Xia Wei1, Chunyan Luo1, Qiannan Zhao1, and Su Lui1
1Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University., Chengdu, China
Synopsis
Keywords: Psychiatric Disorders, Brain Connectivity
Cerebellar dysfunction appears to be a
robust phenomenon in schizophrenia, and stimulation targeted at cerebellum can
alleviate some symptoms. However, the causal information flow and longitudinal
change of cerebrum-cerebellar connectivity were unclear, limiting the choice of
precise stimulation strategies. Using Granger causality analysis, we found
decreased excitatory inflow and increased inhibitory outflow were located on
different cerebellar functional systems in first-episode schizophrenia and
these gradually returned to normal in the context of clinical improvement with
ongoing antipsychotic treatment. Our work potentially provides new information
to facilitate precision medicine targeted at cerebellum.
Introduction
Disrupted cerebellum-cerebral communication has
been proposed resulting in psychotic symptoms and cognitive deficits, which is theorized
as the “cognitive dysmetria” hypothesis[1].
To date, some functional connectivity studies repeatedly showed failures of
cerebellum-cerebral communication on first-episode patients [2–7],
chronic patients[8–11],
and individuals at clinical or genetic risk of schizophrenia[2,5,11–14].
However, the cerebellar causal information inflow and outflow remain unclear.
Moreover, cerebellar subunits exhibit diverse functional connectivity with
cerebrum[15].
Therefore, in this study, we aimed to identify regional cerebellar causal
effect disruptions in first-episode medication-naive schizophrenia and
longitudinal changes with undergoing antipsychotic treatment.Methods
Subjects:
The study included baseline clinical
and neuroimaging data acquired from 180 first-episode patients (79males, mean
age=24.2) and 161 demographically matched healthy controls (81males, mean
age=25.4). The Structured Clinical Interview of DSM-IV was applied for the diagnosis
of schizophrenia. The disease duration for all patients was less than 5 years.
54 of these patients followed up at one-year and 29 at two-year time points.
During follow-ups, symptom severities were evaluated by the Positive and
Negative Symptom Scale (PANSS) at each assessment point.
Imaging
acquisition and preprocessing:
Data for all subjects at all time
points were acquired on a 3T GE Signa EXCITE scanner located at the West China
Hospital, Sichuan University. DPARSF (http://www.restfmri.net) 16
and SPM12 (http://www.fil.ion.ucl.ac.uk/spm) toolkits were used for MRI data
pre-processing, involving removal of ten volumes, slice time correction,
realignment, segmentation, normalization to the MNI space, and spatial
smoothing at 4-mm FWHM. The images were further corrected for white matter and
cerebrospinal fluid signals, and 24 head-motion parameters, and temporally
filtered at 0.01–0.1 Hz. The global signal was not removed in the present
study.
Granger
causality analysis (GCA): The
bivariate coefficient-based, first-order GCA was performed using the REST
(http://www.restfmri.net) software package17,18.
Each of the nine cerebellar systems was examined by whole-brain-to-seed and
seed-to-whole-brain analyses. The whole-brain-to-seed analysis was used to
estimate the driving effect (excitatory or inhibitory) from the other voxels of
the whole brain to the seed (y2x map), whereas the seed-to-whole-brain analysis
was applied to estimate the feedback effect (excitatory or inhibitory) from the
seed to other voxels of the whole brain (x2y map). The y2x maps and x2y maps
were further z-transformed.
Statistical analysis:
Two-sample t-tests were applied to determine the
causal connectivity disruption in untreated first-episode schizophrenia
patients compared to healthy controls. To improve the statistical significance
of the final result, a one-sample t-test for y2x maps of each cerebellar system
was performed for both groups to determine regions which significantly
different from zero (P < 0.05, FDR corrected). After false discovery rate
(FDR) correction, nine “causal effect masks” were generated by integrating the
paired result of the one-sample t-test of the two groups. Under each “causal
effect mask”, the corresponding y2x maps of two groups were subjected to a
two-sample t-test, followed by another FDR correction (P < 0.05, FDR
corrected). The analysis process for the x2y maps was done the same as above.
Further, the paired t-test between baseline and follow-up (one-year or
two-year) GCA values of each region of interest was performed by using the
Statistical Package for Social Sciences (SPSS, version 26.0). Finally, the
correlations between the GCA value of each ROI and the PANSS scores were
calculated for the patient group. The GCA value of each ROI at follow-up minus
baseline was ΔGCA value. PANSS score of each domain at follow-up minus baseline
were ΔPANSS score. The same linear regression analysis was used to test the
associations between the ΔGCA value and ΔPANSS score.Results
We observed decreased excitatory inflow from
cerebral occipital, temporal, parietal lobes, and putamen to cerebellar default
and language systems, whereas increased inhibitory outflow from cerebellar
attention and cingulo-opercular systems to cerebral frontal, parietal lobes in
untreated first-episode schizophrenia patients compared to healthy controls
(Figure 1). At follow-up, all the causal effect inflow to cerebellum was
increased and outflow from cerebellum was decreased with ongoing antipsychotic
treatment, to be specific, the information from left middle occipital gyrus
inflow to cerebellar default and language systems, from the cerebellar
cingulo-opercular system outflow to left angular, from right middle temporal
gyrus (MTG) inflow to cerebellar default system was most significantly restored
to a normal level. The excitatory effect from the right MTG to cerebellar
default system increase was related to the PANSS-total, PANSS-positive,
PANSS-general remission, and the inhibitory effect from cerebellar
cingulo-opercular system to right the opercular part of the right inferior
frontal gyrus decrease was related the PANSS-positive remission (Figure 2). Conclusion
In sum, we found a breakdown of the
cerebellum-cerebral connectivity during the acute phase of schizophrenia which
was normalized in the context of clinical improvement, and different cerebellar
systems express different causal effect disruption, suggesting that more
targeted treatment strategies should be taken for different cerebellar systems.Acknowledgements
We thank all participants for their
involvement in this study.References
1 Andreasen NC, Paradiso S,
O'Leary DS. "Cognitive dysmetria" as an integrative theory of
schizophrenia: a dysfunction in cortical-subcortical-cerebellar circuitry?
