In a recent study, an international team has found thousands of new regulatory regions that control the expression of disease-linked genes. These findings could propel forward genomics-driven precision medicine, which would help identify the best treatment options for every patient.
A different approach to genetic analyses
To study how human genetic variation can impact the risk of developing a disease, researchers often carry out genome-wide association studies (GWAS). These studies examine a patient’s genome to look for genetic variants that could be associated with a particular condition.
These results can be hard to interpret, as many of these genetic variants regulate the activity of other genes instead of driving the disease itself. To distinguish these regulatory regions from the genes directly contributing to the disease itself, researchers have recently been using expression quantitative trait loci (eQTLs). These eQTLs allow scientists to identify the genes that are directly linked to disease risk. The genes, which are directly linked to disease risk, could ultimately have the potential to be used as drug targets.
Investigating the genes that regulate blood gene expression
In a recent study published in Nature Genetics, a team of researchers from the Garvan Institute of Medical Research used two types of eQTLs to investigate the genetics of gene expression in the blood. The researchers took blood samples from 31,684 individuals and used machine learning algorithms to analyse the genomic data. The team investigated regulatory regions adjacent to the genes of interest through cis-eQTLs. They also investigated genes further away through trans-eQTLs.
Through these two methods, the team identified that 88% of genes had a cis-eQTL effect. In contrast, 32% of genes were found to have a trans-eQTL effect. For more than half of these genes, the team could assign them to a particular disease, such as cardiovascular or immune disease.
“While it is clear that genetic variants are almost always a root cause of disease, the mechanism by which they influence disease is far less clear. For instance, while a specific condition may be linked to hundreds of genetic variants, the vast majority contribute to disease by regulating gene activity,” says co-senior author Associate Professor Joseph Powell, Director of the Garvan-Weizmann Centre for Cellular Genomics and Deputy Director of the UNSW Cellular Genomics Futures Institute.
Future applications – Advancing genomic-driven percison medicine
The team have made their large eQTL resources available to researchers worldwide. This means that the results from this study can serve as a starting point for in-depth interpretation of many complex phenotypes associated with different diseases. Furthermore, these eQTL resources could help identify markers that may help determine what treatments would be most beneficial for a particular patient, creating a big breakthrough for genomic-driven precision medicine.
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