Diffusion tensor imaging of white matter degeneration in Alzheimer’s disease and mild cognitive impairment

Microstructural white matter injury contributes to cognitive decline: Besides amyloid and tau

BACKGROUND

Cognitive decline and the progression to Alzheimer's disease (AD) are traditionally associated with amyloid-beta (Aβ) and tau pathologies. This study aims to evaluate the relationships between microstructural white matter injury, cognitive decline and AD core biomarkers.

METHODS

We conducted a longitudinal study of 566 participants using peak width of skeletonized mean diffusivity (PSMD) to quantify microstructural white matter injury. The associations of PSMD with changes in cognitive functions, AD pathologies (Aβ, tau, and neurodegeneration), and volumes of AD-signature regions of interest (ROI) or hippocampus were estimated. The associations between PSMD and the incidences of clinical progression were also tested. Covariates included age, sex, education, apolipoprotein E4 status, smoking, and hypertension.

RESULTS

Higher PSMD was associated with greater cognitive decline (β=-0.012, P < 0.001 for Mini-Mental State Examination score; β<0, P < 0.05 for four cognitive domains) and a higher risk of clinical progression from normal cognition to mild cognitive impairment (MCI) or AD (Hazard ratio=2.11 [1.38-3.23], P < 0.001). These associations persisted independently of amyloid status. PSMD did not predict changes in Aβ or tau levels, but predicted changes in volumes of AD-signature ROI (β=-0.003, P < 0.001) or hippocampus (β=-0.002, P = 0.010). Besides, the whole-brain PSMD could predict cognitive decline better than regional PSMDs.

CONCLUSIONS

PSMD may be a valuable biomarker for predicting cognitive decline and clinical progression to MCI and AD, providing insights besides traditional Aβ and tau pathways. Further research could elucidate its role in clinical assessments and therapeutic strategies.

APOEε4 alters ApoE and Fabp7 in frontal cortex white matter in prodromal Alzheimer's disease

The ApoE ε4 allele (APOEε4) is a major genetic risk factor for sporadic Alzheimer's disease (AD) and is linked to demyelination and cognitive decline. However, its effects on the lipid transporters apolipoprotein E (ApoE) and fatty acid-binding protein 7 (Fabp7), which are crucial for the maintenance of myelin in white matter (WM) during the progression of AD remain underexplored. To evaluate the effects of APOEε4 on ApoE, Fabp7 and myelin in the WM of the frontal cortex (FC), we examined individuals carrying one ε4 allele that came to autopsy with a premortem clinical diagnosis of no cognitive impairment (NCI), mild cognitive impairment (MCI) and mild to moderate AD compared with non-carrier counterparts. ApoE, Fabp7 and Olig2 immunostaining was used to visualize cells, whereas myelin basic protein (MBP) immunocytochemistry and luxol fast blue (LFB) histochemistry of myelin in the WM of the FC were combined with quantitative morphometry. We observed increased numbers of ApoE-positive astrocytes in the WM of both NCI and MCI APOEε4 carriers compared with non-carriers, whereas Fabp7-positive cells were elevated only in AD. Conversely, Olig2 cell counts and MBP immunostaining decreased in MCI APOEε4 carriers compared to non-carriers, while LFB levels were higher in NCI APOEε4 carriers compared to non-carriers. Although no correlations were found between ApoE, Fabp7, and cognitive status, LFB measurements were positively correlated with perceptual speed, global cognition, and visuospatial scores in APOEε4 carriers across clinical groups. The present findings suggest that the ε4 allele compromises FC myelin homeostasis by disrupting the lipid transporters ApoE, Fabp7 and myelination early in the onset of AD. These data support targeting cellular components related to WM integrity as possible treatments for AD.

An SBM and TBSS Analysis in Early-stage Patients With Alzheimer's Disease, Lewy Body Dementias, and Corticobasal Syndrome

OBJECTIVE

To compare gray matter (GM) and white matter (WM) changes in patients with Alzheimer's disease (AD), Lewy body dementias (LBD), corticobasal syndrome (CBS), and healthy controls (HC).

METHODS

Surface-based morphometry (SBM) was assessed on 3D T1-weighted images using FreeSurfer image analysis and WM microstructure was studied using Tract-Based Spatial Statistics (TBSS) in 12 AD, 15 LBD, 10 CBS patients, and 10 HC.

RESULTS

Patients with AD, compared with HC, exhibited reduced cortical surface area and volume in the superior frontal, middle frontal, and medial orbitofrontal cortex. In TBSS, AD patients, compared with HC and LBD, displayed decreased fractional anisotropy, axial diffusivity, and increased radial diffusivity in all major WM tracts. Other comparisons between the groups yielded no differences, either in the SBM or the TBSS analysis.

CONCLUSIONS

The results indicate significant early structural changes in the GM of the frontal lobe, along with WM alterations early in AD patients.

Deep Normative Tractometry for Identifying Joint White Matter Macro- and Micro-structural Abnormalities in Alzheimer's Disease

This study introduces the Deep Normative Tractometry (DNT) framework, that encodes the joint distribution of both macrostructural and microstructural profiles of the brain white matter tracts through a variational autoencoder (VAE). By training on data from healthy controls, DNT learns the normative distribution of tract data, and can delineate along-tract micro- and macro-structural abnormalities. Leveraging a large sample size via generative pre-training, we assess DNT's generalizability using transfer learning on data from an independent cohort acquired in India. Our findings demonstrate DNT's capacity to detect widespread diffusivity abnormalities along tracts in mild cognitive impairment and Alzheimer's disease, aligning closely with results from the Bundle Analytics (BUAN) tractometry pipeline. By incorporating tract geometry information, DNT may be able to distinguish disease-related abnormalities in anisotropy from tract macrostructure, and shows promise in enhancing fine-scale mapping and detection of white matter alterations in neurodegenerative conditions.

Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition

BACKGROUND

The hypothesis of decreased neural inhibition in dementia has been sparsely studied in functional magnetic resonance imaging (fMRI) data across patients with different dementia subtypes, and the role of social and demographic heterogeneities on this hypothesis remains to be addressed.

METHODS

We inferred regional inhibition by fitting a biophysical whole-brain model (dynamic mean field model with realistic inter-areal connectivity) to fMRI data from 414 participants, including patients with Alzheimer's disease, behavioral variant frontotemporal dementia, and controls. We then investigated the effect of disease condition, and demographic and clinical variables on the local inhibitory feedback, a variable related to the maintenance of balanced neural excitation/inhibition.

RESULTS

Decreased local inhibitory feedback was inferred from the biophysical modeling results in dementia patients, specific to brain areas presenting neurodegeneration. This loss of local inhibition correlated positively with years with disease, and showed differences regarding the gender and geographical origin of the patients. The model correctly reproduced known disease-related changes in functional connectivity.

CONCLUSIONS

Results suggest a critical link between abnormal neural and circuit-level excitability levels, the loss of grey matter observed in dementia, and the reorganization of functional connectivity, while highlighting the sensitivity of the underlying biophysical mechanism to demographic and clinical heterogeneities in the patient population.

Advanced brain aging in Parkinson's disease with cognitive impairment

Patients with Parkinson's disease and cognitive impairment (PD-CI) deteriorate faster than those without cognitive impairment (PD-NCI), suggesting an underlying difference in the neurodegeneration process. We aimed to verify brain age differences in PD-CI and PD-NCI and their clinical significance. A total of 94 participants (PD-CI, n = 27; PD-NCI, n = 34; controls, n = 33) were recruited. Predicted age difference (PAD) based on gray matter (GM) and white matter (WM) features were estimated to represent the degree of brain aging. Patients with PD-CI showed greater GM-PAD (7.08 ± 6.64 years) and WM-PAD (8.82 ± 7.69 years) than those with PD-NCI (GM: 1.97 ± 7.13, Padjusted = 0.011; WM: 4.87 ± 7.88, Padjusted = 0.049) and controls (GM: -0.58 ± 7.04, Padjusted = 0.004; WM: 0.88 ± 7.45, Padjusted = 0.002) after adjusting demographic factors. In patients with PD, GM-PAD was negatively correlated with MMSE (Padjusted = 0.011) and MoCA (Padjusted = 0.013) and positively correlated with UPDRS Part II (Padjusted = 0.036). WM-PAD was negatively correlated with logical memory of immediate and delayed recalls (Padjusted = 0.003 and Padjusted < 0.001). Also, altered brain regions in PD-CI were identified and significantly correlated with brain age measures, implicating the neuroanatomical underpinning of neurodegeneration in PD-CI. Moreover, the brain age metrics can improve the classification between PD-CI and PD-NCI. The findings suggest that patients with PD-CI had advanced brain aging that was associated with poor cognitive functions. The identified neuroimaging features and brain age measures can serve as potential biomarkers of PD-CI.

