Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.

Safety and efficacy of ledipasvir-sofosbuvir in black patients with hepatitis C virus infection: A retrospective analysis of phase 3 data.

UNLABELLED: Black patients chronically infected with genotype 1 hepatitis C virus (HCV) have historically had lower rates of response to interferon-based treatment than patients of other races. In the phase 3 ION program, the single-tablet regimen of the NS5A inhibitor ledipasvir and NS5B nucleotide polymerase inhibitor sofosbuvir was shown to be safe and highly effective in the general population. The aim of this study was to evaluate the safety and efficacy of ledipasvir/sofosbuvir in black patients using data from the three open-label ION clinical trials, which evaluated the safety and efficacy of 8, 12, and 24 weeks of ledipasvir/sofosbuvir with or without ribavirin for the treatment of treatment-naïve and treatment-experienced patients with genotype 1 HCV, including those with compensated cirrhosis. The primary endpoint was sustained virologic response at 12 weeks after the end of therapy (SVR12). For our analysis, rates of SVR12, treatment-emergent adverse events, and graded laboratory abnormalities were analyzed in black versus non-black patients. Of the 1949 patients evaluated, 308 (16%) were black. On average, black patients were older, had higher body mass index, were more likely to be IL28B non-CC, and had a lower serum alanine aminotransferase at baseline than non-black patients. Overall, 95% of black and 97% of non-black patients achieved SVR12. The rate of relapse was 3% in black patients as compared with 2% in non-black patients. The most common adverse events included fatigue, headache, nausea, and insomnia. The majority of adverse events occurred more frequently in the ribavirin-containing arms of the studies. No differences were observed in overall safety by race. CONCLUSION: A once-daily dosage of ledipasvir/sofosbuvir was similarly effective in black and non-black patients with genotype 1 HCV infection. The addition of ribavirin did not appear to increase SVR12 but was associated with higher rates of adverse events.

Quantifying Eukaryotic Gene Regulation in Hormone Response and Disease.

Quantifying the function of mammalian enhancers at the genome or population scale has been longstanding challenge in the field of gene regulation. Studies of individual enhancers have provided anecdotal evidence on which many foundational assumptions in the field are based. Genome-scale studies have revealed that the number of sites bound by a given transcription factor far outnumber the genes that the factor regulates. In this dissertation we describe a new method, chromatin immune-enriched reporter assays (ChIP-reporters), and use that approach to comprehensively test the enhancer activity of genomic loci bound by the glucocorticoid receptor (GR). Integrative genomics analyses of our ChIP-reporter data revealed an unexpected mechanism of glucocorticoid (GC)-induced gene regulation. In that mechanism, only the minority of GR bound sites acts as GC-inducible enhancers. Many non-GC-inducible GR binding sites interact with GC-induced sites via chromatin looping. These interactions can increase the activity of GC-induced enhancers. Finally, we describe a method that enables the detection and characterization of the functional effects of non-coding genetic variation on enhancer activity at the population scale. Taken together, these studies yield both mechanistic and genetic evidence that provides context that informs the understanding of the effects of multiple enhancer variants on gene expression.