More than 4 in 10 participants received a rare disease diagnosis as a result of the analysis.
A new analysis of children with difficult-to-diagnose genetic disorders shows that a genome-driven approach to diagnosis, paired with detailed phenotyping, can significantly improve the likelihood of a diagnosis compared with the previous standard of care.
The report, published in The New England Journal of Medicine, involved more than 13,500 families from the United Kingdom and Ireland.1 In the study, about 41% of probands—the first person in a family identified as having a genetic disorder2— received a diagnosis as a result of the analysis.
As genomic sequencing has become more widely available, it has become an important tool for identifying novel molecular causes for rare monogenic disorders, wrote the study authors.
“Pediatrics has particularly benefited from the use of high-throughput next-generation sequencing technologies, partly because of the high clinical need and potential for lifelong benefit with diagnosis and treatment,” they wrote.
These authors make up one of several diagnostic research groups that have been formed in recent years whose goal is to study the genomics of rare pediatric diseases. Known as the Deciphering Developmental Disorders group, the investigators recruited thousands of families of children with severe, probably monogenic, developmental disorders in an effort to investigate possible genetic causes of the disorders.
In each case, the investigators collected standardized phenotypic data and then performed exome sequencing and microarray analyses. Potentially important variants were communicated to clinical teams for validation and diagnostic interpretation, and then the results were communicated with the families, the authors said.
The analyses yielded a high rate of candidate variants. When the investigators analyzed parent-child trios, they averaged 1.0 candidate variant per trio. On a singleton proband level, they found an average of 2.5 candidate variants. The identification of those variants led to a significant rate of diagnosis among the patient group.
“With the use of clinical and computational approaches to variant classification, a diagnosis was made in approximately 41% of probands (5502 of 13,449), of whom 76% had a pathogenic de novo variant,” the authors said. “Another 22% of probands (2997 of 13,449) had variants of uncertain significance in genes that were strongly linked to monogenic developmental disorders.”
The investigators said the factor that led to the greatest chance of a diagnosis was the ability to analyze an entire parent-offspring trio (the patient and both parents). In such cases, the odds ratio for a diagnosis was 4.70 (95% CI, 4.16-5.31). On the other hand, several factors made a diagnosis less likely, including extremely premature birth, in utero exposure to antiepileptic medications, maternal diabetes, and African ancestry.
“Probands of African ancestry had a particularly low diagnostic yield, owing in part to the lack of ancestry-matched controls to estimate allele frequency and the lower likelihood of being recruited in a family trio,” the investigators explained.
An accompanying editorial, said the findings make a strong case for the benefits of a genome-driven approach to diagnosis, alongside detailed clinical phenotyping.3
“Their study also emphasizes the important role of clinicians and clinical acumen, both on the front end of the physician-patient relationship (in phenotyping) and on the back end (in interpreting whether the implicated variant was indeed pathogenic and in determining the clinical relevance of findings to individual patients and their families),” said Jennifer E. Posey, MD, PhD, and James R. Lupski, MD, PhD, both of the Baylor College of Medicine,
In addition to helping provide answers for individual families, the study authors said their findings have added large amounts of scientific knowledge to the literature. They said more than 290 publications have resulted from the project, 60 new disorders have been identified, and 350 genotype- or phenotype-specific projects have been launched.
“Through its genomic analysis of a large clinical cohort using a hybrid clinical–research model, this study shows how the fusion of clinical expertise, genomic science, and bioinformatics can drive diagnosis and discovery in families in which standard, phenotypically driven diagnostic approaches have failed,” the authors concluded.
1. Wright CF, Campbell P, Eberhardt RY, et al. Genomic Diagnosis of Rare Pediatric Disease in the United Kingdom and Ireland. N Engl J Med. 2023;388(17):1559-1571. doi:10.1056/NEJMoa2209046
2. Proband. National Cancer Institute. Accessed July 12, 2023. https://www.cancer.gov/publications/dictionaries/cancer-terms/def/proband
3. Posey JE, Lupski JR. Genomics in clinical practice. N Engl J Med. 2023;388(17):1619-1620. doi:10.1056/NEJMe2302643