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Genome Sequencing Boosts Diagnostic Yield in Children With Unexplained Medical Complexity

21.10.2020

NEW YORK – Genome sequencing led to new genetic diagnoses for nearly a third of children with unexplained complex medical conditions, a study by researchers in the US and Canada has found.

Children with medical complexity (CMC) have at least one chronic condition, depend on a technological tool like a ventilator or require intravenous nutrition or drugs, are under the care of multiple subspecialists, and have substantial healthcare use. For many of these patients, a genetic cause for disease is suspected but often not found through conventional genetic testing.

Researchers led by the Hospital for Sick Children's Robin Hayeems conducted a cohort study to examine the analytical and clinical validity of genome sequencing as a diagnostic test for CMC. As they reported on Tuesday in JAMA Network Open, they sequenced the genomes of 49 patients and some of their family members and determined new molecular genetic diagnoses for 15 of the children.

"This study suggests that genome sequencing has high analytical and clinical validity and can result in new diagnoses in CMC even in the setting of extensive prior investigations," Hayeems and her colleagues wrote in their paper, adding that "[g]enome sequencing is a potentially first-tier genetic test for CMC."

For their study, the researchers recruited families taking part in a structured complex care program. Following medical record review, 143 families met eligibility criteria, and 54 of them were interested and met additional criteria. Patients were eligible if they were thought to have an underlying genetic condition that had not been identified through conventional genetic testing.

In all, 138 individuals from 49 families underwent genome sequencing, including 40 parent-child trios.

As the children previously underwent a mean of four conventional genetic tests, some of their genetic variants, mostly categorized as benign or variants of unknown significance, were known. Sequencing analysis identified all 124 such variants, which, the researchers said, indicates genome sequencing has high analytical validity. 

Fifteen of the 49 probands received a new primary molecular genetic diagnosis following sequencing analysis, representing a diagnostic yield of 30.6 percent. 

One patient, for instance, had a maternally inherited single-exon duplication in the KDM6A gene on the X chromosome that causes Kabuki syndrome, which was not detected by chromosomal microarray analysis, exome sequencing, or a multiplex ligation-dependent probe amplification test of the gene.

Three other children had novel genetic conditions, including a RAC3-related disorder and two novel autosomal dominant neurodevelopmental syndromes. Nine patients had either ultra-rare genetic conditions or very rare genetic conditions with one or more atypical features. Five of these diagnoses had associated management and surveillance recommendations or interventions, and one child with uridine-responsive epileptic encephalopathy was started on a targeted therapy.

In addition, four diagnoses had reproductive counseling implications as there was a sibling recurrence risk of at least 25 percent, while the others appeared to be due to de novo variants and have a low recurrence risk. 

While the researchers noted that this study has a number of limitations — it was a single-center study and the criteria for enrollment in a structured complex care program differ by institution — they added that their findings support the use of genome sequencing as a first-tier genetic test in children with medical complexity. "Genome sequencing has the potential to increase the proportion of CMC for whom diagnoses are established," they wrote.

They added in their paper that additional omics tools like RNA-seq and genome-wide methylation analysis could potentially further boost diagnostic yield for these patients in the future.


Source: https://www.genomeweb.com/sequencing/genome-sequencing-boosts-diagnostic-yield-children-unexplained-medical-complexity#.X5Ayd9AzaUn

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