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Illuminating the genetic basis of complex liver traits in humans via computational genomics / Katerina Gawronski.

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Format:
Book
Thesis/Dissertation
Author/Creator:
Gawronski, Katerina, author.
Contributor:
Voight, Benjamin, degree supervisor.
Brown, Christopher, degree supervisor.
University of Pennsylvania. Department of Cell and Molecular Biology, degree granting institution.
Language:
English
Subjects (All):
Genetics.
Triglycerides.
Body mass index.
Estimates.
Mutation.
Binding sites.
Risk factors.
Cholesterol.
Genomes.
Biology.
Genomics.
Lipids.
Statistical analysis.
Alzheimers disease.
Proteins.
Principal components analysis.
Statins.
Hypotheses.
Blood pressure.
Cardiovascular disease.
Arrays.
Heart.
Haplotypes.
Enzymes.
Cell and molecular biology--Penn dissertations.
Penn dissertations--Cell and molecular biology.
Local Subjects:
Genetics.
Triglycerides.
Body mass index.
Estimates.
Mutation.
Binding sites.
Risk factors.
Cholesterol.
Genomes.
Biology.
Genomics.
Lipids.
Statistical analysis.
Alzheimers disease.
Proteins.
Principal components analysis.
Statins.
Hypotheses.
Blood pressure.
Cardiovascular disease.
Arrays.
Heart.
Haplotypes.
Enzymes.
Cell and molecular biology--Penn dissertations.
Penn dissertations--Cell and molecular biology.
Genre:
Academic theses.
Physical Description:
1 online resource (77 pages)
Contained In:
Dissertations Abstracts International 83-03B.
Place of Publication:
[Philadelphia, Pennsylvania] : University of Pennsylvania ; Ann Arbor : ProQuest Dissertations & Theses, 2021.
Language Note:
English
System Details:
Mode of access: World Wide Web.
text file
Summary:
This dissertation uses statistical and computational methods in human genetics to further our understanding of the genetic basis of liver traits. Genome-wide association studies (GWAS) have provided researchers with many genomic regions associated with liver phenotypes. However, GWA studies do not directly identify causal risk factors, variants, and genes - therefore, in this dissertation, I use complementary computational and statistical approaches to help identify genes, variants, molecular processes, and risk factors for liver traits with cardiometabolic implications. In the first chapter of this dissertation, I examine the role of genetically-driven differences in alternative splicing in blood lipid level variation by mapping splicing quantitative trait loci (sQTL) and integrating these data with lipid GWAS through colocalization analysis. We find that sQTLs provide information as to the causal variants and genes driving variation and provide a level of granularity that cannot be captured by total gene expression measurements. In the second chapter of this dissertation, I use GWAS data in the recently developed framework of Mendelian Randomization (MR) to better understand the causal risk factors for non-alcoholic fatty liver disease (NAFLD) a complex disease of increasing prevalence and limited treatment options. We find that body mass index and central adiposity have independent effects on NAFLD risk, as does birthweight. We are also the first to show that both causal relationships for body mass index and central adiposity replicate in African American and Hispanic populations, which in turn suggests that the underlying genetics of NAFLD are similar across ancestry groups. In sum, this dissertation improves our understanding of complex liver phenotypes by identifying underlying molecular mechanisms and genes (Chapter 1) and genetically determined risk factors (Chapter 2). Importantly, the results of this report provide researchers and clinicians with new targets for pharmacological and behavioral interventions.
Notes:
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Advisors: Voight, Benjamin; Brown, Christopher; Committee members: Lynch, Kristen; Murray, John; Zhang, Nancy.
Department: Cell and Molecular Biology.
Ph.D. University of Pennsylvania 2021.
Local Notes:
School code: 0175
ISBN:
9798535590363
Access Restriction:
Restricted for use by site license.
This item is not available from ProQuest Dissertations & Theses.
This item must not be sold to any third party vendors.

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