Evidence map›Paper›PMID 42812600›Full record

ArticleJournal of the Endocrine Society2026

Phenotyping and hierarchical clustering in genetically unresolved DSD identifies distinct multisystem clinical subgroups-a DSDgene study.

Chrysanthi Kouri, Malika Allimussina, S Faisal Ahmed, Christa E Flück

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Article in Journal of the Endocrine Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chrysanthi KouriPediatric Endocrinology, Diabetology and Metabolism, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland.ORCID https://orcid.org/0000-0002-7225-593X
Malika AllimussinaDevelopmental Endocrinology Research Group, University of Glasgow, Royal Hospital for Children, Glasgow G51 4TF, UK.
S Faisal AhmedDevelopmental Endocrinology Research Group, University of Glasgow, Royal Hospital for Children, Glasgow G51 4TF, UK.
Christa E FlückPediatric Endocrinology, Diabetology and Metabolism, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland.ORCID https://orcid.org/0000-0002-4568-5504

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

cluster analysisDSDgeneticsI-DSD registryorgan anomaliesphenotyping

Identifiers

PMID42812600
PMCPMC13621179

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.