Gray matter network associated with risk for Alzheimer's disease in young to middle-aged adults

APOE ɛ4 constrains engagement of encoding-related compensatory networks in amnestic mild cognitive impairment

People with amnestic mild cognitive impairment (aMCI), compared to healthy older adults (HO), benefit less from semantic congruent cues during episodic encoding. The presence of the apolipoprotein E (APOE) ɛ4 makes this congruency benefit smaller, but the neural correlates of this deficit are unknown. Here, we estimated the source generators of EEG oscillatory activity associated with successful encoding of face-location associations preceded by semantically congruent and incongruent cues in HO (N = 26) and aMCI subjects (N = 34), 16 of which were ɛ4 carriers (ɛ4(+) ) and 18 ɛ4 noncarriers (ɛ4(-) ). Source estimation was performed in those spectrotemporal windows where the power of low-alpha, high-alpha, and beta oscillatory activity differed either between congruent and incongruent faces or between groups. Differences in high-alpha and beta-oscillatory dynamics indicated that aMCI ɛ4(+) are unable to activate lateral regions of the temporal lobe involved in associative memory and congruency benefit in HO. Interestingly, and regardless of APOE genotype, aMCI activated additional regions relative to HO, through alpha oscillations. However, only activation in a distributed fronto-temporo-parietal network in ɛ4 noncarriers was paralleled by enhanced memory. On the contrary, the redundant prefrontal activation shown by aMCI ɛ4(+) did not prevent performance from decreasing. These results indicate that the effect of aMCI-related degeneracy on functional networks is constrained by the presence of APOE ɛ4. Whereas individuals with aMCI ɛ4(-) activate attentional, perceptual and semantic compensatory networks, aMCI ɛ4(+) show reduced processing efficiency and capacity.

Higher homocysteine associated with thinner cortical gray matter in 803 participants from the Alzheimer's Disease Neuroimaging Initiative

A significant portion of our risk for dementia in old age is associated with lifestyle factors (diet, exercise, and cardiovascular health) that are modifiable, at least in principle. One such risk factor, high-homocysteine levels in the blood, is known to increase risk for Alzheimer's disease and vascular disorders. Here, we set out to understand how homocysteine levels relate to 3D surface-based maps of cortical gray matter distribution (thickness, volume, and surface area) computed from brain magnetic resonance imaging in 803 elderly subjects from the Alzheimer's Disease Neuroimaging Initiative data set. Individuals with higher plasma levels of homocysteine had lower gray matter thickness in bilateral frontal, parietal, occipital, and right temporal regions and lower gray matter volumes in left frontal, parietal, temporal, and occipital regions, after controlling for diagnosis, age, and sex and after correcting for multiple comparisons. No significant within-group associations were found in cognitively healthy people, patients with mild cognitive impairment, or patients with Alzheimer's disease. These regional differences in gray matter structure may be useful biomarkers to assess the effectiveness of interventions, such as vitamin B supplements, that aim to prevent homocysteine-related brain atrophy by normalizing homocysteine levels.

Two Alzheimer's disease risk genes increase entorhinal cortex volume in young adults

Alzheimer's disease (AD) risk genes alter brain structure and function decades before disease onset. Apolipoprotein E (APOE) is the strongest known genetic risk factor for AD, and a related gene, apolipoprotein J (APOJ), also affects disease risk. However, the extent to which these genes affect brain structure in young adults remains unclear. Here, we report that AD risk alleles of these two genes, APOE-ε4 and APOJ-C, cumulatively alter brain volume in young adults. Using voxel-based morphometry (VBM) in 57 individuals, we examined the entorhinal cortex, one of the earliest brain regions affected in AD pathogenesis. Apolipoprotein E-ε4 carriers exhibited higher right entorhinal cortex volume compared to non-carriers. Interestingly, APOJ-C risk genotype was associated with higher bilateral entorhinal cortex volume in non-APOE-ε4 carriers. To determine the combined disease risk of APOE and APOJ status per subject, we used cumulative odds ratios as regressors for volumetric measurements. Higher disease risk corresponded to greater right entorhinal cortex volume. These results suggest that, years before disease onset, two key AD genetic risk factors may exert influence on the structure of a brain region where AD pathogenesis takes root.

