The genetic and environmental determinants of the association between brain abnormalities and schizophrenia: the schizophrenia twins and relatives consortium.

University Medical Center Utrecht, Department of Psychiatry, Division of Neuroscience, Rudolf Magnus Institute, Utrecht, The Netherlands.
Biological psychiatry (Impact Factor: 8.93). 02/2012; 71(10):915-21. DOI: 10.1016/j.biopsych.2012.01.010
Source: PubMed

ABSTRACT Structural brain abnormalities are consistently found in schizophrenia (Sz) and have been associated with the familial risk for the disorder. We aim to define the relative contributions of genetic and nongenetic factors to the association between structural brain abnormalities and Sz in a uniquely powered cohort (Schizophrenia Twins and Relatives consortium).
An international multicenter magnetic resonance imaging collaboration was set up to pool magnetic resonance imaging scans from twin pairs in Utrecht (The Netherlands), Helsinki (Finland), London (United Kingdom), and Jena (Germany). A sample of 684 subjects took part, consisting of monozygotic twins (n = 410, with 51 patients from concordant and 52 from discordant pairs) and dizygotic twins (n = 274, with 39 patients from discordant pairs). The additive genetic, common, and unique environmental contributions to the association between brain volumes and risk for Sz were estimated by structural equation modeling.
The heritabilities of most brain volumes were significant and ranged between 52% (temporal cortical gray matter) and 76% (cerebrum). Heritability of cerebral gray matter did not reach significance (34%). Significant phenotypic correlations were found between Sz and reduced volumes of the cerebrum (-.22 [-.30/-.14]) and white matter (-.17 [-.25/-.09]) and increased volume of the third ventricle (.18 [.08/.28]). These were predominantly due to overlapping genetic effects (77%, 94%, and 83%, respectively).
Some of the genes that transmit the risk for Sz also influence cerebral (white matter) volume.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The micro RNA 137 (miR-137) variant rs1625579 has been identified as a genome-wide significant risk variant for schizophrenia. miR-137 has an established role in neurodevelopment and may mediate cognitive dysfunction in schizophrenia. This role of miR-137 may be related to changes in brain morphology for risk-related genotypes; however this has not yet been delineated. Here we considered whether rs1625579 genotype was predictive of indices of brain structure in patients with schizophrenia and healthy controls. Structural magnetic resonance imaging (sMRI) data (i.e. 3T T1-TFE or 1.5T T1-MPRAGE) were acquired from 150 healthy controls and 163 schizophrenic patients. Two volumetric analyses that considered the impact of miR-137/rs1625579 genotype were carried out on sMRI data. In the first analysis, voxel based morphometry was employed to consider genotype-related variability in local grey and white matter across the entire brain volume. Our secondary analysis utilized the FIRST protocol in FSL to consider the volume of subcortical structures (i.e. bilateral accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus). Several brain regions in both analyses demonstrated the expected main effect of participant group (i.e. schizophrenics < controls), yet there were no regions where we observed an impact of rs1635579 genotype on brain volume. Our analyses suggest that the mechanism by which miR-137 confers risk for schizophrenia and impacts upon cognitive function may not be mediated by changes in local brain volume. However, it remains to be determined whether or not alternative measures of brain structure are related to these functions of miR-137. © 2014 Wiley Periodicals, Inc.
    American Journal of Medical Genetics Part B Neuropsychiatric Genetics 07/2014; · 3.27 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Schizophrenia has been conceptualized as a disorder of brain connectivity. Recent studies suggest that brain connectivity may be disproportionally impaired among the so-called rich club. This small core of densely interconnected hub regions has been hypothesized to form an important infrastructure for global brain communication and integration of information across different systems of the brain. Given the heritable nature of the illness, we hypothesized that connectivity disturbances, including abnormal rich club connectivity, may be related to familial vulnerability for schizophrenia. To test this hypothesis, both schizophrenia patients and unaffected siblings of patients were investigated. Rich club organization was examined in networks derived from diffusion-weighted imaging in 40 schizophrenia patients, 54 unaffected siblings of patients, and 51 healthy control subjects. Connectivity between rich club hubs was differentially reduced across groups (P = .014), such that it was highest in controls, intermediate in siblings (7.9% reduced relative to controls), and lowest in patients (19.6% reduced compared to controls). Furthermore, in patients, lower levels of rich club connectivity were found to be related to longer duration of illness and worse overall functioning. Together, these findings suggest that impaired rich club connectivity is related to familial, possibly reflecting genetic, vulnerability for schizophrenia. Our findings support a central role for abnormal rich club organization in the etiology of schizophrenia.
    Schizophrenia Bulletin 12/2013; · 8.61 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Endophenotypes are measurable biomarkers that are correlated with an illness, at least in part, because of shared underlying genetic influences. Endophenotypes may improve our power to detect genes influencing risk of illness by being genetically simpler, closer to the level of gene action, and with larger genetic effect sizes or by providing added statistical power through their ability to quantitatively rank people within diagnostic categories. Furthermore, they also provide insight into the mechanisms underlying illness and will be valuable in developing biologically-based nosologies, through efforts such as RDoC, that seek to explain both the heterogeneity within current diagnostic categories and the overlapping clinical features between them. While neuroimaging, electrophysiological, and cognitive measures are currently most used in psychiatric genetic studies, researchers currently are attempting to identify candidate endophenotypes that are less genetically complex and potentially closer to the level of gene action, such as transcriptomic and proteomic phenotypes. Sifting through tens of thousands of such measures requires automated, high-throughput ways of assessing, and ranking potential endophenotypes, such as the Endophenotype Ranking Value. However, despite the potential utility of endophenotypes for gene characterization and discovery, there is considerable resistance to endophenotypic approaches in psychiatry. In this review, we address and clarify some of the common issues associated with the usage of endophenotypes in the psychiatric genetics community. © 2014 Wiley Periodicals, Inc.
    American Journal of Medical Genetics Part B Neuropsychiatric Genetics 01/2014; · 3.27 Impact Factor

Full-text (2 Sources)

Available from
May 31, 2014