Abnormal white matter independent of hippocampal atrophy in amnestic type mild cognitive impairment

Endocytosis-pathway polygenic scores affects the hippocampal network connectivity and individualized identification across the high-risk of Alzheimer's disease

The neural mechanisms underlying the polygenic effects of the endocytosis pathway on the brain function of Alzheimer's Disease (AD) remain unclear, especially in the prodromal stages of AD from early mild cognitive impairment (EMCI) to late mild cognitive impairment (LMCI). We used an imaging genetic approach to investigate the polygenic effects of the endocytosis pathway on the hippocampal network across the prodromal stages of AD. The subjects' data were selected from the Alzheimer's Disease Neuroimaging Initiative. Hippocampal volumes were examined in subjects of cognitive normal (CN), EMCI and LMCI groups. Multivariate linear regression analysis was employed to measure the effects of disease and endocytosis-based multilocus genetic risk scores (MGRS) on the hippocampal network which was constructed using the bilateral hippocampal regions. We identified hippocampal volumes in LMCI group were smaller than those in CN and EMCI groups. Endocytosis-based MGRS was widely influenced the neural structures within the hippocampal network, especially in the prefrontal-occipital regions and striatum. Compared to low endocytosis-based MGRS carriers, high MGRS carriers showed the opposite trajectory of hippocampal network functional connectivity (FC) across the prodromal stages of AD. Further, a model composed of selected hippocampal FCs and hippocampal volume yielded strong classification powers of EMCI and LMCI. These findings expand our understanding of the pathophysiology of polygenic effects underlying brain network in the prodromal stages of AD.

Diffusion tensor imaging of white matter degeneration in early stage of Alzheimer's disease: a review

Object: Alzheimer's disease is a progressive, irreversible neurodegenerative disorder associated with brain alterations. Diffusion tensor imaging (DTI) has contributed to identify degeneration in white matter cortical microstructural that can be considered an early and specific biomarker for Alzheimer's disease. This review aimed to provide a summary of DTI studies on white matter damage in Alzheimer's disease.Methods: On PubMed, Web of Science and Scopus databases, we reviewed the studies that used DTI for assessing fractional anisotropy in neurofiber tracts involved in Alzheimer's Disease progression: fornix, the cingulum, uncinate fasciculus, superior and inferior longitudinal fasciculus and corpus callosum. We included nine studies that met search criteria.Results: The results showed decreased fractional anisotropy value in mild cognitive impairment (MCI) patients. White matter diffusivity changes were associated with the progression of Alzheimer's disease.Conclusion: Microstructural alterations of the limbic and cortico-cortical tracts could be potential biomarkers for early diagnosis in preclinical disease phase.

White matter microstructural abnormalities in amnestic mild cognitive impairment: A meta-analysis of whole-brain and ROI-based studies

Studies that examined white matter (WM) alterations in amnestic mild cognitive impairment (aMCI) abound. This timely meta-analysis aims to synthesize the results of these studies. Seventy-seven studies (totalN_aMCI=1844) were included. Fourteen region-of-interest-based (ROI-based) (k≥8;N_aMCI≥284 per ROI) and two activation likelihood estimation (ALE) meta-analyses (fractional anisotropy [FA]: k=15;N_aMCI=463; mean diffusivity [MD]: k=8;N_aMCI=193) were carried out. Among the many significant ROI-related findings, reliable FA and MD alterations in the fornix, uncinate fasciculus, and parahippocampal cingulum were observed in aMCI. Larger effects were observed in MD relative to FA. The ALE meta-analysis revealed a significant FA decrease among aMCI subjects in the posterior corona radiata. These results provide robust evidence of the presence of WM abnormalities in aMCI. Our findings also highlight the importance of carrying out both ROI-based and whole-brain-based research to obtain a complete picture of WM microstructural alterations associated with the condition..

Divergent Roles of Vascular Burden and Neurodegeneration in the Cognitive Decline of Geriatric Depression Patients and Mild Cognitive Impairment Patients

