Regional white matter volume differences in nondemented aging and Alzheimer's disease

Associations between diffusion tensor imaging patterns and cerebrospinal fluid markers in mild cognitive impairment

Diffusion tensor imaging (DTI) can be used to detect early signs of increased water diffusivity in white matter tracts in patients with mild cognitive impairment (MCI). This study examined how DTI, alongside cerebrospinal fluid (CSF) biomarkers (like tau proteins and amyloid-β), can help identify early brain changes in MCI. We included 159 individuals (92 with MCI and 67 healthy controls) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and extracted their demographics, CSF biomarkers, and DTI metrics. We compared the biomarkers (CSF biomarkers and DTI markers in 57 white matter tracts) between the two study groups using a general linear model, adjusting for age, sex, and handedness. CSF biomarker levels showed a statistically significant difference between the two study groups. Also, diffusion properties of left Cingulum and left Uncinate fasciculus in both groups were statistically different. Additionally, we explored possible associations between CSF and DTI markers in the MCI group. Our results indicated several statistically significant associations between DTI metrics and CSF biomarkers within specific white matter tracts. These findings underscore the complexity of imaging and molecular markers associated with MCI.

Integrative Epigenomic Landscape of Alzheimer's Disease Brains Reveals Oligodendrocyte Molecular Perturbations Associated with Tau

Alzheimer's disease (AD) brains are characterized by neuropathologic and biochemical changes that are highly variable across individuals. Capturing epigenetic factors that associate with this variability can reveal novel biological insights into AD pathophysiology. We conducted an epigenome-wide association study of DNA methylation (DNAm) in 472 AD brains with neuropathologic measures (Braak stage, Thal phase, and cerebral amyloid angiopathy score) and brain biochemical levels of five proteins (APOE, amyloid-β (Aβ)40, Aβ42, tau, and p-tau) core to AD pathogenesis. Using a novel regional methylation (rCpGm) approach, we identified 5,478 significant associations, 99.7% of which were with brain tau biochemical measures. Of the tau-associated rCpGms, 93 had concordant associations in external datasets comprising 1,337 brain samples. Integrative transcriptome-methylome analyses uncovered 535 significant gene expression associations for these 93 rCpGms. Genes with concurrent transcriptome-methylome perturbations were enriched in oligodendrocyte marker genes, including known AD risk genes such as BIN1 , myelination genes MYRF, MBP and MAG previously implicated in AD, as well as novel genes like LDB3 . We further annotated the top oligodendrocyte genes in an additional 6 brain single cell and 2 bulk transcriptome datasets from AD and two other tauopathies, Pick's disease and progressive supranuclear palsy (PSP). Our findings support consistent rCpGm and gene expression associations with these tauopathies and tau-related phenotypes in both bulk brain tissue and oligodendrocyte clusters. In summary, we uncover the integrative epigenomic landscape of AD and demonstrate tau-related oligodendrocyte gene perturbations as a common potential pathomechanism across different tauopathies.

Changes in the Spatial Structure of Synchronization Connections in EEG During Nocturnal Sleep Apnea

This study involved 72 volunteers divided into two groups according to the apnea-hypopnea index (AHI): AHI>15 episodes per hour (ep/h) (main group, n=39, including 28 men, median AHI 44.15, median age 47), 0≤AHI≤15ep/h (control group, n=33, including 12 men, median AHI 2, median age 28). Each participant underwent polysomnography with a recording of 19 EEG channels. Based on wavelet bicoherence (WB), the magnitude of connectivity between all pairs of EEG channels in six bands was estimated: Df1 0.25;1, Df2 1;4, Df3 4;8, Df4 8;12, Df5 12;20, Df6 20;30 Hz. In all six bands considered, we noted a significant decrease in symmetrical interhemispheric connections in OSA patients. Also, in the main group for slow oscillatory activity Df1 and Df2, we observe a decrease in connection values in the EEG channels associated with the central interhemispheric sulcus. In addition, patients with AHI>15 show an increase in intrahemispheric connectivity, in particular, forming a left hemisphere high-degree synchronization node (connections PzT3, PzF3, PzFp1) in the Df2 band. When considering high-frequency EEG oscillations, connectivity in OSA patients again shows a significant increase within the cerebral hemispheres. The revealed differences in functional connectivity in patients with different levels of AHI are quite stable, remaining when averaging the full nocturnal EEG recording, including both the entire sleep duration and night awakenings. The increase in the number of hypoxia episodes correlates with the violation of the symmetry of interhemispheric functional connections. Maximum absolute values of correlation between the apnea-hypopnea index, AHI, and the WB synchronization strength are observed for the Df2 band in symmetrical EEG channels C3C4 (-0.81) and P3P4 (-0.77). The conducted studies demonstrate the possibility of developing diagnostic systems for obstructive sleep apnea syndrome without using signals from the cardiovascular system and respiratory activity.

Early childhood family threat and longitudinal amygdala-mPFC circuit development: Examining cortical thickness and gray matter-white matter contrast

Early threat-associated cortical thinning may be interpreted as accelerated cortical development. However, non-adaptive processes may show similar macrostructural changes. Examining cortical thickness (CT) together with grey/white-matter contrast (GWC), a proxy for intracortical myelination, may enhance the interpretation of CT findings. In this prospective study, we examined associations between early life family-related threat (harsh parenting, family conflict, and neighborhood safety) and CT and GWC development from late childhood to middle adolescence. MRI was acquired from 4200 children (2069 boys) from the Generation R study at ages 8, 10 and 14 years (in total 6114 scans), of whom 1697 children had >1 scans. Linear mixed effect models were used to examine family factor-by-age interactions on amygdala volume, caudal and rostral anterior cingulate (ACC) and medial orbitofrontal cortex (mOFC) CT and GWC. A neighborhood safety-by-age-interaction was found for rostral ACC GWC, suggesting less developmental change in children from unsafe neighborhoods. Moreover, after more stringent correction for motion, family conflict was associated with greater developmental change in CT but less developmental change in GWC. Results suggest that early threat may blunt ACC GWC development. Our results, therefore, do not provide evidence for accelerated threat-associated structural development of the amygdala-mPFC circuit between ages 8-14 years.

Validation of SynthSeg segmentation performance on CT using paired MRI from radiotherapy patients

INTRODUCTION

Manual segmentation of medical images is labor intensive and especially challenging for images with poor contrast or resolution. The presence of disease exacerbates this further, increasing the need for an automated solution. To this extent, SynthSeg is a robust deep learning model designed for automatic brain segmentation across various contrasts and resolutions. This study validates the SynthSeg robust brain segmentation model on computed tomography (CT), using a multi-center dataset.

METHODS

An open access dataset of 260 paired CT and magnetic resonance imaging (MRI) from radiotherapy patients treated in 5 centers was collected. Brain segmentations from CT and MRI were obtained with SynthSeg model, a component of the Freesurfer imaging suite. These segmentations were compared and evaluated using Dice scores and Hausdorff 95 distance (HD95), treating MRI-based segmentations as the ground truth. Brain regions that failed to meet performance criteria were excluded based on automated quality control (QC) scores.

RESULTS

Dice scores indicate a median overlap of 0.76 (IQR: 0.65-0.83). The mean volume difference is 7.79% (CI: 6.41%-9.18%), with CT segmentations typically smaller than MRI-based. The median HD95 is 2.95 mm (IQR: 1.73-5.39). QC score based thresholding improves median dice by 0.1 and median HD95 by 0.05 mm. Morphological differences related to sex and age, as detected by MRI, were also replicated with CT, with an approximate 17% difference between the CT and MRI results for sex and 10% difference between the results for age.

CONCLUSION

SynthSeg can be utilized for CT-based automatic brain segmentation, but only in applications where precision is not essential. CT performance is lower than MRI based on the integrated QC scores, but low-quality segmentations can be excluded with QC-based thresholding. Additionally, performing CT-based neuroanatomical studies is encouraged, as the results show correlations in sex- and age-based analyses similar to those found with MRI.

Modifiable dementia risk associated with smaller white matter volume and altered 1/f aperiodic brain activity: cross-sectional insights from the LEISURE study

BACKGROUND

The rising prevalence of dementia necessitates identifying early neurobiological markers of dementia risk. Reduced cerebral white matter volume and flattening of the slope of the electrophysiological 1/f spectral power distribution provide neurobiological markers of brain ageing alongside cognitive decline. However, their association with modifiable dementia risk remains to be understood.

METHODS

A cross-sectional sample of 98 healthy older adults (79 females, mean age = 65.44) underwent structural magnetic resonance imaging (sMRI), resting-state electroencephalography (EEG), cognitive assessments and dementia risk scoring using the CogDrisk framework. Univariate and multivariate linear regression models were conducted to investigate the relationships between modifiable dementia risk and sMRI brain volumes, the exponent of EEG 1/f spectral power, and cognition, whilst controlling for non-modifiable factors.

