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

Cerebral atrophy in mild cognitive impairment: A systematic review with meta-analysis

INTRODUCTION

Although mild cognitive impairment (MCI) diagnosis is mainly based on cognitive assessment, reliable estimates of structural changes in specific brain regions, that could be contrasted against normal brain aging and inform diagnosis, are lacking. This study aimed to systematically review the literature reporting on MCI-related brain changes.

METHODS

The MEDLINE database was searched for studies investigating longitudinal structural changes in MCI. Studies with compatible data were included in the meta-analyses. A qualitative review was conducted for studies excluded from meta-analyses.

RESULTS

The analyses revealed a 2.2-fold higher volume loss in the hippocampus, 1.8-fold in the whole brain, and 1.5-fold in the entorhinal cortex in MCI participants.

DISCUSSION

Although the medial temporal lobe is likely to be more vulnerable to MCI pathology, atrophy in this brain area represents a relatively small proportion of whole brain loss, suggesting that future investigations are needed to identify the source of unaccounted volume loss in MCI.

Cognitive and Brain Profiles Associated with Current Neuroimaging Biomarkers of Preclinical Alzheimer's Disease

Neuroimaging biomarkers, namely hippocampal volume loss, temporoparietal hypometabolism, and neocortical β-amyloid (Aβ) deposition, are included in the recent research criteria for preclinical Alzheimer's disease (AD). However, how to use these biomarkers is still being debated, especially regarding their sequence. Our aim was to characterize the cognitive and brain profiles of elders classified as positive or negative for each biomarker to further our understanding of their use in the preclinical diagnosis of AD. Fifty-four cognitively normal individuals (age = 65.8 ± 8.3 years) underwent neuropsychological tests (structural MRI, FDG-PET, and Florbetapir-PET) and were dichotomized into positive or negative independently for each neuroimaging biomarker. Demographic, neuropsychological, and neuroimaging data were compared between positive and negative subgroups. The MRI-positive subgroup had lower executive performances and mixed patterns of lower volume and metabolism in AD-characteristic regions and in the prefrontal cortex. The FDG-positive subgroup showed only hypometabolism, predominantly in AD-sensitive areas extending to the whole neocortex, compared with the FDG-negative subgroup. The amyloid-positive subgroup was older and included more APOE ε4 carriers compared with the amyloid-negative subgroup. When considering MRI and/or FDG biomarkers together (i.e., the neurodegeneration-positive), there was a trend for an inverse relationship with Aβ deposition such that those with neurodegeneration tended to show less Aβ deposition and the reverse was true as well. Our findings suggest that: (1) MRI and FDG biomarkers provide complementary rather than redundant information and (2) relatively young cognitively normal elders tend to have either neurodegeneration or Aβ deposition, but not both, suggesting additive rather than sequential/causative links between AD neuroimaging biomarkers at this age. Significance statement: Neuroimaging biomarkers are included in the recent research criteria for preclinical Alzheimer's disease (AD). However, how to use these biomarkers is still being debated, especially regarding their sequence. Our findings suggest that MRI and FDG-PET biomarkers should be used in combination, offering an additive contribution instead of reflecting the same process of neurodegeneration. Moreover, the present study also challenges the hierarchical use of the neuroimaging biomarkers in preclinical AD because it suggests that the neurodegeneration observed in this population is not due to β-amyloid deposition. Rather, our results suggest that β-amyloid- and tau-related pathological processes may interact but not necessarily appear in a systematic sequence.

Different definitions of neurodegeneration produce similar amyloid/neurodegeneration biomarker group findings

In a cross-sectional imaging study of 1331 cognitively non-impaired subjects aged 50–89, Jack et al. assess the consequences of defining neurodegeneration in five different ways on demographic associations with neurodegeneration, and on amyloidosis and neurodegeneration biomarker status by age. Different neurodegeneration measures provide similar but not completely redundant information.

We recently demonstrated that the frequencies of biomarker groups defined by the presence or absence of both amyloidosis (A+) and neurodegeneration (N+) changed dramatically by age in cognitively non-impaired subjects. Our present objectives were to assess the consequences of defining neurodegeneration in five different ways on the frequency of subjects classified as N+, on the demographic associations with N+, and on amyloidosis and neurodegeneration (A/N) biomarker group frequencies by age. This was a largely cross-sectional observational study of 1331 cognitively non-impaired subjects aged 50–89 drawn from a population-based study of cognitive ageing. We assessed demographic associations with N+, and A/N biomarker group frequencies by age where A+ was defined by amyloid PET and N+ was defined in five different ways: (i) abnormal adjusted hippocampal volume alone; (ii) abnormal Alzheimer’s disease signature cortical thickness alone; (iii) abnormal fluorodeoxyglucose positron emission tomography alone; (iv) abnormal adjusted hippocampal volume or abnormal fluorodeoxyglucose positron emission tomography; and (v) abnormal Alzheimer’s disease signature cortical thickness or abnormal fluorodeoxyglucose positron emission tomography. For each N+ definition, participants were assigned to one of four biomarker groups; A−N−, A+N−, A−N+, or A+N+. The three continuous individual neurodegeneration measures were moderately correlated (r_s = 0.42 to 0.54) but when classified as normal or abnormal had only weak agreement (κ = 0.20 to 0.29). The adjusted hippocampal volume alone definition classified the fewest subjects as N+ while the Alzheimer’s disease signature cortical thickness or abnormal fluorodeoxyglucose positron emission tomography definition classified the most as N+. Across all N+ definitions, N+ subjects tended to be older, more often male and APOE4 carriers, and performed less well on functional status and learning and memory than N− subjects. For all definitions of neurodegeneration, (i) the frequency of A−N− was 100% at age 50 and declined monotonically thereafter; (ii) the frequency of A+N− increased from age 50 to a maximum in the mid-70s and declined thereafter; and3 (iii) the frequency of A−N+ (suspected non-Alzheimer’s pathophysiology) and of A+N+ increased monotonically beginning in the mid-50s and mid-60s, respectively. Overall, different neurodegeneration measures provide similar but not completely redundant information. Despite quantitative differences, the overall qualitative pattern of the A−N−, A+N−, A−N+, and A+N+ biomarker group frequency curves by age were similar across the five different definitions of neurodegeneration. We conclude that grouping subjects by amyloidosis and neurodegeneration status (normal/abnormal) is robust to different imaging definitions of neurodegeneration and thus is a useful way for investigators throughout the field to communicate in a common classification framework.

Anosognosia in Alzheimer disease: Disconnection between memory and self-related brain networks

OBJECTIVE

Impaired awareness is a common symptom in many mental disorders including Alzheimer disease (AD). This study aims at improving our understanding of the neural mechanisms underlying anosognosia of memory deficits in AD by combining measures of regional brain metabolism (resting state fluorodeoxyglucose positron emission tomography [FDG-PET]) and intrinsic connectivity (resting state functional magnetic resonance imaging [fMRI]).

METHODS

Twenty-three patients diagnosed with probable AD based on clinical and biomarker data and 30 matched healthy control subjects were recruited in this study. An anosognosia index (difference between subjective and objective memory scores) was obtained in each participant. Resting state FDG-PET for glucose metabolism measurement and resting state fMRI for intrinsic connectivity measurement were also performed. AD and control groups were compared on behavioral data, and voxelwise correlations between anosognosia and neuroimaging data were conducted within the AD group.

RESULTS

AD patients underestimated their memory deficits. Anosognosia in AD patients correlated with hypometabolism in orbitofrontal (OFC) and posterior cingulate (PCC) cortices. Using OFC and PCC as seed regions, intrinsic connectivity analyses in AD revealed a significant association between anosognosia and reduced intrinsic connectivity between these regions as well as with the medial temporal lobe.

