Plate Nº 71 · recorded September 29, 2026
Health & Medicine ResearchReported finding
New RNA Testing Guidance Could Deliver Clearer Genetic Diagnoses
International guidance co-led by University of Otago researchers sets thresholds for RNA splicing tests, helping clinicians decide whether genetic variants cause disease.
By Priya Raman4 min read770 words
In brief
- Researchers reviewed more than 41,000 genetic variants across 5,458 genes to build evidence-based RNA testing recommendations.
- Well-designed minigene assays matched direct patient RNA testing with complete or high agreement in 89% of comparable cases.
- Variants producing 80% or more abnormal RNA strongly indicated a disease-causing effect; 20% or less strongly argued against it.
People with suspected inherited diseases often face a frustrating bottleneck after genetic testing: a DNA variant is found, but no one can say whether it actually causes disease. New international guidance co-led by University of Otago researchers could change that, giving clinicians clearer rules for interpreting a specific class of RNA-based tests and, ultimately, helping more patients receive a definite diagnosis.
The study, published in Genome Medicine, focuses on RNA splicing — the biological process by which cells join sections of RNA together before using its instructions to build proteins. RNA is the molecule that carries instructions from DNA to the protein-making machinery of the cell. Some genetic variants disrupt splicing and shut down a gene's function, so examining RNA can provide direct evidence about whether a variant is harmful.
A numbers problem
Genetic testing can identify thousands of DNA differences, or variants, in a single person. For each one, clinicians must judge whether it is harmless or disease-causing.
"This is one of the major challenges in clinical genomics," says Dr. George Wiggins of the University of Otago's Faculty of Medicine-Christchurch, who co-led the study with researchers in Australia and Spain. His Otago colleagues, professor Logan Walker and associate professor John Pearson of the Department of Pathology and Molecular Medicine, also contributed.
To build the new recommendations, the team reviewed more than 41,000 genetic variants across 5,458 genes from published studies that used laboratory models called minigene assays. These models recreate the parts of a gene involved in splicing and prove especially useful when RNA cannot be collected directly from a patient — for example, when the relevant tissue is inaccessible.
What the analysis found
The results were encouraging for well-designed traditional minigene assays. Where results from these lab models could be compared with tests using RNA taken directly from patients, the two approaches showed complete or high agreement in 89% of cases. That level of consistency suggests carefully constructed minigene tests can stand in for direct RNA testing when patient tissue is unavailable.
High-throughput tests, which assess very large numbers of variants at once, fared worse. Of seven high-throughput datasets the team assessed, only one showed characteristics considered suitable for direct clinical use.
"These findings show that well-designed RNA-based assays can provide strong evidence for the effect of a genetic variant, while caution should be applied when assays have important design limitations," Wiggins says.
Clear thresholds
The researchers also compared their laboratory findings with clinical classifications in ClinVar, an international database of genetic variants. Two thresholds emerged. Variants that produced 80% or more abnormal RNA provided strong evidence that a variant was disease-causing. Variants producing 20% or less abnormal RNA provided strong evidence against a disease-causing effect. Between those markers lies a zone of uncertainty that clinicians will need to weigh alongside other data.
The study also connects lab evidence to computational prediction. Minigene results improved predictions made by SpliceAI, an artificial intelligence tool that forecasts whether a variant will disrupt splicing. The researchers identified thresholds that could help laboratories distinguish variants likely to have little effect from those likely to cause significant disruption.
From lab bench to clinic
These findings feed into the internationally recognized framework that clinical laboratories already use to classify genetic variants. RNA evidence, when carefully calibrated, can add weight to that classification process.
"Our study provides clinicians with greater certainty about results from specific RNA-based tests, allowing them to better understand the effect a DNA variant has on the fundamental biological process of RNA splicing," Wiggins explains.
The recommendations extend beyond interpretation. They include practical guidance for laboratories on designing and validating RNA tests, assessing how well those tests perform, presenting results, and deciding how much weight the findings should carry in clinical decision-making.
The stakes are tangible. A confirmed diagnosis can open the door to earlier intervention and inform decisions about a patient's wider family, or whānau — the term the researchers use for family connections in Aotearoa New Zealand.
"Ultimately, incorporating these results within an appropriate framework will improve accuracy and variant classification, pave the way for earlier intervention, and increase the number of patients who receive a genetic diagnosis," Wiggins says.
As with any guideline built on retrospective review, adoption will depend on individual laboratories implementing the recommendations and validating them in their own settings. The study's authors argue the payoff justifies the effort: fewer unresolved results, and more patients with answers.
The paper, led by Daffodil M. Canson and colleagues, appears in Genome Medicine (2026), DOI: 10.1186/s13073-026-01746-3.
via Medical Xpress (Source)
More from Priya Raman
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Senior reporter covering industry trends and analytics at SciBeat.
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