Magnetic resonance imaging evidence for presymptomatic change in thalamus and caudate in familial Alzheimer's disease

Bats as instructive animal models for studying longevity and aging

Bats (order Chiroptera) are emerging as instructive animal models for aging studies. Unlike some common laboratory species, they meet a central criterion for aging studies: they live for a long time in the wild or in captivity, for 20, 30, and even >40 years. Healthy aging (i.e., healthspan) in bats has drawn attention to their potential to improve the lives of aging humans due to bat imperviousness to viral infections, apparent low rate of tumorigenesis, and unique ability to repair DNA. At the same time, bat longevity also permits the accumulation of age-associated systemic pathologies that can be examined in detail and manipulated, especially in captive animals. Research has uncovered additional and critical advantages of bats. In multiple ways, bats are better analogs to humans than are rodents. In this review, we highlight eight diverse areas of bat research with relevance to aging: genome sequencing, telomeres, and DNA repair; immunity and inflammation; hearing; menstruation and menopause; skeletal system and fragility; neurobiology and neurodegeneration; stem cells; and senescence and mortality. These examples demonstrate the broad relevance of the bat as an animal model and point to directions that are particularly important for human aging studies.

Volumetric and functional connectivity changes of the thalamic nuclei in different stages of Alzheimer's disease

OBJECTIVE

Memory processes known to be impaired in Alzheimer's disease (AD) are maintained by a large-scale neurocognitive network with subcortical components, including the thalamus. Therefore, we aimed to examine the volumetric and functional changes of the thalamic nuclei at different scales across AD stages.

METHODS

MRI data of patients diagnosed with 20 AD dementia (ADD), 30 amnestic mild cognitive impairment (MCI), and 30 subjective cognitive impairment (SCI) were used. Volumetric and functional connectivity analyzes were performed by dividing the thalamus into anterior, medial, posterior, lateral and intralaminar nucleus groups and their specific subnuclei.

RESULTS

In the course of AD, the volume of the medial group nuclei, especially the mediodorsal medial magnocellular (MDm) nucleus, decreases. Medial group nuclei and MDm functional connectivity with frontal areas were decreased both in ADD and MCI compared to SCI group, while both of them increased their functional connectivity with visual areas in the ADD group compared to the MCI group.

CONCLUSIONS

Our study suggests that the medial group of the thalamus, and specifically the MDm, may be affected in AD.

SIGNIFICANCE

Specific thalamic nuclei may be a critical anatomical region for investigating structural and functional changes in AD.

Heart-brain mapping: Cardiac atrial function is associated with distinct cerebral regions with high free water in older adults

Left atrial (LA) dysfunction has been linked to cognitive impairment and cerebrovascular dysfunction. Higher brain free-water (FW) derived from diffusion-MRI was associated with early and subtle cerebrovascular dysfunction and more severe cognitive impairment. We hypothesized that LA dysfunction would correlate with higher brain free-water (FW) among healthy older adults. 56 community older adults (73.13 ± 3.56 years; 24 female) with normal cognition and without known cardiovascular disease who had undergone cardiac-MRI, brain-MRI, and neuropsychological assessments were included. Whole-brain voxel-level general linear models were constructed to correlate brain FW measures with LA indices. We found lower scores in LA function measures were related to higher grey matter (GM) FW in regions including orbital frontal and right temporal regions (p < 0.01, family-wise error corrected). In parallel, LA dysfunction was associated with higher FW in white matter (WM) fibres including superior longitudinal fasciculus, internal capsule, and superior corona radiata. However, LA dysfunction was not related to WM tissue reduction and GM cortical thinning. Moreover, these cardiac-related higher brain FW were associated with lower executive function and higher serum B-type natriuretic peptide (p < 0.05, Holm-Bonferroni corrected). These findings may have implications for anti-ageing preventive strategies targeting cardiac and cerebral vascular functions to improve heart and brain outcomes.

Neural stem cell-derived exosomes promote mitochondrial biogenesis and restore abnormal protein distribution in a mouse model of Alzheimer's disease

JOURNAL/nrgr/04.03/01300535-202407000-00040/figure1/v/2023-11-20T171125Z/r/image-tiff

Mitochondrial dysfunction is a hallmark of Alzheimer's disease. We previously showed that neural stem cell-derived extracellular vesicles improved mitochondrial function in the cortex of APP/PS1 mice. Because Alzheimer's disease affects the entire brain, further research is needed to elucidate alterations in mitochondrial metabolism in the brain as a whole. Here, we investigated the expression of several important mitochondrial biogenesis-related cytokines in multiple brain regions after treatment with neural stem cell-derived exosomes and used a combination of whole brain clearing, immunostaining, and lightsheet imaging to clarify their spatial distribution. Additionally, to clarify whether the sirtuin 1 (SIRT1)-related pathway plays a regulatory role in neural stem cell-derived exosomes interfering with mitochondrial functional changes, we generated a novel nervous system-SIRT1 conditional knockout APP/PS1 mouse model. Our findings demonstrate that neural stem cell-derived exosomes significantly increase SIRT1 levels, enhance the production of mitochondrial biogenesis-related factors, and inhibit astrocyte activation, but do not suppress amyloid-β production. Thus, neural stem cell-derived exosomes may be a useful therapeutic strategy for Alzheimer's disease that activates the SIRT1-PGC1α signaling pathway and increases NRF1 and COXIV synthesis to improve mitochondrial biogenesis. In addition, we showed that the spatial distribution of mitochondrial biogenesis-related factors is disrupted in Alzheimer's disease, and that neural stem cell-derived exosome treatment can reverse this effect, indicating that neural stem cell-derived exosomes promote mitochondrial biogenesis.

Relationship Between Excessive Daytime Sleepiness and Caudate Nucleus Volume in Patients with Subjective Cognitive Decline: A Study from the SILCODE Using the Volbrain

Background

Excessive daytime sleepiness (EDS) and caudate nucleus volume alterations have been linked to Alzheimer's disease (AD), but their relationship remains unclear under the context of subjective cognitive decline (SCD).

Objective

This study aimed to investigate the relationship between EDS and caudate nucleus volume in patients with SCD.

Methods

The volume of entire brain was measured in 170 patients with SCD, including 37 patients with EDS and 133 non-EDS, from the Sino Longitudinal Study on Cognitive Decline (SILCODE). Participants underwent a comprehensive assessment battery, including neuropsychological and clinical evaluations, blood tests, genetic analysis for APOE ɛ4, and structural MRI scans analyzed using the fully automated segmentation tool, volBrain.

Results

Patients with EDS had significantly increased volume in the total and left caudate nucleus compared to non-EDS. The most significant cognitive behavioral factor associated with caudate nucleus volume in the EDS was the Auditory Verbal Learning Test-recognition.

Conclusions

These findings suggest that EDS may be associated with alterations in caudate nucleus volume, particularly in the left hemisphere, in the context of SCD. Further research is necessary to understand the underlying mechanisms of this relationship and its implications for clinical management.

Decoupling of gray and white matter functional networks in cognitive impairment induced by occupational aluminum exposure

Aluminum (Al) is a low-toxic, accumulative substance with neurotoxicity properties that adversely affect human cognitive function. This study aimed to investigate the neurobiological mechanisms underlying cognitive impairment resulting from occupational Al exposure. Resting-state functional magnetic resonance imaging was conducted on 54 individuals with over 10 years of Al exposure. Al levels were measured, and cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Subsequently, the K-means clustering algorithm was employed to identify functional gray matter (GM) and white matter (WM) networks. Two-sample t-tests were conducted between the cognition impairment group and the control group. Al exhibited a negative correlation with MoCA scores. Participants with cognitive impairment demonstrated reduced functional connectivity (FC) between the middle cingulum network (WM1) and anterior cingulum network (WM2), as well as between the executive control network (WM6) and limbic network (WM10). Notably, decreased FCs were observed between the executive control network (GM5) and WM1, WM4, WM6, and WM10. Additionally, the FC of GM5-GM4 and WM1-WM2 negatively correlated with Trail Making Test Part A (TMT-A) scores. Prolonged Al accumulation detrimentally affects cognition, primarily attributable to executive control and limbic network disruptions.

