Altered whole-brain white matter networks in preclinical Alzheimer's disease

A longitudinal MRI analysis reveals altered brain connectivity and microstructural changes in a transgenic mouse model of Alzheimer's disease

Alzheimer's disease (AD) is characterized by progressive cognitive decline and neuropathological changes, yet the underlying neurobiological mechanisms remain elusive. Here, we employed a multimodal longitudinal neuroimaging approach, using anatomical and functional sequences on a high field magnetic resonance imaging (MRI) preclinical scanner, to investigate alterations in brain connectivity and white matter microstructure in a transgenic mouse model of AD (J20) when compared to wild-type (WT) littermates. Functional connectivity analysis revealed distinct network disruptions in J20 mice, primarily involving connections between posterior and anterior brain regions; importantly, a significant interaction between group and age highlighted an exacerbation of these connectivity changes with advancing age in J20 mice. In addition, significant reductions in fractional anisotropy (FA) were observed in the corpus callosum of J20 mice compared to WT, indicative of microstructural alterations consistent with white matter pathology. The observed alterations in brain connectivity and microstructure provide valuable insights into the spatiotemporal processes underlying AD-related decline and underscore the utility of multimodal neuroimaging in elucidating the neurobiological substrates of AD pathology in animal models.

The brain network hub degeneration in Alzheimer's disease

Alzheimer's disease (AD) has been conceptualized as a syndrome of brain network dysfunction. Recent imaging connectomics studies have provided unprecedented opportunities to map structural and functional brain networks in AD. By reviewing molecular, imaging, and computational modeling studies, we have shown that highly connected brain hubs are primarily distributed in the medial and lateral prefrontal, parietal, and temporal regions in healthy individuals and that the hubs are selectively and severely affected in AD as manifested by increased amyloid-beta deposition and regional atrophy, hypo-metabolism, and connectivity dysfunction. Furthermore, AD-related hub degeneration depends on the imaging modality with the most notable degeneration in the medial temporal hubs for morphological covariance networks, the prefrontal hubs for structural white matter networks, and in the medial parietal hubs for functional networks. Finally, the AD-related hub degeneration shows metabolic, molecular, and genetic correlates. Collectively, we conclude that the brain-network-hub-degeneration framework is promising to elucidate the biological mechanisms of network dysfunction in AD, which provides valuable information on potential diagnostic biomarkers and promising therapeutic targets for the disease.

Reorganization of brain connectivity across the spectrum of clinical cognitive decline

Clinical cognitive decline, leading to Alzheimer's Disease Dementia (ADD), has long been interpreted as a disconnection syndrome, hindering the information flow capacity of the brain, hence leading to the well-known symptoms of ADD. The structural and functional brain connectome analyses play a central role in studies of brain from this perspective. However, most current research implicitly assumes that the changes accompanying the progression of cognitive decline are monotonous in time, whether measured across the entire brain or in fixed cortical regions. We investigate the structural and functional connectivity-wise reorganization of the brain without such assumptions across the entire spectrum. We utilize nodal assortativity as a local topological measure of connectivity and follow a data-centric approach to identify and verify relevant local regions, as well as to understand the nature of underlying reorganization. The analysis of our preliminary experimental data points to statistically significant, hyper and hypo-assortativity regions that depend on the disease's stage, and differ for structural and functional connectomes. Our results suggest a new perspective into the dynamic, potentially a mix of degenerative and compensatory, topological alterations that occur in the brain as cognitive decline progresses.

Non-linear relationship between serum cholesterol levels and cognitive change among older people in the preclinical and prodromal stages of dementia: a retrospective longitudinal study in Taiwan

BACKGROUND

Adverse effects of rigorously lowering low-density lipoprotein cholesterol on cognition have been reported; therefore, we aimed to study the contribution of serum cholesterol in cognitive decline in older people with or without dementia.

METHODS

Cognitive function was assessed by the Cognitive Abilities Screening Instrument (CASI). We investigated associations between serum cholesterol with cognitive decline using multiple regressions controlling for the effects of demographics, vascular risk factors, and treatments.

RESULTS

Most associations between cholesterol and CASI scores could be explained by non-linear and inverted U-shaped relationships (R2 = 0.003-0.006, p < 0.016, Šidákcorrection). The relationships were most evident between changes in cholesterol and CASI scores in older people at the preclinical or prodromal stages of dementia (R2 = 0.02-0.064, p values < 0.016). There were no differences in level of changes in CASI scores between individuals in 1st decile and 10th decile groups of changes in cholesterol (p = 0.266-0.972). However, individuals in the 1st decile of triglyceride changes and with stable and normal cognitive functions showed significant improvement in CASI scores compared to those in the 10th decile (t(202) = 2.275, p values < 0.05).

CONCLUSION

These findings could implicate that rigorously lowering cholesterol may not be suitable for the prevention of cognitive decline among older people, especially among individuals in preclinical or prodromal stages of dementia.

Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease

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

Novel insights into brain lipid metabolism in Alzheimer's disease: Oligodendrocytes and white matter abnormalities

Alzheimer's disease (AD) is the most common cause of dementia. A genome-wide association study has shown that several AD risk genes are involved in lipid metabolism. Additionally, epidemiological studies have indicated that the levels of several lipid species are altered in the AD brain. Therefore, lipid metabolism is likely changed in the AD brain, and these alterations might be associated with an exacerbation of AD pathology. Oligodendrocytes are glial cells that produce the myelin sheath, which is a lipid-rich insulator. Dysfunctions of the myelin sheath have been linked to white matter abnormalities observed in the AD brain. Here, we review the lipid composition and metabolism in the brain and myelin and the association between lipidic alterations and AD pathology. We also present the abnormalities in oligodendrocyte lineage cells and white matter observed in AD. Additionally, we discuss metabolic disorders, including obesity, as AD risk factors and the effects of obesity and dietary intake of lipids on the brain.

Temporal Alterations in White Matter in An App Knock-In Mouse Model of Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia and results in neurodegeneration and cognitive impairment. White matter (WM) is affected in AD and has implications for neural circuitry and cognitive function. The trajectory of these changes across age, however, is still not well understood, especially at earlier stages in life. To address this, we used the AppNL-G-F/NL-G-F knock-in (APPKI) mouse model that harbors a single copy knock-in of the human amyloid precursor protein (APP) gene with three familial AD mutations. We performed in vivo diffusion tensor imaging (DTI) to study how the structural properties of the brain change across age in the context of AD. In late age APPKI mice, we observed reduced fractional anisotropy (FA), a proxy of WM integrity, in multiple brain regions, including the hippocampus, anterior commissure (AC), neocortex, and hypothalamus. At the cellular level, we observed greater numbers of oligodendrocytes in middle age (prior to observations in DTI) in both the AC, a major interhemispheric WM tract, and the hippocampus, which is involved in memory and heavily affected in AD, prior to observations in DTI. Proteomics analysis of the hippocampus also revealed altered expression of oligodendrocyte-related proteins with age and in APPKI mice. Together, these results help to improve our understanding of the development of AD pathology with age, and imply that middle age may be an important temporal window for potential therapeutic intervention.

