New genetic analysis has reanalysed existing data to try and pinpoint the genetic variants that cause 12 different immune-mediated diseases, such as inflammatory bowel disease, multiple sclerosis, and rheumatoid arthritis.
A hospital room. Image credit: Max Pixel, CC0 Public Domain
This new research, from the Wellcome Sanger Institute and collaborators, shows that fine-mapping using regulatory quantitative trait loci (QTLs) is more accurate at predicting disease causal variants than using genome-wide association studies (GWAS) alone.
The study, published in Nature Genetics, found that adding these regulatory data produces biologically relevant predictions of the causal variants. This information could be used to help develop new drugs for immune-mediated diseases by targeting the molecular mechanisms impacted.
Also, the researchers found that particular classes of variants, mainly INDELs1 are underrepresented in genome-wide association studies and that the data produced are much more accurate when the whole genome sequences are available.
Immune-mediated diseases are chronic health conditions that affect up to 9.4 per cent of the world population2. While genome-wide association studies, known as GWAS, have discovered thousands of genetic variants that are associated with these diseases, they do not show which one is the cause and the molecular mechanism through which these variants lead to disease risk.
Regulatory trait loci, known as QTLs, are specific regions of DNA that are associated with certain regulatory traits, such as gene expression. It is possible to show which genetic variants are related to which gene in a certain tissue using QTL mapping. If these QTLs are co-localised to a genomic region shown to be associated with the disease, identified by GWAS, there is a higher probability that they are the causal variants and gives information on their molecular mechanism.
This new research, from the Wellcome Sanger Institute and collaborators, reprocessed the data collected from previous projects that focused on three types of immune cells: monocytes, neutrophils, and T cells.
From the data, they identified 340 genetic loci that could be linked to 12 different immune-mediated diseases. They fine-mapped these loci and identified the genetic variants that were most likely to be the cause of the disease.
To increase the resolution of their study, they harnessed information derived from multiple layers of regulatory data and marked the molecular switches that regulate the activity of human genes. When they used these data, they were able to refine the location of causal variants by more than three times.
By combining these genetic data, the team identified functionally important variants and suggest these for further biological study. As an example, the researchers suggest possible causal variants in the ITGA4 gene for inflammatory bowel disease.
In addition to this, they revealed that specific classes of causal variants, particularly a type known as INDELs, are systematically under-represented in current studies, widening the spectrum of genetic variants to consider.
QTL mapping requires a much smaller number of study individuals compared to GWAS studies – hundreds as opposed to tens of thousands – meaning they could be more economically viable in some cases of research and still give important biological information about the cause of disease.
Source: Sanger Institute