Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease

Increased extra-neurite conductivity of brain in patients with Alzheimer's disease: A pilot study

The objectives of this study were to investigate how the extra-neurite conductivity (EC) and intra-neurite conductivity (IC) were reflected in Alzheimer's disease (AD) patients compared with old cognitively normal (CN) people and patients with amnestic mild cognitive impairment (MCI) and to evaluate the association between those conductivity values and cognitive decline. To do this, high-frequency conductivity (HFC) at the Larmor frequency was obtained using MRI-based electrical property tomography (MREPT) and was decomposed into EC and IC using information of multi-shell multi-gradient direction diffusion tensor images. This prospective single-center study included 20 patients with mild or moderate AD, 25 patients with amnestic MCI, and 21 old CN participants. After decomposing EC and IC from HFC for all participants, we performed voxel-based and regions-of-interest analyses to compare conductivity between the three participant groups and to evaluate the association with either age or the Mini-Mental State Examination (MMSE) scores. We found increased EC in AD compared to CN and MCI. EC was significantly negatively associated with MMSE scores in the insula, and middle temporal gyrus. EC might be used as an imaging biomarker for helping to monitor cognitive function.

Influences of amyloid-β and tau on white matter neurite alterations in dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer's disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models. We evaluated the associations of tau and amyloid-β with DTI and NODDI parameters and examined the correlations of AD-related white matter injury with Clinical Dementia Rating (CDR). Structural equation models (SEM) explored relationships among age, APOE ε4, amyloid-β, tau, and white matter injury. The DLB spectrum group exhibited widespread white matter abnormalities, including reduced fractional anisotropy, increased mean diffusivity, and decreased neurite density index. Tau was significantly associated with limbic and temporal white matter injury, which was, in turn, associated with worse CDR. SEM revealed that amyloid-β exerted indirect effects on white matter injury through tau. We observed widespread disruptions in white matter tracts in DLB that were not attributed to AD pathologies, likely due to α-synuclein-related injury. However, a fraction of the white matter injury could be attributed to AD pathology. Our findings underscore the impact of AD pathology on white matter integrity in DLB and highlight the utility of NODDI in elucidating the biological basis of white matter injury in DLB.

White matter integrity is associated with cognition and amyloid burden in older adult Koreans along the Alzheimer's disease continuum

BACKGROUND

White matter (WM) microstructural changes in the hippocampal cingulum bundle (CBH) in Alzheimer's disease (AD) have been described in cohorts of largely European ancestry but are lacking in other populations.

METHODS

We assessed the relationship between CBH WM integrity and cognition or amyloid burden in 505 Korean older adults aged ≥ 55 years, including 276 cognitively normal older adults (CN), 142 with mild cognitive impairment (MCI), and 87 AD patients, recruited as part of the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's disease (KBASE) at Seoul National University.

RESULTS

Compared to CN, AD and MCI subjects showed significantly higher RD, MD, and AxD values (all p-values < 0.001) and significantly lower FA values (left p ≤ 0.002, right p ≤ 0.015) after Bonferroni adjustment for multiple comparisons. Most tests of cognition and mood (p < 0.001) as well as higher medial temporal amyloid burden (p < 0.001) were associated with poorer WM integrity in the CBH after Bonferroni adjustment.

CONCLUSION

These findings are consistent with patterns of WM microstructural damage previously reported in non-Hispanic White (NHW) MCI/AD cohorts, reinforcing existing evidence from predominantly NHW cohort studies.

The Latest Advances in the Diagnosis and Treatment of Dementia

Dementia is a debilitating neurological condition that is characterized by persistent cognitive decline. It is a global health challenge, with a rapidly increasing prevalence due to an increasing aging population. Although definitive diagnosis of various conditions of dementia is only possible by autopsy, clinical diagnosis can be performed by a specialist. The diagnostic process has evolved with recent breakthroughs in diagnostic tools, such as advanced imaging techniques and biomarkers. These tools facilitate early and accurate identification of the condition. Early diagnosis is vital, as it enables timely interventions to improve the quality of life for affected individuals. Treatment strategies for dementia encompass both pharmacological and non-pharmacological approaches. Non-pharmacological treatments include cognitive training and lifestyle modifications. Among pharmacological treatments, acetyl-cholinesterase inhibitors including donepezil, rivastigmine, and galantamine can be used in various doses based on the severity of the disease. Apart from these, N-methyl-D-aspartate receptor antagonists such as memantine can also be used. Furthermore, personalized treatments have also gained significant attention in dementia treatment. Interdisciplinary care, involving healthcare professionals, social workers, and support networks, is crucial for comprehensive and holistic dementia management.

Degeneration of cholinergic white matter pathways and nucleus basalis of Meynert in individuals with objective subtle cognitive impairment

We evaluated alterations in the nucleus basalis of Meynert (NBM) volume and integrity of cholinergic white matter pathways in objective subtle cognitive impairment (Obj-SCI) individuals. NBM segmentation and cholinergic pathways tracking were conducted at baseline, 12-, 24-, and 48-month follow-ups in 41 Obj-SCI individuals and 61 healthy controls (HC). The baseline and 4-year rate of change in NBM volume and cholinergic pathways mean diffusivity were compared. Associations between cholinergic index changes and pathological processes and cognitive performance were evaluated. After controlling for age, sex, APOE genotype, and total intracranial volume, Obj-SCI individuals exhibited reduced NBM volume and increased medial pathway mean diffusivity compared to HC at baseline. Furthermore, amyloid-positive Obj-SCI individuals exhibited a steeper longitudinal decline in NBM volume than HC. Additionally, decreases in NBM volume and cholinergic pathways integrity were associated with amyloid and vascular pathologies and cognitive decline. Overall, degeneration of the cholinergic system plays an important role in cognitive impairment during the preclinical stage of Alzheimer's disease, which may provide a significant target for early therapeutic interventions.

Diffusion tensor and kurtosis imaging reveal microstructural changes in the trigeminal nerves of patients with trigeminal neuralgia

OBJECTIVES

To evaluate the use of diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) for detection of microstructural changes in the trigeminal nerves of trigeminal neuralgia (TN) patients.

METHODS

Forty TN patients and 40 healthy controls were examined using 3 T magnetic resonance imaging (MRI) to evaluate DTI and DKI parameters in trigeminal nerves. One-way ANOVA was used to test the differences in age, sex, and DTI and DKI parameters between the TN-affected sides, TN-unaffected sides, and controls. For parameters with inter-group differences, pairwise comparisons were performed. Then, the difference ratios (DRs) of the parameters with statistical differences were calculated and used for the receiver operating characteristic (ROC) analysis to assess their diagnostic performance. In addition, for the DTI and DKI parameter values with differences, we used pure DTI and DKI values to perform the ROC analysis.

RESULTS

Compared to the unaffected sides and controls, the FA, MK, and Kr of the affected sides of TN patients were significantly reduced, while ADC was significantly increased (p < 0.05). The diagnostic efficiency of the FA DRs (AUC: 0.974; cutoff value: 0.038; sensitivity: 100%; specificity: 95.0%) was the highest among all DTI and DKI parameters. The DRs of FA and MK more efficiently diagnosed TN than pure FA and MK values.

CONCLUSIONS

DTI and DKI allowed detection of microstructural changes in TN-affected trigeminal nerves. FA DR was the best independent predictor of microstructural changes in TN.

CLINICAL RELEVANCE STATEMENT

Both DTI and DKI can be used for noninvasive quantitative evaluation of the changes in the microstructure of the cisternal segment of the cranial nerves in clinical practice.

KEY POINTS

• Diffusion tensor imaging (DTI) can be used to evaluate the in vivo integrity of white matter and nerve fiber pathway. • Diffusion kurtosis imaging (DKI) has been shown to be considerable sensitive to microstructural changes. • DTI combined with DKI can comprehensively evaluate the status of the TN-affected trigeminal nerve.

