dysfunction. Longitudinal analyses are needed to determine if this and other CSF biomarkers in early Parkinson's disease are associated with the risk of future cognitive decline and dementia. [ABSTRACT FROM AUTHOR]

At the crossroads between Africa and Eurasia, Arabia is necessarily a melting pot, its peoples enriched by successive gene flow over the generations. Estimating the timing and impact of these multiple migrations are important steps in reconstructing the key demographic events in the human history. However, current methods based on genome-wide information identify admixture events inefficiently, tending to estimate only the more recent ages, as here in the case of admixture events across the Red Sea (∼8–37 generations for African input into Arabia, and 30–90 generations for “back-to-Africa” migrations). An mtDNA-based founder analysis, corroborated by detailed analysis of the whole-mtDNA genome, affords an alternative means by which to identify, date and quantify multiple migration events at greater time depths, across the full range of modern human history, albeit for the maternal line of descent only. In Arabia, this approach enables us to infer several major pulses of dispersal between the Near East and Arabia, most likely via the Gulf corridor. Although some relict lineages survive in Arabia from the time of the out-of-Africa dispersal, 60 ka, the major episodes in the peopling of the Peninsula took place from north to south in the Late Glacial and, to a lesser extent, the immediate post-glacial/Neolithic. Exchanges across the Red Sea were mainly due to the Arab slave trade and maritime dominance (from ∼2.5 ka to very recent times), but had already begun by the early Holocene, fuelled by the establishment of maritime networks since ∼8 ka. The main “back-to-Africa” migrations, again undetected by genome-wide dating analyses, occurred in the Late Glacial period for introductions into eastern Africa, whilst the Neolithic was more significant for migrations towards North Africa. [ABSTRACT FROM AUTHOR]

Abstract: Regional brain grey matter volume (GMV) reductions and abnormal cerebrospinal fluid (CSF) levels of τ and Aβ, extensively studied as biomarkers of Alzheimer''s disease (AD), have also been reported in Parkinson''s disease (PD) and related dementia (PDD). However, the relationship between these CSF and MRI biomarkers in PD and PDD remains unexplored. We studied these associations in 33 PD patients (18 with no dementia [PDND]; 15 fulfilling PDD criteria) and 12 neurologically unimpaired controls, with neuropsychological assessment, CSF ELISA studies, and voxel-based morphometry (VBM) analysis of high-field brain MRI. Neuropsychological assessment showed a gradation in cognitive performance from controls to PDND (significantly worse on visuospatial performance) and then to PDD (more impaired on memory, naming, fluency and visuospatial functions). No CSF-VBM correlations were found in controls or PDND patients. In contrast, in the analysis of both the PDD subgroup and the entire PD (PDND + PDD) sample, we found significant negative CSF-GMV correlations for τ and phospho-τ and significant positive CSF-GMV correlations for Aβ in mostly frontal and temporal structures. The correlations in the entire PD sample fitted with a linear model and were thus unlikely to have been driven solely by the PDD subgroup. Additionally, an association between both the CSF markers and the CSF-associated GMV reductions with several neuropsychological functions was found. We interpret that CSF markers of AD pathology are associated with VBM-measures of brain atrophy in PD-related dementia and within the PD cognitive continuum, and deserve further attention as putative biomarkers of cognitive impairment and dementia in PD. [Copyright &y& Elsevier]

The first large-scale fine characterization of Tunisian H lineages clarifies that the post-Last glacial maximum expansion originating in Iberia not only led to the resettlement of Europe but also of North Africa. We found that 46% of 81 Tunisian H lineages subscreened for 1,580 bp in mtDNA coding region were affiliated with H1 and H3 subhaplogroups, which are known to have originated in Iberia. Although no signs of local expansion were detected, which would allow a clear dating of their introduction, the younger and less diverse Tunisian Hi and H3 lineages indicate Iberia as the radiating centre. Major contributions from historical migrations to this Iberian genetic imprint in Tunisia were ruled out by the mtDNA gene pool similarity between Berber/Arab/cosmopolitan samples and some "Andalusian" communities, settled by the descendents of the "Moors" who once lived in Iberia for 10 centuries (between 8th and 17th centuries), before being expelled to Tunisia. [ABSTRACT FROM AUTHOR]

