4.7 Article

Altered structural connectivity in neonates at genetic risk for schizophrenia: A combined study using morphological and white matter networks

Journal

NEUROIMAGE
Volume 62, Issue 3, Pages 1622-1633

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2012.05.026

Keywords

High genetic risk; Newborn infant; Diffusion tensor imaging; Schizophrenia; Brain development; Network analysis

Funding

  1. NIH [EB006733, EB008760, EB008374, EB009634, MH088520, MH070890, MH064065, NS055754, HD053000]

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Recently, an increasing body of evidence suggests that developmental abnormalities related to schizophrenia may occur as early as the neonatal stage. Impairments of brain gray matter and wiring problems of axonal fibers are commonly suspected to be responsible for the disconnection hypothesis in schizophrenia adults, but significantly less is known in neonates. In this study, we investigated 26 neonates who were at genetic risk for schizophrenia and 26 demographically matched healthy neonates using both morphological and white matter networks to examine possible brain connectivity abnormalities. The results showed that both populations exhibited small-world network topology. Morphological network analysis indicated that the brain structural associations of the high-risk neonates tended to have globally lower efficiency, longer connection distance, and less number of hub nodes and edges with relatively higher betweenness. Subgroup analysis showed that male neonates were significantly disease-affected, while the female neonates were not. White matter network analysis, however, showed that the fiber networks were globally unaffected, although several subcortical-cortical connections had significantly less number of fibers in high-risk neonates. This study provides new lines of evidence in support of the disconnection hypothesis, reinforcing the notion that the genetic risk of schizophrenia induces alterations in both gray matter structural associations and white matter connectivity. (c) 2012 Elsevier Inc. All rights reserved.

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