Genetic variation effects on gene expression regulation in autoimmune disease
Study code
DAA205
Lead researcher
Hazel Jones
Study type
Data only
Institution or company
Enhanc3D Genomics
Researcher type
Commercial
Speciality area
Gastroenterology
Summary
The DNA which makes up the human genome has many different functions. Some regions of the genome, called genes, encode molecules that make up our tissues and cells, or which facilitate signalling between them. However, genes are only a small part of the genome. A larger fraction consists of regulatory regions, which control the genes.
Over 99% of the genome is identical between any two individuals, but there will also be some differences, called ‘variants’. Most variants are not found in the genes, but can still influence our risk of contracting a disease, disease progression, or treatment outcomes, by affecting the way the genes are controlled. However, it is technically challenging to identify which genes will be affected by a particular variant, limiting our ability to consider an individual’s genomic information when deciding upon disease diagnosis or treatment approaches.
Using its proprietary analyses, Enhanc3D Genomics can identify the genes which are affected by the variants in people’s genomes. This is done by looking at the way genomes fold up into 3-dimensional structures. We have built a large database which catalogues how genomes should be folded in a wide range of types of immune cell, using multiple different healthy human donors. Enhanc3D Genomics would like to access genomic data from inflammatory bowel disease (IBD) patients and to compare it to the genomic data from these healthy donors. The aim is to see how disease-related variants in patient genomes might affect the way their genomes are folded, to use this information to identify the most important genetic IBD risk factors, and to see if certain cell types are more affected than others. We would also aim to associate treatment response or non-response with patients’ genetic variation. The long-term goal is to match individual patients with the most appropriate treatment course for them.