RESULTS

Smaller global white matter volume (F(1,87) = 6.884, R2 = 0.073, P = .010), and not grey (F(1,87) = 0.540, R2 = 0.006, P = .468) or ventricle volume (F(1,87) = 0.087, R2 = 0.001, P = .769), was associated with higher modifiable dementia risk. A lower exponent, reflecting a flatter 1/f spectral power distribution, was associated with higher dementia risk at frontal (F(1,92) = 4.096, R2 = 0.043, P = .046) but not temporal regions. No significant associations were found between cognitive performance and dementia risk. In multivariate analyses, both white matter volume and the exponent of the 1/f spectral power distribution independently associated with dementia risk.

CONCLUSIONS

Structural and functional neurobiological markers of early brain ageing, but not cognitive function, are independently associated with modifiable dementia risk in healthy older adults.

Brain morphometry in former American football players: findings from the DIAGNOSE CTE research project

Exposure to repetitive head impacts in contact sports is associated with neurodegenerative disorders including chronic traumatic encephalopathy (CTE), which currently can be diagnosed only at post-mortem. American football players are at higher risk of developing CTE given their exposure to repetitive head impacts. One promising approach for diagnosing CTE in vivo is to explore known neuropathological abnormalities at post-mortem in living individuals using structural MRI. MRI brain morphometry was evaluated in 170 male former American football players ages 45-74 years (n = 114 professional; n = 56 college) and 54 same-age unexposed asymptomatic male controls (n = 54, age range 45-74). Cortical thickness and volume of regions of interest were selected based on established CTE pathology findings and were assessed using FreeSurfer. Group differences and interactions with age and exposure factors were evaluated using a generalized least squares model. A separate logistic regression and independent multinomial model were performed to predict each traumatic encephalopathy syndrome (TES) diagnosis, core clinical features and provisional level of certainty for CTE pathology using brain regions of interest. Former college and professional American football players (combined) showed significant cortical thickness and/or volume reductions compared to unexposed asymptomatic controls in the hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus, insula, temporal pole and superior frontal gyrus. Post hoc analyses identified group-level differences between former professional players and unexposed asymptomatic controls in the hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus, insula and superior frontal gyrus. Former college players showed significant volume reductions in the hippocampus, amygdala and superior frontal gyrus compared to the unexposed asymptomatic controls. We did not observe Age × Group interactions for brain morphometric measures. Interactions between morphometry and exposure measures were limited to a single significant positive association between the age of first exposure to organized tackle football and right insular volume. We found no significant relationship between brain morphometric measures and the TES diagnosis core clinical features and provisional level of certainty for CTE pathology outcomes. These findings suggested that MRI morphometrics detect abnormalities in individuals with a history of repetitive head impact exposure that resemble the anatomic distribution of pathological findings from post-mortem CTE studies. The lack of findings associating MRI measures with exposure metrics (except for one significant relationship) or TES diagnosis and core clinical features suggested that brain morphometry must be complemented by other types of measures to characterize individuals with repetitive head impacts.

Inflammaging and Brain Aging

Progress made by the medical community in increasing lifespans comes with the costs of increasing the incidence and prevalence of age-related diseases, neurodegenerative ones included. Aging is associated with a series of morphological changes at the tissue and cellular levels in the brain, as well as impairments in signaling pathways and gene transcription, which lead to synaptic dysfunction and cognitive decline. Although we are not able to pinpoint the exact differences between healthy aging and neurodegeneration, research increasingly highlights the involvement of neuroinflammation and chronic systemic inflammation (inflammaging) in the development of age-associated impairments via a series of pathogenic cascades, triggered by dysfunctions of the circadian clock, gut dysbiosis, immunosenescence, or impaired cholinergic signaling. In addition, gender differences in the susceptibility and course of neurodegeneration that appear to be mediated by glial cells emphasize the need for future research in this area and an individualized therapeutic approach. Although rejuvenation research is still in its very early infancy, accumulated knowledge on the various signaling pathways involved in promoting cellular senescence opens the perspective of interfering with these pathways and preventing or delaying senescence.

Contrasting somatic mutation patterns in aging human neurons and oligodendrocytes

Characterizing somatic mutations in the brain is important for disentangling the complex mechanisms of aging, yet little is known about mutational patterns in different brain cell types. Here, we performed whole-genome sequencing (WGS) of 86 single oligodendrocytes, 20 mixed glia, and 56 single neurons from neurotypical individuals spanning 0.4-104 years of age and identified >92,000 somatic single-nucleotide variants (sSNVs) and small insertions/deletions (indels). Although both cell types accumulate somatic mutations linearly with age, oligodendrocytes accumulated sSNVs 81% faster than neurons and indels 28% slower than neurons. Correlation of mutations with single-nucleus RNA profiles and chromatin accessibility from the same brains revealed that oligodendrocyte mutations are enriched in inactive genomic regions and are distributed across the genome similarly to mutations in brain cancers. In contrast, neuronal mutations are enriched in open, transcriptionally active chromatin. These stark differences suggest an assortment of active mutagenic processes in oligodendrocytes and neurons.

Shared Manifold Regularized Joint Feature Selection for Joint Classification and Regression in Alzheimer's Disease Diagnosis

In Alzheimer's disease (AD) diagnosis, joint feature selection for predicting disease labels (classification) and estimating cognitive scores (regression) with neuroimaging data has received increasing attention. In this paper, we propose a model named Shared Manifold regularized Joint Feature Selection (SMJFS) that performs classification and regression in a unified framework for AD diagnosis. For classification, unlike the existing works that build least squares regression models which are insufficient in the ability of extracting discriminative information for classification, we design an objective function that integrates linear discriminant analysis and subspace sparsity regularization for acquiring an informative feature subset. Furthermore, the local data relationships are learned according to the samples' transformed distances to exploit the local data structure adaptively. For regression, in contrast to previous works that overlook the correlations among cognitive scores, we learn a latent score space to capture the correlations and employ the latent space to design a regression model with l2,1 -norm regularization, facilitating the feature selection in regression task. Moreover, the missing cognitive scores can be recovered in the latent space for increasing the number of available training samples. Meanwhile, to capture the correlations between the two tasks and describe the local relationships between samples, we construct an adaptive shared graph to guide the subspace learning in classification and the latent cognitive score learning in regression simultaneously. An efficient iterative optimization algorithm is proposed to solve the optimization problem. Extensive experiments on three datasets validate the discriminability of the features selected by SMJFS.

Brains of endurance athletes differ in the association areas but not in the primary areas

Regular participation in sports results in a series of physiological adaptations. However, little is known about the brain adaptations to physical activity. Here we aimed to investigate whether young endurance athletes and non-athletes differ in the gray and white matter of the brain and whether cardiorespiratory fitness (CRF) is associated with these differences. We assessed the CRF, volumes of the gray and white matter of the brain using structural magnetic resonance imaging (sMRI), and brain white matter connections using diffusion magnetic resonance imaging (dMRI) in 20 young male endurance athletes and 21 healthy non-athletes. While total brain volume was similar in both groups, the white matter volume was larger and the gray matter volume was smaller in the athletes compared to non-athletes. The reduction of gray matter was located in the association areas of the brain that are specialized in processing of sensory stimuli. In the microstructure analysis, significant group differences were found only in the association tracts, for example, the inferior occipito-frontal fascicle (IOFF) showing higher fractional anisotropy and lower radial diffusivity, indicating stronger myelination in this tract. Additionally, gray and white matter brain volumes, as well as association tracts correlated with CRF. No changes were observed in other brain areas or tracts. In summary, the brain signature of the endurance athlete is characterized by changes in the integration of sensory and motor information in the association areas.

Safety, tolerability, and efficacy estimate of evoked gamma oscillation in mild to moderate Alzheimer's disease

Background

Alzheimer's Disease (AD) is a multifactorial, progressive neurodegenerative disease that disrupts synaptic and neuronal activity and network oscillations. It is characterized by neuronal loss, brain atrophy and a decline in cognitive and functional abilities. Cognito's Evoked Gamma Therapy System provides an innovative approach for AD by inducing EEG-verified gamma oscillations through sensory stimulation. Prior research has shown promising disease-modifying effects in experimental AD models. The present study (NCT03556280: OVERTURE) evaluated the feasibly, safety and efficacy of evoked gamma oscillation treatment using Cognito's medical device (CogTx-001) in participants with mild to moderate AD.

