Synopsis
GABA levels measured with MRS have been associated with
performance in numerous sensory and attention domains. Here we demonstrate in a healthy aging cohort
that frontal GABA levels are predictive of general cognitive function. Furthermore, the previously reported age-related
decrease in GABA levels continues into
advanced age.Introduction
γ-Aminobutyric acid (GABA) is the brain’s principal
inhibitory neurotransmitter. Recent application of GABA-edited MRS provides in
vivo evidence for decreasing GABA levels throughout adulthood [2]. Greater concentrations
of GABA in brain regions underlying perception and attention functions have been
found to predict better performance in those behaviors[3]–[6]. It is unclear however, how
age-related decrements in cerebral GABA concentrations contribute to cognitive
decline, or whether previously reported declines in cerebral GABA
concentrations continue during healthy aging. We hypothesized that: A)
participants with higher GABA levels in frontal cortex would exhibit superior general
cognitive function; and B) the previously reported age-related decrease in
cortical GABA levels continues into old age.
Methods
GABA+ edited MRS data were collected in 94 participants (40 male) between 44 and 92 years old, average age 73.1 ± 9.9 years, without history or clinical evidence of mild cognitive impairment (MCI) or dementia. Due to time constraints, 89 participants had only frontal voxel collected and 90 participants had only the posterior voxel collected. MEGA-PRESS data were collected on a 3T Philips Achieva scanner, using a 32-channel head coil and the following acquisition parameters: TR/TE = 2s/68ms, 14 ms-editing pulses at 1.9 ppm (‘On’) and 7.46 ppm (‘Off’), 320 averages, 2048 data points sampled at 2 kHz, VAPOR water suppression and 8 unsuppressed water averages for quantification. Data were acquired from a frontal voxel and a posterior voxel. Voxel locations are shown Figure 1a . Data were processed using Gannet2.0[7], with integrated voxel-to-image coregistration and segmentation using SPM[8], edited spectra from all participants and voxels are shown in Figure 1b.
The Montreal Cognitive Assessment (MoCA) was administered to assess cognitive functioning.
Methods
GABA+ edited MRS data were collected in 94 participants (40 male) between 44 and 92 years old, average age 73.1 ± 9.9 years, without history or clinical evidence of mild cognitive impairment (MCI) or dementia. Due to time constraints, 89 participants had only frontal voxel collected and 90 participants had only the posterior voxel collected. MEGA-PRESS data were collected on a 3T Philips Achieva scanner, using a 32-channel head coil and the following acquisition parameters: TR/TE = 2s/68ms, 14 ms-editing pulses at 1.9 ppm (‘On’) and 7.46 ppm (‘Off’), 320 averages, 2048 data points sampled at 2 kHz, VAPOR water suppression and 8 unsuppressed water averages for quantification. Data were acquired from a frontal voxel and a posterior voxel. Voxel locations are shown Figure 1a . Data were processed using Gannet2.0[7], with integrated voxel-to-image coregistration and segmentation using SPM[8], edited spectra from all participants and voxels are shown in Figure 1b.
The Montreal Cognitive Assessment (MoCA) was administered to assess cognitive functioning.
Results
Cognition: Higher GABA+ levels in both frontal and posterior cortical regions were associated with stronger cognitive performance. This relationship remained significant for the frontal region, but not the posterior region, after controlling for age, years of education, and brain atrophy (Figure 2). The results of this multiple regression demonstrated that the four predictors accounted for a significant amount of the variance in cognitive performance (R2 = 0.22, F[4,84] = 5.775, p < 0.001). Within this model, higher GABA significantly predicted better score, even when accounting for demographic influences and CSF fraction (β = 3.32, p < 0.01). Cognitive performance was not independently related to age, years of education, and or CSF fraction (β = -0.5, p > 0.05; β = 0.10, p > 0.05; β = 3.95, p > 0.05, respectively).
Ageing: GABA+ levels decreased as a function of age in both regions. To account for age-related brain atrophy, CSF fraction was included with age in the multiple regression models. In the frontal region (R2 = 0.38, F[2, 86] = 26.19, p < 0.001), greater age was related to lower GABA concentrations (β = -9.378, p < 0.01) as shown in Figure 3a and greater CSF concentrations were positively associated with age (β = 57.41, p < 0.001). In the posterior region (R2 = 0.38, F[2, 86] = 26.19, p < 0.001), greater age was related to lower GABA concentrations (β = -13.95, p < 0.01) as shown in Figure 3b; no relationship was found between CSF concentrations and age (β = 1.65, p > .05).
Discussion
These novel findings, from a large, healthy, older population, indicate that cognitive function is influenced by cerebral GABA+ levels in the frontal cortex, and GABA+ levels in both frontal and posterior regions continue to decline in healthy aging. These statistically dissociable effects suggest that proton MRS may provide a clinically useful method for not only the assessment of normal and abnormal age-related cognitive changes but also the underlying physiological underpinnings of these changes.