Single-cell transcriptomics analysis of zebrafish brain reveals adverse effects of manganese on neurogenesis

Manganese (Mn) is considered as an important environmental risk factor for Parkinson's disease. Excessive exposure to Mn can damage various neural cells and affect the neurogenesis, resulting in neurological dysfunction. However, the specific mechanisms of Mn exposure affecting neurogenesis have not been well understood, including compositional changes and heterogeneity of various neural cells. Zebrafish have been successfully used as a neurotoxicity model due to its homology with mammals in several key regions of the brain, as well as its advantages such as small size. We performed single-cell RNA sequencing of zebrafish brains from normal and Mn-exposed groups. Our results suggested that low levels of Mn exposure activated neurogenesis in the zebrafish brain, including promoting the proliferation of neural progenitor cells and differentiation to newborn neurons and oligodendrocytes, while high levels of Mn exposure inhibited neurogenesis and neural function. Mn could affect neurogenesis through specific molecular pathways. In addition, Mn regulated intercellular communication and affected cellular communication in neural cells through specific signaling pathways. Taken together, our study elucidates the cellular composition of the zebrafish brain and adds to the understanding of the mechanisms involved in Mn-induced neurogenesis damage.

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.

A hydrolyzed lipid blend diet promotes myelination in neonatal piglets in a region and concentration-dependent manner

The impact of early life nutrition on myelin development is of interest given that cognitive and behavioral function depends on proper myelination. Evidence shows that myelination can be altered by dietary lipid, but most of these studies have been performed in the context of disease or impairment. Here, we assessed the effects of lipid blends containing various levels of a hydrolyzed fat (HF) system on myelination in healthy piglets. Piglets were sow-reared, fed a control diet, or a diet containing 12%, 25%, or 53% HF consisting of cholesterol, fatty acids, monoglycerides, and phospholipid from lecithin. At postnatal day 28/29, magnetic resonance imaging (MRI) was performed to assess changes to brain development, followed by brain collection for microscopic analyses of myelin in targeted regions using CLARITY tissue clearing, immunohistochemistry, and electron microscopy techniques. Sow-reared piglets exhibited the highest overall brain white matter volume by MRI. However, a 25% HF diet resulted in the greatest total myelin density in the prefrontal cortex based on 3D modeling analysis of myelinated filaments. Nodal gap length and g-ratio were inversely correlated with percentage of HF in the corpus callosum, as well as in the PFC and internal capsule for g-ratio, indicating that a 53% HF diet resulted in the thickest myelin per axon and a 0% HF control diet the thinnest in specific brain regions. These findings indicate that HF promoted myelination in the neonatal piglet in a region- and concentration-dependent manner.

Structural Network Topology Reveals Higher Brain Resilience in Individuals with Preclinical Alzheimer's Disease

Introduction: The diagnosis of Alzheimer's disease (AD) requires the presence of amyloid and tau pathology, but it remains unclear how they affect the structural network in the pre-clinical stage. We aimed to assess differences in topological properties in cognitively normal (CN) individuals with varying levels of amyloid and tau pathology, as well as their association with AD pathology burden. Methods: A total of 68 CN individuals were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding three groups: A-T- (n = 19), A+T- (n = 28), and A+T+ (n = 21). Topological properties were measured from structural connectivity. Group differences and correlations with A and T were evaluated. Results: Compared with the A-T- group, the A+T+ group exhibited changes in the structural network topology. At the global level, higher assortativity was shown in the A+T+ group and was correlated with greater tau burden (r = 0.29, p = 0.02), while no difference in global efficiency was found across the three groups. At the local level, the A+T+ group showed disrupted topological properties in the left hippocampus compared with the A-T- group, characterized by lower local efficiency (p < 0.01) and a lower clustering coefficient (p = 0.014). Conclusions: The increased linkage in the higher level architecture of the white matter network reflected by assortativity may indicate increased brain resilience in the early pathological state. Our results encourage further investigation of the topological properties of the structural network in pre-clinical AD.

Sex differences in the structural rich-club connectivity in patients with Alzheimer's disease

Background and objectives

Alzheimer's disease (AD) is more prevalent in women than in men; however, there is a discrepancy in research on sex differences in AD. The human brain is a large-scale network with hub regions forming a central core, the rich-club, which is vital to cognitive functions. However, it is unknown whether alterations in the rich-clubs in AD differ between men and women. We aimed to investigate sex differences in the rich-club organization in the brains of patients with AD.

Methods

In total, 260 cognitively unimpaired individuals with negative amyloid positron emission tomography (PET) scans, 281 with prodromal AD (mild cognitive impairment due to AD) and 285 with AD dementia who confirmed with positive amyloid PET scans participated in the study. We obtained high-resolution T1-weighted and diffusion tensor images and performed network analysis.

Results

We observed sex differences in the rich-club and feeder connections in patients with AD, suggesting lower structural connectivity strength in women than in men. We observed a significant group-by-sex interaction in the feeder connections, particularly in the thalamus. In addition, the connectivity strength of the thalamus in the feeder connections was significantly correlated with general cognitive function in only men with prodromal AD and women with AD dementia.

Conclusion

Our findings provide important evidence for sex-specific alterations in the structural brain network related to AD.

Diffusion tensor imaging tractography in the one-humped camel (Camelus dromedarius) brain

Introduction

Tractography is a technique used to trace the pathways of the brain using noninvasive diffusion tensor imaging (DTI) data. It is becoming increasingly popular for investigating the brains of domestic mammals and other animals with myelinated fibers but the principle of DTI can also apply for those with unmyelinated fibers. In the case of camels, DTI tractography is a promising method for enhancing current knowledge of the brain's structural connectivity and identifying white-matter tract changes potentially linked to neurodegenerative pathologies. The present study was therefore designed to describe representative white-matter tracts in the one-humped camel DTI tractography.

Methods

Post mortem DTI was used to obtain images of two one-humped camel brains using a 3 Tesla system. T2-weighted images were also acquired to identify regions of interest for each fiber tract and a fiber dissection technique was used to complement the DT images. The main association, commissural, and projection fibers were reconstructed and superimposed on T2-weighted images or fractional anisotropy maps.

Results

The results of the present study show the reconstruction of the most representative tracts, ie the cingulum, the corpus callosum and the internal capsule, in the one-humped camel brain using DTI data acquired post mortem. These DTI results were compared to those from fiber dissection.

Discussion

Anatomy of the cingulum, corpus callosum and internal capsule correlates well with the description in anatomical textbooks and appears to be similar to fibers describe in large animals. Further research will be required to improve and validate these findings and to generate a tractography atlas based on MRI and histological data, as such an atlas would be a valuable resource for future neuroimaging research.

Sleep deprivation aggravated amyloid β oligomers-induced damage to the cerebellum of rats: Evidence from magnetic resonance imaging

For quite a long time, researches on Alzheimer's disease (AD) primarily focused on the cortex and hippocampus, while the cerebellum has been ignored because of its abnormalities considered to appear in the late stage of AD. In recent years, increasing evidence suggest that the cerebellar pathological changes possibly occur in the preclinical phase of AD, which is also associated with sleep disorder. Sleep disturbance is a high risk factor of AD. However, the changes and roles of cerebellum has rarely been reported under conditions of AD accompanied with sleep disorders. In this study, using an amyloid-β oligomers (AβO)-induced rat model of AD subjected to sleep deprivation, combining with a 7.0 T animals structural magnetic resonance imaging (MRI), we assessed structural changes of cerebellum in MRI. Our results showed that sleep deprivation combined with AβO led to an increased FA value in the anterior lobe of cerebellum, decreased ADC value in the cerebellar lobes and cerebellar nuclei, and increased cerebellum volume. Besides that, sleep deprivation exacerbated the damage of AβO to the cerebellar structural network. This study demonstrated that sleep deprivation could aggravate the damage to cerebellum induced by AβO. The present findings provide supporting evidence for the involvement of cerebellum in the early pathology of AD and sleep loss. Our data would contribute to advancing the understanding of the mysterious role of cerebellum in AD and sleep disorders, as well as would be helpful for developing non-invasive MRI biomarkers for screening early AD patients with self-reported sleep disturbances.

