Scott A. Przybelski

MRI patterns of atrophy associated with progression to AD in amnestic Mild Cognitive Impairment

Objective: To compare the patterns of gray matter loss in subjects with amnestic mild cognitive impairment (aMCI) who progress to Alzheimer disease (AD) within a fixed clinical follow-up time vs those who remain stable. Methods: Twenty-one subjects with aMCI were identified from the Mayo Clinic Alzheimers research program who remained clinically stable for their entire observed clinical course (aMCI-S), where the minimum required follow-up time from MRI to last follow-up assessment was 3 years. These subjects were age- and gender-matched to 42 aMCI subjects who progressed to AD within 18 months of the MRI (aMCI-P). Each subject was then age- and gender-matched to a control subject. Voxel-based morphometry (VBM) was used to assess patterns of gray matter atrophy in the aMCI-P and aMCI-S groups compared to the control group, and compared to each other. Results: The aMCI-P group showed bilateral loss affecting the medial and inferior temporal lobe, temporoparietal association neocortex, and frontal lobes, compared to controls. The aMCI-S group showed no regions of gray matter loss when compared to controls. When the aMCI-P and aMCI-S groups were compared directly, the aMCI-P group showed greater loss in the medial and inferior temporal lobes, the temporoparietal neocortex, posterior cingulate, precuneus, anterior cingulate, and frontal lobes than the aMCI-S group. Conclusions: The regions of loss observed in subjects with amnestic mild cognitive impairment (aMCI) who progressed to Alzheimer disease (AD) within 18 months of the MRI are typical of subjects with AD. The lack of gray matter loss in subjects with aMCI who remained clinically stable for their entire observed clinical course is consistent with the notion that patterns of atrophy on MRI at baseline map well onto the subsequent clinical course. GLOSSARY: AD = Alzheimer disease; ADNI = Alzheimers Disease Neuroimaging Initiative; ADPR = Alzheimers Disease Patient Registry; ADRC = Mayo Clinic Alzheimers Disease Research Center; aMCI = amnestic mild cognitive impairment; APOE e4 = apolipoprotein epsilon 4; AVLT = Auditory Verbal Learning Test; CDR-SB = CDR sum of boxes; DCT = discrete cosine transformation; FDR = false discovery rate; FWHM = full-width at half-maximum; GM = gray matter; MMSE = Mini-Mental State Examination; MNI = Montreal Neurological Institute; NIA = National Institute on Aging; TIV = total intracranial volume; VBM = voxel-based morphometry; WM = white matter; WMH = white matter hyperintensity.

Non-Stationarity in the “Resting Brain’s” Modular Architecture

Task-free functional magnetic resonance imaging (TF-fMRI) has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs) identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892) population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain’s modular organization and assign each region to a “meta-modular” group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN) between 28 subjects with Alzheimer’s dementia and 56 cognitively normal elderly subjects matched 1∶2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer’s disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer’s dementia.

Age-related changes in the default mode network are more advanced in Alzheimer disease

Objective: To investigate age-related default mode network (DMN) connectivity in a large cognitively normal elderly cohort and in patients with Alzheimer disease (AD) compared with age-, gender-, and education-matched controls. Methods: We analyzed task-free–fMRI data with both independent component analysis and seed-based analysis to identify anterior and posterior DMNs. We investigated age-related changes in connectivity in a sample of 341 cognitively normal subjects. We then compared 28 patients with AD with 56 cognitively normal noncarriers of the APOE ϵ4 allele matched for age, education, and gender. Results: The anterior DMN shows age-associated increases and decreases in fontal lobe connectivity, whereas the posterior DMN shows mainly age-associated declines in connectivity throughout. Relative to matched cognitively normal controls, subjects with AD display an accelerated pattern of the age-associated changes described above, except that the declines in frontal lobe connectivity did not reach statistical significance. These changes survive atrophy correction and are correlated with cognitive performance. Conclusions: The results of this study indicate that the DMN abnormalities observed in patients with AD represent an accelerated aging pattern of connectivity compared with matched controls.

Distinct anatomical subtypes of the behavioural variant of frontotemporal dementia: a cluster analysis study

