Katharina Brueggen

Basal Forebrain and Hippocampus as Predictors of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment - A Multicenter DTI and Volumetry Study

BACKGROUND Hippocampal grey matter (GM) atrophy predicts conversion from mild cognitive impairment (MCI) to Alzheimers disease (AD). Pilot data suggests that mean diffusivity (MD) in the hippocampus, as measured with diffusion tensor imaging (DTI), may be a more accurate predictor of conversion than hippocampus volume. In addition, previous studies suggest that volume of the cholinergic basal forebrain may reach a diagnostic accuracy superior to hippocampal volume in MCI. OBJECTIVE The present study investigated whether increased MD and decreased volume of the hippocampus, the basal forebrain and other AD-typical regions predicted time to conversion from MCI to AD dementia. METHODS 79 MCI patients with DTI and T1-weighted magnetic resonance imaging (MRI) were retrospectively included from the European DTI Study in Dementia (EDSD) dataset. Of these participants, 35 converted to AD dementia after 6-46 months (mean: 21 months). We used Cox regression to estimate the relative conversion risk predicted by MD values and GM volumes, controlling for age, gender, education and center. RESULTS Decreased GM volume in all investigated regions predicted an increased risk for conversion. Additionally, increased MD in the right basal forebrain predicted increased conversion risk. Reduced volume of the right hippocampus was the only significant predictor in a stepwise model combining all predictor variables. CONCLUSION Volume reduction of the hippocampus, the basal forebrain and other AD-related regions was predictive of increased risk for conversion from MCI to AD. In this study, volume was superior to MD in predicting conversion.

Disrupted white matter structural networks in healthy older adult APOE ε4 carriers – An international multicenter DTI study

The ε4 allelic variant of the Apolipoprotein E gene (APOE ε4) is the best-established genetic risk factor for late-onset Alzheimers disease (AD). White matter (WM) microstructural damages measured with Diffusion Tensor Imaging (DTI) represent an early sign of fiber tract disconnection in AD. We examined the impact of APOE ε4 on WM microstructure in elderly individuals from the multicenter European DTI Study on Dementia. Voxelwise statistical analysis of fractional anisotropy (FA), mean diffusivity, radial and axial diffusivity (MD, radD and axD respectively) was carried out using Tract-Based Spatial Statistics. Seventy-four healthy elderly individuals - 31 APOE ε4 carriers (APOE ε4+) and 43 APOE ε4 non-carriers (APOE ε4-) -were considered for data analysis. All the results were corrected for scanner acquisition protocols, age, gender and for multiple comparisons. APOE ε4+ and APOE ε4- subjects were comparable regarding sociodemographic features and global cognition. A significant reduction of FA and increased radD was found in the APOE ε4+ compared to the APOE ε4- in the cingulum, in the corpus callosum, in the inferior fronto-occipital and in the inferior longitudinal fasciculi, internal and external capsule. APOE ε4+, compared to APOE ε4- showed higher MD in the genu, right internal capsule, superior longitudinal fasciculus and corona radiate. Comparisons stratified by center supported the results obtained on the whole sample. These findings support previous evidence in monocentric studies indicating a modulatory role of APOE ɛ4 allele on WM microstructure in elderly individuals at risk for AD suggesting early vulnerability and/or reduced resilience of WM tracts involved in AD.

Mean diffusivity in cortical gray matter in Alzheimer's disease: The importance of partial volume correction

Mean diffusivity (MD) measured by diffusion tensor imaging can reflect microstructural alterations of the brains gray matter (GM). Therefore, GM MD may be a sensitive marker of neurodegeneration related to Alzheimers Disease (AD). However, due to partial volume effects (PVE), differences in MD may be overestimated because of a higher degree of brain atrophy in AD patients and in cases with mild cognitive impairment (MCI). Here, we evaluated GM MD changes in AD and MCI compared with healthy controls, and the effect of partial volume correction (PVC) on diagnostic utility of MD. We determined region of interest (ROI) and voxel-wise group differences and diagnostic accuracy of MD and volume measures between matched samples of 39 AD, 39 MCI and 39 healthy subjects before and after PVC. Additionally, we assessed whether effects of GM MD values on diagnosis were mediated by volume. ROI and voxel-wise group differences were reduced after PVC. When using these ROIs for predicting group separation in logistic models, both PVE corrected and uncorrected GM MD values yielded a poorer diagnostic accuracy in single predictor models than regional volume. For the discrimination of AD patients and healthy controls, the effect of GM MD on diagnosis was significantly mediated by volume of hippocampus and posterior cingulate ROIs. Our results suggest that GM MD measurements are strongly confounded by PVE in the presence of brain atrophy, underlining the necessity of PVC when using these measurements as specific metrics of microstructural tissue degeneration. Independently of PVC, regional MD was not superior to regional volume in separating prodromal and clinical stages of AD from healthy controls.