Aerobic exercise attenuates abnormal myelination and oligodendrocyte differentiation in 3xTg-AD mice

Pathological features of Alzheimer's Disease (AD) include alterations in the structure and function of neurons as well as of myelin sheaths. Accumulated evidence shows that aerobic type of exercise can enhance neuroplasticity in mouse models of AD. However, whether and how aerobic exercise can affect myelin sheath repair and neuroprotection in the AD models remains unclear. In this study we tested the hypotheses that 1) myelin structural alterations in 3xTg-AD mice would be related to abnormalities in oligodendrocyte lineage cells, resulting in impaired learning and memory, and 2) a 6-month aerobic exercise intervention would have beneficial effects on such alterations. Two-month-old male 3xTg-AD mice were randomly assigned to a control (AC) or an exercise (AE) group, and age-matched male C57BL/6;129 mice were also randomly assigned to a normal control (NC) or an exercise (NE) group, with n = 12 in each group. Mice in the exercise groups were trained on a motor-drive treadmill, 60 min per day, 5 days per week for 6 months. Cognitive function was assessed at the end of the intervention period. Then, brain specimens were obtained for assessments of morphological and oligodendrocyte lineage cell changes. The results of electron microscopy showed that myelin ultrastructure demonstrated a higher percentage of loose and granulated myelin sheath around axons in the temporal lobe in the AC, as compared with the NC group, along with greater cognitive dysfunction at 8-months of age. These differences were accompanied by significantly greater myelin basic protein (MBP) expression and less neuron-glial antigen-2 (NG2) protein and mRNA levels in the AC, compared to the NC. However, there were no significant between-group differences in the G-ratio (the ratio of axon diameter to axon plus myelin sheath diameter) and 2',3'-cyclic-nucleotide 3'-phosphodiesterase (CNPase) protein and mRNA levels. The aerobic exercise ameliorated cognitive deterioration and appeared to keep components of myelin sheath and oligodendrocyte precursor cells stabilized, resulting in a decrease in the percentage of loose and granulated myelin sheath and MBP protein, and an increase in NG2 protein and mRNA levels in the AE group. Therefore, the 6-month exercise intervention demonstrated beneficial effects on myelin lesions, abnormal differentiation of oligodendrocytes and general brain function in the 3xTg-AD mice, providing further insights into the role of aerobic exercise in management of neurodegeneration in AD by maintaining intact myelination.

Functional and structural connectivity in the Papez circuit in different stages of Alzheimer's disease

OBJECTIVE

Alzheimer's disease (AD) is a progressive neurodegenerative continuum with memory impairment. We aimed to examine the detailed functional (FC) and structural connectivity (SC) pattern of the Papez circuit, known as the memory circuit, along the AD.

METHODS

MRI data of 15 patients diagnosed with AD dementia (ADD), 15 patients with the amnestic mild cognitive impairment (MCI), and 15 patients with subjective cognitive impairment were analyzed. The FC analyses were performed between main nodes of the Papez circuit, and the SC was quantified as fractional anisotropy (FA) of the main white matter pathways of the Papez circuit.

RESULTS

The FC between the retrosplenial (RSC) and parahippocampal cortices (PHC) was the earliest affected FC, while a manifest SC change in the ventral cingulum and fornix was observed in the later ADD stage. The RSC-PHC FC and the ventral cingulum FA efficiently predicted the memory performance of the non-demented participants.

CONCLUSIONS

Our findings revealed the importance of the Papez circuit as target regions along the AD.

SIGNIFICANCE

The ventral cingulum connecting the RSC and PHC, a critical overlap area between the Papez circuit and the default mode network, seems to be a target region associated with the earliest objective memory findings in AD.

White matter integrity is associated with cognition and amyloid burden in older adult Koreans along the Alzheimer's disease continuum

BACKGROUND

White matter (WM) microstructural changes in the hippocampal cingulum bundle (CBH) in Alzheimer's disease (AD) have been described in cohorts of largely European ancestry but are lacking in other populations.

METHODS

We assessed the relationship between CBH WM integrity and cognition or amyloid burden in 505 Korean older adults aged ≥55 years, including 276 cognitively normal older adults (CN), 142 mild cognitive impairment (MCI), and 87 AD, recruited as part of the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's disease (KBASE) at Seoul National University.

RESULTS

Compared to CN, AD and MCI subjects showed decreased WM integrity in the bilateral CBH. Cognition, mood, and higher amyloid burden were also associated with poorer WM integrity in the CBH.

CONCLUSION

These findings are consistent with patterns of WM microstructural damage previously reported in non-Hispanic White (NHW) MCI/AD cohorts, reinforcing existing evidence from predominantly NHW cohort studies.

Localized White Matter Tract Integrity Measured by Diffusion Tensor Imaging Is Altered in People with Mild Cognitive Impairment and Associated with Dual-Task and Single-Task Gait Speed

BACKGROUND

Altered white matter (WM) tract integrity may contribute to mild cognitive impairment (MCI) and gait abnormalities.

OBJECTIVE

The purpose of this study was to determine whether diffusion tensor imaging (DTI) metrics were altered in specific portions of WM tracts in people with MCI and to determine whether gait speed variations were associated with the specific DTI metric changes.

METHODS

DTI was acquired in 44 people with MCI and 40 cognitively normal elderly controls (CNCs). Fractional anisotropy (FA) and radial diffusivity (RD) were measured along 18 major brain WM tracts using probabilistic tractography. The average FA and RD along the tracts were compared between the groups using MANCOVA and post-hoc tests. The tracts with FA or RD differences between the groups were examined using an along-tract exploratory analysis to identify locations that differed between the groups. Associations between FA and RD in whole tracts and in the segments of the tracts that differed between the groups and usual/dual-task gait velocities and gross cognition were examined.

RESULTS

Lower FA and higher RD was observed in right cingulum-cingulate gyrus endings (rh.ccg) of the MCI group compared to the CNC group. These changes were localized to the posterior portions of the rh.ccg and correlated with gait velocities.

CONCLUSION

Lower FA and higher RD in the posterior portion of the rh.ccg adjacent to the posterior cingulate suggests decreased microstructural integrity in the MCI group. The correlation of these metrics with gait velocities suggests an important role for this tract in maintaining normal cognitive-motor function.

Diffusion Changes in Hippocampal Cingulum in Early Biologically Defined Alzheimer's Disease

BACKGROUND

Diagnosis of Alzheimer's disease (AD) was recently shifted from clinical to biological construct to reflect underlying neuropathological status, where amyloid deposition designated patients to the Alzheimer's continuum, and additional tau positivity represented AD.

OBJECTIVE

To investigate white matter (WM) alteration in the brain of patients in the Alzheimer's continuum.

METHODS

A total of 236 subjects across the clinical and biological spectra of AD were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding five groups: A-T-cognitively normal (CN), A+T-CN, A+T+ CN, A+T+ mild cognitive impairment, and A+T+ AD. WM alteration was measured by diffusion tensor imaging (DTI). Group differences, correlation of DTI measures with amyloid and tau, and diagnostic performance of such measures were evaluated.

RESULTS

Compared with A-T-CN, widespread WM alteration was observed in the Alzheimer's continuum, including hippocampal cingulum (CGH), cingulum of the cingulate gyrus, and uncinate fasciculus. Diffusion changes measured by regional mean fractional anisotropy (FA) in the bilateral CGH were first detected in the A+T+ CN group and associated with tau burden in the Alzheimer's continuum (p < 0.001). For discrimination between A+T+ CN and A-T-CN groups, CGH FA achieved accuracy, sensitivity, and specificity of 74%, 58%, and 78% for right CGH and 57%, 83%, and 47% respectively for left CGH.

CONCLUSION

WM alteration is widespread in the Alzheimer's continuum. Diffusion alteration in CGH occurred early and was correlated with tau pathology, thus may be a promising biomarker in preclinical AD.

Fornix degeneration in risk factors of Alzheimer's disease, possible trigger of cognitive decline

Risk factors of late-onset Alzheimer's disease (AD) such as aging, type 2 diabetes, obesity, heart failure, and traumatic brain injury can facilitate the appearance of cognitive decline and dementia by triggering cerebrovascular pathology and neuroinflammation. White matter (WM) microstructure and function are especially vulnerable to these conditions. Microstructural WM changes, assessed with diffusion weighted magnetic resonance imaging, can already be detected at preclinical stages of AD, and in the presence of the aforementioned risk factors. Particularly, the limbic system and cortico-cortical association WM tracts, which myelinate late during brain development, degenerate at the earliest stages. The fornix, a C-shaped WM tract that originates from the hippocampus, is one of the limbic tracts that shows early microstructural changes. Fornix integrity is necessary for ensuring an intact executive function and memory performance. Thus, a better understanding of the mechanisms that cause fornix degeneration is critical in the development of therapeutic strategies aiming to prevent cognitive decline in populations at risk. In this literature review, i) we deepen the idea that partial loss of forniceal integrity is an early event in AD, ii) we describe the role that common risk factors of AD can play in the degeneration of the fornix, and iii) we discuss some potential cellular and physiological mechanisms of WM degeneration in the scenario of cerebrovascular disease and inflammation.