Both geriatric depression and mild cognitive impairment (MCI) confer an increased risk for the development of dementia. The mechanisms underlying the development of cognitive impairment in geriatric depression patients remain controversial. The present study aimed to explore the association of cognitive decline with vascular risk, white matter hyperintensity (WMH) burden and hippocampal volume in both remitted geriatric depression (RGD) subjects and amnestic mild cognitive impairment (aMCI) subjects. Forty-one RGD subjects, 51 aMCI subjects, and 64 healthy elderly subjects underwent multimodal MRI scans and neuropsychological tests at both baseline and a 35-month follow-up. According to the changing patterns (declining or stable) of global cognitive function during the follow-up period, each group was further divided into a declining subgroup and a stable subgroup. The Framingham 10-year cardiovascular risk, WMH volume and hippocampal volume were measured to assess vascular pathology and neurodegeneration, respectively. The RGD declining group displayed a higher vascular risk and greater WMH volume than the RGD stable group, whereas no such difference was found in the aMCI subjects. In contrast, the aMCI declining group displayed a smaller left hippocampal volume than the aMCI stable group, whereas no such difference was found in the RGD subjects. Furthermore, greater increases in the WHM volume correlated with greater decreases in global cognitive function in the RGD declining group, and greater decreases in the left hippocampal volume correlated with greater decreases in global cognitive function in the aMCI declining group. In conclusion, the cognitive decline in RGD patients is associated with vascular burden, whereas the cognitive decline in aMCI patients is associated with neurodegeneration. These findings could contribute to a better understanding of the specific mechanisms of the development of dementia in each condition.

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment

Objectives

Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer’s disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI).

Method

MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus.

Results

We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors.

Conclusions

Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI.

Key Points

• PCC functioning during episodic memory relates to hippocampal functioning in MCI.

• PCC functioning during episodic memory does not relate to hippocampal structure in MCI.

• Functional network changes are an important predictor of PCC functioning in MCI.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4768-1) contains supplementary material, which is available to authorized users.

Methodology for computing white matter nerve fiber orientation in human histological slices

BACKGROUND

The gold standard for mapping nerve fiber orientation in white matter of the human brain is histological analysis through biopsy. Such mappings are a crucial step in validating non-invasive techniques for assessing nerve fiber orientation in the human brain by using diffusion MRI. However, the manual extraction of nerve fiber directions of histological slices is tedious, time consuming, and prone to human error.

NEW METHOD

The presented semi-automated algorithm first creates a binary-segmented mask of the nerve fibers in the histological image, and then extracts an estimate of average directionality of nerve fibers through a Fourier-domain analysis of the masked image. It also generates an uncertainty level for its estimate of average directionality.

RESULTS AND COMPARISON WITH EXISTING METHODS

The average orientations of the semi-automatic method were first compared to a qualitative expert opinion based on visual inspection of nerve fibers. A weighted RMS difference between the expert estimate and the algorithmically determined angle (weighted by expert's confidence in his estimate) was 15.4°, dropping to 9.9° when only cases with an expert confidence level of greater than 50% were included. The algorithmically determined angles were then compared with angles extracted using a manual segmentation technique, yielding an RMS difference of 11.2°.

CONCLUSION

The presented semi-automated method is in good agreement with both qualitative and quantitative manual expert-based approaches for estimating directionality of nerve fibers in white matter from images of stained histological slices of the human brain.

Impaired and preserved aspects of feedback learning in aMCI: contributions of structural connectivity

Distinct lines of research demonstrated that patients with amnestic mild cognitive impairment (aMCI), a potential precursor of Alzheimer disease (AD), are particularly impaired in remembering relations between items and that the use of emotional targets can facilitate memory in patients with AD. We link these findings by examining learning through positive and negative feedback in patients with aMCI, and explore its anatomic underpinnings with diffusion tensor imaging and tractography. Compared to healthy controls, patients with single-domain aMCI were impaired in learning from positive feedback, while learning from negative outcomes was preserved. Among pathways within the brain circuit involved in feedback learning, abnormal white matter microstructure was observed in tracts, which connect left-hemispheric amygdala with hippocampus and entorhinal cortex. In all participants, reduced white matter integrity in this left fiber tract was specifically associated with learning from positive outcomes. Microstructure of right-hemispheric tracts between amygdala and entorhinal cortex was related to learning from negative feedback, and was not compromised in aMCI patients. Our results provide new insight into how anatomical connections might contribute to impaired and preserved aspects of learning behaviors in the early AD process and indicate potential compensatory mechanisms.

Abnormal functional connectivity of the default mode network in remitted late-onset depression

BACKGROUND

The functional neural network model has been a major method used to investigate mechanisms of neuropsychopathy. There is considerable evidence that late-onset depression (LOD) is the prodrome, or the early clinical manifestation, of Alzheimer's disease (AD). The default mode network (DMN) is one of the neural networks that can be used to explore the complex relationships between depressive symptoms, episodic memory deficits and other cognitive impairments. To date, no study has directly linked the DMN to LOD while focusing on episodic memory and the influence of apolipoprotein E4 (APOE4), a major genetic risk factor for AD in LOD patients.

