Functional connectivity changes differ in early and late-onset Alzheimer's disease

Early brain connectivity alterations and cognitive impairment in a rat model of Alzheimer's disease

BACKGROUND

Animal models of Alzheimer's disease (AD) are essential to understanding the disease progression and to development of early biomarkers. Because AD has been described as a disconnection syndrome, magnetic resonance imaging (MRI)-based connectomics provides a highly translational approach to characterizing the disruption in connectivity associated with the disease. In this study, a transgenic rat model of AD (TgF344-AD) was analyzed to describe both cognitive performance and brain connectivity at an early stage (5 months of age) before a significant concentration of β-amyloid plaques is present.

METHODS

Cognitive abilities were assessed by a delayed nonmatch-to-sample (DNMS) task preceded by a training phase where the animals learned the task. The number of training sessions required to achieve a learning criterion was recorded and evaluated. After DNMS, MRI acquisition was performed, including diffusion-weighted MRI and resting-state functional MRI, which were processed to obtain the structural and functional connectomes, respectively. Global and regional graph metrics were computed to evaluate network organization in both transgenic and control rats.

RESULTS

The results pointed to a delay in learning the working memory-related task in the AD rats, which also completed a lower number of trials in the DNMS task. Regarding connectivity properties, less efficient organization of the structural brain networks of the transgenic rats with respect to controls was observed. Specific regional differences in connectivity were identified in both structural and functional networks. In addition, a strong correlation was observed between cognitive performance and brain networks, including whole-brain structural connectivity as well as functional and structural network metrics of regions related to memory and reward processes.

CONCLUSIONS

In this study, connectivity and neurocognitive impairments were identified in TgF344-AD rats at a very early stage of the disease when most of the pathological hallmarks have not yet been detected. Structural and functional network metrics of regions related to reward, memory, and sensory performance were strongly correlated with the cognitive outcome. The use of animal models is essential for the early identification of these alterations and can contribute to the development of early biomarkers of the disease based on MRI connectomics.

Does the Interplay Between Aging and Neuroinflammation Modulate Alzheimer's Disease Clinical Phenotypes? A Clinico-Pathological Perspective

Alzheimer's disease (AD) is a chronic neurodegenerative disorder and is the most common cause of dementia worldwide. Cumulative data suggests that neuroinflammation plays a prominent and early role in AD, and there is compelling data from different research groups of age-associated dysregulation of the neuroimmune system. From the clinical point of view, despite clinical resemblance and neuropathological findings, there are important differences between the group of patients with sporadic early-onset (<65 years old) and late-onset AD (>65 years old). Thus, it seems important to understand the age-dependent relationship between neuroinflammation and the underlying biology of AD in order to identify potential explanations for clinical heterogeneity, interpret biomarkers, and promote the best treatment to different clinical AD phenotypes. The study of the delicate balance between pro-inflammatory or anti-inflammatory sides of immune players in the different ages of onset of AD would be important to understand treatment efficacy in clinical trials and eventually, not only direct treatment to early disease stages, but also the possibility of establishing different treatment approaches depending on the age of the patient. In this review, we would like to summarize what is currently known about the interplay between "normal" age associated inflammatory changes and AD pathological mechanisms, and also the potential differences between early-onset and late-onset AD taking into account the age-related neuroimmune background at disease onset.

Brain Networks are Independently Modulated by Donepezil, Sleep, and Sleep Deprivation

Resting-state connectivity has been widely studied in the healthy and pathological brain. Less well-characterized are the brain networks altered during pharmacological interventions and their possible interaction with vigilance. In the hopes of finding new biomarkers which can be used to identify cortical activity and cognitive processes linked to the effects of drugs to treat neurodegenerative diseases such as Alzheimer's disease, the analysis of networks altered by medication would be particularly interesting. Eleven healthy subjects were recruited in the context of the European Innovative Medicines Initiative 'PharmaCog'. Each underwent five sessions of simultaneous EEG-fMRI in order to investigate the effects of donepezil and memantine before and after sleep deprivation (SD). The SD approach has been previously proposed as a model for cognitive impairment in healthy subjects. By applying network based statistics (NBS), we observed altered brain networks significantly linked to donepezil intake and sleep deprivation. Taking into account the sleep stages extracted from the EEG data we revealed that a network linked to sleep is interacting with sleep deprivation but not with medication intake. We successfully extracted the functional resting-state networks modified by donepezil intake, sleep and SD. We observed donepezil induced whole brain connectivity alterations forming a network separated from the changes induced by sleep and SD, a result which shows the utility of this approach to check for the validity of pharmacological resting-state analysis of the tested medications without the need of taking into account the subject specific vigilance.