Early changes in Alpha band power and DMN BOLD activity in Alzheimer’s disease: A simultaneous resting state EEG-fMRI study

Simultaneous resting state functional magnetic resonance imaging (rsfMRI)–resting state electroencephalography (rsEEG) studies in healthy adults showed robust positive associations of signal power in the alpha band with BOLD signal in the thalamus, and more heterogeneous associations in cortical default mode network (DMN) regions. Negative associations were found in occipital regions. In Alzheimer’s disease (AD), rsfMRI studies revealed a disruption of the DMN, while rsEEG studies consistently reported a reduced power within the alpha band. The present study is the first to employ simultaneous rsfMRI-rsEEG in an AD sample, investigating the association of alpha band power and BOLD signal, compared to healthy controls (HC). We hypothesized to find reduced positive associations in DMN regions and reduced negative associations in occipital regions in the AD group. Simultaneous resting state fMRI–EEG was recorded in 14 patients with mild AD and 14 HC, matched for age and gender. Power within the EEG alpha band (8–12 Hz, 8–10 Hz, and 10–12 Hz) was computed from occipital electrodes and served as regressor in voxel-wise linear regression analyses, to assess the association with the BOLD signal. Compared to HC, the AD group showed significantly decreased positive associations between BOLD signal and occipital alpha band power in clusters in the superior, middle and inferior frontal cortex, inferior temporal lobe and thalamus (p < 0.01, uncorr., cluster size ≥ 50 voxels). This group effect was more pronounced in the upper alpha sub-band, compared to the lower alpha sub-band. Notably, we observed a high inter-individual heterogeneity. Negative associations were only reduced in the lower alpha range in the hippocampus, putamen and cerebellum. The present study gives first insights into the relationship of resting-state EEG and fMRI characteristics in an AD sample. The results suggest that positive associations between alpha band power and BOLD signal in numerous regions, including DMN regions, are diminished in AD.

The Primacy Effect in Amnestic Mild Cognitive Impairment: Associations with Hippocampal Functional Connectivity

Background: The “primacy effect,” i.e., increased memory recall for the first items of a series compared to the following items, is reduced in amnestic mild cognitive impairment (aMCI). Memory task-fMRI studies demonstrated that primacy recall is associated with higher activation of the hippocampus and temporo-parietal and frontal cortical regions in healthy subjects. Functional magnetic resonance imaging (fMRI) at resting state revealed that hippocampus functional connectivity (FC) with neocortical brain areas, including regions of the default mode network (DMN), is altered in aMCI. The present study aimed to investigate whether resting state fMRI FC between the hippocampus and cortical brain regions, especially the DMN, is associated with primacy recall performance in aMCI. Methods: A number of 87 aMCI patients underwent resting state fMRI and verbal episodic memory assessment. FC between the left or right hippocampus, respectively, and all other voxels in gray matter was mapped voxel-wise and used in whole-brain regression analyses, testing whether FC values predicted delayed primacy recall score. The delayed primacy score was defined as the number of the first four words recalled on the California Verbal Learning Test. Additionally, a partial least squares (PLS) analysis was performed, using DMN regions as seeds to identify the association of their functional interactions with delayed primacy recall. Results: Voxel-based analyses indicated that delayed primacy recall was mainly (positively) associated with higher FC between the left and right hippocampus. Additionally, significant associations were found for higher FC between the left hippocampus and bilateral temporal cortex, frontal cortical regions, and for higher FC between the right hippocampus and right temporal cortex, right frontal cortical regions, left medial frontal cortex and right amygdala (p < 0.01, uncorr.). PLS analysis revealed positive associations of delayed primacy recall with FC between regions of the DMN, including the left and right hippocampus, as well as middle cingulate cortex and thalamus (p < 0.04). In conclusion, in the light of decreased hippocampus function in aMCI, inter-hemispheric hippocampus FC and hippocampal FC with brain regions predominantly included in the DMN may contribute to residual primacy recall in aMCI.

Hippocampal mean diffusivity for the diagnosis of dementia and mild cognitive impairment in primary care

BACKGROUND Hippocampal mean diffusivity (MD) measured by Diffusion-Tensor Imaging is a promising diagnostic marker for Mild Cognitive Impairment (MCI) and dementia. Its performance has yet to be evaluated in primary care patients, who vary systematically from patients visiting specialized care settings. OBJECTIVE We assessed the diagnostic accuracy of hippocampus diffusivity for detecting MCI and dementia in a sample recruited from primary care, compared to a sample from specialized care. METHOD One sample was recruited from a primary care intervention trial (DelpHi-MV) (n=70), and the other sample was recruited from our memory clinic (n=70). The samples were matched pairwise for diagnosis, MMSE, age, gender, and education. They included dementia patients, MCI patients and healthy subjects. Mean MD was calculated for the left and right hippocampus, corrected for partial volume effects. Within each sample, left or right hippocampal MD served as predictor for diagnostic group in logistic regressions, which were additionally controlled for white matter lesions. RESULTS In the primary care sample, hippocampal MD detected dementia with high cross-validated accuracy (left: AUC=.92; right: AUC=.85), but did not classify MCI with an accuracy above chance (left: AUC=.58; right: AUC=.44). In the memory clinic sample, hippocampal MD classified both dementia (left: AUC=.91; right: AUC=.91) and MCI (left: AUC=.86; right: AUC=.83) with high cross-validated accuracy. CONCLUSION Hippocampal MD supported the identification of dementia but did not contribute to the detection of MCI in the primary care patient population.

