Complex diseases are caused by a combination of genetic and environmental factors, many of which are not fully understood. Although some complex diseases can be highly heritable, many do not follow specific, clear models of inheritance and are not often the result of a single mutated gene. In fact, >90% of disease associated variants are located in non-coding regions of the genome.1 Roughly 5% of complex diseases are caused by monogenic inheritence, while the vast majority is polygenic.2 Autoimmune and rheumatic diseases, atherosclerosis and many forms of heart disease, neurological disorders, and psychiatric disorders are all types of disease that fall into this category.
Given their multifactorial nature, researching complex diseases has proven challenging. Luckily, genomics technologies, including arrays and next-generation sequencing (NGS), are helping accelerate research and are paving the way to achieve greater understanding of disease etiology and, hopefully one day, the diagnosis, treatment, and prevention of these diseases.
The century-old institution is taking its research global, collecting international samples to find disease-associated variantsRead Article
Ms. Sookyoung Kim, the Chief Researcher, Future Medicine Research Institute discusses the results of her evaluation of Illumina DNA Prep with Exome 2.0 Plus Enrichment.Read Interview
The winner of Illumina’s Polygenic Risk Scores Research Grant aims to find outRead Article
Genome-wide association studies uncover common and rare variants associated with disease
Differential expression analysis measures changes in gene expression under different conditions or in response to determinite stimuli.
Quantitative trait loci (QTL) analysis identifies molecular markers that correlate to a quantitative change in a particular trait or dynamic outcome.
Epigenetic analysis elucidates the biological mechanisms that alter gene activity resulting from non-coding variation and the environment.
A polygenic risk score represents an approximation of an individual’s genetic risk for disease, based on the sum of the risk alleles for a disease trait, relative to the population.