The goal of this proposed K99/R00 application is to prepare Dr. Semanti Mukherjee to become an independent investigator in psychiatric genetics and computational biology. The primary training objectives are: 1) to expand the applicant's background knowledge in etiology, pathophysiology, and treatment of neuropsychiatric disease, with a major goal of appreciating the role of endophenotypes in explicating disease genetics;and 2) gain theoretical and computational training to develop methods to organize and interpret the complex patterns of rare and novel mutations discovered by next generation sequencing. These training objectives are specifically planned to support two planned research projects. Initially, emphasis will be on development of novel approaches to analyze existing datasets collected by my mentors, particularly Drs. Todd Lencz and Anil Malhotra of Zucker Hillside Hospital. Additional training in computational genomics will be provided by Dr. Itsik Pe'er of Columbia University. In the R00 phase, increased focus is placed upon generating targeted next- generation sequencing and genotype data for more comprehensive analyses. The novel analytic methods I will develop with Dr. Pe'er, as well as the results emerging from these projects, will serve as a rich source of preliminary data to apply for an R01 grant to conduct complex analyses involving large-scale whole genome sequencing datasets that will become available over the next several years. In both components of the Research plan, aims are focused on explicating the role of the major histocompatibility complex (MHC) in schizophrenia. While schizophrenia is a genetically complex disease, the strongest genetic signal observed to date spans the MHC, but precise localization and functional characterization has been impossible due to unique properties of the region. Importantly, the MHC signal supports the well-establish observation of increased risk of SZ associated with prenatal infection and co- occurrence with autoimmune/inflammatory disorders. Hence clarification of role of MHC genetic variation in SZ etiology promises to open new avenues for pathophysiological and treatment research. Research will be primarily performed in our unique Ashkenazi Jewish (AJ) case-control cohort, drawn from a founder population, which can serve to dramatically reduce genetic heterogeneity at the MHC locus. We will also make use of the resources of the Ashkenazi Genome Consortium, which has pioneered the use of whole genome sequencing in this population. Project deliverables will include not only novel genetic association data, including SNP data, haplotype data, and next-generation sequencing data, but also novel analytic algorithms for enhanced interrogation of these datasets.
Schizophrenia (SZ) constitutes the fifth leading cause of disability in the US. Although strongly heritable, specific genetic risk factors remain unclear. In this application, I aim to develop novel analytic approaches state-of-the-art next-generation sequencing technology in a large, ethnically homogeneous cohort of SZ cases and controls. Findings will create new opportunities for diagnosis and prediction of schizophrenia, and for understanding its biology.
|Lencz, T; Knowles, E; Davies, G et al. (2014) Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT). Mol Psychiatry 19:168-74|