Methods

The present study was a randomized, double blind, sham-controlled, 6-months clinical trial in participants with mild to moderate AD. The trial enrolled 76 participants, aged 50 or older, who met the clinical criteria for AD with baseline MMSE scores between 14 and 26. Participants were randomly assigned 2:1 to receive self-administered daily, one-hour, therapy, evoking EEG-verified gamma oscillations or sham treatment. The CogTx-001 device was use at home with the help of a care partner, over 6 months. The primary outcome measures were safety, evaluated by physical and neurological exams and monthly assessments of adverse events (AEs) and MRI, and tolerability, measured by device use. Although the trial was not statistically powered to evaluate potential efficacy outcomes, primary and secondary clinical outcome measures included several cognitive and functional endpoints.

Results

Total AEs were similar between groups, there were no unexpected serious treatment related AEs, and no serious treatment-emergent AEs that led to study discontinuation. MRI did not show Amyloid-Related Imaging Abnormalities (ARIA) in any study participant. High adherence rates (85-90%) were observed in sham and treatment participants. There was no statistical separation between active and sham arm participants in primary outcome measure of MADCOMS or secondary outcome measure of CDR-SB or ADAS-Cog14. However, some secondary outcome measures including ADCS-ADL, MMSE, and MRI whole brain volume demonstrated reduced progression in active compared to sham treated participants, that achieved nominal significance.

Conclusion

Our results demonstrate that 1-h daily treatment with Cognito's Evoked Gamma Therapy System (CogTx-001) was safe and well-tolerated and demonstrated potential clinical benefits in mild to moderate AD.Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03556280.

Noninvasive Gamma Sensory Stimulation May Reduce White Matter and Myelin Loss in Alzheimer's Disease

BACKGROUND

Patients with Alzheimer's disease (AD) demonstrate progressive white matter atrophy and myelin loss. Restoring myelin content or preventing demyelination has been suggested as a therapeutic approach for AD.

OBJECTIVE

Herein, we investigate the effects of non-invasive, combined visual and auditory gamma-sensory stimulation on white matter atrophy and myelin content loss in patients with AD.

METHODS

In this study, we used the magnetic resonance imaging (MRI) data from the OVERTURE study (NCT03556280), a randomized, controlled, clinical trial in which active treatment participants received daily, non-invasive, combined visual and auditory, 40 Hz stimulation for six months. A subset of OVERTURE participants who meet the inclusion criteria for detailed white matter (N = 38) and myelin content (N = 36) assessments are included in the analysis. White matter volume assessments were performed using T1-weighted MRI, and myelin content assessments were performed using T1-weighted/T2-weighted MRI. Treatment effects on white matter atrophy and myelin content loss were assessed.

RESULTS

Combined visual and auditory gamma-sensory stimulation treatment is associated with reduced total and regional white matter atrophy and myelin content loss in active treatment participants compared to sham treatment participants. Across white matter structures evaluated, the most significant changes were observed in the entorhinal region.

CONCLUSIONS

The study results suggest that combined visual and auditory gamma-sensory stimulation may modulate neuronal network function in AD in part by reducing white matter atrophy and myelin content loss. Furthermore, the entorhinal region MRI outcomes may have significant implications for early disease intervention, considering the crucial afferent connections to the hippocampus and entorhinal cortex.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration

INTRODUCTION

Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification.

MATERIALS AND METHODS

We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition.

RESULTS

CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration.

DISCUSSION

These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation.

HIGHLIGHTS

Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Graph-Based Fusion of Imaging, Genetic and Clinical Data for Degenerative Disease Diagnosis

Graph learning methods have achieved noteworthy performance in disease diagnosis due to their ability to represent unstructured information such as inter-subject relationships. While it has been shown that imaging, genetic and clinical data are crucial for degenerative disease diagnosis, existing methods rarely consider how best to use their relationships. How best to utilize information from imaging, genetic and clinical data remains a challenging problem. This study proposes a novel graph-based fusion (GBF) approach to meet this challenge. To extract effective imaging-genetic features, we propose an imaging-genetic fusion module which uses an attention mechanism to obtain modality-specific and joint representations within and between imaging and genetic data. Then, considering the effectiveness of clinical information for diagnosing degenerative diseases, we propose a multi-graph fusion module to further fuse imaging-genetic and clinical features, which adopts a learnable graph construction strategy and a graph ensemble method. Experimental results on two benchmarks for degenerative disease diagnosis (Alzheimers Disease Neuroimaging Initiative and Parkinson's Progression Markers Initiative) demonstrate its effectiveness compared to state-of-the-art graph-based methods. Our findings should help guide further development of graph-based models for dealing with imaging, genetic and clinical data.

Sex moderates the association between age and myelin water fraction in the cingulum and fornix among older adults without dementia

Background

Decreasing white matter integrity in limbic pathways including the fornix and cingulum have been reported in Alzheimer's disease (AD), although underlying mechanisms and potential sex differences remain understudied. We therefore sought to explore sex as a moderator of the effect of age on myelin water fraction (MWF), a measure of myelin content, in older adults without dementia (N = 52).

Methods

Participants underwent neuropsychological evaluation and 3 T MRI at two research sites. Multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) quantified MWF in 3 a priori regions including the fornix, hippocampal cingulum (CgH), and cingulate cingulum (CgC). The California Verbal Learning Test-Second Edition assessed learning and delayed recall. Multiple linear regressions assessed for (1) interactions between age and sex on regional MWF and (2) associations of regional MWF and memory.

Results

(1) There was a significant age by sex interaction on MWF of the fornix (p = 0.002) and CgC (p = 0.005), but not the CgH (p = 0.192); as age increased, MWF decreased in women but not men. (2) Fornix MWF was associated with both learning and recall (ps < 0.01), but MWF of the two cingulum regions were not (p > 0.05). Results were unchanged when adjusting for hippocampal volume.

Conclusion

The current work adds to the literature by illuminating sex differences in age-related myelin decline using a measure sensitive to myelin and may help facilitate detection of AD risk for women.

The effect of processing pipelines, input images and age on automatic cortical morphology estimates

BACKGROUND AND OBJECTIVE

Magnetic resonance imaging of the brain allows to enrich the study of the relationship between cortical morphology, healthy ageing, diseases and cognition. Since manual segmentation of the cerebral cortex is time consuming and subjective, many software packages have been developed. FreeSurfer (FS) and Advanced Normalization Tools (ANTs) are the most used and allow as inputs a T1-weighted (T1w) image or its combination with a T2-weighted (T2w) image. In this study we evaluated the impact of different software and input images on cortical estimates. Additionally, we investigated whether the variation of the results depending on software and inputs is also influenced by age.

METHODS

For 240 healthy subjects, cortical thickness was computed with ANTs and FreeSurfer. Estimates were derived using both the T1w image and adding the T2w image. Significant effects due to software, input images and age range were investigated with ANOVA statistical analysis. Moreover, the accuracy of the cortical thickness estimates was assessed based on their age-prediction precision.

RESULTS

Using FreeSurfer and ANTs with T1w or T1w-T2w images resulted in significant differences in the cortical thickness estimates. These differences change with the age range of the subjects. Regardless of the images used, the more recent FS version tested exhibited the best performances in terms of age prediction.

CONCLUSIONS

Our study points out the importance of i) consistently processing data using the same tool; ii) considering the software, input images and the age range of the subjects when comparing multiple studies.

Lipidomic Alterations in the Cerebral Cortex and White Matter in Sporadic Alzheimer's Disease

Non-targeted LC-MS/MS-based lipidomic analysis was conducted in post-mortem human grey matter frontal cortex area 8 (GM) and white matter of the frontal lobe centrum semi-ovale (WM) to identify lipidome fingerprints in middle-aged individuals with no neurofibrillary tangles and senile plaques, and cases at progressive stages of sporadic Alzheimer's disease (sAD). Complementary data were obtained using RT-qPCR and immunohistochemistry. The results showed that WM presents an adaptive lipid phenotype resistant to lipid peroxidation, characterized by a lower fatty acid unsaturation, peroxidizability index, and higher ether lipid content than the GM. Changes in the lipidomic profile are more marked in the WM than in GM in AD with disease progression. Four functional categories are associated with the different lipid classes affected in sAD: membrane structural composition, bioenergetics, antioxidant protection, and bioactive lipids, with deleterious consequences affecting both neurons and glial cells favoring disease progression.

Adenosine A2A receptor availability in cerebral gray and white matter of patients with Parkinson's disease

OBJECTIVE

Atrophic changes in cerebral gray matter of patients with PD have been reported extensively. There is evidence suggesting an association between cortical gyrification changes and white matter abnormalities. Adenosine A2A receptors have been shown to be upregulated in cerebral white matter and on reactive astrocytes in preclinical models of neurodegenerative diseases. We, therefore, sought to investigate in vivo changes in A2A receptor availability in cerebral gray and white matter of PD patients and its association with gray matter atrophy.

