Yu Sui1, Pippa Storey1, Hilary Bertisch2, Matthew Lustberg1, Taylor Coats1, Donald Goff3, Alexey Samsonov4, and Mariana Lazar1
1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States, 2Department of Rehabilitation Medicine, New York University School of Medicine, New York, NY, United States, 3Department of Psychiatry, New York University School of Medicine, New York, NY, United States, 4Department of Radiology, University of Wisconsin at Madison, Madison, WI, United States
Synopsis
Myelin dysfunction
has frequently been identified as one of the neural abnormalities in
schizophrenia, yet systematic in vivo
examination of myelin content in patients is lacking. The current study compared
the degree of myelination in schizophrenia patients and comparison healthy
controls. Myelin content was estimated by constructing quantitative whole-brain
maps of macromolecular proton fraction, which is believed to be one of the
biomarkers for myelination in neural tissues. Statistical analysis revealed
that SZ patients were associated with a significant reduction in myelin content
throughout white matter, as well as in several grey matter regions including
cingulate cortex and hippocampus.
Introduction
In recent years,
alterations in brain circuits and abnormalities in brain maturation such as
myelin dysfunction have been often indicated in schizophrenia research [1].
However, most of the myelin-related hypotheses are largely based on results
from animal models and histological studies, while reliable in vivo approaches for myelin measurement
are still being tested. The current study employed a quantitative magnetization
transfer mapping technique (qMT) [2,3,4] to estimate myelin content in both
healthy controls and patients on the schizophrenia disorder spectrum (SZ),
which included schizophrenia and schizoaffective disorder diagnoses.Methods
Fifteen healthy
controls and nine age-matched SZ patients participated in the study. Patients’ diagnosis of a schizophrenia spectrum
disorder and the lack of an Axis I diagnosis in controls was confirmed using
the Diagnostic Interview for Genetic Studies. All participants were scanned on
Siemens Prisma 3T scanner using a three-dimensional gradient echo MT-weighted
sequence with a voxel size of 1.5x1.5x1.5mm and approximately full brain
coverage. One MT-weighted (TR = 29 ms; FA = 10°) and two variable flip angle datasets (TR =
21ms; FA = 4° and 25°) were collected. Off resonance saturation was
achieved by applying a Gaussian pulse with effective saturation FA = 560°, pulse duration =
12.288 ms, and offset frequency = 4 kHz. The total imaging time was around nine
minutes. The images were used to calculate macromolecular proton fraction (MPF)
as previously described [4]. A high-resolution T1-weighted MPRAGE image was
also obtained for each participant to perform brain segmentation using
FreeSurfer. Mean MPF data from regions previously indicated to be involved in
schizophrenia [5] were extracted according to the Destrieux Atlas provided by
the FreeSurfer, which include both white and grey matter regions such as the
corpus callosum, cingulate cortex, dorsolateral prefrontal cortex (dlPFC),
thalamus, and hippocampus. FSL, Matlab, and SPSS were used for ROI data analysis.
