Schizophrenia has been considered a neurodevelopmental disorder for over two decades, yet the specific neurodevelopmental mechanisms that contribute to the cortical pathology central to schizophrenia remain unknown. Genetic vulnerability for schizophrenia has been recognized for almost 100 years;nevertheless, the relationship between genetic risk and specific neurodevelopmental mechanisms is unclear. The UNC Conte Center, """"""""Prospective Studies of the Pathogenesis of Schizophrenia,"""""""" will answer three key questions in an effort to synthesize neurodevelopmental mechanisms, genetic vulnerability, and the development of schizophrenia: 1) At what stage of development does cortical pathology arise in children at risk for schizophrenia? 2) How does cortical pathology contribute to the developmental expression of cognitive deficits and clinical symptoms of schizophrenia? and 3) Can an apparently diverse set of developmental mechanisms and risk genes give rise to a common cortical pathology implicated in schizophrenia? The central hypothesis of this competitive renewal of the UNC Conte Center is that genetic vulnerability for schizophrenia can compromise multiple mechanisms of early cortical development, each of which can ultimately contribute to aberrant cortical circuitry, neurocognitive deficits, and the clinical symptoms of schizophrenia. The clinical projects of the UNC Conte Center will use state-of-the-art multimodal imaging and image analysis to study the development of cortical structure and function in children at genetic high risk for schizophrenia during the two critical periods of cortical synaptic development: synaptic elaboration during early childhood (Project 1), and synaptic remodeling and elimination during adolescence (Project 2). In parallel, the preclinical projects will assess cortical precursor proliferation, neuronal migration and synapse formation in mouse models of three well characterized sets of risk genes: NCAM (Project 3);22q11 genes (Project 4), and Neuregulin/Erb4 (Project 5). These projects will be supported by 3 cores - 1) Administrative, 2) Neuroimage Analysis 3) Biostatistics and Data Management;each part of the current Conte Center. Our goal is to synthesize clinical characterization of abnormal cortical structure and function in genetically vulnerable children with detailed assessment of abnormal neurodevelopmental mechanisms in the cortex of mice carrying mutations in specific risk genes. UNC Conte Center offers a focused, directed, and integrated set of clinical and basic projects and experiments that will identify fundamental mechanisms of cortical development that are the basis of the neurodevelopmental pathogenesis that is thought to underlie schizophrenia.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Specialized Center (P50)
Project #
5P50MH064065-09
Application #
7902024
Study Section
Special Emphasis Panel (ZMH1-ERB-S (03))
Program Officer
Zalcman, Steven J
Project Start
2001-07-01
Project End
2012-07-31
Budget Start
2010-08-01
Budget End
2011-07-31
Support Year
9
Fiscal Year
2010
Total Cost
$1,910,307
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Psychiatry
Type
Schools of Medicine
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Lyu, Ilwoo; Kim, Sun Hyung; Girault, Jessica B et al. (2018) A cortical shape-adaptive approach to local gyrification index. Med Image Anal 48:244-258
Stephens, Rebecca L; Langworthy, Benjamin; Short, Sarah J et al. (2018) Verbal and nonverbal predictors of executive function in early childhood. J Cogn Dev 19:182-200
Girault, Jessica B; Langworthy, Benjamin W; Goldman, Barbara D et al. (2018) The Predictive Value of Developmental Assessments at 1 and 2 for Intelligence Quotients at 6. Intelligence 68:58-65
Tu, Liyun; Styner, Martin; Vicory, Jared et al. (2018) Skeletal Shape Correspondence Through Entropy. IEEE Trans Med Imaging 37:1-11
Jha, Shaili C; Xia, Kai; Schmitt, James Eric et al. (2018) Genetic influences on neonatal cortical thickness and surface area. Hum Brain Mapp 39:4998-5013
Wang, Yan; Ma, Guangkai; An, Le et al. (2017) Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI. IEEE Trans Biomed Eng 64:569-579
Xia, K; Zhang, J; Ahn, M et al. (2017) Genome-wide association analysis identifies common variants influencing infant brain volumes. Transl Psychiatry 7:e1188
Sadeghi, Neda; Gilmore, John H; Gerig, Guido (2017) Twin-singleton developmental study of brain white matter anatomy. Hum Brain Mapp 38:1009-1024
Wei, Lifang; Cao, Xiaohuan; Wang, Zhensong et al. (2017) Learning-based deformable registration for infant MRI by integrating random forest with auto-context model. Med Phys 44:6289-6303
Gao, Wei; Lin, Weili; Grewen, Karen et al. (2017) Functional Connectivity of the Infant Human Brain: Plastic and Modifiable. Neuroscientist 23:169-184

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