Deep Normative Tractometry for Identifying Joint White Matter Macro- and Micro-structural Abnormalities in Alzheimer's Disease

This study introduces the Deep Normative Tractometry (DNT) framework, that encodes the joint distribution of both macrostructural and microstructural profiles of the brain white matter tracts through a variational autoencoder (VAE). By training on data from healthy controls, DNT learns the normative distribution of tract data, and can delineate along-tract micro-and macro-structural abnormalities. Leveraging a large sample size via generative pre-training, we assess DNT's generalizability using transfer learning on data from an independent cohort acquired in India. Our findings demonstrate DNT's capacity to detect widespread diffusivity abnormalities along tracts in mild cognitive impairment and Alzheimer's disease, aligning closely with results from the Bundle Analytics (BUAN) tractometry pipeline. By incorporating tract geometry information, DNT may be able to distinguish disease-related abnormalities in anisotropy from tract macrostructure, and shows promise in enhancing fine-scale mapping and detection of white matter alterations in neurodegenerative conditions.

Fronto-limbic white matter microstructural changes in psychiatrically healthy adults with childhood trauma

Childhood trauma (CT) may influence brain white matter microstructure; however, few studies have examined the differential impact of distinct CT types on white matter microstructure in psychiatrically healthy adults living in a developing country. In adults without significant medical or psychiatric disorders, we investigated the association(s) between CT, including abuse and neglect, and fractional anisotropy (FA) of limbic tracts previously shown to be associated with CT. Participants underwent diffusion tensor imaging and completed the Childhood Trauma Questionnaire. Multivariate analysis of variance models were used to test the effects of total overall CT, as well as CT subtypes, on FA in six fronto-limbic tracts, adjusting for age, sex, and educational level. The final sample included 69 adults (age 47 ± 17 years; 70% female). Overall, CT had a significant main effect on FA for tracts of interest (p < .001). Greater CT severity was associated with lower FA for the bilateral and left stria terminalis (uncorrected) as well as the bilateral, left, and right anterior limb of the internal capsule (ALIC; corrected). Exposure to total non-violent/deprivational trauma specifically was associated with lower FA of the bilateral, left, and right ALIC, suggesting that distinct types of CT are associated with differential white matter changes in apparently healthy adults. The ALIC predominantly carries fibers connecting the thalamus with prefrontal cortical regions. Microstructural alterations in the ALIC may be associated with functional brain changes, which may be adaptive or increase the risk of accelerated age-related cognitive decline, maladaptive behaviors, and subsyndromal psychiatric symptoms.

Identifying potential imaging markers for diffusion property changes in a mouse model of amyotrophic lateral sclerosis: Application of the continuous time random walk model to ultrahigh b-value diffusion-weighted MR images of spinal cord tissue

Diffusion MRI (dMRI) explores tissue microstructures by analyzing diffusion-weighted signal decay measured at different b-values. While relatively low b-values are used for most dMRI models, high b-value diffusion-weighted imaging (DWI) techniques have gained interest given that the non-Gaussian water diffusion behavior observed at high b-values can yield potentially valuable information. In this study, we investigated anomalous diffusion behaviors associated with degeneration of spinal cord tissue using a continuous time random walk (CTRW) model for DWI data acquired across an extensive range of ultrahigh b-values. The diffusion data were acquired in situ from the lumbar level of spinal cords of wild-type and age-matched transgenic SOD1G93A mice, a well-established animal model of amyotrophic lateral sclerosis (ALS) featuring progressive degeneration of axonal tracts in this tissue. Based on the diffusion decay behaviors at low and ultrahigh b-values, we applied the CTRW model using various combinations of b-values and compared diffusion metrics calculated from the CTRW model between the experimental groups. We found that diffusion-weighted signal decay curves measured with ultrahigh b-values (up to 858,022 s/mm2 in this study) were well represented by the CTRW model. The anomalous diffusion coefficient obtained from lumbar spinal cords was significantly higher in SOD1G93A mice compared with control mice (14.7 × 10-5  ± 5.54 × 10-5  vs. 7.87 × 10-5  ± 2.48 × 10-5  mm2 /s, p = 0.01). We believe this is the first study to illustrate the efficacy of the CTRW model for analyzing anomalous diffusion regimes at ultrahigh b-values. The CTRW modeling of ultrahigh b-value dMRI can potentially present a novel approach for noninvasively evaluating alterations in spinal cord tissue associated with ALS pathology.

Assessment of Gray Matter Microstructural Alterations in Alzheimer's Disease by Free Water Imaging

Background

Cortical neurodegenerative processes may precede the emergence of disease symptoms in patients with Alzheimer's disease (AD) by many years. No study has evaluated the free water of patients with AD using gray matter-based spatial statistics.

Objective

The aim of this study was to explore cortical microstructural changes within the gray matter in AD by using free water imaging with gray matter-based spatial statistics.

Methods

Seventy-one participants underwent multi-shell diffusion magnetic resonance imaging, 11C-Pittsburgh compound B positron emission tomography, and neuropsychological evaluations. The patients were divided into two groups: healthy controls (n = 40) and the AD spectrum group (n = 31). Differences between the groups were analyzed using voxel-based morphometry, diffusion tensor imaging, and free water imaging with gray matter-based spatial statistics.

Results

Voxel-based morphometry analysis revealed gray matter volume loss in the hippocampus of patients with AD spectrum compared to that in controls. Furthermore, patients with AD spectrum exhibited significantly greater free water, mean diffusivity, and radial diffusivity in the limbic areas, precuneus, frontal lobe, temporal lobe, right putamen, and cerebellum than did the healthy controls. Overall, the effect sizes of free water were greater than those of mean diffusivity and radial diffusivity, and the larger effect sizes of free water were thought to be strongly correlated with AD pathology.

Conclusions

This study demonstrates the utility of applying voxel-based morphometry, gray matter-based spatial statistics, free water imaging and diffusion tensor imaging to assess AD pathology and detect changes in gray matter.

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.

White matter alterations in mild cognitive impairment revealed by meta-analysis of diffusion tensor imaging using tract-based spatial statistics

The neuropathological mechanism of mild cognitive impairment (MCI) remains unclarified. Diffusion tensor imaging (DTI) studies revealed white matter (WM) microarchitecture alterations in MCI, but consistent findings and conclusions have not yet been drawn. The present coordinate-based meta-analysis (CBMA) of tract-based spatial statistics (TBSS) studies aimed to identify the most prominent and robust WM abnormalities in patients with MCI. A systematic search of relevant studies was conducted through January 2022 to identify TBSS studies comparing fractional anisotropy (FA) between MCI patients and healthy controls (HC). We used the seed-based d mapping (SDM) software to achieve the CBMA and analyze regional FA alterations in MCI. Meta-regression analysis was subsequently applied to explore the potential associations between clinical variables and FA changes. MCI patients demonstrated significantly decreased FA in widely distributed areas in the corpus callosum (CC), including the genu, body, and splenium of the CC, as well as one cluster in the left striatum. FA in the body of the CC and in three clusters in the splenium of the CC was negatively associated with the mean age. Additionally, FA in the genu of the CC and in three clusters in the splenium of the CC had negative correlations with the MMSE scores. Disrupted integrities of the CC and left striatum might play vital roles in the process of cognitive decline. These findings enhanced our understanding of the neural mechanism underlying WM neurodegeneration in MCI and provided perspectives for the early detection and intervention of dementia.Registration number: CRD42022235716.

