Fine mapping with epigenetic information and 3D structure

Since 2005, thousands of genome-wide association studies (GWAS) have been published, identifying hundreds of thousands of genetic variants that increase risk of complex traits such as autoimmune diseases. This wealth of data has the potential to improve patient care, through personalized medicine and the identification of novel drug targets. However, the potential of GWAS for clinical translation has not been fully achieved yet, due to the fact that the functional interpretation of risk variants and the identification of causal variants and genes are challenging. The past decade has seen the development of great advances that are facilitating the overcoming of these limitations, by utilizing a plethora of genomics and epigenomics tools to map and characterize regulatory elements and chromatin interactions, which can be used to fine map GWAS loci, and advance our understanding of the biological mechanisms that cause disease.

Automated summary

Since 2005, thousands of GWAS have been conducted to identify genetic variants associated with complex traits such as autoimmune diseases. The data from these studies has the potential to improve patient care through personalized medicine and the discovery of new drug targets. However, fully realizing the clinical translation of GWAS has been challenging due to the difficulty in interpreting the functional effects of risk variants and identifying causal variants and genes. Recent advances in genomics and epigenomics tools have helped overcome these limitations by mapping and characterizing regulatory elements and chromatin interactions, allowing for a better understanding of the biological mechanisms underlying disease.