Tract-specific differences in white matter microstructure between young adult APOE ε4 carriers and non-carriers: A replication and extension study

The parahippocampal cingulum bundle (PHCB) interconnects regions known to be vulnerable to early Alzheimer's disease (AD) pathology, including posteromedial cortex and medial temporal lobe. While AD-related pathology has been robustly associated with alterations in PHCB microstructure, specifically lower fractional anisotropy (FA) and higher mean diffusivity (MD), emerging evidence indicates that the reverse pattern is evident in younger adults at increased risk of AD. In one such study, Hodgetts et al. (2019) reported that healthy young adult carriers of the apolipoprotein-E (APOE) ε4 allele - the strongest common genetic risk factor for AD - showed higher FA and lower MD in the PHCB but not the inferior longitudinal fasciculus (ILF). These results are consistent with proposals claiming that heightened neural activity and intrinsic connectivity play a significant role in increasing posteromedial cortex vulnerability to amyloid-β and tau spread beyond the medial temporal lobe. Given the implications for understanding AD risk, here we sought to replicate Hodgetts et al.'s finding in a larger sample (N = 128; 40 APOE ε4 carriers, 88 APOE ε4 non-carriers) of young adults (age range = 19-33). Extending this work, we also conducted an exploratory analysis using a more advanced measure of white matter microstructure: hindrance modulated orientational anisotropy (HMOA). Contrary to the original study, we did not observe higher FA or lower MD in the PHCB of APOE ε4 carriers relative to non-carriers. Bayes factors (BFs) further revealed moderate-to-strong evidence in support of these null findings. In addition, we observed no APOE ε4-related differences in PHCB HMOA. Our findings indicate that young adult APOE ε4 carriers and non-carriers do not differ in PHCB microstructure, casting some doubt on the notion that early-life variation in PHCB tract microstructure might enhance vulnerability to amyloid-β accumulation and/or tau spread.

The impact of genetic risk for Alzheimer's disease on the structural brain networks of young adults

Introduction

We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer's disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children.

Methods

Diffusion MRI data were used to perform whole-brain tractography and generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant's genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and (a) the graph theoretical metrics of the structural networks and (b) the rich-club, feeder and local connectivity of the whole-brain networks.

Results

In the visual subnetwork, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.19, p = 1.4 × 10-3), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r = 0.16, p = 5.5 × 10-3), and the mean clustering coefficient was negatively correlated with the tau-protein binding PRS (r = -0.16, p = 0.016). In the default mode network, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.14, p = 0.044). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r = -0.16, p = 0.035; r = -0.15, p = 0.036).

Discussion

We identified small reductions in brain connectivity in young adults at risk of developing Alzheimer's disease in later life.

Dance activity interventions targeting cognitive functioning in older adults with mild cognitive impairment: A meta-analysis

Objectives

To comprehensively determine the effect of dance activities on the cognitive functions and its sub-domains of older adults with mild cognitive impairment (MCI).

Methods

We obtained data from PubMed, Web of Science, EBSCO, China national knowledge infrastructure, Wanfang data, and VIP databases from 2017/01/01 to 2022/03/01. We included trials of older adults with MCI that underwent dance activity intervention and fulfilled the inclusion criteria. Two researchers independently assessed the quality of the study using the Cochrane risk of the bias assessment tool. Meta-analysis was performed when data were available, with further subgroup analysis, using Review Manager 5.4, and sensitivity analysis was performed using Stata software 15.1.

Results

Search terms yielded 183 articles, of which 12 fulfilled the inclusion criteria. This included 7 high-quality studies and 5 medium-quality studies. A total of 820 older adults were analyzed. Results showed that dance activity had beneficial effects for global cognition [SMD_MMSE = 0.65, 95% CI_MMSE (0.20, 1.09), p_MMSE = 0.004; SMD_MoCA = 0.87, 95% CI_MoCA (0.44, 1.29), p_MoCA < 0.0001], memory [SMD = 0.61, 95% CI (0.35, 0.88), p < 0.00001], visuospatial function [SMD = −0.39, 95% CI (−0.60, −0.19), p = 0.0002], cognitive flexibility [SMD = −0.31, 95% CI (−0.52, −0.11), p = 0.003], attention [SMD = 0.34, 95% CI (0.07, 0.61), p = 0.01], and balance [SMD = 1.25, 95% CI (0.06, 2.44), p = 0.04]. Further subgroup analysis showed that open-skill dance activity (OSDA) was more effective in promoting global cognition in older adults with MCI than closed-skill dance activity (CSDA) because of the different stimulation provided by the two types of dance activities in the brain regions of the older adults (p = 0.0002). It could be speculated that dance activity improved cognitive function mainly by affecting the microstructure and function of the cingulate tract, hippocampus, cardiovascular function, and other brain areas of older adults with MCI.

Conclusion

Dance activities can significantly improve global cognition, memory, visuospatial function, cognitive flexibility, attention, and balance in older adults with MCI. However, more trials with rigorous study designs are necessary to provide more concrete evidence in the future.

Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants

Cohort studies report inconsistent associations between body mass index (BMI) and all-cause incident dementia. Furthermore, evidence on fat distribution and body composition measures are scarce and few studies estimated the association between early life adiposity and dementia risk. Here, we included 322,336 participants from UK biobank to investigate the longitudinal association between life course adiposity and risk of all-cause incident dementia and to explore the underlying mechanisms driven by metabolites, inflammatory cells and brain structures. Among the 322,336 individuals (mean (SD) age, 62.24 (5.41) years; 53.9% women) in the study, during a median 8.74 years of follow-up, 5083 all-cause incident dementia events occurred. The risk of dementia was 22% higher with plumper childhood body size (p < 0.001). A strong U-shaped association was observed between adult BMI and dementia. More fat and less fat-free mass distribution on arms were associated with a higher risk of dementia. Interestingly, similar U-shaped associations were found between BMI and four metabolites (i.e., 3-hydroxybutrate, acetone, citrate and polyunsaturated fatty acids), four inflammatory cells (i.e., neutrophil, lymphocyte, monocyte and leukocyte) and abnormalities in brain structure that were also related to dementia. The findings that adiposity is associated with metabolites, inflammatory cells and abnormalities in brain structure that were related to dementia risk might provide clues to underlying biological mechanisms. Interventions to prevent dementia should begin early in life and include not only BMI control but fat distribution and body composition.

Structural Connectivity in Down Syndrome and Alzheimer's Disease

Down syndrome (DS) arises from the triplication of chromosome 21, which leads to an atypical neurodevelopment and the overproduction of the amyloid precursor protein, predisposing to early Alzheimer's disease (AD). Not surprisingly, trisomy 21 is widely considered a model to study predementia stages of AD. After decades, in which neural loss was the main focus, research in AD is now moving toward understanding the neurodegenerative aspects affecting white matter. Motivated by the development of magnetic resonance imaging (MRI)-based diffusion techniques, this shift in focus has led to several exploratory studies on both young and older individuals with DS. In this review, we synthesise the initial efforts made by researchers in characterising in-vivo structural connectivity in DS, together with the AD footprint on top of such pre-existing connectivity related to atypical brain development. The white matter structures found to be affected in DS are the corpus callosum and all the main long-association fibres, namely the inferior fronto-occipital fasciculus, the inferior and superior longitudinal fasciculus, the uncinate fasciculus and the cingulum bundle. Furthermore, the cingulum bundle and the corpus callosum appear to be particularly sensitive to early AD changes in this population. Findings are discussed in terms of their functional significance, alongside methodological considerations and implications for future research.

Long-term structural brain changes in adult rats after mild ischaemic stroke

Preclinical studies of remote degeneration have largely focused on brain changes over the first few days or weeks after stroke. Accumulating evidence suggests that neurodegeneration occurs in other brain regions remote to the site of infarction for months and even years following ischaemic stroke. Brain atrophy appears to be driven by both axonal degeneration and widespread brain inflammation. The evolution and duration of these changes are increasingly being described in human studies, using advanced brain imaging techniques. Here, we sought to investigate long-term structural brain changes in a model of mild focal ischaemic stroke following injection of endothlin-1 in adult Long–Evans rats (n = 14) compared with sham animals (n = 10), over a clinically relevant time-frame of 48 weeks. Serial structural and diffusion-weighted MRI data were used to assess dynamic volume and white matter trajectories. We observed dynamic regional brain volume changes over the 48 weeks, reflecting both normal changes with age in sham animals and neurodegeneration in regions connected to the infarct following ischaemia. Ipsilesional cortical volume loss peaked at 24 weeks but was less prominent at 36 and 48 weeks. We found significantly reduced fractional anisotropy in both ipsi- and contralesional motor cortex and cingulum bundle regions of infarcted rats (P < 0.05) from 4 to 36 weeks, suggesting ongoing white matter degeneration in tracts connected to but distant from the stroke. We conclude that there is evidence of significant cortical atrophy and white matter degeneration up to 48 weeks following infarct, consistent with enduring, pervasive stroke-related degeneration.