White matter injury, cholesterol dysmetabolism, and APP/Abeta dysmetabolism interact to produce Alzheimer's disease (AD) neuropathology: A hypothesis and review

We postulate that myelin injury contributes to cholesterol release from myelin and cholesterol dysmetabolism which contributes to Abeta dysmetabolism, and combined with genetic and AD risk factors, leads to increased Abeta and amyloid plaques. Increased Abeta damages myelin to form a vicious injury cycle. Thus, white matter injury, cholesterol dysmetabolism and Abeta dysmetabolism interact to produce or worsen AD neuropathology. The amyloid cascade is the leading hypothesis for the cause of Alzheimer's disease (AD). The failure of clinical trials based on this hypothesis has raised other possibilities. Even with a possible new success (Lecanemab), it is not clear whether this is a cause or a result of the disease. With the discovery in 1993 that the apolipoprotein E type 4 allele (APOE4) was the major risk factor for sporadic, late-onset AD (LOAD), there has been increasing interest in cholesterol in AD since APOE is a major cholesterol transporter. Recent studies show that cholesterol metabolism is intricately involved with Abeta (Aβ)/amyloid transport and metabolism, with cholesterol down-regulating the Aβ LRP1 transporter and upregulating the Aβ RAGE receptor, both of which would increase brain Aβ. Moreover, manipulating cholesterol transport and metabolism in rodent AD models can ameliorate pathology and cognitive deficits, or worsen them depending upon the manipulation. Though white matter (WM) injury has been noted in AD brain since Alzheimer's initial observations, recent studies have shown abnormal white matter in every AD brain. Moreover, there is age-related WM injury in normal individuals that occurs earlier and is worse with the APOE4 genotype. Moreover, WM injury precedes formation of plaques and tangles in human Familial Alzheimer's disease (FAD) and precedes plaque formation in rodent AD models. Restoring WM in rodent AD models improves cognition without affecting AD pathology. Thus, we postulate that the amyloid cascade, cholesterol dysmetabolism and white matter injury interact to produce and/or worsen AD pathology. We further postulate that the primary initiating event could be related to any of the three, with age a major factor for WM injury, diet and APOE4 and other genes a factor for cholesterol dysmetabolism, and FAD and other genes for Abeta dysmetabolism.

Hypergraph representation of multimodal brain networks for patients with end-stage renal disease associated with mild cognitive impairment

The structure and function of brain networks (BN) may be altered in patients with end-stage renal disease (ESRD). However, there are relatively few attentions on ESRD associated with mild cognitive impairment (ESRDaMCI). Most studies focus on the pairwise relationships between brain regions, without taking into account the complementary information of functional connectivity (FC) and structural connectivity (SC). To address the problem, a hypergraph representation method is proposed to construct a multimodal BN for ESRDaMCI. First, the activity of nodes is determined by connection features extracted from functional magnetic resonance imaging (fMRI) (i.e., FC), and the presence of edges is determined by physical connections of nerve fibers extracted from diffusion kurtosis imaging (DKI) (i.e., SC). Then, the connection features are generated through bilinear pooling and transformed into an optimization model. Next, a hypergraph is constructed according to the generated node representation and connection features, and the node degree and edge degree of the hypergraph are calculated to obtain the hypergraph manifold regularization (HMR) term. The HMR and L₁ norm regularization terms are introduced into the optimization model to achieve the final hypergraph representation of multimodal BN (HRMBN). Experimental results show that the classification performance of HRMBN is significantly better than that of several state-of-the-art multimodal BN construction methods. Its best classification accuracy is 91.0891%, at least 4.3452% higher than that of other methods, verifying the effectiveness of our method. The HRMBN not only achieves better results in ESRDaMCI classification, but also identifies the discriminative brain regions of ESRDaMCI, which provides a reference for the auxiliary diagnosis of ESRD.

White matter hyperintensities are a prominent feature of autosomal dominant Alzheimer’s disease that emerge prior to dementia

Background

To promote the development of effective therapies, there is an important need to characterize the full spectrum of neuropathological changes associated with Alzheimer’s disease. In line with this need, this study examined white matter abnormalities in individuals with early-onset autosomal dominant Alzheimer’s disease, in relation to age and symptom severity.

Methods

This is a cross-sectional analysis of data collected in members of a large kindred with a PSEN1 E280A mutation. Participants were recruited between September 2011 and July 2012 from the Colombian Alzheimer’s Prevention Initiative registry. The studied cohort comprised 50 participants aged between 20 and 55 years, including 20 cognitively unimpaired mutation carriers, 9 cognitively impaired mutation carriers, and 21 non-carriers. Participants completed an MRI, a lumbar puncture for cerebrospinal fluid collection, a florbetapir PET scan, and neurological and neuropsychological examinations. The volume of white matter hyperintensities (WMH) was compared between cognitively unimpaired carriers, cognitively impaired carriers, and non-carriers. Relationships between WMH, age, and cognitive performance were further examined in mutation carriers.

Results

The mean (SD) age of participants was 35.8 (9.6) years and 64% were women. Cardiovascular risk factors were uncommon and did not differ across groups. Cognitively impaired carriers [median, 6.37; interquartile range (IQR), 9.15] had an increased volume of WMH compared to both cognitively unimpaired carriers [median, 0.85; IQR, 0.79] and non-carriers [median, 1.07; IQR, 0.71]. In mutation carriers, the volume of WMH strongly correlated with cognition and age, with evidence for an accelerated rate of changes after the age of 43 years, 1 year earlier than the estimated median age of symptom onset. In multivariable regression models including cortical amyloid retention, superior parietal lobe cortical thickness, and cerebrospinal fluid phospho-tau, the volume of WMH was the only biomarker independently and significantly contributing to the total explained variance in cognitive performance.

Conclusions

The volume of WMH is increased among individuals with symptomatic autosomal-dominant Alzheimer’s disease, begins to increase prior to clinical symptom onset, and is an independent determinant of cognitive performance in this group. These findings suggest that WMH are a key component of autosomal-dominant Alzheimer’s disease that is closely related to the progression of clinical symptoms.

Evaluation of functional MRI-based human brain parcellation: a review

Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.

Coupling analysis between functional and structural brain networks in Alzheimer's disease

The coupling between functional and structural brain networks is difficult to clarify due to the complicated alterations in gray matter and white matter for the development of Alzheimer's disease (AD). A cohort of 112 participants [normal control group (NC, 62 cases), mild cognitive impairment group (MCI, 31 cases) and AD group (19 cases)], was recruited in our study. The brain networks of rsfMRI functional connectivity (rsfMRI-FC) and diffusion tensor imaging structural connectivity (DTI-SC) across the three groups were constructed, and their correlations were evaluated by Pearson's correlation analyses and multiple comparison with Bonferroni correction. Furthermore, the correlations between rsfMRI-SC/DTI-FC coupling and four neuropsychological scores of mini-mental state examination (MMSE), clinical dementia rating-sum of boxes (CDR-SB), functional activities questionnaire (FAQ) and montreal cognitive assessment (MoCA) were inferred by partial correlation analyses, respectively. The results demonstrated that there existed significant correlation between rsfMRI-FC and DTI-SC (p < 0.05), and the coupling of rsfMRI-FC/DTI-SC showed negative correlation with MMSE score (p < 0.05), positive correlations with CDR-SB and FAQ scores (p < 0.05), and no correlation with MoCA score (p > 0.05). It was concluded that there existed FC/SC coupling and varied network characteristics for rsfMRI and DTI, and this would provide the clues to understand the underlying mechanisms of cognitive deficits of AD.