METHODS

In total, 33 remitted LOD (rLOD) patients and 33 elderly controls underwent fMRI scanning using low-frequency BOLD signal imaging during the resting state and during an episodic memory task. Furthermore, function-based functional connectivities (FCs) in the region of interesting (ROI) (posterior cingulate cortex (PCC) of the DMN) were analysed to explore interactions between disease states, task states and genetic risk factors (APOE4).

RESULTS

Compared to healthy control subjects (HC), the FCs between the PCC and the right medial temporal lobe of the rLOD patients were significantly stronger during rest (p<0.005) and significantly weaker (p<0.05) during performance of the task. The mode of change from rest to task performance in the HC was in contrast to the mode of change in the rLOD patients. The FCs of the rLOD patients without APOE4 were significantly increased (p<0.05) in the resting state, but the rLOD patients who carried APOE4 showed a trend toward decreased FCs.

LIMITATIONS

The sample size was small. While the study was cross-sectional, we did not differentiate between the various types of antidepressants the patients used, which may have had different effects on cognitive function, especially on episodic memory.

CONCLUSION

Our results suggested that rLOD might be the prodrome, or the early clinical manifestation, of AD and that rLOD patients with APOE4 showed an increased risk for episodic memory decline and AD.

White matter changes in patients with amnestic mild cognitive impairment detected by diffusion tensor imaging

Compared to normal aging adults, individuals with amnestic mild cognitive impairment (aMCI) have significantly increased risk for progressing into Alzheimer's disease (AD). Autopsy studies found that most of the brains of aMCI cases showed anatomical features associated with AD pathology. The recent development of non-invasive neuroimaging technique, such as diffusion tensor imaging (DTI), makes it possible to investigate the microstructures of the cerebral white matter in vivo. We hypothesized that disrupted white matter (WM) integrity existed in aMCI. So we used DTI technique, by measuring fractional anisotropy (FA) and mean diffusivity (MD), to test the brain structures involved in patients with aMCI. DTI scans were collected from 40 patients with aMCI, and 28 normal controls (NC). Tract-based spatial statistics (TBSS) analyses of whole-brain FA and MD images in each individual and group comparisons were carried out. Compared to NC, aMCI patients showed significant FA reduction bilaterally, in the association and projection fibers of frontal, parietal, and temporal lobes, corpus callosum, bilateral corona radiation, right posterior thalamic radiation and right sagittal stratum. aMCI patients also showed significantly increased MD widespreadly in the association and projection fibers of frontal, parietal and temporal lobes, and corpus callosum. Assessment of the WM integrity of the frontal, parietal, temporal lobes, and corpus callosum by using DTI measures may aid early diagnosis of aMCI.

Quantitative longitudinal interrelationships between brain metabolism and amyloid deposition during a 2-year follow-up in patients with early Alzheimer's disease

PURPOSE

Similar regional anatomical distributions were reported for fibrillary amyloid deposition [measured by (11)C-Pittsburgh compound B (PIB) positron emission tomography (PET)] and brain hypometabolism [measured by (18)F-fluorodeoxyglucose (FDG) PET] in numerous Alzheimer's disease (AD) studies. However, there is a lack of longitudinal studies evaluating the interrelationships of these two different pathological markers in the same AD population. Our most recent AD study suggested that the longitudinal pattern of hypometabolism anatomically follows the pattern of amyloid deposition with temporal delay, which indicates that neuronal dysfunction may spread within the anatomical pattern of amyloid pathology. Based on this finding we now hypothesize that in early AD patients quantitative longitudinal decline in hypometabolism may be related to the amount of baseline amyloid deposition during a follow-up period of 2 years.

METHODS

Fifteen patients with mild probable AD underwent baseline (T1) and follow-up (T2) examination after 24 ± 2.1 months with [(18)F]FDG PET, [(11)C]PIB PET, structural T1-weighted MRI and neuropsychological testing [Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery]. Longitudinal cognitive measures and quantitative PET measures of amyloid deposition and metabolism [standardized uptake value ratios (SUVRs)] were obtained using volume of interest (VOI)-based approaches in the frontal-lateral-retrosplenial (FLR) network and in predefined bihemispheric brain regions after partial volume effect (PVE) correction of PET data. Statistical group comparisons (SUVRs and cognitive measures) between patients and 15 well-matched elderly controls who had undergone identical imaging procedures once as well as Pearson's correlation analyses within patients were performed.

