Christiane Möller

Different patterns of gray matter atrophy in early- and late-onset Alzheimer’s disease

We assessed patterns of gray matter atrophy according to-age-at-onset in a large sample of 215 Alzheimers disease (AD) patients and 129 control subjects with voxel-based morphometry using 3-Tesla 3D T1-weighted magnetic resonance imaging. Local gray matter amounts were compared between late- and early-onset AD patients and older and younger control subjects, taking into account the effect of apolipoprotein E. Additionally, combined effects of age and diagnosis on volumes of hippocampus and precuneus were assessed. Compared with age-matched control subjects, late-onset AD patients exhibited atrophy of the hippocampus, right temporal lobe, and cerebellum, whereas early-onset AD patients showed gray matter atrophy in hippocampus, temporal lobes, precuneus, cingulate gyrus, and inferior frontal cortex. Direct comparisons between late- and early-onset AD patients revealed more pronounced atrophy of precuneus in early-onset AD patients and more severe atrophy in medial temporal lobe in late-onset AD patients. Age and diagnosis independently affected the hippocampus; moreover, the interaction between age and diagnosis showed that precuneus atrophy was most prominent in early-onset AD patients. Our results suggest that patterns of atrophy might vary in the spectrum of AD.

Single-Subject Grey Matter Graphs in Alzheimer's Disease

Coordinated patterns of cortical morphology have been described as structural graphs and previous research has demonstrated that properties of such graphs are altered in Alzheimers disease (AD). However, it remains unknown how these alterations are related to cognitive deficits in individuals, as such graphs are restricted to group-level analysis. In the present study we investigated this question in single-subject grey matter networks. This new method extracts large-scale structural graphs where nodes represent small cortical regions that are connected by edges when they show statistical similarity. Using this method, unweighted and undirected networks were extracted from T1 weighted structural magnetic resonance imaging scans of 38 AD patients (19 female, average age 72±4 years) and 38 controls (19 females, average age 72±4 years). Group comparisons of standard graph properties were performed after correcting for grey matter volumetric measurements and were correlated to scores of general cognitive functioning. AD networks were characterised by a more random topology as indicated by a decreased small world coefficient (p = 3.53×10−5), decreased normalized clustering coefficient (p = 7.25×10−6) and decreased normalized path length (p = 1.91×10−7). Reduced normalized path length explained significantly (p = 0.004) more variance in measurements of general cognitive decline (32%) in comparison to volumetric measurements (9%). Altered path length of the parahippocampal gyrus, hippocampus, fusiform gyrus and precuneus showed the strongest relationship with cognitive decline. The present results suggest that single-subject grey matter graphs provide a concise quantification of cortical structure that has clinical value, which might be of particular importance for disease prognosis. These findings contribute to a better understanding of structural alterations and cognitive dysfunction in AD.

Atrophy Patterns in Early Clinical Stages Across Distinct Phenotypes of Alzheimer’s Disease

Alzheimers disease (AD) can present with distinct clinical variants. Identifying the earliest neurodegenerative changes associated with each variant has implications for early diagnosis, and for understanding the mechanisms that underlie regional vulnerability and disease progression in AD. We performed voxel‐based morphometry to detect atrophy patterns in early clinical stages of four AD phenotypes: Posterior cortical atrophy (PCA, “visual variant,” n = 93), logopenic variant primary progressive aphasia (lvPPA, “language variant,” n = 74), and memory‐predominant AD categorized as early age‐of‐onset (EOAD, <65 years, n = 114) and late age‐of‐onset (LOAD, >65 years, n = 114). Patients with each syndrome were stratified based on: (1) degree of functional impairment, as measured by the clinical dementia rating (CDR) scale, and (2) overall extent of brain atrophy, as measured by a neuroimaging approach that sums the number of brain voxels showing significantly lower gray matter volume than cognitively normal controls (n = 80). Even at the earliest clinical stage (CDR = 0.5 or bottom quartile of overall atrophy), patients with each syndrome showed both common and variant‐specific atrophy. Common atrophy across variants was found in temporoparietal regions that comprise the posterior default mode network (DMN). Early syndrome‐specific atrophy mirrored functional brain networks underlying functions that are uniquely affected in each variant: Language network in lvPPA, posterior cingulate cortex‐hippocampal circuit in amnestic EOAD and LOAD, and visual networks in PCA. At more advanced stages, atrophy patterns largely converged across AD variants. These findings support a model in which neurodegeneration selectively targets both the DMN and syndrome‐specific vulnerable networks at the earliest clinical stages of AD. Hum Brain Mapp 36:4421–4437, 2015.