Aberrant pattern of regional cerebral blood flow in Alzheimer's disease: a voxel-wise meta-analysis of arterial spin labeling MR imaging studies

Many studies have applied arterial spin labeling (ASL) to characterize cerebral perfusion patterns of Alzheimer's disease (AD). However, findings across studies are not conclusive. A quantitatively voxel-wise meta-analysis to pool the resting-state ASL studies that measure regional cerebral blood flow (rCBF) alterations in AD was conducted to identify the most consistent and replicable perfusion pattern using seed-based d mapping. The meta-analysis, including 17 ASL studies encompassing 327 AD patients and 357 healthy controls, demonstrated that decreased rCBF in AD patients relative to healthy controls were consistently identified in the bilateral posterior cingulate cortices (PCC)/precuneus, bilateral inferior parietal lobules (IPLs), and left dorsolateral prefrontal cortex. The meta-regression analysis showed that more severe cognitive impairment in the AD samples correlated with greater decreases of rCBF in the bilateral PCC and left IPL. This study characterizes an aberrant ASL-rCBF perfusion pattern of AD involving the posterior default mode network and executive network, which are implicated in its pathophysiology and hold promise for developing imaging biomarkers.

Brain network connectivity differs in early-onset neurodegenerative dementia

OBJECTIVE

To investigate functional brain network architecture in early-onset Alzheimer disease (EOAD) and behavioral variant frontotemporal dementia (bvFTD).

METHODS

Thirty-eight patients with bvFTD, 37 patients with EOAD, and 32 age-matched healthy controls underwent 3D T1-weighted and resting-state fMRI. Graph analysis and connectomics assessed global and local functional topologic network properties, regional functional connectivity, and intrahemispheric and interhemispheric between-lobe connectivity.

RESULTS

Despite similarly extensive cognitive impairment relative to controls, patients with EOAD showed severe global functional network alterations (lower mean nodal strength, local efficiency, clustering coefficient, and longer path length), while patients with bvFTD showed relatively preserved global functional brain architecture. Patients with bvFTD demonstrated reduced nodal strength in the frontoinsular lobe and a relatively focal altered functional connectivity of frontoinsular and temporal regions. Functional connectivity breakdown in the posterior brain nodes, particularly in the parietal lobe, differentiated patients with EOAD from those with bvFTD. While EOAD was associated with widespread loss of both intrahemispheric and interhemispheric functional correlations, bvFTD showed a preferential disruption of the intrahemispheric connectivity.

CONCLUSIONS

Disease-specific patterns of functional network topology and connectivity alterations were observed in patients with EOAD and bvFTD. Graph analysis and connectomics may aid clinical diagnosis and help elucidate pathophysiologic differences between neurodegenerative dementias.

Early-Onset Alzheimer Disease

Early-onset Alzheimer disease (EOAD), with onset in individuals younger than 65 years, although overshadowed by the more common late-onset AD (LOAD), differs significantly from LOAD. EOAD comprises approximately 5% of AD and is associated with delays in diagnosis, aggressive course, and age-related psychosocial needs. One source of confusion is that a substantial percentage of EOAD are phenotypic variants that differ from the usual memory-disordered presentation of typical AD. The management of EOAD is similar to that for LOAD, but special emphasis should be placed on targeting the specific cognitive areas involved and more age-appropriate psychosocial support and education.

Resting-state network dysfunction in Alzheimer's disease: A systematic review and meta-analysis

Introduction

We performed a systematic review and meta-analysis of the Alzheimer's disease (AD) literature to examine consistency of functional connectivity alterations in AD dementia and mild cognitive impairment, using resting-state functional magnetic resonance imaging.

Methods

Studies were screened using a standardized procedure. Multiresolution statistics were performed to assess the spatial consistency of findings across studies.

Results

Thirty-four studies were included (1363 participants, average 40 per study). Consistent alterations in connectivity were found in the default mode, salience, and limbic networks in patients with AD dementia, mild cognitive impairment, or in both groups. We also identified a strong tendency in the literature toward specific examination of the default mode network.

Discussion

Convergent evidence across the literature supports the use of resting-state connectivity as a biomarker of AD. The locations of consistent alterations suggest that highly connected hub regions in the brain might be an early target of AD.

Difference in imaging biomarkers of neurodegeneration between early and late-onset amnestic Alzheimer's disease

Neuroimaging biomarkers differ between patients with early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). Whether these changes reflect cognitive heterogeneity or differences in disease severity is still unknown. This study aimed at investigating changes in neuroimaging biomarkers, according to the age of onset of the disease, in mild amnestic Alzheimer's disease patients with positive amyloid biomarkers in cerebrospinal fluid. Both patient groups were impaired on tasks assessing verbal and visual recognition memory. EOAD patients showed greater executive and linguistic deficits, while LOAD patients showed greater semantic memory impairment. In EOAD and LOAD, hypometabolism involved the bilateral temporoparietal junction and the posterior cingulate cortex. In EOAD, atrophy was widespread, including frontotemporoparietal areas, whereas it was limited to temporal regions in LOAD. Atrophic volumes were greater in EOAD than in LOAD. Hypometabolic volumes were similar in the 2 groups. Greater extent of atrophy in EOAD, despite similar extent of hypometabolism, could reflect different underlying pathophysiological processes, different glucose-based compensatory mechanisms or distinct level of premorbid atrophic lesions.