Schizophr Bull. 1998;24(2):203-218.
2 Bang M, Park H-J, Pae C, et
al. Aberrant cerebro-cerebellar functional connectivity and minimal
self-disturbance in individuals at ultra-high risk for psychosis and with
first-episode schizophrenia. Schizophrenia
Research. 2018;202:138-140.
3 Guo W, Zhang F, Liu F, et al.
Cerebellar abnormalities in first-episode, drug-naive schizophrenia at rest.
Psychiatry Res Neuroimaging.
2018;276:73-79.
4 Lee K-H, Oh H, Suh J-HS, et
al. Functional and Structural Connectivity of the Cerebellar Nuclei With the
Striatum and Cerebral Cortex in First-Episode Psychosis. J Neuropsychiatry Clin Neurosci.
2019;31(2):143-151.
5 Li Z, Huang J, Hung KSY, et
al. Cerebellar hypoactivation is associated with impaired sensory integration
in schizophrenia. J Abnorm Psychol.
2021;130(1):102-111.
6 Park SH, Kim T, Ha M, et al.
Intrinsic cerebellar functional connectivity of social cognition and theory of
mind in first-episode psychosis patients. NPJ Schizophr. 2021;7(1):59.
7 Xie YJ, Xi YB, Cui L-B, et al.
Functional connectivity of cerebellar dentate nucleus and cognitive
impairments in patients with drug-naive and first-episode schizophrenia. Psychiatry Res. 2021;300:113937.
8 Clark SV, Tannahill A, Calhoun
VD, Bernard JA, Bustillo J, Turner JA. Weaker Cerebellocortical Connectivity
Within Sensorimotor and Executive Networks in Schizophrenia Compared to
Healthy Controls: Relationships with Processing Speed. Brain Connect. 2020;10(9):490-503.
9 He H, Luo C, Luo Y, et al.
Reduction in gray matter of cerebellum in schizophrenia and its influence on
static and dynamic connectivity. Hum
Brain Mapp. 2019;40(2):517-528.
10 Shinn AK, Baker JT,
Lewandowski KE, Öngür D, Cohen BM. Aberrant cerebellar connectivity in motor
and association networks in schizophrenia. Front Hum Neurosci. 2015;9.
11 Wang H, Guo W, Liu F, et al.
Patients with first-episode, drug-naive schizophrenia and subjects at
ultra-high risk of psychosis shared increased cerebellar-default mode network
connectivity at rest. Scientific
Reports. 2016;6:26124.
12 Bernard JA, Dean DJ, Kent JS,
et al. Cerebellar networks in individuals at ultra high-risk of psychosis:
impact on postural sway and symptom severity. Hum Brain Mapp. 2014;35(8):4064-4078.
13 Cao H, Chén OY, Chung Y, et
al. Cerebello-thalamo-cortical hyperconnectivity as a state-independent
functional neural signature for psychosis prediction and characterization.
Nature Communications.
2018;9(1):3836.
14 Cao H, Wei X, Hu N, et al.
Cerebello-Thalamo-Cortical Hyperconnectivity Classifies Patients and Predicts
Long-Term Treatment Outcome in First-Episode Schizophrenia. Schizophr Bull. 2021;89(9):S83-S83.
15 Ji JL, Diehl C, Schleifer C,
et al. Schizophrenia Exhibits Bi-directional Brain-Wide Alterations in
Cortico-Striato-Cerebellar Circuits. Cerebral
Cortex (New York, N.Y. : 1991). 2019;29(11):4463-4487.
16 Chao-Gan Y, Yu-Feng Z. DPARSF:
A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.
Frontiers In Systems Neuroscience.
2010;4:13.
17 Zang Z-X, Yan C-G, Dong Z-Y,
Huang J, Zang Y-F. Granger causality analysis implementation on MATLAB: A
graphic user interface toolkit for fMRI data processing. Journal of Neuroscience Methods.
2012;203(2):418-426.
18 Song X-W, Dong Z-Y, Long X-Y,
et al. REST: a toolkit for resting-state functional magnetic resonance imaging
data processing. PLoS One.
2011;6(9):e25031.