Deciphering the four-letter code : The genetic basis of complex traits and common disease

Abstract

Deoxyribonucleic acid (DNA) is made up of four bases: adenine (A), cytosine (C), guanine (G), and thymine (T). Assembled in a strategic fashion, these bases code for the unique genomes of all walks of life, from viruses, to rodents, to primates. The human genome, mapped completely for the first time in April of 2003, is 3 billion bases long and contains approximately 20,000 genes.

The genome of a randomly selected individual, checked base by base, will be approximately 99.9% identical to the reference map of the human genome. The other 0.1% (roughly 3 million bases total) will contain changes in the DNA that do not match to the canonical reference genome. These changes, or genetic variants, can have biological consequence, as they can impact the shape and function of the proteins for which genes code. Genetic variation accounts for much of the visible (phenotypic) diversity – such as eye color or height – that can be observed in humans today. Such variation also plays a role in susceptibility to disease in humans.

In the last ten years, a major breakthrough in identifying the genetic changes that increase risk of disease has been genome-wide association studies (GWAS). In these studies, genetic variants (called single-nucleotide polymorphisms, or SNPs) observed in individuals with a particular trait or disorder (affected individuals) are compared to genetic variants observed in healthy (unaffected) individuals. SNPs that are observed more often in affected individuals than in unaffected individuals are associated to increased disease risk. They mark regions (called “loci”, singular “locus”) of the genome that can contain clues about a disease. Knowing which genes in a locus, when mutated, can increase risk of disease is a crucial first step in understanding why certain people are susceptible to disease while others are not. To date, GWAS have identified more than 7,000 loci that influence risk of disease. The primary goal of the work in this thesis is to identify genetic variants associated to risk of common disease. Finding such mutations can help identify disease-causing genes, potentially improving our ability to prevent, properly diagnose or treat illness in humans.