Differences in Depressive Patterns According to Disease Severityin Early-Onset Alzheimer's Disease

BACKGROUND & OBJECTIVE

Depression frequently combines with dementia, including early-onset Alzheimer's disease (EOAD). We investigated differences in prevalence and characteristics of depressive symptoms according to dementia severity in EOAD patients.

METHODS

The 15-item Korean version of the Geriatric Depression Scale (GDS-15) was administered to 412 EOAD patients. Factor analysis was used to assess GDS-15 factor structure. We subdivided participants into three groups by disease severity, then compared the frequencies and scores of individual GDS-15 items and performed logistic regression analysis to assess associations between depressive symptoms and EOAD stage.

RESULTS

Factor analysis yielded three factor categories: 1) "hopelessness and ominousness" (symptoms no. 6, 8, 12, 14, 15); 2) "unhappiness and dissatisfaction" (no. 1, 3, 5, 7, 11); and 3) "monotony and lack of energy" (no. 2, 4, 9, 10, 13). Factor 2 depressive symptoms (no. 1, 5, 11) were less common in moderate EOAD. The risk of Factor 1 symptoms: no. 12 (OR, 2.04; 95% CI, 1.19-3.50; p = 0.010) and 14 (OR, 1.84; 95% CI, 1.07-3.16; p = 0.028) was higher in mild than very mild EOAD. The risk of Factor 2 symptoms: no. 9 (OR, 2.69; 95% CI, 1.08-6.71; p = 0.033) and 13 (OR, 2.12; 95% CI, 1.02-4.40; p = 0.043) was higher in moderate than mild EOAD.

CONCLUSION

We confirmed that depressive symptoms differ according to EOAD severity. When assessing depressive symptoms related to dementia progression, we recommend focusing on "hopelessness and ominousness" in very mild EOAD and "unhappiness and dissatisfaction" in mild EOAD.

Disrupted global metastability and static and dynamic brain connectivity across individuals in the Alzheimer's disease continuum

As findings on the neuropathological and behavioral components of Alzheimer's disease (AD) continue to accrue, converging evidence suggests that macroscale brain functional disruptions may mediate their association. Recent developments on theoretical neuroscience indicate that instantaneous patterns of brain connectivity and metastability may be a key mechanism in neural communication underlying cognitive performance. However, the potential significance of these patterns across the AD spectrum remains virtually unexplored. We assessed the clinical sensitivity of static and dynamic functional brain disruptions across the AD spectrum using resting-state fMRI in a sample consisting of AD patients (n = 80) and subjects with either mild (n = 44) or subjective (n = 26) cognitive impairment (MCI, SCI). Spatial maps constituting the nodes in the functional brain network and their associated time-series were estimated using spatial group independent component analysis and dual regression, and whole-brain oscillatory activity was analyzed both globally (metastability) and locally (static and dynamic connectivity). Instantaneous phase metrics showed functional coupling alterations in AD compared to MCI and SCI, both static (putamen, dorsal and default-mode) and dynamic (temporal, frontal-superior and default-mode), along with decreased global metastability. The results suggest that brains of AD patients display altered oscillatory patterns, in agreement with theoretical premises on cognitive dynamics.

A genetic screen of the mutations in the Korean patients with early-onset Alzheimer's disease

Early-onset Alzheimer's disease (EOAD) has distinct clinical characteristics in comparison to late-onset Alzheimer's disease (LOAD). The genetic contribution is suggested to be more potent in EOAD. However, the frequency of causative mutations in EOAD could be variable depending on studies. Moreover, no mutation screening study has been performed yet employing large population in Korea. Previously, we reported that the rate of family history of dementia in EOAD patients was 18.7% in a nationwide hospital-based cohort study, the Clinical Research Center for Dementia of South Korea (CREDOS) study. This rate is much lower than in other countries and is even comparable to the frequency of LOAD patients in our country. To understand the genetic characteristics of EOAD in Korea, we screened the common Alzheimer's disease (AD) mutations in the consecutive EOAD subjects from the CREDOS study from April 2012 to February 2014. We checked the sequence of APP (exons 16-17), PSEN1 (exons 3-12), and PSEN2 (exons 3-12) genes. We identified different causative or probable pathogenic AD mutations, PSEN1 T116I, PSEN1 L226F, and PSEN2 V214L, employing 24 EOAD subjects with a family history and 80 without a family history of dementia. PSEN1 T116I case demonstrated autosomal dominant trait of inheritance, with at least 11 affected individuals over 2 generations. However, there was no family history of dementia within first-degree relation in PSEN1 L226F and PSEN2 V214L cases. Approximately, 55.7% of the EOAD subjects had APOE ε4 allele, while none of the mutation-carrying subjects had the allele. The frequency of genetic mutation in this study is lower compared to the studies from other countries. The study design that was based on nationwide cohort, which minimizes selection bias, is thought to be one of the contributors to the lower frequency of genetic mutation. However, the possibility of the greater likeliness of earlier onset of sporadic AD in Korea cannot be excluded. We suggest early AD onset and not carrying APOE ε4 allele are more reliable factors for predicting an induced genetic mutation than the presence of the family history in Korean EOAD population.

