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.
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.
Authors: Marc M Bohlken; Rachel M Brouwer; René C W Mandl; René S Kahn; Hilleke E Hulshoff Pol Journal: Schizophr Bull Date: 2016-04-07 Impact factor: 9.306
Authors: Marinka M G Koenis; Rachel M Brouwer; Suzanne C Swagerman; Inge L C van Soelen; Dorret I Boomsma; Hilleke E Hulshoff Pol Journal: Hum Brain Mapp Date: 2017-11-14 Impact factor: 5.038
Authors: Syed Ali Ahsan; Kassem Chendeb; Robert G Briggs; Luke R Fletcher; Ryan G Jones; Arpan R Chakraborty; Cameron E Nix; Christina C Jacobs; Alison M Lack; Daniel T Griffin; Charles Teo; Michael Edward Sughrue Journal: J Neurooncol Date: 2020-01-01 Impact factor: 4.130
Authors: Graham L Baum; Rastko Ciric; David R Roalf; Richard F Betzel; Tyler M Moore; Russell T Shinohara; Ari E Kahn; Simon N Vandekar; Petra E Rupert; Megan Quarmley; Philip A Cook; Mark A Elliott; Kosha Ruparel; Raquel E Gur; Ruben C Gur; Danielle S Bassett; Theodore D Satterthwaite Journal: Curr Biol Date: 2017-05-25 Impact factor: 10.834
Authors: Max de Leeuw; Marc M Bohlken; René Cw Mandl; Manon Hj Hillegers; René S Kahn; Matthijs Vink Journal: Neuropsychopharmacology Date: 2016-07-21 Impact factor: 7.853
Authors: Graham L Baum; David R Roalf; Philip A Cook; Rastko Ciric; Adon F G Rosen; Cedric Xia; Mark A Elliott; Kosha Ruparel; Ragini Verma; Birkan Tunç; Ruben C Gur; Raquel E Gur; Danielle S Bassett; Theodore D Satterthwaite Journal: Neuroimage Date: 2018-02-24 Impact factor: 6.556
Authors: Javier Gomez-Pilar; Rodrigo de Luis-García; Alba Lubeiro; Henar de la Red; Jesús Poza; Pablo Núñez; Roberto Hornero; Vicente Molina Journal: Hum Brain Mapp Date: 2018-04-02 Impact factor: 5.038