| Literature DB >> 29722142 |
Celine Maes1, Lize Hermans1, Lisa Pauwels1, Sima Chalavi1, Inge Leunissen1, Oron Levin1, Koen Cuypers1,2, Ronald Peeters3,4, Stefan Sunaert3,4, Dante Mantini1, Nicolaas A J Puts5,6, Richard A E Edden5,6, Stephan P Swinnen1,7.
Abstract
Levels of GABA, the main inhibitory neurotransmitter in the brain, can be regionally quantified using magnetic resonance spectroscopy (MRS). Although GABA is crucial for efficient neuronal functioning, little is known about age-related differences in GABA levels and their relationship with age-related changes in brain structure. Here, we investigated the effect of age on GABA levels within the left sensorimotor cortex and the occipital cortex in a sample of 85 young and 85 older adults using the MEGA-PRESS sequence. Because the distribution of GABA varies across different brain tissues, various correction methods are available to account for this variation. Considering that these correction methods are highly dependent on the tissue composition of the voxel of interest, we examined differences in voxel composition between age groups and the impact of these various correction methods on the identification of age-related differences in GABA levels. Results indicated that, within both voxels of interest, older (as compared to young adults) exhibited smaller gray matter fraction accompanied by larger fraction of cerebrospinal fluid. Whereas uncorrected GABA levels were significantly lower in older as compared to young adults, this age effect was absent when GABA levels were corrected for voxel composition. These results suggest that age-related differences in GABA levels are at least partly driven by the age-related gray matter loss. However, as alterations in GABA levels might be region-specific, further research should clarify to what extent gray matter changes may account for age-related differences in GABA levels within other brain regions.Entities:
Keywords: aging; cerebrospinal fluid; gamma aminobutyric acid; gray matter; magnetic resonance spectroscopy
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Year: 2018 PMID: 29722142 PMCID: PMC6866434 DOI: 10.1002/hbm.24201
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.038