INTERPRETATION

Anosognosia in AD is due not only to functional changes within cortical midline structures involved in self-referential processes (OFC, PCC), but also to disconnection between these regions as well as with the medial temporal lobe. These findings suggest that the lack of awareness of memory deficits in AD results from a disruption of the communication within, but also between, the self-related and the memory-related brain networks.

Differential associations of age with volume and microstructure of hippocampal subfields in healthy older adults

Hippocampal atrophy in advanced healthy aging has frequently been reported. However, the vulnerability of different hippocampal subfields to age-related atrophy is still a source of debate. Moreover, the association of age with the microstructural integrity of subfields is largely unknown. In this study, we investigated the associations between age and volume as well as microstructural integrity of hippocampal subfields using a three-dimensional (3D) surface mapping approach. Forty-three healthy older adults spanning the age range from 60 to 85 years underwent T1-weighted and diffusion-tensor imaging. Analyses demonstrated an association of age with hippocampal volume predominantly in the most anterior part of the hippocampal head, mainly corresponding to the subiculum. In contrast, the association of age with hippocampal microstructural integrity was mainly confined to regions located in the hippocampal body and tail, corresponding to the subiculum and CA1. Results indicate that age-related volumetric and microstructural alterations within hippocampal subfields provide complementary information and reflect different age-related processes. Potential mechanisms underlying the differential associations of age with volume and microstructure of hippocampal subfields are discussed.

Altered amygdalar resting-state connectivity in depression is explained by both genes and environment

Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals.

Detection of early changes in the parahippocampal and posterior cingulum bundles during mild cognitive impairment by using high-resolution multi-parametric diffusion tensor imaging

We aimed to determine alterations occurring in the parahippocampal cingulum bundle (PhC) and posterior cingulum bundle (PoC) in patients with mild cognitive impairment (MCI) through analysis of high-resolution multi-parametric diffusion tensor imaging (DTI). Participants comprised 41 patients with MCI (21 AD converters [MCI-C] and 20 non-converters [MCI-NC]), 20 patients with Alzheimer׳s disease (AD), and 26 healthy elderly subjects who underwent prospective examination with high-resolution DTI. An atlas-based regions-of-interest (ROIs) method calculated fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR) in the PhC and PoC. For the PhC, FA values showed significant decreases, and MD and DR values showed significantly increases, in the MCI-C and AD groups compared with the healthy controls, although the MCI-C and MCI-NC groups did not differ significantly in these metrics. Conversely, none of the diffusion metrics for the PoC showed a significant difference among the MCI groups and the control groups, although there were significant differences between the AD group and control groups. High-resolution multi-parametric DTI analysis was able to detect substantial changes in diffusion anisotropy and diffusivity in the PhC of patients with MCI who were destined to convert to AD.

Stress, PTSD, and dementia

The physiological consequences of acute and chronic stress on a range of organ systems have been well documented after the pioneering work of Hans Selye more than 70 years ago. More recently, an association between exposure to stressful life events and the development of later-life cognitive dysfunction has been proposed. Several plausible neurohormonal pathways and genetic mechanisms exist to support such an association. However, many logistical and methodological barriers must be overcome before a defined causal linkage can be firmly established. Here the authors review recent studies of the long-term cognitive consequences of exposures to cumulative ordinary life stressors as well as extraordinary traumatic events leading to posttraumatic stress disorder. Suggestive effects have been demonstrated for the role of life stress in general, and posttraumatic stress disorder in particular, on a range of negative cognitive outcomes, including worse than normal changes with aging, Alzheimer's disease, and vascular dementia. However, given the magnitude of the issue, well-controlled studies are relatively few in number, and the effects they have revealed are modest in size. Moreover, the effects have typically only been demonstrated on a selective subset of measures and outcomes. Potentially confounding factors abound and complicate causal relationships despite efforts to contain them. More well-controlled, carefully executed longitudinal studies are needed to confirm the apparent association between stress and dementia, clarify causal relationships, develop reliable antemortem markers, and delineate distinct patterns of risk in subsets of individuals.

Prefrontal hypometabolism in Alzheimer disease is related to longitudinal amyloid accumulation in remote brain regions

In PET studies of patients with Alzheimer disease (AD), prominent hypometabolism can occur in brain regions without major amyloid load. These hypometabolism-only (HO) areas may not be explained easily as a consequence of local amyloid toxicity. The aim of this longitudinal multimodal imaging study was the investigation of locoregional and remote relationships between metabolism in HO areas and longitudinal amyloid increase in functionally connected brain areas, with a particular focus on intrinsic functional connectivity as a relevant linking mechanism between pathology and dysfunction.

METHODS

Fifteen AD patients underwent longitudinal examinations with (11)C-Pittsburgh compound B ((11)C-PiB) and (18)F-FDG PET (mean follow-up period, 2 y). The peak HO region was identified by the subtraction of equally thresholded statistical T maps (hypometabolism minus amyloid burden), resulting from voxel-based statistical parametric mapping group comparisons between the AD patients and 15 healthy controls. Then functionally connected and nonconnected brain networks were identified by means of seed-based intrinsic functional connectivity analysis of the resting-state functional MRI data of healthy controls. Finally, network-based, region-of-interest-based, and voxel-based correlations were calculated between longitudinal changes of normalized (11)C-PiB binding and (18)F-FDG metabolism.

RESULTS

Positive voxel-based and region-of-interest-based correlations were demonstrated between longitudinal (11)C-PiB increases in the HO-connected network, encompassing bilateral temporoparietal and frontal brain regions, and metabolic changes in the peak HO region as well as locoregionally within several AD-typical brain regions.

CONCLUSION

Our results indicate that in AD amyloid accumulation in remote but functionally connected brain regions may significantly contribute to longitudinally evolving hypometabolism in brain regions not strongly affected by local amyloid pathology, supporting the amyloid- and network-degeneration hypothesis.

White matter disruption at the prodromal stage of Alzheimer's disease: relationships with hippocampal atrophy and episodic memory performance

White matter tract alterations have been consistently described in Alzheimer's disease (AD). In particular, limbic fronto-temporal connections, which are critical to episodic memory function, may degenerate early in the course of the disease. However the relation between white matter tract degeneration, hippocampal atrophy and episodic memory impairment at the earliest stages of AD is still unclear. In this magnetic resonance imaging study, white matter integrity and hippocampal volumes were evaluated in patients with amnestic mild cognitive impairment due to AD (Albert et al., 2011) (n = 22) and healthy controls (n = 15). Performance in various episodic memory tasks was also evaluated in each participant. Relative to controls, patients showed a significant reduction of white matter fractional anisotropy (FA) and increase of radial diffusivity (RD) in the bilateral uncinate fasciculus, parahippocampal cingulum and fornix. Within the patient group, significant intra-hemispheric correlations were notably found between hippocampal grey matter volume and FA in the uncinate fasciculus, suggesting a relationship between atrophy and disconnection of the hippocampus. Moreover, episodic recognition scores were related with uncinate fasciculus FA across patients. These results indicate that fronto-hippocampal connectivity is reduced from the earliest pre-demential stages of AD. Disruption of fronto-hippocampal connections may occur progressively, in parallel with hippocampal atrophy, and may specifically contribute to early initial impairment in episodic memory.

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Limbic fronto-temporal connections (cingulum, uncinate fasciculus and fornix) are altered from the prodromal stage of AD.

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In prodromal AD patients, intra-hemispheric correlations were found between uncinate fasciculus FA and hippocampal atrophy.