Resting state functional connectivity differences between behavioral variant frontotemporal dementia and Alzheimer’s disease

Introduction: Alzheimers disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. Early differentiation between both types of dementia may be challenging due to heterogeneity and overlap of symptoms. Here, we apply resting state functional magnetic resonance imaging (fMRI) to study functional brain connectivity differences between AD and bvFTD. Methods: We used resting state fMRI data of 31 AD patients, 25 bvFTD patients, and 29 controls from two centers specialized in dementia. We studied functional connectivity throughout the entire brain, applying two different analysis techniques, studying network-to-region and region-to-region connectivity. A general linear model approach was used to study group differences, while controlling for physiological noise, age, gender, study center, and regional gray matter volume. Results: Given gray matter differences, we observed decreased network-to-region connectivity in bvFTD between (a) lateral visual cortical network and lateral occipital and cuneal cortex, and (b) auditory system network and angular gyrus. In AD, we found decreased network-to-region connectivity between the dorsal visual stream network and lateral occipital and parietal opercular cortex. Region-to-region connectivity was decreased in bvFTD between superior temporal gyrus and cuneal, supracalcarine, intracalcarine cortex, and lingual gyrus. Conclusion: We showed that the pathophysiology of functional brain connectivity is different between AD and bvFTD. Our findings support the hypothesis that resting state fMRI shows disease-specific functional connectivity differences and is useful to elucidate the pathophysiology of AD and bvFTD. However, the group differences in functional connectivity are less abundant than has been shown in previous studies.

Relation between subcortical grey matter atrophy and conversion from mild cognitive impairment to Alzheimer's disease

Objective To investigate whether subcortical grey matter atrophy predicts progression from mild cognitive impairment (MCI) to Alzheimers disease (AD), and to compare subcortical volumes between AD, MCI and controls. To assess the correlation between subcortical grey matter volumes and severity of cognitive impairment. Methods We included 773 participants with three-dimensional T1-weighted MRI at 3 T, made up of 181 controls, who had subjective memory symptoms with normal cognition, 201 MCIs and 391 AD. During follow-up (2.0±0.9 years), 35 MCIs converted to AD (progressive MCI) and 160 MCIs remained stable (stable MCI). We segmented volumes of six subcortical structures of the amygdala, thalamus, caudate nucleus, putamen, globus pallidus and nucleus accumbens, and of the hippocampus, using FMRIBs integrated registration and segmentation tool. Results Analysis of variances, adjusted for sex and age, showed that all structures, except the globus pallidus, were smaller in AD than in controls. In addition, the amygdala, thalamus, putamen, nucleus accumbens and hippocampus were smaller in MCIs than in controls. Across groups, all subcortical greymatter volumes, except the globus pallidus, showed a positive correlation with cognitive function, as measured by Mini Mental State Examination (MMSE) (0.16<r<0.28, all p<0.05). Cox proportional hazards analyses adjusted for age, sex, education, Cambridge Cognitive Examination-Revised (CAMCOG-R) and MMSE showed that smaller volumes of the hippocampus and nucleus accumbens were associated with increased risk of progression from MCI to AD (HR (95% CI) 1.60 (1.15 to 2.21); 1.60 (1.09 to 2.35), p<0.05). Conclusions In addition to the hippocampus, the nucleus accumbens volume loss was also associated with increased risk of progression from MCI to AD. Furthermore, volume loss of subcortical grey matter structures was associated with severity of cognitive impairment.

