Background
Schizophrenia is a disorder of brain connectivity and altered neurodevelopmental processes.
Cross-sectional case-control studies in different age groups have suggested that deficits
in cortical thickness in childhood-onset schizophrenia may normalize over time, suggesting
a disorder-related difference in cortical growth trajectories.
Methods
We acquired magnetic resonance imaging scans repeated over several years for each
subject, in a sample of 106 patients with childhood-onset schizophrenia and 102 age-matched
healthy volunteers. Using semiparametric regression, we modeled the effect of schizophrenia
on the growth curve of cortical thickness in ~80,000 locations across the cortex,
in the age range 8 to 30 years. In addition, we derived normative developmental modules
composed of cortical regions with similar maturational trajectories for cortical thickness
in typical brain development.
Results
We found abnormal nonlinear growth processes in prefrontal and temporal areas that
have previously been implicated in schizophrenia, distinguishing for the first time
between cortical areas with age-constant deficits in cortical thickness and areas
whose maturational trajectories are altered in schizophrenia. In addition, we showed
that when the brain is divided into five normative developmental modules, the areas
with abnormal cortical growth overlap significantly only with the cingulo-fronto-temporal
module.
Conclusions
These findings suggest that abnormal cortical development in schizophrenia may be
modularized or constrained by the normal community structure of developmental modules
of the human brain connectome.
Key Words
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Biological PsychiatryAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Brain volumes in schizophrenia: A meta-analysis in over 18 000 subjects.Schizophr Bull. 2013; 39: 1129-1138
- Meta-analysis of gray matter anomalies in schizophrenia: Application of anatomic likelihood estimation and network analysis.Biol Psychiatry. 2008; 64: 774-781
- Heterogeneity of brain structural variation and the structural imaging endophenotypes in schizophrenia.Neuropsychobiology. 2012; 66: 44-49
- Meta-analysis of diffusion tensor imaging studies in schizophrenia.Schizophr Res. 2009; 108: 3-10
- Regional deficits in brain volume in schizophrenia: A meta-analysis of voxel-based morphometry studies.Am J Psychiatry. 2005; 162: 2233-2245
- Cognitive fitness of cost-efficient brain functional networks.Proc Natl Acad Sci U S A. 2009; 106: 11747-11752
- Disrupted small-world networks in schizophrenia.Brain. 2008; 131: 945-961
- Disrupted axonal fiber connectivity in schizophrenia.Biol Psychiatry. 2011; 69: 80-89
- Disturbed grey matter coupling in schizophrenia.Eur Neuropsychopharmacol. 2013; 23: 46-54
- Age of onset of schizophrenia: Perspectives from structural neuroimaging studies.Schizophr Bull. 2011; 37: 504-513
- Neurodevelopmental model of schizophrenia: Update 2012.Mol Psychiatry. 2012; 17: 1228-1238
- Morphological properties of the action-observation cortical network in adolescents with low and high resistance to peer influence.Soc Neurosci. 2008; 3: 303-316
- Why do many psychiatric disorders emerge during adolescence?.Nat Rev Neurosci. 2008; 9: 947-957
- Dynamic mapping of human cortical development during childhood through early adulthood.Proc Natl Acad Sci U S A. 2004; 101: 8174-8179
- Childhood onset schizophrenia: Cortical brain abnormalities as young adults.J Child Psychol Psychiatry. 2006; 47: 1003-1012
- Imaging structural covariance between human brain regions.Nat Rev Neurosci. 2013; 14: 322-336
- Patterns of coordinated anatomical change in human cortical development: A longitudinal neuroimaging study of maturational coupling.Neuron. 2011; 72: 873-884
- The convergence of maturational change and structural covariance in human cortical networks.J Neurosci. 2013; 33: 2889-2899
- Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex.Neuroimage. 2012; 59: 1239-1248
- Semiparametric Regression.Cambridge University Press, New York2003
- Generalized Additive Models.Chapman & Hall, Boca Raton, FL2006
- Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI.Neuroimage. 2006; 31: 993-1003
- Brain size and cortical structure in the adult human brain.Cereb Cortex. 2008; 18: 2181-2191
- Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification.Neuroimage. 2005; 27: 210-221
Wood S, Scheipl F (2012): gamm4: Generalized additive mixed models using mgcv and lme4. R package version 0.1-6. Available at: http://CRAN.R-project.org/package=gamm4. Accessed July 7, 2013.
- Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models.J R Stat Soc Series B Stat Methodol. 2010; 73: 3-36
- Stable and efficient multiple smoothing parameter estimation for generalized additive models.J Am Stat Assoc. 2004; 99: 673-686
- Thin plate regression splines.J R Stat Soc Series B Stat Methodol. 2003; 65: 95-114
- Modelling and smoothing parameter estimation with multiple quadratic penalties.J R Stat Soc Series B Stat Methodol. 2000; 62: 413-428
Reiss P, Chen Y-H, Huang L, Huo L (2012): vows: Voxelwise semiparametrics. R package version 0.2-0. Available at: http://CRAN.R-project.org/package=vows. Accessed July 7, 2013.
Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K (2012): cluster: Cluster Analysis Basics and Extensions. R package version 1.14.3. Available at: http://CRAN.R-project.org/package=cluster. Accessed July 7, 2013.
- A CLUE for CLUster ensembles.J Stat Softw. 2005; 14: 65-72
Hornik K, Bohm W (2012): clue: Cluster Ensembles. R package version 0.3-45. Available at: http://CRAN.R-project.org/package=clue. Accessed July 7, 2013.
- Functional principal component regression and functional partial least squares.J Am Stat Assoc. 2007; 102: 984-996
- Random-effects models for longitudinal data.Biometrics. 1982; 38: 963-974
- On semiparametric regression with O’Sullivan penalized splines.Aust N Z J Stat. 2008; 50: 179-198
- Varying-coefficient models.J R Stat Soc Series B Stat Methodol. 1993; 55: 757-796
- On p-values for smooth components of an extended generalized additive model.Biometrika. 2013; 100: 221-228
- Adaptive linear step-up procedures that control the false discovery rate.Biometrika. 2006; 93: 491-507
- Smoothed functional principal components analysis by choice of norm.Ann Stat. 1996; 24: 1-24
Kaufman L, Rousseeuw P (1987): Clustering by means of medoids. In: Dodge Y, editor. Statistical Data Analysis Based on the L1--Norm and Related Methods. Amsterdam: North Holland, 405–416
- Clustering functional data.J Classification. 2003; 20: 93-114
- Simple models of human brain functional networks.Proc Natl Acad Sci U S A. 2012; 109: 5868-5873
- The anatomical distance of functional connections predicts brain network topology in health and schizophrenia.Cereb Cortex. 2013; 23: 127-138
- Evolution and development of brain networks: From Caenorhabditis elegans to Homo sapiens.Network. 2011; 22: 143-147
- The economy of brain network organization.Nat Rev Neurosci. 2012; 13: 336-349
- Brain development during childhood and adolescence: A longitudinal MRI study.Nat Neurosci. 1999; 2: 861-863
- Maze training in mice induces MRI-detectable brain shape changes specific to the type of learning.Neuroimage. 2011; 54: 2086-2095
- Synapse elimination and plasticity in developing human cerebral cortex.Am J Ment Defic. 1984; 88: 488-496
- How does your cortex grow?.J Neurosci. 2011; 31: 7174-7177
- Neurodevelopmental trajectories of the human cerebral cortex.J Neurosci. 2008; 28: 3586-3594
- When does brain aging accelerate? Dangers of quadratic fits in cross-sectional studies.Neuroimage. 2010; 50: 1376-1383
- Age-related alterations in the modular organization of structural cortical network by using cortical thickness from MRI.Neuroimage. 2011; 56: 235-245
- Revealing modular architecture of human brain structural networks by using cortical thickness from MRI.Cereb Cortex. 2008; 18: 2374-2381
- Schizophrenia as a disorder of developmentally reduced synaptic connectivity.Arch Gen Psychiatry. 2000; 57: 637-648
- Schizophrenia: Caused by a fault in programmed synaptic elimination during adolescence?.J Psychiatr Res. 1982-1983; 17: 319-334
- Development of the prefrontal cortex during adolescence: Insights into vulnerable neural circuits in schizophrenia.Neuropsychopharmacology. 1997; 16: 385-398
