Dataset Information

Gray Matter Volume and Cognitive Performance During Normal Aging. A Voxel-Based Morphometry Study.

ABSTRACT: Normal aging is characterized by decline in cognitive functioning in conjunction with extensive gray matter (GM) atrophy. A first aim of this study was to determine GM volume differences related to aging by comparing two groups of participants, middle-aged group (MAG, mean age 41 years, N = 16) and older adults (OG, mean age 71 years, N = 14) who underwent an magnetic resonance images (MRI) voxel-based morphometry (VBM) evaluation. The VBM analyses included two optimized pipelines, for the cortex and for the cerebellum. Participants were also evaluated on a wide range of cognitive tests assessing both domain-general and language-specific processes, in order to examine how GM volume differences between OG and MAG relate to cognitive performance. Our results show smaller bilateral GM volume in the OG relative to the MAG, in several cerebral and right cerebellar regions involved in language and executive functions. Importantly, our results also revealed smaller GM volume in the right cerebellum in OG relative to MAG, supporting the idea of a complex cognitive role for this structure. This study provides a broad picture of cerebral, but also cerebellar and cognitive changes associated with normal aging.

SUBMITTER: Ramanoel S

PROVIDER: S-EPMC6085481 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Gray Matter Volume and Cognitive Performance During Normal Aging. A Voxel-Based Morphometry Study.

Ramanoël Stephen S Hoyau Elena E Kauffmann Louise L Renard Félix F Pichat Cédric C Boudiaf Naïla N Krainik Alexandre A Jaillard Assia A Baciu Monica M

Frontiers in aging neuroscience 20180803

Normal aging is characterized by decline in cognitive functioning in conjunction with extensive gray matter (GM) atrophy. A first aim of this study was to determine GM volume differences related to aging by comparing two groups of participants, middle-aged group (MAG, mean age 41 years, <i>N</i> = 16) and older adults (OG, mean age 71 years, <i>N</i> = 14) who underwent an magnetic resonance images (MRI) voxel-based morphometry (VBM) evaluation. The VBM analyses included two optimized pipelines, ...[more]

PMID: 30123123

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Project description:Results from studies that have examined age-related changes in gray matter based on structural MRI scans have not always been consistent. Reasons for this variability likely include small or unevenly-distributed samples, different methods for tissue class segmentation and spatial normalization, and the use of different statistical models. Particularly relevant to the latter is the method of adjusting for global (total) gray matter when making inferences about regionally-specific changes. In the current study, we use voxel-based morphometry (VBM) to explore the impact of these methodological choices in assessing age-related changes in gray matter volume in a sample of 420 adults evenly distributed between the ages of 18-77 years. At a broad level, we replicate previous findings, showing age-related gray matter decline in nearly all parts of the brain, with particularly rapid decline in inferior regions of frontal cortex (e.g., insula and left inferior frontal gyrus) and the central sulcus. Segmentation was improved by increasing the number of tissue classes and using less age-biased templates, and registration was improved by using a diffeomorphic flow-based algorithm (DARTEL) rather than a "constrained warp" approach. Importantly, different approaches to adjusting for global effects--not adjusting, Local Covariation, Global Scaling, and Local Scaling--significantly affected regionally-specific estimates of age-related decline, as demonstrated by ranking age effects across anatomical ROIs. Split-half cross-validation showed that, on average, Local Covariation explained a greater proportion of age-related variance across these ROIs than did Global Scaling. Nonetheless, the appropriate choice for global adjustment depends on one's assumptions and specific research questions. More generally, these results emphasize the importance of being explicit about the assumptions underlying key methodological choices made in VBM analyses and the inferences that follow.

Project description:IntroductionWe performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging.MethodsTranscriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 ?m) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability.ResultsTranscripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT.ConclusionExpression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation.

Dataset Information

Gray Matter Volume and Cognitive Performance During Normal Aging. A Voxel-Based Morphometry Study.

Publications

Gray Matter Volume and Cognitive Performance During Normal Aging. A Voxel-Based Morphometry Study.

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