Study provides deep insights into the association between genes and diseases

A team of international scientists examined genomic data from more than 30,000 individuals and unraveled thousands of new regulatory regions that regulate disease-linked genes—a resource that is now made available to scientists globally.

(L-R) Jose Alquicira, Dr Seyhan Yazar, A/Professor Joseph Powell. Image Credit: Garvan Institute of Medical Research.

The research was co-led by the Garvan Institute of Medical Research. The observations are a great step for genomics-driven precision medicine and can help pinpoint markers that indicate which patients will benefit better from which treatment. The research was published on September 2^nd, 2021 in the journal Nature Genetics.

In this study we have provided an entirely new view of genetic regulation by uncovering an in-depth picture of how genes and disease are linked. It is the most comprehensive analysis of how human genetic variation affects gene expression to date.”

Joseph Powell, Study Co-Senior Author, Associate Professor, and Director, Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research

Joseph Powell is also the Deputy Director of the UNSW Cellular Genomics Futures Institute.

“Our discovery provides researchers an entirely new perspective on their genes of interest and will help prioritize genes that may be more relevant for therapeutic intervention. It could also lead us to better markers for tracking disease progression and the efficacy of medicines,” adds co-senior author Professor Lude Franke from the University Medical Centre Groningen, Netherlands.

New insight on gene activity

To analyze how human genetic variation affects the risk of disease, scientists mostly undertake genome-wide association studies, which scan the genomes of patients and hunt for genetic variants more commonly linked with a particular condition.

However, interpreting these results is not straightforward—rather than directly driving disease, most of the genetic variants regulate the gene activity, influencing the amount of protein production.

By identifying these regulatory regions, called expression quantitative trait loci (eQTLs), scientists could get a better understanding of which genes directly contribute to disease risk and the genes that could be aimed with precision treatments.

In the current research, scientists employed specialized machine learning algorithms to examine genomic data from the blood samples of 31,684 people.

“Thanks to the statistical power of this large dataset, we were able to uncover new regulatory regions on the human genome. Instead of just cataloging the regulatory gene locations that were adjacent (known as cis-eQTLs), we were able to reveal genes that modulated the activity of more distant genes (known as trans-eQTLs),” remarks associate professor Powell.

The researchers analyzed millions of genes and discovered that 88% had a cis-eQTL effect and that 32% of genes also had a trans-eQTL effect more distant in the genome, the majority of which was assigned to a biological impact, like immune and cardiovascular diseases.

Uncovering new genomic links to disease

While it’s 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.”

Joseph Powell, Study Co-Senior Author, Associate Professor, and Director, Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research

Associate professor Powell further says, “Understanding which genes this regulation ‘converges’ on will be invaluable to identify targets for new potential medicines. If a pharmaceutical company develops a therapy that targets a certain molecule, our resource can help identify how its expression is regulated and if the genetic background of different patients is likely to impact its efficacy.”

“What we’ve discovered is an entirely new level of genomic information, providing a deeper understanding of biology and disease,” he concludes.