A new era for myelin research in Neurofibromatosis type 1

Evidence for myelin regulating higher-order brain function and disease is rapidly accumulating; however, defining cellular/molecular mechanisms remains challenging partially due to the dynamic brain physiology involving deep changes during development, aging, and in response to learning and disease. Furthermore, as the etiology of most neurological conditions remains obscure, most research models focus on mimicking symptoms, which limits understanding of their molecular onset and progression. Studying diseases caused by single gene mutations represents an opportunity to understand brain dys/function, including those regulated by myelin. Here, we discuss known and potential repercussions of abnormal central myelin on the neuropathophysiology of Neurofibromatosis Type 1 (NF1). Most patients with this monogenic disease present with neurological symptoms diverse in kind, severity, and onset/decline, including learning disabilities, autism spectrum disorders, attention deficit and hyperactivity disorder, motor coordination issues, and increased risk for depression and dementia. Coincidentally, most NF1 patients show diverse white matter/myelin abnormalities. Although myelin-behavior links were proposed decades ago, no solid data can prove or refute this idea yet. A recent upsurge in myelin biology understanding and research/therapeutic tools provides opportunities to address this debate. As precision medicine moves forward, an integrative understanding of all cell types disrupted in neurological conditions becomes a priority. Hence, this review aims to serve as a bridge between fundamental cellular/molecular myelin biology and clinical research in NF1.

Regulation of lipid synthesis in myelin modulates neural activity and is required for motor learning

Brain function relies on both rapid electrical communication in neural circuitry and appropriate patterns or synchrony of neural activity. Rapid communication between neurons is facilitated by wrapping nerve axons with insulation by a myelin sheath composed largely of different lipids. Recent evidence has indicated that the extent of myelination of nerve axons can adapt based on neural activity levels and this adaptive myelination is associated with improved learning of motor tasks, suggesting such plasticity may enhance effective learning. In this study, we examined whether another aspect of myelin plasticity-changes in myelin lipid synthesis and composition-may also be associated with motor learning. We combined a motor learning task in mice with in vivo two-photon imaging of neural activity in the primary motor cortex (M1) to distinguish early and late stages of learning and then probed levels of some key myelin lipids using mass spectrometry analysis. Sphingomyelin levels were elevated in the early stage of motor learning while galactosylceramide levels were elevated in the middle and late stages of motor learning, and these changes were correlated across individual mice with both learning performance and neural activity changes. Targeted inhibition of oligodendrocyte-specific galactosyltransferase expression, the enzyme that synthesizes myelin galactosylceramide, impaired motor learning. Our results suggest regulation of myelin lipid composition could be a novel facet of myelin adaptations associated with learning.

Activity-dependent oligodendrocyte calcium dynamics and their changes in Alzheimer's disease

Oligodendrocytes (OCs) form myelin around axons, which is dependent on neuronal activity. This activity-dependent myelination plays a crucial role in training and learning. Previous studies have suggested that neuronal activity regulates proliferation and differentiation of oligodendrocyte precursor cells (OPCs) and myelination. In addition, deficient activity-dependent myelination results in impaired motor learning. However, the functional response of OC responsible for neuronal activity and their pathological changes is not fully elucidated. In this research, we aimed to understand the activity-dependent OC responses and their different properties by observing OCs using in vivo two-photon microscopy. We clarified that the Ca2+ activity in OCs is neuronal activity dependent and differentially regulated by neurotransmitters such as glutamate or adenosine triphosphate (ATP). Furthermore, in 5-month-old mice models of Alzheimer's disease, a period before the appearance of behavioral abnormalities, the elevated Ca2+ responses in OCs are ATP dependent, suggesting that OCs receive ATP from damaged tissue. We anticipate that our research will help in determining the correct therapeutic strategy for neurodegenerative diseases beyond the synapse.

Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease

Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.

Microstructure abnormalities of the diffusion quantities in children with attention-deficit/hyperactivity disorder: an AFQ and TBSS study

Objective

To explore the specific alterations of white matter microstructure in children with attention-deficit/hyperactivity disorder (ADHD) by automated fiber quantification (AFQ) and tract-based spatial statistics (TBSS), and to analyze the correlation between white matter abnormality and impairment of executive function.

Methods

In this prospective study, a total of twenty-seven patients diagnosed with ADHD (20 males, 7 females; mean age of 8.89 ± 1.67 years) and twenty-two healthy control (HC) individuals (11 males, 11 females, mean age of 9.82 ± 2.13 years) were included. All participants were scanned with diffusion kurtosis imaging (DKI) and assessed for executive functions. AFQ and TBSS analysis methods were used to investigate the white matter fiber impairment of ADHD patients, respectively. Axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA) of 17 fiber properties were calculated using the AFQ. The mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), mean diffusivity (MDDKI), axial diffusivity (ADDKI), radial diffusivity (RDDKI) and fractional anisotropy (FADKI) of DKI and AD, RD, MD, and FA of diffusion tensor imaging (DTI) assessed the integrity of the white matter based on TBSS. Partial correlation analyses were conducted to evaluate the correlation between white matter abnormalities and clinical test scores in ADHD while taking age, gender, and education years into account. The analyses were all family-wise error rate (FWE) corrected.

Results

ADHD patients performed worse on the Behavior Rating Inventory of Executive Function (BRIEF) test (p < 0.05). Minor variances existed in gender and age between ADHD and HC, but these variances did not yield statistically significant distinctions. There were no significant differences in TBSS for DKI and DTI parameters (p > 0.05, TFCE-corrected). Compared to HC volunteers, the mean AD value of right cingulum bundle (CB_R) fiber tract showed a significantly higher level in ADHD patients following the correction of FWE. As a result of the point-wise comparison between groups, significant alterations (FWE correction, p < 0.05) were mainly located in AD (nodes 36-38, nodes 83-97) and MD (nodes 92-95) of CB_R. There was no significant correlation between white matter diffusion parameters and clinical test scores in ADHD while taking age, gender, and education years into account.

Conclusion

The AFQ method can detect ADHD white matter abnormalities in a specific location with greater sensitivity, and the CB_R played a critical role. Our findings may be helpful in further studying the relationship between focal white matter abnormalities and ADHD.

Cuprizone drives divergent neuropathological changes in different mouse models of Alzheimer's disease

Myelin degradation is a normal feature of brain aging that accelerates in Alzheimer's disease (AD). To date, however, the underlying biological basis of this correlation remains elusive. The amyloid cascade hypothesis predicts that demyelination is caused by increased levels of the β-amyloid (Aβ) peptide. Here we report on work supporting the alternative hypothesis that early demyelination is upstream of amyloid. We challenged two different mouse models of AD (R1.40 and APP/PS1) using cuprizone-induced demyelination and tracked the responses with both neuroimaging and neuropathology. In oppose to amyloid cascade hypothesis, R1.40 mice, carrying only a single human mutant APP (Swedish; APP SWE ) transgene, showed a more abnormal changes of magnetization transfer ratio and diffusivity than in APP/PS1 mice, which carry both APP SWE and a second PSEN1 transgene (delta exon 9; PSEN1 dE9 ). Although cuprizone targets oligodendrocytes (OL), magnetic resonance spectroscopy and targeted RNA-seq data in R1.40 mice suggested a possible metabolic alternation in axons. In support of alternative hypotheses, cuprizone induced significant intraneuronal amyloid deposition in young APP/PS1, but not in R1.40 mice, and it suggested the presence of PSEN deficiencies, may accelerate Aβ deposition upon demyelination. In APP/PS1, mature OL is highly vulnerable to cuprizone with significant DNA double strand breaks (53BP1 + ) formation. Despite these major changes in myelin, OLs, and Aβ immunoreactivity, no cognitive impairment or hippocampal pathology was detected in APP/PS1 mice after cuprizone treatment. Together, our data supports the hypothesis that myelin loss can be the cause, but not the consequence, of AD pathology.

SIGNIFICANCE STATEMENT

The causal relationship between early myelin loss and the progression of Alzheimer's disease remains unclear. Using two different AD mouse models, R1.40 and APP/PS1, our study supports the hypothesis that myelin abnormalities are upstream of amyloid production and deposition. We find that acute demyelination initiates intraneuronal amyloid deposition in the frontal cortex. Further, the loss of oligodendrocytes, coupled with the accelerated intraneuronal amyloid deposition, interferes with myelin tract diffusivity at a stage before any hippocampus pathology or cognitive impairments occur. We propose that myelin loss could be the cause, not the consequence, of amyloid pathology during the early stages of Alzheimer's disease.

Association between polygenic risk for Alzheimer's disease and brain structure in children and adults

BACKGROUND

The correlations between genetic risk for Alzheimer's disease (AD) with comprehensive brain regions at a regional scale are still not well understood. We aim to explore whether these associations vary across different age stages.

METHODS

This study used large existing genome-wide association datasets to calculate polygenic risk score (PRS) for AD in two populations from the UK Biobank (N ~ 23 000) and Adolescent Brain Cognitive Development Study (N ~ 4660) who had multimodal macrostructural and microstructural magnetic resonance imaging (MRI) metrics. We used linear mixed-effect models to assess the strength of the association between AD PRS and multiple MRI metrics of regional brain structures at different stages of life.

