Jingli Chen1,2, Yarui Wei1,2, Kangkang Xue1,2, and Jingliang Cheng1,2
1Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, 2Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Magnetic Resonance Imaging, Zhengzhou, China
Synopsis
Keywords: Neurodegeneration, Gray Matter, gray matter volume / early-onset schizophrenia / adult-onset schizophrenia /neurodevelopment / visual perception / visual cognitive
We
aimed to investigate the interaction characteristics of schizophrenia and onset age and its underlying
molecular mechanisms by using T1-weighted high-resolution magnetic resonance
imaging (3DT1) and the JuSpace toolbox. 150 first-episode drug-naïve
schizophrenia and 119 matched normal controls were recruited and underwent 3DT1
scans. Our results show that the two main effects
of factors and interaction effect in gray matter volume and their underlying
molecular mechanisms have varying degrees of specificity changes. Particularly, the abnormality of the visual
perception system and higher visual
cognitive functions in early-onset schizophrenia (EOS) have guiding
significance for the mechanism and treatment of EOS.
Introduction
Early-onset schizophrenia (EOS: onset
after the age of 18) is thought to be clinically and neurobiologically
continuous with adult-onset schizophrenia (AOS: onset 13–18 years),
with a poor outcome and high severity, increased genetic vulnerability, and a 12.3% prevalence1-3. Differences in the age of onset of schizophrenia may
explain the inconsistent findings and the heterogeneity of the disorder itself4, 5. According
to the well-known neurodevelopmental hypothesis, schizophrenia starts early in
the process of brain development and gradually leads to dynamic structural
abnormalities of the brain6.
Therefore, understanding the impact of developmental status on pathological
processes involving brain structures in schizophrenia is crucial to comprehend
the pathophysiology of schizophrenia. Moreover, neurotransmitters are involved
in a variety of developmental processes, including neuronal proliferation,
differentiation, and the process of apoptosis, in addition to their primary
role in regulating synaptic communication7, 8.
And, the
gray matter density on magnetic
resonance imaging (MRI) is an indirect indicator of the intricate
architecture of glia, vasculature, and neurons with dendritic and synaptic
processes9. Previous
studies have generally used longitudinal data on schizophrenia to study the
effects of development on schizophrenia, but data from such studies are
relatively difficult to collect. Our study uses cross-sectional data
in an interactive manner to investigate the effect of the age-onset of
schizophrenia on gray matter volume (GMV) and to
explore the underlying pathophysiological mechanisms in conjunction with
molecular structural abnormalities.Materials and Methods
FES patients (84 AOS
and 66 EOS) and NC (73
adults and 46 adolescents) were included in this study. All participants were
scanned using 3.0 T MRI scanner with 8-channel receiver array head coil
(Discovery MR750, GE, USA). Spatial-3D high-resolution T1-weighted images (3DT1)
were acquired using a brain volume sequence with the following settings: repetition time/echo time =
8.2/3.2 ms, slice thickness = 1 mm, slice gap = 0 mm,
flip angle = 12°, slice number = 1, field of view (FOV) = 25.6 ×
25.6 cm2, number of averages = 1, matrix size = 256 × 256, voxel
size = 1 × 1 ×1 mm3.