The behavioural variant of frontotemporal dementia is a progressive neurodegenerative syndrome characterized by changes in personality and behaviour. It is typically associated with frontal lobe atrophy, although patterns of atrophy are heterogeneous. The objective of this study was to examine case-by-case variability in patterns of grey matter atrophy in subjects with the behavioural variant of frontotemporal dementia and to investigate whether behavioural variant of frontotemporal dementia can be divided into distinct anatomical subtypes. Sixty-six subjects that fulfilled clinical criteria for a diagnosis of the behavioural variant of frontotemporal dementia with a volumetric magnetic resonance imaging scan were identified. Grey matter volumes were obtained for 26 regions of interest, covering frontal, temporal and parietal lobes, striatum, insula and supplemental motor area, using the automated anatomical labelling atlas. Regional volumes were divided by total grey matter volume. A hierarchical agglomerative cluster analysis using Wards clustering linkage method was performed to cluster the behavioural variant of frontotemporal dementia subjects into different anatomical clusters. Voxel-based morphometry was used to assess patterns of grey matter loss in each identified cluster of subjects compared to an age and gender-matched control group at P < 0.05 (family-wise error corrected). We identified four potentially useful clusters with distinct patterns of grey matter loss, which we posit represent anatomical subtypes of the behavioural variant of frontotemporal dementia. Two of these subtypes were associated with temporal lobe volume loss, with one subtype showing loss restricted to temporal lobe regions (temporal-dominant subtype) and the other showing grey matter loss in the temporal lobes as well as frontal and parietal lobes (temporofrontoparietal subtype). Another two subtypes were characterized by a large amount of frontal lobe volume loss, with one subtype showing grey matter loss in the frontal lobes as well as loss of the temporal lobes (frontotemporal subtype) and the other subtype showing loss relatively restricted to the frontal lobes (frontal-dominant subtype). These four subtypes differed on clinical measures of executive function, episodic memory and confrontation naming. There were also associations between the four subtypes and genetic or pathological diagnoses which were obtained in 48% of the cohort. The clusters did not differ in behavioural severity as measured by the Neuropsychiatric Inventory; supporting the original classification of the behavioural variant of frontotemporal dementia in these subjects. Our findings suggest behavioural variant of frontotemporal dementia can therefore be subdivided into four different anatomical subtypes.

Atrophy rates accelerate in amnestic mild cognitive impairment

Background: We tested if rates of brain atrophy accelerate in individuals with amnestic mild cognitive impairment (aMCI) as they progress to typical late onset Alzheimer disease (AD). We included comparisons to subjects with aMCI who did not progress (labeled aMCI-S) and also to cognitively normal elderly subjects (CN). Methods: We studied 46 subjects with aMCI who progressed to AD (labeled aMCI-P), 46 CN, and 23 aMCI-S. All subjects must have had three or more serial MRI scans. Rates of brain shrinkage and ventricular expansion were measured across all available serial MRI scans in each subject. Change in volumes relative to the point at which subjects progressed to a clinical diagnosis of AD (the index date) was modeled in aMCI-P. Change in volumes relative to age was modeled in all three clinical groups. Results: In aMCI-P the change in pre to post index rate (i.e., acceleration) of ventricular expansion was 1.7 cm3/year, and acceleration in brain shrinkage was 5.3 cm3/year. Brain volume declined and ventricular volume increased in all three groups with age. Volume changes decelerated with increasing age in aMCI-P, and to a lesser extent in aMCI-S, but were linear in the matched CN. Among all subjects with aMCI, rates of atrophy were greater in apolipoprotein E ε4 carriers than noncarriers. Conclusions: Rates of atrophy accelerate as individuals progress from amnestic mild cognitive impairment (aMCI) to typical late onset Alzheimer disease (AD). Rates of atrophy are greater in younger than older subjects with aMCI who progressed to AD and subjects with aMCI who did not progress. We did not find that atrophy rates varied with age in 70- to 90-year-old cognitively normal subjects.

Effect of APOE ε4 Status on Intrinsic Network Connectivity in Cognitively Normal Elderly Subjects

OBJECTIVE To examine default mode and salience network functional connectivity as a function of APOE ε4 status in a group of cognitively normal age-, sex-, and education-matched older adults. DESIGN Case-control study. SUBJECTS Fifty-six cognitively normal APOE ε4 carriers and 56 age-, sex- and education-matched cognitively normal APOE ε4 noncarriers. MAIN OUTCOME MEASURE Alterations in in-phase default mode and salience network connectivity in APOE ε4 carriers compared with APOE ε4 noncarriers ranging from 63 to 91 years of age. RESULTS A posterior cingulate seed revealed decreased in-phase connectivity in regions of the posterior default mode network that included the left inferior parietal lobe, left middle temporal gyrus, and bilateral anterior temporal lobes in the ε4 carriers relative to APOE ε4 noncarriers. An anterior cingulate seed showed greater in-phase connectivity in the salience network including the cingulate gyrus, medial prefrontal cortex, bilateral insular cortex, striatum, and thalamus in APOE ε4 carriers vs noncarriers. There were no groupwise differences in brain anatomy. CONCLUSIONS The observation of functional alterations in default mode and salience network connectivity in the absence of structural changes between APOE ε4 carriers and noncarriers suggests that alterations in connectivity may have the potential to serve as an early biomarker.

Clinicopathologic and 11C-Pittsburgh compound B implications of Thal amyloid phase across the Alzheimer’s disease spectrum

Murray et al. examine the correspondence between Thal amyloid phase, tau pathology and clinical characteristics in a large Alzheimer’s disease autopsy series. They extrapolate their findings to an autopsy cohort for which Pittsburgh compound-B imaging data are available, and evaluate the neuropathological significance of a quantitative amyloid-β imaging cut-off point.