RESULTS

Compared to those with lower PRSs, adolescents with higher PRSs had thinner cortex in the caudal anterior cingulate and supramarginal. In the middle-aged and elderly population, AD PRS had correlations with regional structure shrink primarily located in the cingulate, prefrontal cortex, hippocampus, thalamus, amygdala, and striatum, whereas the brain expansion was concentrated near the occipital lobe. Furthermore, both adults and adolescents with higher PRSs exhibited widespread white matter microstructural changes, indicated by decreased fractional anisotropy (FA) or increased mean diffusivity (MD).

CONCLUSIONS

In conclusion, our results suggest genetic loading for AD may influence brain structures in a highly dynamic manner, with dramatically different patterns at different ages. This age-specific change is consistent with the classical pattern of brain impairment observed in AD patients.

The genetic architecture of fornix white matter microstructure and their involvement in neuropsychiatric disorders

The fornix is a white matter bundle located in the center of the hippocampaldiencephalic limbic circuit that controls memory and executive functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out a genome-wide association analysis of 30,832 UK Biobank individuals of the six fornix diffusion magnetic resonance imaging (dMRI) traits. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the single nucleotide polymorphisms (SNP), locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in adolescent brain cognitive development (ABCD) cohort. The GWAS identified 63 independent significant variants within 20 genomic loci associated (P < 8.33 × 10^-9) with the six fornix dMRI traits. Geminin coiled-coil domain containing (GMNC) and NUAK family SNF1-like kinase 1 (NUAK1) gene were highlighted, which were found in UKB and replicated in ABCD. The heritability of the six traits ranged from 10% to 27%. Gene mapping strategies identified 213 genes, where 11 were supported by all of four methods. Gene-based analyses revealed pathways relating to cell development and differentiation, with astrocytes found to be significantly enriched. Pleiotropy analyses with eight neurological and psychiatric disorders revealed shared variants, especially with schizophrenia under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of fornix and their relevance in neurological and psychiatric disorders.

Circulating polyunsaturated fatty acids, fish oil supplementation, and risk of incident dementia: a prospective cohort study of 440,750 participants

Cohort studies report inconsistent associations between omega-3 polyunsaturated fatty acids (n-3 PUFA) or fish oil and dementia risk. Furthermore, evidence relating omega-6 polyunsaturated fatty acids (n-6 PUFA) with dementia is scarce. Here, we included 440,750 dementia-free participants from UK Biobank to comprehensively investigate the associations between plasma levels of different types of PUFA, fish oil supplementation, and dementia risk. During a median follow-up of 9.25 years, 7768 incident dementia events occurred. Higher plasma levels of five PUFA measures showed consistent associations with lower dementia risk (hazard ratios [95% confidence intervals] for per standard deviation increment of plasma concentrations 0.85 [0.81-0.89] for total PUFAs; 0.90 [0.86-0.95] for omega-3 PUFAs; 0.92 [0.87-0.96] for docosahexaenoic acid (DHA); 0.86 [0.82-0.90] for omega-6 PUFAs; 0.86 [0.82-0.90] for linoleic acid (LA); all p < 0.001). Compared with non-users, fish oil supplement users had a 7% decreased risk of developing all-cause dementia (0.93 [0.89-0.97], p = 0.002), and the relationship was partially mediated by plasma n-3 PUFA levels (omega-3 PUFAs: proportion of mediation = 57.99%; DHA: proportion of mediation = 56.95%). Furthermore, we observed significant associations of plasma n-3 PUFA levels and fish oil supplementation with peripheral immune markers that were related to dementia risk, as well as the positive associations of plasma PUFA levels with brain gray matter volumes and white matter microstructural integrity, suggesting they may affect dementia risk by affecting peripheral immunity and brain structure. Taken together, higher plasma PUFA levels and fish oil supplementation were associated with lower risk of incident dementia. This study may support the value of interventions to target PUFAs (specifically n-3 PUFAs) to prevent dementia.

Association between cumulative smoking exposure and cognitive decline in non-demented older adults: NEDICES study

Whether cumulative smoking exposure is associated with cognitive decline among older adults remains unresolved. To address this question, we used data from the Neurological Disorders in Central Spain (NEDICES) cohort study, in which 2624 older adults were evaluated at two-time points separated by three years. A 37-item version of the Mini-Mental State Examination (MMSE-37) was administered at two visits to assess cognitive change. Regarding smoking exposure, we calculated an individual baseline score based on pack-years (i.e., packs of cigarettes smoked per day multiplied by years of smoking) in current and former smokers. Thus, smoking exposure was categorized into tertiles (low: < 19.0, medium: 19.0-47.0, and high: > 47.0). We used multivariable generalized estimating equation models to assess associations between pack-years and smoking status with 37-MMSE total score change from baseline to follow-up. The MMSE-37 total score had a decline of 1.05 points (confidence interval [CI] 95% 0.62 to 1.48) in the lower tertile of pack-years, 1.16 (CI 95% 0.70 to 1.62) in the middle tertile and 1.17 (CI 95% 0.70 to 1.65) in the higher tertile compared to never smokers, after adjusting for several demographic and clinical variables. The same occurred with smoking status, i.e., a decline of 1.33 (CI 95% 0.87 to 1.79) in current smokers and 1.01 (CI 95% 0.63 to 1.40) in former smokers. Our study provides evidence of the cumulative effect of smoking on cognition in older adults. Using a prospective population-based design, we demonstrated that cumulative smoking exposure was associated with cognitive decline in non-demented older adults. More population-based evidence is required to elucidate this association in older adults without dementia.

Apolipoprotein E ε4 disrupts oligodendrocyte differentiation by interfering with astrocyte-derived lipid transport

Carriers of the APOE4 (apolipoprotein E ε4) variant of the APOE gene are subject to several age-related health risks, including Alzheimer's disease (AD). The deficient lipid and cholesterol transport capabilities of the APOE4 protein are one reason for the altered risk profile. In particular, APOE4 carriers are at elevated risk for sporadic AD. While deposits o misfolded proteins are present in the AD brain, white matter (WM) myelin is also disturbed. As myelin is a lipid- and cholesterol-rich structure, the connection to APOE makes considerable biological sense. To explore the APOE-WM connection, we have analyzed the impact of human APOE4 on oligodendrocytes (OLs) of the mouse both in vivo and in vitro. We find that APOE proteins is enriched in astrocytes but sparse in OL. In human APOE4 (hAPOE4) knock-in mice, myelin lipid content is increased but the density of major myelin proteins (MBP, MAG, and PLP) is largely unchanged. We also find an unexpected but significant reduction of cell density of the OL lineage (Olig2+ ) and an abnormal accumulation of OL precursors (Nkx 2.2+ ), suggesting a disruption of OL differentiation. Gene ontology analysis of an existing RNA-seq dataset confirms a robust transcriptional response to the altered chemistry of the hAPOE4 mouse brain. In culture, the uptake of astrocyte-derived APOE during Lovastatin-mediated depletion of cholesterol synthesis is sufficient to sustain OL differentiation. While endogenous hAPOE protein isoforms have no effects on OL development, exogenous hAPOE4 abolishes the ability of very low-density lipoprotein to restore myelination in Apoe-deficient, cholesterol-depleted OL. Our data suggest that APOE4 impairs myelination in the aging brain by interrupting the delivery of astrocyte-derived lipids to the oligodendrocytes. We propose that high myelin turnover and OL exhaustion found in APOE4 carriers is a likely explanation for the APOE-dependent myelin phenotypes of the AD brain.

Therapeutic Inhalation of Hydrogen Gas for Alzheimer’s Disease Patients and Subsequent Long-Term Follow-Up as a Disease-Modifying Treatment: An Open Label Pilot Study

(1) Background: Alzheimer’s disease (AD) is a progressive and fatal neurodegenerative disorder. Hydrogen gas (H2) is a therapeutic medical gas with multiple functions such as anti-oxidant, anti-inflammation, anti-cell death, and the stimulation of energy metabolism. To develop a disease-modifying treatment for AD through multifactorial mechanisms, an open label pilot study on H2 treatment was conducted. (2) Methods: Eight patients with AD inhaled 3% H2 gas for one hour twice daily for 6 months and then followed for 1 year without inhaling H2 gas. The patients were clinically assessed using the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-cog). To objectively assess the neuron integrity, diffusion tensor imaging (DTI) with advanced magnetic resonance imaging (MRI) was applied to neuron bundles passing through the hippocampus. (3) Results: The mean individual ADAS-cog change showed significant improvement after 6 months of H2 treatment (−4.1) vs. untreated patients (+2.6). As assessed by DTI, H2 treatment significantly improved the integrity of neurons passing through the hippocampus vs. the initial stage. The improvement by ADAS-cog and DTI assessments were maintained during the follow-up after 6 months (significantly) or 1 year (non-significantly). (4) Conclusions: This study suggests that H2 treatment not only relieves temporary symptoms, but also has disease-modifying effects, despite its limitations.

