UCLA

Investigating the genetic causes of disease allows for better understanding of disease pathology, and can lead to improved prevention, detection, and treatment of these diseases. In this dissertation I focus on investigations into the genetic architecture of two rare diseases, congenital heart disease (CHD) and coccidioidomycosis (also known as Valley Fever). First, I investigate CHD genetics. One percent of babies are born with congenital heart birth defects, defined by a failure of normal heart development leading to significant physiological defects. Only 30% of cases have a known, single-gene, pathogenic mutation associated with the CHD phenotype. All phenotypes have genetic and environmental contributions to them though. Thus, for a large proportion of individuals, we do not know what the genetic contribution is to the birth defect. We used a trio-based cohort of individuals that contains probands with CHD that remain genetically undiagnosed. We asked whether common variants can have an effect on disease phenotype presence and severity. We use genome-wide association (GWAS) data on CHD endo-phenotypes from publicly available datasets to develop polygenic risk scores (PRS) correlating with disease risk and disease severity. We find that PRS estimated using a GWAS for heart valve problems and heart murmur explain 2.5% of the variance in case-control status of CHD (all SNVs p=7.90e-3, fetal cardiac SNVs p=8.00e-3), and 1.8% of the variance in severity of CHD (fetal cardiac SNVs p=6.20e-3, all SNVs p=0.015). These results show that common variants captured in CHD phenotype-matched GWAS have a modest, but significant contribution to phenotypic expression of CHD. As a second project, I investigate the genetics of susceptibility to severe manifestations of coccidioidomycosis. Currently, it remains unknown why some individuals get more severe Valley Fever infections than others. Coccidioidomycosis, or Valley Fever, is a caused by a fungal infection with Coccidiodes Immities or Posadasii, which are endemic to the Southwest United States and parts of Central and South America. While 60% of people who inhale the fungal spores are asymptomatic (and thus often are not even reported), 40% of people develop a pneumonia-like infection. Most people recover, but a subset of the population develops chronic pulmonary disease and an even smaller number of people, 1% of all infected people, develop disseminated infections which spread to other areas of the body and can lead to meningitis and death. Treatment involves prolonged antifungal use, which contains the infection but has numerous side effects after long-term use. So, it is imperative we develop better ways to detect patients at risk for severe disease and then treat those patients. We use a cohort of Valley Fever patients to look at the genetic causes of having more severe phenotypes. Our dataset is split into patients with uncomplicated Valley Fever (UVF), chronic pulmonary coccidioidomycosis (CPC), and disseminated coccidioidomycosis (DCM). For the purposes of this study we considered UVF patients to be controls, as these patients recover without prolonged antifungal treatment. There is no large cohort of patients who have established coccidioidomycosis infection but without any symptoms. We show that having African genetic similarity is associated with increased risk of severe disease. We also explain how African genetic similarity does not necessarily correlate with self-identified race and ethnicity (SIRE) or skin-color. We also identify identity-by-descent segments shared by individuals with severe disease that may contain risk variants for developing severe disease. In conclusion, I present here a dissertation focused on the genetics of two rare conditions: congenital heart disease and of susceptibility to severe coccidioidomycosis. Researching rare diseases is important because although they affect a smaller proportion of the population, they can have a severe effect on the lives of the individuals with these diseases. In addition, collectively all rare-disease patients around the world represent over 350 million people and represent a significant disease burden. Finally, understanding the genetics of rare disease can help us understand and interpret genetic variation contributing to rare diseases.