4.7 Article

Generative network models of altered structural brain connectivity in schizophrenia

期刊

NEUROIMAGE
卷 225, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2020.117510

关键词

Generative network models; Intermediate phenotype; Structural connectivity; Polygenetic risk; Cognition

资金

  1. China Scholarship Council
  2. German Research Foundation (DFG) [ME 1591/4-1, BR 5951/1-1, GRK 2350, TO 539/3-1]
  3. German Federal Ministry of Education and Research (BMBF) [01GQ1102, 01ZX1314G, 01GS08147, 01GQ1003B]
  4. German Research Foundation [DFG HI 1928/2-1]
  5. European Union [602450, 602805, 115300, HEALTH-F2-2010-241909]
  6. Innovative Medicines Initiative Joint Undertaking (IMI) [115008]
  7. Ministry of Science, Research and the Arts of the State of BadenWuerttemberg, Germany (MWK) [42-04HV.MED(16)/16/1]
  8. John D. and Catherine T. MacArthur Foundation
  9. Alfred P. Sloan Foundation
  10. Army Research Laboratory [W911NF-10-2-0022, W911NF-14-1-0679]
  11. Army Research Office [W911NF-10-2-0022, W911NF-14-1-0679]
  12. National Institute of Health [2-R01-DC-009209-11, 1R01HD086888-01, R01-MH107235, R01-MH107703, R21-M MH-106799]
  13. Office of Naval Research
  14. National Science Foundation [BCS-1441502, CAREER PHY-1554488, BCS-1631550]
  15. Deutsche Forschungsgemeinschaft, DFG [SCHW 1768/1-1]
  16. Indiana University Office of the Vice President for Research Emerging Area of Research Initiative, Learning: Brains, Machines and Children
  17. German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understand-ing of Causes and Mechanisms in Mental Disorders), under the auspices of the e:Med Programme [01ZX1314A/01ZX1614A]

向作者/读者索取更多资源

The study highlights spatial constraints and local topological structure as two interrelated mechanisms contributing to regular brain network formation and altered connectomes in schizophrenia patients and individuals at familial risk for schizophrenia.
Alterations in the structural connectome of schizophrenia patients have been widely characterized, but the mechanisms remain largely unknown. Generative network models have recently been introduced as a tool to test the biological underpinnings of altered brain network formation. We evaluated different generative network models in healthy controls (n=152), schizophrenia patients (n=66), and their unaffected first-degree relatives (n=32), and we identified spatial and topological factors contributing to network formation. We further investigated how these factors relate to cognition and to polygenic risk for schizophrenia. Our data show that among the four tested classes of generative network models, structural brain networks were optimally accounted for by a two-factor model combining spatial constraints and topological neighborhood structure. The same wiring model explained brain network formation across study groups. However, relatives and schizophrenia patients exhibited significantly lower spatial constraints and lower topological facilitation compared to healthy controls. Further exploratory analyses point to potential associations of the model parameter reflecting spatial constraints with the polygenic risk for schizophrenia and cognitive performance. Our results identify spatial constraints and local topological structure as two interrelated mechanisms contributing to regular brain network formation as well as altered connectomes in schizophrenia and healthy individuals at familial risk for schizophrenia. On an exploratory level, our data further point to the potential relevance of spatial constraints for the genetic risk for schizophrenia and general cognitive functioning, thereby encouraging future studies in following up on these observations to gain further insights into the biological basis and behavioral relevance of model parameters.

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