Axonal transport impairment and its relationship with diffusion tensor imaging metrics of a murine model of p301L tau induced tauopathy

Diffusion Tensor Imaging (DTI) and Manganese Enhanced MRI (MEMRI) are noninvasive tools to characterize neural fiber microstructure and axonal transport. A combination of both may provide novel insights into the progress of neurodegeneration. To investigate the relationship of DTI and MEMRI in white matter of tauopathy, twelve optic nerves of 11-month-old p301L tau mice were imaged and finished with postmortem immunohistochemistry. MEMRI was used to quantify Mn2+ accumulation rates in the optic nerve (ON, termed ONAR) and the Superior Colliculus (SC, termed SCAR), the primary terminal site of ON in mice. We found that both ONAR and SCAR revealed a significant linear correlation with mean diffusion (mD) and radial diffusion (rD) but not with other DTI quantities. Immunohistochemistry findings showed that ONAR, mD, and rD are significantly correlated with the myelin content (Myelin Basic Protein, p < 0.05) but not with the axonal density (SMI-31), tubulin density, or tau aggregates (AT8 staining). In summary, slower axonal transport appeared to have less myelinated axons and thinner remaining axons, associated with reduced rD and mD of in vivo DTI. A combination of in vivo MEMRI and DTI can provide critical information to delineate the progress of white matter deficits in neurodegenerative diseases.

Deep brain stimulation of fornix for memory improvement in Alzheimer's disease: A critical review

Memory reflects the brain function in encoding, storage and retrieval of the data or information, which is a fundamental ability for any live organism. The development of approaches to improve memory attracts much attention due to the underlying mechanistic insight and therapeutic potential to treat neurodegenerative diseases with memory loss, such as Alzheimer's disease (AD). Deep brain stimulation (DBS), a reversible, adjustable, and non-ablative therapy, has been shown to be safe and effective in many clinical trials for neurodegenerative and neuropsychiatric disorders. Among all potential regions with access to invasive electrodes, fornix is considered as it is the major afferent and efferent connection of the hippocampus known to be closely associated with learning and memory. Indeed, clinical trials have demonstrated that fornix DBS globally improved cognitive function in a subset of patients with AD, indicating fornix can serve as a potential target for neurosurgical intervention in treating memory impairment in AD. The present review aims to provide a better understanding of recent progresses in the application of fornix DBS for ameliorating memory impairments in AD patients.

Automated quantification of brain connectivity in Alzheimer's disease using ClusterMetric

Diffusion magnetic resonance imaging tractography allows investigating brain structural connections in a noninvasive way and has been widely used for understanding neurological disease. Quantification of brain connectivity along with its length by dividing a fiber bundle into multiple segments (node) is a powerful approach to assess biological properties, which is termed as tractometry. However, current tractometry methods face challenges in node identification along with the length of complex bundles whose morphology is difficult to summarize. In addition, the anatomic measure reflecting the macroscopic fiber cross-section has not been followed in previous tractometry. In this paper, we propose an automated fiber bundle quantification, which we refer to as ClusterMetric. The ClusterMetric uses a data-driven approach to identify fiber clusters corresponding to subdivisions of the white matter anatomy and identify consistent space nodes along the length of clusters across individuals. The proposed method is demonstrated by applicating to our collected dataset including 23 Alzheimer's disease (AD) patients and 22 healthy controls (HCs) and a public dataset of ADNI including 53 AD patients and 85 HCs. The altered white matter tracts in AD group are observed using both datasets, which involve several major fiber tracts including the corpus callosum, corona-radiata-frontal, arcuate fasciculus, inferior occipito-frontal fasciculus, uncinate fasciculus, thalamo-frontal, superior longitudinal fasciculus, inferior cerebellar peduncle, cingulum bundle, and extreme capsule. These fiber clusters represent the white matter connections that could be most affected in AD, suggesting the ability of our method in identifying potential abnormalities specific to local regions within a fiber cluster.

Application of High-Frequency Conductivity Map Using MRI to Evaluate It in the Brain of Alzheimer's Disease Patients

Background

The previous studies reported increased concentrations of metallic ions, imbalanced Na+ and K+ ions, and the increased mobility of protons by microstructural disruptions in Alzheimer's disease (AD).

Purpose

(1) to apply a high-frequency conductivity (HFC) mapping technique using a clinical 3T MRI system, (2) compare HFC values in the brains of participants with AD, amnestic mild cognitive impairment (MCI), and cognitively normal (CN) elderly people, (3) evaluate the relationship between HFC values and cognitive decline, and (4) explore usefulness of HFC values as an imaging biomarker to evaluate the differentiation of AD from CN.

Materials and Methods

This prospective study included 74 participants (23 AD patients, 27 amnestic MCI patients, and 24 CN elderly people) to explore the clinical application of HFC mapping in the brain from March 2019 to August 2021. We performed statistical analyses to compare HFC maps between the three participant groups, evaluate the association of HFC maps with Mini-Mental State Examination (MMSE) scores, and to evaluate the differentiation between the participant groups for HFC values for some brain areas.

Results

We obtained a good HFC map non-invasively. The HFC value was higher in the AD group than in the CN and MCI groups. MMSE scores were negatively associated with HFC values. Age was positively associated with HFC values. The HFC value in the insula has a high area under the receiver operating characteristic (ROC) curve (AUC) value to differentiate AD patients from the CN participants (Sensitivity [SE] = 82, Specificity [SP] =97, AUC = 0.902, p < 0.0001), better than gray matter volume (GMV) in hippocampus (SE = 79, SP = 83, AUC = 0.880, p < 0.0001). The classification for differentiating AD from CN was highest by adding the hippocampal GMV to the insular HFC value (SE = 87, SP = 87, AUC = 0.928, p < 0.0001).

Conclusion

High-frequency conductivity values were significantly increased in the AD group compared to the CN group and increased with age and disease severity. HFC values of the insula along with the GMV of the hippocampus can be used as an imaging biomarker to improve the differentiation of AD from CN.

A diagnostic index based on quantitative susceptibility mapping and voxel-based morphometry may improve early diagnosis of Alzheimer's disease

OBJECTIVES

Voxel-based morphometry (VBM) is widely used to quantify the progression of Alzheimer's disease (AD), but improvement is still needed for accurate early diagnosis. We evaluated the feasibility of a novel diagnosis index for early diagnosis of AD based on quantitative susceptibility mapping (QSM) and VBM.

METHODS

Thirty-seven patients with AD, 24 patients with mild cognitive impairment (MCI) due to AD, and 36 cognitively normal (NC) subjects from four centers were included. A hybrid sequence was performed by using 3-T MRI with a 3D multi-echo GRE sequence to obtain both a T1-weighted image for VBM and phase images for QSM. The index was calculated from specific voxels in QSM and VBM images by using a linear support vector machine. The method of voxel extraction was optimized to maximize diagnostic accuracy, and the optimized index was compared with the conventional VBM-based index using receiver operating characteristic analysis.

RESULTS

The index was optimal when voxels were extracted as increased susceptibility (AD > NC) in the parietal lobe and decreased gray matter volume (AD < NC) in the limbic system. The optimized proposed index showed excellent performance for discrimination between AD and NC (AUC = 0.94, p = 1.1 × 10^-10) and good performance for MCI and NC (AUC = 0.87, p = 1.8 × 10^-6), but poor performance for AD and MCI (AUC = 0.68, p = 0.018). Compared with the conventional index, AUCs were improved for all cases, especially for MCI and NC (p < 0.05).

CONCLUSIONS

In this preliminary study, the proposed index based on QSM and VBM improved the diagnostic performance between MCI and NC groups compared with the VBM-based index.

KEY POINTS

• We developed a novel diagnostic index for Alzheimer's disease based on quantitative susceptibility mapping (QSM) and voxel-based morphometry (VBM). • QSM and VBM images can be acquired simultaneously in a single sequence with little increasing scan time. • In this preliminary study, the proposed diagnostic index improved the discriminative performance between mild cognitive impairment and normal control groups compared with the conventional VBM-based index.