Neuropsychiatric subsyndromes and brain metabolic network dysfunctions in early onset Alzheimer's disease

Neuropsychiatric symptoms (NPSs) often occur in early-age-of-onset Alzheimer's disease (EOAD) and cluster into sub-syndromes (SSy). The aim of this study was to investigate the association between 18 F-FDG-PET regional and connectivity-based brain metabolic dysfunctions and neuropsychiatric SSy. NPSs were assessed in 27 EOAD using the Neuropsychiatric Inventory and further clustered into four SSy (apathetic, hyperactivity, affective, and psychotic SSy). Eighty-five percent of EOAD showed at least one NPS. Voxel-wise correlations between SSy scores and brain glucose metabolism (assessed with 18 F-FDG positron emission tomography) were studied. Interregional correlation analysis was used to explore metabolic connectivity in the salience (aSN) and default mode networks (DMN) in a larger sample of EOAD (N = 51) and Healthy Controls (N = 57). The apathetic, hyperactivity, and affective SSy were highly prevalent (>60%) as compared to the psychotic SSy (33%). The hyperactivity SSy scores were associated with increase of glucose metabolism in frontal and limbic structures, implicated in behavioral control. A comparable positive correlation with part of the same network was found for the affective SSy scores. On the other hand, the apathetic SSy scores were negatively correlated with metabolism in the bilateral orbitofrontal and dorsolateral frontal cortex known to be involved in motivation and decision-making processes. Consistent with these SSy regional correlations with brain metabolic dysfunction, the connectivity analysis showed increases in the aSN and decreases in the DMN. Behavioral abnormalities in EOAD are associated with specific dysfunctional changes in brain metabolic activity, in particular in the aSN that seems to play a crucial role in NPSs in EOAD. Hum Brain Mapp 37:4234-4247, 2016. © 2016 Wiley Periodicals, Inc.

Predictive factors for disease progression in patients with early-onset Alzheimer's disease

BACKGROUND

Only a few studies have investigated disease progression in patients with early-onset Alzheimer's disease (EOAD). Therefore, the aim of this study was to investigate disease progression in patients with EOAD and the influence of various factors, such as gender, education, and apolipoprotein E (APOE) genotype on disease progression.

METHODS

A total of 288 EOAD patients were enrolled in the study. Linear mixed models were used to investigate the rate of cognitive and functional decline in terms of age at onset, gender, education, follow-up period, and APOE genotype.

RESULTS

EOAD patients showed an annual decline of -1.54 points/years in the Korean version mini-mental examination score, an annual increase of 3.46 points/year in the Seoul instrumental activities of daily living (SIADL) score, and an annual increase of 1.15 points/year in the clinical dementia rating scale-sum of boxes score. After stratification, higher educated patients showed faster disease progression in all three parameters, and female patients demonstrated faster disease progression as assessed by the SIADL score. Age at onset and APOE genotype had no influence on disease progression.

CONCLUSION

We confirmed the rate of disease progression in Korean patients with EOAD in real-life hospital-based clinical practice. The results of this study suggest that education and female gender, not APOE genotype, may be important as independent strong predictive factors for disease progression in patients with EOAD.

Glucose Metabolic Brain Networks in Early-Onset vs. Late-Onset Alzheimer's Disease

Objective: Early-onset Alzheimer's disease (EAD) shows distinct features from late-onset Alzheimer's disease (LAD). To explore the characteristics of EAD, clinical, neuropsychological, and functional imaging studies have been conducted. However, differences between EAD and LAD are not clear, especially in terms of brain connectivity and networks. In this study, we investigated the differences in metabolic connectivity between EAD and LAD by adopting graph theory measures.

Methods: We analyzed ¹⁸F-fluorodeoxyglucose-positron emission tomography (FDG-PET) images to investigate the distinct features of metabolic connectivity between EAD and LAD. Using metabolic connectivity and graph theory analysis, metabolic network differences between LAD and EAD were explored.