Early Alzheimer's disease-like reductions in gray matter and cognitive function with aging in nonhuman primates

Introduction

Age-related neuropathology associated with sporadic Alzheimer's disease (AD) often develops well before the onset of symptoms. Given AD's long preclinical period, translational models are needed to identify early signatures of pathological decline.

Methods

Using structural magnetic resonance imaging and cognitive assessments, we examined the relationships among age, cognitive performance, and neuroanatomy in 48 vervet monkeys (Chlorocebus aethiops sabaeus) ranging from young adults to very old.

Results

We found negative associations of age with cortical gray matter volume (P = .003) and the temporal-parietal cortical thickness meta-region of interest (P = .001). Additionally, cortical gray matter volumes predicted working memory at approximately 1-year follow-up (correct trials at the 20s delay [P = .008]; correct responses after longer delays [P = .004]).

Discussion

Cortical gray matter diminishes with age in vervets in regions relevant to AD, which may increase risk of cognitive impairment. This study lays the groundwork for future investigations to test therapeutics to delay or slow pathological decline.

Retinal layer assessments as potential biomarkers for brain atrophy in the Rhineland Study

Retinal assessments have been discussed as biomarkers for brain atrophy. However, available studies did not investigate all retinal layers due to older technology, reported inconsistent results, or were based on small sample sizes. We included 2872 eligible participants of the Rhineland Study with data on spectral domain-optical coherence tomography (SD-OCT) and brain magnetic resonance imaging (MRI). We used multiple linear regression to examine relationships between retinal measurements and volumetric brain measures as well as fractional anisotropy (FA) as measure of microstructural integrity of white matter (WM) for different brain regions. Mean (SD) age was 53.8 ± 13.2 years (range 30-94) and 57% were women. Volumes of the inner retina were associated with total brain and grey matter (GM) volume, and even stronger with WM volume and FA. In contrast, the outer retina was mainly associated with GM volume, while both, inner and outer retina, were associated with hippocampus volume. While we extend previously reported associations between the inner retina and brain measures, we found additional associations of the outer retina with parts of the brain. This indicates that easily accessible retinal SD-OCT assessments may serve as biomarkers for clinical monitoring of neurodegenerative diseases and merit further research.

Shenzhiling oral liquid protects the myelin sheath against Alzheimer's disease through the PI3K/Akt-mTOR pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Shenzhiling oral liquid (SZL), a traditional Chinese medicine (TCM) compound, is firstly approved by the Chinese Food and Drug Administration (CFDA) for the treatment of mild to moderate Alzheimer's disease (AD). SZL is composed of ten Chinese herbs, and the precise therapy mechanism of its action to AD is far from fully understood.

AIM OF THE STUDY

The purpose of this study was to observe whether SZL is an effective therapy for amyloid-beta (Aβ)-induced myelin sheath and oligodendrocytes impairments. Notably, the primary aim was to elucidate whether and through what underlying mechanism SZL protects the myelin sheath through the PI3K/Akt-mTOR signaling pathway in Aβ₄₂-induced OLN-93 oligodendrocytes in vitro.

MATERIALS AND METHODS

APP/PS1 mice were treated with SZL or donepezil continuously for three months, and Aβ₄₂-induced oligodendrocyte OLN-93 cells mimicking AD pathogenesis of myelin sheath impairments were incubated with SZL-containing serum or with donepezil. LC-MS/MS was used to analysis the active components of SZL and SZL-containing serum. The Y maze test was administered after 3 months of treatment, and the hippocampal tissues of the APP/PS1 mice were then harvested for observation of myelin sheath and oligodendrocyte morphology. Cell viability and toxicity were assessed using CCK-8 and lactate dehydrogenase (LDH) release assays, and flow cytometry was used to measure cell apoptosis. The expression of the myelin proteins MBP, PLP, and MAG and that of Aβ₄₂ and Aβ₄₀ in the hippocampi of APP/PS1 mice were examined after SZL treatment. Simultaneously, the expression of p-PI3K, PI3K, p-Akt, Akt, p-mTOR, and mTOR were also examined. The expression of proteins, including CNPase, Olig2, NKX2.2, MBP, PLP, MAG, MOG, p-PI3K, PI3K, p-Akt, Akt, p-mTOR, and mTOR, was determined by immunofluorescence and Western blot, and the corresponding gene expression was evaluated by qPCR in Aβ₄₂-induced OLN-93 oligodendrocytes.

RESULTS

LC-MS/MS detected a total of 126 active compounds in SZL-containing serum, including terpenoids, flavones, phenols, phenylpropanoids and phenolic acids. SZL treatment significantly improved memory and cognition in APP/PS1 mice and decreased the G-ratio of myelin sheath, alleviated myelin sheath and oligodendrocyte impairments by decreasing Aβ₄₂ and Aβ₄₀ accumulation and increasing the expression of myelin proteins MBP, PLP, MAG, and PI3K/Akt-mTOR signaling pathway associated protein in the hippocampi of APP/PS1 mice. SZL-containing serum also significantly reversed the OLN-93 cell injury induced by Aβ₄₂ by increasing cell viability and enhanced the expression of MBP, PLP, MAG, and MOG. Meanwhile, SZL-containing serum facilitated the maturation and differentiation of oligodendrocytes in Aβ₄₂-induced OLN-93 cells by heightening the expression of CNPase, Olig2 and NKX2.2. SZL-containing serum treatment also fostered the expression of p-PI3K, PI3K, p-Akt, Akt, p-mTOR, and mTOR, indicating an activating PI3K/Akt-mTOR signaling pathway in OLN-93 cells. Furthermore, the effects of SZL on myelin proteins, p-Akt, and p-mTOR were clearly inhibited by LY294002 and/or rapamycin, antagonists of PI3K and m-TOR, respectively.

CONCLUSIONS

Our findings indicate that SZL exhibits a neuroprotective effect on the myelin sheath by promoting the expression of myelin proteins during AD, and its mechanism of action is closely related to the activation of the PI3K/Akt-mTOR signaling pathway.

Cell type-specific potential pathogenic genes and functional pathways in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a pervasive age-related and highly heritable neurodegenerative disorder but has no effective therapy. The complex cellular microenvironment in the AD brain impedes our understanding of pathogenesis. Thus, a comprehensive investigation of cell type-specific responses in AD is crucial to provide precise molecular and cellular targets for therapeutic development.

METHODS

Here, we integrated analyzed 4,441 differentially expressed genes (DEGs) that were identified from 263,370 single-cells in cortex samples by single-nucleus RNA sequencing (snRNA-seq) between 42 AD-pathology subjects and 39 normal controls within 3 studies. DEGs were analyzed in microglia, astrocytes, oligodendrocytes, excitatory neurons, inhibitory neurons, and endothelial cells, respectively. In each cell type, we identified both common DEGs which were observed in all 3 studies, and overlapping DEGs which have been seen in at least 2 studies. Firstly, we showed the common DEGs expression and explained the biological functions by comparing with existing literature or multil-omics signaling pathways knowledgebase. We then determined the significant modules and hub genes, and explored the biological processes using the overlapping DEGs. Finally, we identified the common and distinct dysregulated pathways using overall DEGs and overlapping DEGs in a cell type-specific manner.