- Postnatal development of prefrontal inhibitory circuits and the pathophysiology of cognitive dysfunction in schizophrenia.Ann N Y Acad Sci. 2004; 1021: 64-76
- Expression profiles of schizophrenia susceptibility genes during human prefrontal cortical development.J Psychiatry Neurosci. 2009; 34: 450-458
- Infragranular gene expression disturbances in the prefrontal cortex in schizophrenia: Signature of altered neural development?.Neurobiol Dis. 2010; 37: 738-746
- Consistency and interpretation of changes in millimeter-scale cortical intrinsic curvature across three independent datasets in schizophrenia.Neuroimage. 2012; 63: 611-621
- The Generation R Study: Design and cohort update 2010.Eur J Epidemiol. 2010; 25: 823-841
- Schizophrenia, neuroimaging and connectomics.Neuroimage. 2012; 62: 2296-2314
- Aberrant frontal and temporal complex network structure in schizophrenia: A graph theoretical analysis.J Neurosci. 2010; 30: 15915-15926
- Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling.Neuroimage. 2009; 47: 56-64
- Cortical thickness is influenced by regionally specific genetic factors.Biol Psychiatry. 2010; 67: 493-499
- Hierarchical genetic organization of human cortical surface area.Science. 2012; 335: 1634-1636
- Functional brain development in humans.Nat Rev Neurosci. 2001; 2: 475-483
- Development itself is the key to understanding developmental disorders.Trends Cogn Sci. 1998; 2: 389-398
- Further analysis of the data by Akaike’s information criterion and the finite corrections.Comm Stat Theor Meth. 1978; 7: 13-26
- Massively parallel nonparametric regression, with an application to developmental brain mapping.J Comput Graph Stat. 2014; 23: 232-248
- Nonparametric Regression and Generalized Linear Models.Chapman & Hall, Boca Raton, FL1994
- Neurocognitive deficit in schizophrenia: A quantitative review of the evidence.Neuropsychology. 1998; 12: 426-445
- Cortical brain development in nonpsychotic siblings of patients with childhood-onset schizophrenia.Arch Gen Psychiatry. 2007; 64: 772-780
- Atypical handedness in schizophrenia: Some methodological and theoretical issues.Schizophr Bull. 1999; 25: 63-78
- Handedness, language lateralisation and anatomical asymmetry in schizophrenia: Meta-analysis.Br J Psychiatry. 2001; 178: 344-351
- Handedness in schizophrenia: A quantitative review of evidence.Acta Psychiatr Scand. 2005; 111: 410-419
- Handedness, heritability, neurocognition and brain asymmetry in schizophrenia.Brain. 2010; 133: 3113-3122
Article info
Publication history
Published online: February 24, 2014
Accepted:
February 10,
2014
Received in revised form:
January 17,
2014
Received:
July 14,
2013
Identification
Copyright
© 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
ScienceDirect
Access this article on ScienceDirectLinked Article
- Finding Pieces to the Puzzle of Brain Structure in SchizophreniaBiological PsychiatryVol. 76Issue 6
- PreviewThe neurodevelopmental origins of schizophrenia have been suspected for more than a century, and the last half century of neuroimaging research has further supported the idea that anomalous brain growth trajectories underlie risk for psychotic syndromes. The article by Alexander-Bloch et al. (1) (this issue) marks significant progress in assembling the data necessary to define the healthy trajectories of brain development and how these processes may go awry in people who develop schizophrenia. The article is a technical tour de force, applying sophisticated neuroimaging and statistical methods to map age-associated growth curves and assess their differences between a group of people who have childhood-onset schizophrenia (COS) and a healthy comparison group.
- Full-Text
- Preview
