Structural Brain Connectivity as a Genetic Marker for Schizophrenia

Abstract

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.

Association between structural brain network efficiency and intelligence increases during adolescence

“…A recent longitudinal study in adolescents between 15 and 19 years, comparable with our second and third wave, also reported both increases and decreases in FA and streamline count during late adolescence, with preferential maturation in hub‐to‐hub connections (Baker et al, ). Our findings are also in alignment with development of white matter volume (Brouwer et al, ; Paus, ), which is consistent with the small but positive association between white matter volume and FA reported in adult twins (Bohlken et al, ). Also, our FA‐weighted findings align with cross‐sectional reports of streamline‐count weighted efficiency of brain networks showing largely positive correlations with age in childhood and adolescence (Dennis et al, ; Hagmann et al, ; Zhao et al, ) while leveling off or showing a negative correlation in adulthood (Dennis et al, ; Gong et al, ; Lim, Han, Uhlhaas, & Kaiser, ; Zhao et al, ).…”

Changes in White Matter Organization in Adolescent Offspring of Schizophrenia Patients

“…This suggests some level of specificity in how the genetic vulnerability for schizophrenia impacts the development of white matter tracts. Indeed, in a discordant twin study genetic overlap between reductions in white matter integrity and schizophrenia liability has been found primarily in frontal and subcortical regions (Bohlken et al, 2016). It may well be that this genetic vulnerability for changes in frontostriatal white matter together with risk alleles impacting dopamine function (Vink et al, 2016a) may contribute to altered FA values in this particular tract.…”

Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth

“…Edges were defined where at least one streamline connected a pair of nodes end-to-end. Edge weights were primarily defined by the average FA along streamlines connecting any pair of nodes [17,30,48] (see Figure 2). In addition to these FA-weighted networks, supplemental analyses evaluated edge weights defined as the streamline count and streamline density using deterministic tractography (see below).…”