Toru Ishii1, Koji Fujimoto1, Hideto Kuribayashi2, Yuta Urushibata2, Nouha Salibi3, Ravi Teja Seethamraju3, Sinyeob Ahn3, Tadashi Isa1, and Tomohisa Okada1
1Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan, 2Siemens Healthcare K.K., Japan, Tokyo, Japan, 3Siemens Healthcare, Charlestown, MA, United States
Synopsis
The purpose of this
study was to quantify changes of neurochemical concentrations in
human brain associated with normal aging with greater sensitivity and accuracy
using ultra-high field 7T-MRI. 1H magnetic resonance spectra in the
posterior cingulate cortex of 54 healthy adults were measured using a
stimulated echo acquisition mode (STEAM) sequence with short echo time, and
analysed with LCModel. In addition to the expected result of NAA decrease with
aging, both Glutamate and GABA showed significant negative correlations with
age. The results may provide significant insights in understanding alterations
of human brain accompanying the normal aging.
Introduction
Early
detection and prevention of dementia are unmet medical needs around the world. As
a premise for investigating the neurodegenerative process, to understand changes
in the brain associated with normal aging is indispensable. Proton
magnetic resonance spectroscopy (MRS) is a promising method for such a purpose
as it can noninvasively assess neurochemical concentrations in human brain in
vivo. However, the results of previous studies on age-associated changes of
neurochemicals using MRS at 1.5T or 3T are not necessarily consistent1-3,
and thus the metabolic changes across life span still remain to be elucidated. This
inconsistency of results could be attributable to low sensitivity and
specificity which arise from low magnetic fields. Here, we aimed to quantify
changes of neurochemical concentrations related to normal aging with high
sensitivity and accuracy using ultra-high field 7 T-MRI.Methods
Fifty-four
healthy adults (28 females, age;48.8 ± 21.2 (mean ± standard deviation) years,
age range; 20–77 years) who had no history of any neurological or psychiatric
disorders were enrolled under approval of IRB. Subjects who scored <24 on
the Montreal Cognitive Assessment (MoCA) and >10 on the Patient Health
Qustionnaire-9 (PHQ-9) were excluded in advance. Two neurologists reviewed all elderly
participants to exclude those with incipient neurological disorders.
MRS was scanned with a 7T
whole-body scanner (Magnetom 7T, Siemens, Erlangen, Germany) using a
single-transmit volume coil and a 32-receiver head coil (Nova Medical, MA, USA).
A 20-mm cubic
volumes-of-interest (VOI) was positioned at the posterior cingulate cortex
(PCC) across the mid-sagittal plane on acquired T1-weighted images (Figure 1). Consistent
voxel placement among brains was confirmed by the same neuroradiologist for all
scans. FASTMAP shimming (prototype) and transmit amplitude adjustment were
performed in the MRS voxel. Proton MR spectra were acquired using a stimulated
echo acquisition mode (STEAM) sequence (prototype) with short echo time (TR = 8000 ms; TE =
5 ms; mixing time = 45 ms; 32 averages) with water (VAPOR4) and
outer volume suppressions. Water unsuppressed spectra of the same MRS voxel
were also acquired.
All spectra were analyzed using
LCModel 6.3-1L (LA Systems, Tokyo, Japan) using the metabolite basis set of alanine
(Ala), aspartate (Asp), Cr, GABA, glucose (Glc), glutamine (Gln), glutamate (Glu),
glutathione (GSH), GPC, lactate (Lac), mIns, NAA, NAAG, PCr, PCh, scyllo-inositol (sIns), taurine (Tau) and -CrCH2, supplied as a
standard option. Eddy current correction and water-scaling for quantification
were performed using the water unsuppressed spectra5. Metabolites with
mean CRLB value less
than 20%
were included for further statistical analysis.
Associations between age and neurochemical concentrations were analyzed by linear regression.
Bonferroni corrections were used to correct for multiple comparisons, and
corrected P values below 0.05 were
considered statistically significant.Results
A
representative MR spectrum, fit curve and residual are shown in Figure 1. Nine
neurochemicals were quantified with mean CRLB <20%. Figure 2 shows the results
of regression analyses for metabolites and age. Concentrations
of NAA, Glu, GABA and tCho showed significant negative correlation with age (P < 0.005) (Figure 3). These
correlations remained significant after discarding individual data with CRLB ≧ 20%. Tau and GSH showed weak negative trends (P = 0.01 and 0.02, respectively). Concentrations
of tCr, Gln and mIns did not show significant correlation with age.Discussion
In line
with some previous reports6, our results showed that NAA, which is
thought to be a neuronal marker, decrease with age. Moreover, the results showed
that both the main inhibitory and excitatory neurotransmitters in the brain, GABA
and Glutamate, significantly decrease with aging. Because regression slopes
were steeper in GABA and Glutamate than in NAA, reduction of GABA and Glutamate
with aging might reflect not only the results of nonspecific neuronal loss but alterations
in regulation of synaptic function. This result is consistent with previous
animal studies with MRS7. Although mIns, a possible glial marker,
was not correlated significantly across all subjects, there was a tendency for
age-related increase in elderly people. It may indicate that mIns increases in
non-linear fashion with aging.Conclusion
Comprehensive
MRS data of neurochemical alterations related to aging were acquired with 7T ultra-high
field scanning. The results may provide a basis for understanding changes in human
brain associated with normal aging and will contribute to elucidate disease-specific
neurodegenerative process.Acknowledgements
We acknowledge his technical contribution of Dr. Moran R Gerald, Siemens Healthcare Canada.
References
1 Reyngoudt
H, Claeys T, Vlerick L, Verleden S, Acou M, Deblaere K, De Deene Y, Audenaert
K, Goethals I, Achten E (2012) Age-related differences in metabolites in the
posterior cingulate cortex and hippocampus of normal ageing brain: a 1H-MRS
study. European journal of radiology 81 (3):e223-231.
2. Chang
L, Jiang CS, Ernst T (2009) Effects of age and sex on brain glutamate and other
metabolites. Magnetic resonance imaging 27 (1):142-145
3. Charlton
RA, McIntyre DJ, Howe FA, Morris RG, Markus HS (2007) The relationship between
white matter brain metabolites and cognition in normal aging: the GENIE study.
Brain research 1164:108-116
4. Tkac
I, Starcuk Z, Choi IY,
Gruetter R. In vivo 1H NMR spectroscopy of rat brain at 1 ms echo time. Magn
Reson Med 1999; 41:649-656.
5.
Gasparovic C, Song T,
Devier D,
Bockholt HJ,
Caprihan A,
Mullins PG,
Posse S,
Jung RE,
Morrison LA.
Use of tissue water as a concentration reference
for proton spectroscopic imaging. Magn. Reson. Med. 2006; 55(6): 1219–1226.
6. Fayed
N, Andres E, Viguera L, Modrego PJ, Garcia-Campayo J (2014) Higher
glutamate+glutamine and reduction of N-acetylaspartate in posterior cingulate
according to age range in patients with cognitive impairment and/or pain.
Academic radiology 21 (9):1211-1217.
7. Duarte
JM, Do KQ, Gruetter R (2014) Longitudinal neurochemical modifications in the
aging mouse brain measured in vivo by 1H magnetic resonance spectroscopy.
Neurobiology of aging 35 (7):1660-1668.