STRUCTURAL INTEGRITY IN SUBJECTIVE COGNITIVE DECLINE, MILD COGNITIVE IMPAIRMENT AND ALZHEIMER’S DISEASE BASED ON MULTICENTER DIFFUSION TENSOR IMAGING: RESULTS FROM THE DELCODE STUDY

discrimination between NC and AD stratified by age was also calculated, optimal MTA cut-off values for the age ranges 50-64, 65–74, 75-84 were 1.0, 1.5, 2.0, the sensitivity and specificity were 92.3% and 68.4%; 90.4% and 85.2%, 70.8% and 82.3%, respectively(Table 1). Conclusions: This new age-based cutoff of MTA scale showed better diagnostic accuracy for detecting AD with high sensitivity and specificity in Chinese population.

COGNITIVE RESERVE AND HIPPOCAMPAL MICROSTRUCTURAL INTEGRITY IN COGNITIVELY HEALTHY OLDER PEOPLE AND MCI PATIENTS

cognitive change over time in the presence of amyloid pathology. Methods: Cognitively normal individuals (N1⁄4253) in the Harvard Aging Brain Study were followed for an average of 4.4 years (range 1-7 years) after baseline assessment on cognitive and brain indices. Cognitive change from the first follow-up was measured using a global composite that incorporated aspects of memory, executive function, and processing speed. Cognitive resilience was operationalized as the residual of baseline global cognition after regressing the effects of age, sex, years of education, and socio-economic status. Brain resilience was operationalized as the residual shared variance among cortical and regional thickness measures, hippocampus and striatal volume, fractional anisotropy of thewhitematter, and glucose metabolism after regressing the effects of age, sex, years of education, socio-economic status. Cognitive resilience and brain resilience were only weakly correlated with one another. A linear mixed model framework examined the impact of interactions between baseline amyloid burden (measured with Pittsburgh Compound B) and cognitive resilience or brain resilience on the trajectory of cognitive change, controlling for APOE and demographic factors. Results: Cognitive resilience was associated with baseline cognitive performance but not with change over time, and did not interact with amyloid burden. Brain resilience was weakly associated with baseline cognitive performance but was significantly associated with less decline in cognition over time, and exhibited an interaction (Time*Brain Resilience*Amyloid, p<.005) such that the impact of elevated amyloid burden on cognitive decline was moderated by higher brain resilience (see Figure).Conclusions:These results suggest that indices of brain health, rather than cognitive health, at baseline may aid in prediction of cognitive change over time, and may protect against decline associated with amyloid pathology. Understanding how such measures of brain health immunize an individual against amyloid-related cognitive decline may provide clues to delaying or preventing the onset of Alzheimer’s dementia.

MICROSTRUCTURAL CHANGES IN ALZHEIMER’S DISEASE, MILD COGNITIVE IMPAIRMENT, AND SUBJECTIVE COGNITIVE DECLINE BASED ON MULTICENTER DIFFUSION TENSOR IMAGING: A TBSS ANALYSIS OF DELCODE DATA

Figure 2. Proportion of subjects in each category (normal vs abnormal) at each EBM stage. Proportion of negative scans in dark blue and positive scans in green. Each EBM stage on the x-axis corresponds to the occurrence of a new regional transition event. Stage 0 corresponds to no events having occurred and stage 20 is when all events have occurred. Events are ordered by the maximum likelihood event sequence for the whole population as shown in Figure 1.

USEFULNESS AND STABILITY OF MULTICENTER DIFFUSION TENSOR IMAGING AS AN EARLY MARKER FOR SUBJECTIVE COGNITIVE DECLINE AND AMNESTIC MILD COGNITIVE IMPAIRMENT: FIRST RESULTS FROM THE PROSPECTIVE DZNE DELCODE STUDY

heterogeneous, being associated with all four subtypes, but predominantly the frontotemporal and subcortical subtypes. Conclusions:We demonstrate the use of a probabilistic generative model of disease subtypes to characterise genetic FTD heterogeneity. Our results provide new insights into the phenotypic variability in the C9orf72 mutation, revealing that this group consists neuroanatomically of two major subtypes. Further studies will be required to understand how these map on to the underlying clinical syndromes and pathology.