Faye McKenna1,2, Laura Miles1, Jeffrey Donaldson1, F. Xavier Castellanos3, Donald Goff3, and Mariana Lazar1
1Radiology, Center for Biomedical Imaging, New York, NY, United States, 2Sackler Institute of Graduate Biomedical Sciences, New York, NY, United States, 3Psychiatry, New York University School of Medicine, New York, NY, United States
Synopsis
In this study, we employed diffusion kurtosis imaging (DKI) to
test for differences in gray matter (GM) microstructure in schizophrenia (SZ) and autism
spectrum disorder (ASD). Significantly increased metrics of DKI were
found in SZ compared to HC participants, while significantly decreased metrics
of DKI were found in ASD compared to HC in the temporal lobe and sub-lobar temporal regions of interest (ROIs).
In
vivo DKI metrics appear to be sensitive to
GM microstructural pathology in SZ and ASD and may provide new information on the neural underpinnings of these disorders.
Background
Prior histological post-mortem studies have
shown gray matter (GM) microstructural abnormalities in the temporal lobe (TL)
to be a pathological feature of both schizophrenia (SZ) and autism spectrum
disorder (ASD).1–3 Despite
offering a unique view of microstructural integrity, histological studies are
often restricted to small sample sizes and isolated brain regions, and may be
confounded by damage to the tissue caused by the fixation process. Evaluation
of microstructure in vivo may thus provide essential means to circumvent these
limitations. However, examination of
gray matter microstructure has remained to date scarce due to the relative lack
of non-invasive methods to assess it.
The aim of this work is to evaluate the feasibility of employing diffusional
kurtosis imaging (DKI) to describe gray matter abnormalities in schizophrenia
and autism. DKI is an extension of DTI
that accounts for non-Gaussian water diffusion contributions to the diffusion
MRI (dMRI) signal and provides several
kurtosis indices that reflect tissue microstructural complexity.4 Examining
microscopic GM changes across SZ and ASD may help build a more comprehensive
model of these diseases and lead to a better understanding of how DKI indexes
tissue cytoarchitecture.Methods
DKI data was acquired in two data sets: 17 SZ patients and 18 matched healthy
comparison controls (HC) (right-handed males, 30-55 years old), and 16 ASD
patients and 17 matched HC (males, 18-25). Mean (MK), axial (AK), radial (RK)
kurtosis and mean diffusivity (MD) metrics were calculated for the temporal
lobe and 18 sub-lobar regions of interest (ROIs) delineated by the Desikan-Killiany
atlas.5 Analyses used
independent-samples t-test to compare diffusion metrics (MK, RK, AK and MD)
between patients and HCs in the two data sets in each ROI. The
Benjamini-Hochberg (HB) procedure was employed in each analysis to correct for
multiple comparisons and decrease the false discovery (FDR) rate.6 Differences were considered
significant for p<0.05 HB FDR corrected and at trend level for p<0.10 HB
FDR corrected.Results
Increases were found in
MK, RK, AK and MD in SZ compared to HC in the whole temporal lobe and
sub-temporal ROIs: banks of the superior temporal sulcus (bankssts), entorhinal
cortex, fusiform and parahippocampal gyri, inferior and middle temporal gyri,
and temporal pole ROIs (Figure 1-2). Decreases were found in MK, RK and MD in
ASD compared to HC in the whole temporal lobe and sub-temporal ROIs: bankssts,
fusiform, parahippocampal, inferior temporal, middle temporal and superior
temporal gyri, transverse temporal cortex, and temporal pole ROIs (Figure 1;
Figure 3).Discussion
Anatomical T1-weighted MRI studies have
documented macroscale GM volume loss and cortical thinning in the TL in SZ with
both increase and decrease reported in ASD.7,8 Results presented here suggest that DKI may be
sensitive to disease-specific changes in GM tissue microstructure and can be
used to create distinct pathology profiles of each disease. The increased
kurtosis in SZ may be due to a more restrictive microstructural arrangement
(increased microglia and cell packing, iron and protein deposits noted in GM ex vivo), while decreased kurtosis in
ASD may reflect abnormalities that create a less restrictive microstructural
environment (decreased neuronal density and size, astrogliosis demonstrated in
GM ex vivo). 1–3,9–11Conclusion
In
vivo DKI metrics appear to be sensitive to GM microstructural
pathology in SZ and ASD and may provide useful biomarkers of abnormal cortical
structure and function in psychiatric and neurological disorders.Acknowledgements
This
work was supported by the National Institute of Mental Health awards R21 MH085228, R01 MH108962 and R03-MH076180 . We greatly thank all of our participants for
their help with this study and Researchmatch for supporting our recruitment
efforts.References
1. Van Kesteren,
C. F. M. G. et al. Immune involvement in the pathogenesis of
schizophrenia: A meta-analysis on postmortem brain studies. Transl.
Psychiatry 7, (2017).
2. Van Kooten, I.
A. J. et al. Neurons in the fusiform gyrus are fewer and smaller in
autism. Brain 131, 987–999 (2008).
3. Casanova, M.
F. The neuropathology of autism. in The Molecular Basis of Autism
153–171 (2015). doi:10.1007/978-1-4939-2190-4_8
4. Jensen, J. H.
& Helpern, J. A. MRI quantification of non-Gaussian water diffusion by
kurtosis analysis. NMR in Biomedicine 23, 698–710 (2010).
5. Desikan, R. S.
et al. An automated labeling system for subdividing the human cerebral
cortex on MRI scans into gyral based regions of interest. Neuroimage 31,
968–980 (2006).
6. Hochberg, B.
Controlling the False Discovery Rate: a Practical and Powerful Approach to
Multiple Testing. J. R. Stat. Soc. 57, 289–300 (1995).
7. Zipursky, R.
B., Lim, K. O., Sullivan, E. V., Brown, B. W. & Pfefferbaum, A. Widespread
Cerebral Gray Matter Volume Deficits in Schizophrenia. Arch. Gen. Psychiatry
49, 195–205 (1992).
8. Greimel, E. et
al. Changes in grey matter development in autism spectrum disorder. Brain
Struct. Funct. 218, 929–942 (2013).
9. Gong, N. J., Wong,
C. S., Hui, E. S., Chan, C. C. & Leung, L. M. Hemisphere, gender and
age-related effects on iron deposition in deep gray matter revealed by
quantitative susceptibility mapping. NMR Biomed. 28, 1267–1274
(2015).
10. Sokolov, B. P.,
Tcherepanov, A. A., Haroutunian, V. & Davis, K. L. Levels of mRNAs encoding
synaptic vesicle and synaptic plasma membrane proteins in the temporal cortex
of elderly schizophrenic patients. Biol. Psychiatry 48, 184–196
(2000).
11. Cho, K. I. K. et
al. Microstructural Changes in Higher-Order Nuclei of the Thalamus in
Patients With First-Episode Psychosis. Biological Psychiatry (2018).
doi:10.1016/j.biopsych.2018.05.019