| dc.identifier.uri | http://hdl.handle.net/11401/77611 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | The ability to unveil the genetic landscape of human disease at an extraordinarily detailed resolution through high-throughput DNA sequencing promises a transformation of medical practice toward precision medicine. However, it is not a straight path from producing individual genomics data to pinpointing the disease-contributory variants and delivering the personalized therapy, due to the complexity of human genome architecture, genotype-phenotype correlation and disease pathogenesis. But first and foremost for precision medicine to succeed is to ensure the reliability and accuracy of the generation and interpretation of clinical genomics. However, due to a lack of an unbiased high-throughput targeted resequencing protocol, the validity and comparability of each DNA sequencing platform, protocol and variant detection algorithm has yet to be characterized. Meanwhile, a comprehensive investigation of the clinical findings must be equally executed in order to achieve a better design of sequencing projects and prioritization of disease-associated variants, especially for patients presenting a complex history. However, the hurdles to obtaining first-hand clinical data and a lack of standardized vocabulary use in medical documentation have prohibited this information from being utilized to its maximum potential. Furthermore, before any therapeutics can be developed, a robust disease model needs to be constructed to prove the causality of the pinpointed variants and understand the functional impact of it in disease affected cell types or tissues. This dissertation research aims to address some of the above issues to help advance the implementation of precision medicine. In particular, the first study aims to assess the validity issue of clinical genomics data by providing a robust, high-throughput, targeted resequencing protocol. Study 2 aims to illustrate the opportunity and challenge of utilizing clinical genomics to identify the genetic basis of human diseases with two real-world examples, including our newly discovered genetic disorder TAF1 syndrome. Study 3 aims to investigate the functional impact of Naa10 S37P, a variant identified through clinical genomics that contributes to a rare disease Ogden syndrome, in patients’ fibroblasts. And the last study aims to model the cardiac dysrhythmias of Ogden syndrome using patient specific induced pluripotent stem cell-derived cardiomyocytes to shed some light on the mechanism of Ogden syndrome pathogenesis. | |
| dcterms.abstract | The ability to unveil the genetic landscape of human disease at an extraordinarily detailed resolution through high-throughput DNA sequencing promises a transformation of medical practice toward precision medicine. However, it is not a straight path from producing individual genomics data to pinpointing the disease-contributory variants and delivering the personalized therapy, due to the complexity of human genome architecture, genotype-phenotype correlation and disease pathogenesis. But first and foremost for precision medicine to succeed is to ensure the reliability and accuracy of the generation and interpretation of clinical genomics. However, due to a lack of an unbiased high-throughput targeted resequencing protocol, the validity and comparability of each DNA sequencing platform, protocol and variant detection algorithm has yet to be characterized. Meanwhile, a comprehensive investigation of the clinical findings must be equally executed in order to achieve a better design of sequencing projects and prioritization of disease-associated variants, especially for patients presenting a complex history. However, the hurdles to obtaining first-hand clinical data and a lack of standardized vocabulary use in medical documentation have prohibited this information from being utilized to its maximum potential. Furthermore, before any therapeutics can be developed, a robust disease model needs to be constructed to prove the causality of the pinpointed variants and understand the functional impact of it in disease affected cell types or tissues. This dissertation research aims to address some of the above issues to help advance the implementation of precision medicine. In particular, the first study aims to assess the validity issue of clinical genomics data by providing a robust, high-throughput, targeted resequencing protocol. Study 2 aims to illustrate the opportunity and challenge of utilizing clinical genomics to identify the genetic basis of human diseases with two real-world examples, including our newly discovered genetic disorder TAF1 syndrome. Study 3 aims to investigate the functional impact of Naa10 S37P, a variant identified through clinical genomics that contributes to a rare disease Ogden syndrome, in patients’ fibroblasts. And the last study aims to model the cardiac dysrhythmias of Ogden syndrome using patient specific induced pluripotent stem cell-derived cardiomyocytes to shed some light on the mechanism of Ogden syndrome pathogenesis. | |
| dcterms.available | 2017-09-20T16:53:01Z | |
| dcterms.contributor | Lyon, Gholson J. | en_US |
| dcterms.contributor | Mills, Alea A. | en_US |
| dcterms.contributor | Entcheva, Emilia | en_US |
| dcterms.contributor | Sternglanz, Rolf | en_US |
| dcterms.contributor | Brennand, Kristen | en_US |
| dcterms.contributor | . | en_US |
| dcterms.creator | Wu, Yiyang | |
| dcterms.dateAccepted | 2017-09-20T16:53:01Z | |
| dcterms.dateSubmitted | 2017-09-20T16:53:01Z | |
| dcterms.description | Department of Genetics | en_US |
| dcterms.extent | 246 pg. | en_US |
| dcterms.format | Monograph | |
| dcterms.format | Application/PDF | en_US |
| dcterms.identifier | http://hdl.handle.net/11401/77611 | |
| dcterms.issued | 2017-05-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:53:01Z (GMT). No. of bitstreams: 1
Wu_grad.sunysb_0771E_13259.pdf: 141796149 bytes, checksum: 9beffa4cc74dcddc27abe90a87673be8 (MD5)
Previous issue date: 1 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | Genetics | |
| dcterms.subject | clinical genomics, iPSC disease modeling, long QT, N-terminal acetylation, Ogden syndrome, precision medicine | |
| dcterms.title | Toward Precision Medicine: From Clinical Genomics to iPSC Disease Modeling | |
| dcterms.type | Dissertation | |