Basal forebrain volume and metabolism in carriers of the Colombian mutation for autosomal dominant Alzheimer's disease

We aimed to study atrophy and glucose metabolism of the cholinergic basal forebrain in non-demented mutation carriers for autosomal dominant Alzheimer's disease (ADAD). We determined the level of evidence for or against atrophy and impaired metabolism of the basal forebrain in 167 non-demented carriers of the Colombian PSEN1 E280A mutation and 75 age- and sex-matched non-mutation carriers of the same kindred using a Bayesian analysis framework. We analyzed baseline MRI, amyloid PET, and FDG-PET scans of the Alzheimer's Prevention Initiative ADAD Colombia Trial. We found moderate evidence against an association of carrier status with basal forebrain volume (Bayes factor (BF10) = 0.182). We found moderate evidence against a difference of basal forebrain metabolism (BF10 = 0.167). There was only inconclusive evidence for an association between basal forebrain volume and delayed memory and attention (BF10 = 0.884 and 0.184, respectively), and between basal forebrain volume and global amyloid load (BF10 = 2.1). Our results distinguish PSEN1 E280A mutation carriers from sporadic AD cases in which cholinergic involvement of the basal forebrain is already detectable in the preclinical and prodromal stages. This indicates an important difference between ADAD and sporadic AD in terms of pathogenesis and potential treatment targets.

Thalamic segmentation based on diffusion tensor imaging in patients with trigeminal neuralgia

Classical trigeminal neuralgia (CTN) refers to episodic pain that is strictly confined to the trigeminal distribution area, and the thalamus is an important component of the trigeminal sensory pathway. Probabilistic tracking imaging algorithm was used to identify specific connections between the thalamus and the cortex, in order to identify structural changes in the thalamus of patients with CTN and perform thalamic segmentation. A total of 32 patients with CTN and 32 healthy controls underwent DTI-MRI scanning (3.0 T). Differences in fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) between the groups were studied. Correlation analysis was performed with clinical course and pain level. Compared to the healthy controls, patients in the CTN group had significantly reduced FA, increased AD, RD and MD in somatosensory subregion of the bilateral thalamus, increased RD in frontal subregion, increased RD and MD in motor subregion. Correlation analysis showed that patient history was positively correlated with pain grading, and that medical history was positively correlated with significantly reduced FA in somatosensory subregion, negatively correlated with increased RD and MD in motor subregion. We used DTI-based probabilistic fiber tracking to discover altered structural connectivity between the thalamus and cerebral cortex in patients with CTN and to obtain a thalamic segmentation atlas, which will help to further understand the pathophysiology of CTN and serve as a future reference for thalamic deep brain stimulation electrode implantation for the treatment of intractable pain.

Diagnosis-Guided Deep Subspace Clustering Association Study for Pathogenetic Markers Identification of Alzheimer's Disease Based on Comparative Atlases

The roles of brain region activities and genotypic functions in the pathogenesis of Alzheimer's disease (AD) remain unclear. Meanwhile, current imaging genetics methods are difficult to identify potential pathogenetic markers by correlation analysis between brain network and genetic variation. To discover disease-related brain connectome from the specific brain structure and the fine-grained level, based on the Automated Anatomical Labeling (AAL) and human Brainnetome atlases, the functional brain network is first constructed for each subject. Specifically, the upper triangle elements of the functional connectivity matrix are extracted as connectivity features. The clustering coefficient and the average weighted node degree are developed to assess the significance of every brain area. Since the constructed brain network and genetic data are characterized by non-linearity, high-dimensionality, and few subjects, the deep subspace clustering algorithm is proposed to reconstruct the original data. Our multilayer neural network helps capture the non-linear manifolds, and subspace clustering learns pairwise affinities between samples. Moreover, most approaches in neuroimaging genetics are unsupervised learning, neglecting the diagnostic information related to diseases. We presented a label constraint with diagnostic status to instruct the imaging genetics correlation analysis. To this end, a diagnosis-guided deep subspace clustering association (DDSCA) method is developed to discover brain connectome and risk genetic factors by integrating genotypes with functional network phenotypes. Extensive experiments prove that DDSCA achieves superior performance to most association methods and effectively selects disease-relevant genetic markers and brain connectome at the coarse-grained and fine-grained levels.

Dementia risk and thalamic nuclei volumetry in healthy midlife adults: the PREVENT Dementia study

A reduction in the volume of the thalamus and its nuclei has been reported in Alzheimer's disease, mild cognitive impairment and asymptomatic individuals with risk factors for early-onset Alzheimer's disease. Some studies have reported thalamic atrophy to occur prior to hippocampal atrophy, suggesting thalamic pathology may be an early sign of cognitive decline. We aimed to investigate volumetric differences in thalamic nuclei in middle-aged, cognitively unimpaired people with respect to dementia family history and apolipoprotein ε4 allele carriership and the relationship with cognition. Seven hundred participants aged 40-59 years were recruited into the PREVENT Dementia study. Individuals were stratified according to dementia risk (approximately half with and without parental dementia history). The subnuclei of the thalamus of 645 participants were segmented on T1-weighted 3 T MRI scans using FreeSurfer 7.1.0. Thalamic nuclei were grouped into six regions: (i) anterior, (ii) lateral, (iii) ventral, (iv) intralaminar, (v) medial and (vi) posterior. Cognitive performance was evaluated using the computerized assessment of the information-processing battery. Robust linear regression was used to analyse differences in thalamic nuclei volumes and their association with cognitive performance, with age, sex, total intracranial volume and years of education as covariates and false discovery rate correction for multiple comparisons. We did not find significant volumetric differences in the thalamus or its subregions, which survived false discovery rate correction, with respect to first-degree family history of dementia or apolipoprotein ε4 allele status. Greater age was associated with smaller volumes of thalamic subregions, except for the medial thalamus, but only in those without a dementia family history. A larger volume of the mediodorsal medial nucleus (Pfalse discovery rate = 0.019) was associated with a faster processing speed in those without a dementia family history. Larger volumes of the thalamus (P = 0.016) and posterior thalamus (Pfalse discovery rate = 0.022) were associated with significantly worse performance in the immediate recall test in apolipoprotein ε4 allele carriers. We did not find significant volumetric differences in thalamic subregions in relation to dementia risk but did identify an interaction between dementia family history and age. Larger medial thalamic nuclei may exert a protective effect on cognitive performance in individuals without a dementia family history but have little effect on those with a dementia family history. Larger volumes of posterior thalamic nuclei were associated with worse recall in apolipoprotein ε4 carriers. Our results could represent initial dysregulation in the disease process; further study is needed with functional imaging and longitudinal analysis.

The Role of the Anterior Thalamic Nuclei in the Genesis of Memory Disorders in Alzheimer's Disease: An Exploratory Study

BACKGROUND

Increasing evidence is demonstrating that degeneration of specific thalamic nuclei, in addition to the hippocampus, may occur in Alzheimer's disease (AD) from the prodromal stage (mild cognitive impairment - MCI) and contribute to memory impairment.

OBJECTIVE

Here, we evaluated the presence of macro and micro structural alterations at the level of the anterior thalamic nuclei (ATN) and medio-dorsal thalamic nuclei (MDTN) in AD and amnestic MCI (aMCI) and the possible relationship between such changes and the severity of memory impairment.

METHODS

For this purpose, a sample of 50 patients with aMCI, 50 with AD, and 50 age- and education-matched healthy controls (HC) were submitted to a 3-T MRI protocol with whole-brain T1-weighted and diffusion tensor imaging and a comprehensive neuropsychological assessment.

RESULTS

At macro-structural level, both the ATN and MDTN were found significantly smaller in patients with aMCI and AD when compared to HC subjects. At micro-structural level, instead, diffusion alterations that significantly differentiated aMCI and AD patients from HC subjects were found only in the ATN, but not in the MDTN. Moreover, diffusion values of the ATN were significantly associated with poor episodic memory in the overall patients' group.

CONCLUSIONS

These findings represent the first in vivo evidence of a relevant involvement of ATN in the AD-related neurodegeneration and memory profile and strengthen the importance to look beyond the hippocampus when considering neurological conditions characterized by memory decline.

Exploratory Correlation of The Human Structural Connectome with Non-MRI Variables in Alzheimer's Disease

INTRODUCTION

Discovery of the associations between brain structural connectivity and clinical and demographic variables can help to better understand the vulnerability and resilience of the brain architecture to neurodegenerative diseases and to discover biomarkers.

METHODS

We used four diffusion-MRI databases, three related to Alzheimer's disease, to exploratorily correlate structural connections between 85 brain regions with non-MRI variables, while stringently correcting the significance values for multiple testing and ruling out spurious correlations via careful visual inspection. We repeated the analysis with brain connectivity augmented with multi-synaptic neural pathways.

RESULTS

We found 85 and 101 significant relationships with direct and augmented connectivity, respectively, which were generally stronger for the latter. Age was consistently linked to decreased connectivity, and healthier clinical scores were generally linked to increased connectivity.

