Yuhei Takado1, Hiroyuki Takuwa1, Urushihata Takuya1, Manami Takahashi1, Maiko Ono1, Jun Maeda1, Masafumi Shimojo1, Nobuhiro Nitta2, Sayaka Shibata2, Ichio Aoki2, Naruhiko Sahara1, Tetsuya Suhara1, and Makoto Higuchi1
1Department of Functional Brain Imaging Research, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan, 2Department of Molecular Imaging and Theranostics, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
Synopsis
Amyloid beta protein and tau proteins are two major
hallmarks of the pathology of Alzheimer’s disease. To elucidate the
relationship between brain metabolites and tau protein, we performed H-MRS and
tau PET imaging of tauopathy mouse model (rTg4510). Five rTg4510 mice and five
wild-type mice were scanned at the age of 4 and 6 months by H-MRS and tau PET.
We demonstrated that the amount of tau had negative correlations with the
amount of taurine, tNAA, and glutamate, indicating that tau might reduce those
metabolites selectively and caused neural impairment.
INTRODUCTION
Amyloid beta protein (Aβ) and tau proteins are two major
hallmarks of the pathology of Alzheimer’s disease (AD). To elucidate the impact
of these abnormal proteins on brain metabolism is important for finding
therapeutic strategies since brain metabolism is strongly involved in brain
health. H-MRS is a valuable technique which can speculate the brain conditions
via brain metabolites. Since abnormal proteins can be visualized by positron
emission tomography (PET) imaging (1), it is possible to investigate the
relationship between abnormal proteins and brain metabolites by multimodal
imaging. While Aβ load detected by PET is reported to be correlated with the
amount of myoinositol (2), which is believed to be a potential glial marker of
AD, the association of tau with brain metabolites has yet to be clarified. In
this study, to elucidate the relationship between brain metabolites and tau, we
performed H-MRS and tau PET imaging of a tauopathy mouse model (rTg4510) (3). METHODS
Five rTg4510 mice and five wild-type mice
anesthetized with 1–2% isoflurane were scanned at the age of 4 and 6 months by
H-MRS as well as tau PET which enables to detect tau in vivo. H-MRS experiments
were done using a 7 T spectrometer (Biospec, AVANCE-III, Bruker Biospin) with a
dual-channel phased-array cooled surface coil for transmission and reception
(cryoprobe©, Bruker Biospin) using a PRESS sequence (TR/TE = 4000/20 ms).
Volumes of interest (VOIs) were localized in frontal cortex as well as
hippocampus. A total of 256 acquisitions for frontal cortex and 296
acquisitions for hippocampus were collected. Using water signal as a reference,
absolute metabolite concentrations were calculated using LCModel. PET scans
were performed using a microPET Focus 220 animal scanner (Siemens Medical
Solutions) immediately after intravenous injection of tau PET tracer. Summation
images from 30 to 60 min after the tracer injection were generated with maximum
a posteriori reconstruction, and dynamic images were reconstructed with
filtered backprojection using a 0.5-mm Hanning’s filter. VOIs were placed on
hippocampus, brain cortex, and cerebellum (as a reference), using PMOD image
analysis software (PMOD Technologies). To investigate the correlation between
tau load detected by PET and brain metabolites (tNAA, myoinositol, glutamate
(Glu), glutamine (Gln), GABA, and taurine), Pearson’s rank correlation tests
were performed. A t-test was used to compare the concentration of taurine in
the VOIs of hippocampus and frontal cortex between the rTg4510 mice and
wild-type mice. Immunostaining was performed on scanned mice by using AT8 and
NeuN for tau staining and neuron staining, respectively.RESULTS
Typical spectra and tau PET images of rTg4510 and wild-type mice at
the age of 6 months were shown in the Fig. 1. The correlations between
metabolites and tau load were shown in the Fig. 2. While tau load detected by
tau PET had correlations with the concentrations of taurine (r = −0.706), tNAA
(r = −0.58), and Glu (r = −0.52), there were no significant correlations with
myoinositol, Gln, and GABA (Fig. 2). There was a significant difference in
taurine concentrations (Fig. 3; p < 0.05), which had the strongest
correlation with tau load among the metabolites, between rTg4510 and wild-type
mice at the age of 6 months. Immunostaining by AT8 showed abundant tau in the
cortex and hippocampus of rTg4510 mice (Fig. 4). NeuN showed that neural loss
was evident in the rTg4510 mouse (Fig. 4).DISCUSSION
This is the first study which investigated the association between
tau load detected by PET and brain metabolites using tauopathy model mice in
vivo. Among brain metabolites, taurine had the strongest negative correlation
with tau accumulation. It is reported that taurine has a therapeutic effect on
amyloid precursor protein knockout (APP KO) mice (4). To our knowledge, the
association between taurine and tau has not been reported yet. The amount of
tau load also had negative correlations with tNAA as well as Glu, indicating
that tau might reduce those metabolites selectively and caused neural
impairment.CONCLUSION
We demonstrated that the amount of tau had negative correlations with the amount of taurine, tNAA, and glutamate, indicating that tau might reduce those metabolites selectively and caused neural impairment. Multimodal
imaging could be valuable for elucidating the new pathophysiology of the
disease.Acknowledgements
No acknowledgement found.References
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