Longitudinal gray-matter volume change in the default-mode network: utility of volume standardized with global gray-matter volume for Alzheimer's disease: a preliminary study

Epigenetic Clock Deceleration and Maternal Reproductive Efforts: Associations With Increasing Gray Matter Volume of the Precuneus

Reproductive efforts, such as pregnancy, delivery, and interaction with children, make maternal brains optimized for child-rearing. However, extensive studies in non-human species revealed a tradeoff between reproductive effort and life expectancy. In humans, large demographic studies have shown that this is the case for the most part; however, molecular marker studies regarding aging remain controversial. There are no studies simultaneously evaluating the relationship between reproductive effort, aging, and brain structures. We therefore examined the associations between reproductive efforts (parity status, number of deliveries, motherhood period, and cumulative motherhood period), DNA methylation age (mAge) acceleration (based on Horvath’s multi-tissue clock and the skin & blood clock), and the regional gray matter volumes (obtained through brain magnetic resonance imaging (MRI) using voxel-based morphometry) in 51 mothers aged 27–46 years of children in early childhood. We found that increasing reproductive efforts were significantly associated with decelerated aging in mothers with one to four children, even after adjusting for the confounding effects in the multiple linear regression models. We also found that the left precuneus gray matter volume was larger as deceleration of aging occurred; increasing left precuneus gray matter volume, on the other hand, mediates the relationship between parity status and mAge deceleration. Our findings suggest that mothers of children in early childhood, who have had less than four children, may benefit from deceleration of aging mediated via structural changes in the precuneus.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

Voxel-based meta-analysis of grey matter changes in Alzheimer's disease

Background

Voxel-based morphometry (VBM) using structural brain MRI has been widely used for the assessment of impairment in Alzheimer’s disease (AD), but previous studies in VBM studies on AD remain inconsistent.

Objective

We conducted meta-analyses to integrate the reported studies to determine the consistent grey matter alterations in AD based on VBM method.

Methods

The PubMed, ISI Web of Science, EMBASE and Medline database were searched for articles between 1995 and June 2014. Manual searches were also conducted, and authors of studies were contacted for additional data. Coordinates were extracted from clusters with significant grey matter difference between AD patients and healthy controls (HC). Meta-analysis was performed using a new improved voxel-based meta-analytic method, Effect Size Signed Differential Mapping (ES-SDM).

Results

Thirty data-sets comprising 960 subjects with AD and 1195 HC met inclusion criteria. Grey matter volume (GMV) reduction at 334 coordinates in AD and no GMV increase were found in the current meta-analysis. Significant reductions in GMV were robustly localized in the limbic regions (left parahippocampl gyrus and left posterior cingulate gyrus). In addition, there were GM decreases in right fusiform gyrus and right superior frontal gyrus. The findings remain largely unchanged in the jackknife sensitivity analyses.

Conclusions

Our meta-analysis clearly identified GMV atrophy in AD. These findings confirm that the most prominent and replicable structural abnormalities in AD are in the limbic regions and contributes to the understanding of pathophysiology underlying AD.