RESULTS

Up-regulated LINGO1 has been seen in both oligodendrocytes and excitatory neurons across 3 studies. Interestingly, genes enriched in the mitochondrial module were up-regulated across all cell types, which indicates mitochondrial dysfunction in the AD brain. The estrogen signaling pathway seems to be the most common pathway that is disrupted in AD.

CONCLUSION

Together, these analyses provide detailed information of cell type-specific and overall transcriptional changes and pathways underlying the human AD-pathology. These findings may provide important insights for drug development to tackle this disease.

Atrophy of Basal Forebrain Initiates with Tau Pathology in Individuals at Risk for Alzheimer's Disease

Evidence suggests that the basal forebrain (BF) cholinergic system degenerates early in the course of Alzheimer's disease (AD), likely due to the vulnerability of BF cholinergic neurons to tau pathology. However, it remains unclear whether the presence of tauopathy is the only requirement for initiating the BF degeneration in asymptomatic subjects at risk for AD (AR-AD), and how BF structural deficits evolve from normal aging to preclinical and prodromal AD. Here, we provide human in vivo magnetic resonance imaging evidence supporting that abnormal cerebrospinal fluid levels of phosphorylated tau (T+) are selectively associated with bilateral volume loss of the nucleus basalis of Meynert (nbM, Ch4) in AR-AD individuals. Spreading of atrophy to medial septum and vertical limb of diagonal band Broca (Ch1-Ch2) occurred in both preclinical and prodromal AD. With the exception of A+, all groups revealed significant correlations between volume reduction of BF cholinergic compartments and atrophy of their innervated regions. Overall, these results support the central role played by tauopathy in instigating the nbM degeneration in AR-AD individuals and the necessary coexistence of both AD proteinopathies for spreading damage to larger BF territories, thus affecting the core of the BF cholinergic projection system.

Progressive Brain Degeneration From Subjective Cognitive Decline to Amnestic Mild Cognitive Impairment: Evidence From Large-Scale Anatomical Connection Classification Analysis

People with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are both at high risk for Alzheimer’s disease (AD). Behaviorally, both SCD and aMCI have subjective reports of cognitive decline, but the latter suffers a more severe objective cognitive impairment than the former. However, it remains unclear how the brain develops from SCD to aMCI. In the current study, we aimed to investigate the topological characteristics of the white matter (WM) network that can successfully identify individuals with SCD or aMCI from healthy control (HC) and to describe the relationship of pathological changes between these two stages. To this end, three groups were recruited, including 22 SCD, 22 aMCI, and 22 healthy control (HC) subjects. We constructed WM network for each subject and compared large-scale topological organization between groups at both network and nodal levels. At the network level, the combined network indexes had the best performance in discriminating aMCI from HC. However, no indexes at the network level can significantly identify SCD from HC. These results suggested that aMCI but not SCD was associated with anatomical impairments at the network level. At the nodal level, we found that the short-path length can best differentiate between aMCI and HC subjects, whereas the global efficiency has the best performance in differentiating between SCD and HC subjects, suggesting that both SCD and aMCI had significant functional integration alteration compared to HC subjects. These results converged on the idea that the neural degeneration from SCD to aMCI follows a gradual process, from abnormalities at the nodal level to those at both nodal and network levels.

Interactions Between Aging and Alzheimer's Disease on Structural Brain Networks

Normative aging and Alzheimer's disease (AD) propagation alter anatomical connections among brain parcels. However, the interaction between the trajectories of age- and AD-linked alterations in the topology of the structural brain network is not well understood. In this study, diffusion-weighted magnetic resonance imaging (MRI) datasets of 139 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were used to document their structural brain networks. The 139 participants consist of 45 normal controls (NCs), 37 with early mild cognitive impairment (EMCI), 27 with late mild cognitive impairment (LMCI), and 30 AD patients. All subjects were further divided into three subgroups based on their age (56-65, 66-75, and 71-85 years). After the structural connectivity networks were built using anatomically-constrained deterministic tractography, their global and nodal topological properties were estimated, including network efficiency, characteristic path length, transitivity, modularity coefficient, clustering coefficient, and betweenness. Statistical analyses were then performed on these metrics using linear regression, and one- and two-way ANOVA testing to examine group differences and interactions between aging and AD propagation. No significant interactions were found between aging and AD propagation in the global topological metrics (network efficiency, characteristic path length, transitivity, and modularity coefficient). However, nodal metrics (clustering coefficient and betweenness centrality) of some cortical parcels exhibited significant interactions between aging and AD propagation, with affected parcels including left superior temporal, right pars triangularis, and right precentral. The results collectively confirm the age-related deterioration of structural networks in MCI and AD patients, providing novel insight into the cross effects of aging and AD disorder on brain structural networks. Some early symptoms of AD may also be due to age-associated anatomic vulnerability interacting with early anatomic changes associated with AD.

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.

Disrupted White Matter Networks from Subjective Memory Impairment to Amnestic Mild Cognitive Impairment

BACKGROUND AND OBJECTIVE

Subjective memory impairment (SMI) is a preclinical stage prior to amnestic mild cognitive impairment (aMCI) along with the Alzheimer's disease (AD) continuum. We hypothesized that SMI patients had white matter (WM) network disruptions similar to those in aMCI patients.

METHODS

We used diffusion-tensor magnetic resonance imaging and graph theory to construct, analyze, and compare the WM networks among 20 normal controls (NC), 20 SMI patients, and 20 aMCI patients.

RESULTS

Compared with the NC group, the SMI group had significantly decreased global and local efficiency and an increased shortest path length. Moreover, similar to the aMCI group, the SMI group had lower nodal efficiency in regions located in the frontal and parietal lobes, limbic systems, and caudate nucleus compared to that of the NC group.

CONCLUSION

Similar to aMCI patient, SMI patients exhibited WM network disruptions, and detection of these disruptions could facilitate the early detection of SMI.

Diffusion Tensor Imaging Tractography of White Matter Tracts in the Equine Brain

Tractography, a noninvasive technique tracing brain pathways from diffusion tensor magnetic resonance imaging (DTI) data, is increasingly being used for brain investigation of domestic mammals. In the equine species, such a technique could be useful to improve our knowledge about structural connectivity or to assess structural changes of white matter tracts potentially associated with neurodegenerative diseases. The goals of the present study were to establish the feasibility of DTI tractography in the equine brain and to provide a morphologic description of the most representative tracts in this species. Postmortem DTI and susceptibility-weighted imaging (SWI) of an equine brain were acquired with a 3-T system using a head coil. Association, commissural, and projection fibers, the three fiber groups typically investigated in tractography studies, were successfully reconstructed and overlaid on SWI or fractional anisotropy maps. The fibers derived from DTI correlate well with their description in anatomical textbooks. Our results demonstrate the feasibility of using postmortem DTI data to reconstruct the main white matter tracts of the equine brain. Further DTI acquisitions and corresponding dissections of equine brains will be necessary to validate these findings and create an equine stereotaxic white matter atlas that could be used in future neuroimaging research.

Tau pathology in early Alzheimer's disease is linked to selective disruptions in neurophysiological network dynamics

Understanding the role of Tau protein aggregation in the pathogenesis of Alzheimer's disease is critical for the development of new Tau-based therapeutic strategies to slow or prevent dementia. We tested the hypothesis that Tau pathology is associated with functional organization of widespread neurophysiological networks. We used electro-magnetoencephalography with [¹⁸F]AV-1451 PET scanning to quantify Tau-dependent network changes. Using a graph theoretical approach to brain connectivity, we quantified nodal measures of functional segregation, centrality, and the efficiency of information transfer and tested them against levels of [¹⁸F]AV-1451. Higher Tau burden in early Alzheimer's disease was associated with a shift away from the optimal small-world organization and a more fragmented network in the beta and gamma bands, whereby parieto-occipital areas were disconnected from the anterior parts of the network. Similarly, higher Tau burden was associated with decreases in both local and global efficiency, especially in the gamma band. The results support the translational development of neurophysiological "signatures" of Alzheimer's disease, to understand disease mechanisms in humans and facilitate experimental medicine studies.