Voxel-based
morphometry analyses were preprocessed with the Computational Anatomy Toolbox, a
software extension to the Statistical Parametric Mapping (SPM12). Processing
steps include image evaluation, normalization, segmenting, resampling, and
smoothing. And,
using the JuSpace toolkit (Dukart et al., 2021), we evaluated the spatial
correlation between the GMV difference map (interaction effect, main effects)
and positron emission tomography/single photon computed emission tomography (PET/SPECT)
maps to examine if there was a link between factors-induced alterations in GMV
and neurotransmitter expression. For GMV comparisons, two-way analysis
of variance (ANOVA) was used to examine the main effect of the diagnosis
(schizophrenia vs. controls) and age (adolescent vs. adults) and their
interaction effects between diagnosis and age. Multiple
comparisons were corrected according to the Gaussian random field (GRF) theory
(voxel-wise P < 0.001, cluster-wise P < 0.05, two-tail, and
cluster extent threshold at k > 30). Post
hoc comparisons were used by Mann-Whitney (P < 0.05/2 for main effect
analyses, P < 0.05/4 for interaction effect analyses,
Bonferroni-corrected). Furthermore, a correlation analysis between clinical
measures and significant outcomes between groups was performed by Spearman's
rank correlation.Results
Compared to AOS, EOS
and adult NC had larger GMV in right middle frontal gyrus. Compared to
adolescent NC, EOS and adult NC had smaller GMV in right lingual gyrus, right
fusiform gyrus, and right cerebellum_6 (Figure 1). Disease-induced
GMV reductions were mainly distributed in frontal, parietal, thalamus, visual, motor
cortex, and medial temporal lobe structures (Figure 2.). Age-induced
GMV alterations were mainly distributed in visual and motor cortex (Figure 2). The
changed GMV induced by schizophrenia, age, and their interaction were related
to dopaminergic and serotonergic receptors. Age is also related to glutamate
receptors, and schizophrenia is also associated with (GABAa)ergic and
noradrenergic receptors (Figure 2). Correlation
analysis showed that the GMV reduction of the right MFG in AOS was positively
correlated with the negative score (P = 0.021, rho = 0.251), and
the GMV reduction in the right fusiform gyrus and the right lingual gyrus of
EOS was positively correlated with the CPT_IT score, respectively (P =
0.025, rho = 0.337; P = 0.049, rho = 0.298) (Figure 3).Discussion and conclusion
The current findings suggest that
disruptions in visual perceptual system and abnormalities in higher visual cognitive functions in EOS and their underlying
molecular mechanisms were influenced by developmental status, which may provide
clues for early intervention in EOS.Acknowledgements
The
authors would like to express their gratitude to the individuals who
participated in this study. We also express our gratitude to the technical
staff of the Magnetic Resonance Department of the First Affiliated Hospital of
Zhengzhou University, who helped to acquire images of patients, and the staff
of the Department of Psychiatry of the First Affiliated Hospital of Zhengzhou
University. And, all authors declared no conflict of interest.References
1. Diaz-Caneja
CM, Pina-Camacho L, Rodriguez-Quiroga A, Fraguas D, Parellada M, Arango C.
Predictors of outcome in early-onset psychosis: a systematic review. NPJ
Schizophr 2015;1:14005.
2. Ahn K, An SS, Shugart YY,
Rapoport JL. Common polygenic variation and risk for childhood-onset
schizophrenia. Mol Psychiatry Jan 2016;21(1):94-96.
3. Arango C, Buitelaar JK, Correll
CU, et al. The transition from adolescence to adulthood in patients with schizophrenia:
Challenges, opportunities and recommendations. Eur Neuropsychopharmacol Jun
2022;59:45-55.
4. Zhang C, Wang Q, Ni P, et al.
Differential Cortical Gray Matter Deficits in Adolescent- and Adult-Onset
First-Episode Treatment-Naive Patients with Schizophrenia. Sci Rep Aug
31 2017;7(1):10267.
5. Gogtay N, Vyas NS, Testa R, Wood
SJ, Pantelis C. Age of onset of schizophrenia: perspectives from structural
neuroimaging studies. Schizophr Bull May 2011;37(3):504-513.
6. Rapoport JL, Giedd JN, Gogtay N.
Neurodevelopmental model of schizophrenia: update 2012. Mol Psychiatry Dec
2012;17(12):1228-1238.
7. Xing L, Huttner WB.
Neurotransmitters as Modulators of Neural Progenitor Cell Proliferation During
Mammalian Neocortex Development. Front Cell Dev Biol 2020;8:391.
8. Heather A. Cameron TGH, Ronald
D. G. McKay. Regulation of Neurogenesis by Growth Factors and
Neurotransmitters. Journal of Neurobiology 1998;31.
9. Nitin Gogtay*† JNG, Leslie
Lusk*, Kiralee M. Hayashi‡, Deanna Greenstein*,A. Catherine Vaituzis*, Tom F.
Nugent III*, David H. Herman*, Liv S. Clasen*, Arthur W. Toga‡, Judith L.
Rapoport*, and Paul M. Thompson‡. Dynamic mapping of human cortical development
during childhood through early adulthood. PNAS 2004;101.