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In prodromal AD patients, uncinate fasciculus FA was correlated with scores on episodic recognition.

Neurostatistical imaging for diagnosing dementia: translational approach from laboratory neuroscience to clinical routine

Statistical analysis in neuroimaging (referred to as "neurostatistical imaging") is important in clinical neurology. Here, neurostatistical imaging and its superiority for diagnosing dementia are reviewed. In neurodegenerative dementia, the proportional distribution of brain perfusion, metabolism, or atrophy is important for understanding the symptoms and status of patients and for identifying regions of pathological damage. Although absolute quantitative changes are important in vascular disease, they are less important than relative values in neurodegenerative dementia. Even under resting conditions in healthy individuals, the distribution of brain perfusion and metabolism is asymmetrical and differs among areas. To detect small changes, statistical analysis such as the Z-score--the number of standard deviations by which a patient's voxel value differs from the normal mean value--comparing normal controls is useful and also facilitates clinical assessment. Our recent finding of a longitudinal one-year reduction of glucose metabolism around the olfactory tract in Alzheimer's disease using the recently-developed DARTEL normalization procedure is also presented. Furthermore, a newly-developed procedure to assess brain atrophy with CT-based voxel-based morphometry is illustrated. The promising possibilities of CT in neurostatistical imaging are also presented.

Intrinsic functional component analysis via sparse representation on Alzheimer's disease neuroimaging initiative database

Alzheimer's disease (AD) is the most common type of dementia (accounting for 60% to 80%) and is the fifth leading cause of death for those people who are 65 or older. By 2050, one new case of AD in United States is expected to develop every 33 sec. Unfortunately, there is no available effective treatment that can stop or slow the death of neurons that causes AD symptoms. On the other hand, it is widely believed that AD starts before development of the associated symptoms, so its prestages, including mild cognitive impairment (MCI) or even significant memory concern (SMC), have received increasing attention, not only because of their potential as a precursor of AD, but also as a possible predictor of conversion to other neurodegenerative diseases. Although these prestages have been defined clinically, accurate/efficient diagnosis is still challenging. Moreover, brain functional abnormalities behind those alterations and conversions are still unclear. In this article, by developing novel sparse representations of whole-brain resting-state functional magnetic resonance imaging signals and by using the most updated Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we successfully identified multiple functional components simultaneously, and which potentially represent those intrinsic functional networks involved in the resting-state activities. Interestingly, these identified functional components contain all the resting-state networks obtained from traditional independent-component analysis. Moreover, by using the features derived from those functional components, it yields high classification accuracy for both AD (94%) and MCI (92%) versus normal controls. Even for SMC we can still have 92% accuracy.

Patterns of regional gray matter and white matter atrophy in cortical multiple sclerosis

We investigated the patterns of regional distribution of focal lesions, white matter (WM) and gray matter (GM) atrophy in patients with cortical (cort) MS in comparison to classical (c) MS patients. Nine cort-MS, nine c-MS and nine age-matched healthy controls (HC) underwent a brain MRI exam, including FLAIR and high-resolution T1-weighted scans. MS patients underwent neurological and neuropsychological assessment. Between-group differences of GM and WM volumes and their correlations with neuropsychological performances were assessed with voxel-based morphometry. FLAIR and T1 lesion probability maps (LPMs) were also obtained. Performance at neuropsychological tests was worse in cort-MS than in c-MS patients. Compared to HC, MS patients had a distributed pattern of GM and WM atrophy. No GM/WM area was more atrophic in c-MS vs cort-MS patients. Compared to c-MS, cort-MS patients experienced GM atrophy of frontal-temporal-parietal areas and cingulate cortex and WM atrophy of the cingulum bundle, bilateral cerebral peduncles, right inferior longitudinal fasciculus and left superior longitudinal fasciculus. FLAIR and T1 LPMs did not differ between c-MS vs cort-MS patients. A higher susceptibility to neurodegenerative processes in key brain regions known to be related to cognitive functions is likely to underlie the clinical manifestations of cort-MS.

Grey matter hypometabolism and atrophy in Parkinson's disease with cognitive impairment: a two-step process

The pathophysiological process underlying cognitive decline in Parkinson's disease is not well understood. Cerebral atrophy and hypometabolism have been described in patients with Parkinson's disease and dementia or mild cognitive impairment with respect to control subjects. However, the exact relationships between atrophy and hypometabolism are still unclear. To determine the extension and topographical distribution of hypometabolism and atrophy in the different cognitive states of Parkinson's disease, we examined 46 patients with Parkinson's disease (19 female, 27 male; 71.7 ± 5.9 years old; 14.6 ± 4.2 years of disease evolution; modified Hoehn and Yahr mean stage 3.1 ± 0.7). Cognitive status was diagnosed as normal in 14 patients, as mild cognitive impairment in 17 and as dementia in 15 patients. Nineteen normal subjects (eight female, 11 male; 68.1 ± 3.2 years old) were included as controls. (18)F-fluorodeoxyglucose positron emission tomography and magnetic resonance imaging scans were obtained, co-registered, corrected for partial volume effect and spatially normalized to the Montreal Neurological Institute space in each subject. Smoothing was applied to the positron emission tomography and magnetic resonance imaging scans to equalize their effective smoothness and resolution (10 mm and 12 mm full-width at half-maximum and Gaussian kernel, respectively). Z-score maps for atrophy and for hypometabolism were obtained by comparing individual images to the data set of control subjects. For each group of patients, a paired Student's t-test was performed to statistically compare the two Z-map modalities (P < 0.05 false discovery rate corrected) using the direct voxel-based comparison technique. In patients with mild cognitive impairment, hypometabolism exceeded atrophy in the angular gyrus, occipital, orbital and anterior frontal lobes. In patients with dementia, the hypometabolic areas observed in the group with mild cognitive impairment were replaced by areas of atrophy, which were surrounded by extensive zones of hypometabolism. Areas where atrophy was more extended than hypometabolism were found in the precentral and supplementary motor areas in both patients with mild cognitive impairment and with dementia, and in the hippocampus and temporal lobe in patients with dementia. These findings suggest that there is a gradient of severity in cortical changes associated with the development of cognitive impairment in Parkinson's disease in which hypometabolism and atrophy represent consecutive stages of the same process in most of the cortical regions affected.

Early Brain Loss in Circuits Affected by Alzheimer's Disease is Predicted by Fornix Microstructure but may be Independent of Gray Matter

In a cohort of community-recruited elderly subjects with normal cognition at initial evaluation, we found that baseline fornix white matter (WM) microstructure was significantly correlated with early volumetric longitudinal tissue change across a region of interest (called fornix significant ROI, fSROI), which overlaps circuits known to be selectively vulnerable to Alzheimer’s dementia pathology. Other WM and gray matter regions had much weaker or non-existent associations with longitudinal tissue change. Tissue loss in fSROI was in turn a significant factor in a survival model of cognitive decline, as was baseline fornix microstructure. These findings suggest that WM deterioration in the fornix and tissue loss in fSROI may be the early beginnings of posterior limbic circuit and default mode network degeneration. We also found that gray matter baseline volumes in the entorhinal cortex and hippocampus predicted cognitive decline in survival models. But since GM regions did not also significantly predict brain-tissue loss, our results may imply a view in which early, prodromal deterioration appears as two quasi independent processes in white and gray matter regions of the limbic circuit crucial to memory.

White matter microstructure in late middle-age: Effects of apolipoprotein E4 and parental family history of Alzheimer's disease

INTRODUCTION

Little is still known about the effects of risk factors for Alzheimer's disease (AD) on white matter microstructure in cognitively healthy adults. The purpose of this cross-sectional study was to assess the effect of two well-known risk factors for AD, parental family history and APOE4 genotype.