Joint independent component analysis for hypothesizing spatiotemporal relationships between longitudinal gray and white matter changes in preclinical Alzheimer's disease

Characterizing relationships between gray matter (GM) and white matter (WM) in early Alzheimer's disease (AD) would improve understanding of how and when AD impacts the brain. However, modeling these relationships across brain regions and longitudinally remains a challenge. Thus, we propose extending joint independent component analysis (jICA) into spatiotemporal modeling of regional cortical thickness and WM bundle volumes leveraging multimodal MRI. We jointly characterize these GM and WM features in a normal aging (n=316) and an age- and sex-matched preclinical AD cohort (n=81) at each of two imaging sessions spaced three years apart, training on the normal aging population in cross-validation and interrogating the preclinical AD cohort. We find this joint model identifies reproducible, longitudinal changes in GM and WM between the two imaging sessions and that these changes are associated with preclinical AD and are plausible considering the literature. We compare this joint model to two focused models: (1) GM features at the first session and WM at the second and (2) vice versa. The joint model identifies components that correlate poorly with those from the focused models, suggesting the different models resolve different patterns. We find the strength of association with preclinical AD is improved in the GM to WM model, which supports the hypothesis that medial temporal and frontal thinning precedes volume loss in the uncinate fasciculus and inferior anterior-posterior association fibers. These results suggest that jICA effectively generates spatiotemporal hypotheses about GM and WM in preclinical AD, especially when specific intermodality relationships are considered a priori.

Age-related differences in white matter microstructure measured by advanced diffusion MRI in healthy older adults at risk for Alzheimer's disease

Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion imaging technique, which can detect more distinct microstructural features compared to conventional Diffusion Tensor Imaging (DTI). NODDI allows the signal to be divided into multiple water compartments and derive measures for orientation dispersion index (ODI), neurite density index (NDI) and volume fraction of isotropic diffusion compartment (FISO). This study aimed to investigate which diffusion metric-fractional anisotropy (FA), mean diffusivity (MD), NDI, ODI, or FISO-is most influenced by aging and reflects cognitive function in a population of healthy older adults at risk for Alzheimer's disease (AD). Age was significantly associated with all but one diffusion parameters and regions of interest. NDI and MD in the cingulate region adjacent to the cingulate cortex showed a significant association with a composite measure of Executive Function and was proven to partially mediate the relationship between aging and Executive Function decline. These results suggest that both DTI and NODDI parameters are sensitive to age-related differences in white matter regions vulnerable to aging, particularly among older adults at risk for AD.

Predicting Attentional Vulnerability to Sleep Deprivation: A Multivariate Pattern Analysis of DTI Data

BACKGROUND

Large individual differences exist in sleep deprivation (SD) induced sustained attention deterioration. Several brain imaging studies have suggested that the activities within frontal-parietal network, cortico-thalamic connections, and inter-hemispheric connectivity might underlie the neural correlates of vulnerability/resistance to SD. However, those traditional approaches are based on average estimates of differences at the group level. Currently, a neuroimaging marker that can reliably predict this vulnerability at the individual level is lacking.

METHODS

Efficient transfer of information relies on the integrity of white matter (WM) tracts in the human brain, we therefore applied machine learning approach to investigate whether the WM diffusion metrics can predict vulnerability to SD. Forty-nine participants completed the psychomotor vigilance task (PVT) both after resting wakefulness (RW) and after 24 h of sleep deprivation (SD). The number of PVT lapse (reaction time > 500 ms) was calculated for both RW condition and SD condition and participants were categorized as vulnerable (24 participants) or resistant (25 participants) to SD according to the change in the number of PVT lapses between the two conditions. Diffusion tensor imaging were acquired to extract four multitype WM features at a regional level: fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) learning approach using leave-one-out cross-validation (LOOCV) was performed to assess the discriminative power of WM features in SD-vulnerable and SD-resistant participants.

RESULTS

LSVM analysis achieved a correct classification rate of 83.67% (sensitivity: 87.50%; specificity: 80.00%; and area under the receiver operating characteristic curve: 0.85) for differentiating SD-vulnerable from SD-resistant participants. WM fiber tracts that contributed most to the classification model were primarily commissural pathways (superior longitudinal fasciculus), projection pathways (posterior corona radiata, anterior limb of internal capsule) and association pathways (body and genu of corpus callosum). Furthermore, we found a significantly negative correlation between changes in PVT lapses and the LSVM decision value.

CONCLUSION

These findings suggest that WM fibers connecting (1) regions within frontal-parietal attention network, (2) the thalamus to the prefrontal cortex, and (3) the left and right hemispheres contributed the most to classification accuracy.

Application of diffusion tensor imaging in Alzheimer’s disease: quantification of white matter microstructural changes

Background

Alzheimer’s disease (AD) is the most common cause of dementia in the aging population, responsible for 60–70% of all demented cases. Diffusion tensor imaging (DTI) is a very recent technique that allows the mapping of white matter (WM) microstructure changes in neurological disorders. The current study was conducted to compare DTI parameters between AD patients and healthy elderly subjects and to determine whether DTI can act as a potential biomarker for AD.

Results

There were significant differences in Modified Mini-Mental State Examination (MMMSE) and Clinical Dementia Rating (CDR) between the two groups. As regards the DTI parameters, significant differences were found between AD patients versus healthy subjects, in the mean diffusivity (MD) of the splenium [(1.05 ± 0.19) vs. (0.92 ± 0.22) , P=0.03], the MD of the right uncinate fasciculus [(0.92 ± 0.04) vs. (0.87 ± 0.05), P= 0.01],  and MD of the right arcuate fasciculus (AF) [(0.83 ± 0.04) vs. (0.79 ± 0.04) P =0.01],  as well as the MD of the right and left inferior fronto-occipital fasiculus (IFOF) [(0.89 ± 0.06) vs. (0.83 ± 0.04), P=0.01]. In addition, there were significant differences in the fractional anisotropy (FA) of the right and left cingulum between both groups [(0.45 ± 0.02) vs. (0.47 ± 0.03), P=0.01 and (0.45 ± 0.03) vs. 0.49± 0.04), P=0.01, respectively]. The overall accuracy of the aforementioned parameters ranged between 73 and 81% with the MD of the left cingulum revealing the highest accuracy.

Conclusion

DTI proofed to be a useful tool in differentiating AD patients from healthy subjects. In our study, we found that the splenium, cingulum, IFOF, and the right UF and right AF are the main tracts involved in AD. The left cingulum provided the highest accuracy in differentiating AD from normal subjects.

High-resolution microscopic diffusion anisotropy imaging in the human hippocampus at 3T

PURPOSE

Several neurological conditions are associated with microstructural changes in the hippocampus that can be observed using DWI. Imaging studies often use protocols with whole-brain coverage, imposing limits on image resolution and worsening partial-volume effects. Also, conventional single-diffusion-encoding methods confound microscopic diffusion anisotropy with size variance of microscopic diffusion environments. This study addresses these issues by implementing a multidimensional diffusion-encoding protocol for microstructural imaging of the hippocampus at high resolution.

METHODS

The hippocampus of 8 healthy volunteers was imaged at 1.5-mm isotropic resolution with a multidimensional diffusion-encoding sequence developed in house. Microscopic fractional anisotropy (µFA) and normalized size variance (C_MD ) were estimated using q-space trajectory imaging, and their values were compared with DTI metrics. The overall scan time was 1 hour. The reproducibility of the protocol was confirmed with scan-rescan experiments, and a shorter protocol (14 minutes) was defined for situations with time constraints.

RESULTS

Mean µFA (0.47) was greater than mean FA (0.20), indicating orientation dispersion in hippocampal tissue microstructure. Mean C_MD was 0.17. The reproducibility of q-space trajectory imaging metrics was comparable to DTI, and microstructural metrics in the healthy hippocampus are reported.

CONCLUSION

This work shows the feasibility of high-resolution microscopic anisotropy imaging in the human hippocampus at 3 T and provides reference values for microstructural metrics in a healthy hippocampus.

Bridging the Gap Between Morphometric Similarity Mapping and Gene Transcription in Alzheimer's Disease

Disruptions in brain connectivity have been widely reported in Alzheimer’s disease (AD). Morphometric similarity (MS) mapping provides a new way of estimating structural connectivity by interregional correlation of T1WI- and DTI-derived parameters within individual brains. Here, we aimed to identify AD-related MS changing patterns and genes related to the changes and further explored the molecular and cellular mechanism underlying MS changes in AD. Both 3D-T1WI and DTI data of 106 AD patients and 106 well-matched healthy elderly individuals from the ADNI database were included in our study. Cortical regions with significantly decreased MS were found in the temporal and parietal cortex, increased MS was found in the frontal cortex and variant changes were found in the occipital cortex in AD patients. Mean MS in regions with significantly changed MS was positively or negatively associated with memory function. Negative MS-related genes were significantly downregulated in AD, specifically enriched in neurons, and participated in biological processes, with the most significant term being synaptic transmission. This study revealed AD-related cortical MS changes associated with memory function. Linking gene expression to cortical MS changes may provide a possible molecular and cellular substrate for MS abnormality and cognitive decline in AD.

