Identifying Schizophrenia Risk Loci in the MHC Using Next Generation Sequencing

描述(由申请人提供)：这项建议的K99/R00申请的目标是为Semanti Mukherjee博士准备成为精神病学遗传学和计算生物学的独立研究员。主要的培训目标是：1)扩大申请者在病因学、病理生理学和神经精神疾病治疗方面的背景知识，主要目标是评价内表型在解释疾病遗传学中的作用；2)获得理论和计算培训，以开发方法来组织和解释通过下一代测序发现的罕见和新的突变的复杂模式。这些培训目标是专门为支持两个计划中的研究项目而制定的。最初，重点将是开发新的方法来分析我的导师们收集的现有数据集，特别是扎克希尔赛德医院的托德·伦茨博士和阿尼尔·马尔霍特拉博士。哥伦比亚大学的Itsik Pe‘er博士将提供计算基因组学方面的额外培训。在R00阶段，更多的重点放在为更全面的分析生成目标下一代测序和基因数据。我将与佩尔博士共同开发的新分析方法，以及这些项目产生的结果，将作为丰富的初步数据来源，申请R01拨款，以进行涉及大规模全基因组测序数据集的复杂分析，这些数据集将在未来几年提供。在研究计划的两个组成部分中，目标都集中在阐明主要组织相容性复合体(MHC)在精神分裂症中的作用。虽然精神分裂症是一种基因复杂的疾病，但迄今为止观察到的最强的遗传信号跨越了MHC，但由于该地区的独特性质，精确的定位和功能表征一直是不可能的。重要的是，MHC信号支持了与产前感染相关的SZ风险增加以及与自身免疫性/炎症性疾病共存的良好观察。因此，阐明MHC基因变异在SZ病因学中的作用有望为SZ的病理生理和治疗研究开辟新的途径。研究将主要在我们独特的德系犹太人(AJ)病例对照队列中进行，该队列来自创始人群体，这可以显著降低MHC基因座的遗传异质性。我们还将利用德系克纳齐人基因组联盟的资源，该联盟率先在这个种群中使用全基因组测序。项目成果将不仅包括新的遗传关联数据，包括SNP数据、单倍型数据和下一代测序数据，还包括用于增强对这些数据集的询问的新的分析算法。

DESCRIPTION (provided by applicant): 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.