22q11Deletion Syndrome (22q11DS) is a rare disease caused by the deletion of about 40 genes in chromosome 22. Individuals with 22q11DS have a 30% risk of developing schizophrenia. This high incidence, in combination with the known genetic defects, makes 22q11DS a unique disease model for the investigation of the etiology of schizophrenia, especially in its early stages. This two-year proposal will investigate abnormalities of white matter in subjects diagnosed with 22q11DS at the time of psychosis onset. These subjects will be compared to those who are not psychotic and are diagnosed with 22q11DS, and with healthy controls. This project will use diffusion MR imaging (dMRI) to investigate and to quantify white matter abnormalities in the brain. DMRI is a relatively new MR imaging technique that makes it possible to investigate white matter of the brain in vivo. We will focus on the changes occurring at the onset of the disease in young adult subjects with and without psychosis. We hypothesize that we will find changes in white matter at the onset of psychosis. We hypothesize that these changes are likely an expression of inflammation-like processes, which have been observed in first- episode schizophrenia. We will test our hypothesis using a novel approach for measuring extracellular water in the brain. This measurement is called the Free Water component of fractional anisotropy and it has been found to be associated with edema and neuroinflammation. We expect to find these changes in white matter localized to commissural and fronto-parietal connections. These are brain regions with many intersecting fibers, which are difficult to analyze using more conventional DTI measures such as single tensor based measurements. Here we will use two-tensor tractography to overcome the problem of intersecting fibers. We will also use a novel automated approach, the White Matter Query Language (WMQL), to identify specific white matter fiber tracts. This is particularly important as our cohort of 90 participants is relatively large and could not be manually segmented with the resources available in an R21 grant. The results of these measurements will be correlated with clinical, neurocognitive assessments, and corrected for medication use in order to fully characterize the sample. The presumed ongoing neuroinflammatory processes, in those 22q11DS subjects who are psychotic versus those who are not, will be correlated with measurement of cytokines concentrations from the subjects' blood. The knowledge gained about the processes occurring in white matter in subjects with 22q11DS at the onset of psychosis will add enormously to our understanding of the mechanisms underlying psychosis in general and open doors for future intervention using targeted treatment such as anti-inflammatory medications.
Our project will explore changes in the white matter in the brains of individuals diagnosed with 22q11Deletion Syndrome, a genetic disease with a deletion on chromosome 22 that is associated with a high risk for developing schizophrenia. We propose to investigate changes in the white matter of the brain, regions that form the connections involved in thinking, emotion, and behavior, in 22q11Deletion Syndrome patients who have developed psychosis, compared with those who have not, and in a comparison group of healthy controls. Specifically, we will research the presence of inflammation-like processes, using both imaging and serum biomarkers, which we believe may be associated with onset of psychosis. Such inflammatory processes could become the target of novel therapeutic approaches for the treatment of schizophrenia.
| Kikinis, Zora; Cho, Kang Ik K; Coman, Ioana L et al. (2017) Abnormalities in brain white matter in adolescents with 22q11.2 deletion syndrome and psychotic symptoms. Brain Imaging Behav 11:1353-1364 |
| Oestreich, Lena K L; Lyall, Amanda E; Pasternak, Ofer et al. (2017) Characterizing white matter changes in chronic schizophrenia: A free-water imaging multi-site study. Schizophr Res 189:153-161 |
| Tylee, Daniel S; Kikinis, Zora; Quinn, Thomas P et al. (2017) Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study. Neuroimage Clin 15:832-842 |