More Atrophy of Deep Gray Matter Structures in Frontotemporal Dementia Compared to Alzheimer's Disease

BACKGROUND The involvement of frontostriatal circuits in frontotemporal dementia (FTD) suggests that deep gray matter structures (DGM) may be affected in this disease. OBJECTIVE We investigated whether volumes of DGM structures differed between patients with behavioral variant FTD (bvFTD), Alzheimers disease (AD), and subjective complaints (SC) and explored relationships between DGM structures, cognition, and neuropsychiatric functioning. METHODS For this cross-sectional study, we included 24 patients with FTD and matched them based on age, gender, and education at a ratio of 1:3 to 72 AD patients and 72 patients with SC who served as controls. Volumes of hippocampus, amygdala, thalamus, caudate nucleus, putamen, globus pallidus, and nucleus accumbens were estimated by automated segmentation of 3D T1-weighted MRI. MANOVA with Bonferroni adjusted post-hoc tests was used to compare volumes between groups. Relationships between volumes, cognition, and neuropsychiatric functioning were examined using multivariate linear regression and Spearman correlations. RESULTS Nucleus accumbens and caudate nucleus discriminated all groups, with most severe atrophy in FTD. Globus pallidus volumes were smallest in FTD and discriminated FTD from AD and SC. Hippocampus, amygdala, thalamus, and putamen were smaller in both dementia groups compared to SC. Associations between amygdala and memory were found to be different in AD and FTD. Globus pallidus and nucleus accumbens were related to attention and executive functioning in FTD. CONCLUSION Nucleus accumbens, caudate nucleus, and globus pallidus were more severely affected in FTD than in AD and SC. The associations between cognition and DGM structures varied between the diagnostic groups. The observed difference in volume of these DGM structures supports the idea that next to frontal cortical atrophy, DGM structures, as parts of the frontal circuits, are damaged in FTD rather than in AD.

Quantitative regional validation of the visual rating scale for posterior cortical atrophy

AbstractObjectivesValidate the four-point visual rating scale for posterior cortical atrophy (PCA) on magnetic resonance images (MRI) through quantitative grey matter (GM) volumetry and voxel-based morphometry (VBM) to justify its use in clinical practice.MethodsTwo hundred twenty-nine patients with probable Alzheimer’s disease and 128 with subjective memory complaints underwent 3T MRI. PCA was rated according to the visual rating scale. GM volumes of six posterior structures and the total posterior region were extracted using IBASPM and compared among PCA groups. To determine which anatomical regions contributed most to the visual scores, we used binary logistic regression. VBM compared local GM density among groups.ResultsPatients were categorised according to their PCA scores: PCA-0 (n = 122), PCA-1 (n = 143), PCA-2 (n = 79), and PCA-3 (n = 13). All structures except the posterior cingulate differed significantly among groups. The inferior parietal gyrus volume discriminated the most between rating scale levels. VBM showed that PCA-1 had a lower GM volume than PCA-0 in the parietal region and other brain regions, whereas between PCA-1 and PCA-2/3 GM atrophy was mostly restricted to posterior regions.ConclusionsThe visual PCA rating scale is quantitatively validated and reliably reflects GM atrophy in parietal regions, making it a valuable tool for the daily radiological assessment of dementia.Key Points• Visual rating scale reflects grey matter atrophy in posterior brain regions. • Different PCA scores corresponded well to different quantitative degrees of atrophy. • Inferior parietal gyrus volume influenced assessment based on the visual rating scale. • This simple visual rating scale makes it useful for radiological dementia assessment.

A Longitudinal Study on Resting State Functional Connectivity in Behavioral Variant Frontotemporal Dementia and Alzheimer’s Disease

BACKGROUND/OBJECTIVE Alzheimers disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. We applied longitudinal resting state functional magnetic resonance imaging (fMRI) to delineate functional brain connections relevant for disease progression and diagnostic accuracy. METHODS We used two-center resting state fMRI data of 20 AD patients (65.1±8.0 years), 12 bvFTD patients (64.7±5.4 years), and 22 control subjects (63.8±5.0 years) at baseline and 1.8-year follow-up. We used whole-network and voxel-based network-to-region analyses to study group differences in functional connectivity at baseline and follow-up, and longitudinal changes in connectivity within and between groups. RESULTS At baseline, connectivity between paracingulate gyrus and executive control network, between cuneal cortex and medial visual network, and between paracingulate gyrus and salience network was higher in AD compared with controls. These differences were also present after 1.8 years. At follow-up, connectivity between angular gyrus and right frontoparietal network, and between paracingulate gyrus and default mode network was lower in bvFTD compared with controls, and lower compared with AD between anterior cingulate gyrus and executive control network, and between lateral occipital cortex and medial visual network. Over time, connectivity decreased in AD between precuneus and right frontoparietal network and in bvFTD between inferior frontal gyrus and left frontoparietal network. Longitudinal changes in connectivity between supramarginal gyrus and right frontoparietal network differ between both patient groups and controls. CONCLUSION We found disease-specific brain regions with longitudinal connectivity changes. This suggests the potential of longitudinal resting state fMRI to delineate regions relevant for disease progression and for diagnostic accuracy, although no group differences in longitudinal changes in the direct comparison of AD and bvFTD were found.