Cognitive decline and brain pathology in aging--need for a dimensional, lifespan and systems vulnerability view

Changes in brain structure and activity as well as cognitive function are commonly seen in aging. However, it is not known when aging of brain and cognition starts, and how much of the changes observed in seemingly healthy older adults that can be ascribed to incipient neurodegenerative disease. Recent research has yielded evidence that the borders between development and aging sometimes can be fuzzy, as can the borders between dementing disease and normal age changes. In this review, we argue that many factors affecting cognitive decline and dementia represents quantitative rather than qualitative differences in characteristics that commonly exist in the population. Further, factors known to affect brain and cognition in aging will often do so through a life-long accumulation of impact, and does not need to be specific to aging. And finally, a host of environmental and genetic factors and their interplay determine optimal aging, leaving room for potential for environmental interventions to affect the outcome of the aging process. Together, we argue that these factors call for a dimensional rather than categorical, lifespan rather than aging, and multidimensional systems-vulnerability rather than simple "hypothetical biomarker" model of age-associated cognitive decline and dementia. This has implications for how we should view lifespan trajectories of change in brain and cognitive function, and how we can study, prevent, diagnose and treat age-associated cognitive deficits.

Exercise, APOE genotype, and the evolution of the human lifespan

Humans have exceptionally long lifespans compared with other mammals. However, our longevity evolved when our ancestors had two copies of the apolipoprotein E (APOE) ɛ4 allele, a genotype that leads to a high risk of Alzheimer's disease (AD), cardiovascular disease, and increased mortality. How did human aging evolve within this genetic constraint? Drawing from neuroscience, anthropology, and brain-imaging research, we propose the hypothesis that the evolution of increased physical activity approximately 2 million years ago served to reduce the amyloid plaque and vascular burden of APOE ɛ4, relaxing genetic constraints on aging. This multidisciplinary approach links human evolution with health and provides a complementary perspective on aging and neurodegenerative disease that may help identify key mechanisms and targets for intervention.

Regional covariance patterns of gray matter alterations in Alzheimer's disease and its replicability evaluation

PURPOSE

To identify regional network covariance patterns of gray matter associated with Alzheimer's disease (AD) and to further evaluate its replicability and stability.

MATERIALS AND METHODS

This study applied a multivariate analytic approach based on scaled subprofile modeling (SSM) to structural magnetic resonance imaging (MRI) data from 19 patients with AD and 19 healthy controls (HC). We further applied the derived covariance patterns to examine the replicability and stability of AD-associated covariance patterns in an independent dataset (13 AD and 14 HC) acquired with a different scanner.

RESULTS

The AD-associated covariance patterns identified from SSM combined principal components mainly involved the temporal lobe and parietal lobe. The expression of covariance patterns was significantly higher in AD patients than HC (t(36)  = 5.84, P = 5.75E-7) and predicted the AD/HC group membership (84% sensitivity and 90% specificity). In replicability evaluation, the expression of the forward applied covariance patterns was still statistically significant and had acceptable discriminability (69% sensitivity and 71% specificity).

CONCLUSION

AD patients showed regional gray matter alterations in a reliable covariance manner. The results suggest that SSM has utility for characterizing covariant features, and therefore can assist with further understanding covariance patterns of gray matter in AD based on the view of the network.

Structural interactions within the default mode network identified by Bayesian network analysis in Alzheimer's disease

Alzheimer’s disease (AD) is a well-known neurodegenerative disease that is associated with dramatic morphological abnormalities. The default mode network (DMN) is one of the most frequently studied resting-state networks. However, less is known about specific structural dependency or interactions among brain regions within the DMN in AD. In this study, we performed a Bayesian network (BN) analysis based on regional grey matter volumes to identify differences in structural interactions among core DMN regions in structural MRI data from 80 AD patients and 101 normal controls (NC). Compared to NC, the structural interactions between the medial prefrontal cortex (mPFC) and other brain regions, including the left inferior parietal cortex (IPC), the left inferior temporal cortex (ITC) and the right hippocampus (HP), were significantly reduced in the AD group. In addition, the AD group showed prominent increases in structural interactions from the left ITC to the left HP, the left HP to the right ITC, the right HP to the right ITC, and the right IPC to the posterior cingulate cortex (PCC). The BN models significantly distinguished AD patients from NC with 87.12% specificity and 81.25% sensitivity. We then used the derived BN models to examine the replicability and stability of AD-associated BN models in an independent dataset and the results indicated discriminability with 83.64% specificity and 80.49% sensitivity. The results revealed that the BN analysis was effective for characterising regional structure interactions and the AD-related BN models could be considered as valid and predictive structural brain biomarker models for AD. Therefore, our study can assist in further understanding the pathological mechanism of AD, based on the view of the structural network, and may provide new insights into classification and clinical application in the study of AD in the future.

Networks of anatomical covariance

Functional imaging or diffusion-weighted imaging techniques are widely used to understand brain connectivity at the systems level and its relation to normal neurodevelopment, cognition or brain disorders. It is also possible to extract information about brain connectivity from the covariance of morphological metrics derived from anatomical MRI. These covariance patterns may arise from genetic influences on normal development and aging, from mutual trophic reinforcement as well as from experience-related plasticity. This review describes the basic methodological strategies, the biological basis of the observed covariance as well as applications in normal brain and brain disease before a final review of future prospects for the technique.