METHODS

Eighteen patients with PD without dyskinesia and seven healthy controls were enrolled for this study. Brain MRI and dynamic PET scan was acquired with [11C]TMSX radioligand which binds selectively to A2A receptors. FreeSurfer software was used to segment cerebral gray and white matter structures. The resulting masks were used to calculate region specific volumes and to derive distribution volume ratios (DVRs), after co-registration with PET images, for the quantification of specific [11C]TMSX binding.

RESULTS

We showed an increase in A2A receptor availability in frontal (P < 0.001) and parietal (P < 0.001) white matter and a decrease in occipital (P = 0.02) gray matter of PD patients as compared to healthy controls. A decrease in gray matter volume ratios was observed in frontal (P < 0.01), parietal (P < 0.001), temporal (P < 0.01) and occipital (P < 0.01) ROIs in patients with PD versus healthy controls.

CONCLUSIONS

Our results suggest a role of A2A receptor-based signaling in the neurodegenerative changes seen in the cerebral gray and white matter of patients with PD.

White matter hyperintensities in former American football players

INTRODUCTION

The presentation, risk factors, and etiologies of white matter hyperintensities (WMH) in people exposed to repetitive head impacts are unknown. We examined the burden and distribution of WMH, and their association with years of play, age of first exposure, and clinical function in former American football players.

METHODS

A total of 149 former football players and 53 asymptomatic unexposed participants (all men, 45-74 years) completed fluid-attenuated inversion recovery magnetic resonance imaging, neuropsychological testing, and self-report neuropsychiatric measures. Lesion Segmentation Toolbox estimated WMH. Analyses were performed in the total sample and stratified by age 60.

RESULTS

In older but not younger participants, former football players had greater total, frontal, temporal, and parietal log-WMH compared to asymptomatic unexposed men. In older but not younger former football players, greater log-WMH was associated with younger age of first exposure to football and worse executive function.

DISCUSSION

In older former football players, WMH may have unique presentations, risk factors, and etiologies.

HIGHLIGHTS

Older but not younger former football players had greater total, frontal, temporal, and parietal lobe white matter hyperintensities (WMH) compared to same-age asymptomatic unexposed men. Younger age of first exposure to football was associated with greater WMH in older but not younger former American football players. In former football players, greater WMH was associated with worse executive function and verbal memory.

Evolutionary and genomic perspectives of brain aging and neurodegenerative diseases

This chapter utilizes genomic concepts and evolutionary perspectives to further understand the possible links between typical brain aging and neurodegenerative diseases, focusing on the two most prevalent of these: Alzheimer's disease and Parkinson's disease. Aging is the major risk factor for these neurodegenerative diseases. Researching the evolutionary and molecular underpinnings of aging helps to reveal elements of the typical aging process that leave individuals more vulnerable to neurodegenerative pathologies. Very little is known about the prevalence and susceptibility of neurodegenerative diseases in nonhuman species, as only a few individuals have been observed with these neuropathologies. However, several studies have investigated the evolution of lifespan, which is closely connected with brain size in mammals, and insights can be drawn from these to enrich our understanding of neurodegeneration. This chapter explores the relationship between the typical aging process and the events in neurodegeneration. First, we examined how age-related processes can increase susceptibility to neurodegenerative diseases. Second, we assessed to what extent neurodegeneration is an accelerated form of aging. We found that while at the phenotypic level both neurodegenerative diseases and the typical aging process share some characteristics, at the molecular level they show some distinctions in their profiles, such as variation in genes and gene expression. Furthermore, neurodegeneration of the brain is associated with an earlier onset of cellular, molecular, and structural age-related changes. In conclusion, a more integrative view of the aging process, both from a molecular and an evolutionary perspective, may increase our understanding of neurodegenerative diseases.

Diffusion tensor imaging of superficial prefrontal white matter in healthy aging

The prefrontal cortex (PFC) is a heterogenous structure that is highly susceptible to the effects of aging. Few studies have investigated age effects on the superficial white matter (WM) contained within the PFC using in-vivo magnetic resonance imaging (MRI). This study used diffusion tensor imaging (DTI) tractography to examine the effects of age, sex, and intracranial volume (ICV) on superficial WM within specific PFC subregions, and to model the relationships with age using higher order polynomial regression modelling. PFC WM of 140 healthy individuals, aged 18-85, was segmented into medial and lateral orbitofrontal, medial prefrontal, and dorsolateral prefrontal subregions. Differences due to age in microstructural parameters such as fractional anisotropy (FA), axial and radial diffusivities, and macrostructural measures of tract volumes, fiber counts, average fiber lengths, and average number of fibers per voxel were examined. We found that most prefrontal subregions demonstrated age effects, with decreases in FA, tract volume, and fiber counts, and increases in all diffusivity measures. Age relationships were mostly non-linear, with higher order regressions chosen in most cases. Declines in PFC FA began at the onset of adulthood while the greatest changes in diffusivity and volume did not occur until middle age. The effects of age were most prominent in medial tracts while the lateral orbitofrontal tracts were less affected. Significant effects of sex and ICV were also observed in certain parameters. The patterns mostly followed myelination order, with late-myelinating prefrontal subregions experiencing earlier and more pronounced age effects, further supporting the frontal theory of aging.

Contrasting patterns of somatic mutations in neurons and glia reveal differential predisposition to disease in the aging human brain

Characterizing the mechanisms of somatic mutations in the brain is important for understanding aging and disease, but little is known about the mutational patterns of different cell types. We performed whole-genome sequencing of 71 oligodendrocytes and 51 neurons from neurotypical individuals (0.4 to 104 years old) and identified >67,000 somatic single nucleotide variants (sSNVs) and small insertions and deletions (indels). While both cell types accumulate mutations with age, oligodendrocytes accumulate sSNVs 69% faster than neurons (27/year versus 16/year) whereas indels accumulate 42% slower (1.8/year versus 3.1/year). Correlation with single-cell RNA and chromatin accessibility from the same brains revealed that oligodendrocyte mutations are enriched in inactive genomic regions and are distributed similarly to mutations in brain cancers. In contrast, neuronal mutations are enriched in open, transcriptionally active chromatin. These patterns highlight differences in the mutagenic processes in glia and neurons and suggest cell type-specific, age-related contributions to neurodegeneration and oncogenesis.

Sex difference in the associations of socioeconomic status, cognitive function and brain volume with dementia in old adults: Findings from the OASIS study

Background

Sex differences in the association of cognitive function and imaging measures with dementia have not been fully investigated while sex-based investigation of dementia has been discussed. Understanding sex differences in the dementia-related socioeconomic, cognitive, and imaging measurements is important for uncovering sex-related pathways to dementia and facilitating early diagnosis, family planning, and cost control.

Methods

We selected data from the Open Access Series of Imaging Studies with longitudinal measurements of brain volumes on 150 individuals aged 60 to 96 years. Dementia status was determined using the Clinical Dementia Rating (CDR) scale, and Alzheimer's disease was diagnosed as a CDR of ≥ 0.5. Generalized estimating equation models were used to estimate the associations of socioeconomic, cognitive and imaging factors with dementia in men and women.

Results

Lower education affected dementia more in women than in men. Age, education, Mini-Mental State Examination (MMSE), and normalized whole-brain volume (nWBV) were associated with dementia in women whereas only MMSE and nWBV were associated with dementia in men. Lower socioeconomic status was associated with a reduced estimated total intracranial volume in men, but not in women. Ageing and lower MMSE scores were associated with reduced nWBV in both men and women.

Conclusions

The association between education and prevalence of dementia differs in men and women. Women may have more risk factors for dementia than men.

Longitudinal Patterns of Brain Changes in a Community Sample in Relation to Aging and Cognitive Status

BACKGROUND

Aging and Alzheimer's disease (AD) are characterized by widespread cortical and subcortical atrophy. Though atrophy patterns between aging and AD overlap considerably, regional differences between these two conditions may exist. Few studies, however, have investigated these patterns in large community samples.

OBJECTIVE

Elaborate longitudinal changes in brain morphometry in relation to aging and cognitive status in a well-characterized community cohort.

METHODS

Clinical and neuroimaging data were compiled from 72 participants from the Cardiovascular Health Study-Cognition Study, a community cohort of healthy aging and probable AD participants. Two time points were identified for each participant with a mean follow-up time of 5.36 years. MRI post-processing, morphometric measurements, and statistical analyses were performed using FreeSurfer, Version 7.1.1.