Results: Results showed the decreased connectivity centered in the cingulate gyri and occipital regions in EAD, whereas decreased connectivity in the occipital and temporal regions as well as increased connectivity in the supplementary motor area were observed in LAD when compared with age-matched control groups. Global efficiency and clustering coefficients were decreased in EAD but not in LAD. EAD showed progressive network deterioration as a function of disease severity and clinical dementia rating (CDR) scores, mainly in terms of connectivity between the cingulate gyri and occipital regions. Global efficiency and clustering coefficients were also decreased along with disease severity.

Conclusion: These results indicate that EAD and LAD have distinguished features in terms of metabolic connectivity, with EAD demonstrating more extensive and progressive deterioration.

Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease

Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.

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We use machine learning classification to classify Alzheimer's disease.

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For classification we use anatomical MRI, diffusion MRI, and resting state fMRI.

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Grey matter density is most successful for single modality classification.

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Combining multiple modalities improves classification of Alzheimer's disease.

Abnormal Resting-State Functional Connectivity Strength in Mild Cognitive Impairment and Its Conversion to Alzheimer's Disease

Individuals diagnosed with mild cognitive impairment (MCI) are at high risk of transition to Alzheimer's disease (AD). However, little is known about functional characteristics of the conversion from MCI to AD. Resting-state functional magnetic resonance imaging was performed in 25 AD patients, 31 MCI patients, and 42 well-matched normal controls at baseline. Twenty-one of the 31 MCI patients converted to AD at approximately 24 months of follow-up. Functional connectivity strength (FCS) and seed-based functional connectivity analyses were used to assess the functional differences among the groups. Compared to controls, subjects with MCI and AD showed decreased FCS in the default-mode network and the occipital cortex. Importantly, the FCS of the left angular gyrus and middle occipital gyrus was significantly lower in MCI-converters as compared with MCI-nonconverters. Significantly decreased functional connectivity was found in MCI-converters compared to nonconverters between the left angular gyrus and bilateral inferior parietal lobules, dorsolateral prefrontal and lateral temporal cortices, and the left middle occipital gyrus and right middle occipital gyri. We demonstrated gradual but progressive functional changes during a median 2-year interval in patients converting from MCI to AD, which might serve as early indicators for the dysfunction and progression in the early stage of AD.

Executive Abilities as Reflected by Clock Hand Placement: Frontotemporal Dementia Versus Early-Onset Alzheimer Disease

The clock-drawing test (CDT) is widely used in clinical practice to diagnose and distinguish patients with dementia. It remains unclear, however, whether the CDT can distinguish among the early-onset dementias. Accordingly, we examined the ability of both quantitative and qualitative CDT analyses to distinguish behavioral variant frontotemporal dementia (bvFTD) and early-onset Alzheimer disease (eAD), the 2 most common neurodegenerative dementias with onset <65 years of age. We hypothesized that executive aspects of the CDT would discriminate between these 2 disorders. The study compared 15 patients with bvFTD and 16 patients with eAD on the CDT using 2 different scales and correlated the findings with neuropsychological testing and magnetic resonance imaging. The total CDT scores did not discriminate bvFTD and eAD; however, specific analysis of executive hand placement items successfully distinguished the groups, with eAD exhibiting greater errors than bvFTD. The performance on those executive hand placement items correlated with measures of naming as well as visuospatial and executive function. On tensor-based morphometry of the magnetic resonance images, executive hand placement correlated with right frontal volume. These findings suggest that lower performance on executive hand placement items occurs with involvement of the right dorsolateral frontal-parietal network for executive control in eAD, a network disproportionately affected in AD of early onset. Rather than the total performance on the clock task, the analysis of specific errors, such as executive hand placement, may be useful for early differentiation of eAD, bvFTD, and other conditions.

Early-onset and late-onset Alzheimer's disease are associated with distinct patterns of memory impairment

The goal of this study was to investigate the specific patterns of memory breakdown in patients suffering from early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). Twenty EOAD patients, twenty LOAD patients, twenty matched younger controls, and twenty matched older controls participated in this study. All participants underwent a detailed neuropsychological assessment, an MRI scan, an FDG-PET scan, and AD patients had biomarkers as supporting evidence of both amyloïdopathy and neuronal injury. Results of the neuropsychological assessment showed that both EOAD and LOAD groups were impaired in the domains of memory, executive functions, language, praxis, and visuoconstructional abilities, when compared to their respective control groups. EOAD and LOAD groups, however, showed distinct patterns of memory impairment. Even though both groups were similarly affected on measures of episodic, short term and working memory, in contrast semantic memory was significantly more impaired in LOAD than in EOAD patients. The EOAD group was not more affected than the LOAD group in any memory domain. EOAD patients, however, showed significantly poorer performance in other cognitive domains including executive functions and visuoconstructional abilities. A more detailed analysis of the pattern of semantic memory performance among patient groups revealed that the LOAD was more profoundly impaired, in tasks of both spontaneous recall and semantic recognition. Voxel-Based Morphometry (VBM) analyses showed that impaired semantic performance in patients was associated with reduced gray matter volume in the anterior temporal lobe (ATL) region, while PET-FDG analyses revealed that poorer semantic performance was associated with greater hypometabolism in the left temporoparietal region, both areas reflecting key regions of the semantic network. Results of this study indicate that EOAD and LOAD patients present with distinct patterns of memory impairment, and that a genuine semantic impairment may represent one of the clinical hallmarks of LOAD.