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.

18F-florbetapir PET as a marker of myelin integrity across the Alzheimer's disease spectrum

Purpose

Recent evidence suggests that PET imaging with amyloid-β (Aβ) tracers can be used to assess myelin integrity in cerebral white matter (WM). Alzheimer’s disease (AD) is characterized by myelin changes that are believed to occur early in the disease course. Nevertheless, the extent to which demyelination, as measured with Aβ PET, contributes to AD progression remains unexplored.

Methods

Participants with concurrent ¹⁸F-florbetapir (FBP) PET, MRI, and cerebrospinal fluid (CSF) examinations were included (241 cognitively normal, 347 Aβ-positive cognitively impaired, and 207 Aβ-negative cognitively impaired subjects). A subset of these participants had also available diffusion tensor imaging (DTI) images (n = 195). We investigated cross-sectional associations of FBP retention in the white matter (WM) with MRI-based markers of WM degeneration, AD clinical progression, and fluid biomarkers. In longitudinal analyses, we used linear mixed models to assess whether FBP retention in normal-appearing WM (NAWM) predicted progression of WM hyperintensity (WMH) burden and clinical decline.

Results

In AD-continuum individuals, FBP retention in NAWM was (1) higher compared with WMH regions, (2) associated with DTI-based measures of WM integrity, and (3) associated with longitudinal progression of WMH burden. FBP uptake in WM decreased across the AD continuum and with increasingly abnormal CSF biomarkers of AD. Furthermore, FBP retention in the WM was associated with large-calibre axon degeneration as reflected by abnormal plasma neurofilament light chain levels. Low FBP uptake in NAWM predicted clinical decline in preclinical and prodromal AD, independent of demographics, global cortical Aβ, and WMH burden. Most of these associations were also observed in Aβ-negative cognitively impaired individuals.

Conclusion

These results support the hypothesis that FBP retention in the WM is myelin-related. Demyelination levels progressed across the AD continuum and were associated with clinical progression at early stages, suggesting that this pathologic process might be a relevant degenerative feature in the disease course.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05493-y.

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.

Characterization of Brain Iron Deposition Pattern and Its Association With Genetic Risk Factor in Alzheimer's Disease Using Susceptibility-Weighted Imaging

The presence of iron is an important factor for normal brain functions, whereas excessive deposition of iron may impair normal cognitive function in the brain and lead to Alzheimer’s disease (AD). MRI has been widely applied to characterize brain structural and functional changes caused by AD. However, the effectiveness of using susceptibility-weighted imaging (SWI) for the analysis of brain iron deposition is still unclear, especially within the context of early AD diagnosis. Thus, in this study, we aim to explore the relationship between brain iron deposition measured by SWI with the progression of AD using various feature selection and classification methods. The proposed model was evaluated on a 69-subject SWI imaging dataset consisting of 24 AD patients, 21 mild cognitive impairment patients, and 24 normal controls. The identified AD progression-related regions were then compared with the regions reported from previous genetic association studies, and we observed considerable overlap between these two. Further, we have identified a new potential AD-related gene (MEF2C) closely related to the interaction between iron deposition and AD progression in the brain.

Reduced Hippocampal Glutamate and Posterior Cingulate N-Acetyl Aspartate in Mild Cognitive Impairment and Alzheimer's Disease Is Associated with Episodic Memory Performance and White Matter Integrity in the Cingulum: A Pilot Study

Identification of biological changes underlying the early symptoms of Alzheimer's disease (AD) will help to identify and stage individuals prior to symptom onset. The limbic system, which supports episodic memory and is impaired early in AD, is a primary target. In this study, brain metabolism and microstructure evaluated by high field (7 Tesla) proton magnetic resonance spectroscopy (1H-MRS) and diffusion tensor imaging (DTI) were evaluated in the limbic system of eight individuals with mild cognitive impairment (MCI), nine with AD, and sixteen normal elderly controls (NEC). Left hippocampal glutamate and posterior cingulate N-acetyl aspartate concentrations were reduced in MCI and AD compared to NEC. Differences in DTI metrics indicated volume and white matter loss along the cingulum in AD compared to NEC. Metabolic and microstructural changes were associated with episodic memory performance assessed using Craft Story 21 Recall and Benson Complex Figure Copy. The current study suggests that metabolite concentrations measured using 1H-MRS may provide insight into the underlying metabolic and microstructural processes of episodic memory impairment.

Comparison of CSF neurofilament light chain, neurogranin, and tau to MRI markers

INTRODUCTION

We determined whether cerebrospinal fluid (CSF) neurofilament light (NfL), neurogranin (Ng), and total-tau (t-tau) differentially mapped to magnetic resonance imaging (MRI) measures of cortical thickness, microstructural integrity (corpus callosum and cingulum fractional anisotropy [FA]), and white matter hyperintensities (WMH).

METHODS

Analyses included 536 non-demented Mayo Clinic Study of Aging participants with CSF NfL, Ng, t-tau, amyloid beta (Aβ)42 and longitudinal MRI scans. Linear mixed models assessed longitudinal associations between CSF markers and MRI changes.

RESULTS

Higher CSF NfL was associated with decreasing microstructural integrity and WMH. Higher t-tau was associated with decreasing temporal lobe and Alzheimer's disease (AD) meta region of interest (ROI) cortical thickness. There was no association between Ng and any MRI measure. CSF Aβ42 interacted with Ng for declines in temporal lobe and AD meta ROI cortical thickness and cingulum FA.

DISCUSSION

CSF NfL predicts changes in white matter integrity, t-tau reflects non-specific changes in cortical thickness, and Ng reflects AD-specific synaptic and neuronal degeneration.

Accelerating Structural Degeneration in Temporal Regions and Their Effects on Cognition in Aging of MCI Patients

Age is the major risk factor for Alzheimer's disease (AD) and for mild cognitive impairment (MCI). However, there is limited evidence about MCI-specific aging-related simultaneous changes of the brain structure and their impact on cognition. We analyzed the brain imaging data from 269 subjects (97 MCI patients and 172 cognitively normal [CN] elderly) using voxel-based morphometry and tract-based spatial statistics procedures to explore the special structural pattern during aging. We found that the patients with MCI showed accelerated age-related reductions in gray matter volume in the left planum temporale, thalamus, and posterior cingulate gyrus. The similar age×group interaction effect was found in the fractional anisotropy of the bilateral parahippocampal cingulum white matter tract, which connects the temporal regions. Importantly, the age-related temporal gray matter and white matter alterations were more significantly related to performance in memory and attention tasks in MCI patients. The accelerated degeneration patterns in the brain structure provide evidence for different neural mechanisms underlying aging in MCI patients. Temporal structural degeneration may serve as a potential imaging marker for distinguishing the progression of the preclinical AD stage from normal aging.

Apathy in small vessel cerebrovascular disease is associated with deficits in effort-based decision making

Patients with small vessel cerebrovascular disease frequently suffer from apathy, a debilitating neuropsychiatric syndrome, the underlying mechanisms of which remain to be established. Here we investigated the hypothesis that apathy is associated with disrupted decision making in effort-based decision making, and that these alterations are associated with abnormalities in the white matter network connecting brain regions that underpin such decisions. Eighty-two patients with MRI evidence of small vessel disease were assessed using a behavioural paradigm as well as diffusion weighted MRI. The decision-making task involved accepting or rejecting monetary rewards in return for performing different levels of physical effort (hand grip force). Choice data and reaction times were integrated into a drift diffusion model that framed decisions to accept or reject offers as stochastic processes approaching a decision boundary with a particular drift rate. Tract-based spatial statistics were used to assess the relationship between white matter tract integrity and apathy, while accounting for depression. Overall, patients with apathy accepted significantly fewer offers on this decision-making task. Notably, while apathetic patients were less responsive to low rewards, they were also significantly averse to investing in high effort. Significant reductions in white matter integrity were observed to be specifically related to apathy, but not to depression. These included pathways connecting brain regions previously implicated in effort-based decision making in healthy people. The drift rate to decision parameter was significantly associated with both apathy and altered white matter tracts, suggesting that both brain and behavioural changes in apathy are associated with this single parameter. On the other hand, depression was associated with an increase in the decision boundary, consistent with an increase in the amount of evidence required prior to making a decision. These findings demonstrate altered effort-based decision making for reward in apathy, and also highlight dissociable mechanisms underlying apathy and depression in small vessel disease. They provide clear potential brain and behavioural targets for future therapeutic interventions, as well as modelling parameters that can be used to measure the effects of treatment at the behavioural level.

