Peter Kochunov1, Habib Ganjgahi2, Anderson Winkler3, Sinead Kelly4, Dinesh K Shukla1, Xiaoming Du1, Neda Jahanshad4, Laura Rowland1, Hemalatha Sampath1, Binish Patel1, Patricio O'Donnell5, Zhiyong Xie5, Sara A Paciga6, Christian R Schubert6,7, Jian Chen8, Guohao Zhang8, Paul M Thompson4, Thomas E Nichols2, L Elliot Hong1. 1. Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland. 2. Department of Statistics, University of Warwick, Warwick, United Kingdom. 3. FMRIB Centre, Oxford University, Oxford, United Kingdom. 4. Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, California. 5. Neuroscience Research Unit, Worldwide Research and Development, Pfizer Inc, 610 Main Street, Cambridge, Massachusetts, 02139. 6. Enterprise Scientific Technology Operations, Worldwide Research and Development, Pfizer Inc, Eastern Point Rd, Groton, Connecticut, 06340. 7. Biogen, Cambridge, Massachusetts, 02142. 8. Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Maryland, 21250.
Abstract
BACKGROUND: Altered brain connectivity is implicated in the development and clinical burden of schizophrenia. Relative to matched controls, schizophrenia patients show (1) a global and regional reduction in the integrity of the brain's white matter (WM), assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA), and (2) accelerated age-related decline in FA values. In the largest mega-analysis to date, we tested if differences in the trajectories of WM tract development influenced patient-control differences in FA. We also assessed if specific tracts showed exacerbated decline with aging. METHODS: Three cohorts of schizophrenia patients (total n = 177) and controls (total n = 249; age = 18-61 years) were ascertained with three 3T Siemens MRI scanners. Whole-brain and regional FA values were extracted using ENIGMA-DTI protocols. Statistics were evaluated using mega- and meta-analyses to detect effects of diagnosis and age-by-diagnosis interactions. RESULTS: In mega-analysis of whole-brain averaged FA, schizophrenia patients had lower FA (P = 10-11 ) and faster age-related decline in FA (P = 0.02) compared with controls. Tract-specific heterochronicity measures, that is, abnormal rates of adolescent maturation and aging explained approximately 50% of the regional variance effects of diagnosis and age-by-diagnosis interaction in patients. Interactive, three-dimensional visualization of the results is available at www.enigma-viewer.org. CONCLUSION: WM tracts that mature later in life appeared more sensitive to the pathophysiology of schizophrenia and were more susceptible to faster age-related decline in FA values. Hum Brain Mapp 37:4673-4688, 2016.
BACKGROUND: Altered brain connectivity is implicated in the development and clinical burden of schizophrenia. Relative to matched controls, schizophreniapatients show (1) a global and regional reduction in the integrity of the brain's white matter (WM), assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA), and (2) accelerated age-related decline in FA values. In the largest mega-analysis to date, we tested if differences in the trajectories of WM tract development influenced patient-control differences in FA. We also assessed if specific tracts showed exacerbated decline with aging. METHODS: Three cohorts of schizophreniapatients (total n = 177) and controls (total n = 249; age = 18-61 years) were ascertained with three 3T Siemens MRI scanners. Whole-brain and regional FA values were extracted using ENIGMA-DTI protocols. Statistics were evaluated using mega- and meta-analyses to detect effects of diagnosis and age-by-diagnosis interactions. RESULTS: In mega-analysis of whole-brain averaged FA, schizophreniapatients had lower FA (P = 10-11 ) and faster age-related decline in FA (P = 0.02) compared with controls. Tract-specific heterochronicity measures, that is, abnormal rates of adolescent maturation and aging explained approximately 50% of the regional variance effects of diagnosis and age-by-diagnosis interaction in patients. Interactive, three-dimensional visualization of the results is available at www.enigma-viewer.org. CONCLUSION: WM tracts that mature later in life appeared more sensitive to the pathophysiology of schizophrenia and were more susceptible to faster age-related decline in FA values. Hum Brain Mapp 37:4673-4688, 2016.
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