The Brain Activity in Brodmann Area 17: A Potential Bio-Marker to Predict Patient Responses to Antiepileptic Drugs

In this study, we aimed to predict newly diagnosed patient responses to antiepileptic drugs (AEDs) using resting-state functional magnetic resonance imaging tools to explore changes in spontaneous brain activity. We recruited 21 newly diagnosed epileptic patients, 8 drug-resistant (DR) patients, 11 well-healed (WH) patients, and 13 healthy controls. After a 12-month follow-up, 11 newly diagnosed epileptic patients who showed a poor response to AEDs were placed into the seizures uncontrolled (SUC) group, while 10 patients were enrolled in the seizure-controlled (SC) group. By calculating the amplitude of fractional low-frequency fluctuations (fALFF) of blood oxygen level-dependent signals to measure brain activity during rest, we found that the SUC patients showed increased activity in the bilateral occipital lobe, particularly in the cuneus and lingual gyrus compared with the SC group and healthy controls. Interestingly, DR patients also showed increased activity in the identical cuneus and lingual gyrus regions, which comprise Brodmann's area 17 (BA17), compared with the SUC patients; however, these abnormalities were not observed in SC and WH patients. The receiver operating characteristic (ROC) curves indicated that the fALFF value of BA17 could differentiate SUC patients from SC patients and healthy controls with sufficient sensitivity and specificity prior to the administration of medication. Functional connectivity analysis was subsequently performed to evaluate the difference in connectivity between BA17 and other brain regions in the SUC, SC and control groups. Regions nearby the cuneus and lingual gyrus were found positive connectivity increased changes or positive connectivity changes with BA17 in the SUC patients, while remarkably negative connectivity increased changes or positive connectivity decreased changes were found in the SC patients. Additionally, default mode network (DMN) regions showed negative connectivity increased changes or negative changes with BA17 in the SUC patients. The abnormal increased in BA17 activity may be a key point that plays a substantial role in facilitating seizure onset.

Spatial patterns of atrophy, hypometabolism, and amyloid deposition in Alzheimer's disease correspond to dissociable functional brain networks

Recent neuroimaging studies of Alzheimer's disease (AD) have emphasized topographical similarities between AD-related brain changes and a prominent cortical association network called the default-mode network (DMN). However, the specificity of distinct imaging abnormalities for the DMN compared to other intrinsic connectivity networks (ICNs) of the limbic and heteromodal association cortex has not yet been examined systematically. We assessed regional amyloid load using AV45-PET, neuronal metabolism using FDG-PET, and gray matter volume using structural MRI in 473 participants from the Alzheimer's Disease Neuroimaging Initiative, including preclinical, predementia, and clinically manifest AD stages. Complementary region-of-interest and voxel-based analyses were used to assess disease stage- and modality-specific changes within seven principle ICNs of the human brain as defined by a standardized functional connectivity atlas. Amyloid deposition in AD dementia showed a preference for the DMN, but high effect sizes were also observed for other neocortical ICNs, most notably the frontoparietal-control network. Atrophic changes were most specific for an anterior limbic network, followed by the DMN, whereas other neocortical networks were relatively spared. Hypometabolism appeared to be a mixture of both amyloid- and atrophy-related profiles. Similar patterns of modality-dependent network specificity were also observed in the predementia and, for amyloid deposition, in the preclinical stage. These quantitative data confirm a high vulnerability of the DMN for multimodal imaging abnormalities in AD. However, rather than being selective for the DMN, imaging abnormalities more generally affect higher order cognitive networks and, importantly, the vulnerability profiles of these networks markedly differ for distinct aspects of AD pathology.

Loss of functional connectivity is greater outside the default mode network in nonfamilial early-onset Alzheimer's disease variants

The common and specific involvement of brain networks in clinical variants of Alzheimer's disease (AD) is not well understood. We performed task-free ("resting-state") functional imaging in 60 nonfamilial AD patients, including 20 early-onset AD (age at onset <65 years, amnestic/dysexecutive deficits), 24 logopenic aphasia (language deficits), and 16 posterior cortical atrophy patients (visual deficits), as well as 60 healthy controls. Seed-based connectivity analyses were conducted to assess differences between groups in 3 default mode network (DMN) components (anterior, posterior, and ventral) and 4 additional non-DMN networks: left and right executive-control, language, and higher visual networks. Significant decreases in connectivity were found across AD variants compared with controls in the non-DMN networks. Within the DMN components, patients showed higher connectivity in the anterior DMN, in particular in logopenic aphasia. No significant differences were found for the posterior and ventral DMN. Our findings suggest that loss of functional connectivity is greatest in networks outside the DMN in early-onset and nonamnestic AD variants and may thus be a better biomarker in these patients.