DISCUSSION

Our findings help to elucidate which structural brain networks are affected in Alzheimer's disease and aging and highlight the importance of including indirect connections.

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

BACKGROUND

Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical.

METHODS

Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination).

RESULTS

Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone.

CONCLUSION

Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.

Exploratory correlation of the human structural connectome with non-MRI variables in Alzheimer's disease

Introduction

Discovery of the associations between brain structural connectivity and clinical and demographic variables can help to better understand the vulnerability and resilience of the brain architecture to neurodegenerative diseases and to discover biomarkers.

Methods

We used four diffusion-MRI databases, three related to Alzheimer's disease (AD), to exploratorily correlate structural connections between 85 brain regions with non-MRI variables, while stringently correcting the significance values for multiple testing and ruling out spurious correlations via careful visual inspection. We repeated the analysis with brain connectivity augmented with multi-synaptic neural pathways.

Results

We found 85 and 101 significant relationships with direct and augmented connectivity, respectively, which were generally stronger for the latter. Age was consistently linked to decreased connectivity, and healthier clinical scores were generally linked to increased connectivity.

Discussion

Our findings help to elucidate which structural brain networks are affected in AD and aging and highlight the importance of including indirect connections.

Increased TSPO expression, pyroglutamate-modified amyloid beta (AβN3(pE)) accumulation and transient clustering of microglia in the thalamus of Tg-SwDI mice

Epidemiological studies showed that Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA) frequently co-occur; however, the precise mechanism is not well understood. A unique animal model (Tg-SwDI mice) was developed to investigate the early-onset and robust accumulation of both parenchymal and vascular Aβ in the brain. Tg-SwDI mice have been extensively used to study the mechanisms of cerebrovascular dysfunction, neuroinflammation, neurodegeneration, and cognitive decline observed in AD/CAA patients and to design biomarkers and therapeutic strategies. In the present study, we documented interesting new features in the thalamus of Tg-SwDI mice: 1) a sharp increase in the expression of ionized calcium-binding adapter molecule 1 (Iba-1) in microglia in 6-month-old animals; 2) microglia clustering at six months that disappeared in old animals; 3) N-truncated/modified AβN3(pE) peptide in 9-month-old female and 12-month-old male mice; 4) an age-dependent increase in translocator protein (TSPO) expression. These findings reinforce the versatility of this model for studying multiple pathological issues involved in AD and CAA.

Assessment of complementary white matter microstructural changes and grey matter atrophy in a preclinical model of Alzheimer's disease

Alzheimer's disease (AD) has been associated with amyloid and tau pathology, as well as neurodegeneration. Beyond these hallmark features, white matter microstructural abnormalities have been observed using MRI. The objective of this study was to assess grey matter atrophy and white matter microstructural changes in a preclinical mouse model of AD (3xTg-AD) using voxel-based morphometry (VBM) and free-water (FW) diffusion tensor imaging (FW-DTI). Compared to controls, lower grey matter density was observed in the 3xTg-AD model, corresponding to the small clusters in the caudate-putamen, hypothalamus, and cortex. DTI-based fractional anisotropy (FA) was decreased in the 3xTg model, while the FW index was increased. Notably, the largest clusters for both FW-FA and FW index were in the fimbria, with other regions including the anterior commissure, corpus callosum, forebrain septum, and internal capsule. Additionally, the presence of amyloid and tau in the 3xTg model was confirmed with histopathology, with significantly higher levels observed across many regions of the brain. Taken together, these results are consistent with subtle neurodegenerative and white matter microstructural changes in the 3xTg-AD model that manifest as increased FW, decreased FW-FA, and decreased grey matter density.

Altered global signal topography in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease associated with widespread disruptions in intrinsic local specialization and global integration in the functional system of the brain. These changes in integration may further disrupt the global signal (GS) distribution, which might represent the local relative contribution to global activity in functional magnetic resonance imaging (fMRI).

METHODS

fMRI scans from a discovery dataset (n = 809) and a validated dataset (n = 542) were used in the analysis. We investigated the alteration of GS topography using the GS correlation (GSCORR) in patients with mild cognitive impairment (MCI) and AD. The association between GS alterations and functional network properties was also investigated based on network theory. The underlying mechanism of GSCORR alterations was elucidated using imaging-transcriptomics.

FINDINGS

Significantly increased GS topography in the frontal lobe and decreased GS topography in the hippocampus, cingulate gyrus, caudate, and middle temporal gyrus were observed in patients with AD (P_adj < 0.05). Notably, topographical GS changes in these regions correlated with cognitive ability (P < 0.05). The changes in GS topography also correlated with the changes in functional network segregation (ρ = 0.5). Moreover, the genes identified based on GS topographical changes were enriched in pathways associated with AD and neurodegenerative diseases.

INTERPRETATION

Our findings revealed significant changes in GS topography and its molecular basis, confirming the informative role of GS in AD and further contributing to the understanding of the relationship between global and local neuronal activities in patients with AD.

FUNDING

Beijing Natural Science Funds for Distinguished Young Scholars, China; Fundamental Research Funds for the Central Universities, China; National Natural Science Foundation, China.

Shared and unique effects of ApoEε4 and pathogenic gene mutation on cognition and imaging in preclinical familial Alzheimer's disease

BACKGROUND

Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD.

METHODS

One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation.

RESULTS

Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups.

CONCLUSIONS

There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.

Progressive structural and covariance connectivity abnormalities in patients with Alzheimer's disease

Background

Alzheimer's disease (AD) is one of most prevalent neurodegenerative diseases worldwide and characterized by cognitive decline and brain structure atrophy. While studies have reported substantial grey matter atrophy related to progression of AD, it remains unclear about brain regions with progressive grey matter atrophy, covariance connectivity, and the associations with cognitive decline in AD patients.

Objective

This study aims to investigate the grey matter atrophy, structural covariance connectivity abnormalities, and the correlations between grey matter atrophy and cognitive decline during AD progression.

Materials

We analyzed neuroimaging data of healthy controls (HC, n = 45) and AD patients (n = 40) at baseline (AD-T1) and one-year follow-up (AD-T2) obtained from the Alzheimer's Disease Neuroimaging Initiative. We investigated AD-related progressive changes of grey matter volume, covariance connectivity, and the clinical relevance to further understand the pathological progression of AD.

Results

The results showed clear patterns of grey matter atrophy in inferior frontal gyrus, prefrontal cortex, lateral temporal gyrus, posterior cingulate cortex, insula, hippocampus, caudate, and thalamus in AD patients. There was significant atrophy in bilateral superior temporal gyrus (STG) and left caudate in AD patients over a one-year period, and the grey matter volume decrease in right STG and left caudate was correlated with cognitive decline. Additionally, we found reduced structural covariance connectivity between right STG and left caudate in AD patients. Using AD-related grey matter atrophy as features, there was high discrimination accuracy of AD patients from HC, and AD patients at different time points.

Relationships between brain tissue damage, oxygen desaturation, and disease severity in obstructive sleep apnea evaluated by diffusion tensor imaging

STUDY OBJECTIVES

Patients with obstructive sleep apnea (OSA) show brain injury in sites responsible for autonomic, cognitive, and respiratory functions. Brain changes in OSA may vary with disease severity as assessed by the apnea-hypopnea index (AHI), which does not provide information about the apnea depth and length in contrast to oxygen desaturation. Although significant associations with brain injury and AHI are known in OSA, it is unclear whether AHI or the extent of oxygen desaturations better correlate with brain damage. We evaluated associations between brain changes, AHI, and oxygen desaturation using diffusion tensor imaging-based measures.

METHODS

We acquired diffusion tensor imaging data from 19 patients with OSA using a 3.0-Tesla MRI scanner and calculated, normalized, and smoothed mean, axial, and radial diffusivity maps that were used for correlations between brain changes, oxygen desaturation, and AHI values.

RESULTS

Positive correlations with extent of injury (mean, axial, and radial diffusivity values) and AHI appeared in the frontal areas, cingulate and insula, amygdala, hippocampus, and basal pons, and negative associations emerged in the putamen, internal-capsule, globus-pallidus, and cerebellar cortices. Regional diffusivity values and oxygen desaturation showed positive correlations in the cingulate, frontal, putamen, and cerebellar sites, and negative relationships in several areas, including the occipital cortex.

CONCLUSIONS

Patients with OSA show negative and positive correlations, indicated by increased and decreased diffusivity values, resulting from chronic and acute changes in those areas. The extent of injury in OSA partially depends on the extent of AHI and oxygen desaturation, with the effects representing continued development from acute to chronic processes.