RESULTS

Cortical volume was significantly decreased in the bilateral superior frontal, bilateral inferior parietal, and left superior parietal regions, among others. Cortical thickness was significantly reduced in the bilateral superior frontal and left inferior parietal regions, among others. Overall gray and white matter volumes and hippocampal subfields also demonstrated significant reductions. Cortical volume atrophy trajectories between cognitively stable and cognitively declined participants were significantly different in the right postcentral region.

CONCLUSION

Observed volume reductions were consistent with previous studies investigating morphometric brain changes. Patterns of brain atrophy between AD and aging may be different in magnitude but exhibit widespread spatial overlap. These findings help characterize patterns of brain atrophy that may reflect the general population. Larger studies may more definitively establish population norms of aging and AD-related neuroimaging changes.

Neurobiological Mechanisms of Cognitive Decline Correlated with Brain Aging

Cognitive decline has emerged as one of the greatest health threats of old age. Meanwhile, aging is the primary risk factor for Alzheimer's disease (AD) and other prevalent neurodegenerative disorders. Developing therapeutic interventions for such conditions demands a greater understanding of the processes underlying normal and pathological brain aging. Despite playing an important role in the pathogenesis and incidence of disease, brain aging has not been well understood at a molecular level. Recent advances in the biology of aging in model organisms, together with molecular- and systems-level studies of the brain, are beginning to shed light on these mechanisms and their potential roles in cognitive decline. This chapter seeks to integrate the knowledge about the neurological mechanisms of age-related cognitive changes that underlie aging.

TREM2 dependent and independent functions of microglia in Alzheimer's disease

Microglia are central players in brain innate immunity and have been the subject of extensive research in Alzheimer's disease (AD). In this review, we aim to summarize the genetic and functional discoveries that have advanced our understanding of microglia reactivity to AD pathology. Given the heightened AD risk posed by rare variants of the microglial triggering receptor expressed on myeloid cells 2 (TREM2), we will focus on the studies addressing the impact of this receptor on microglia responses to amyloid plaques, tauopathy and demyelination pathologies in mouse and human. Finally, we will discuss the implications of recent discoveries on microglia and TREM2 biology on potential therapeutic strategies for AD.

Vitamin D deficit is associated with accelerated brain aging in the general population

Vitamin D deficiency has been associated with reduced neurocognitive functioning and the neurodegenerative processes. However, existing evidence on brain structural correlates of vitamin D deficiency is controversial. We sought to investigate associations of vitamin D levels with imaging patterns of brain aging. In addition, we investigated whether low vitamin D levels were associated with gray matter volumes, whole brain volumes and hippocampus volumes. Structural MRI data and vitamin D levels were obtained in 1,865 subjects from the general population. Linear regressions were applied to investigate the association of vitamin D levels and vitamin D deficiency with imaging derived brain age, total brain, gray matter and hippocampal volumes. Different sets of covariates were included. Vitamin D deficiency was significantly associated with increased brain age. Also, linear vitamin D levels were significantly associated with total brain and gray matter volumes, while no significant association with hippocampal volume was found. Further interaction analyses showed that this association was only significant for male subjects. Our results support previous findings suggesting that vitamin D-deficient individuals have an accelerated brain aging. In addition, associations between vitamin D levels and total brain/ gray matter volumes suggest neuroprotective effects of vitamin D on the brain.

Both brain size and biological sex contribute to variation in white matter microstructure in middle-aged healthy adults

Whether head size and/or biological sex influence proxies of white matter (WM) microstructure such as fractional anisotropy (FA) and mean diffusivity (MD) remains controversial. Diffusion tensor imaging (DTI) indices are also associated with age, but there are large discrepancies in the spatial distribution and timeline of age-related differences reported. The aim of this study was to evaluate the associations between intracranial volume (ICV), sex, and age and DTI indices from WM in a population-based study of healthy individuals (n = 812) aged 50-66 in the Nord-Trøndelag health survey. Semiautomated tractography and tract-based spatial statistics (TBSS) analyses were performed on the entire sample and in an ICV-matched sample of men and women. The tractography results showed a similar positive association between ICV and FA in all major WM tracts in men and women. Associations between ICV and MD, radial diffusivity and axial diffusivity were also found, but to a lesser extent than FA. The TBSS results showed that both men and women had areas of higher and lower FA when controlling for age, but after controlling for age and ICV only women had areas with higher FA. The ICV matched analysis also demonstrated that only women had areas of higher FA. Age was negatively associated with FA across the entire WM skeleton in the TBSS analysis, independent of both sex and ICV. Combined, these findings demonstrated that both ICV and sex contributed to variation in DTI indices and emphasized the importance of considering ICV as a covariate in DTI analysis.

Association of physical activity levels and brain white matter in older Latino adults

OBJECTIVE

Investigate the associations between self-reported physical activity (PA) engagement and white matter (WM) health (i.e. volume, integrity, and hyperintensities) in older Latinos.

DESIGN

Cross-sectional study with community-dwelling older adults from predominantly Latino neighborhoods. Participants: Thirty-four cognitively healthy older Latinos from two different cohorts. Measurements: Participants self-reported demographic information, PA engagement [Community Healthy Activities Model Program for Seniors (CHAMPS) Physical Activity Questionnaire for Older Adults] and magnetic resonance imaging (MRI). We used high-resolution three-dimensional T1- and T2-FLAIR weighted images and diffusion tensor imaging acquired via 3 T MRI. We performed a series of hierarchical linear regression models with the addition of relevant covariates to examine the associations between self-reported PA levels and WM volume, integrity, and hyperintensities (separately). We adjusted p-values with the use of the Benjamini-Hochberg's false discovery rate procedure.

RESULTS

Higher reported levels of leisure-time moderate-to-vigorous PA were significantly associated with higher WM volume of the posterior cingulate (β = 0.220, SE = 0.125, 95% CI 0.009-0.431, p = 0.047) and isthmus cingulate (β = 0.212, SE = 0.110, 95% CI 0.001-0.443, p = 0.044) after controlling for intracranial volume. Higher levels of total PA were significantly associated with higher overall WM volume of these same regions (posterior cingulate: β = 0.220, SE = 0.125, CI 0.024-0.421, p = 0.046; isthmus cingulate: β = 0.220, SE = 0.125, 95% CI 0.003-0.393; p = 0.040). Significant p-values did not withstand Benjamini-Hochberg's adjustment. PA was not significantly associated with WM integrity or WM hyperintensities.

CONCLUSION

Higher levels of PA, particularly higher leisure-time moderate-to-vigorous PA, might be associated with greater WM volume in select white matter regions key to brain network integration for physical and cognitive functioning in older Latinos. More research is needed to further confirm these associations.

Imaging of Normal Brain Aging

Understanding normal brain aging physiology is essential to improving healthy human longevity, differentiation, and early detection of diseases, such as neurodegenerative diseases, which are an enormous social and economic burden. Functional decline, such as reduced physical activity and cognitive abilities, is typically associated with brain aging. The authors summarize the aging brain mechanism and effects of aging on the brain observed by brain structural MR imaging and advanced neuroimaging techniques, such as diffusion tensor imaging and functional MR imaging.

Neural Mechanisms of Perceiving and Subsequently Recollecting Emotional Facial Expressions in Young and Older Adults

It is known that emotional facial expressions modulate the perception and subsequent recollection of faces and that aging alters these modulatory effects. Yet, the underlying neural mechanisms are not well understood, and they were the focus of the current fMRI study. We scanned healthy young and older adults while perceiving happy, neutral, or angry faces paired with names. Participants were then provided with the names of the faces and asked to recall the facial expression of each face. fMRI analyses focused on the fusiform face area (FFA), the posterior superior temporal sulcus (pSTS), the OFC, the amygdala, and the hippocampus (HC). Univariate activity, multivariate pattern (MVPA), and functional connectivity analyses were performed. The study yielded two main sets of findings. First, in pSTS and the amygdala, univariate activity and MVPA discrimination during the processing of facial expressions were similar in young and older adults, whereas in FFA and OFC, MVPA discriminated facial expressions less accurately in older than young adults. These findings suggest that facial expression representations in FFA and OFC reflect age-related dedifferentiation and positivity effect. Second, HC-OFC connectivity showed subsequent memory effects (SMEs) for happy expressions in both age groups, HC-FFA connectivity exhibited SMEs for happy and neutral expressions in young adults, and HC-pSTS interactions displayed SMEs for happy expressions in older adults. These results could be related to compensatory mechanisms and positivity effects in older adults. Taken together, the results clarify the effects of aging on the neural mechanisms in perceiving and encoding facial expressions.

