Complex and Genetic Disease Research
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.
Featured Research Stories
FMRIはイルミナの新しいエクソーム濃縮を用いてゲノム研究の効率向上を実現しています
Future Medicine Research InstituteのChief ResearcherであるSookyoung Kim氏がIllumina DNA Prep with Exome 2.0 Plus Enrichmentの評価結果について語ります。
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See How Genomics Empowers Breakthroughs in Complex and Genetic Disease Research
Disease Association Studies
Genome-wide association studies uncover common and rare variants associated with disease
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Gene Target Identification and Pathway Analysis
Differential Expression Analysis
Differential expression analysis measures changes in gene expression under different conditions or in response to determinite stimuli.
Expression Anaysis by RNA-Seq Provides:
- Quantitative changes in expression across the transcriptome in different conditions
- The ability to profile disease state changes and responses to therapeutics
Quantitative trait loci (QTL)
Quantitative trait loci (QTL) analysis identifies molecular markers that correlate to a quantitative change in a particular trait or dynamic outcome.
QTL Analysis Provides:
- Immediate insight into a probable biological basis for disease associations
- Identification of gene networks involved in disease pathogenesis
Epigenetic Analysis
Epigenetic analysis elucidates the biological mechanisms that alter gene activity resulting from non-coding variation and the environment.
Epigenomic Analysis Provides:
- Insight into disease mechanisms for non-coding variants
- A genome-wide view of changes and patterns in regulatory mechanisms
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Polygenic Risk Scoring
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.
Polygenic risk scores have the potential to:
- Stratify patients for clinical trials
- Stratify samples for cohort analysis
- Assess an individual’s heritable risk for disease