CITATION

Sahib A, Roy B, Kang D, Aysola RS, Wen E, Kumar R. Relationships between brain tissue damage, oxygen desaturation, and disease severity in obstructive sleep apnea evaluated by diffusion tensor imaging. J Clin Sleep Med. 2022;18(12):2713-2721.

Topographic Mapping of Isolated Thalamic Infarcts Using Vascular and Novel Probabilistic Functional Thalamic Landmarks

Purpose

We aimed to re-evaluate the relationship between thalamic infarct (TI) localization and clinical symptoms using a vascular (VTM) and a novel functional territorial thalamic map (FTM).

Methods

Magnetic resonance imaging (MRI) and clinical data of 65 patients with isolated TI were evaluated (female n = 23, male n = 42, right n = 23, left n = 42). A VTM depicted the known seven thalamic vascular territories (VT: inferolateral, anterolateral, inferomedial, posterior, central, anteromedian, posterolateral). An FTM was generated from a probabilistic thalamic nuclei atlas to determine six functionally defined territories (FT: anterior: memory/emotions; ventral: motor/somatosensory/language; medial: behavior/emotions/nociception, oculomotor; intralaminar: arousal/pain; lateral: visuospatial/somatosensory/conceptual and analytic thinking; posterior: audiovisual/somatosensory). Four neuroradiologists independently assigned diffusion-weighted imaging (DWI) lesions to the territories mapped by the VTM and FTM. Findings were correlated with clinical features.

Results

The most frequent symptom was a hemisensory syndrome (58%), which was not specific for any territory. A co-occurrence of hemisensory syndrome and hemiparesis had positive predictive values (PPV) of 76% and 82% for the involvement of the inferolateral VT and ventral FT, respectively. Thalamic aphasia had a PPV of 63% each for involvement of the anterolateral VT and ventral FT. Neglect was associated with involvement of the inferolateral VT/ventral FT. Interrater reliability for the assignment of DWI lesions to the VTM was fair (κ = 0.36), but good (κ = 0.73) for the FTM.

Conclusion

The FTM revealed a greater reproducibility for the topographical assignment of TI than the VTM. Sensorimotor hemiparesis and neglect are predictive for a TI in the inferolateral VT/ventral FT. The hemisensory syndrome alone does not allow any topographical assignment.

Self-reported sleepiness associates with greater brain and cortical volume and lower prevalence of ischemic covert brain infarcts in a community sample

STUDY OBJECTIVES

We evaluated if self-reported sleepiness was associated with neuroimaging markers of brain aging and ischemic damage in a large community-based sample.

METHODS

Participants from the Framingham Heart Study Offspring cohort (n = 468, 62.5 ± 8.7 years old, 49.6%M) free of dementia, stroke, and neurological diseases, completed sleep questionnaires and polysomnography followed by magnetic resonance imaging (MRI), 3 years later on average. We used linear and logistic regression models to evaluate the associations between Epworth Sleepiness Scale (ESS) scores and total brain, cortical and subcortical gray matter, and white matter hyperintensities volumes, and the presence of covert brain infarcts.

RESULTS

Higher sleepiness scores were associated with larger total brain volume, greater cortical gray matter volume, and a lower prevalence of covert brain infarcts, even when adjusting for a large array of potential confounders, including demographics, sleep profiles and disorders, organic health diseases, and proxies for daytime cognitive and physical activities. Interactions indicated that more sleepiness was associated with larger cortical gray matter volume in men only and in APOE ε4 noncarriers, whereas a trend for smaller cortical gray matter volume was observed in carriers. In longitudinal analyses, those with stable excessive daytime sleepiness over time had greater total brain and cortical gray matter volumes, whereas baseline sleepiness scores were not associated with subsequent atrophy or cognitive decline.

CONCLUSION

Our findings suggest that sleepiness is not necessarily a marker of poor brain health when not explained by diseases or sleep debt and sleep disorders. Rather, sleepiness could be a marker of preserved sleep-regulatory processes and brain health in some cases.

Decoding transcriptional signatures of the association between free water and macroscale organizations in healthy adolescents

We leveraged a novel index of diffusion MRI to investigate the relationships among cortical free water, macro-organizations and gene expression in healthy adults. Few research has been conducted to investigate the role of free water in the healthy adults due to it can easily be affected also by aging diseases. High quality data of 350 subjects from Human Connectome Project were used in our study. Cortical free water was estimated by using a bi-tensor model. The free water was high in the limbic, insular and somatosensory cortex, while being lower in motor and association cortex. The negative correlation between the free water and cortical thickness has been consistently identified in almost all the cortical regions. Negative correlation between the cortical free water and structural covariance (rho=-0.38, p_spin=0.005) revealed the free water was sensitive to cortical heterogeneity. Using human gene expression dataset, we found the gene expression pattern of the relationship between the free water and cortical thickness spatially coupled with primary gradient of structural covariance network (rho=0.40, p_spin=0.004). Our findings indicated the free water was sensitive to the cortical cellular status. The relationship between free water and macroscale organization also reflected hierarchal structures of cerebral cortex.

Sex Modulates the Pathological Aging Effect on Caudate Functional Connectivity in Mild Cognitive Impairment

Purpose

To assess the pathological aging effect on caudate functional connectivity among mild cognitive impairment (MCI) participants and examine whether and how sex and amyloid contribute to this process.

Materials and Methods

Two hundred and seventy-seven functional magnetic resonance imaging (fMRI) sessions from 163 cognitive normal (CN) older adults and 309 sessions from 139 participants with MCI were included as the main sample in our analysis. Pearson's correlation was used to characterize the functional connectivity (FC) between caudate nuclei and each brain region, then caudate nodal strength was computed to quantify the overall caudate FC strength. Association analysis between caudate nodal strength and age was carried out in MCI and CN separately using linear mixed effect (LME) model with covariates (education, handedness, sex, Apolipoprotein E4, and intra-subject effect). Analysis of covariance was conducted to investigate sex, amyloid status, and their interaction effects on aging with the fMRI data subset having amyloid status available. LME model was applied to women and men separately within MCI group to evaluate aging effects on caudate nodal strength and each region's connectivity with caudate nuclei. We then evaluated the roles of sex and amyloid status in the associations of neuropsychological scores with age or caudate nodal strength. An independent cohort was used to validate the sex-dependent aging effects in MCI.

Results

The MCI group had significantly stronger age-related increase of caudate nodal strength compared to the CN group. Analyzing women and men separately revealed that the aging effect on caudate nodal strength among MCI participants was significant only for women (left: P = 6.23 × 10-7, right: P = 3.37 × 10-8), but not for men (P > 0.3 for bilateral caudate nuclei). The aging effects on caudate nodal strength were not significantly mediated by brain amyloid burden. Caudate connectivity with ventral prefrontal cortex substantially contributed to the aging effect on caudate nodal strength in women with MCI. Higher caudate nodal strength is significantly related to worse cognitive performance in women but not in men with MCI.

Conclusion

Sex modulates the pathological aging effects on caudate nodal strength in MCI regardless of amyloid status. Caudate nodal strength may be a sensitive biomarker of pathological aging in women with MCI.

Evaluating the impact of MR image harmonization on thalamus deep network segmentation

Medical image segmentation is one of the core tasks of medical image analysis. Automatic segmentation of brain magnetic resonance images (MRIs) can be used to visualize and track changes of the brain's anatomical structures that may occur due to normal aging or disease. Machine learning techniques are widely used in automatic structure segmentation. However, the contrast variation between the training and testing data makes it difficult for segmentation algorithms to generate consistent results. To address this problem, an image-to-image translation technique called MR image harmonization can be used to match the contrast between different data sets. It is important for the harmonization to transform image intensity while maintaining the underlying anatomy. In this paper, we present a 3D U-Net algorithm to segment the thalamus from multiple MR image modalities and investigate the impact of harmonization on the segmentation algorithm. Manual delineations of thalamic nuclei on two data sets are available. However, we aim to analyze the thalamus in another large data set where ground truth labels are lacking. We trained two segmentation networks, one with unharmonized images and the other with harmonized images, on one data set with manual labels, and compared their performances on the other data set with manual labels. These two data groups were diagnosed with two brain disorders and were acquired with similar imaging protocols. The harmonization target is the large data set without manual labels, which also has a different imaging protocol. The networks trained on unharmonized and harmonized data showed no significant difference when evaluating on the other data set; demonstrating that image harmonization can maintain the anatomy and does not affect the segmentation task. The two networks were evaluated on the harmonization target data set and the network trained on harmonized data showed significant improvement over the network trained on unharmonized data. Therefore, the network trained on harmonized data provides the potential to process large amounts of data from other sites, even in the absence of site-specific training data.