Rhinal hypometabolism on FDG PET in healthy APO-E4 carriers: impact on memory function and metabolic networks

PURPOSE

The ε4 allele of the apolipoprotein E (APO-E4) gene, a genetic risk factor for Alzheimer's disease (AD), also modulates brain metabolism and function in healthy subjects. The aim of the present study was to explore cerebral metabolism using FDG PET in healthy APO-E4 carriers by comparing cognitively normal APO-E4 carriers to noncarriers and to assess if patterns of metabolism are correlated with performance on cognitive tasks. Moreover, metabolic connectivity patterns were established in order to assess if the organization of neural networks is influenced by genetic factors.

METHODS

Whole-brain PET statistical analysis was performed at voxel-level using SPM8 with a threshold of p < 0.005, corrected for volume, with age, gender and level of education as nuisance variables. Significant hypometabolism between APO-E4 carriers (n = 11) and noncarriers (n = 30) was first determined. Mean metabolic values with clinical/neuropsychological data were extracted at the individual level, and correlations were searched using Spearman's rank test in the whole group. To evaluate metabolic connectivity from metabolic cluster(s) previously identified in the intergroup comparison, voxel-wise interregional correlation analysis (IRCA) was performed between groups of subjects.

RESULTS

APO-E4 carriers had reduced metabolism within the left anterior medial temporal lobe (MTL), where neuropathological changes first appear in AD, including the entorhinal and perirhinal cortices. A correlation between metabolism in this area and performance on the DMS48 (delayed matching to sample-48 items) was found, in line with converging evidence involving the perirhinal cortex in object-based memory. Finally, a voxel-wise IRCA revealed stronger metabolic connectivity of the MTL cluster with neocortical frontoparietal regions in carriers than in noncarriers, suggesting compensatory metabolic networks.

CONCLUSION

Exploring cerebral metabolism using FDG PET can contribute to a better understanding of the influence of genetic factors on cerebral metabolism at both the local and network levels leading to phenotypical variations of the healthy brain and selective vulnerability.

Single-subject gray matter graph properties and their relationship with cognitive impairment in early- and late-onset Alzheimer's disease

Abstract We investigated the relationships between gray matter graph properties and cognitive impairment in a sample of 215 patients with Alzheimer's disease (AD) and also whether age of disease onset modifies such relationships. We expected that more severe cognitive impairment in AD would be related to more random graph topologies. Single-subject gray matter graphs were constructed from T1-weighted magnetic resonance imaging scans. The following global and local graph properties were calculated: betweenness centrality, normalized clustering coefficient γ, and normalized path length λ. Local clustering, path length, and betweenness centrality measures were determined for 90 anatomically defined areas. Regression models with as interaction term age of onset (i.e., early onset when patients were ≤65 years old and late onset when they were >65 years old at the time of diagnosis)×graph property were used to assess the relationships between cognitive functioning in five domains (memory, language, visuospatial, attention, and executive). Worse cognitive impairment was associated with more random graphs, as indicated by low γ, λ, and betweenness centrality values. Three interaction effects for age of onset×global graph property were found: Low γ and λ values more strongly related to memory impairment in early-onset patients; low beta values were significantly related to impaired visuospatial functioning in late-onset patients. For the local graph properties, language impairment showed the strongest relationship with decreased clustering coefficient in the left superior temporal gyrus across the entire sample. Our study shows that single-subject gray matter graph properties are associated with individual differences in cognitive impairment.

Cerebro-cerebellar connectivity is increased in primary lateral sclerosis

Increased functional connectivity in resting state networks was found in several studies of patients with motor neuron disorders, although diffusion tensor imaging studies consistently show loss of white matter integrity. To understand the relationship between structural connectivity and functional connectivity, we examined the structural connections between regions with altered functional connectivity in patients with primary lateral sclerosis (PLS), a long-lived motor neuron disease. Connectivity matrices were constructed from resting state fMRI in 16 PLS patients to identify areas of differing connectivity between patients and healthy controls. Probabilistic fiber tracking was used to examine structural connections between regions of differing connectivity. PLS patients had 12 regions with increased functional connectivity compared to controls, with a predominance of cerebro-cerebellar connections. Increased functional connectivity was strongest between the cerebellum and cortical motor areas and between the cerebellum and frontal and temporal cortex. Fiber tracking detected no difference in connections between regions with increased functional connectivity. We conclude that functional connectivity changes are not strongly based in structural connectivity. Increased functional connectivity may be caused by common inputs, or by reduced selectivity of cortical activation, which could result from loss of intracortical inhibition when cortical afferents are intact.