Between-group comparisons were performed for demographic characteristics and MPF
values.Results
No significant group
difference was found for demographic features including subjects’ age, gender,
and handedness (Table 1), except for years of education where SZ group had a
slightly lower average compared to healthy controls. For MPF data, myelin
content estimation was predominantly higher in white matter compared to grey
matter across subject groups (Figure 2). More importantly, SZ group showed significantly
decreased myelin content as estimated by MPF values in cingulate cortex (p=.039), hippocampus (p=.019), and overall cerebral white
matter (p=.041) (Figure 2). Discussion
The current study suggest
that SZ is associated with a pervasive reduction in myelin content throughout
white matter, which might interfere with local neuronal signaling and
ultimately disrupt neural communication. This loss of myelin was also found in cingulate
cortex and hippocampus – grey matter structures that are critical in
higher-order cognitive functions including emotion and memory. These results may
provide valuable insight into the specific white and grey matter deficits
related to SZ, and shed light on the developmental trajectory of the disorder given
the distinct time course of myelin maturation. Furthermore, it is also worth
noting that although dysmyelination in schizophrenia has been often suggested
by diffusion imaging studies [1], diffusion imaging in itself only offers an
indirect assessment of myelination that cannot distinguish among
dysmyelination, axonal loss, or combined pathologies [6]. Previous studies have
also employed magnetization transfer ratio (MTR), a semi-quantitative approach,
to estimate myelination with mixed
results [7,8], likely due to the lack of specificity of MTR to myelin and its
dependence on various additional parameters including tissue T1 and
B1 excitation field. Here we used a more direct approach of myelin
estimation using a novel, quantitative, fast processing method [4] based on
single point MPF mapping methodology [2]. Although MPF measurements may be
affected by other factors, such as inflammation [9], the magnitude of observed
between group differences here suggest that these differences are likely to be largely
reflective of changes in myelin content. Future work is needed to integrate qMT and diffusion imaging, and
further discriminate between myelin deficits from dysmyelination or axonal
loss.Conclusion
The current study employed
a direct, quantitative approach of in vivo
myelin estimation, supporting that white and gray matter abnormalities in SZ
are likely due, at least in part, to myelin deficits. This improved accuracy in
characterizing myelin loss in patients may potentially encourage more refined
categorization of schizophrenia patients, which may lead to more specific
therapeutic approaches for the disorder.Acknowledgements
This study was funded by National Institute of Mental HealthReferences
1. Uranova, N. A., Vostrikov,
V. M., Orlovskaya, D. D., & Rachmanova, V. I. (2004). Oligodendroglial
density in the prefrontal cortex in schizophrenia and mood disorders: a study
from the Stanley Neuropathology Consortium. Schizophrenia research, 67(2), 269-275.
2. Yarnykh, V. L. (2012). Fast macromolecular
proton fraction mapping from a single off‐resonance
magnetization transfer measurement. Magnetic resonance in medicine, 68(1),
166-178.
3. Mossahebi, P., Yarnykh, V. L., &
Samsonov, A. (2014). Analysis and correction of biases in cross‐relaxation MRI due to biexponential longitudinal
relaxation. Magnetic resonance in medicine, 71(2),
830-838.
4. Samsonov, A. A., Mossahebi, P., Anderson,
A., Velikina, J. V., Johnson, K. M., Johnson, S. C., Fleming, J. O., & Field,
A. S. (2014). High Resolution, Motion Corrected Mapping of Macromolecular
Proton Fraction (MPF). Clinically Acceptable Time Using 3D Undersampled
Radials. In Proc of ISMRM (p. 3337).
5. Takahashi, N., Sakurai,
T., Davis, K. L., & Buxbaum, J. D. (2011). Linking oligodendrocyte and
myelin dysfunction to neurocircuitry abnormalities in schizophrenia. Progress in Neurobiology, 93(1),
13–24. http://doi.org/10.1016/j.pneurobio.2010.09.004
6. Kubicki, M., McCarley, R., Westin, C. F.,
Park, H. J., Maier, S., Kikinis, R., ... & Shenton, M. E. (2007). A review
of diffusion tensor imaging studies in schizophrenia. Journal of
psychiatric research, 41(1), 15-30.
7. De Weijer, A. D., Mandl, R. C. W., Diederen,
K. M. J., Neggers, S. F. W., Kahn, R. S., Pol, H. H., & Sommer, I. E. C.
(2011). Microstructural alterations of the arcuate fasciculus in schizophrenia
patients with frequent auditory verbal hallucinations. Schizophrenia
research, 130(1), 68-77.
8. Palaniyappan, L., Al-Radaideh, A., Mougin,
O., Gowland, P., & Liddle, P. F. (2013). Combined white matter imaging
suggests myelination defects in visual processing regions in schizophrenia. Neuropsychopharmacology, 38(9),
1808-1815.
9. Harrison, N. A., Cooper, E., Dowell, N. G.,
Keramida, G., Voon, V., Critchley, H. D., & Cercignani, M. (2015).
Quantitative magnetization transfer imaging as a biomarker for effects of
systemic inflammation on the brain. Biological psychiatry, 78(1),
49-57.