Date of Graduation

2017

Document Type

Dissertation

Degree Type

PhD

College

Eberly College of Arts and Sciences

Department

Political Science

Committee Chair

Jeff Worsham

Committee Co-Chair

John Kilwein

Committee Member

Warren Eller

Committee Member

Dave Hauser

Committee Member

Patrick Hickey

Committee Member

Matthew Jacobsmeier

Abstract

Primary immune deficiencies (PIDs) are genetic disorders that lead to defects in normal immune responses. While the causative gene for many of the more severe defects is known, new defects leading to additional syndromes are being described with increasing frequency. The most common group of PIDs are the primary antibody deficiencies (PADs), which manifest with low serum immunoglobulin levels, defective responses to vaccinations, and, for most, recurrent infections. In this work, we explore the genetic basis of common variable immune deficiency (CVID), the most common symptomatic PID, and related PADs using next-generation sequencing technology. In a large cohort of patients with CVID, we demonstrate that targeted screening of known PID-causing genes using a customizable filter for whole exome sequencing is a fruitful approach. We examine genetic heterogeneity in our cohort, identifying new gene candidates, including IKZF1, PAX5, DOCK11, and BRWD1. Through analysis of genetic heterogeneity, we also identify damaging mutations in LIG1 and subsequently provide the first in-depth description of immune deficiency caused by recessive mutations in this gene in three kindreds. Lastly, we turn our attention to genetic homogeneity in our CVID cohort by first addressing the need to efficiently remove non-pathogenic variations from patient exomes. We describe a new filtering approach using blacklists that is highly efficient at removing non-pathogenic variants from exomes with an extremely low false-negative rate. We then apply this blacklist approach in a custom automated pipeline to identify enrichment of known and novel gene candidates in rare disease cohorts, including CVID. Overall, this work presents a detailed analysis of known and novel genetic variation in the most common symptomatic congenital immune deficiencies and provides new computational tools for analysis of these and other genetic syndromes.

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