Developmental changes in multivariate neuroanatomical patterns that predict risk for psychosis in 22q11.2 deletion syndrome

doi:10.1016/j.jpsychires.2010.07.008

Journal of Psychiatric Research

Volume 45, Issue 3, March 2011, Pages 322-331

https://doi.org/10.1016/j.jpsychires.2010.07.008 Get rights and content

Abstract

The primary objective of the current prospective study was to examine developmental patterns of voxel-by-voxel gray and white matter volumes (GMV, WMV, respectively) that would predict psychosis in adolescents with 22q11.2 deletion syndrome (22q11.2DS), the most common known genetic risk factor for schizophrenia. We performed a longitudinal voxel-based morphometry analysis using structural T1 MRI scans from 19 individuals with 22q11.2DS and 18 typically developing individuals. In 22q11.2DS, univariate analysis showed that greater reduction in left dorsal prefrontal cortical (dPFC) GMV over time predicted greater psychotic symptoms at Time2. This dPFC region also showed significantly reduced volumes in 22q11.2DS compared to typically developing individuals at Time1 and 2, greater reduction over time in 22q11.2DS COMT^Met compared to COMT^Val, and greater reduction in those with greater decline in verbal IQ over time. Leave-one-out Multivariate pattern analysis results (MVPA) on the other hand, showed that patterns of GM and WM morphometric changes over time in regions including but not limited to the dPFC predicted risk for psychotic symptoms (94.7–100% accuracy) significantly better than using univariate analysis (63.1%). Additional predictive brain regions included medial PFC and dorsal cingulum. This longitudinal prospective study shows novel evidence of morphometric spatial patterns predicting the development of psychotic symptoms in 22q11.2DS, and further elucidates the abnormal maturational processes in 22q11.2DS. The use of neuroimaging using MVPA may hold promise to predict outcome in a variety of neuropsychiatric disorders.

Introduction

The 22q11.2DS, also known as velocardiofacial syndrome (Shprintzen et al., 1978), is the most common microdeletion syndrome in humans occurring in at least 1–5000 live births (Botto et al., 2003). It has been shown that at least 25% of individuals with 22q11.2DS develop a schizophrenia-like psychosis by young adulthood (Murphy et al., 1999). Being the most common identifiable genetic risk factor for schizophrenia, 22q11.2DS serves as an important model from which to elucidate the path leading from a well defined genetic defect to variation in brain development and eventually to the evolution of psychotic symptoms.

Research has shown links between the development of psychotic symptoms and VIQ decline or catechol-O-methyltransferase (COMT) hemizygosity (Gothelf et al., 2005), but no studies have demonstrated whether neuroanatomical patterns can predict the development of psychotic symptoms in 22q11.2DS. This may be due to the fact that past longitudinal studies have used univariate analysis of more crude volumetric or lobar volume measures (Gothelf et al., 2005) rather than multivariate analysis of voxel-based measures, which could be a more sensitive and powerful measure in detecting subtle regional changes. Indeed, studies have begun to elucidate neuroanatomical patterns that predict disease transition in at-risk mental states of psychosis (Koutsouleris et al., 2009). Therefore, the main purpose of the current study was to identify neuroanatomical patterns that predicted risk of psychotic symptoms with high accuracy using cross-validation support vector machine (SVM) algorithms and to compare that with univariate methods.

Section snippets

Subjects

Time1 and Time2 data included 19 children with 22q11.2DS and 18 typically developing (TD) controls. The presence of the 22q11.2 microdeletion was confirmed in all subjects with 22q11.2DS by fluorescence in situ hybridization (FISH). All controls were screened and were not included in the study if they had a history of major psychiatric disorder or neurological or cognitive impairment. The follow-up interval was 4.9 ± 0.7 for the 22q11.2DS group and 4.9 ± 0.9 years for the controls. The

Between-group differences using univariate analysis

Summaries of baseline (Time1) and follow-up (Time2) brain TTV is presented in Table 1, and results of regional brain volume are presented in Table 3. When repeated measures ANCOVA was performed (total GMV and age as covariates), there was a main effect of diagnostic group, a main effect of time, but no significant interaction (p = 0.01 corrected, Fig. 1a and b). Differences in regional GMV between 22q11.2DS and TD groups were very similar at Time1 and Time2 with the 22q11.2DS group showing

Discussion

In this longitudinal study of 22q11.2DS adolescents, we show that later psychotic symptoms can be predicted by developmental changes in morphometric spatial GMV and WMV patterns with very high accuracy using cross-validated MVPA (94.7 and 100%, respectively), and significantly better than using univariate analysis of the PFC GMV (63.1%). We further show that longitudinal VBM analysis replicates and extends previous findings regarding the developmental neuroanatomical characteristics of

Financial disclosure

None.

Role of funding sources

This study was funded by grants NIMH MH50047-15 (Dr. Reiss), NARSAD Young Investigator Award (Drs. Gothelf and Hoeft), the Child Health Research Program from the Stanford University School of Medicine and NICHD 1K23HD054720-01 (Dr Hoeft). The NIMH, NARSAD and NICHD had no further role in the study design; collection, analysis, and interpretation of data; writing of the report; and decision to submit the paper for publication.

Contributors

Doron Gothelf: author, subject recruitment, data collection, data analysis.

Fumiko Hoeft: author, method development, data analysis.

Takefumi Ueno: author, data analysis.

Lisa Sugiura: data management, data analysis.

Agatha D. Lee & Paul Thompson: method development, data analysis.

Allan Reiss: author, data analysis and oversees the research project.

Conflict of interest

No authors have any conflicts of interest. No authors have any financial ties to any people or organizations that could have influenced this research study.

Acknowledgement

None.

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¹: Shared first authors. Authors contributed equally.

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Developmental changes in multivariate neuroanatomical patterns that predict risk for psychosis in 22q11.2 deletion syndrome

Abstract

Introduction

Section snippets

Subjects

Between-group differences using univariate analysis

Discussion

Financial disclosure

Role of funding sources

Contributors

Conflict of interest

Acknowledgement

Psychiatry Research

Schizophrenia Research

The Journal of the American Academy of Child and Adolescent Psychiatry

Biological Psychiatry

Schizophrenia Research

NeuroImage

Schizophrenia Research

Alterations in midline cortical thickness and gyrification patterns mapped in children with 22q11.2 deletions

Cerebral Cortex

Mapping cortical thickness in children with 22q11.2 deletions

Cerebral Cortex

A population-based study of the 22q11.2 deletion: phenotype, incidence, and contribution to major birth defects in the population

Pediatrics

Relative glucose metabolic rate higher in white matter in patients with schizophrenia

American Journal of Psychiatry

Brain and behaviour in children with 22q11.2 deletion syndrome: a volumetric and voxel-based morphometry MRI study

Brain

Children and adolescents with velocardiofacial syndrome: a volumetric MRI study

American Journal of Psychiatry