Disruption of oligodendrocyte progenitor cells is an early sign of pathology in the triple transgenic mouse model of Alzheimer's disease

There is increasing evidence that myelin disruption is related to cognitive decline in Alzheimer's disease (AD). In the CNS, myelin is produced by oligodendrocytes, which are generated throughout life by adult oligodendrocyte progenitor cells (OPCs), also known as NG2-glia. To address whether alterations in myelination are related to age-dependent changes in OPCs, we analyzed NG2 and myelin basic protein (MBP) immunolabelling in the hippocampus of 3×Tg-AD mice at 6 and 24 months of age, compared with non-Tg age-matched controls. There was an age-related decrease in MBP immunostaining and OPC density, together with a decline in the number of OPC sister cells, a measure of OPC replication. Notably, the loss of myelin and OPC sister cells occurred earlier at 6 months in 3xTg-AD, suggesting accelerated aging, although there was not a concomitant decline in OPC numbers at this age, suggesting the observed changes in myelin were not a consequence of replicative exhaustion, but possibly of OPC disruption or senescence. In line with this, a key finding is that compared to age-match controls, OPC displayed marked morphological atrophy at 6 months in 3xTg-AD followed by morphological hypertrophy at 24 months, as deduced from significant changes in total cell surface area, total cell volume, somata volume and branching of main processes. Moreover, we show that hypertrophic OPCs surround and infiltrate amyloid-β (Aβ) plaques, a key pathological hallmark of AD. The results indicate that OPCs undergo complex age-related remodeling in the hippocampus of the 3xTg-AD mouse model. We conclude that OPC disruption is an early pathological sign in AD and is a potential factor in accelerated myelin loss and cognitive decline.

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Life-long generation of myelin is the function of adult oligodendrocyte progenitor cells (OPCs).

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Age-related loss of myelin is accelerated in the 3xTg-AD mouse model of Alzheimer's disease (AD).

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OPCs are disrupted at an early stage of 3xTg-AD.

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Dysregulation of OPC and myelin loss are important biomarkers for AD-like pathology.

Assessment of a Cognitive-Motor Training Program in Adults at Risk for Developing Dementia

Background

With the prevalence of dementia increasing each year, pre-clinically implemented therapeutic interventions are needed. It has been suggested that cascading neural network failures may bring on behavioural deficits associated with Alzheimer’s disease.

Methods

Previously we have shown that cognitive-motor integration (CMI) training in adults with cognitive impairments generalized to improved global cognitive and activities of daily living scores. Here we employ a novel movement control–based training approach involving CMI rather than traditional cognition-only brain training. We hypothesized that such training would stimulate widespread neural networks and enhance rule-based visuomotor ability in at-risk individuals.

Results

We observed a significant improvement in bimanual coordination in the at-risk training group. We also observed significant decreases in movement variability for the most complex CMI condition in the at-risk and healthy training groups.

Conclusions

These data suggest that integrating cognition into action in a training intervention may be effective at strengthening vulnerable brain networks in asymptomatic adults at risk for developing dementia.

Connectivity and morphology of hubs of the cerebral structural connectome are associated with brain resilience in AD- and age-related pathology

The physiological basis of resilience to age-associated and AD-typical neurodegenerative pathology is still not well understood. So far, the established resilience factor intelligence has been shown to be associated with white matter network global efficiency, a key constituent of which are highly connected hubs. However, hub properties have also been shown to be impaired in AD. Individual predisposition or vulnerability of hub properties may thus modulate the impact of pathology on cognitive outcome and form part of the physiological basis of resilience. 85 cognitively normal elderly subjects and patients with MCI with DWI, MRI and AV45-PET scans were included from ADNI. We reconstructed the global WM networks in each subject and characterized hub-properties of GM regions using graph theory by calculating regional betweenness centrality. Subsequently, we investigated whether regional GM volume (GMV) and structural WM connectivity (WMC) of more hub-like regions was more associated with resilience, quantified as cognitive performance independent of amyloid burden, tau and WM lesions. Subjects with higher resilience showed higher increased regional GMV and WMC in more hub-like compared to less hub-like GM-regions. Additionally, this association was in some instances further increased at elevated amounts of brain pathology. Higher GMV and WMC of more hub-like regions may contribute more to resilience compared to less hub-like regions, reflecting their increased importance to brain network efficiency, and may thus form part of the neurophysiological basis of resilience. Future studies should investigate the factors leading to higher GMV and WMC of hubs in non-demented elderly with higher resilience.

Genetic risk for Alzheimer disease in children: Evidence from early-life IQ and brain white-matter microstructure

It remains unclear whether the genetic risk for late‐onset Alzheimer disease (AD) is linked to premorbid individual differences in general cognitive ability and brain structure. The objective of the present study was to determine whether the genetic risk of late‐onset AD is related to premorbid individual differences in intelligence quotient (IQ) and characteristics of the cerebral white‐matter in children. The study sample included children of the Generation R Study from Rotterdam, The Netherlands. IQ was measured using a well‐validated Dutch nonverbal IQ test (n = 1908) at ages 5 to 9 years. White‐matter microstructure was assessed by measuring fractional anisotropy (FA) of white‐matter tracts using diffusion tensor imaging (DTI) (n = 919) at ages 9 to 12 years. Genetic risk was quantified using three biologically defined genetic risk scores (GRSs) hypothesized to be related to the pathophysiology of late‐onset AD: immune response, cholesterol/lipid metabolism and endocytosis. Higher genetic risk for late‐onset AD that included genes associated with immune responsivity had a negative influence on cognition and cerebral white‐matter microstructure. For each unit increase in the immune response GRS, IQ decreased by 0.259 SD (95% CI [−0.500, −0.017]). For each unit increase in the immune response GRS, global FA decreased by 0.373 SD (95% CI [−0.721, −0.026]). Neither cholesterol/lipid metabolism nor endocytosis GRSs were associated with IQ or cerebral white‐matter microstructure. Our findings suggest that elevated genetic risk for late‐onset AD may in part be manifest during childhood neurodevelopment through alterations in immune responsivity.

Graph theoretical quantification of white matter reorganization after cortical stroke in mice

Stroke is a devastating disease leading to cell death and disconnection between neurons both locally and remote, often resulting in severe long-term disability. Spontaneous reorganization of areas and pathways not primarily affected by ischemia is, however, associated with albeit limited recovery of function. Quantitative mapping of whole-brain changes of structural connectivity concerning the ischemia-induced sensorimotor deficit and recovery thereof would help to target structural plasticity in order to improve rehabilitation. Currently, only in vivo diffusion MRI can extract the structural whole-brain connectome noninvasively. This approach is, however, used primarily in human studies. Here, we applied atlas-based MRI analysis and graph theory to DTI in wild-type mice with cortical stroke lesions. Using a DTI network approach and graph theory, we aimed at gaining insights into the dynamics of the spontaneous reorganization after stroke related to the recovery of function. We found evidence for altered structural integrity of connections of specific brain regions, including the breakdown of connections between brain regions directly affected by stroke as well as long-range rerouting of intra- and transhemispheric connections related to improved sensorimotor behavior.

