A new data analysis technique has shown success in identifying the faulty genes that cause rare genetic diseases.

A Struggle for Diagnosis

Despite advances in sequencing technologies, rare disease patients still struggle to receive a diagnosis. Only 30% of patients receive a diagnosis after whole genome sequencing, which is often used as a last resort after exome and panel sequencing fail. All of these technologies struggle to spot the subtle changes in the genome that cause the majority of genetic diseases. These can include slight mutations in healthy genes that do not appear abnormal enough to be flagged up during comparison to the reference genome.

However, a new data analysis approach that compares allele activity could enable subtle disease-causing genes to be identified.

Different Variations of the Same Gene

People inherit two alleles for every gene, one from their mother, one from their father. Alleles are different forms of the same gene; for instance, in your eye colour gene you could have an allele for brown eyes from your father, and an allele for blue eyes from your mother.

Many rare genetic diseases are caused by mutations in a single allele of a gene. Therefore, comparing the activity of a person’s maternal and paternal alleles can flag up any faulty alleles that could be causing a disease. As the maternal and paternal alleles are in exactly the same molecular environment, comparing them eliminates many of the other variables which can affect gene activity. A method known as ANEVA-DOT has been developed to do this. It works by calculating the differences in transcription between the maternal and paternal alleles of each gene and compares the results to the healthy transcription range expected for each gene. ANEVA-DOT flags up any alleles that display any unexpected activity.

Even if multiple genes have abnormal activity, ANEVA-DOT can significantly narrow down the number of genes that need to be tested though other methods.

Testing the System

The ANEVA-DOT system was applied to patients with muscular dystrophy disorders, a genetic muscular degenerative disease. The system successfully identified the disease-causing genes in patients who already had a diagnosis. In patients without diagnosis, the system flagged up several muscle related genes that displayed abnormal activity and could plausibly be linked to muscular dystrophy. One patient was able to receive a diagnosis, after the causative gene was flagged up by ANEVA-DOT.

ANEVA-Dot is now being utilised at a children’s hospital in San Francisco to diagnose newborns with suspected rare genetic diseases.

To find out more about diagnosing rare diseases, read our interview with David Bick, Smith Family Clinic for Genomic Medicine.