Tamara Vasilkovska1, Bram Callewaert1, Somaie Salajeghe1, Dorian Pustina2, Longbin Liu2, Mette Skinbjerg2, Celia Dominguez2, Ignacio Munoz-Sanjuan2, Annemie Van der Linden1, and Marleen Verhoye1
1Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium, 2CHDI Foundation, Princeton, NJ, United States
Synopsis
Static FC changes in neurodegeneration can
indicate underlining neural mechanism pathology present in pre-manifest disease
stage. In addition to the spatial FC component, quasi-periodic patterns (QPPs)
implement spatiotemporal information of neural activity, allowing integrated
assessment of possible initial changes in large-scale brain dynamics. We
measured Low Frequency (LF) BOLD changes using rsfMRI in Q175 HD mouse model at 3 and 12 months
of age. Results indicate decreased FC between specific regions in heterozygous
compared to wild-type mice at 12 months. Both at 3 and 12 months, additional
QPPs are present in the heterozygous group, deviating from the wild type group.
Introduction
Resting
state fMRI (rsfMRI) is a method that uses the LF fluctuations of Blood
Oxygenated Level Dependent (BOLD) signal within the brain, indicating changes
in brain activity at rest, due to blood flow and oxygenation changes.
Furthermore, the correlation of these LF BOLD changes between specific neuro-anatomically
defined outlined brain regions, represents the static FC of the putative brain
areas. FC has been shown to be sensitive to discrete pathological processes in
neurodegenerative diseases, such as Huntington’s Disease.1 However, FC does
not provide temporal information of the BOLD changes, leading to the need for a
more sophisticated approach – the Quasi Periodic Patterns (QPPs). The QPPs
represent spatiotemporal patterns of recurring brain dynamics correlated to
neural activity.2 QPPs have been shown to indicate aberrant changes in
large-scale brain networks in an Alzheimer’s disease mouse model.3
Huntington’s disease (HD) is an inherited neurodegenerative
disease, involving mutations in the huntingtin gene (HTT). Abnormal and
increasing (>40) repeat expansion of the CAG (cytosine-adenine-guanine) in HTT causes the mutant variant of HTT (mHTT). The underlying HD mechanisms
are still not clear and require further research. HD animal models allow a more
in-depth investigation of the HD pathogenesis which can potentially facilitate translating
preclinical findings to clinical studies. The Q175 Heterozygous (HET) mouse model
imitates human development of HD. Accumulation of mHTT protein species in this
model increases in size and density as a function of aging.4-6 Furthermore,
this is seen in the striatum and cortex at 4 and 6 months of age, respectively.
In this study, we aim to investigate connectivity changes and differential QPPs
in Q175 mice using dynamic rsfMRI. To the best of our
knowledge, this is the first study in which FC and QPP in an HD rodent model are
assessed. Methods
rsfMRI
data was acquired in 24 3-month and 35 12-month old Q175 HET and wild type (WT)
male mice (two groups at each age, N HET/N WT (age): 12/12 (3M) and 19/16
(12M)) using a 9.4T Biospec MRI scanner with a head cryo-coil. Mice were
anesthetized using a mixture of medetomidine (0.075mg/kg s.c. bolus; 0.15 mg/kg/h
s.c. infusion) and 0.5% isoflurane. Physiological parameters were continuously
monitored and kept stable throughout the procedures. rsfMRI scans were acquired
40min post-bolus for 10min. The rsfMRI was measured using a
T2*-weighted single shot EPI sequence (Matrix dimensions [90x70], TR/TE 500/15ms,
12 horizontal slices of 0.4mm (see Fig.1), 1200 repetitions, pixel dimensions
of (300x300x400) µm3). After the rsfMRI scan, 3D RARE images were acquired,
in order to create a study specific 3D template (TR 2000 ms, TE 42ms, MD [256 128
32], resolution (78 x 156 x 312) µm3). Pre-processing of the data
including: debiasing, realignment, co-registration, normalization and smoothing were performed using SPM12 software (Statistical Parametric Mapping). Static
FC and all QPP-related analyses (hierarchical clustering, phase sorting, global
signal regression, selection and visualization) were performed using MATLAB
2018b. The FC matrices were calculated limiting the included ROIs to those
reported to be affected in HD.7 A two-sample t-test was performed on only
those connections that were found to be significant in at least one of both
groups to evaluate potential FC changes in the HD group compared to WT group
(p-value <0.05, FDR corrected). The spatiotemporal dynamics of BOLD patterns
were extracted with a specific pattern finding algorithm.8 Results
Fig.
2 shows the FC differences between the two groups (HET and WT) at 3 (Fig.2a)
and 12 months (Fig.2b). At 12 months (Fig.2b), the FC profiles indicate
significantly lower connectivity between: CPu(L)-CPu(R), CPu(R)-Piri(R),
Ctx_Cl(R)-M1(R) and Ctx_Cl(R)-S1(R) in HET compared to WT mice, while at 3
months (Fig.2a) there was no significant FC difference between the two groups. A
representative QPP segment from a long sliding window of 20TR (10s) is shown in
Fig.3. Fig.4 shows a representative spatiotemporal QPP segment for both HET and
WT at 3 months, indicating connectivity patterns which differ between the
groups. Fig.5 shows representative QPP
pattern segments at a given time point for 12 months for both HET and WT. We observed
qualitatively different patterns as well as lateralization in the HET compared
to WT group. Discussion and Conclusion
Our results
suggest significant decrease in FC between HET-related regions at 12 months, as
well as differential QPP patterns starting at 3 months and with a more
distinctive QPP pattern alteration between groups at 12 months. The affected regions in both methods suggest
connectivity changes in HET in both the striatum and cortical regions and additionally, in areas linked
to the olfactory processing system.9 Therefore, further histological
assessment is needed to link the changes in functional connectivity and altered
quasi-periodic patterns of brain activity with mHTT deposition. Acknowledgements
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