Results
Cognition: Higher GABA+ levels in both frontal and posterior cortical regions were associated with stronger cognitive performance. This relationship remained significant for the frontal region, but not the posterior region, after controlling for age, years of education, and brain atrophy (Figure 2). The results of this multiple regression demonstrated that the four predictors accounted for a significant amount of the variance in cognitive performance (R2 = 0.22, F[4,84] = 5.775, p < 0.001). Within this model, higher GABA significantly predicted better score, even when accounting for demographic influences and CSF fraction (β = 3.32, p < 0.01). Cognitive performance was not independently related to age, years of education, and or CSF fraction (β = -0.5, p > 0.05; β = 0.10, p > 0.05; β = 3.95, p > 0.05, respectively).
Ageing: GABA+ levels decreased as a function of age in both regions. To account for age-related brain atrophy, CSF fraction was included with age in the multiple regression models. In the frontal region (R2 = 0.38, F[2, 86] = 26.19, p < 0.001), greater age was related to lower GABA concentrations (β = -9.378, p < 0.01) as shown in Figure 3a and greater CSF concentrations were positively associated with age (β = 57.41, p < 0.001). In the posterior region (R2 = 0.38, F[2, 86] = 26.19, p < 0.001), greater age was related to lower GABA concentrations (β = -13.95, p < 0.01) as shown in Figure 3b; no relationship was found between CSF concentrations and age (β = 1.65, p > .05).
Discussion
These novel findings, from a large, healthy, older population, indicate that cognitive function is influenced by cerebral GABA+ levels in the frontal cortex, and GABA+ levels in both frontal and posterior regions continue to decline in healthy aging. These statistically dissociable effects suggest that proton MRS may provide a clinically useful method for not only the assessment of normal and abnormal age-related cognitive changes but also the physiological underpinnings of these changes.
Acknowledgements
Acknowledgements
This study was supported in part by the Center for Cognitive
Aging and Memory at the University of Florida, the McKnight Brain Research Foundation, NIH/NCATS CTSA grant UL1TR000064 and KL2
TR000065, and the Claude D. Pepper Center at the University of Florida (P30
AG028740).References
[1] N.
A. J. Puts and R. A. E. Edden, “In vivo magnetic resonance spectroscopy of
GABA: a methodological review.,” Prog. Nucl. Magn. Reson. Spectrosc.,
vol. 60, pp. 29–41, Jan. 2012.
[2] F.
Gao, R. A. E. Edden, M. Li, N. A. J. Puts, G. Wang, C. Liu, B. Zhao, H. Wang,
X. Bai, C. Zhao, X. Wang, and P. B. Barker, “Edited magnetic resonance
spectroscopy detects an age-related decline in brain GABA levels,” Neuroimage,
vol. 78, pp. 75–82, 2013.
[3] N.
A. J. Puts, R. A. E. Edden, C. J. Evans, F. McGlone, and D. J. McGonigle, “Regionally
specific human GABA concentration correlates with tactile discrimination
thresholds.,” J. Neurosci., vol. 31, no. 46, pp. 16556–60, Nov. 2011.
[4] N.
A. Puts, A. D. Harris, D. Crocetti, C. Nettles, H. S. Singer, M. Tommerdahl, R.
A. Edden, and S. H. Mostofsky, “Reduced GABAergic inhibition and abnormal
sensory processing in children with Tourette Syndrome.,” J. Neurophysiol.,
p. jn.00060.2015, Jun. 2015.
[5] R.
A. E. Edden, S. D. Muthukumaraswamy, T. C. A. Freeman, and K. D. Singh, “Orientation
discrimination performance is predicted by GABA concentration and gamma
oscillation frequency in human primary visual cortex.,” J. Neurosci.,
vol. 29, no. 50, pp. 15721–6, Dec. 2009.
[6] P.
Sumner, R. A. E. Edden, A. Bompas, C. J. Evans, and K. D. Singh, “More GABA,
less distraction: a neurochemical predictor of motor decision speed.,” Nat.
Neurosci., vol. 13, pp. 825–827, 2010.
7] R.
A. E. Edden, N. A. J. Puts, A. D. Harris, P. B. Barker, and C. J. Evans, “Gannet:
A batch-processing tool for the quantitative analysis of gamma-aminobutyric
acid–edited MR spectroscopy spectra.,” J. Magn. Reson. Imaging, vol. 40,
no. 6, pp. 1445–52, Dec. 2014.
[8] J.
Ashburner and K. J. Friston, “Unified segmentation.,” Neuroimage, vol.
26, no. 3, pp. 839–51, 2005.