Brain recovery of the NAc fibers and prediction of craving changes in person with heroin addiction: A longitudinal study

BACKGROUND

Progress have been made in brain function recovery after long-term abstinence in person with heroin addiction (PHA). However, less is known about whether the nucleus accumbens (NAc) white matter pathways can recover in PHA by prolonged abstinence.

METHODS

Forty-two PHA and Thirty-nine age- and gender- matched healthy controls (HCs) were recruited. Two MRI scans were obtained at baseline (PHA1) and 8-month follow-up (PHA2). We employed tractography atlas-based analysis (TABS) method to investigate fractional anisotropy (FA) changes in NAc fiber tracts (i.e., Insula-NAc, ventral tegmental area (VTA)-NAc, medial prefrontal cortex (MPFC)-NAc) in PHA. A partial least square regression (PLSR) analysis was carried to explore whether FA of NAc fiber tracts can predict longitudinal craving changes.

RESULTS

Relative to HCs, lower FA was found in the right Insula-NAc and VTA-NAc fiber tracts in PHA1, and PHA2 showed increased FA values in these tracts compared with PHA1. Furthermore, changes of FA of NAc fiber tracts can predict longitudinal craving changes (r = 0.51). Additionally, craving changes can also be predicted from FA changes in the left Insula-NAc (r = 0.601) and VTA-NAc (r = 0.384) fiber alone.

CONCLUSIONS

Results indicated that the right Insula-NAc and VTA-NAc fiber tracts are potential biomarkers for brain recovery. Prediction of craving changes highlighted the utility of structural markers to inform clinical decision-making of treatment for PHA.

Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease

The causes of the neurodegenerative processes in Alzheimer's disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole-brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid-beta (Aβ₄₂ ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole-brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aβ₄₂ alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aβ₄₂ , phosphorylated tau protein (p-Tau) and total tau (t-Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p-Tau and t-Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early-stage disease and patients with Alzheimer's disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.

Differences in structural MRI and diffusion tensor imaging underlie visuomotor performance declines in older adults with an increased risk for Alzheimer's disease

Introduction

Visuomotor impairments have been demonstrated in preclinical AD in individuals with a positive family history of dementia and APOE e4 carriers. Previous behavioral findings have also reported sex-differences in performance of visuomotor tasks involving a visual feedback reversal. The current study investigated the relationship between grey and white matter changes and non-standard visuomotor performance, as well as the effects of APOE status, family history of dementia, and sex on these brain-behavior relationships.

Methods

Older adults (n = 49) with no cognitive impairments completed non-standard visuomotor tasks involving a visual feedback reversal, plane-change, or combination of the two. Participants with a family history of dementia or who were APOE e4 carriers were considered at an increased risk for AD. T1-weighted anatomical scans were used to quantify grey matter volume and thickness, and diffusion tensor imaging measures were used to quantify white matter integrity.

Results

In APOE e4 carriers, grey and white matter structural measures were associated with visuomotor performance. Regression analyses showed that visuomotor deficits were predicted by lower grey matter thickness and volume in areas of the medial temporal lobe previously implicated in visuomotor control (entorhinal and parahippocampal cortices). This finding was replicated in the diffusion data, where regression analyses revealed that lower white matter integrity (lower FA, higher MD, higher RD, higher AxD) was a significant predictor of worse visuomotor performance in the forceps minor, forceps major, cingulum, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Some of these tracts overlap with those important for visuomotor integration, namely the forceps minor, forceps major, SLF, IFOF, and ILF.

Conclusion

These findings suggest that measuring the dysfunction of brain networks underlying visuomotor control in early-stage AD may provide a novel behavioral target for dementia risk detection that is easily accessible, non-invasive, and cost-effective. The results also provide insight into the structural differences in inferior parietal lobule that may underlie previously reported sex-differences in performance of the visual feedback reversal task.

Diet Control and Swimming Exercise Ameliorate HFD-Induced Cognitive Impairment Related to the SIRT1-NF-κB/PGC-1α Pathways in ApoE-/- Mice

High-fat diet- (HFD-) induced neuroinflammation may ultimately lead to an increased risk of cognitive impairment. Here, we evaluate the effects of diet control and swimming or both on the prevention of cognitive impairment by enhancing SIRT1 activity. Twenty-week-old ApoE-/- mice were fed a HFD for 8 weeks and then were treated with diet control and/or swimming for 8 weeks. Cognitive function was assessed using the novel object recognition test (NORT) and Y-maze test. The expression of sirtuin-1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), brain-derived neurotrophic factor (BDNF), nuclear factor kappa B p65 (NF-κB p65), interleukin-1β (IL-1β), and tumour necrosis factor-α (TNF-α) in the hippocampus was measured by western blotting. The levels of fractional anisotropy (FA), N-acetylaspartate (NAA)/creatine (Cr) ratio, choline (Cho)/Cr ratio, and myo-inositol (MI)/Cr ratio in the hippocampus were evaluated by diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) using 7.0-T magnetic resonance imaging (MRI). Our results showed that cognitive dysfunction and hippocampal neuroinflammation appeared to be remarkably observed in apolipoprotein E (ApoE)-/- mice fed with HFD. Diet control plus swimming significantly reversed HFD-induced cognitive decline, reduced the time spent exploring the novel object, and ameliorated spontaneous alternation in the Y-maze test. Compared with the HFD group, ApoE-/- mice fed diet control and/or subjected to swimming had an increase in FA, NAA/Cr, and Cho/Cr; a drop in MI/Cr; elevated expression levels of SIRT1, PGC-1α, and BDNF; and inhibited production of proinflammatory cytokines, including NF-κB p65, IL-1β, and TNF-α. SIRT1, an NAD⁺-dependent class III histone enzyme, deacetylases and regulates the activity of PGC-1α and NF-κB. These data indicated that diet control and/or swimming ameliorate cognitive deficits through the inhibitory effect of neuroinflammation via SIRT1-mediated pathways, strongly suggesting that swimming and/or diet control could be potentially effective nonpharmacological treatments for cognitive impairment.

Neurobiological Mechanisms of Cognitive Decline Correlated with Brain Aging

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

Longitudinal White and Gray Matter Response to Precision Medicine-Guided Intervention for Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a debilitating condition that is widely known to adversely affect gray matter (GM) and white matter (WM) tracts within the brain. Recently, precision medicine has shown promise in alleviating the clinical and gross morphological trajectories of patients with AD. However, regional morphological changes have not yet been adequately characterized.

OBJECTIVE

Investigate regional morphological responses to a precision medicine-guided intervention with regards to white and gray matter in AD and mild cognitive impairment (MCI).

METHODS

Clinical and neuroimaging data were compiled over a 9-month period from 25 individuals who were diagnosed with AD or MCI receiving individualized treatment plans. Structural T1-weighted MRI scans underwent segmentation and volumetric quantifications via Neuroreader. Longitudinal changes were calculated via annualized percent change of WM or GM ratios.

RESULTS

Montreal Cognitive Assessment scores (p < 0.001) and various domains of the Computerized Neurocognitive Screening Vital Signs significantly improved from baseline to 9-month follow-up. There was regional variability in WM and GM atrophy or hypertrophy, but none of these observed changes were statistically significant after correction for multiple comparisons.