RESULTS

Group comparison revealed significant cognitive decline and increased mean PIB/decreased FDG SUVRs in the FLR network as well as in several AD-typical regions in patients relative to controls. Concurrent with cognitive decline patients showed longitudinal increase in mean PIB/decrease in mean FDG SUVRs over time in the FLR network and in several AD-typical brain regions. Correlation analyses of FLR network SUVRs in patients revealed significant positive correlations between PIB T1 and delta FDG (FDG T1-T2) SUVRs, between PIB T1 and PIB T2 SUVRs, between FDG T1 and PIB T2 SUVRs as well as between FDG T1 and FDG T2 SUVRs, while significant negative correlations were found between FDG T1 and delta PIB (PIB T1-T2) SUVRs as well as between FDG T2 and delta FDG (FDG T1-T2) SUVRs. These findings were confirmed in locoregional correlation analyses, revealing significant associations in the same directions for two left hemispheric regions and nine right hemispheric regions, showing the strongest association for bilateral precuneus.

CONCLUSION

Baseline amyloid deposition in patients with mild probable AD was associated with longitudinal metabolic decline. Additionally, mildly decreased/relatively preserved baseline metabolism was associated with a longitudinal increase in amyloid deposition. The latter bidirectional associations were present in the whole AD-typical FLR network and in several highly interconnected hub regions (i.e. in the precuneus). Our longitudinal findings point to a bidirectional quantitative interrelationship of the two investigated AD pathologies, comprising an initial relative maintenance of neuronal activity in already amyloid-positive hub regions (neuronal compensation), followed by accelerated amyloid deposition, accompanied by functional neuronal decline (neuronal breakdown) along with cognitive decline.

Butyrylcholinesterase genotype and gender influence Alzheimer's disease phenotype

Retrospective data are presented to support a spectrum of early Alzheimer's disease (AD) along a continuum defined by gender and genotype. The putative neurodegenerative mechanisms driving distinct phenotypes at each end of the spectrum are glial hypoactivity associated with early failure of synaptic cholinergic neurotransmission and glial overactivation associated with loss of neural network connectivity due to accelerated age-related breakdown of myelin. In early AD, male butyrylcholinesterase K-variant carriers with one or two apolipoprotein ɛ4 alleles have prominent medial temporal atrophy, synaptic failure, cognitive decline, and accumulation of aggregated beta-amyloid peptide. Increasing synaptic acetylcholine in damaged but still functional cholinergic synapses improves cognitive symptoms, whereas increasing the ability of glia to support synapses and to clear beta-amyloid peptide might be disease-modifying. Conversely, chronic glial overactivation can also drive degenerative processes and in butyrylcholinesterase K-variant negative females generalized glial overactivation may be the main driver from mild cognitive impairment to AD. Females are more likely than males to have accelerated age-related myelin breakdown, more widespread white matter loss, loss of neural network connectivity, whole brain atrophy, and functional decline. Increasing extracellular acetylcholine levels blocks glial activation, reduces myelin loss and damage to neural network connectivity, and is disease-modifying. Between extremes characterized by gender, genotype, and age, pathophysiology may be mixed and this spectrum may explain much of the heterogeneity of amnestic mild cognitive impairment. Preservation of the functional integrity of the neural network may be an important component of strengthening cognitive reserve and significantly delaying the onset and progression of dementia, particularly in females. Prospective confirmation of these hypotheses is required. Implications for future research and therapeutic opportunities are discussed.

White matter integrity and reaction time intraindividual variability in healthy aging and early-stage Alzheimer disease

Aging and early-stage Alzheimer disease (AD) have been shown to be associated with increased RT intraindividual variability (IIV, as reflected by the coefficient of variation) and an exaggeration of the slow tail of the reaction time (RT) distribution in attentional control tasks, based on ex-Gaussian analyses. The current study examined associations between white matter volume, IIV, and ex-Gaussian RT distribution parameters in cognitively normal aging and early-stage AD. Three RT attention tasks (Stroop, Simon, and a consonant-vowel odd-even switching task) in conjunction with MRI-based measures of cerebral and regional white matter volume were obtained in 133 cognitively normal and 33 early-stage AD individuals. Larger volumes were associated with less IIV and less slowing in the tail of the RT distribution, and larger cerebral and inferior parietal white matter volumes were associated with faster modal reaction time. Collectively, these results support a role of white matter integrity in IIV and distributional skewing, and are consistent with the hypothesis that IIV and RT distributional skewing are sensitive to breakdowns in executive control processes in normal and pathological aging.