Aberrant Inter-hemispheric Connectivity in Patients With Recurrent Major Depressive Disorder: A Multimodal MRI Study

Objective

Inter-hemispheric network dysconnectivity has been well-documented in patients with recurrent major depressive disorder (MDD). However, it has remained unclear how structural networks between bilateral hemispheres relate to inter-hemispheric functional dysconnectivity and depression severity in MDD. Our study attempted to investigate the alterations in corpus callosum macrostructural and microstructural as well as inter-hemispheric homotopic functional connectivity (FC) in patients with recurrent MDD and to determine how these alterations are related with depressive severity.

Materials and Methods

Resting-state functional MRI (fMRI), T1WI anatomical images and diffusion tensor MRI of the whole brain were performed in 140 MDD patients and 44 normal controls matched for age, sex, years of education. We analyzed the macrostructural and microstructural integrity as well as voxel-mirrored homotopic functional connectivity (VMHC) of corpus callosum (CC) and its five subregion. Two-sample t-test was used to investigate the differences between the two groups. Significant subregional metrics were correlated with depression severity by spearman's correlation analysis, respectively.

Results

Compared with control subjects, MDD patients had significantly attenuated inter-hemispheric homotopic FC in the bilateral medial prefrontal cortex, and impaired anterior CC microstructural integrity (each comparison had a corrected P < 0.05), whereas CC macrostructural measurements remained stable. In addition, disruption of anterior CC microstructural integrity correlated with a reduction in FC in the bilateral medial prefrontal cortex, which correlated with depression severity in MDD patients. Furthermore, disruption of anterior CC integrity exerted an indirect influence on depression severity in MDD patients through an impairment of inter-hemispheric homotopic FC.

Conclusion

These findings may help to advance our understanding of the neurobiological basis of depression by identifying region-specific interhemispheric dysconnectivity.

An aberrant hippocampal subregional network, rather than structure, characterizes major depressive disorder

BACKGROUND

Behavioral and neuroimaging studies have implicated the hippocampus as a cardinal neural structure in major depressive disorder (MDD) pathogenesis. The hippocampal subregion-specific structural and functional abnormalities in MDD remain unknown.

METHODS

Multimodal magnetic resonance imaging (MRI) was acquired in 140 patients with MDD and 44 age- and sex-matched healthy controls (HCs). We quantified hippocampal subregional volumes and fractional anisotropy (FA) following a structural and diffusion MRI data analysis processing stream. Hippocampal subregional networks were established using seed-based functional connectivity (FC) analysis. Univariate analysis was used to investigate the differences between the two groups. Significant subfield metrics were correlated with depression severity.

RESULTS

Compared with HCs, we did not find significant differences in subregional volumes or FA metrics in the MDD group. The MDD group exhibited a significantly weaker connectivity of the right hippocampal subregional networks with the temporal cortex (extending to the insula) and basal ganglia but showed increased connectivity of the right subiculum to the bilateral lingual gyrus. The FC between the right cornu ammonis 1 and right fusiform, between the right hippocampal amygdala transition area and the bilateral basal ganglia, were negatively correlated with depression severity (r = -0.224, p = 0.010; r = -0.196, p = 0.025, respectively) in the MDD group.

LIMITATIONS

This study did not consider the longitudinal changes in the structure and functional connectivity of the hippocampal subregion.

CONCLUSION

These findings advance our understanding of the neurobiological basis of depression by identifying the hippocampal subregional structural and functional abnormalities.

Association Between Microstructural Asymmetry of Temporal Lobe White Matter and Memory Decline After Anterior Temporal Lobectomy

BACKGROUND AND OBJECTIVES

Risk for memory decline is a substantial concern in patients with temporal lobe epilepsy (TLE) undergoing anterior temporal lobectomy (ATL). Although prior studies have identified associations between memory and integrity of white matter (WM) networks within the medial temporal lobe (MTL) preoperatively, we contribute a study examining whether microstructural asymmetry of deep and superficial WM networks within the MTL predicts postoperative memory decline.

METHODS

Patients with drug-resistant TLE were recruited from 2 epilepsy centers in a prospective longitudinal study. All patients completed preoperative T1 and diffusion-weighted MRI (DWI) as well as preoperative and postoperative neuropsychological testing. Preoperative fractional anisotropy (FA) of the WM directly beneath the neocortex (i.e., superficial WM [SWM]) and of deep WM tracts associated with memory were calculated. Asymmetry was calculated for hippocampal volume and FA of each WM tract or region and examined in linear and logistic regressions with preoperative to postoperative memory change as the primary outcome.

RESULTS

Data were analyzed from 42 patients with TLE (19 left TLE [LTLE], 23 right TLE [RTLE]) who underwent ATL. Leftward FA asymmetry of the entorhinal SWM was associated with decline on prose and associative recall in LTLE, whereas leftward FA asymmetry of the uncinate fasciculus (UNC) was associated with decline on prose recall only. After controlling for preoperative memory score and hippocampal volume, leftward FA asymmetry of the entorhinal SWM uniquely contributed to decline in both prose and associative recall (β = -0.46; SE 0.14 and β = -0.68; SE 0.22, respectively) and leftward FA asymmetry of the UNC uniquely contributed to decline in prose recall (β = -0.31; SE 0.14). A model combining asymmetry of hippocampal volume and entorhinal FA correctly classified memory outcomes in 79% of patients with LTLE for prose (area under the curve [AUC] 0.89; sensitivity 82%; specificity 75%) and 81% of patients for associative (AUC 0.79; sensitivity 83%; specificity 80%) recall. Entorhinal SWM asymmetry was the strongest predictor in both models.

DISCUSSION

Preoperative asymmetry of deep WM and SWM integrity within the MTL is a strong predictor of postoperative memory decline in TLE, suggesting that surgical decision-making may benefit from considering each patient's WM network adequacy and reserve in addition to hippocampal integrity.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that preoperative asymmetry of deep WM and SWM integrity within the MTL is a predictor of postoperative memory decline.

White matter-associated microglia: New players in brain aging and neurodegenerative diseases

There has been growing interest in brain aging and rejuvenation. It is well known that brain aging is one of the leading causes of neurodegenerative diseases, such as Alzheimer's disease, but brain aging alone can cause cognitive decline. Microglia are thought to act as 'conductors' of white matter aging by modulating diverse glial cells and phagocytosing white matter-derived myelin debris. A recent study identified a specific subpopulation of microglia in the white matter of aged mice, termed white matter-associated microglia (WAM). Additionally, senescent microglia show impaired phagocytic function and altered lipid metabolism, which cause accumulation of lipid metabolites and eventually lead to myelin sheath degeneration. These results suggest that senescent WAM could be pivotal players in axonal loss during brain aging. The aim of this review is to assess the current state of knowledge on brain aging, with an emphasis on the roles of the white matter and microglia, and suggest potential approaches for rejuvenating the aged brain.

Qualitative and Quantitative Comparison of Hippocampal Volumetric Software Applications: Do All Roads Lead to Rome?

Brain volumetric software is increasingly suggested for clinical routine. The present study quantifies the agreement across different software applications. Ten cases with and ten gender- and age-adjusted healthy controls without hippocampal atrophy (median age: 70; 25–75% range: 64–77 years and 74; 66–78 years) were retrospectively selected from a previously published cohort of Alzheimer’s dementia patients and normal ageing controls. Hippocampal volumes were computed based on 3 Tesla T1-MPRAGE-sequences with FreeSurfer (FS), Statistical-Parametric-Mapping (SPM; Neuromorphometrics and Hammers atlases), Geodesic-Information-Flows (GIF), Similarity-and-Truth-Estimation-for-Propagated-Segmentations (STEPS), and Quantib™. MTA (medial temporal lobe atrophy) scores were manually rated. Volumetric measures of each individual were compared against the mean of all applications with intraclass correlation coefficients (ICC) and Bland–Altman plots. Comparing against the mean of all methods, moderate to low agreement was present considering categorization of hippocampal volumes into quartiles. ICCs ranged noticeably between applications (left hippocampus (LH): from 0.42 (STEPS) to 0.88 (FS); right hippocampus (RH): from 0.36 (Quantib™) to 0.86 (FS). Mean differences between individual methods and the mean of all methods [mm³] were considerable (LH: FS −209, SPM-Neuromorphometrics −820; SPM-Hammers −1474; Quantib™ −680; GIF 891; STEPS 2218; RH: FS −232, SPM-Neuromorphometrics −745; SPM-Hammers −1547; Quantib™ −723; GIF 982; STEPS 2188). In this clinically relevant sample size with large spread in data ranging from normal aging to severe atrophy, hippocampal volumes derived by well-accepted applications were quantitatively different. Thus, interchangeable use is not recommended.

