Genomic tool highly effective at detecting rare disease diagnoses

by Murdoch Children's Research Institute

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A newly developed open-source tool designed for rigorous reanalysis of genomic data is highly effective at detecting new rare disease diagnoses. The tool's ability to frequently and automatically reexamine stored DNA data will ensure more timely answers for hundreds of families.

World-leading research has found Talos, created and validated by researchers in Australia and the United States, was able to find rare disease diagnoses at scale, quickly and at low cost, addressing a major bottleneck.

The findings, published in Nature Medicine, noted the tool was remarkably efficient, identifying new genetic diagnoses in more than 200 patients for whom genomic testing had failed to find the cause of their condition. The results also lay the groundwork for AI-enabled approaches in this rapidly growing field of genomic medicine.

The research was led by Murdoch Children's Research Institute (MCRI) and Victorian Clinical Genetics Services (VCGS) in collaboration with the Centre for Population Genomics (a joint initiative between MCRI and the Garvan Institute of Medical Research), the Broad Institute of MIT and Harvard and Microsoft Research.

MCRI Professor Zornitza Stark, also a clinical geneticist at VCGS, said Talos would transform outcomes for patients and families affected by rare disease.

In Australia, genetic conditions, such as muscular dystrophy, affect more than one in every 17 people.

Stark said while genomic testing had revolutionized rare disease diagnosis, more than half of patients remained undiagnosed after their initial test.

"Unlike most medical investigations, genomic data can be stored long term and reanalyzed as knowledge advances," she said. "However, manual reanalysis is labor-intensive, costly and difficult to implement at scale, meaning few patients currently benefit.

"We developed Talos to overcome these barriers by automating the reanalysis process. The tool integrates monthly updates of new knowledge about genes and variants and their role in disease, automatically only flagging potential new diagnoses. This allows the reanalysis process to be scaled to thousands of patients and to be performed frequently."

The researchers first validated Talos using two previously analyzed rare disease cohorts involving 1,089 patients from across the United States and Australia. Talos successfully identified about 90% of already known diagnoses and returned an average of just 1.3 candidate variants per family, demonstrating a high efficiency rate.

Broad Institute Associate Member Kaitlin Samocha, also an assistant professor in the Center for Genomic Medicine at Massachusetts General Hospital and Harvard Medical School, said, "As genetic sequencing becomes a standard part of health care, the backlog of undiagnosed families is growing rapidly. We designed Talos to return only a few variants per patient, reducing the analytical bottleneck and speeding up the time to diagnosis."

For the study, the team then tested Talos in a cohort of 4,735 children and adults with rare diseases. The families had previously undergone genomic testing either through Australian Genomics or VCGS, but diagnosis remained a mystery. Talos identified 241 new diagnoses, delivering a 5.1% additional diagnostic yield across a wide range of conditions spanning neurodevelopmental, cardiac and renal disorders.

More than half of the additional diagnoses resulted from advances in scientific knowledge. The median time for Talos to make a new diagnosis once additional knowledge became publicly available was 32 days, with some diagnoses achieved in as little as one day. The estimated cost was less than USD$12 to run the initial workflow on every 1,000 genomes and then less than USD$2 per year to run the reanalysis monthly.

Importantly, the study noted that the new diagnoses were already having a wider impact on families. Further testing has already taken place in more than 50 additional family members, informing surveillance, treatment and reproductive decision-making, particularly for inherited heart conditions.

Professor Daniel MacArthur, director of the Centre for Population Genomics, said the findings highlighted the rapid pace of genomic discovery and the importance of systematic reanalysis.

"Every year, hundreds of new gene-disease associations and thousands of new variant interpretations are published," he said. "Automated reanalysis allows us to translate that knowledge into real clinical benefit for families much faster than traditional models."

The work also establishes foundations for the integration of artificial intelligence tools into the diagnosis of genetic conditions, a focus of the newly formed Australian Alliance for Secure Genomics and AI in Rare Disease (AASGARD) consortium, led by MacArthur and his team.

Microsoft Research Principal Researcher Jeremiah Wander said: "Talos is open-source, auditable and designed to run on standard computing infrastructure, with low ongoing costs when deployed at scale. The study provides critical evidence to inform future policy around rare disease diagnostics."

Annabelle, 5, has ReNU syndrome, a rare genetic disorder that causes severe intellectual and physical disabilities. She is visually impaired, nonverbal and has significant developmental delays. Until about a year ago, she also experienced frequent seizures.

Kiera said there were no signs before birth that Annabelle would face lifelong health challenges.

"Within 24 hours of being born, Annabelle was taken to The Royal Children's Hospital's Intensive Care Unit," she said.

"Annabelle couldn't breathe or eat on her own, and without modern medicine she would have died. It took six weeks for doctors to stabilize her before we could take her home. We had no answers at that point besides the suspicion she had an undiagnosed genetic condition."

Annabelle was enrolled in the Acute Care Genomics study, led by MCRI and VCGS, which delivers ultrarapid genomic testing for critically ill newborns with suspected genetic conditions.

Her genomic data was kept on file and reanalyzed years later using Talos. ReNU syndrome was identified in 2025, and soon after, Annabelle received a diagnosis thanks to the tool.

"Having a severely sick child is extraordinarily overwhelming and traumatizing," Kiera said. "A diagnosis helps provide a framework among the chaos and uncertainty. It also means you're not left blaming yourself for something that happened entirely by chance."

Kiera said Talos would ensure families impacted by rare disease received more timely answers.

"Annabelle experienced frequent seizures for years, seizures that, left uncontrolled, cause permanent brain damage," she said. "Knowing her diagnosis sooner could have led to earlier, more targeted seizure management."

Kiera said having a diagnosis meant she could also connect with other affected families.

"The diagnosis connects you to a community of families who truly understand," she said. "When you have a child with a rare disease, the isolation is profound. Finding others who are living the same reality makes an enormous difference."

To help manage her condition, Annabelle has weekly therapy sessions, including physio and speech, as well as taking multiple medications to control her seizures.

"Developmentally, Annabelle functions at the level of a 6-month-old baby, requiring around-the-clock care," Kiera said.

"She just started at a specialist school, which almost seemed impossible a year ago. Any improvement, even small gains in awareness or comfort, is meaningful beyond words. And the way medicine is moving, that gives us real hope."

Publication details

Matthew J. Welland et al, Automated reanalysis of genomic data for rare disease diagnostics at scale, Nature Medicine (2026). DOI: 10.1038/s41591-026-04477-5

Journal information: Nature Medicine

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Clinical geneticsChildren's healthPediatrics Provided by Murdoch Children's Research Institute Who's behind this story?

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