Biomarkers Derived from Alterations in Overlapping Community Structure of Resting-state Brain Functional Networks for Detecting Alzheimer's Disease

Recent studies show that overlapping community structure is an important feature of the brain functional network. However, alterations in such overlapping community structure in Alzheimer's disease (AD) patients have not been examined yet. In this study, we investigate the overlapping community structure in AD by using resting-state functional magnetic resonance imaging (rs-fMRI) data. The collective sparse symmetric non-negative matrix factorization (cssNMF) is adopted to detect the overlapping community structure. Experimental results on 28 AD patients and 32 normal controls (NCs) from the ADNI2 dataset show that the two groups have remarkable differences in terms of the optimal number of communities, the hierarchy of communities detected at different scales, network functional segregation, and nodal functional diversity. In particular, the frontal-parietal and basal ganglia networks exhibit significant differences between the two groups. A machine learning framework proposed in this paper for AD detection achieved an accuracy of 76.7% when using the detected community strengths of the frontal-parietal and basal ganglia networks only as input features. These findings provide novel insights into the understanding of pathological changes in the brain functional network organization of AD and show the potential of the community structure-related features for AD detection.

Whole-Brain Afferent Inputs to the Caudate Nucleus, Putamen, and Accumbens Nucleus in the Tree Shrew Striatum

Day-active tree shrews have a well-developed internal capsule (ic) that clearly separates the caudate nucleus (Cd) and putamen (Pu). The striatum consists of the Cd, ic, Pu, and accumbens nucleus (Acb). Here, we characterized the cytoarchitecture of the striatum and the whole-brain inputs to the Cd, Pu, and Acb in tree shrews by using immunohistochemistry and the retrograde tracer Fluoro-Gold (FG). Our data show the distribution patterns of parvalbumin (PV), nitric oxide synthase (NOS), calretinin (CR), and tyrosine hydroxylase (TH) immunoreactivity in the striatum of tree shrews, which were different from those observed in rats. The Cd and Pu mainly received inputs from the thalamus, motor cortex, somatosensory cortex, subthalamic nucleus, substantia nigra, and other cortical and subcortical regions, whereas the Acb primarily received inputs from the anterior olfactory nucleus, claustrum, infralimbic cortex, thalamus, raphe nucleus, parabrachial nucleus, ventral tegmental area, and so on. The Cd, Pu, and Acb received inputs from different neuronal populations in the ipsilateral (60, 67, and 63 brain regions, respectively) and contralateral (23, 20, and 36 brain regions, respectively) brain hemispheres. Overall, we demonstrate that there are species differences between tree shrews and rats in the density of PV, NOS, CR, and TH immunoreactivity in the striatum. Additionally, we mapped for the first time the distribution of whole-brain input neurons projecting to the striatum of tree shrews with FG injected into the Cd, Pu, and Acb. The similarities and differences in their brain-wide input patterns may provide new insights into the diverse functions of the striatal subregions.

Going round in circles-The Papez circuit in Alzheimer's disease

The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer's disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is 'only' one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit 'downstream' of the hippocampus. However, this notion is oversimplistic, and increasing evidence suggests that other Papez regions might be affected before or concurrently with the hippocampus. In addition, AD research has mostly focused on episodic memory deficits, whereas spatial navigation processes are also subserved by the Papez circuit with increasing evidence supporting its valuable potential as a diagnostic measure of incipient AD pathophysiology. In the current review, we take a step forward analysing recent evidence on the structural and functional integrity of the Papez circuit across AD disease stages. Specifically, we will review the integrity of specific Papez regions from at-genetic-risk (APOE4 carriers), to mild cognitive impairment (MCI), to dementia stage of sporadic AD and autosomal dominant AD (ADAD). We related those changes to episodic memory and spatial navigation/orientation deficits in AD. Finally, we provide an overview of how the Papez circuit is affected in AD diseases and their specific symptomology contributions. This overview strengthened the need for moving away from a hippocampal-centric view to a network approach on how the whole Papez circuit is affected in AD and contributes to its symptomology, informing future research and clinical approaches.

Conductance-Based Structural Brain Connectivity in Aging and Dementia

Background: Structural brain connectivity has been shown to be sensitive to the changes that the brain undergoes during Alzheimer's disease (AD) progression. Methods: In this work, we used our recently proposed structural connectivity quantification measure derived from diffusion magnetic resonance imaging, which accounts for both direct and indirect pathways, to quantify brain connectivity in dementia. We analyzed data from the second phase of Alzheimer's Disease Neuroimaging Initiative and third release in the Open Access Series of Imaging Studies data sets to derive relevant information for the study of the changes that the brain undergoes in AD. We also compared these data sets to the Human Connectome Project data set, as a reference, and eventually validated externally on two cohorts of the European DTI Study in Dementia database. Results: Our analysis shows expected trends of mean conductance with respect to age and cognitive scores, significant age prediction values in aging data, and regional effects centered among subcortical regions, and cingulate and temporal cortices. Discussion: Results indicate that the conductance measure has prediction potential, especially for age, that age and cognitive scores largely overlap, and that this measure could be used to study effects such as anticorrelation in structural connections. Impact statement This work presents a methodology and a set of analyses that open new possibilities in the study of healthy and pathological aging. The methodology used here is sensitive to direct and indirect pathways in deriving brain connectivity measures from diffusion-weighted magnetic resonance imaging, and therefore provides information that many state-of-the-art methods do not account for. As a result, this technique may provide the research community with ways to detect subtle effects of healthy aging and Alzheimer's disease.

Carbon Nanotube Exposure Triggers a Cerebral Peptidomic Response: Barrier Compromise, Neuroinflammation, and a Hyperexcited State

The unique physicochemical properties of carbon nanomaterials and their ever-growing utilization generate a serious concern for occupational risk. Pulmonary exposure to these nanoparticles induces local and systemic inflammation, cardiovascular dysfunction, and even cognitive deficits. Although multiple routes of extrapulmonary toxicity have been proposed, the mechanism for and manner of neurologic effects remain minimally understood. Here, we examine the cerebral spinal fluid (CSF)-derived peptidomic fraction as a reflection of neuropathological alterations induced by pulmonary carbon nanomaterial exposure. Male C57BL/6 mice were exposed to 10 or 40 µg of multiwalled carbon nanotubes (MWCNT) by oropharyngeal aspiration. Serum and CSFs were collected 4 h post exposure. An enriched peptide fraction of both biofluids was analyzed using ion mobility-enabled data-independent mass spectrometry for label-free quantification. MWCNT exposure induced a prominent peptidomic response in the blood and CSF; however, correlation between fluids was limited. Instead, we determined that a MWCNT-induced peptidomic shift occurred specific to the CSF with 292 significant responses found that were not in serum. Identified MWCNT-responsive peptides depicted a mechanism involving aberrant fibrinolysis (fibrinopeptide A), blood-brain barrier permeation (homeobox protein A4), neuroinflammation (transmembrane protein 131L) with reactivity by astrocytes and microglia, and a pro-degradative (signal transducing adapter molecule, phosphoglycerate kinase), antiplastic (AF4/FMR2 family member 1, vacuolar protein sorting-associated protein 18) state with the excitation-inhibition balance shifted to a hyperexcited (microtubule-associated protein 1B) phenotype. Overall, the significant pathologic changes observed were consistent with early neurodegenerative disease and were diagnostically reflected in the CSF peptidome.

Functional MRI-Specific Alterations in Salience Network in Mild Cognitive Impairment: An ALE Meta-Analysis

Background Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Amnestic MCI (aMCI) and non-amnestic MCI are the two subtypes of MCI with the former having a higher risk for progressing to Alzheimer's disease (AD). Compared with healthy elderly adults, individuals with MCI have specific functional alterations in the salience network (SN). However, no consistent results are documenting these changes. This meta-analysis aimed to investigate the specific functional alterations in the SN in MCI and aMCI. Methods: We systematically searched PubMed, Embase, and Web of Science for scientific neuroimaging literature based on three research methods, namely, functional connectivity (FC), regional homogeneity (ReHo), and the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF). Then, we conducted the coordinate-based meta-analysis by using the activation likelihood estimation algorithm. Results: In total, 30 functional neuroimaging studies were included. After extracting the data and analyzing it, we obtained specific changes in some brain regions in the SN including decreased ALFF/fALFF in the left superior temporal gyrus, the insula, the precentral gyrus, and the precuneus in MCI and aMCI; increased FC in the thalamus, the caudate, the superior temporal gyrus, the insula, and the cingulate gyrus in MCI; and decreased ReHo in the anterior cingulate gyrus in aMCI. In addition, as to FC, interactions of the SN with other networks including the default mode network and the executive control network were also observed mainly in the middle frontal gyrus and superior frontal gyrus in MCI and inferior frontal gyrus in aMCI. Conclusions: Specific functional alternations in the SN and interactions of the SN with other networks in MCI could be useful as potential imaging biomarkers for MCI or aMCI. Meanwhile, it provided a new insight in predicting the progression of health to MCI or aMCI and novel targets for proper intervention to delay the progression. Systematic Review Registration: [PROSPERO], identifier [No. CRD42020216259].