The importance of basal-temporal white matter to pre- and post-surgical naming ability in temporal lobe epilepsy

OBJECTIVE

Emerging research highlights the importance of basal-temporal cortex, centered on the fusiform gyrus, to both pre-surgical naming ability and post-surgical naming outcomes in temporal lobe epilepsy (TLE). In this study, we investigate whether integrity of the white matter network that interconnects this basal region to the distributed language network affects naming ability and risk for post-surgical naming decline.

METHODS

Patients with drug-resistant TLE were recruited from two epilepsy centers in a prospective longitudinal study. The pre-surgical dataset included 50 healthy controls, 47 left TLE (L-TLE), and 41 right TLE (R-TLE) patients. All participants completed pre-surgical T1- and diffusion-weighted MRI (dMRI), as well as neuropsychological tests of auditory and visual naming. Nineteen L-TLE and 18 R-TLE patients underwent anterior temporal lobectomy (ATL) and also completed post-surgical neuropsychological testing. Pre-surgical fractional anisotropy (FA) of the white matter directly beneath the fusiform neocortex (i.e., superficial white matter; SWM) and of deep white matter tracts with connections to the basal-temporal cortex [inferior longitudinal fasciculus (ILF) and inferior frontal occipital fasciculus (IFOF)] was calculated. Clinical variables, hippocampal volume, and FA of each white matter tract or region were examined in linear regressions with naming scores, or change in naming scores, as the primary outcomes.

RESULTS

Pre-surgically, higher FA in the bilateral ILF, bilateral IFOF, and left fusiform SWM was associated with better visual and auditory naming scores (all ps < 0.05 with FDR correction). In L-TLE, higher pre-surgical FA was also associated with less naming decline post-surgically, but results varied across tracts. When including only patients with typical language dominance, only integrity of the right fusiform SWM was associated with less visual naming decline (p = .0018).

DISCUSSION

Although a broad network of white matter network matter may contribute to naming ability pre-surgically, the reserve capacity of the contralateral (right) fusiform SWM may be important for mitigating visual naming decline following ATL in L-TLE. This shows that the study of the structural network interconnecting the basal-temporal region to the wider language network has implications for understanding both pre- and post-surgical naming in TLE.

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.

Bidirectional Association Between Sleep and Brain Atrophy in Aging

Human brain aging is characterized by the gradual deterioration of its function and structure, affected by the interplay of a multitude of causal factors. The sleep, a periodically repeating state of reversible unconsciousness characterized by distinct electrical brain activity, is crucial for maintaining brain homeostasis. Indeed, insufficient sleep was associated with accelerated brain atrophy and impaired brain functional connectivity. Concurrently, alteration of sleep-related transient electrical events in senescence was correlated with structural and functional deterioration of brain regions responsible for their generation, implying the interconnectedness of sleep and brain structure. This review discusses currently available data on the link between human brain aging and sleep derived from various neuroimaging and neurophysiological methods. We advocate the notion of a mutual relationship between the sleep structure and age-related alterations of functional and structural brain integrity, pointing out the position of high-quality sleep as a potent preventive factor of early brain aging and neurodegeneration. However, further studies are needed to reveal the causality of the relationship between sleep and brain aging.

Eccentric rehabilitation induces white matter plasticity and sensorimotor recovery in chronic spinal cord injury

Experience-dependent white matter plasticity offers new potential for rehabilitation-induced recovery after neurotrauma. This first-in-human translational experiment combined myelin water imaging in humans and genetic fate-mapping of oligodendrocyte lineage cells in mice to investigate whether downhill locomotor rehabilitation that emphasizes eccentric muscle actions promotes white matter plasticity and recovery in chronic, incomplete spinal cord injury (SCI). In humans, of 20 individuals with SCI that enrolled, four passed the imaging screen and had myelin water imaging before and after a 12-week (3 times/week) downhill locomotor treadmill training program (SCI + DH). One individual was excluded for imaging artifacts. Uninjured control participants (n = 7) had two myelin water imaging sessions within the same day. Changes in myelin water fraction (MWF), a histopathologically-validated myelin biomarker, were analyzed in a priori motor learning and non-motor learning brain regions and the cervical spinal cord using statistical approaches appropriate for small sample sizes. PDGFRα-CreER^T2:mT/mG mice, that express green fluorescent protein on oligodendrocyte precursor cells and subsequent newly-differentiated oligodendrocytes upon tamoxifen-induced recombination, were either naive (n = 6) or received a moderate (75 kilodyne), contusive SCI at T9 and were randomized to downhill training (n = 6) or unexercised groups (n = 6). We initiated recombination 29 days post-injury, seven days prior to downhill training. Mice underwent two weeks of daily downhill training on the same 10% decline grade used in humans. Between-group comparison of functional (motor and sensory) and histological (oligodendrogenesis, oligodendroglial/axon interaction, paranodal structure) outcomes occurred post-training. In humans with SCI, downhill training increased MWF in brain motor learning regions (postcentral, precuneus) and mixed motor and sensory tracts of the ventral cervical spinal cord compared to control participants (P < 0.05). In mice with thoracic SCI, downhill training induced oligodendrogenesis in cervical dorsal and lateral white matter, increased axon-oligodendroglial interactions, and normalized paranodal structure in dorsal column sensory tracts (P < 0.05). Downhill training improved sensorimotor recovery in mice by normalizing hip and knee motor control and reducing hyperalgesia, both of which were associated with new oligodendrocytes in the cervical dorsal columns (P < 0.05). Our findings indicate that eccentric-focused, downhill rehabilitation promotes white matter plasticity and improved function in chronic SCI, likely via oligodendrogenesis in nervous system regions activated by the training paradigm. Together, these data reveal an exciting role for eccentric training in white matter plasticity and sensorimotor recovery after SCI.

Brain aging mechanisms with mechanical manifestations

Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.

Association of Superficial White Matter Alterations with Cerebrospinal Fluid Biomarkers and Cognitive Decline in Neurodegenerative Dementia

BACKGROUND

Superficial white matter (SWM) alterations correlated with cognitive decline have been described in Alzheimer's disease (AD).

OBJECTIVE

The study aims to extend the investigation of the SWM alterations to AD and non-AD neurodegenerative dementia (ND) and explore the relationship with cerebrospinal fluid (CSF) biomarkers and clinical data.

METHODS

From a database of 323 suspected dementia cases, we retrospectively recruited 55 ND with abnormal amyloid-β42 (AD) and 38 ND with normal amyloid-β42 (non-AD) and collected clinical data, CSF biomarkers, and magnetic resonance images. Ten healthy controls (HC) were recruited for imaging and Mini-Mental State Examination (MMSE). Diffusion tensor imaging (DTI) measurements were performed in the lobar SWM regions and Kruskal Wallis tests were used for among-group comparison. Spearman's correlation tests were performed between DTI measures, CSF biomarkers, and clinical data.

RESULTS

AD and non-AD showed significant differences in the DTI measures across the SWM compared to HC. Significant differences between AD and non-AD were detected in the left parietal lobe. DTI measures correlated with amyloid-β42 and MMSE diffusely in the SWM, less extensively with total-tau and phosphorylated tau, and with disease duration in the parietal lobe bilaterally.

CONCLUSION

Widespread SWM alterations occur in both AD and non-AD ND and AD shows appreciably more severe alterations in the parietal SWM. Notably, the alterations in the SWM are strongly linked not only to the cognitive decline but also to the diagnostic CSF biomarkers. Further studies are encouraged to evaluate the DTI measures in the SWM as in vivo non-invasive biomarkers in the preclinical phase.

Neurodegeneration Over 3 Years Following Ischaemic Stroke: Findings From the Cognition and Neocortical Volume After Stroke Study

Background: Stroke survivors are at high risk of dementia, associated with increasing age and vascular burden and with pre-existing cognitive impairment, older age. Brain atrophy patterns are recognised as signatures of neurodegenerative conditions, but the natural history of brain atrophy after stroke remains poorly described. We sought to determine whether stroke survivors who were cognitively normal at time of stroke had greater total brain (TBV) and hippocampal volume (HV) loss over 3 years than controls. We examined whether stroke survivors who were cognitively impaired (CI) at 3 months following their stroke had greater brain volume loss than cognitively normal (CN) stroke participants over the next 3 years.

Methods: Cognition And Neocortical Volume After Stroke (CANVAS) study is a multi-centre cohort study of first-ever or recurrent adult ischaemic stroke participants compared to age- and sex-matched community controls. Participants were followed with MRI and cognitive assessments over 3 years and were free of a history of cognitive impairment or decline at inclusion. Our primary outcome measure was TBV change between 3 months and 3 years; secondary outcomes were TBV and HV change comparing CI and CN participants. We investigated associations between group status and brain volume change using a baseline-volume adjusted linear regression model with robust standard error.