Brain connectivity during Alzheimer's disease progression and its cognitive impact in a transgenic rat model

The research of Alzheimer's disease (AD) in its early stages and its progression till symptomatic onset is essential to understand the pathology and investigate new treatments. Animal models provide a helpful approach to this research, since they allow for controlled follow-up during the disease evolution. In this work, transgenic TgF344-AD rats were longitudinally evaluated starting at 6 months of age. Every 3 months, cognitive abilities were assessed by a memory-related task and magnetic resonance imaging (MRI) was acquired. Structural and functional brain networks were estimated and characterized by graph metrics to identify differences between the groups in connectivity, its evolution with age, and its influence on cognition. Structural networks of transgenic animals were altered since the earliest stage. Likewise, aging significantly affected network metrics in TgF344-AD, but not in the control group. In addition, while the structural brain network influenced cognitive outcome in transgenic animals, functional network impacted how control subjects performed. TgF344-AD brain network alterations were present from very early stages, difficult to identify in clinical research. Likewise, the characterization of aging in these animals, involving structural network reorganization and its effects on cognition, opens a window to evaluate new treatments for the disease.

Abnormal Anatomical Rich-Club Organization and Structural-Functional Coupling in Mild Cognitive Impairment and Alzheimer's Disease

Emerging research indicates interruptions in the wiring organization of the brain network in Mild cognitive impairment (MCI) and Alzheimer's disease (AD). Due to the important role of rich-club organization in distinguishing abnormalities of AD patients and the close relationship between structural connectivity (SC) and functional connectivity (FC), our study examined whether changes in SC-FC coupling and the relationship with abnormal rich-club organizations during the development of diseases may contribute to the pathophysiology of AD. Structural diffusion-tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) were performed in 38 normal controls (NCs), 40 MCI patients and 19 AD patients. Measures of the rich-club structure and its role in global structural-functional coupling were administered. Our study found decreased levels of feeder and local connectivity in MCI and AD patients, which were the main contributing factors to the lower efficiency of the brain structural network. Another important finding was that we have more accurately characterized the changing pattern of functional brain dynamics. The enhanced coupling between SC and FC in MCI and AD patients might be due to disruptions in optimal structural organization. More interestingly, we also found increases in the SC-FC coupling for feeder and local connections in MCI and AD patients. SC-FC coupling also showed significant differences between MCI and AD patients, mainly between the abnormal feeder connections. The connection density and coupling strength were significantly correlated with clinical metrics in patients. The present findings enhanced our understanding of the neurophysiologic mechanisms associated with MCI and AD.

Identifying Vulnerable Brain Networks in Mouse Models of Genetic Risk Factors for Late Onset Alzheimer's Disease

The major genetic risk for late onset Alzheimer’s disease has been associated with the presence of APOE4 alleles. However, the impact of different APOE alleles on the brain aging trajectory, and how they interact with the brain local environment in a sex specific manner is not entirely clear. We sought to identify vulnerable brain circuits in novel mouse models with homozygous targeted replacement of the mouse ApoE gene with either human APOE3 or APOE4 gene alleles. These genes are expressed in mice that also model the human immune response to age and disease-associated challenges by expressing the human NOS2 gene in place of the mouse mNos2 gene. These mice had impaired learning and memory when assessed with the Morris water maze (MWM) and novel object recognition (NOR) tests. Ex vivo MRI-DTI analyses revealed global and local atrophy, and areas of reduced fractional anisotropy (FA). Using tensor network principal component analyses for structural connectomes, we inferred the pairwise connections which best separate APOE4 from APOE3 carriers. These involved primarily interhemispheric connections among regions of olfactory areas, the hippocampus, and the cerebellum. Our results also suggest that pairwise connections may be subdivided and clustered spatially to reveal local changes on a finer scale. These analyses revealed not just genotype, but also sex specific differences. Identifying vulnerable networks may provide targets for interventions, and a means to stratify patients.

Oligodendrocytes in Development, Myelin Generation and Beyond

Oligodendrocytes are the myelinating cells of the central nervous system (CNS) that are generated from oligodendrocyte progenitor cells (OPC). OPC are distributed throughout the CNS and represent a pool of migratory and proliferative adult progenitor cells that can differentiate into oligodendrocytes. The central function of oligodendrocytes is to generate myelin, which is an extended membrane from the cell that wraps tightly around axons. Due to this energy consuming process and the associated high metabolic turnover oligodendrocytes are vulnerable to cytotoxic and excitotoxic factors. Oligodendrocyte pathology is therefore evident in a range of disorders including multiple sclerosis, schizophrenia and Alzheimer’s disease. Deceased oligodendrocytes can be replenished from the adult OPC pool and lost myelin can be regenerated during remyelination, which can prevent axonal degeneration and can restore function. Cell population studies have recently identified novel immunomodulatory functions of oligodendrocytes, the implications of which, e.g., for diseases with primary oligodendrocyte pathology, are not yet clear. Here, we review the journey of oligodendrocytes from the embryonic stage to their role in homeostasis and their fate in disease. We will also discuss the most common models used to study oligodendrocytes and describe newly discovered functions of oligodendrocytes.

Abnormal Structural Brain Connectome in Individuals with Preclinical Alzheimer's Disease

Alzheimer's disease has a long preclinical phase during which amyloid pathology and neurodegeneration accumulate in the brain without producing overt cognitive deficits. It is currently unclear whether these early disease stages are associated with a progressive disruption in the communication between brain regions that subsequently leads to cognitive decline and dementia. In this study we assessed the organization of structural networks in cognitively normal (CN) individuals harboring amyloid pathology (A+N-), neurodegeneration (A-N+), or both (A+N+) from the prospective and longitudinal Swedish BioFINDER study. We combined graph theory with diffusion tensor imaging to investigate integration, segregation, and centrality measures in the brain connectome in the previous groups. At baseline, our findings revealed a disrupted network topology characterized by longer paths, lower efficiency, increased clustering and modularity in CN A-N+ and CN A+N+, but not in CN A+N-. After 2 years, CN A+N+ showed significant abnormalities in all global network measures, whereas CN A-N+ only showed abnormalities in the global efficiency. Network connectivity and organization were associated with memory in CN A+N+ individuals. Altogether, our findings suggest that amyloid pathology is not sufficient to disrupt structural network topology, whereas neurodegeneration is.

Multivariate Analysis of White Matter Structural Networks of Alzheimer's Disease

The connectome-wide association studies exploring association between brain connectome and disease phenotypes have suffered from massive number of comparisons. In this paper, we propose to apply a multivariate distance-based analytic framework on brain white matter (WM) structural networks invaded by Alzheimer's disease (AD). Eighty-three subjects including patients with AD, amnestic mild cognitive impairment (aMCI) and healthy subjects were scanned with dMRI. By constructing WM structural network for each individual, we used both multivariate and traditional univariate statistical models to complimentarily analyze network pattern and fiber strength changes due to AD. WM connections linked with several brain structures were found significantly changed between AD group and normal controls. No significant findings were observed between aMCI group and normal controls. Our results demonstrate the sensitivity of the combined connectome-based analytic framework in detecting abnormalities of structural brain network.

No relationship between fornix and cingulum degradation and within-network decreases in functional connectivity in prodromal Alzheimer's disease

INTRODUCTION

The earliest changes in the brain due to Alzheimer's disease are associated with the neural networks related to memory function. We investigated changes in functional and structural connectivity among regions that support memory function in prodromal Alzheimer's disease, i.e., during the mild cognitive impairment (MCI) stage.

