Abstract
Several lines of evidence suggest that efficient information integration between brain regions is disrupted in schizophrenia. Abnormalities in white matter tracts that interconnect brain regions may be directly relevant to this pathophysiological process. As a complex mental disorder with high heritability, mapping abnormalities in patients and their first-degree relatives may help to disentangle the risk factors for schizophrenia. We established a weighted network model of white matter connections using diffusion tensor imaging in 25 nuclear families with schizophrenic probands (19 patients and 41 unaffected parents) and two unrelated groups of normal controls (24 controls matched with patients and 26 controls matched with relatives). The patient group showed lower global efficiency and local efficiency. The decreased regional efficiency was localized in hubs such as the bilateral frontal cortices, bilateral anterior cingulate cortices, and left precuneus. The global efficiency was negatively correlated with cognition scores derived from a 5-factor model of schizophrenic psychopathology. We also found that unaffected parents displayed decreased regional efficiency in the right temporal cortices, left supplementary motor area, left superior temporal pole, and left thalamus. The global efficiency tended to be lower in unaffected parents. Our data suggest that (1) the global efficiency loss in neuroanatomical networks may be associated with the cognitive disturbances in schizophrenia; and (2) genetic vulnerability to schizophrenia may influence the anatomical organization of an individual’s brain networks.
Electronic Supplementary Material
Supplementary material is available for this article at 10.1007/s12264-014-1518-0 and is accessible for authorized users.
Keywords: network analysis, diffusion tensor imaging, tractography, white matter, small-world architecture
Electronic supplementary material
Footnotes
These authors contributed equally to this work.
Electronic Supplementary Material
Supplementary material is available for this article at 10.1007/s12264-014-1518-0 and is accessible for authorized users.
Contributor Information
Hao Yan, Email: hao_y@bjmu.edu.cn.
Dai Zhang, Email: daizhang@bjmu.edu.cn.
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