In Alzheimer's disease, post-mortem studies have shown that the first cortical site where neurofibrillary tangles appear is the transentorhinal region, a subregion within the medial temporal lobe that largely overlaps with Brodmann area 35, and the entorhinal cortex. Here we used tau-PET imaging to investigate the sequence of tau pathology progression within the human medial temporal lobe and across regions in the posterior-medial system. Our objective was to study how medial temporal tau is related to functional connectivity, regional atrophy, and memory performance. We included 215 amyloid-β- cognitively unimpaired, 81 amyloid-β+ cognitively unimpaired and 87 amyloid-β+ individuals with mild cognitive impairment, who each underwent 18F-RO948 tau and 18F-flutemetamol amyloid PET imaging, structural T1-MRI and memory assessments as part of the Swedish BioFINDER-2 study. First, event-based modelling revealed that the entorhinal cortex and Brodmann area 35 show the earliest signs of tau accumulation followed by the anterior and posterior hippocampus, Brodmann area 36 and the parahippocampal cortex. In later stages, tau accumulation became abnormal in neocortical temporal and finally parietal brain regions. Second, in cognitively unimpaired individuals, increased tau load was related to local atrophy in the entorhinal cortex, Brodmann area 35 and the anterior hippocampus and tau load in several anterior medial temporal lobe subregions was associated with distant atrophy of the posterior hippocampus. Tau load, but not atrophy, in these regions was associated with lower memory performance. Further, tau-related reductions in functional connectivity in critical networks between the medial temporal lobe and regions in the posterior-medial system were associated with this early memory impairment. Finally, in patients with mild cognitive impairment, the association of tau load in the hippocampus with memory performance was partially mediated by posterior hippocampal atrophy. In summary, our findings highlight the progression of tau pathology across medial temporal lobe subregions and its disease stage-specific association with memory performance. While tau pathology might affect memory performance in cognitively unimpaired individuals via reduced functional connectivity in critical medial temporal lobe-cortical networks, memory impairment in mild cognitively impaired patients is associated with posterior hippocampal atrophy. [ABSTRACT FROM AUTHOR]

Background: Changes in grey matter covariance networks have been reported in preclinical and clinical stages of Alzheimer's disease (AD) and have been associated with amyloid-β (Aβ) deposition and cognitive decline. However, the role of tau pathology on grey matter networks remains unclear. Based on previously reported associations between tau pathology, synaptic density and brain structural measures, tau-related connectivity changes across different stages of AD might be expected. We aimed to assess the relationship between tau aggregation and grey matter network alterations across the AD continuum. Methods: We included 533 individuals (178 Aβ-negative cognitively unimpaired (CU) subjects, 105 Aβ-positive CU subjects, 122 Aβ-positive patients with mild cognitive impairment, and 128 patients with AD dementia) from the BioFINDER-2 study. Single-subject grey matter networks were extracted from T1-weighted images and graph theory properties including degree, clustering coefficient, path length, and small world topology were calculated. Associations between tau positron emission tomography (PET) values and global and regional network measures were examined using linear regression models adjusted for age, sex, and total intracranial volume. Finally, we tested whether the association of tau pathology with cognitive performance was mediated by grey matter network disruptions. Results: Across the whole sample, we found that higher tau load in the temporal meta-ROI was associated with significant changes in degree, clustering, path length, and small world values (all p < 0.001), indicative of a less optimal network organisation. Already in CU Aβ-positive individuals associations between tau burden and lower clustering and path length were observed, whereas in advanced disease stages elevated tau pathology was progressively associated with more brain network abnormalities. Moreover, the association between higher tau load and lower cognitive performance was only partly mediated (9.3 to 9.5%) through small world topology. Conclusions: Our data suggest a close relationship between grey matter network disruptions and tau pathology in individuals with abnormal amyloid. This might reflect a reduced communication between neighbouring brain areas and an altered ability to integrate information from distributed brain regions with tau pathology, indicative of a more random network topology across different AD stages. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a deterioration of neuronal connectivity. The pathological accumulation of tau in neurons is one of the hallmarks of AD and has been connected to the loss of dendritic spines of pyramidal cells, which are the major targets of cortical excitatory synapses and key elements in memory storage. However, the detailed mechanisms underlying the loss of dendritic spines in individuals with AD are still unclear. Here, we used graph-theory approaches to compare the distribution of dendritic spines from neurons with and without tau pathology of AD individuals. We found that the presence of tau pathology determines the loss of dendritic spines in clusters, ruling out alternative models where spine loss occurs at random locations. Since memory storage has been associated with synaptic clusters, the present results provide a new insight into the mechanisms by which tau drives synaptic damage in AD, paving the way to memory deficits through alterations of spine organization. [ABSTRACT FROM AUTHOR]