METHODS

Twenty-three older healthy controls and 25 adults with MCI underwent multimodal MRI scanning. Limbic white matter tracts-the fornix, parahippocampal cingulum, retrosplenial cingulum, subgenual cingulum and uncinate fasciculus-were reconstructed in ExploreDTI using constrained spherical deconvolution-based tractography. Using a network-of-interest approach, resting-state functional connectivity time-series correlations among sub-parcellations of the default mode and limbic networks, the hippocampus and the thalamus were calculated in Conn.

ANALYSIS

Controlling for age, education, and gender between group linear regressions of five diffusion-weighted measures and of resting state connectivity measures were performed per hemisphere. FDR-corrections were performed within each class of measures. Correlations of within-network Fisher Z-transformed correlation coefficients and the mean diffusivity per tract were performed. Whole-brain graph theory measures of cluster coefficient and average path length were inspecting using the resting state data.

RESULTS & CONCLUSION

MCI-related changes in white matter structure were found in the fornix, left parahippocampal cingulum, left retrosplenial cingulum and left subgenual cingulum. Functional connectivity decreases were observed in the MCI group within the DMN-a sub-network, between the hippocampus and sub-areas -a and -c of the DMN, between DMN-c and DMN-a, and, in the right hemisphere only between DMN-c and both the thalamus and limbic-a. No relationships between white matter tract 'integrity' (mean diffusivity) and within sub-network functional connectivity were found. Graph theory revealed that changes in the MCI group was mostly restricted to diminished between-neighbour connections of the hippocampi and of nodes within DMN-a and DMN-b.

Early Detection and Treatment of Patients with Alzheimer's Disease: Future Perspectives

Alzheimer's disease affects approximately 6% of people over the age of 65 years. It is characterized as chronic degeneration of cortical neurons, with loss of memory, cognition and executive functions. As the disease progresses, it is accompanied by accumulation of amyloid plaques and neurofibrillary tangles in key areas of the brain, leading to a loss of neurogenesis and synaptic plasticity in the hippocampus, along with changes in the levels of essential neurotransmitters such as acetylcholine and glutamate. Individuals with concomitant diseases such as depression, diabetes and cardiovascular disorders have a higher risk of developing Alzheimer's disease, and those who have a healthier diet and partake in regular exercise and intellectual stimulation have a lower risk of developing the disorder. This chapter describes the advances made in early diagnosis of Alzheimer's disease as this could help to improve outcomes for the patients by facilitating earlier treatment.

White Matter Correlates of Cognitive Performance on the UCSF Brain Health Assessment

OBJECTIVE

White matter (WM) microstructural changes are increasingly recognized as a mechanism of age-related cognitive differences. This study examined the associations between patterns of WM microstructure and cognitive performance on the University of California, San Francisco (UCSF) Brain Health Assessment (BHA) subtests of memory (Favorites), executive functions and speed (Match), and visuospatial skills (Line Orientation) within a sample of older adults.

METHOD

Fractional anisotropy (FA) in WM tracts and BHA performance were examined in 84 older adults diagnosed as neurologically healthy (47), with mild cognitive impairment (19), or with dementia (18). The relationships between FA and subtest performances were evaluated using regression analyses. We then explored whether regional WM predicted performance after accounting for variance explained by global FA.

RESULTS

Memory performance was associated with FA of the fornix and the superior cerebellar peduncle; and executive functions and speed, with the body of the corpus callosum. The fornix-memory association and the corpus callosum-executive association remained significant after accounting for global FA. Neither tract-based nor global FA was associated with visuospatial performance.

CONCLUSIONS

Memory and executive functions are associated with different patterns of WM diffusivity. Findings add insight into WM alterations underlying age- and disease-related cognitive decline.

Communicability Characterization of Structural DWI Subcortical Networks in Alzheimer's Disease

In this paper, we investigate the connectivity alterations of the subcortical brain network due to Alzheimer’s disease (AD). Mostly, the literature investigated AD connectivity abnormalities at the whole brain level or at the cortex level, while very few studies focused on the sub-network composed only by the subcortical regions, especially using diffusion-weighted imaging (DWI) data. In this work, we examine a mixed cohort including 46 healthy controls (HC) and 40 AD patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data set. We reconstruct the brain connectome through the use of state of the art tractography algorithms and we propose a method based on graph communicability to enhance the information content of subcortical brain regions in discriminating AD. We develop a classification framework, achieving 77% of area under the receiver operating characteristic (ROC) curve in the binary discrimination AD vs. HC only using a 12×12 subcortical features matrix. We find some interesting AD-related connectivity patterns highlighting that subcortical regions tend to increase their communicability through cortical regions to compensate the physical connectivity reduction between them due to AD. This study also suggests that AD connectivity alterations mostly regard the inter-connectivity between subcortical and cortical regions rather than the intra-subcortical connectivity.

The Influence of Genetic Factors and Cognitive Reserve on Structural and Functional Resting-State Brain Networks in Aging and Alzheimer's Disease

Magnetic resonance imaging (MRI) offers significant insight into the complex organization of neural networks within the human brain. Using resting-state functional MRI data, topological maps can be created to visualize changes in brain activity, as well as to represent and assess the structural and functional connections between different brain regions. Crucially, Alzheimer's disease (AD) is associated with progressive loss in this connectivity, which is particularly evident within the default mode network. In this paper, we review the recent literature on how factors that are associated with risk of dementia may influence the organization of the brain network structures. In particular, we focus on cognitive reserve and the common genetic polymorphisms of APOE and BDNF Val66Met.

Identifying Brain Connectivity Using Network-Based Statistics in Amnestic Mild Cognitive Impairment Stratified by β-Amyloid Positivity

BACKGROUND

The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by β amyloid (Aβ) status and compare them using network-based statistics (NBS).

METHODS

Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [18F]-Florbetaben amyloid positron emission tomography. We performed the NBS analysis to compare the whole-brain white matter structural networks extracted from diffusion tensor images.

RESULTS

One hundred sixteen participants (Aβ- cognitively normal [CN], n = 35; Aβ- aMCI, n = 42; Aβ+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between Aβ+ aMCI and Aβ- aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, Aβ+ aMCI showed reduced connectivity mainly in the medial frontal regions, while Aβ- aMCI showed somewhat uniform disruption when compared to CN.

CONCLUSION

Structural network analysis using network-based approach in aMCI may shed light on further understanding of white matter disruption in the prodromal stage of Alzheimer's disease.

Connectome-wide network analysis of white matter connectivity in Alzheimer's disease

A multivariate analytical strategy may pinpoint the structural connectivity patterns associated with Alzheimer's disease (AD) pathology in connectome-wide association studies. Diffusion magnetic resonance imaging data from 161 participants including subjects with healthy controls, AD, stable and converting mild cognitive impairment, were selected for group-wise comparisons. A multivariate distance matrix regression (MDMR) analysis was performed to detect abnormality in brain structural network along with disease progression. Based on the seed regions returned by the MDMR analysis, supervised learning was applied to evaluate the disease predictive performance. Nine brain regions, including the left orbital part of superior and middle frontal gyrus, the bilateral supplementary motor area, the bilateral insula, the left hippocampus, the left putamen, and the left thalamus demonstrated extremely significant structural pattern changes along with the progression of AD. The disease classification was more efficient when based on the key connectivity related to these seed regions than when based on whole-brain structural connectivity. MDMR analysis reveals brain network reorganization caused by AD pathology. The key structural connectivity detected in this study exhibits promising distinguishing capability to predict prodromal AD patients.