Dataset Information

Regional Gray Matter Volume Links Rest-Activity Rhythm Fragmentation With Past Cognitive Decline.

ABSTRACT:

Objectives

We examined the extent to which measures of neurodegeneration and cerebrovascular disease explain the rest-activity rhythm (RAR)-cognition link.

Methods

Seventy participants (mean age at MRI?=?86, standard deviation (SD)?=?2.6; 53% female) had cognitive, MRI, and accelerometer data. The slope of cognitive decline was defined applying a mixed model to 10 repeated Modified Mini Mental Status Test (3MS) measures over 14 years. Regional gray matter volume (GMV), white matter hyperintensities, and RARs were measured around year 12.

Results

Past 3MS decline was related to RAR fragmentation (per SD ? = -0.43, 95% confidence interval: -0.73, -0.14) and lower posterior parietal GMV (per standard deviation ??=?0.47, 95% confidence interval: 0.14, 0.79). Higher RAR fragmentation was related to lower posterior parietal GMV (Pearson r = -0.39, n?=?70, p?=?0.0007), which attenuated the association of RAR fragmentation and past cognitive decline by 17%.

Conclusions

Longitudinal studies are warranted to understand the temporal relations and mechanisms linking RAR fragmentation and neurodegeneration.

SUBMITTER: Smagula SF

PROVIDER: S-EPMC6980463 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Regional Gray Matter Volume Links Rest-Activity Rhythm Fragmentation With Past Cognitive Decline.

Smagula Stephen F SF Chahine Lana L Metti Andrea A Rangarajan Anusha A Aizenstein Howard J HJ Tian Qu Q Rosano Caterina C

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry 20190719 2

<h4>Objectives</h4>We examined the extent to which measures of neurodegeneration and cerebrovascular disease explain the rest-activity rhythm (RAR)-cognition link.<h4>Methods</h4>Seventy participants (mean age at MRI = 86, standard deviation (SD) = 2.6; 53% female) had cognitive, MRI, and accelerometer data. The slope of cognitive decline was defined applying a mixed model to 10 repeated Modified Mini Mental Status Test (3MS) measures over 14 years. Regional gray matter volume (GMV), white matte ...[more]

PMID: 31377045

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Project description:BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.MethodsDifferences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.LimitationsThe method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Dataset Information

Regional Gray Matter Volume Links Rest-Activity Rhythm Fragmentation With Past Cognitive Decline.

Objectives

Methods

Results

Conclusions

Publications

Regional Gray Matter Volume Links Rest-Activity Rhythm Fragmentation With Past Cognitive Decline.

Similar Datasets

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