Physical Exercise and Alzheimer's Disease: Effects on Pathophysiological Molecular Pathways of the Disease

Alzheimer’s disease (AD), the most common form of neurodegenerative dementia in adults worldwide, is a multifactorial and heterogeneous disorder characterized by the interaction of genetic and epigenetic factors and the dysregulation of numerous intracellular signaling and cellular/molecular pathways. The introduction of the systems biology framework is revolutionizing the study of complex diseases by allowing the identification and integration of cellular/molecular pathways and networks of interaction. Here, we reviewed the relationship between physical activity and the next pathophysiological processes involved in the risk of developing AD, based on some crucial molecular pathways and biological process dysregulated in AD: (1) Immune system and inflammation; (2) Endothelial function and cerebrovascular insufficiency; (3) Apoptosis and cell death; (4) Intercellular communication; (5) Metabolism, oxidative stress and neurotoxicity; (6) DNA damage and repair; (7) Cytoskeleton and membrane proteins; (8) Synaptic plasticity. Moreover, we highlighted the increasingly relevant role played by advanced neuroimaging technologies, including structural/functional magnetic resonance imaging, diffusion tensor imaging, and arterial spin labelling, in exploring the link between AD and physical exercise. Regular physical exercise seems to have a protective effect against AD by inhibiting different pathophysiological molecular pathways implicated in AD.

Systematic Assessment of the Impact of DTI Methodology on Fractional Anisotropy Measures in Alzheimer's Disease

White matter microstructural changes in Alzheimer's disease (AD) are often assessed using fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI). FA depends on the acquisition and analysis methods, including the fitting algorithm. In this study, we compared FA maps from different acquisitions and fitting algorithms in AD, mild cognitive impairment (MCI), and healthy controls (HCs) using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Three acquisitions from two vendors were compared (Siemens 30, GE 48, and Siemens 54 directions). DTI data were fit using nine fitting algorithms (four linear least squares (LLS), two weighted LLS (WLLS), and three non-linear LLS (NLLS) from four software tools (FSL, DSI-Studio, CAMINO, and AFNI). Different cluster volumes and effect-sizes were observed across acquisitions and fits, but higher consistency was observed as the number of diffusion directions increased. Significant differences were observed between HC and AD groups for all acquisitions, while significant differences between HC and MCI groups were only observed for GE48 and SI54. Using the intraclass correlation coefficient, AFNI-LLS and CAMINO-RESTORE were the least consistent with the other algorithms. By combining data across all three acquisitions and nine fits, differences between AD and HC/MCI groups were observed in the fornix and corpus callosum, indicating FA differences in these regions may be robust DTI-based biomarkers. This study demonstrates that comparisons of FA across aging populations could be confounded by variability in acquisitions and fit methodologies and that identifying the most robust DTI methodology is critical to provide more reliable DTI-based neuroimaging biomarkers for assessing microstructural changes in AD.

Anatomy and White Matter Connections of the Parahippocampal Gyrus

BACKGROUND

The parahippocampal gyrus is understood to have a role in high cognitive functions including memory encoding and retrieval and visuospatial processing. A detailed understanding of the exact location and nature of associated white tracts could significantly improve postoperative morbidity related to declining capacity. Through diffusion tensor imaging-based fiber tracking validated by gross anatomic dissection as ground truth, we have characterized these connections based on relationships to other well-known structures.

METHODS

Diffusion imaging from the Human Connectome Project for 10 healthy adult controls was used for tractography analysis. We evaluated the parahippocampal gyrus as a whole based on connectivity with other regions. All parahippocampal gyrus tracts were mapped in both hemispheres, and a lateralization index was calculated with resultant tract volumes.

RESULTS

We identified 2 connections of the parahippocampal gyrus: inferior longitudinal fasciculus and cingulum. Lateralization of the cingulum was detected (P < 0.05).

CONCLUSIONS

The parahippocampal gyrus is an important center for memory processing. Subtle differences in executive functioning following surgery for limbic tumors may be better understood in the context of the fiber-bundle anatomy highlighted by this study.

The Correlation of Reduced Fractional Anisotropy in the Cingulum With Suicide Risk in Bipolar Disorder

Objective: This study aims to investigate the significant alterations in brain white matter integrity in individuals with bipolar disorder (BD) who had attempted suicide by applying a tract-based spatial statistics (TBSS) approach with tensor-based spatial normalization. Methods: A TBSS approach with novel tensor-based registration was used to compare the white matter fractional anisotropy (FA) between 51 individuals with BD, of whom 19 had attempted suicide, and 43 healthy controls (HC). The suicide attempt was assessed with the Columbia-Suicide Severity Rating Scale (C-SSRS). In addition, we also investigated the correlations of FA values with clinical measures in BD, including illness duration, and the severity of depression and anxiety measured by the Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA), respectively. Results: A significant reduction of FA value in the hippocampal cingulum was observed in BD individuals who had attempted suicide compared with those who had not. For the genu/body of the corpus callosum, inferior fronto-occipital fasciculus, uncinate fasciculus, and anterior thalamic radiation, the reductions in FA values were significantly greater in both BD subgroups who attempted suicide and who did not, compared to HC. The correlation analysis showed that the illness duration of attempters was correlated to the FA value of the genu of the corpus callosum, while the HAMD and HAMA scores of non-attempters were relevant to the FA of the superior longitudinal fasciculus. Conclusion: The observation that white matter integrity was altered in the hippocampal cingulum in BD individuals who attempted suicide suggested that this brain area may be the neurobiological basis of suicide attempts. Our findings also support the involvement of white matter (WM) microstructure of frontal-subcortical circuits in the neurobiological mechanism of BD. In addition, the illness duration of patients with attempted suicide may have an effect on the altered integrity of the corpus callosum.

Association between microstructural white matter abnormalities and cognitive functioning in patients with type 2 diabetes mellitus: a diffusion tensor imaging study

Background

Diffusion tensor imaging (DTI) technique is important for exploring more sensitive imaging-based biomarkers in prevention and early treatment of cognitive dysfunction induced by type 2 diabetes mellitus (DM).

Objectives

To predict early cognitive dysfunction and detection of microstructural white matter changes in patients with type 2 DM by diffusion tensor imaging.

Patients and methods

A case-control study included thirty patients aged ≥ 18 years old of both sexes with type 2 DM and 30 controls. All subjects underwent to Montreal Cognitive Assessment (MoCA) “Arabic version”: to detect mild cognitive impairment (MCI) and diffusion tensor imaging study (DTI).

Results

Mild cognitive impairment is related to type 2 DM (56.7% of diabetic group), reduced fractional anisotropy (FA) values, and elevated mean diffusivity (MD) values were related to cognitive impairment evaluated through Montreal Cognitive Assessment (MoCA) in patients with type 2 DM.

Conclusion

The integrity of the white matter measured using DTI vary in MCI diabetics compared with non-MCI diabetics. Such changes have major implications on the cognitive function.

Implicating causal brain imaging endophenotypes in Alzheimer's disease using multivariable IWAS and GWAS summary data

Recent evidence suggests the existence of many undiscovered heritable brain phenotypes involved in Alzheimer's Disease (AD) pathogenesis. This finding necessitates methods for the discovery of causal brain changes in AD that integrate Magnetic Resonance Imaging measures and genotypic data. However, existing approaches for causal inference in this setting, such as the univariate Imaging Wide Association Study (UV-IWAS), suffer from inconsistent effect estimation and inflated Type I errors in the presence of genetic pleiotropy, the phenomenon in which a variant affects multiple causal intermediate risk phenotypes. In this study, we implement a multivariate extension to the IWAS model, namely MV-IWAS, to consistently estimate and test for the causal effects of multiple brain imaging endophenotypes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in the presence of pleiotropic and possibly correlated SNPs. We further extend MV-IWAS to incorporate variant-specific direct effects on AD, analogous to the existing Egger regression Mendelian Randomization approach, which allows for testing of remaining pleiotropy after adjusting for multiple intermediate pathways. We propose a convenient approach for implementing MV-IWAS that solely relies on publicly available GWAS summary data and a reference panel. Through simulations with either individual-level or summary data, we demonstrate the well controlled Type I errors and superior power of MV-IWAS over UV-IWAS in the presence of pleiotropic SNPs. We apply the summary statistic based tests to 1578 heritable imaging derived phenotypes (IDPs) from the UK Biobank. MV-IWAS detected numerous IDPs as possible false positives by UV-IWAS while uncovering many additional causal neuroimaging phenotypes in AD which are strongly supported by the existing literature.

