Beyond the molecular diagnosis: clinically relevant findings from genomic reassessment in patients with Prader-Willi syndrome

Abstract Prader-Willi syndrome (PWS) results from loss of paternal gene expression at chromosome 15q11.2-q13. Conventional testing reliably establishes the diagnosis and defines the molecular class but may not resolve complex chromosome 15 architecture or detect genome-wide variation relevant to medication response and other clinical risks. Historical results generally remain the basis for lifelong classification without re-evaluation as technologies advance. We evaluated whether genome sequencing (GS) could add clinically useful information beyond molecular confirmation of PWS. Fifty individuals underwent GS through a fully remote, registry-enabled study integrating structural, copy-number, small-variant, pharmacogenomic, phenotype, and medication-history analyses with multidisciplinary interpretation, genetic counseling, and return of selected findings. Overall, 34/50 participants (68%) had at least one finding beyond that provided by conventional PWS testing. GS revealed previously unresolved or more complex chromosome 15 architecture in 13/50 participants (26%), refined or resolved molecular subtype assignments in 8/50 (16%), identified guideline-supported pharmacogenomic recommendations in 20/48 (41.7%), detected ACMG secondary findings in 2/47 (4.3%), and identified additional variants for clinically contextualized return in 12/47 (25.5%); categories were not mutually exclusive. In the largest GS PWS cohort reported to date, GS improved resolution of the disease-causing locus while identifying additional findings relevant to prescribing, surveillance, and individualized clinical evaluation. These results support genomic reassessment as a means of refining longstanding molecular classifications and identifying clinically relevant variation beyond the primary diagnosis, whilst demonstrating the feasibility of comprehensive genomic interpretation and responsible return of results through a fully remote framework.