Imaging structural co-variance between human brain regions

Brain structure varies between people in a markedly organized fashion. Communities of brain regions co-vary in their morphological properties. For example, cortical thickness in one region influences the thickness of structurally and functionally connected regions. Such networks of structural co-variance partially recapitulate the functional networks of healthy individuals and the foci of grey matter loss in neurodegenerative disease. This architecture is genetically heritable, is associated with behavioural and cognitive abilities and is changed systematically across the lifespan. The biological meaning of this structural co-variance remains controversial, but it appears to reflect developmental coordination or synchronized maturation between areas of the brain. This Review discusses the state of current research into brain structural co-variance, its underlying mechanisms and its potential value in the understanding of various neurological and psychiatric conditions.

Mapping joint grey and white matter reductions in Alzheimer's disease using joint independent component analysis

Alzheimer's disease (AD) is a neurodegenerative disease concomitant with grey and white matter damages. However, the interrelationship of volumetric changes between grey and white matter remains poorly understood in AD. Using joint independent component analysis, this study identified joint grey and white matter volume reductions based on structural magnetic resonance imaging data to construct the covariant networks in twelve AD patients and fourteen normal controls (NC). We found that three networks showed significant volume reductions in joint grey-white matter sources in AD patients, including (1) frontal/parietal/temporal-superior longitudinal fasciculus/corpus callosum, (2) temporal/parietal/occipital-frontal/occipital, and (3) temporal-precentral/postcentral. The corresponding expression scores distinguished AD patients from NC with 85.7%, 100% and 85.7% sensitivity for joint sources 1, 2 and 3, respectively; 75.0%, 66.7% and 75.0% specificity for joint sources 1, 2 and 3, respectively. Furthermore, the combined source of three significant joint sources best predicted the AD/NC group membership with 92.9% sensitivity and 83.3% specificity. Our findings revealed joint grey and white matter loss in AD patients, and these results can help elucidate the mechanism of grey and white matter reductions in the development of AD.

Characterizing healthy samples for studies of human cognitive aging

Characterizing the cognitive declines associated with aging, and differentiating them from the effects of disease in older adults, are important goals for human neuroscience researchers. This is also an issue of public health urgency in countries with rapidly aging populations. Progress toward understanding cognitive aging is complicated by numerous factors. Researchers interested in cognitive changes in healthy older adults need to consider these complexities when they design and interpret studies. This paper addresses important factors in study design, patient demographics, co-morbid and incipient medical conditions, and assessment instruments that will allow researchers to optimize the characterization of healthy participants and produce meaningful and generalizable research outcomes from studies of cognitive aging. Application of knowledge from well-designed studies should be useful in clinical settings to facilitate the earliest possible recognition of disease and guide appropriate interventions to best meet the needs of the affected individual and public health priorities.

Correlations between FDG PET glucose uptake-MRI gray matter volume scores and apolipoprotein E ε4 gene dose in cognitively normal adults: a cross-validation study using voxel-based multi-modal partial least squares

We previously introduced a voxel-based, multi-modal application of the partial least square algorithm (MMPLS) to characterize the linkage between patterns in a person's complementary complex datasets without the need to correct for multiple regional comparisons. Here we used it to demonstrate a strong correlation between MMPLS scores to characterize the linkage between the covarying patterns of fluorodeoxyglucose positron emission tomography (FDG PET) measurements of regional glucose metabolism and magnetic resonance imaging (MRI) measurements of regional gray matter associated with apolipoprotein E (APOE) ε4 gene dose (i.e., three levels of genetic risk for late-onset Alzheimer's disease (AD)) in cognitively normal, late-middle-aged persons. Coregistered and spatially normalized FDG PET and MRI images from 70% of the subjects (27 ε4 homozygotes, 36 ε4 heterozygotes and 67 ε4 non-carriers) were used in a hypothesis-generating MMPLS analysis to characterize the covarying pattern of regional gray matter volume and cerebral glucose metabolism most strongly correlated with APOE-ε4 gene dose. Coregistered and spatially normalized FDG PET and MRI images from the remaining 30% of the subjects were used in a hypothesis-testing MMPLS analysis to generate FDG PET-MRI gray matter MMPLS scores blind to their APOE genotype and characterize their relationship to APOE-ε4 gene dose. The hypothesis-generating analysis revealed covarying regional gray matter volume and cerebral glucose metabolism patterns that resembled those in traditional univariate analyses of AD and APOE-ε4 gene dose and PET-MRI scores that were strongly correlated with APOE-ε4 gene dose (p<1 × 10(-16)). The hypothesis-testing analysis results showed strong correlations between FDG PET-MRI gray matter scores and APOE-ε4 gene dose (p = 8.7 × 10(-4)). Our findings support the possibility of using the MMPLS to analyze complementary datasets from the same person in the presymptomatic detection and tracking of AD.