PEAβ Triggers Cognitive Decline and Amyloid Burden in a Novel Mouse Model of Alzheimer's Disease

Understanding the physiopathology of Alzheimer’s disease (AD) has improved substantially based on studies of mouse models mimicking at least one aspect of the disease. Many transgenic lines have been established, leading to amyloidosis but lacking neurodegeneration. The aim of the current study was to generate a novel mouse model that develops neuritic plaques containing the aggressive pyroglutamate modified amyloid-β (pEAβ) species in the brain. The TAPS line was developed by intercrossing of the pEAβ-producing TBA2.1 mice with the plaque-developing line APPswe/PS1ΔE9. The phenotype of the new mouse line was characterized using immunostaining, and different cognitive and general behavioral tests. In comparison to the parental lines, TAPS animals developed an earlier onset of pathology and increased plaque load, including striatal pEAβ-positive neuritic plaques, and enhanced neuroinflammation. In addition to abnormalities in general behavior, locomotion, and exploratory behavior, TAPS mice displayed cognitive deficits in a variety of tests that were most pronounced in the fear conditioning paradigm and in spatial learning in comparison to the parental lines. In conclusion, the combination of a pEAβ- and a plaque-developing mouse model led to an accelerated amyloid pathology and cognitive decline in TAPS mice, qualifying this line as a novel amyloidosis model for future studies.

Relation-Induced Multi-Modal Shared Representation Learning for Alzheimer's Disease Diagnosis

The fusion of multi-modal data (e.g., magnetic resonance imaging (MRI) and positron emission tomography (PET)) has been prevalent for accurate identification of Alzheimer's disease (AD) by providing complementary structural and functional information. However, most of the existing methods simply concatenate multi-modal features in the original space and ignore their underlying associations which may provide more discriminative characteristics for AD identification. Meanwhile, how to overcome the overfitting issue caused by high-dimensional multi-modal data remains appealing. To this end, we propose a relation-induced multi-modal shared representation learning method for AD diagnosis. The proposed method integrates representation learning, dimension reduction, and classifier modeling into a unified framework. Specifically, the framework first obtains multi-modal shared representations by learning a bi-directional mapping between original space and shared space. Within this shared space, we utilize several relational regularizers (including feature-feature, feature-label, and sample-sample regularizers) and auxiliary regularizers to encourage learning underlying associations inherent in multi-modal data and alleviate overfitting, respectively. Next, we project the shared representations into the target space for AD diagnosis. To validate the effectiveness of our proposed approach, we conduct extensive experiments on two independent datasets (i.e., ADNI-1 and ADNI-2), and the experimental results demonstrate that our proposed method outperforms several state-of-the-art methods.

Predicting Brain Regions Related to Alzheimer's Disease Based on Global Feature

Alzheimer's disease (AD) is a neurodegenerative disease that commonly affects the elderly; early diagnosis and timely treatment are very important to delay the course of the disease. In the past, most brain regions related to AD were identified based on imaging methods, and only some atrophic brain regions could be identified. In this work, the authors used mathematical models to identify the potential brain regions related to AD. In this study, 20 patients with AD and 13 healthy controls (non-AD) were recruited by the neurology outpatient department or the neurology ward of Peking University First Hospital from September 2017 to March 2019. First, diffusion tensor imaging (DTI) was used to construct the brain structural network. Next, the authors set a new local feature index 2hop-connectivity to measure the correlation between different regions. Compared with the traditional graph theory index, 2hop-connectivity exploits the higher-order information of the graph structure. And for this purpose, the authors proposed a novel algorithm called 2hopRWR to measure 2hop-connectivity. Then, a new index global feature score (GFS) based on a global feature was proposed by combing five local features, namely degree centrality, betweenness centrality, closeness centrality, the number of maximal cliques, and 2hop-connectivity, to judge which brain regions are related to AD. As a result, the top ten brain regions identified using the GFS scoring difference between the AD and the non-AD groups were associated to AD by literature verification. The results of the literature validation comparing GFS with the local features showed that GFS was superior to individual local features. Finally, the results of the canonical correlation analysis showed that the GFS was significantly correlated with the scores of the Mini-Mental State Examination (MMSE) scale and the Montreal Cognitive Assessment (MoCA) scale. Therefore, the authors believe the GFS can also be used as a new biomarker to assist in diagnosis and objective monitoring of disease progression. Besides, the method proposed in this paper can be used as a differential network analysis method for network analysis in other domains.

Structural Changes in Thalamic Nuclei Across Prodromal and Clinical Alzheimer's Disease

BACKGROUND

Increasing evidence suggests that thalamic nuclei may atrophy in Alzheimer's disease (AD). We hypothesized that there will be significant atrophy of limbic thalamic nuclei associated with declining memory and cognition across the AD continuum.

OBJECTIVE

The objective of this work was to characterize volume differences in thalamic nuclei in subjects with early and late mild cognitive impairment (MCI) as well as AD when compared to healthy control (HC) subjects using a novel MRI-based thalamic segmentation technique (THOMAS).

METHODS

MPRAGE data from the ADNI database were used in this study (n = 540). Healthy control (n = 125), early MCI (n = 212), late MCI (n = 114), and AD subjects (n = 89) were selected, and their MRI data were parcellated to determine the volumes of 11 thalamic nuclei for each subject. Volumes across the different clinical subgroups were compared using ANCOVA.

RESULTS

There were significant differences in thalamic nuclei volumes between HC, late MCI, and AD subjects. The anteroventral, mediodorsal, pulvinar, medial geniculate, and centromedian nuclei were significantly smaller in subjects with late MCI and AD when compared to HC subjects. Furthermore, the mediodorsal, pulvinar, and medial geniculate nuclei were significantly smaller in early MCI when compared to HC subjects.

CONCLUSION

This work highlights nucleus specific atrophy within the thalamus in subjects with early and late MCI and AD. This is consistent with the hypothesis that memory and cognitive changes in AD are mediated by damage to a large-scale integrated neural network that extends beyond the medial temporal lobes.

Associations between subregional thalamic volume and brain pathology in autosomal dominant Alzheimer's disease

Histopathological reports suggest that subregions of the thalamus, which regulates multiple physiological and cognitive processes, are not uniformly affected by Alzheimer's disease. Despite this, structural neuroimaging studies often consider the thalamus as a single region. Identification of in vivo Alzheimer's-dependent volumetric changes in thalamic subregions may aid the characterization of early nuclei-specific neurodegeneration in Alzheimer's disease. Here, we leveraged access to the largest single-mutation cohort of autosomal-dominant Alzheimer's disease to test whether cross-sectional abnormalities in subregional thalamic volumes are evident in non-demented mutation carriers (n = 31), compared to non-carriers (n = 36), and whether subregional thalamic volume is associated with age, markers of brain pathology and cognitive performance. Using automatic parcellation we examined the thalamus in six subregions (anterior, lateral, ventral, intralaminar, medial, and posterior) and their relation to age and brain pathology (amyloid and tau), as measured by PET imaging. No between-group differences were observed in the volume of the thalamic subregions. In carriers, lower volume in the medial subregion was related to increased cortical amyloid and entorhinal tau burden. These findings suggest that thalamic Alzheimer's-related volumetric reductions are not uniform even in preclinical and prodromal stages of autosomal-dominant Alzheimer's disease and therefore, this structure should not be considered as a single, unitary structure in Alzheimer's disease research.

Complete Evaluation of Dementia: PET and MRI Correlation and Diagnosis for the Neuroradiologist

This article will familiarize neuroradiologists with the pathophysiology, clinical findings, and standard MR imaging and PET imaging features of multiple forms of dementia as well as new emerging techniques. Cases were compiled from multiple institutions with the goal of improved diagnostic accuracy and improved patient care as well as information about biomarkers on the horizon. Dementia topics addressed include the following: Alzheimer disease, frontotemporal dementia, cerebral amyloid angiopathy, Lewy body dementia, Parkinson disease and Parkinson disease variants, amyotrophic lateral sclerosis, multisystem atrophy, Huntington disease vascular dementia, and Creutzfeldt-Jakob disease.