METHODS

This study included 343 participants from the Wisconsin Registry for Alzheimer's Prevention, who underwent diffusion tensor imaging (DTI). A region of interest analysis was performed on fractional anisotropy maps, in addition to mean, radial, and axial diffusivity maps, aligned to a common template space using a diffeomorphic, tensor-based registration method. The analysis focused on brain regions known to be affected in AD including the corpus callosum, superior longitudinal fasciculus, fornix, cingulum, and uncinate fasciculus. Analyses assessed the impact of APOE4, parental family history of AD, age, and sex on white matter microstructure in late middle-aged participants (aged 47-76 years).

RESULTS

Both APOE4 and parental family history were associated with microstructural white matter differences. Participants with parental family history of AD had higher FA in the genu of the corpus callosum and the superior longitudinal fasciculus. We observed an interaction between family history and APOE4, where participants who were family history positive but APOE4 negative had lower axial diffusivity in the uncinate fasciculus, and participants who were both family history positive and APOE4 positive had higher axial diffusivity in this region. We also observed an interaction between APOE4 and age, whereby older participants (=65 years of age) who were APOE4 carriers, had higher MD in the superior longitudinal fasciculus and in the portion of the cingulum bundle running adjacent to the cingulate cortex, compared to non-carriers. Older participants who were APOE4 carriers also showed higher radial diffusivity in the genu compared to non-carriers. Across all participants, age had an effect on FA, MD, and axial and radial diffusivities. Sex differences were observed in FA and radial diffusivity.

CONCLUSION

APOE4 genotype, parental family history of AD, age, and sex are all associated with microstructural white matter differences in late middle-aged adults. In participants at risk for AD, alterations in diffusion characteristics-both expected and unexpected-may represent cellular changes occurring at the earliest disease stages, but further work is needed. Higher mean, radial, and axial diffusivities were observed in participants who are more likely to be experiencing later stage preclinical pathology, including participants who were both older and carried APOE4, or who were positive for both APOE4 and parental family history of AD.

Rates of β-amyloid accumulation are independent of hippocampal neurodegeneration

OBJECTIVE

To test the hypotheses predicted in a hypothetical model of Alzheimer disease (AD) biomarkers that rates of β-amyloid (Aβ) accumulation on PET imaging are not related to hippocampal neurodegeneration whereas rates of neurodegenerative brain atrophy depend on the presence of both amyloid and neurodegeneration in a population-based sample.

METHODS

A total of 252 cognitively normal (CN) participants from the Mayo Clinic Study of Aging had 2 or more serial visits with both amyloid PET and MRI. Subjects were classified into 4 groups based on baseline positive/negative amyloid PET (A+ or A-) and baseline hippocampal volume (N+ or N-). We compared rates of amyloid accumulation and rates of brain atrophy among the 4 groups.

RESULTS

At baseline, 148 (59%) were amyloid negative and neurodegeneration negative (A-N-), 29 (12%) amyloid negative and neurodegeneration positive (A-N+), 56 (22%) amyloid positive and neurodegeneration negative (A+N-), and 19 (8%) amyloid positive and neurodegeneration positive (A+N+). High rates of Aβ accumulation were found in those with abnormal amyloid at baseline and were not influenced by hippocampal neurodegeneration at baseline. In contrast, rates of brain atrophy were greatest in A+N+.

CONCLUSIONS

We describe a 2-feature biomarker approach to classifying elderly CN subjects that is complementary to the National Institute on Aging-Alzheimer's Association preclinical staging criteria. Our results support 2 key concepts in a model of the temporal evolution of AD biomarkers. First, the rate of Aβ accumulation is not influenced by neurodegeneration and thus may be a biologically independent process. Second, Aβ pathophysiology increases or catalyzes neurodegeneration.

Longitudinal changes in brains of patients with fluent primary progressive aphasia

Primary progressive aphasia (PPA) is a rare clinical dementia syndrome with predominant, progressive language impairment. Clinical symptoms, linguistic impairment and the course of the disease may vary considerably between patients. In order to capture these aspects, longitudinal assessments of neurofunctional changes in PPA including their relationship to behaviour and clinical symptoms are mandatory, ideally at intervals shorter than 1 year. Here, we report a longitudinal fMRI study investigating the development of lexical processing and their neural basis in PPA patients over 1year. Four logopenic PPA patients and four matched controls were scanned 3 times (T1, T2, T3, at 6months intervals) while performing a visual lexical decision task on German words and pseudowords. Group differences for the lexicality effect (pseudowords>words) were assessed at time point T1 and its longitudinal changes in the BOLD signal associated with the lexicality effect were analysed. Brain atrophy was assessed with a high-resolution MPRAGE sequence and analysed using deformation based morphometry (DBM). From the very beginning of the study, PPA patients showed reduced left-hemispheric and increased right-hemispheric activations compared to controls. During the progression of the disease, activation increased predominantly in left posterior middle temporal gyrus (pMTG) and inferior frontal junction area, whereas the same regions decreased in activity in control brains. Interestingly, DBM data showed that this increase in activation in PPA patients was accompanied by progressing atrophy in the same regions. At a behavioural level, the accuracy in the lexical decision task was comparably high for both groups during the whole period of examination, despite some large variability between patients. To conclude, the dissociation between (i) maintained high performance, (ii) increased activity in regions involved in lexical access such as pMTG, and (iii) progressive atrophy of the very same regions supports the notion of a compensatory mechanism in brains of PPA patients for maintaining language while brain atrophy is progressing. The activity increase within a left-lateralised fronto-temporal network seems vital for high-level performance, whereas initial right-hemispheric recruitment of homologue language regions, which is reminiscent of that in vascular aphasics, has no continuous impact on lexical performance.

Imaging Brain Metabolism and Pathology in Alzheimer's Disease with Positron Emission Tomography

Current Positron Emission Tomography (PET) biomarkers for Alzheimer's disease (AD) assess either neuronal function, or associated pathological features of this common neurodegenerative disease. The most widely accepted clinical PET tool for AD is 18-fluorodeoxyglucose PET (FDG-PET), which measures cerebral metabolic glucose utilization rate (CMRglc). FDG-PET is a marker of synaptic activity, neuronal function, and neuronal metabolic activity. AD is characterized by a distinct pattern of hypometabolism, as seen with the FDG images. This pattern can show variability across different subjects and is present before a patient is demented, specifically in amnestic mild cognitive impairment a clinical diagnosis defined as an intermediate state from normal aging to dementia. In addition to FDG PET, novel PET approaches assess known pathological hallmarks of AD including extracellular amyloid-beta plaques (Aβ) and intracellular neurofibrillary tangles composed of tau fibrils. Already, amyloid PET imaging is a tool that allows in vivo imaging of extracellular beta-amyloid levels. Efforts to bring tau imaging into clinical use continue, but this approach is hampered by the intracellular nature of tau protein deposition, subsequent weak radiotracer binding, and low image contrast. Several new candidate probes for tau-specific PET imaging are currently available but have not found their way into broad clinical applications. This study gives an overview of the most recent PET-based neuroimaging techniques for AD. We place special emphasis on PET data analysis and interpretation techniques, as well as radiochemistry for imaging metabolism and assessing Aβ and tau pathology.

