Ela Knapik - US grants

[unreadable] DESCRIPTION (provided by applicant): Craniofacial birth defects are frequent human dysmorphologies, many of unknown genetic causes. The zebrafish crusher variant results in malformed head skeleton and short body. Crusher fish have a mutation in the gene encoding Sec23a, a component of CORN vesicles, which take part in protein trafficking from the endoplasmic reticulum (ER) to the Golgi apparatus. A genetic lesion in the human SEC23A gene causes cranio-lenticulo-sutural dysplasia, which has similar skeletal deficits to crusher mutants. Our research shows that chondrocytes in the head skeleton of crusher mutants fail to secrete collagen in the extracellular space leading to misshaped or missing cartilages. Instead, procollagen accumulates in the ER indicating a severe paucity in the secretory flow. We found that the second sec23 gene, sec23b, is also essential for craniofacial development suggesting that both isoforms have critical functions in chondrocytes. We hypothesize that craniofacial morphogenesis is sensitive to obstructions in protein trafficking. We will study how Sec23a insufficiency impairs growth, survival and differentiation of chondrocytes in zebrafish and chondrogenic rat cells (Aim 1). To distinguish the specific roles of the two Sec23 isozymes, we will analyze the phenotypes of single and double mutants and investigate how loss of one or both isoforms affects trafficking of distinct protein classes in live zebrafish embryos and chondrogenic cells (Aim 2). To examine how the sec23 lesions interfere with the assembly and function of CORN complexes, we will analyze the properties of mutated Sec23 proteins in yeast and cell-free biochemical assays (Aim 3). The proposed research will determine the role of Sec23-dependent protein trafficking by identifying molecular and cellular deficits in craniofacial dysmorphologies linked to a secretory blockade. This knowledge might lead to future diagnostic and therapeutic tools. Because several pathological conditions like scar formation and fibrosis involve secretion of extracellular matrix proteins, finding out how intracellular transport of large cargo is regulated could offer new ways to handle common human disorders. [unreadable] [unreadable] [unreadable]

Abstract: We propose in this application to use truly unique resources available to the Vanderbilt University research community to identify and characterize genetic risk factors for neuropsychiatric disorders. Our overarching hypothesis is that co-morbid phenotypes that cut across neuropsychiatric disorders can be used to identify more homogeneous genetic risk factors that will also be cross-cutting for neuropsychiatric diseases. To address this hypothesis, we will harness the long-standing strengths in neuroscience at Vanderbilt including extensive expertise in conducting in vivo and in vitro experimental validation studies, the strong team of investigators with long-standing research programs in key co-morbid phenotypes and neuropsychiatric disease, and our track record in developing and applying novel integrative approaches for genome investigation. The clinical data warehouse at Vanderbilt is called the Synthetic Derivative (SD), and contains continuously updated electronic health records (EHR) on more than 2,500,000 individuals. DNA samples are available on more than 217,000 of the individuals in the SD through BioVU, the biobank at Vanderbilt University. Individuals with more longitudinal data some going back as long as 20-30 years have been prioritized for genome investigation, and genome interrogation (GWAS or whole genome sequencing) will be available on > 120,000 of these subjects in 2018. The SD provides unprecedented power for characterizing cross-cutting comorbidities for neuropsychiatric disorders, and the large number of BioVU samples with genome interrogation coupled with the novel analytic approaches we have devised to optimize genome investigations in BioVU create a dynamic engine for discovery research. Our specific aims are to: 1) Use EHR data on more than 2,500,000 individuals to investigate the relationship between neuropsychiatric disorders and comorbid phenotypes shared among multiple of these disorders; 2) Use the novel PrediXcan approach to identify genes for which genetically predicted expression is significantly associated with neuropsychiatric disease, neuropsychiatric disease plus comorbidity, or comorbidity for more than 120,000 samples in BioVU; and 3) Prioritize genes for validation using improved network and pathway analyses, and then experimentally validate genes implicated in neuropsychiatric and comorbid phenotypes.