Exercise Training-Related Changes in Cortical Gray Matter Diffusivity and Cognitive Function in Mild Cognitive Impairment and Healthy Older Adults

Individuals with Mild Cognitive Impairment (MCI) are at an elevated risk of dementia and exhibit deficits in cognition and cortical gray matter (GM) volume, thickness, and microstructure. Meanwhile, exercise training appears to preserve brain function and macrostructure may help delay or prevent the onset of dementia in individuals with MCI. Yet, our understanding of the neurophysiological effects of exercise training in individuals with MCI remains limited. Recent work suggests that the measures of gray matter microstructure using diffusion imaging may be sensitive to early cognitive and neurophysiological changes in the aging brain. Therefore, this study is aimed to determine the effects of exercise training in cognition and cortical gray matter microstructure in individuals with MCI vs. cognitively healthy older adults. Fifteen MCI participants and 17 cognitively intact controls (HC) volunteered for a 12-week supervised walking intervention. Following the intervention, MCI and HC saw improvements in cardiorespiratory fitness, performance on Trial 1 of the Rey Auditory Verbal Learning Test (RAVLT), a measure of verbal memory, and the Controlled Oral Word Association Test (COWAT), a measure of verbal fluency. After controlling for age, a voxel-wise analysis of cortical gray matter diffusivity showed individuals with MCI exhibited greater increases in mean diffusivity (MD) in the left insular cortex than HC. This increase in MD was positively associated with improvements in COWAT performance. Additionally, after controlling for age, the voxel-wise analysis indicated a main effect of Time with both groups experiencing an increase in left insular and left and right cerebellar MD. Increases in left insular diffusivity were similarly found to be positively associated with improvements in COWAT performance in both groups, while increases in cerebellar MD were related to gains in episodic memory performance. These findings suggest that exercise training may be related to improvements in neural circuits that govern verbal fluency performance in older adults through the microstructural remodeling of cortical gray matter. Furthermore, changes in left insular cortex microstructure may be particularly relevant to improvements in verbal fluency among individuals diagnosed with MCI.

Biphasic cortical macro- and microstructural changes in autosomal dominant Alzheimer's disease

INTRODUCTION

A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti-amyloid clinical trials.

METHODS

In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity-a novel marker of cortical microstructure-changes in 389 participants from the Dominantly Inherited Alzheimer Network.

RESULTS

In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations.

DISCUSSION

These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials.

Obstructive Sleep Apnea and the Brain: a Focus on Gray and White Matter Structure

PURPOSE OF REVIEW

Obstructive sleep apnea is extremely prevalent in the elderly and may precipitate dementia. We review recent advances on gray and white matter structure in obstructive sleep apnea, the impact of treatment, and potential pathological and neurodegenerative processes underlying brain structural changes.

RECENT FINDINGS

Two opposite patterns are observed in neuroimaging studies of obstructive sleep apnea. One may indicate cellular damage (gray matter atrophy, higher white matter hyperintensity burden, lower white matter fractional anisotropy, higher water diffusivities), while the other (gray matter hypertrophy, restricted white matter diffusivities) may reflect transitory responses, such as intracellular edema, reactive gliosis or compensatory structural changes. Treating obstructive sleep apnea could partly reverse these structural changes. Structural alterations related to obstructive sleep apnea may follow a multi-determined biphasic pattern depending on numerous factors (e.g. severity, symptomatology, age) that could tip the scale toward neurodegeneration and need to be investigated by longitudinal studies.

APOE-ε4-related differences in left thalamic microstructure in cognitively healthy adults

APOE-ε4 is a main genetic risk factor for developing late onset Alzheimer's disease (LOAD) and is thought to interact adversely with other risk factors on the brain. However, evidence regarding the impact of APOE-ε4 on grey matter structure in asymptomatic individuals remains mixed. Much attention has been devoted to characterising APOE-ε4-related changes in the hippocampus, but LOAD pathology is known to spread through the whole of the Papez circuit including the limbic thalamus. Here, we tested the impact of APOE-ε4 and two other risk factors, a family history of dementia and obesity, on grey matter macro- and microstructure across the whole brain in 165 asymptomatic individuals (38-71 years). Microstructural properties of apparent neurite density and dispersion, free water, myelin and cell metabolism were assessed with Neurite Orientation Density and Dispersion (NODDI) and quantitative magnetization transfer (qMT) imaging. APOE-ε4 carriers relative to non-carriers had a lower macromolecular proton fraction (MPF) in the left thalamus. No risk effects were present for cortical thickness, subcortical volume, or NODDI indices. Reduced thalamic MPF may reflect inflammation-related tissue swelling and/or myelin loss in APOE-ε4. Future prospective studies should investigate the sensitivity and specificity of qMT-based MPF as a non-invasive biomarker for LOAD risk.

The presymptomatic phase of amyotrophic lateral sclerosis: are we merely scratching the surface?

Presymptomatic studies in ALS have consistently captured considerable disease burden long before symptom manifestation and contributed important academic insights. With the emergence of genotype-specific therapies, however, there is a pressing need to address practical objectives such as the estimation of age of symptom onset, phenotypic prediction, informing the optimal timing of pharmacological intervention, and identifying a core panel of biomarkers which may detect response to therapy. Existing presymptomatic studies in ALS have adopted striking different study designs, relied on a variety of control groups, used divergent imaging and electrophysiology methods, and focused on different genotypes and demographic groups. We have performed a systematic review of existing presymptomatic studies in ALS to identify common themes, stereotyped shortcomings, and key learning points for future studies. Existing presymptomatic studies in ALS often suffer from sample size limitations, lack of disease controls and rarely follow their cohort until symptom manifestation. As the characterisation of presymptomatic processes in ALS serves a multitude of academic and clinical purposes, the careful review of existing studies offers important lessons for future initiatives.

Putaminal diffusion tensor imaging measures predict disease severity across human prion diseases

Therapeutic trials of disease-modifying agents in neurodegenerative disease typically require several hundred participants and long durations for clinical endpoints. Trials of this size are not feasible for prion diseases, rare dementia disorders associated with misfolding of prion protein. In this situation, biomarkers are particularly helpful. On diagnostic imaging, prion diseases demonstrate characteristic brain signal abnormalities on diffusion-weighted MRI. The aim of this study was to determine whether cerebral water diffusivity could be a quantitative imaging biomarker of disease severity. We hypothesized that the basal ganglia were most likely to demonstrate functionally relevant changes in diffusivity. Seventy-one subjects (37 patients and 34 controls) of whom 47 underwent serial scanning (23 patients and 24 controls) were recruited as part of the UK National Prion Monitoring Cohort. All patients underwent neurological assessment with the Medical Research Council Scale, a functionally orientated measure of prion disease severity, and diffusion tensor imaging. Voxel-based morphometry, voxel-based analysis of diffusion tensor imaging and regions of interest analyses were performed. A significant voxel-wise correlation of decreased Medical Research Council Scale score and decreased mean, radial and axial diffusivities in the putamen bilaterally was observed (P < 0.01). Significant decrease in putamen mean, radial and axial diffusivities over time was observed for patients compared with controls (P = 0.01), and there was a significant correlation between monthly decrease in putamen mean, radial and axial diffusivities and monthly decrease in Medical Research Council Scale (P < 0.001). Step-wise linear regression analysis, with dependent variable decline in Medical Research Council Scale, and covariates age and disease duration, showed the rate of decrease in putamen radial diffusivity to be the strongest predictor of rate of decrease in Medical Research Council Scale (P < 0.001). Sample size calculations estimated that, for an intervention study, 83 randomized patients would be required to provide 80% power to detect a 75% amelioration of decline in putamen radial diffusivity. Putamen radial diffusivity has potential as a secondary outcome measure biomarker in future therapeutic trials in human prion diseases.

Measuring cortical mean diffusivity to assess early microstructural cortical change in presymptomatic familial Alzheimer's disease

Background

There is increasing interest in improving understanding of the timing and nature of early neurodegeneration in Alzheimer’s disease (AD) and developing methods to measure this in vivo. Autosomal dominant familial Alzheimer’s disease (FAD) provides the opportunity for investigation of presymptomatic change. We assessed early microstructural breakdown of cortical grey matter in FAD with diffusion-weighted MRI.