Advances in longitudinal studies of amnestic mild cognitive impairment and Alzheimer's disease based on multi-modal MRI techniques

Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD), and 75%-80% of aMCI patients finally develop AD. So, early identification of patients with aMCI or AD is of great significance for prevention and intervention. According to cross-sectional studies, it is known that the hippocampus, posterior cingulate cortex, and corpus callosum are key areas in studies based on structural MRI (sMRI), functional MRI (fMRI), and diffusion tensor imaging (DTI) respectively. Recently, longitudinal studies using each MRI modality have demonstrated that the neuroimaging abnormalities generally involve the posterior brain regions at the very beginning and then gradually affect the anterior areas during the progression of aMCI to AD. However, it is not known whether follow-up studies based on multi-modal neuroimaging techniques (e.g., sMRI, fMRI, and DTI) can help build effective MRI models that can be directly applied to the screening and diagnosis of aMCI and AD. Thus, in the future, large-scale multi-center follow-up studies are urgently needed, not only to build an MRI diagnostic model that can be used on a single person, but also to evaluate the variability and stability of the model in the general population. In this review, we present longitudinal studies using each MRI modality separately, and then discuss the future directions in this field.

Cerebral white matter integrity and resting-state functional connectivity in middle-aged patients with type 2 diabetes

Early detection of brain abnormalities at the preclinical stage can be useful for developing preventive interventions to abate cognitive decline. We examined whether middle-aged type 2 diabetic patients show reduced white matter integrity in fiber tracts important for cognition and whether this abnormality is related to preestablished altered resting-state functional connectivity in the default mode network (DMN). Diabetic and nondiabetic participants underwent diffusion tensor imaging, functional magnetic resonance imaging, and cognitive assessment. Multiple diffusion measures were calculated using streamline tractography, and correlations with DMN functional connectivity were determined. Diabetic patients showed lower fractional anisotropy (FA) (a measure of white matter integrity) in the cingulum bundle and uncinate fasciculus. Control subjects showed stronger functional connectivity than patients between the posterior cingulate and both left fusiform and medial frontal gyri. FA of the cingulum bundle was correlated with functional connectivity between the posterior cingulate and medial frontal gyrus for combined groups. Thus, middle-aged patients with type 2 diabetes show white matter abnormalities that correlate with disrupted functional connectivity in the DMN, suggesting that common mechanisms may underlie structural and functional connectivity. Detecting brain abnormalities in middle age enables implementation of therapies to slow progression of neuropathology.

Relationship between brain volumetric changes and interim drinking at six months in alcohol-dependent patients

BACKGROUND

Chronic alcohol consumption results in brain damage potentially reversible with abstinence. It is however difficult to gauge the degree of recovery of brain tissues with abstinence since changes are subtle and a significant portion of patients relapse. State-of-the-art morphometric methods are increasingly used in neuroimaging studies to detect subtle brain changes at a voxel level. Our aim was to use the most refined morphometric methods to observe in alcohol dependence the relationship between volumetric changes and interim drinking over a 6-month follow-up.

METHODS

Overall, 19 patients with alcohol dependence received volumetric T1-weighted magnetic resonance imaging (MRI) after detoxification. A 6-month follow-up study was then conducted, during which 11 of them received a second MRI scan. First, correlations were conducted between gray matter (GM) and white matter (WM) volumes of patients at alcohol treatment entry and the amount of alcohol consumed between treatment entry and follow-up. Second, longitudinal analyses were performed from pairs of MRI scans using tensor-based morphometry in the 11 patients, and correlations were computed between the resultant Jacobian maps of GM and WM and interim drinking.

RESULTS

Our preliminary results showed that, among others, alcoholics with smaller thalamus at alcohol treatment entry tended to resume with heavy alcohol consumption (p < 0.005 uncorrected [unc.]). Our longitudinal study revealed an overall inverse relationship between recovery of brain structures like the cerebellum, striatum, and cingulate gyrus, and the amount of alcohol consumed over the 6-month follow-up (p < 0.005 unc.). The recovery could be observed not only with strict abstinence but also in cases of moderate resumption of alcohol consumption, when there had been no drastic relapse into alcohol dependence.

CONCLUSIONS

Those preliminary findings indicate that the volume of the thalamus at treatment entry may have an influence on subsequent interim drinking. There is recovery of certain brain regions even when patients resume with moderate, but not drastic, alcohol consumption.

Midsagittal brain variation and MRI shape analysis of the precuneus in adult individuals

Recent analyses indicate that the precuneus is one of the main centres of integration in terms of functional and structural processes within the human brain. This neuroanatomical element is formed by different subregions, involved in visuo-spatial integration, memory and self-awareness. We analysed the midsagittal brain shape in a sample of adult humans (n = 90) to evidence the patterns of variability and geometrical organization of this area. Interestingly, the major brain covariance pattern within adult humans is strictly associated with the relative proportions of the precuneus. Its morphology displays a marked individual variation, both in terms of geometry (mostly in its longitudinal dimensions) and anatomy (patterns of convolution). No patent differences are evident between males and females, and the allometric effect of size is minimal. However, in terms of morphology, the precuneus does not represent an individual module, being influenced by different neighbouring structures. Taking into consideration the apparent involvement of the precuneus in higher-order human brain functions and evolution, its wide variation further stresses the important role of these deep parietal areas in modern neuroanatomical organization.

Structural hippocampal network alterations during healthy aging: a multi-modal MRI study

While hippocampal atrophy has been described during healthy aging, few studies have examined its relationship with the integrity of White Matter (WM) connecting tracts of the limbic system. This investigation examined WM structural damage specifically related to hippocampal atrophy in healthy aging subjects (n = 129), using morphological MRI to assess hippocampal volume and Diffusion Tensor Imaging (DTI) to assess WM integrity. Subjects with Mild Cognitive Impairment (MCI) or dementia were excluded from the analysis. In our sample, increasing age was significantly associated with reduced hippocampal volume and reduced Fractional Anisotropy (FA) at the level of the fornix and the cingulum bundle. The findings also demonstrate that hippocampal atrophy was specifically associated with reduced FA of the fornix bundle, but it was not related to alteration of the cingulum bundle. Our results indicate that the relationship between hippocampal atrophy and fornix FA values is not due to an independent effect of age on both structures. A recursive regression procedure was applied to evaluate sequential relationships between the alterations of these two brain structures. When both hippocampal atrophy and fornix FA values were included in the same model to predict age, fornix FA values remained significant whereas hippocampal atrophy was no longer significantly associated with age. According to this latter finding, hippocampal atrophy in healthy aging could be mediated by a loss of fornix connections. Structural alterations of this part of the limbic system, which have been associated with neurodegeneration in Alzheimer's disease, result at least in part from the aging process.

Body mass and white matter integrity: the influence of vascular and inflammatory markers

High adiposity is deleteriously associated with brain health, and may disproportionately affect white matter integrity; however, limited information exists regarding the mechanisms underlying the association between body mass (BMI) and white matter integrity. The present study evaluated whether vascular and inflammatory markers influence the relationship between BMI and white matter in healthy aging. We conducted a cross-sectional evaluation of white matter integrity, BMI, and vascular/inflammatory factors in a cohort of 138 healthy older adults (mean age: 71.3 years). Participants underwent diffusion tensor imaging, provided blood samples, and participated in a health evaluation. Vascular risk factors and vascular/inflammatory blood markers were assessed. The primary outcome measure was fractional anisotropy (FA) of the genu, body, and splenium (corpus callosum); exploratory measures included additional white matter regions, based on significant associations with BMI. Regression analyses indicated that higher BMI was associated with lower FA in the corpus callosum, cingulate, and fornix (p<.001). Vascular and inflammatory factors influenced the association between BMI and FA. Specifically, BMI was independently associated with the genu [β=-.21; B=-.0024; 95% CI, -.0048 to -.0000; p=.05] and cingulate fibers [β=-.39; B=-.0035; 95% CI,-.0056 to -.0015; p<.001], even after controlling for vascular/inflammatory risk factors and blood markers. In contrast, BMI was no longer significantly associated with the fornix and middle/posterior regions of the corpus callosum after controlling for these markers. Results partially support a vascular/inflammatory hypothesis, but also suggest a more complex relationship between BMI and white matter characterized by potentially different neuroanatomic vulnerability.