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Functional connectivity is increased in primary lateral sclerosis.

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Functional connections with the cerebellum were prominent.

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Cortico-cerebellar connectivity correlated with clinical measures.

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No corresponding changes occurred in structural connectivity.

Anterior and posterior MTL networks in aging and MCI

Two neuroanatomically dissociable, large-scale cortical memory networks, referred to as the anterior and posterior medial temporal lobe (MTL) networks have recently been described in young adults using resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI)-based functional connectivity (fc-BOLD). They have been hypothesized to subserve distinct mnemonic and non-memory cognitive functions and are thought to be associated with differential vulnerability in neurological disorders. In this article, we demonstrate the existence of these functional networks in an older adult population and in a cohort of patients diagnosed with amnestic mild cognitive impairment (aMCI). Anatomic subregions of interest in the MTL were defined using high-resolution T2-weighted MRI and used as seeds for defining the putative networks using fc-BOLD. Although the literature has suggested that the posterior MTL network is particularly vulnerable to early Alzheimer's disease, we show that both the networks are affected in MCI, to varying degrees, compared with the control group. Furthermore, cortical thickness in the brain regions defined by these networks was reduced in MCI.

Widespread disruption of functional brain organization in early-onset Alzheimer's disease

Early-onset Alzheimer's disease (AD) patients present a different clinical profile than late-onset AD patients. This can be partially explained by cortical atrophy, although brain organization might provide more insight. The aim of this study was to examine functional connectivity in early-onset and late-onset AD patients. Resting-state fMRI scans of 20 early-onset (<65 years old), 28 late-onset (≥65 years old) AD patients and 15 "young" (<65 years old) and 31 "old" (≥65 years old) age-matched controls were available. Resting-state network-masks were used to create subject-specific maps. Group differences were examined using a non-parametric permutation test, accounting for gray-matter. Performance on five cognitive domains were used in a correlation analysis with functional connectivity in AD patients. Functional connectivity was not different in any of the RSNs when comparing the two control groups (young vs. old controls), which implies that there is no general effect of aging on functional connectivity. Functional connectivity in early-onset AD was lower in all networks compared to age-matched controls, where late-onset AD showed lower functional connectivity in the default-mode network. Functional connectivity was lower in early-onset compared to late-onset AD in auditory-, sensory-motor, dorsal-visual systems and the default mode network. Across patients, an association of functional connectivity of the default mode network was found with visuoconstruction. Functional connectivity of the right dorsal visual system was associated with attention across patients. In late-onset AD patients alone, higher functional connectivity of the sensory-motor system was associated with poorer memory performance. Functional brain organization was more widely disrupted in early-onset AD when compared to late-onset AD. This could possibly explain different clinical profiles, although more research into the relationship of functional connectivity and cognitive performance is needed.

A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementia

In resting state fMRI (rs-fMRI), only functional connectivity (FC) reductions in the default mode network (DMN) are normally reported as a biomarker for Alzheimer's disease (AD). In this investigation we have developed a comprehensive strategy to characterize the FC changes occurring in multiple networks and applied it in a pilot study of subjects with AD and Mild Cognitive Impairment (MCI), compared to healthy controls (HC). Resting state networks (RSNs) were studied in 14 AD (70 ± 6 years), 12 MCI (74 ± 6 years), and 16 HC (69 ± 5 years). RSN alterations were present in almost all the 15 recognized RSNs; overall, 474 voxels presented a reduced FC in MCI and 1244 in AD while 1627 voxels showed an increased FC in MCI and 1711 in AD. The RSNs were then ranked according to the magnitude and extension of FC changes (gFC), putting in evidence 6 RSNs with prominent changes: DMN, frontal cortical network (FCN), lateral visual network (LVN), basal ganglia network (BGN), cerebellar network (CBLN), and the anterior insula network (AIN). Nodes, or hubs, showing alterations common to more than one RSN were mostly localized within the prefrontal cortex and the mesial-temporal cortex. The cerebellum showed a unique behavior where voxels of decreased gFC were only found in AD while a significant gFC increase was only found in MCI. The gFC alterations showed strong correlations (p < 0.001) with psychological scores, in particular Mini-Mental State Examination (MMSE) and attention/memory tasks. In conclusion, this analysis revealed that the DMN was affected by remarkable FC increases, that FC alterations extended over several RSNs, that derangement of functional relationships between multiple areas occurred already in the early stages of dementia. These results warrant future work to verify whether these represent compensatory mechanisms that exploit a pre-existing neural reserve through plasticity, which evolve in a state of lack of connectivity between different networks with the worsening of the pathology.