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dc.contributor.authorSimmons, Michael
dc.date.accessioned2017-05-26T20:14:32Z
dc.date.available2017-05-26T20:14:32Z
dc.date.issued2017-05-26
dc.identifier.urihttp://hdl.handle.net/10150/623630
dc.descriptionA Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.en
dc.description.abstractGenetic association studies simplify genotype‐phenotype relationship investigation by considering only the presence of a given polymorphism and the presence or absence of a given downstream phenotype. Although such associations do not indicate causation, collections of phenotypes sharing association with a single genetic polymorphism may provide valuable mechanistic insights. In this thesis we explore such genetic pleiotropy with Deep Phenotype Association Studies (DeePAS) using data from the Age‐Related Eye Study 2 (AREDS2). We also employ a novel text mining approach to extract pleiotropic associations from the published literature as a hypothesis generation mechanism. Is it possible to identify pleiotropic genetic associations across multiple published abstracts and validate these in data from AREDS2? Data from the AREDS2 trial includes 123 phenotypes including AMD features, other ocular conditions, cognitive function and cardiovascular, neurological, gastrointestinal and endocrine disease. A previously validated relationship extraction algorithm was used to isolate descriptions of genetic associations with these phenotypes in MEDLINE abstracts. Results were filtered to exclude negated findings and normalize variant mentions. Genotype data was available for 1826 AREDS2 participants. A DeePAS was performed by evaluating the association between selected SNPs and all available phenotypes. Associations that remained significant after Bonferroni‐correction were replicated in AREDS. LitWAS analysis identified 9372 SNPs with literature support for at least two distinct phenotypes, with an average of 3.1 phenotypes/SNP. PheWAS analyses revealed that two variants of the ARMS2‐HTRA1 locus at 10q26, rs10490924 and rs3750846, were significantly associated with sub‐retinal hemorrhage in AMD (rs3750846 OR 1.79 (1.41‐2.27), p=1.17*10‐7). This associated remained significant even in populations of participants with neovascular AMD. Furthermore, odds ratios for the development of sub‐retinal hemorrhage in the presence of the rs3750846 SNP were similar between incident and prevalent AREDS2 sub‐populations (OR: 1.94 vs 1.75). This association was also replicated in data from the AREDS trial. No literature‐defined pleiotropic associations tested remained significant after multiple‐testing correction. The rs3750846 variant of the ARMS2‐HTRA1 locus is associated with sub‐retinal hemorrhage. Automatic literature mining, when paired with clinical data, is a promising method for exploring genotype‐phenotype relationships.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the College of Medicine - Phoenix, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectText Miningen
dc.subjectGenetic Association Studiesen
dc.subjectGWASen
dc.subjectPheWASen
dc.subjectAge-related Macular Degenerationen
dc.subjectAMDen
dc.subjectAREDS2en
dc.subjectARMS2en
dc.subjectPhenomeen
dc.subjectHtrA1 Proteinen
dc.subject.meshEye Diseasesen
dc.subject.meshMacular Degenerationen
dc.subject.meshData Miningen
dc.subject.meshGenetic Pleiotropyen
dc.subject.meshPhenotypeen
dc.subject.meshPolymorphism, Geneticen
dc.subject.meshRandomized Controlled Trials as Topicen
dc.subject.meshGenetic Testingen
dc.subject.meshRetinal Hemorrhageen
dc.titleIdentifying Genetic Pleiotropy through a Literature-wide Association Study (LitWAS) and a Phenotype Association Study (PheWAS) in the Age-related Eye Disease Study 2 (AREDS2)en_US
dc.typetext; Electronic Thesisen
dc.contributor.departmentThe University of Arizona College of Medicine - Phoenixen
dc.description.collectioninformationThis item is part of the College of Medicine - Phoenix Scholarly Projects 2017 collection. For more information, contact the Phoenix Biomedical Campus Library at pbc-library@email.arizona.edu.en_US
dc.contributor.mentorLu, Zhiyongen
refterms.dateFOA2018-06-26T09:35:35Z
html.description.abstractGenetic association studies simplify genotype‐phenotype relationship investigation by considering only the presence of a given polymorphism and the presence or absence of a given downstream phenotype. Although such associations do not indicate causation, collections of phenotypes sharing association with a single genetic polymorphism may provide valuable mechanistic insights. In this thesis we explore such genetic pleiotropy with Deep Phenotype Association Studies (DeePAS) using data from the Age‐Related Eye Study 2 (AREDS2). We also employ a novel text mining approach to extract pleiotropic associations from the published literature as a hypothesis generation mechanism. Is it possible to identify pleiotropic genetic associations across multiple published abstracts and validate these in data from AREDS2? Data from the AREDS2 trial includes 123 phenotypes including AMD features, other ocular conditions, cognitive function and cardiovascular, neurological, gastrointestinal and endocrine disease. A previously validated relationship extraction algorithm was used to isolate descriptions of genetic associations with these phenotypes in MEDLINE abstracts. Results were filtered to exclude negated findings and normalize variant mentions. Genotype data was available for 1826 AREDS2 participants. A DeePAS was performed by evaluating the association between selected SNPs and all available phenotypes. Associations that remained significant after Bonferroni‐correction were replicated in AREDS. LitWAS analysis identified 9372 SNPs with literature support for at least two distinct phenotypes, with an average of 3.1 phenotypes/SNP. PheWAS analyses revealed that two variants of the ARMS2‐HTRA1 locus at 10q26, rs10490924 and rs3750846, were significantly associated with sub‐retinal hemorrhage in AMD (rs3750846 OR 1.79 (1.41‐2.27), p=1.17*10‐7). This associated remained significant even in populations of participants with neovascular AMD. Furthermore, odds ratios for the development of sub‐retinal hemorrhage in the presence of the rs3750846 SNP were similar between incident and prevalent AREDS2 sub‐populations (OR: 1.94 vs 1.75). This association was also replicated in data from the AREDS trial. No literature‐defined pleiotropic associations tested remained significant after multiple‐testing correction. The rs3750846 variant of the ARMS2‐HTRA1 locus is associated with sub‐retinal hemorrhage. Automatic literature mining, when paired with clinical data, is a promising method for exploring genotype‐phenotype relationships.


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