Differences in structural covariance brain networks between behavioral variant frontotemporal dementia and Alzheimer's disease

Disease‐specific patterns of gray matter atrophy in Alzheimers disease (AD) and behavioral variant frontotemporal dementia (bvFTD) overlap with distinct structural covariance networks (SCNs) in cognitively healthy controls. This suggests that both types of dementia target specific structural networks. Here, we study SCNs in AD and bvFTD. We used structural magnetic resonance imaging data of 31 AD patients, 24 bvFTD patients, and 30 controls from two centers specialized in dementia. Ten SCNs were defined based on structural covariance of gray matter density using independent component analysis. We studied group differences in SCNs using F‐tests, with Bonferroni corrected t‐tests, adjusted for age, gender, and study center. Associations with cognitive performance were studied using linear regression analyses. Cross‐sectional group differences were found in three SCNs (all P < 0.0025). In bvFTD, we observed decreased anterior cingulate network integrity compared with AD and controls. Patients with AD showed decreased precuneal network integrity compared with bvFTD and controls, and decreased hippocampal network and anterior cingulate network integrity compared with controls. In AD, we found an association between precuneal network integrity and global cognitive performance (P = 0.0043). Our findings show that AD and bvFTD target different SCNs. The comparison of both types of dementia showed decreased precuneal (i.e., default mode) network integrity in AD and decreased anterior cingulate (i.e., salience) network integrity in bvFTD. This confirms the hypothesis that AD and bvFTD have distinct anatomical networks of degeneration and shows that structural covariance gives valuable insights in the understanding of network pathology in dementia. Hum Brain Mapp 37:978–988, 2016.

Identifying bvFTD Within the Wide Spectrum of Late Onset Frontal Lobe Syndrome: A Clinical Approach

OBJECTIVE The behavioral variant of frontotemporal dementia (bvFTD) can be difficult to diagnose because of the extensive differential diagnosis, including many other diseases presenting with a frontal lobe syndrome. We aimed to identify the diagnostic spectrum causing a late onset frontal lobe syndrome and examine the quality of commonly used instruments to distinguish between bvFTD and non-bvFTD patients, within this syndrome. METHODS A total of 137 patients fulfilling the criteria of late onset frontal lobe syndrome, aged 45 to 75 years, were included in a prospective observational study. Diagnoses were made after clinical and neuropsychological examination, and neuroimaging and cerebral spinal fluid results were taken into account. Baseline characteristics and the scores on the Mini-Mental State Exam (MMSE), frontal assessment battery (FAB), Frontal Behavioral Inventory (FBI), and Stereotypy Rating Inventory (SRI) were compared between the bvFTD and the non-bvFTD group. RESULTS Fifty-five (40%) of the patients received a bvFTD diagnosis (33% probable and 7% possible bvFTD). Fifty-one patients (37%) had a psychiatric disorder, including 20 with major depressive disorder. Thirty-one patients received an alternative neurological, including neurodegenerative, diagnosis. MMSE and FAB scores were unspecific for a particular diagnosis. A score above 12 on the positive FBI subscale or a score above 5 on the SRI were indicative of a bvFTD diagnosis. CONCLUSION A broad spectrum of both neurological and psychiatric disorders underlies late onset frontal lobe syndrome, of which bvFTD was the most prevalent diagnosis in our cohort. The commonly used MMSE and the FAB could not successfully distinguish between bvFTD and non-bvFTD, but this could be achieved with the more specific FBI and SRI.