INVESTIGATING COMPUTATIONAL METHODS TO MODEL THE GENOTYPIC AND PHENOTYPIC COMPLEXITY OF ADVERSE HEALTH OUTCOMES: UNDERSTANDING UNDERCOVER HERITABILITY

Open Access
Author:
Verma, Shefali Setia
Graduate Program:
Integrative Biosciences
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
March 19, 2018
Committee Members:
  • Marylyn Deriggi Ritchie, Dissertation Advisor
  • Shaun A Mahony, Committee Chair
  • Stephen Wade Schaeffer, Committee Member
  • Cooduvalli S Shashikant, Committee Member
  • William S. Bush, Outside Member
Keywords:
  • Association Studies
  • GWAS
  • Rare Variants
  • Common Variants
  • Epistasis
  • Genetic Etiology
  • Complex Traits
  • Heritability
Abstract:
Genome-wide association studies (GWAS) are the most popular and widely conducted experiments to understand the genetic architecture of common diseases. Though GWAS have been successful in identifying many common genetic variants associated with common complex diseases, these studies have some shortcomings in explaining genetic heritability (specifically the broad-sense heritability). Thus, the genetic architecture of complex diseases can be further understood by exploring dominance and interacting variance components along with additive effects. Testing of common variants to understand genetic etiology of common diseases is commonly referred to as Common Disease Common Variants (CDCV) hypothesis where it is believed that many high frequency, or common genetic variants could have large effects on common disease risk. Due to the low cost of sequencing and advancement in technology, a plethora of sequencing data has also been generated which helps in identifying the low frequency or rare genetic variants. Another alternative hypothesis, the Common Disease Rare Variant (CDRV) hypothesis, suggests that low frequency (or rare) variants with high penetrance could largely affect the susceptibility to common genetic diseases. Many pieces of evidence for CDCV and CDRV hypotheses exist in the literature. Thus, both common and rare variant association studies (GWAS and Rare Variant Association Studies or RVAS) have shown importance in understanding missing heritability. To no surprise, it is likely that missing genotypic variance components can be explained by studying common and rare variants together and by integrating both additive and non-additive effects. The aims described in this thesis, address some of the challenges associated with additive and non-additive effect detection in common and rare genetic variants to apply them to dissect the heritability for a disease trait –steps towards uncovering the mystery of heritability.