Connectome-scale assessments of structural and functional connectivity in MCI

Mild cognitive impairment (MCI) has received increasing attention not only because of its potential as a precursor for Alzheimer's disease but also as a predictor of conversion to other neurodegenerative diseases. Although MCI has been defined clinically, accurate and efficient diagnosis is still challenging. Although neuroimaging techniques hold promise, compared to commonly used biomarkers including amyloid plaques, tau protein levels and brain tissue atrophy, neuroimaging biomarkers are less well validated. In this article, we propose a connectomes-scale assessment of structural and functional connectivity in MCI via two independent multimodal DTI/fMRI datasets. We first used DTI-derived structural profiles to explore and tailor the most common and consistent landmarks, then applied them in a whole-brain functional connectivity analysis. The next step fused the results from two independent datasets together and resulted in a set of functional connectomes with the most differentiation power, hence named as "connectome signatures." Our results indicate that these "connectome signatures" have significantly high MCI-vs-controls classification accuracy, at more than 95%. Interestingly, through functional meta-analysis, we found that the majority of "connectome signatures" are mainly derived from the interactions among different functional networks, for example, cognition-perception and cognition-action domains, rather than from within a single network. Our work provides support for using functional "connectome signatures" as neuroimaging biomarkers of MCI.

White matter abnormalities and structural hippocampal disconnections in amnestic mild cognitive impairment and Alzheimer's disease

The purpose of this project was to evaluate white matter degeneration and its impact on hippocampal structural connectivity in patients with amnestic mild cognitive impairment, non-amnestic mild cognitive impairment and Alzheimer’s disease. We estimated white matter fractional anisotropy, mean diffusivity and hippocampal structural connectivity in two independent cohorts. The ADNI cohort included 108 subjects [25 cognitively normal, 21 amnestic mild cognitive impairment, 47 non-amnestic mild cognitive impairment and 15 Alzheimer’s disease]. A second cohort included 34 subjects [15 cognitively normal and 19 amnestic mild cognitive impairment] recruited in Montreal. All subjects underwent clinical and neuropsychological assessment in addition to diffusion and T1 MRI. Individual fractional anisotropy and mean diffusivity maps were generated using FSL-DTIfit. In addition, hippocampal structural connectivity maps expressing the probability of connectivity between the hippocampus and cortex were generated using a pipeline based on FSL-probtrackX. Voxel-based group comparison statistics of fractional anisotropy, mean diffusivity and hippocampal structural connectivity were estimated using Tract-Based Spatial Statistics. The proportion of abnormal to total white matter volume was estimated using the total volume of the white matter skeleton. We found that in both cohorts, amnestic mild cognitive impairment patients had 27-29% white matter volume showing higher mean diffusivity but no significant fractional anisotropy abnormalities. No fractional anisotropy or mean diffusivity differences were observed between non-amnestic mild cognitive impairment patients and cognitively normal subjects. Alzheimer’s disease patients had 66.3% of normalized white matter volume with increased mean diffusivity and 54.3% of the white matter had reduced fractional anisotropy. Reduced structural connectivity was found in the hippocampal connections to temporal, inferior parietal, posterior cingulate and frontal regions only in the Alzheimer’s group. The severity of white matter degeneration appears to be higher in advanced clinical stages, supporting the construct that these abnormalities are part of the pathophysiological processes of Alzheimer’s disease.

In vivo characterization of the early states of the amyloid-beta network

Alzheimer's disease is a neurodegenerative disease that is associated with the abnormal accumulation of amyloid-β. Much is known about regional brain atrophy in Alzheimer's disease, yet our knowledge about the network nature of Alzheimer's disease-associated amyloid-β accumulation is limited. We use stepwise connectivity analysis of Pittsburgh Compound B positron emission tomography images to reveal the network properties of amyloid-β deposits in normal elderly subjects and clinical patients with Alzheimer's disease. We found that amyloid-β accumulation in the medial temporal lobe is associated with accumulation in cortical regions such as orbitofrontal, lateral temporal and precuneus/posterior cingulate cortices in Alzheimer's disease. In normal subjects, there was a predominant association between amyloid-β deposits in the hippocampus and the midline prefrontal/orbitofrontal regions, even in those with very low amyloid-β burden. Moreover, the orbitofrontal cortex, amygdala nucleus and hippocampus exhibit hub properties in the amyloid-β network that may be critical to understanding the putative spreading mechanisms of Alzheimer's disease pathology in early stages.

Relation between structural and functional connectivity in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is characterized by abnormalities in both brain structure and function within a frontolimbic network. However, little is known about the relation between structural and functional abnormalities in MDD. Here, we used a multimodal neuroimaging approach to investigate the relation between structural connectivity and functional connectivity within the frontolimbic network.

METHODS

Eighteen MDD and 24 healthy control subjects were included, of which the integrity of the uncinate fasciculus was assessed that connects the subgenual anterior cingulate cortex (ACC) to the medial temporal lobe (MTL) with diffusion tensor imaging. Furthermore, we assessed the functional connectivity between these brain regions with functional magnetic resonance imaging.

RESULTS

The results showed that white matter integrity of the uncinate fasciculus was reduced and that functional connectivity between the subgenual ACC and MTL was enhanced in MDD. Importantly, we identified a negative correlation between uncinate fasciculus integrity and subgenual ACC functional connectivity with the bilateral hippocampus in MDD but not in healthy control subjects. Moreover, this negative structure-function relation in MDD was positively associated with depression severity.

CONCLUSIONS

These findings suggest that structural abnormalities in MDD are associated with increased functional connectivity between subgenual ACC and MTL and that these changes are concomitant with severity of depressive symptoms. This association indicates that structural abnormalities in MDD contribute to increased functional connectivity within the frontolimbic network.

Relationships between years of education and gray matter volume, metabolism and functional connectivity in healthy elders

More educated elders are less susceptible to age-related or pathological cognitive changes. We aimed at providing a comprehensive contribution to the neural mechanism underlying this effect thanks to a multimodal approach. Thirty-six healthy elders were selected based on neuropsychological assessments and cerebral amyloid imaging, i.e. as presenting normal cognition and a negative florbetapir-PET scan. All subjects underwent structural MRI, FDG-PET and resting-state functional MRI scans. We assessed the relationships between years of education and i) gray matter volume, ii) gray matter metabolism and iii) functional connectivity in the brain areas showing associations with both volume and metabolism. Higher years of education were related to greater volume in the superior temporal gyrus, insula and anterior cingulate cortex and to greater metabolism in the anterior cingulate cortex. The latter thus showed both volume and metabolism increases with education. Seed connectivity analyses based on this region showed that education was positively related to the functional connectivity between the anterior cingulate cortex and the hippocampus as well as the inferior frontal lobe, posterior cingulate cortex and angular gyrus. Increased connectivity was in turn related with improved cognitive performances. Reinforcement of the connectivity of the anterior cingulate cortex with distant cortical areas of the frontal, temporal and parietal lobes appears as one of the mechanisms underlying education-related reserve in healthy elders.

Recent advances in imaging Alzheimer's disease

Advances in brain imaging technology in the past five years have contributed greatly to the understanding of Alzheimer's disease (AD). Here, we review recent research related to amyloid imaging, new methods for magnetic resonance imaging analyses, and statistical methods. We also review research that evaluates AD risk factors and brain imaging, in the context of AD prediction and progression. We selected a variety of illustrative studies, describing how they advanced the field and are leading AD research in promising new directions.

Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults

Studies of functional connectivity suggest that the default mode network (DMN) might be relevant for cognitive functions. Here, we examined metabolic and structural connectivity between major DMN nodes, the posterior cingulate (PCC) and medial prefrontal cortex (MPFC), in relation to normal working memory (WM). DMN was captured using independent component analysis of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) data from 35 young healthy adults (27.1 ± 5.1 years). Metabolic connectivity, a correlation between FDG uptake in PCC and MPFC, was examined in groups of subjects with (relative to median) low (n=18) and high (n=17) performance on digit span backward test as an index of verbal WM. In addition, fiber tractography based on PCC and MPFC nodes as way points was performed in a subset of subjects. FDG uptake in the DMN nodes did not differ between high and low performers. However, significantly (p=0.01) lower metabolic connectivity was found in the group of low performers. Furthermore, as compared to high performers, low performers showed lower density of the left superior cingulate bundle. Verbal WM performance is related to metabolic and structural connectivity within the DMN in young healthy adults. Metabolic connectivity as quantified with FDG-PET might be a sensitive marker of the normal variability in some cognitive functions.

White matter atrophy in Alzheimer's disease variants

BACKGROUND

In comparison with late-onset Alzheimer's disease (LOAD, onset, >65 years), early-age-of-onset Alzheimer's disease (EOAD, onset, <65 years) more often presents with language, visuospatial, and/or executive impairment, often occurring earlier than a progressive memory deficit. The logopenic variant of primary progressive aphasia (lv-PPA) and posterior cortical atrophy (PCA) have recently been described as possible atypical variants of EOAD. Lv-PPA is characterized by isolated language deficit, whereas PCA is characterized by predominant visuospatial deficits. Severe hemispheric gray matter (GM) atrophy associated with EOAD, lv-PPA, and PCA has been described, but regional patterns of white matter (WM) damage are still poorly understood.

METHODS

Using structural magnetic resonance imaging and voxel-based morphometry, we investigated WM damage in patients with EOAD (n = 16), PCA (n = 13), lv-PPA (n = 10), and LOAD (n = 14) at presentation and 72 age-matched control subjects.

RESULTS

In patients with EOAD, PCA, and lv-PPA, WM atrophy was centered on the lateral temporal and parietal regions, including the cingulum and posterior corpus callosum. Compared with control subjects, patients with lv-PPA showed more severe left parietal damage, and patients with PCA showed more severe occipital atrophy. Moreover, patients with EOAD had greater cingulum atrophy compared with those with LOAD. LOAD showed WM damage in the medial temporal regions and less extensive hemispheric involvement.

CONCLUSION

Patterns of WM damage in EOAD, lv-PPA, and PCA are consistent with the clinical syndromes and GM atrophy patterns. WM injury in AD atypical variants may contribute to symptoms and disease pathogenesis.

Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers

In 2010, we put forward a hypothetical model of the major biomarkers of Alzheimer's disease (AD). The model was received with interest because we described the temporal evolution of AD biomarkers in relation to each other and to the onset and progression of clinical symptoms. Since then, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of our assumptions, which has allowed us to modify our original model. Refinements to our model include indexing of individuals by time rather than clinical symptom severity; incorporation of interindividual variability in cognitive impairment associated with progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and recognition that the two major proteinopathies underlying AD biomarker changes, amyloid β (Aβ) and tau, might be initiated independently in sporadic AD, in which we hypothesise that an incident Aβ pathophysiology can accelerate antecedent limbic and brainstem tauopathy.

Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer's disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain's connectivity pattern, allowing us to discover genetic variants that affect the human brain's wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer's disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

Voxel-wise co-analysis of macro- and microstructural brain alteration in mild cognitive impairment and Alzheimer's disease using anatomical and diffusion MRI

BACKGROUND AND PURPOSE

To determine if a voxel-wise "co-analysis" of structural and diffusion tensor magnetic resonance imaging (MRI) together reveals additional brain regions affected in mild cognitive impairment (MCI) and Alzheimer's disease (AD) than voxel-wise analysis of the individual MRI modalities alone.

METHODS

Twenty-one patients with MCI, 21 patients with AD, and 21 cognitively normal healthy elderly were studied with MRI. Maps of deformation and fractional anisotropy (FA) were computed and used as dependent variables in univariate and multivariate statistical models.

RESULTS

Univariate voxel-wise analysis of macrostructural changes in MCI showed atrophy in the right anterior temporal lobe, left posterior parietal/precuneus region, WM adjacent to the cingulate gyrus, and dorsolateral prefrontal regions, consistent with prior research. Univariate voxel-wise analysis of microstructural changes in MCI showed reduced FA in the left posterior parietal region extending into the corpus callosum, consistent with previous work. The multivariate analysis, which provides more information than univariate tests when structural and FA measures are correlated, revealed additional MCI-related changes in corpus callosum and temporal lobe.

CONCLUSION

These results suggest that in corpus callosum and temporal regions macro- and microstructural variations in MCI can be congruent, providing potentially new insight into the mechanisms of brain tissue degeneration.

Region-specific hierarchy between atrophy, hypometabolism, and β-amyloid (Aβ) load in Alzheimer's disease dementia

Gray matter atrophy, glucose hypometabolism, and β-amyloid Aβ deposition are well-described hallmarks of Alzheimer's disease, but their relationships are poorly understood. The present study aims to compare the local levels of these three alterations in humans with Alzheimer's disease. Structural magnetic resonance imaging, (18)F-fluorodeoxyglucose positron emission tomography (PET), and (18)F-florbetapir PET data from 34 amyloid-negative healthy controls and 20 demented patients with a high probability of Alzheimer's disease etiology (attested using neuroimaging biomarkers as recently recommended) were analyzed. For each patient and imaging modality, age-adjusted Z-score maps were computed, and direct between-modality voxelwise comparison and correlation analyses were performed. Significant differences in the levels of atrophy, hypometabolism, and Aβ deposition were found in most brain areas, but the hierarchy differed across regions. A cluster analysis revealed distinct subsets of regions: (1) in the hippocampus, atrophy exceeded hypometabolism, whereas Aβ load was minimal; (2) in posterior association areas, Aβ deposition was predominant, together with high hypometabolism and lower but still significant atrophy; and (3) in frontal regions, Aβ deposition was maximal, whereas structural and metabolic alterations were low. Atrophy and hypometabolism significantly correlated in the hippocampus and temporo-parietal cortex, whereas Aβ load was not significantly related to either atrophy or hypometabolism. These findings provide direct evidence for regional variations in the hierarchy and relationships between Aβ load, hypometabolism, and atrophy. Altogether, these variations probably reflect the differential involvement of region-specific pathological or protective mechanisms, such as the presence of neurofibrillary tangles, disconnection, as well as compensation processes.

