FRIDAY, April 14, 2023 (HealthDay News) -- Multimodal analysis of genome-wide data can diagnose probands with severe, probably monogenic, difficult-to-diagnose developmental disorders, according to a study published online April 12 in the New England Journal of Medicine.
Caroline F. Wright, Ph.D., from the University of Exeter Medical School in the United Kingdom, and colleagues conducted a large-scale sequencing study involving more than 13,500 families with probands with severe, probably monogenic, difficult-to-diagnose developmental disorders. To investigate novel genetic causes, standardized phenotypic data were collected and exome sequencing and microarray analyses were performed. An iterative variant analysis pipeline was developed and candidate variants were reported for validation and diagnostic interpretation. The analyses included 13,449 probands.
The researchers reported 1.0 candidate variant per parent-offspring trio and 2.5 variants per singleton proband, on average. In approximately 41 percent of probands, a diagnosis was made with use of clinical and computational approaches to variant classification; 76 percent had a pathogenic de novo variant. Variants of uncertain significance were identified in genes that were strongly linked to monogenic developmental disorders in 22 percent of probands. The largest effect on the probability of diagnosis was recruitment in a parent-offspring trio (odds ratio, 4.70). The likelihood of receiving a diagnosis was lower for probands born extremely prematurely (22 to 27 weeks of gestation), with in utero exposure to antiepileptic medications, with mothers with diabetes, and for African ancestry (odds ratios, 0.39, 0.44, 0.52, and 0.51, respectively).
"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 write.
Two authors disclosed financial ties to the biopharmaceutical industry.
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