Alterations of brain microstructures in a mouse model of prenatal opioid exposure detected by diffusion MRI

Growing opioid use among pregnant women is fueling a crisis of infants born with prenatal opioid exposure. A large body of research has been devoted to studying the management of opioid withdrawal during the neonatal period in these infants, but less substantive work has explored the long-term impact of prenatal opioid exposure on neurodevelopment. Using a translationally relevant mouse model of prenatal methadone exposure (PME), the aim of the study is to investigate the cerebral microstructural differences between the mice with PME and prenatal saline exposure (PSE). The brains of eight-week-old male offspring with either PME (n = 15) or PSE (n = 15) were imaged using high resolution in-vivo diffusion magnetic resonance imaging on a 9.4 Tesla small animal scanner. Brain microstructure was characterized using diffusion tensor imaging (DTI) and Bingham neurite orientation dispersion and density imaging (Bingham-NODDI). Voxel-based analysis (VBA) was performed using the calculated microstructural parametric maps. The VBA showed significant (p < 0.05) bilateral alterations in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI) and dispersion anisotropy index (DAI) across several cortical and subcortical regions, compared to PSE. Particularly, in PME offspring, FA, MD and AD were significantly higher in the hippocampus, dorsal amygdala, thalamus, septal nuclei, dorsal striatum and nucleus accumbens. These DTI-based results suggest widespread bilateral microstructural alterations across cortical and subcortical regions in PME offspring. Consistent with the observations in DTI, Bingham-NODDI derived ODI exhibited significant reduction in PME offspring within the hippocampus, dorsal striatum and cortex. NODDI-based results further suggest reduction in dendritic arborization in PME offspring across multiple cortical and subcortical regions. To our best knowledge, this is the first study of prenatal opioid exposure to examine microstructural organization in vivo. Our findings demonstrate perturbed microstructural complexity in cortical and subcortical regions persisting into early adulthood which could interfere with critical neurodevelopmental processes in individuals with prenatal opioid exposure.

Actigraphy-estimated physical activity is associated with functional and structural brain connectivity among older adults

Higher physical activity levels are associated with reduced cognitive decline among older adults; however, current understanding of underlying brain mechanisms is limited. This cross-sectional study investigated the relationship between actigraphy-estimated total volume of physical activity (TVPA) and magnetic resonance imaging (MRI) measures of white matter hyperintensities (WMH), and functional and structural brain connectivity, measured by resting-state functional MRI and diffusion tensor imaging. Study participants (N = 156, mean age = 71 years) included 136 with normal cognition and 20 with Mild Cognitive Impairment. Higher TVPA was associated with greater functional connectivity within the default-mode network and greater network modularity (a measure of network specialization), as well as with greater anisotropy and lower radial diffusion in white matter, suggesting better structural connectivity. These associations with functional and structural connectivity were independent of one another and independent of the level of vascular risk, APOE-ε4 status, cognitive reserve, and WMH volume, which were not associated with TVPA. Findings suggest that physical activity is beneficial for brain connectivity among older individuals with varying levels of risk for cognitive decline.

Does Loss of Integrity of the Cingulum Bundle Link Amyloid-β Accumulation and Neurodegeneration in Alzheimer’s Disease?

Background: Alzheimer’s disease is characterized by the accumulation of amyloid-β (Aβ) into plaques, aggregation of tau into neurofibrillary tangles, and neurodegenerative processes including atrophy. However, there is a poorly understood spatial discordance between initial Aβ deposition and local neurodegeneration. Objective: Here, we test the hypothesis that the cingulum bundle links Aβ deposition in the cingulate cortex to medial temporal lobe (MTL) atrophy. Methods: 21 participants with mild cognitive impairment (MCI) from the UMC Utrecht memory clinic (UMCU, discovery sample) and 37 participants with MCI from Alzheimer’s Disease Neuroimaging Initiative (ADNI, replication sample) with available Aβ-PET scan, T1-weighted and diffusion-weighted MRI were included. Aβ load of the cingulate cortex was measured by the standardized uptake value ratio (SUVR), white matter integrity of the cingulum bundle was assessed by mean diffusivity and atrophy of the MTL by normalized MTL volume. Relationships were tested with linear mixed models, to accommodate multiple measures for each participant. Results: We found at most a weak association between cingulate Aβ and MTL volume (added R2 <0.06), primarily for the posterior hippocampus. In neither sample, white matter integrity of the cingulum bundle was associated with cingulate Aβ or MTL volume (added R2 <0.01). Various sensitivity analyses (Aβ-positive individuals only, posterior cingulate SUVR, MTL sub region volume) provided similar results. Conclusion: These findings, consistent in two independent cohorts, do not support our hypothesis that loss of white matter integrity of the cingulum is a connecting factor between cingulate gyrus Aβ deposition and MTL atrophy.

Diffusion Tensor Imaging Profiles Can Distinguish Diffusivity and Neural Properties of White Matter Injury in Hydrocephalus vs. Non-hydrocephalus Using a Strategy of a Periodic Table of DTI Elements

Background:

The aim of this study was to create a simplistic taxonomy to improve transparency and consistency in, and reduce complexity of, interpreting diffusion tensor imaging (DTI) profiles in white matter disruption. Using a novel strategy of a periodic table of DTI elements, we examined if DTI profiles could demonstrate neural properties of disruption sufficient to characterize white matter changes specific for hydrocephalus vs. non-hydrocephalus, and to distinguish between cohorts of neural injury by their differing potential for reversibility.

Methods

DTI datasets from three clinical cohorts representing pathological milestones from reversible to irreversible brain injury were compared to those of healthy controls at baseline, over time and with interventions. The final dataset comprised patients vs. controls in the following groupings: mild traumatic brain injury (mTBI), n = 24 vs. 27, normal pressure hydrocephalus (NPH), n = 16 vs. 9 and Alzheimer's disease (AD), n = 27 vs. 47. We generated DTI profiles from fractional anisotropy (FA) and mean, axial and radial diffusivity measures (MD, L1 and L2 and 3 respectively), and constructed an algorithm to map changes consistently to a periodic table of elements, which fully described their diffusivity and neural properties.

Results

Mapping tissue signatures to a periodic table of DTI elements rapidly characterized cohorts by their differing patterns of injury. At baseline, patients with mTBI displayed the most preserved tracts. In NPH, the magnitude of changes was dependent on “familial” DTI neuroanatomy, i.e., potential for neural distortion from risk of ventriculomegaly. With time, patients with Alzheimer's disease were significantly different to controls across multiple measures. By contrast, patients with mTBI showed both loss of integrity and pathophysiological processes of neural repair. In NPH, some patterns of injury, such as “stretch/compression” and “compression” were more reversible following intervention than others; these neural profile properties suggested “microstructural resilience” to injury.

Conclusion

Using the novel strategy of a periodic table of DTI elements, our study has demonstrated it is possible to distinguish between different cohorts along the spectrum of brain injury by describing neural profile properties of white matter disruption. Further work to contribute datasets of disease toward this proposed taxonomic framework would enhance the translatability of DTI profiles to the clinical-research interface.

Apolipoprotein E ε4 Mediates Myelin Breakdown by Targeting Oligodendrocytes in Sporadic Alzheimer Disease

White matter degradation in the frontal lobe is one of the earliest detectable changes in aging and Alzheimer disease. The ε4 allele of apolipoprotein E (APOE4) is strongly associated with such myelin pathology but the underlying cellular mechanisms remain obscure. We hypothesized that, as a lipid transporter, APOE4 directly triggers pathology in the cholesterol-rich myelin sheath independent of AD pathology. To test this, we performed immunohistochemistry on brain tissues from healthy controls, sporadic, and familial Alzheimer disease subjects. While myelin basic protein expression was largely unchanged, in frontal cortex the number of oligodendrocytes (OLs) was significantly reduced in APOE4 brains independent of their Braak stage or NIA-RI criteria. This high vulnerability of OLs was confirmed in humanized APOE3 or APOE4 transgenic mice. A gradual decline of OL numbers was found in the aging brain without associated neuronal loss. Importantly, the application of lipidated human APOE4, but not APOE3, proteins significantly reduced the formation of myelinating OL in primary cell culture derived from Apoe-knockout mice, especially in cholesterol-depleted conditions. Our findings suggest that the disruption of myelination in APOE4 carriers may represent a direct OL pathology, rather than an indirect consequence of amyloid plaque formation or neuronal loss.

