Journal of the Endocrine Society · 2026
Phenotyping and hierarchical clustering in genetically unresolved DSD identifies distinct multisystem clinical subgroups-a DSDgene study.
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Kouri Chrysanthi, Allimussina Malika, Ahmed S Faisal, Flück Christa E
Аннотация
CONTEXT: A substantial proportion of individuals with differences of sex development (DSD) remain without an identifiable molecular diagnosis. Systematic phenotyping may reveal clinically relevant patterns and inform genomic investigation.
OBJECTIVE: To identify phenotypic patterns among individuals with genetically unresolved DSD and determine whether multisystem anomalies form distinct clinical clusters and exhibit overlap with established DSD-associated conditions.
DESIGN: Data from the I-DSD Registry were analyzed for individuals with 46,XY or 46,XX DSD lacking a molecular diagnosis. A 3-part approach was used: (1) unsupervised hierarchical clustering based on Gower distance; (2) supervised phenotype-guided classification using reference profiles for NR5A1/SF-1 deficiency and P450 oxidoreductase deficiency (PORD); and (3) exploratory comparison with Human Phenotype Ontology (HPO)-derived profiles of established DSD-associated genes.
RESULTS: Among 1391 screened individuals, 345 (24.8%) fulfilled inclusion criteria, including the presence of at least 1 additional organ anomaly, 83.8% had a 46,XY karyotype. The most frequent associated findings were small for gestational age (28.1%), cardiac anomalies (21.4%), central nervous system (CNS) (15.7%), and renal anomalies (14.5%). Unsupervised clustering identified 5 phenotypic groups, including craniofacial-dominant and CNS-dominant clusters. Phenotype-guided classification showed overlap with SF-1-deficiency-associated phenotypes in 11% of cases and with PORD-associated phenotypes in 22%. Comparison with HPO-derived profiles of 81 DSD-associated genes demonstrated phenotypic similarities between several clusters and known gene-associated anomaly spectra.
CONCLUSION: Systematic phenotyping identifies recognizable patterns of multisystem involvement in genetically unresolved DSD. Several clusters overlap with established DSD-associated conditions and gene-specific anomaly profiles, supporting phenotype-driven surveillance, multidisciplinary care, and informing future genomic re-evaluation strategies.
OBJECTIVE: To identify phenotypic patterns among individuals with genetically unresolved DSD and determine whether multisystem anomalies form distinct clinical clusters and exhibit overlap with established DSD-associated conditions.
DESIGN: Data from the I-DSD Registry were analyzed for individuals with 46,XY or 46,XX DSD lacking a molecular diagnosis. A 3-part approach was used: (1) unsupervised hierarchical clustering based on Gower distance; (2) supervised phenotype-guided classification using reference profiles for NR5A1/SF-1 deficiency and P450 oxidoreductase deficiency (PORD); and (3) exploratory comparison with Human Phenotype Ontology (HPO)-derived profiles of established DSD-associated genes.
RESULTS: Among 1391 screened individuals, 345 (24.8%) fulfilled inclusion criteria, including the presence of at least 1 additional organ anomaly, 83.8% had a 46,XY karyotype. The most frequent associated findings were small for gestational age (28.1%), cardiac anomalies (21.4%), central nervous system (CNS) (15.7%), and renal anomalies (14.5%). Unsupervised clustering identified 5 phenotypic groups, including craniofacial-dominant and CNS-dominant clusters. Phenotype-guided classification showed overlap with SF-1-deficiency-associated phenotypes in 11% of cases and with PORD-associated phenotypes in 22%. Comparison with HPO-derived profiles of 81 DSD-associated genes demonstrated phenotypic similarities between several clusters and known gene-associated anomaly spectra.
CONCLUSION: Systematic phenotyping identifies recognizable patterns of multisystem involvement in genetically unresolved DSD. Several clusters overlap with established DSD-associated conditions and gene-specific anomaly profiles, supporting phenotype-driven surveillance, multidisciplinary care, and informing future genomic re-evaluation strategies.