Multi-modal MRI analysis with disease-specific spatial filtering: initial testing to predict mild cognitive impairment patients who convert to Alzheimer's disease

BACKGROUND

Alterations of the gray and white matter have been identified in Alzheimer's disease (AD) by structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). However, whether the combination of these modalities could increase the diagnostic performance is unknown.

METHODS

Participants included 19 AD patients, 22 amnestic mild cognitive impairment (aMCI) patients, and 22 cognitively normal elderly (NC). The aMCI group was further divided into an "aMCI-converter" group (converted to AD dementia within 3 years), and an "aMCI-stable" group who did not convert in this time period. A T(1)-weighted image, a T(2) map, and a DTI of each participant were normalized, and voxel-based comparisons between AD and NC groups were performed. Regions-of-interest, which defined the areas with significant differences between AD and NC, were created for each modality and named "disease-specific spatial filters" (DSF). Linear discriminant analysis was used to optimize the combination of multiple MRI measurements extracted by DSF to effectively differentiate AD from NC. The resultant DSF and the discriminant function were applied to the aMCI group to investigate the power to differentiate the aMCI-converters from the aMCI-stable patients.

RESULTS

The multi-modal approach with AD-specific filters led to a predictive model with an area under the receiver operating characteristic curve (AUC) of 0.93, in differentiating aMCI-converters from aMCI-stable patients. This AUC was better than that of a single-contrast-based approach, such as T(1)-based morphometry or diffusion anisotropy analysis.

CONCLUSION

The multi-modal approach has the potential to increase the value of MRI in predicting conversion from aMCI to AD.

Correlation of cognitive dysfunction and diffusion tensor MRI measures in patients with mild and moderate multiple sclerosis

PURPOSE

To compare the diffusion tensor imaging (DTI) measures of multiple sclerosis (MS) patients and healthy subjects in every brain voxel and to correlate them with Paced Auditory Serial Addition Test (PASAT) scores.

MATERIALS AND METHODS

Fractional anisotropy (FA), and mean, longitudinal, and transverse diffusivity are compared between control subjects and MS patients, which were subdivided as mildly and moderately impaired. In addition, PASAT scores are correlated for both MS groups with the diffusion measures. An optimized voxel based analysis (VBA) method, in terms of coregistration, atlas construction, and image smoothing, was thereby used.

RESULTS

Diffusion differences between the control subjects and the patients with MS were found in the corpus callosum, inferior longitudinal fasciculus, cortico spinal tracts, forceps major, superior longitudinal fasciculus, and cingulum. In addition, we observed significant correlations of the FA and PASAT scores in the left inferior longitudinal fasciculus, the forceps minor, the capsula interna and externa, the genu of the corpus callosum, the left cingulum, the superior longitudinal fasciculus, and the corona radiata.

CONCLUSION

Diffusion differences were observed between the mildly impaired MS patients and control subjects. In addition, different diffusion measures correlated with PASAT scores for cognitive decline in parietal, frontal, as well as temporal white matter (WM) regions.

Sequential relationships between grey matter and white matter atrophy and brain metabolic abnormalities in early Alzheimer's disease

Hippocampal atrophy, posterior cingulate and frontal glucose hypometabolism, and white-matter tract disruption are well described early macroscopic events in Alzheimer's disease. The relationships between these three types of alterations have been documented in previous studies, but their chronology still remains to be established. The present study used multi-modal fluorodeoxyglucose-positron emission tomography and magnetic resonance imaging longitudinal data to address this question in patients with amnestic mild cognitive impairment. We found unidirectional, specific sequential relationships between: (i) baseline hippocampal atrophy and both cingulum bundle (r = 0.70; P = 3 × 10⁻³) and uncinate fasciculus (r = 0.75; P = 7 × 10⁻⁴) rate of atrophy; (ii) baseline cingulum bundle atrophy and rate of decline of posterior (r = 0.72; P = 2 × 10⁻³); and anterior (r = 0.74; P = 1 × 10⁻³) cingulate metabolism; and (iii) baseline uncinate white matter atrophy and subgenual metabolism rate of change (r = 0.65; P = 6 × 10⁻³). Baseline local grey matter atrophy was not found to contribute to hypometabolism progression within the posterior and anterior cingulate as well as subgenual cortices. These findings suggest that hippocampal atrophy progressively leads to disruption of the cingulum bundle and uncinate fasciculus, which in turn leads to glucose hypometabolism of the cingulate and subgenual cortices, respectively. This study reinforces the relevance of remote mechanisms above local interactions to account for the pattern of metabolic brain alteration observed in amnestic mild cognitive impairment, and provides new avenues to assess the sequence of events in complex diseases characterized by multiple manifestations.