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Original Investigation |

Structural Brain Connectivity as a Genetic Marker for Schizophrenia

Marc M. Bohlken, MSc1; Rachel M. Brouwer, PhD1; René C. W. Mandl, PhD1; Martijn P. Van den Heuvel, PhD1; Anna M. Hedman, PhD1; Marc De Hert, MD, PhD2; Wiepke Cahn, MD, PhD1; René S. Kahn, MD, PhD1; Hilleke E. Hulshoff Pol, PhD1
[+] Author Affiliations
1Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
2Department of Neurosciences, Z.org KU Leuven-University Psychiatric Centre, Katholieke Unibersiteit, Leuven, Belgium
JAMA Psychiatry. 2016;73(1):11-19. doi:10.1001/jamapsychiatry.2015.1925.
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Importance  Schizophrenia is accompanied by a loss of integrity of white matter connections that compose the structural brain network, which is believed to diminish the efficiency of information transfer among brain regions. However, it is unclear to what extent these abnormalities are influenced by the genetic liability for developing the disease.

Objective  To determine whether white matter integrity is associated with the genetic liability for developing schizophrenia.

Design, Setting, and Participants  In 70 individual twins discordant for schizophrenia and 130 matched individual healthy control twins, structural equation modeling was applied to quantify unique contributions of genetic and environmental factors on brain connectivity and disease liability. The data for this study were collected from October 1, 2008, to September 30, 2013. The data analysis was performed between November 1, 2013, and March 30, 2015.

Main Outcome Measures  Structural connectivity and network efficiency were assessed through diffusion-weighted imaging, measuring fractional anisotropy (FA) and streamlines.

Results  The sample included 30 monozygotic twins matched to 72 control participants and 40 dizygotic twins matched to 58 control participants. Lower global FA was significantly correlated with increased schizophrenia liability (phenotypic correlation, −0.25; 95% CI, −0.38 to −0.10; P = .001), with 83.4% explained by common genes. In total, 8.1% of genetic variation in global FA was shared with genetic variance in schizophrenia liability. Local reductions in network connectivity (as defined by FA-weighted local efficiency) of frontal, striatal, and thalamic regions encompassed 85.7% of genetically affected areas. Multivariate genetic modeling revealed that global FA contributed independently of other genetic markers, such as white matter volume and cortical thickness, to schizophrenia liability.

Conclusions and Relevance  Global reductions in white matter integrity in schizophrenia are largely explained by the genetic risk of developing the disease. Network analysis revealed that genetic liability for schizophrenia is primarily associated with reductions in connectivity of frontal and subcortical regions, indicating a loss of integrity along the white matter fibers in these regions. The reported reductions in white matter integrity likely represent a separate and novel genetic vulnerability marker for schizophrenia.

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Figure 1.
Global Fractional Anisotropy (FA) Across Twin Groups

On the y-axis, the normalized FA values are given per study participant. Normalized values were obtained by first performing linear regression for age, handedness, and sex, followed by a normalization of the mean (SD) on the residuals of the regression. On the x-axis, the results are shown per group. In the discordant groups, the affected twin is shown first, and the co-twin is shown second. In the control groups, the order of twin 1 and twin 2 is assigned at random. The final 4 boxplots show the mean connectivity values for patients (mean [SD] FA, 0.428 [0.020]), monozygotic co-twins (mean [SD] FA, 0.431 [0.014]), dizygotic co-twins (mean [SD] FA, 0.442 [0.020]), and control twins (mean [SD] FA, 0.441 [0.018]). The length of the boxplot whiskers is 1.5 times the interquartile range.

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Figure 2.
Structural Fractional Anisotropy (FA)–Weighted Local Efficiency in Schizophrenia

Colored nodes represent gray matter regions that show affected FA‐weighted local efficiency in schizophrenia (false discovery rate corrected) for total phenotypic correlation (rph), genetic factors (rph-a), and environmental factors (rph-e). Colored connections show affected FA in schizophrenia. The size of the nodes is proportional to the number of structural connections (degree). Connections colored in red and yellow are genetically affected in structure (FA). Connections drawn in cyan or purple are affected through environmental factors in structure (FA).

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Figure 3.
Multivariate Genetic Model Incorporating Schizophrenia Liability (SZ), Global Fractional Anisotropy (FA), Cortical Thickness (CT), and White Matter Volume (WMV)

Circles in red hues indicate latent genetic factors (A1 through A4); circles in blue hues indicate latent environmental factors (E1 through E4). Shared environmental effects were only modeled for SZ because the other variables did not show evidence of shared environmental influence in bivariate genetic modeling. Solid arrows indicate significant paths between latent and observed variables; dashed arrows indicate nonsignificant paths. See Table 2 for estimates of phenotypic, genetic, and environmental associations among variables.

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