Structural and functional connectivity abnormalities of the default mode network in patients with Alzheimer's disease and mild cognitive impairment within two independent datasets

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive dementia, and amnestic mild cognitive impairment (aMCI) has been defined as a transitional stage between normal aging and AD. Accumulating evidence has shown that altered functional connectivity (FC) and structural connectivity (SC) in the default mode network (DMN) is the prominent hallmarks of AD. However, the relationship between the changes in SC and FC of the DMN is not yet clear. In the present study, we derived the FC and SC matrices of the DMN with functional magnetic resonance imaging (fMRI) and diffusion-weighted imaging (DWI) data and further assessed FC and SC abnormalities within a discovery dataset of 120 participants (39 normal controls, 34 patients with aMCI and 47 patients with AD), as well as a replication dataset of 122 participants (43 normal controls, 37 patients with aMCI and 42 patients with AD). Disrupted SC and FC were found among DMN components (e.g., the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), and hippocampus) in patients in the aMCI and AD groups in the discovery dataset; most of the disrupted connections were also identified in the replication dataset. More importantly, some SC and FC elements were significantly correlated with the cognitive ability of patients with aMCI and AD. In addition, we found structural-functional decoupling between the PCC and the right hippocampus in patients in the aMCI and AD groups. These findings of the alteration of DMN connectivity in neurodegenerative cohorts deepen our understanding of the pathophysiological mechanisms of AD.

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.

Brain-behavior investigation of potential cognitive markers of Alzheimer's disease in middle age: a multi-modal imaging study

Early detection of Alzheimer's disease remains a challenge, and the development and validation of novel cognitive markers of Alzheimer's disease is critical to earlier disease detection. The goal of the present study is to examine brain-behavior relationships of translational cognitive paradigms dependent on the medial temporal lobes and prefrontal cortices, regions that are first to undergo Alzheimer's-associated changes. We employed multi-modal structural and functional MRI to examine brain-behavior relationships in a healthy, middle-aged sample (N = 133; 40-60 years). Participants completed two medial temporal lobe-dependent tasks (virtual Morris Water Task and Transverse Patterning Discriminations Task), and a prefrontal cortex-dependent task (Reversal Learning Task). No associations were found between various MRI measures of brain integrity and the Transverse Patterning or Reversal Learning tasks (p's > .05). We report associations between virtual Morris Water Task performance and medial temporal lobe volume, hippocampal microstructural organization, fornix integrity, and functional connectivity within the executive control and frontoparietal control resting state networks (all p's < 0.05; did not survive correction for multiple comparisons). This study suggests that virtual Morris Water Task performance is associated with medial temporal lobe integrity in middle age, a critical window for detection and prevention of Alzheimer's disease, and may be useful as an early cognitive marker of Alzheimer's disease risk.

Regional Brain Fusion: Graph Convolutional Network for Alzheimer's Disease Prediction and Analysis

Alzheimer's disease (AD) has raised extensive concern in healthcare and academia as one of the most prevalent health threats to the elderly. Due to the irreversible nature of AD, early and accurate diagnoses are significant for effective prevention and treatment. However, diverse clinical symptoms and limited neuroimaging accuracy make diagnoses challenging. In this article, we built a brain network for each subject, which assembles several commonly used neuroimaging data simply and reasonably, including structural magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and amyloid positron emission tomography (PET). Based on some existing research results, we applied statistical methods to analyze (i) the distinct affinity of AD burden on each brain region, (ii) the topological lateralization between left and right hemispheric sub-networks, and (iii) the asymmetry of the AD attacks on the left and right hemispheres. In the light of advances in graph convolutional networks for graph classifications and summarized characteristics of brain networks and AD pathologies, we proposed a regional brain fusion-graph convolutional network (RBF-GCN), which is constructed with an RBF framework mainly, including three sub-modules, namely, hemispheric network generation module, multichannel GCN module, and feature fusion module. In the multichannel GCN module, the improved GCN by our proposed adaptive native node attribute (ANNA) unit embeds within each channel independently. We not only fully verified the effectiveness of the RBF framework and ANNA unit but also achieved competitive results in multiple sets of AD stages' classification tasks using hundreds of experiments over the ADNI clinical dataset.

Plasma phosphorylated-tau181 levels reflect white matter microstructural changes across Alzheimer's disease progression

Alzheimer's Disease (AD) is characterized by cognitive impairments that hinder daily activities and lead to personal and behavioral problems. Plasma hyperphosphorylated tau protein at threonine 181 (p-tau181) has recently emerged as a new sensitive tool for the diagnosis of AD patients. We herein investigated the association of plasma P-tau181 and white matter (WM) microstructural changes in AD. We obtained data from a large prospective cohort of elderly individuals participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI), which included baseline measurements of plasma P-tau181 and imaging findings. A subset of 41 patients with AD, 119 patients with mild cognitive impairments (MCI), and 43 healthy controls (HC) was included in the study, all of whom had baseline blood P-tau181 levels and had also undergone Diffusion Tensor Imaging. The analysis revealed that the plasma level of P-tau181 has a positive correlation with changes in Mean Diffusivity (MD), Radial Diffusivity (RD), and Axial Diffusivity (AxD), but a negative with Fractional Anisotropy (FA) parameters in WM regions of all participants. There is also a significant association between WM microstructural changes in different regions and P-tau181 plasma measurements within each MCI, HC, and AD group. In conclusion, our findings clarified that plasma P-tau181 levels are associated with changes in WM integrity in AD. P-tau181 could improve the accuracy of diagnostic procedures and support the application of blood-based biomarkers to diagnose WM neurodegeneration. Longitudinal clinical studies are also needed to demonstrate the efficacy of the P-tau181 biomarker and predict its role in structural changes.

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.

Segmental Abnormalities of White Matter Microstructure in End-Stage Renal Disease Patients: An Automated Fiber Quantification Tractography Study

Background and Purpose: End-stage renal disease (ESRD) results in extensive white matter abnormalities, but the specific damage segment cannot be identified. This study aimed to determine the segmental abnormalities of white matter microstructure in ESRD and its relationship with cognitive and renal function indicators. Methods: Eighteen ESRD patients and 19 healthy controls (HCs) were prospectively recruited. All participants underwent DTI and clinical assessments. Automatic fiber quantification (AFQ) was applied to generate bundle profiles along 16 main white matter tracts. We compared the DTI parameters between groups. Besides, we used partial correlation and multiple linear regression analyses to explore the associations between white matter integrity and cognitive performance as well as renal function indicators. Results: In the global tract level, compared to HCs, ESRD patients had greater MD, AD, and RD values and lower FA value in several fibers (P < 0.05, FDR correction). In the point-wise level, extensive damage existed in specific locations of different fiber tracts, particularly in the left hemisphere (P < 0.05, FDR correction). Among these tracts, the mean AD values of the left cingulum cingulate correlated negatively with MoCA score. Urea and UA level were independent predictors of the AD value of superior component of the left corticospinal. Besides, urea level was the independent predictors of mean MD value of left anterior thalamic radiation (ATR). Conclusion: White matter fiber tract damage in ESRD patients may be characterized by abnormalities in its specific location, especially in the left hemisphere. Aberrational specific located fibers were related to cognitive impairment and renal dysfunction.

Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study

Pathological cerebral white matter changes in Alzheimer's disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer's disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer's disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants' diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer's disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer's disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer's disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer's disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer's disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter.

The role of multimodal MRI in mild cognitive impairment and Alzheimer's disease

BACKGROUND AND PURPOSE

Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD), where neurodegeneration is not as considerable, thereby potentially increasing the effect of treatments. Therefore, highly sensitive and specific classification of subjects with MCI is necessary, where various MRI modalities have displayed promise.

METHODS

Structural, diffusion, and resting-state (RS) functional MRI analyses were performed on the AD (n = 26), MCI (n = 5), and healthy control (HC) (n = 14) group. Structural analysis was performed via voxel-based morphometry (VBM) and volumetric subcortical segmentation analysis. Fractional anisotropy and mean diffusivity were estimated during the diffusion analysis. RS analysis investigated seed-based functional connectivity. Classification via support vector machine was performed to evaluate which MRI modality most accurately differentiated the groups. Multiple linear regression was conducted to evaluate the MRI modalities correlation with clinical assessment scores.

RESULTS

Classification of MCI and HC displayed highest accuracy based on diffusion MRI, which besides demonstrated high correlation with clinical scores. Classification was equally accurate in AD, when using VBM or diffusion tensor imaging measures. Yet, more variance was explained by VBM measures in the clinical assessment scores of the AD group.

CONCLUSIONS

This study highlights the potential of diffusion MRI in differentiating MCI from HC and AD. However, the results need to be interpreted with caution as sample size and artifacts in the MRI data probably influenced the results.

The Associations Between White Matter Disruptions and Cognitive Decline at the Early Stage of Subcortical Vascular Cognitive Impairment: A Case-Control Study

Objective

Emerging evidence suggests that white matter (WM) disruption is associated with the incidence of subcortical vascular cognitive impairment (SVCI). However, our knowledge regarding this relationship in the early stage of SVCI is limited. We aimed to investigate the associations between WM disruptions and cognitive declines at the early stage of SVCI.