Dementia with Lewy bodies and Alzheimer disease: Neurodegenerative patterns characterized by DTI

Objective: To identify the patterns of diffusivity changes in patients with dementia with Lewy bodies (DLB) and Alzheimer disease (AD) and to determine whether diffusion tensor MRI (DTI) is complementary to structural MRI in depicting the tissue abnormalities characteristic of DLB and AD. Methods: We studied clinically diagnosed age-, gender-, and education-matched subjects with DLB (n = 30), subjects with AD (n = 30), and cognitively normal (CN) subjects (n = 60) in a case-control study. DTI was performed at 3T with a fluid-attenuated inversion recovery–based DTI sequence that enabled cortical diffusion measurements. Mean diffusivity (MD) and gray matter (GM) density were measured from segmented cortical regions. Tract-based diffusivity was measured using color-coded fractional anisotropy (FA) maps. Results: Patients with DLB were characterized by elevated MD in the amygdala and decreased FA in the inferior longitudinal fasciculus (ILF). ILF diffusivity was associated with the presence of visual hallucinations (p = 0.007), and amygdala diffusivity was associated with Unified Parkinsons Disease Rating Scale (r = 0.50; p = 0.005) in DLB. In contrast, patients with AD were characterized by elevated MD in the medial temporal, temporal, and parietal lobe association cortices and decreased FA in the fornix, cingulum, and ILF. Amygdala diffusivity was complementary to GM density in discriminating DLB from CN; hippocampal and parahippocampal diffusivity was complementary to GM density in discriminating AD from CN. Conclusion: Increased amygdalar diffusivity in the absence of tissue loss in dementia with Lewy bodies (DLB) may be related to microvacuolation, a common pathology associated with Lewy body disease in the amygdala. Diffusivity measurements were complementary to structural MRI, demonstrating that measures of diffusivity on diffusion tensor MRI are valuable tools for characterizing the tissue abnormalities characteristic of Alzheimer disease and DLB.

Multimodality Imaging Characteristics of Dementia with Lewy Bodies

Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimers disease (AD). Our objective was to determine whether the (11)C-Pittsburgh Compound-B (PiB) retention and regional hypometabolism on positron emission tomography (PET) and regional cortical atrophy on magnetic resonance imaging (MRI) are complementary in characterizing patients with DLB and differentiating them from AD. We studied age-, gender-, and education-matched patients with a clinical diagnosis of DLB (n = 21), AD (n = 21), and cognitively normal subjects (n = 42). Hippocampal atrophy, global cortical PiB retention and occipital lobe metabolism in combination distinguished DLB from AD better than any of the measurements alone (area under the receiver operating characteristic = 0.98). Five of the DLB and AD patients who underwent autopsy were distinguished through multimodality imaging. These data demonstrate that magnetic resonance imaging and PiB positron emission tomography contribute to characterizing the distinct pathological mechanisms in patients with AD compared with DLB. Occipital and posterior parietotemporal lobe hypometabolism is a distinguishing feature of DLB and this regional hypometabolic pattern is independent of the amyloid pathology.

APOE modifies the association between Aβ load and cognition in cognitively normal older adults.

Objective: To determine the relationship between β-amyloid (Aβ) load as measured by [11C]–Pittsburgh compound B (PiB) PET and cognitive function in cognitively normal older adults. Methods: We studied 408 cognitively normal older adults who participated in the population-based Mayo Clinic Study of Aging (MCSA) from January 2009 through March 2011. The participants underwent PiB PET and neuropsychometric testing within 6 months. The association between PiB retention and cognitive function was measured by partial correlation and an interaction with APOE status was tested using linear regression after adjusting for age, sex, and education. Results: Higher PiB retention was associated with cognitive performance (Spearman partial r = −0.18; p < 0.01), specifically the memory, language, attention/executive, and visual-spatial processing domains in the whole group of participants. The association between PiB retention and cognition was modified by the APOE status on linear regression analysis even after controlling for the differences in the distribution of PiB values among APOE ϵ4 carriers and noncarriers (p = 0.02). Cognitive performance was associated with the Aβ deposition in the frontal, temporal, and parietal lobe association cortices in APOE ϵ4 carriers on SPM analysis (p < 0.001). Conclusion: There is a modest association between PiB retention and cognitive function in cognitively normal older adults and this relationship between Aβ load and cognitive function is modified by APOE status. Whereas Aβ load is associated with greater cognitive impairment in APOE ϵ4 carriers, the cognitive function in APOE ϵ4 noncarriers is influenced less by the Aβ load, suggesting that APOE isoforms modulate the harmful effects of Aβ on cognitive function. Neurology® 2012;78:232–240