Results: Ninety-three stroke (26 women, 66.7 ± 12 years) and 39 control participants (15 women, 68.7 ± 7 years) were available at 3 years. TBV loss in stroke patients was greater than controls: stroke mean (M) = 20.3 cm³ ± SD 14.8 cm³; controls M = 14.2 cm³ ± SD 13.2 cm³; [adjusted mean difference 7.88 95%CI (2.84, 12.91) p-value = 0.002]. TBV decline was greater in those stroke participants who were cognitively impaired (M = 30.7 cm³; SD = 14.2 cm³) at 3 months (M = 19.6 cm³; SD = 13.8 cm³); [adjusted mean difference 10.42; 95%CI (3.04, 17.80), p-value = 0.006]. No statistically significant differences in HV change were observed.

Conclusions: Ischaemic stroke survivors exhibit greater neurodegeneration compared to stroke-free controls. Brain atrophy is greater in stroke participants who were cognitively impaired early after their stroke. Early cognitive impairment was associated greater subsequent atrophy, reflecting the combined impacts of stroke and vascular brain burden. Atrophy rates could serve as a useful biomarker for trials testing interventions to reduce post-stroke secondary neurodegeneration.

Clinical Trail Registration:http://www.clinicaltrials.gov, identifier: NCT02205424.

Multimodal Prediction of Alzheimer's Disease Severity Level Based on Resting-State EEG and Structural MRI

While several biomarkers have been developed for the detection of Alzheimer's disease (AD), not many are available for the prediction of disease severity, particularly for patients in the mild stages of AD. In this paper, we explore the multimodal prediction of Mini-Mental State Examination (MMSE) scores using resting-state electroencephalography (EEG) and structural magnetic resonance imaging (MRI) scans. Analyses were carried out on a dataset comprised of EEG and MRI data collected from 89 patients diagnosed with minimal-mild AD. Three feature selection algorithms were assessed alongside four machine learning algorithms. Results showed that while MRI features alone outperformed EEG features, when both modalities were combined, improved results were achieved. The top-selected EEG features conveyed information about amplitude modulation rate-of-change, whereas top-MRI features comprised information about cortical area and white matter volume. Overall, a root mean square error between predicted MMSE values and true MMSE scores of 1.682 was achieved with a multimodal system and a random forest regression model.

The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.

DeepVolume: Brain Structure and Spatial Connection-Aware Network for Brain MRI Super-Resolution

Thin-section magnetic resonance imaging (MRI) can provide higher resolution anatomical structures and more precise clinical information than thick-section images. However, thin-section MRI is not always available due to the imaging cost issue. In multicenter retrospective studies, a large number of data are often in thick-section manner with different section thickness. The lack of thin-section data and the difference in section thickness bring considerable difficulties in the study based on the image big data. In this article, we introduce DeepVolume, a two-step deep learning architecture to address the challenge of accurate thin-section MR image reconstruction. The first stage is the brain structure-aware network, in which the thick-section MR images in axial and sagittal planes are fused by a multitask 3-D U-net with prior knowledge of brain volume segmentation, which encourages the reconstruction result to have correct brain structure. The second stage is the spatial connection-aware network, in which the preliminary reconstruction results are adjusted slice-by-slice by a recurrent convolutional network embedding convolutional long short-term memory (LSTM) block, which enhances the precision of the reconstruction by utilizing the previously unassessed sagittal information. We used 305 paired brain MRI samples with thickness of 1.0 mm and 6.5 mm in this article. Extensive experiments illustrate that DeepVolume can produce the state-of-the-art reconstruction results by embedding more anatomical knowledge. Furthermore, considering DeepVolume as an intermediate step, the practical and clinical value of our method is validated by applying the brain volume estimation and voxel-based morphometry. The results show that DeepVolume can provide much more reliable brain volume estimation in the normalized space based on the thick-section MR images compared with the traditional solutions.

Brain Shape Changes Associated With Cerebral Atrophy in Healthy Aging and Alzheimer's Disease

Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white and gray matter volume loss, ventricular enlargement, and loss of gyrification all caused by a myriad of subcellular and cellular aging processes. While the biology of brain aging has been investigated extensively, the mechanics of brain aging remains vastly understudied. Here, we propose a multiphysics model that couples tissue atrophy and Alzheimer's disease biomarker progression. We adopt the multiplicative split of the deformation gradient into a shrinking and an elastic part. We model atrophy as region-specific isotropic shrinking and differentiate between a constant, tissue-dependent atrophy rate in healthy aging, and an atrophy rate in Alzheimer's disease that is proportional to the local biomarker concentration. Our finite element modeling approach delivers a computational framework to systematically study the spatiotemporal progression of cerebral atrophy and its regional effect on brain shape. We verify our results via comparison with cross-sectional medical imaging studies that reveal persistent age-related atrophy patterns. Our long-term goal is to develop a diagnostic tool able to differentiate between healthy and accelerated aging, typically observed in Alzheimer's disease and related dementias, in order to allow for earlier and more effective interventions.

Associations between sleep apnea and advanced brain aging in a large-scale population study

Advanced brain aging is commonly regarded as a risk factor for neurodegenerative diseases, for example, Alzheimer's dementia, and it was suggested that sleep disorders such as obstructive sleep apnea (OSA) are significantly contributing factors to these neurodegenerative processes. To determine the association between OSA and advanced brain aging, we investigated the specific effect of two indices quantifying OSA, namely the apnea-hypopnea index (AHI) and the oxygen desaturation index (ODI), on brain age, a score quantifying age-related brain patterns in 169 brain regions, using magnetic resonance imaging and overnight polysomnography data from 690 participants (48.8% women, mean age 52.5 ± 13.4 years) of the Study of Health in Pomerania. We additionally investigated the mediating effect of subclinical inflammation parameters on these associations via a causal mediation analysis. AHI and ODI were both positively associated with brain age (AHI std. effect [95% CI]: 0.07 [0.03; 0.12], p-value: 0.002; ODI std. effect [95% CI]: 0.09 [0.04; 0.13], p-value: < 0.0003). The effects remained stable in the presence of various confounders such as diabetes and were partially mediated by the white blood cell count, indicating a subclinical inflammation process. Our results reveal an association between OSA and brain age, indicating subtle but widespread age-related changes in regional brain structures, in one of the largest general population studies to date, warranting further examination of OSA in the prevention of neurodegenerative diseases.

Circulating Angiotensin-(1-7) Is Reduced in Alzheimer's Disease Patients and Correlates With White Matter Abnormalities: Results From a Pilot Study

Introduction

Alzheimer’s disease (AD) is the leading cause of dementia worldwide. Despite the extensive research, its pathophysiology remains largely unelucidated. Currently, more attention is being given to the disease’s vascular and inflammatory aspects. In this context, the renin-angiotensin system (RAS) emerges as a credible player in AD pathogenesis. The RAS has multiple physiological functions, conducted by its two opposing axes: the classical, led by Angiotensin II (Ang II), and the alternative, driven by Angiotensin-(1–7) [Ang-(1–7)]. These peptides were shown to interact with AD pathology in animal studies, but evidence from humans is scarce. Only 20 studies dosed RAS molecules in AD patients’ bloodstream, none of which assessed both axes simultaneously. Therefore, we conducted a cross-sectional, case-control exploratory study to compare plasma levels of Ang II and Ang-(1–7) in AD patients vs. age-matched controls. Within each group, we searched for correlations between RAS biomarkers and measures from magnetic resonance imaging (MRI).

Methods

We evaluated patients with AD (n = 14) and aged-matched controls (n = 14). Plasma Ang II and Ang-(1–7) were dosed using ELISA. Brain MRI was performed in a 3 Tesla scan, and a three-dimensional T1-weighted volumetric sequence was obtained. Images were then processed by FreeSurfer to calculate: (1) white matter hypointensities (WMH) volume; (2) volumes of hippocampus, medial temporal cortex, and precuneus. Statistical analyses used non-parametrical tests (Mann-Whitney and Spearman).

Results

Ang-(1–7) levels in plasma were significantly lower in the AD patients than in controls [median (25th–75th percentiles)]: AD [101.5 (62.43–126.4)] vs. controls [209.3 (72–419.1)], p = 0.014. There was no significant difference in circulating Ang II. In the AD patients, but not in controls, there was a positive and significant correlation between Ang-(1–7) values and WMH volumes (Spearman’s rho = 0.56, p = 0.038). Ang-(1–7) did not correlate with cortical volumes in AD or in controls. Ang II did not correlate with any MRI variable in none of the groups.

Conclusion

If confirmed, our results strengthen the hypothesis that RAS alternative axis is downregulated in AD, and points to a possible interaction between Ang-(1–7) and cerebrovascular lesions in AD.