In 2021, the Indian Undiagnosed Diseases Program was initiated for patients without a definite diagnosis despite extensive evaluation in four participating sites. Between February 2021 and March 2023, a total of 88 patients were recruited and underwent deep phenotyping. A uniform methodology for data re-analysis was implemented as the first step prior to conducting additional genomic testing. The largest cohort was of 38 patients with neurodevelopmental disorders (NDD). A genetic diagnosis was achieved in 24 of the 88 patients (27.2%), including 7 cases within the NDD cohort. Factors contributing to the increased diagnostic yield included: (a) identification of a novel disease association in DAAM2 gene, and (b) limitations of the standard analysis pipeline, particularly for synonymous variants in SELENOI and KIAA0753 genes, non-frameshift variant in GLRX5 gene, low-coverage variant in GJC2 gene, large deletions in PCNT and PHKG2 genes, and intronic variants in VPS33B and FBN1. Improved phenotyping led to a diagnosis in three cases, while genomic variants missed in the previous bioinformatics analysis were identified in 12 cases. The study also contributed to the development of enhanced bioinformatics scripts for variant prioritization and more refined literature search for novel disease associations. It highlights the importance of incorporating data reanalysis into clinical workflows before pursuing advanced diagnostic tests, particularly in resource-limited settings where healthcare expenses are often borne out of pocket.
Keywords: DAAM2; KIAA0753; Indian; bioinformatics; neurodevelopmental; next generation sequencing; reanalysis; undiagnosed.
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