Methods

Diffusion-weighted and T1-weighed MRI were acquired in 38 FAD mutation carriers (17 symptomatic, 21 presymptomatic) and 39 controls. Mean diffusivity (MD) was calculated for six cortical regions previously identified as being particularly vulnerable to FAD-related neurodegeneration. Linear regression compared MD between symptomatic and presymptomatic carriers and controls, adjusting for age and sex. Spearman coefficients assessed associations between cortical MD and cortical thickness. Spearman coefficients also assessed associations between cortical MD and estimated years to/from onset (EYO). Across mutation carriers, linear regression assessed associations between MD and EYO, adjusting for cortical thickness.

Results

Compared with controls, cortical MD was higher in symptomatic mutation carriers (mean ± SD CDR = 0.88 ± 0.39) for all six regions (p < 0.001). In late presymptomatic carriers (within 8.1 years of predicted symptom onset), MD was higher in the precuneus (p = 0.04) and inferior parietal cortex (p = 0.003) compared with controls. Across all presymptomatic carriers, MD in the precuneus correlated with EYO (p = 0.04). Across all mutation carriers, there was strong evidence (p < 0.001) of association between MD and cortical thickness in all regions except entorhinal cortex. After adjusting for cortical thickness, there remained an association (p < 0.05) in mutation carriers between MD and EYO in all regions except entorhinal cortex.

Conclusions

Cortical MD measurement detects microstructural breakdown in presymptomatic FAD and correlates with proximity to symptom onset independently of cortical thickness. Cortical MD may thus be a feasible biomarker of early AD-related neurodegeneration, offering additional/complementary information to conventional MRI measures.

White Matter Changes on Diffusion Tensor Imaging in the FINGER Randomized Controlled Trial

Background:

Early pathological changes in white matter microstructure can be studied using the diffusion tensor imaging (DTI). It is not only important to study these subtle pathological changes leading to cognitive decline, but also to ascertain how an intervention would impact the white matter microstructure and cognition in persons at-risk of dementia.

Objectives:

To study the impact of a multidomain lifestyle intervention on white matter and cognitive changes during the 2-year Finnish Geriatric Intervention Study to prevent Cognitive Impairment and Disability (FINGER), a randomized controlled trial in at-risk older individuals (age 60–77 years) from the general population.

Methods:

This exploratory study consisted of a subsample of 60 FINGER participants. Participants were randomized to either a multidomain intervention (diet, exercise, cognitive training, and vascular risk management, n = 34) or control group (general health advice, n = 26). All underwent baseline and 2-year brain DTI. Changes in fractional anisotropy (FA), diffusivity along domain (F1) and non-domain (F2) diffusion orientations, mean diffusivity (MD), axial diffusivity (AxD), radial diffusivity (RD), and their correlations with cognitive changes during the 2-year multidomain intervention were analyzed.

Results:

FA decreased, and cognition improved more in the intervention group compared to the control group (p < 0.05), with no significant intergroup differences for changes in F1, F2, MD, AxD, or RD. The cognitive changes were significantly positively related to FA change, and negatively related to RD change in the control group, but not in the intervention group.

Conclusion:

The 2-year multidomain FINGER intervention may modulate white matter microstructural alterations.

Early diagnosis and treatment of Alzheimer's disease: new definitions and challenges

The prevalence of Alzheimer's disease (AD), a progressive neurodegenerative disorder, is expected to more than double by 2050. Studies on the pathophysiology of AD have been changing our understanding of this disorder and setting a new scenario for drug development and other therapies. Concepts like the "amyloid cascade" and the "continuum of AD," discussed in this article, are now well established. From updated classifications and recommendations to advances in biomarkers of AD, we aim to critically assess the literature on AD, addressing new definitions and challenges that emerged from recent studies on the subject. Updates on the status of major clinical trials are also given, and future perspectives are discussed.

Imaging Alzheimer's genetic risk using diffusion MRI: A systematic review

Diffusion magnetic resonance imaging (dMRI) is an imaging technique which probes the random motion of water molecules in tissues and has been widely applied to investigate changes in white matter microstructure in Alzheimer's Disease. This paper aims to systematically review studies that examined the effect of Alzheimer's risk genes on white matter microstructure. We assimilated findings from 37 studies and reviewed their diffusion pre-processing and analysis methods. Most studies estimate the diffusion tensor (DT) and compare derived quantitative measures such as fractional anisotropy and mean diffusivity between groups. Those with increased AD genetic risk are associated with reduced anisotropy and increased diffusivity across the brain, most notably the temporal and frontal lobes, cingulum and corpus callosum. Structural abnormalities are most evident amongst those with established Alzheimer's Disease. Recent studies employ signal representations and analysis frameworks beyond DT MRI but show that dMRI overall lacks specificity to disease pathology. However, as the field advances, these techniques may prove useful in pre-symptomatic diagnosis or staging of Alzheimer's disease.

Substantia Nigra Volumetry with 3-T MRI in De Novo and Advanced Parkinson Disease

Background Magnetization transfer-prepared T1-weighted MRI can depict a hyperintense subregion of the substantia nigra involved in the degeneration process of Parkinson disease. Purpose To evaluate quantitative measurement of substantia nigra volume by using MRI to support clinical diagnosis and staging of Parkinson disease. Materials and Methods In this prospective study, a high-spatial-resolution magnetization transfer-prepared T1-weighted volumetric sequence was performed with a 3-T MRI machine between January 2014 and October 2015 for participants with de novo Parkinson disease, advanced Parkinson disease, and healthy control participants. A reproducible semiautomatic quantification analysis method that entailed mesencephalic intensity as an internal reference was used for hyperintense substantia nigra volumetry normalized to intracranial volume. A general linear model with age and sex as covariates was used to compare the three groups. Results Eighty participants were evaluated: 20 healthy control participants (mean age ± standard deviation, 56 years ± 11; 11 women), 29 participants with de novo Parkinson disease (64 years ± 10; 19 men), and 31 participants with advanced Parkinson disease (60 years ± 9; 16 women). Volumetric measurement of hyperintense substantia nigra from magnetization transfer-prepared T1-weighted MRI helped differentiate healthy control participants from participants with advanced Parkinson disease (mean difference for ipsilateral side, 64 mm³ ± 14, P < .001; mean difference for contralateral side, 109 mm³ ± 14, P < .001) and helped distinguish healthy control participants from participants with de novo Parkinson disease (mean difference for ipsilateral side, 45 mm³ ± 15, P < .01; mean difference for contralateral side, 66 mm³ ± 15, P < .001) and participants with de novo Parkinson disease from those with advanced Parkinson disease (mean difference for ipsilateral side, 20 mm³ ± 13, P = .40; mean difference for contralateral side, 43 mm³ ± 13, P = .004). Conclusion Magnetization transfer-prepared T1-weighted MRI volumetry of the substantia nigra helped differentiate the stages of Parkinson disease. © RSNA, 2020 Online supplemental material is available for this article.

Cortical microstructural correlates of astrocytosis in autosomal-dominant Alzheimer disease

OBJECTIVE

To study the macrostructural and microstructural MRI correlates of brain astrocytosis, measured with ¹¹C-deuterium-L-deprenyl (¹¹C-DED)-PET, in familial autosomal-dominant Alzheimer disease (ADAD).

METHODS

The total sample (n = 31) comprised ADAD mutation carriers (n = 10 presymptomatic, 39.2 ± 10.6 years old; n = 3 symptomatic, 55.5 ± 2.0 years old) and noncarriers (n = 18, 44.0 ± 13.7 years old) belonging to families with mutations in either the presenilin-1 or amyloid precursor protein genes. All participants underwent structural and diffusion MRI and neuropsychological assessment, and 20 participants (6 presymptomatic and 3 symptomatic mutation carriers and 11 noncarriers) also underwent ¹¹C-DED-PET.

RESULTS

Vertex-wise interaction analyses revealed a differential relationship between carriers and noncarriers in the association between ¹¹C-DED binding and estimated years to onset (EYO) and between cortical mean diffusivity (MD) and EYO. These differences were due to higher ¹¹C-DED binding in presymptomatic carriers, with lower binding in symptomatic carriers compared to noncarriers, and to lower cortical MD in presymptomatic carriers, with higher MD in symptomatic carriers compared to noncarriers. Using a vertex-wise local correlation approach, ¹¹C-DED binding was negatively correlated with cortical MD and positively correlated with cortical thickness.

CONCLUSIONS

Our proof-of-concept study is the first to show that microstructural and macrostructural changes can reflect underlying neuroinflammatory mechanisms in early stages of Alzheimer disease (AD). The findings support a role for neuroinflammation in AD pathogenesis, with potential implications for the correct interpretation of neuroimaging biomarkers as surrogate endpoints in clinical trials.