Diffusion-weighted MRI in neurodegenerative and psychiatric animal models: Experimental strategies and main outcomes

Preclinical MRI approaches constitute a key tool to study a wide variety of neurological and psychiatric illnesses, allowing a more direct investigation of the disorder substrate and, at the same time, the possibility of back-translating such findings to human subjects. However, the lack of consensus on the optimal experimental scheme used to acquire the data has led to relatively high heterogeneity in the choice of protocols, which can potentially impact the comparison between results obtained by different groups, even using the same animal model. This is especially true for diffusion-weighted MRI data, where certain experimental choices can impact not only on the accuracy and precision of the extracted biomarkers, but also on their biological meaning. With this in mind, we extensively examined preclinical imaging studies that used diffusion-weighted MRI to investigate neurodegenerative, neurodevelopmental and psychiatric disorders in rodent models. In this review, we discuss the main findings for each preclinical model, with a special focus on the analysis and comparison of the different acquisition strategies used across studies and their impact on the heterogeneity of the findings.

Machine Learning for the Classification of Alzheimer’s Disease and Its Prodromal Stage Using Brain Diffusion Tensor Imaging Data: A Systematic Review

Alzheimer’s disease is notoriously the most common cause of dementia in the elderly, affecting an increasing number of people. Although widespread, its causes and progression modalities are complex and still not fully understood. Through neuroimaging techniques, such as diffusion Magnetic Resonance (MR), more sophisticated and specific studies of the disease can be performed, offering a valuable tool for both its diagnosis and early detection. However, processing large quantities of medical images is not an easy task, and researchers have turned their attention towards machine learning, a set of computer algorithms that automatically adapt their output towards the intended goal. In this paper, a systematic review of recent machine learning applications on diffusion tensor imaging studies of Alzheimer’s disease is presented, highlighting the fundamental aspects of each work and reporting their performance score. A few examined studies also include mild cognitive impairment in the classification problem, while others combine diffusion data with other sources, like structural magnetic resonance imaging (MRI) (multimodal analysis). The findings of the retrieved works suggest a promising role for machine learning in evaluating effective classification features, like fractional anisotropy, and in possibly performing on different image modalities with higher accuracy.

Frontal-executive and corticolimbic structural brain circuitry in older people with remitted depression, mild cognitive impairment, Alzheimer's dementia, and normal cognition

A history of depression is a risk factor for dementia. Despite strong epidemiologic evidence, the pathways linking depression and dementia remain unclear. We assessed structural brain alterations in white and gray matter of frontal-executive and corticolimbic circuitries in five groups of older adults putatively at-risk for developing dementia- remitted depression (MDD), non-amnestic MCI (naMCI), MDD+naMCI, amnestic MCI (aMCI), and MDD+aMCI. We also examined two other groups: non-psychiatric ("healthy") controls (HC) and individuals with Alzheimer's dementia (AD). Magnetic resonance imaging (MRI) data were acquired on the same 3T scanner. Following quality control in these seven groups, from diffusion-weighted imaging (n = 300), we compared white matter fractional anisotropy (FA), mean diffusivity (MD), and from T1-weighted imaging (n = 333), subcortical volumes and cortical thickness in frontal-executive and corticolimbic regions of interest (ROIs). We also used exploratory graph theory analysis to compare topological properties of structural covariance networks and hub regions. We found main effects for diagnostic group in FA, MD, subcortical volume, and cortical thickness. These differences were largely due to greater deficits in the AD group and to a lesser extent aMCI compared with other groups. Graph theory analysis revealed differences in several global measures among several groups. Older individuals with remitted MDD and naMCI did not have the same white or gray matter changes in the frontal-executive and corticolimbic circuitries as those with aMCI or AD, suggesting distinct neural mechanisms in these disorders. Structural covariance global metrics suggested a potential difference in brain reserve among groups.

Structural disconnectivity and the risk of dementia in the general population

Objective

The disconnectivity hypothesis postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion MRI to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study.

Methods

Global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 people without dementia (mean age 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005 and 2011. We modeled the association of these diffusion measures with risk of dementia (follow-up until 2016) and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype.

Results

During a median follow-up of 6.8 years, 101 participants had incident dementia, of whom 83 had clinical Alzheimer disease (AD). Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval (CI)] per SD increase for MD 1.79 [1.44–2.23] and FA 0.65 [0.52–0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in people without dementia (difference in global cognition per SD increase in MD [95% CI] was −0.04 [−0.07 to −0.01]). Associations were most profound in the projection, association, and limbic system tracts.

Conclusions

Structural disconnectivity is associated with an increased risk of dementia and more pronounced cognitive decline in the general population.

Focal white matter disruptions along the cingulum tract explain cognitive decline in amnestic mild cognitive impairment (aMCI)

White matter abnormalities of the human brain are implicated in typical aging and neurodegenerative diseases. However, our understanding of how fine-grained changes in microstructural properties along white matter tracts are associated with memory and cognitive decline in normal aging and mild cognitive impairment remains elusive. We quantified tract profiles with a newer method that can reliably measure fine-grained changes in white matter properties along the tracts using advanced multi-shell diffusion magnetic resonance imaging in 25 patients with amnestic mild cognitive impairment (aMCI) and 23 matched healthy controls (HC). While the changes in tract profiles were parallel across aMCI and HC, we found a significant focal shift in the profile at specific locations along major tracts sub-serving memory in aMCI. Particularly, our findings depict white matter alterations at specific locations on the right cingulum cingulate, the right cingulum hippocampus and anterior corpus callosum (CC) in aMCI compared to HC. Notably, focal changes in white matter tract properties along the cingulum tract predicted memory and cognitive functioning in aMCI. The results suggest that white matter disruptions at specific locations of the cingulum bundle may be a hallmark for the early prediction of Alzheimer’s disease and a predictor of cognitive decline in aMCI.

White matter networks dissociate semantic control from semantic knowledge representations: Evidence from voxel-based lesion-symptom mapping

Although semantic system is composed of two distinctive processes (i.e., semantic knowledge and semantic control), it remains unknown in which way these two processes dissociate from each other. Investigating the white matter neuroanatomy underlying these processes helps improve understanding of this question. To address this issue, we recruited brain-damaged patients with semantic dementia (SD) and semantic aphasia (SA), who had selective predominant deficits in semantic knowledge and semantic control, respectively. We built regression models to identify the white matter network associated with the semantic performance of each patient group. Semantic knowledge deficits in the SD patients were associated with damage to the left medial temporal network, while semantic control deficits in the SA patients were associated with damage to the other two networks (left frontal-temporal/occipital and frontal-subcortical networks). The further voxel-based analysis revealed additional semantic-relevant white matter tracts. These findings specify different processing principles of the components in semantic system.

Higher Hippocampal Mean Diffusivity Values in Asymptomatic Welders

Chronic high-level manganese (Mn)-induced neurotoxicity has been associated with Mn accumulation in the basal ganglia and higher risk for developing parkinsonism. Recent studies in Mn-exposed animals revealed Mn accumulation in the hippocampus, the presence of Aβ diffuse plaques, and deficits in associative learning, the latter being hallmarks of Alzheimer's disease (AD) or related disorders. This and recent evidence of hippocampal Mn accumulation in welders prompted us to test the hypothesis that welders with chronic Mn exposure would display changes in the hippocampus. Subjects with (welders; n = 42) or without (controls; n = 31) welding history were studied. Mn exposure was estimated by occupational questionnaires, whole blood Mn, and R1 imaging (estimate of short-term brain Mn accumulation). Hippocampal diffusion tensor imaging (DTI; estimate of microstructural brain changes) and volume were determined. Compared with controls, welders displayed no significant difference in hippocampal volume (p = .165). Welders, however, exhibited higher DTI hippocampal mean diffusivity (MD) values compared with controls (p = .035) that was evident particularly in older welders (>50 years, p = .002). Hippocampal MD was associated significantly with age in welders (R = 0.59; p < .001) but not in controls (p = .16). Moreover, higher hippocampal MD values (age adjusted) were associated with long-term cumulative Mn exposure (R = 0.36, p = .021). Welders with chronic exposure have higher MD values in the hippocampus that become greater with increasing age, a brain change that is similar to that observed in those at risk for AD. The current results suggest that Mn exposure, coupled with aging, may make welders more vulnerable to AD or AD-like changes.