Auto-immune diseases, such as lupus, are frequently genetically complex and can be caused by different mutations in many different genes, making it hard to identify the pathway that leads to these diseases. Correctly identifying the genetic cause of lupus in an individual is important when choosing a precision therapy for them. When diseases that develop in different ways have very similar symptoms, yet have very different treatments, how do doctors decide how to proceed? New research from an international collaboration of medical researchers, clinicians and bioinformaticians at the Centre for Personalised Immunology, headquartered at The Australian National University, has identified rare variants in two genes that cause a particular form of lupus, which reveals exactly how it should be treated.

The team has collected genome data from individuals that suffer from systemic lupus erythrematosis to build the largest dataset of its type for this disease in Australia. Within the group of lupus sufferers, they identified rare mutations in lupus-associated genes, mutations which have been shown to increase the patterns of inflammation typical of this disease. A key part of this research conducted by the Centre for Personalised Immunology was the collection and sequencing of over 4000 patient genomes.

Processing and analysis of this significant dataset was accomplished using NCI’s computing and data expertise. Access to the computational resources of NCI was an essential factor that allowed the team to make their findings.

Bioinformatician Dr Dan Andrews from the John Curtin School of Medical Research says, “Having access to NCI’s world-class supercomputing and data storage simplifies so much of the research process. We can do so much more scientific work by fully making use of the amazing capacities available to us just across the road.

“NCI solves so many problems for us that other research teams just have to deal with themselves. We have stored and processed over 4000 human genomes, and haven’t even scratched the surface of what we can learn from them yet.”

The research team is now working on finding other genes and variants that lead to diseases like lupus. Given the complexity of both the disease and the human genome, the more supercomputing power they can put behind the project the better.

This research highlight was originally published in the 2018-2019 NCI Annual Report.