The association between cerebrospinal fluid (CSF) amyloid beta (Aβ) Aβ38 or Aβ40 and brain grey- and white matter integrity is poorly understood. We studied this in 213 cognitively normal 70-year-olds, and in subgroups defined by presence/absence of the APOE ε4 allele and Aβ pathology: Aβ−/APOE−, Aβ+/APOE−, Aβ−/APOE+ and Aβ+/APOE+. CSF Aβ was quantified using ELISA and genotyping for APOE was performed. Low CSF Aβ42 defined Aβ plaque pathology. Brain volumes were assessed using Freesurfer-5.3, and white matter integrity using tract-based statistics in FSL. Aβ38 and Aβ40 were positively correlated with cortical thickness, some subcortical volumes and white matter integrity in the total sample, and in 3 of the subgroups: Aβ−/APOE−, Aβ+/APOE− and Aβ−/APOE+. In Aβ+/APOE+ subjects, higher Aβ38 and Aβ40 were linked to reduced cortical thickness and subcortical volumes. We hypothesize that production of all Aβ species decrease in brain regions with atrophy. In Aβ+/APOE+, Aβ-dysregulation may be linked to cortical atrophy in which high Aβ levels is causing pathological changes in the gray matter of the brain. • Low CSF Amyloid-beta (Aβ)38 & 40 is associated with brain volume in cognitively normal elderly. • CSF Aβ42 was not a predictor of brain volume. • Low 38 & 40 Aβ may be linked neurodegeneration of non-Alzheimer type. • Low CSF Aβ38 &40 may be linked to decreased neural integrity in atrophic brain regions. • low or high CSF Aβ38 &40 may be linked to app dysregulation in preclinical AD. [ABSTRACT FROM AUTHOR]

Background: The panel of fluid- and imaging-based biomarkers available for neurodegenerative disease research is growing and has the potential to close important gaps in research and the clinic. With this growth and increasing use, appropriate implementation and interpretation are paramount. Various biomarkers feature nuanced differences in strengths, limitations, and biases that must be considered when investigating disease etiology and clinical utility. For example, neuropathological investigations of Alzheimer's disease pathogenesis can fall in disagreement with conclusions reached by biomarker-based investigations. Considering the varied strengths, limitations, and biases of different research methodologies and approaches may help harmonize disciplines within the neurodegenerative disease field. Purpose of review: Along with separate review articles covering fluid and imaging biomarkers in this issue of Alzheimer's Research and Therapy, we present the result of a discussion from the 2019 Biomarkers in Neurodegenerative Diseases course at the University College London. Here, we discuss themes of biomarker use in neurodegenerative disease research, commenting on appropriate use, interpretation, and considerations for implementation across different neurodegenerative diseases. We also draw attention to areas where biomarker use can be combined with other disciplines to understand issues of pathophysiology and etiology underlying dementia. Lastly, we highlight novel modalities that have been proposed in the landscape of neurodegenerative disease research and care. [ABSTRACT FROM AUTHOR]

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course "Biomarkers in neurodegenerative diseases". In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis. [ABSTRACT FROM AUTHOR]