Rare diseases remain a substantial challenge for healthcare systems worldwide, and 80% are attributable to genetic factors. Although exome sequencing (ES) and genome sequencing (GS) have become routine and widely accessible in our current clinical practice due to reduced costs and policy support, progress in systematically capturing deep and structured phenotypic data has lagged behind, limiting diagnostic accuracy. Integrating deep phenotyping with genomic analysis may help close the diagnostic gap. However, its value has not been comprehensively assessed in clinical practice, particularly in the absence of a systematic medical geneticist program in our current clinical settings. We accessed and reviewed the clinical and sequencing data of patients with a rare or suspected genetic disorder assessed at our center between 2022 and 2024. Through detailed case vignettes, we evaluated how granular bedside data influenced the diagnostic outcomes. Expert consensus and literature review were then used to construct a continually updated Recommended Phenotypes Panel and to build a nine-domain framework termed iDREAMS (integrating Deep phenotyping with genetic analysis for Rare disease Evaluation And Management Strategies). Deep phenotyping uncovered diagnostic clues missed by standard assessments across all nine domains, guiding genome analysis, shortening the diagnostic odyssey, and refining counselling in numerous cases. The panel streamlined data capture for clinicians, improved multidisciplinary case discussions, and fed directly into the iDREAMS framework, offering a reproducible pathway from phenotype to genotype. Systematic deep phenotyping is pivotal for closing the “sequencing-analysis” gap in rare disease diagnostics. The iDREAMS framework provides a practical, scalable model that enhances diagnostic accuracy, lowers the entry barrier for resource-limited settings, and extends the reach of precision medicine to patients who had long remained undiagnosed.
Li et al. (Thu,) studied this question.