Structural networks in Alzheimer's disease

Alzheimer's disease (AD) appears to be a uniquely human condition, which is possibly attributable to our expanded longevity and peculiar capacity for episodic memory. Due to a lack of naturally-occurring animal model for investigating AD pathogenesis, our knowledge about the disease must be derived from correlational observation of humans, or from animal models produced by genetic manipulation of known risk factors in humans. Advances in neuroimaging, cellular and molecular science, and computational methods have proven useful for the improvement of such techniques, but the general limitation persists; as a result we remain without clear answers to some of the fundamental questions posed by AD. On the other hand, much progress has been made in characterizing the longitudinal progression of AD pathology, which includes the formation of "plaques and tangles", a distinct topological pattern of atrophy of grey and white matter, and the concurrent decline of specific cognitive functions, beginning with mild memory impairments and ending with general debilitating dementia. In this review, we first discuss the existing literature which characterizes AD etiology, pathology, and pathogenesis, with the intention of framing the disease as primarily a "disconnection syndrome". We next describe methodologies for investigating the topological properties of human brain networks, using graph theoretical techniques and connectivity information derived from anatomical and diffusion-weighted MR imaging. Finally, we discuss how these methodologies have been applied to systems-level analyses of AD, to help characterize the network changes underlying the disease process, and how these patterns relate to specific cognitive outcome measures.

Different patterns of white matter degeneration using multiple diffusion indices and volumetric data in mild cognitive impairment and Alzheimer patients

Alzheimeŕs disease (AD) represents the most prevalent neurodegenerative disorder that causes cognitive decline in old age. In its early stages, AD is associated with microstructural abnormalities in white matter (WM). In the current study, multiple indices of diffusion tensor imaging (DTI) and brain volumetric measurements were employed to comprehensively investigate the landscape of AD pathology. The sample comprised 58 individuals including cognitively normal subjects (controls), amnestic mild cognitive impairment (MCI) and AD patients. Relative to controls, both MCI and AD subjects showed widespread changes of anisotropic fraction (FA) in the corpus callosum, cingulate and uncinate fasciculus. Mean diffusivity and radial changes were also observed in AD patients in comparison with controls. After controlling for the gray matter atrophy the number of regions of significantly lower FA in AD patients relative to controls was decreased; nonetheless, unique areas of microstructural damage remained, e.g., the corpus callosum and uncinate fasciculus. Despite sample size limitations, the current results suggest that a combination of secondary and primary degeneration occurrs in MCI and AD, although the secondary degeneration appears to have a more critical role during the stages of disease involving dementia.

Shapes of the trajectories of 5 major biomarkers of Alzheimer disease

OBJECTIVE

To characterize the shape of the trajectories of Alzheimer disease biomarkers as a function of Mini-Mental State Examination (MMSE) score.

DESIGN AND SETTING

Longitudinal registries from the Mayo Clinic and the Alzheimer's Disease Neuroimaging Initiative.

PATIENTS

Two different samples (n = 343 and n = 598) were created that spanned the cognitive spectrum from normal to Alzheimer disease dementia. Subgroup analyses were performed in members of both cohorts (n = 243 and n = 328) who were amyloid positive at baseline.

MAIN OUTCOME MEASURES

The shape of biomarker trajectories as a function of MMSE score, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebrospinal fluid (CSF) Aβ42 and tau levels, amyloid and fluorodeoxyglucose positron emission tomography imaging, and structural magnetic resonance imaging.

RESULTS

Baseline biomarker values generally worsened (ie, nonzero slope) with lower baseline MMSE score. Baseline hippocampal volume, amyloid positron emission tomography, and fluorodeoxyglucose positron emission tomography values plateaued (ie, nonlinear slope) with lower MMSE score in 1 or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE score. Nonconstant within-subject rates (deceleration) of biomarker change were found in only 1 model.

CONCLUSIONS

Biomarker trajectory shapes by MMSE score were complex and were affected by interactions with age and APOE status. Nonlinearity was found in several baseline effects models. Nonconstant within-subject rates of biomarker change were found in only 1 model, likely owing to limited within-subject longitudinal follow-up. Creating reliable models that describe the full trajectories of Alzheimer disease biomarkers will require significant additional longitudinal data in individual participants.

The importance of group-wise registration in tract based spatial statistics study of neurodegeneration: a simulation study in Alzheimer's disease

Tract-based spatial statistics (TBSS) is a popular method for the analysis of diffusion tensor imaging data. TBSS focuses on differences in white matter voxels with high fractional anisotropy (FA), representing the major fibre tracts, through registering all subjects to a common reference and the creation of a FA skeleton. This work considers the effect of choice of reference in the TBSS pipeline, which can be a standard template, an individual subject from the study, a study-specific template or a group-wise average. While TBSS attempts to overcome registration error by searching the neighbourhood perpendicular to the FA skeleton for the voxel with maximum FA, this projection step may not compensate for large registration errors that might occur in the presence of pathology such as atrophy in neurodegenerative diseases. This makes registration performance and choice of reference an important issue. Substantial work in the field of computational anatomy has shown the use of group-wise averages to reduce biases while avoiding the arbitrary selection of a single individual. Here, we demonstrate the impact of the choice of reference on: (a) specificity (b) sensitivity in a simulation study and (c) a real-world comparison of Alzheimer's disease patients to controls. In (a) and (b), simulated deformations and decreases in FA were applied to control subjects to simulate changes of shape and WM integrity similar to what would be seen in AD patients, in order to provide a "ground truth" for evaluating the various methods of TBSS reference. Using a group-wise average atlas as the reference outperformed other references in the TBSS pipeline in all evaluations.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Decreased gray matter diffusivity: a potential early Alzheimer's disease biomarker?

BACKGROUND

Gray matter atrophy, an important biomarker for early Alzheimer's disease, might be due to white matter changes within gray matter.

METHODS

Twenty older participants with significant memory decline over a 12-year period (T12) were matched to 20 nondeclining participants. All participants were magnetic resonance imaging scanned at T12. Cortical thickness and diffusion tensor imaging analyses were performed.

RESULTS

Lower cortical thickness values were associated with lower diffusion values in frontal and parietal gray matter areas. This association was only present in the memory decline group. The cortical thickness-diffusion tensor imaging correlations showed significant group differences in the posterior cingulate gyrus, precuneus, and superior frontal gyrus.

CONCLUSIONS

Decreased gray matter diffusivity in the posterior cingulate/precuneus area might be a disease-specific process and a potential new biomarker for early Alzheimer's disease. Future studies should validate its potential as a biomarker and focus on cellular changes underlying diffusivity changes in gray matter.

Surgery and brain atrophy in cognitively normal elderly subjects and subjects diagnosed with mild cognitive impairment

BACKGROUND

Structural magnetic resonance imaging is used to longitudinally monitor the progression of Alzheimer disease from its presymptomatic to symptomatic phases. Using magnetic resonance imaging data from the Alzheimer's Disease Neuroimaging Initiative, we tested the hypothesis that surgery would impact brain parameters associated with progression of dementia.

METHODS

Brain images from the neuroimaging initiative database were used to study normal volunteer subjects and patients with mild cognitive impairment for the age group 55 to 90 inclusive. We compared changes in regional brain anatomy for three visits that defined two intervisit intervals for a surgical cohort (n = 41) and a propensity matched nonsurgical control cohort (n = 123). The first interval for the surgical cohort contained the surgical date. Regional brain volumes were determined with Freesurfer and quantitatively described with J-image software (University of California at San Francisco, San Francisco, California). Statistical analysis used Repeated Measures ANCOVA (SPSS, v.18.0; Chicago, IL).

RESULTS

We found that surgical patients, during the first follow-up interval (5-9 months), but not subsequently, had increased rates of atrophy for cortical gray matter and hippocampus, and lateral ventricle enlargement, as compared with nonsurgical controls. A composite score of five cognitive tests during this interval showed reduced performance for surgical patients with mild cognitive impairment.

CONCLUSIONS

Elderly subjects after surgery experienced an increased rate of brain atrophy during the initial evaluation interval, a time associated with enhanced risk for postoperative cognitive dysfunction. Although there was no difference in atrophy rate by diagnosis, subjects with mild cognitive impairment suffered greater subsequent cognitive effects.