Method

We performed a case–control study, involving 22 cases and 19 controls. The cases were patients at the early stage of SVCI, which was defined as subcortical ischemic vascular disease with normal global cognitive measures (pre-SVCI). The controls were healthy people matched by age, sex, and education years. We assessed the differences in a battery of neuropsychological tests between the two groups, investigated the diffusion changes in 40 WM tracts among the participants via an atlas-based segmentation strategy, and compared the differences between the cases and controls by multiple linear regression analysis. We then evaluated the relationships between diffusion indices and cognitive assessment scores by Pearson’s correlation.

Results

The pre-SVCI group exhibited significant differences in the Montreal cognitive assessment (MoCA), Rey–Osterrieth Complex Figure (R-O)-copy, and Trail Making Test (TMT)-B test compared with the controls. Compared with the controls, some long associative and projective bundles, such as the right anterior corona radiata (ACR), the right inferior fronto-occipital fasciculus (IFOF), and the left external capsule (EC), were extensively damaged in cases after Bonferroni correction (p < 0.05/40). Damages to specific fibers, such as the right ACR, IFOF, and posterior thalamic radiation (PTR), exhibited significant correlations with declines in MoCA, R-O delay, and the Mini-Mental State Examination (MMSE), respectively, after Bonferroni correction (p < 0.05/14).

Conclusion

Long WM tracts, especially those in the right hemisphere, were extensively damaged in the pre-SVCI patients and correlated with declines in executive functions and spatial processing. Patients of pre-SVCI are likely at an ultra-early stage of SVCI, and there is a very high risk of this condition becoming SVCI.

Combined Support Vector Machine Classifier and Brain Structural Network Features for the Individual Classification of Amnestic Mild Cognitive Impairment and Subjective Cognitive Decline Patients

OBJECTIVE

Individuals with subjective cognitive decline (SCD) or amnestic mild cognitive impairment (aMCI) represent important targets for the early detection and intervention of Alzheimer's disease (AD). In this study, we employed a multi-kernel support vector machine (SVM) to examine whether white matter (WM) structural networks can be used for screening SCD and aMCI.

METHODS

A total of 138 right-handed participants [51 normal controls (NC), 36 SCD, 51 aMCI] underwent MRI brain scans. For each participant, three types of WM networks with different edge weights were constructed with diffusion MRI data: fiber number-weighted networks, mean fractional anisotropy-weighted networks, and mean diffusivity (MD)-weighted networks. By employing a multiple-kernel SVM, we seek to integrate information from three weighted networks to improve classification performance. The accuracy of classification between each pair of groups was evaluated via leave-one-out cross-validation.

RESULTS

For the discrimination between SCD and NC, an area under the curve (AUC) value of 0.89 was obtained, with an accuracy of 83.9%. Further analysis revealed that the methods using three types of WM networks outperformed other methods using single WM network. Moreover, we found that most of discriminative features were from MD-weighted networks, which distributed among frontal lobes. Similar classification performance was also reported in the differentiation between subjects with aMCI and NCs (accuracy = 83.3%). Between SCD and aMCI, an AUC value of 0.72 was obtained, with an accuracy of 72.4%, sensitivity of 74.5% and specificity of 69.4%. The highest accuracy was achieved with features only selected from MD-weighted networks.

CONCLUSION

White matter structural network features help machine learning algorithms accurately identify individuals with SCD and aMCI from NCs. Our findings have significant implications for the development of potential brain imaging markers for the early detection of AD.

Specific White Matter Tracts and Diffusion Properties Predict Conversion From Mild Cognitive Impairment to Alzheimer's Disease

Identifying biomarkers that can assess the risk of developing Alzheimer's Disease (AD) remains a significant challenge. In this study, we investigated the integrity levels of brain white matter in 34 patients with mild cognitive impairment (MCI) who later converted to AD and 53 stable MCI patients. We used diffusion tensor imaging (DTI) and automated fiber quantification to obtain the diffusion properties of 20 major white matter tracts. To identify which tracts and diffusion measures are most relevant to AD conversion, we used support vector machines (SVMs) to classify the AD conversion and non-conversion MCI patients based on the diffusion properties of each tract individually. We found that diffusivity measures from seven white matter tracts were predictive of AD conversion with axial diffusivity being the most predictive diffusion measure. Additional analyses revealed that white matter changes in the central and parahippocampal terminal regions of the right cingulate hippocampal bundle, central regions of the right inferior frontal occipital fasciculus, and posterior and anterior regions of the left inferior longitudinal fasciculus were the best predictors of conversion from MCI to AD. An SVM based on these white matter tract regions achieved an accuracy of 0.75. These findings provide additional potential biomarkers of AD risk in MCI patients.

Diffusion MRI detects basal forebrain cholinergic abnormalities in the 3xTg-AD mouse model of Alzheimer's disease

Degeneration of the basal forebrain (BF) is detected early in the course of Alzheimer's disease (AD). Reduction in the number of BF cholinergic (ChAT) neurons associated with age-related hippocampal cholinergic neuritic dystrophy is described in the 3xTg-AD mouse model; however, no prior diffusion MRI (dMRI) study has explored the presence of BF alterations in this model. Here we investigated the ability of diffusion MRI (dMRI) to detect abnormalities in BF microstructure for the 3xTg-AD mouse model, along with related pathology in the hippocampus (HP) and white matter (WM) tracks comprising the septo-hippocampal pathway. 3xTg-AD and normal control (NC) mice were imaged in vivo using the specific dMRI technique known as diffusional kurtosis imaging (DKI) at 2, 8, and 15 months of age, and 8 dMRI parameters were measured at each time point. Our results revealed significant lower dMRI values in the BF of 2 months-old 3xTg-AD mice compared with NC mice, most likely related to the increased number of ChAT neurons seen in this AD mouse model at this age. They also showed significant age-related dMRI changes in the BF of both groups between 2 and 8 months of age, mainly a decrease in fractional anisotropy and axial diffusivity, and an increase in radial kurtosis. These dMRI changes in the BF may be reflecting the complex aging and pathological microstructural changes described in this region. Group differences and age-related changes were also observed in the HP, fimbria (Fi) and fornix (Fx). In the HP, diffusivity values were significantly higher in the 2 months-old 3xTg-AD mice, and the HP of NC mice showed a significant increase in axial kurtosis after 8 months, reflecting a normal pattern of increased fiber density complexity, which was not seen in the 3xTg-AD mice. In the Fi, mean and radial diffusivity values were significantly higher, and fractional anisotropy, radial kurtosis and kurtosis fractional anisotropy were significantly lower in the 2 months-old 3xTg-AD mice. The age trajectories for both NC and TG mice in the Fi and Fx were similar between 2 and 8 months, but after 8 months there was a significant decrease in diffusivity metrics associated with an increase in kurtosis metrics in the 3xTg-AD mice. These later HP, Fi and Fx dMRI changes probably reflect the growing number of dystrophic neurites and AD pathology progression in the HP, accompanied by WM disruption in the septo-hippocampal pathway. Our results demonstrate that dMRI can detect early cytoarchitectural abnormalities in the BF, as well as related aging and neurodegenerative changes in the HP, Fi and Fx of the 3xTg-AD mice. Since DKI is widely available on clinical scanners, these results also support the potential of the considered dMRI parameters as in vivo biomarkers for AD disease progression.

Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer's disease

Beta-amyloid (Aβ) and tau proteins, the pathological hallmarks of Alzheimer's disease (AD), are believed to spread through connected regions of the brain. Combining diffusion imaging and positron emission tomography, we investigated associations between white matter microstructure specifically in bundles connecting regions where Aβ or tau accumulates and pathology. We focused on free-water-corrected diffusion measures in the anterior cingulum, posterior cingulum, and uncinate fasciculus in cognitively normal older adults at risk of sporadic AD and presymptomatic mutation carriers of autosomal dominant AD. In Aβ-positive or tau-positive groups, lower tissue fractional anisotropy and higher mean diffusivity related to greater Aβ and tau burden in both cohorts. Associations were found in the posterior cingulum and uncinate fasciculus in preclinical sporadic AD, and in the anterior and posterior cingulum in presymptomatic mutation carriers. These results suggest that microstructural alterations accompany pathological accumulation as early as the preclinical stage of both sporadic and autosomal dominant AD.