AI-Based Facial Phenotyping Supports a Shared Molecular Axis in PACS1-, PACS2-, and WDR37-Related Syndromes

dc.contributor
Institut Català de la Salut
dc.contributor
[Del Rincón J, Gil-Salvador M, Lucia-Campos C, Acero L, Arnedo M] Unit of Clinical Genetics and Functional Genomics, Department of Pharmacology and Physiology, School of Medicine, University of Zaragoza, CIBERER-GCV2 and IIS-Aragon-GIIS062, Zaragoza, Spain. [Trujillano L] Àrea de Genètica Clínica i Molecular, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Grup de Recerca de Medicina Genètica, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain
dc.contributor
Vall d'Hebron Barcelona Hospital Campus
dc.contributor.author
Acero, Laura
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Arnedo, Maria
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del Rincón de la Villa, Julia
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Gil Salvador, Marta
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Lucia Campos, Cristina
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Trujillano Lidón, Laura
dc.date.accessioned
2025-11-05T18:26:55Z
dc.date.available
2025-11-05T18:26:55Z
dc.date.issued
2025-11-04T11:21:11Z
dc.date.issued
2025-11-04T11:21:11Z
dc.date.issued
2025-08
dc.identifier
del Rincón J, Gil-Salvador M, Lucia-Campos C, Acero L, Trujillano L, Arnedo M, et al. AI-Based Facial Phenotyping Supports a Shared Molecular Axis in PACS1-, PACS2-, and WDR37-Related Syndromes. Int J Mol Sci. 2025 Aug;26(16):7964.
dc.identifier
1422-0067
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http://hdl.handle.net/11351/14007
dc.identifier
10.3390/ijms26167964
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40869285
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001557737900001
dc.identifier.uri
http://hdl.handle.net/11351/14007
dc.description.abstract
AI-based facial analysis; Schuurs-Hoeijmakers syndrome; Dysmorphology
dc.description.abstract
Anàlisi facial basada en intel·ligència artificial; Síndrome de Schuurs-Hoeijmakers; Dismorfologia
dc.description.abstract
Análisis facial basado en inteligencia artificial; Síndrome de Schuurs-Hoeijmakers; Dismorfología
dc.description.abstract
Despite significant advances in gene discovery, the molecular basis of many rare genetic disorders remains poorly understood. The concept of disease modules, clusters of functionally related genes whose disruption leads to overlapping phenotypes, offers a valuable framework for interpreting these conditions. However, identifying such relationships remains particularly challenging in ultra-rare syndromes due to the limited number of documented cases. We hypothesized that AI-based facial phenotyping could aid in identifying shared molecular mechanisms by detecting phenotypic convergence among clinically related syndromes. To test this, we used Schuurs–Hoeijmakers syndrome (SHMS; OMIM #615009), caused by a recurrent de novo variant in PACS1, as a model to explore potential phenotypic and functional associations with PACS2-related disorder (DEE66; OMIM #618067) and WDR37-related disorder (NOCGUS; OMIM #618652). Facial photographs of individuals with SHMS were analyzed using the DeepGestalt and GestaltMatcher algorithms. In addition to consistently recognizing SHMS as a distinct clinical entity, the algorithms frequently matched DEE66 and NOCGUS, suggesting a shared facial gestalt. Binary comparisons further confirmed overlapping craniofacial features among the three disorders. These findings were supported by literature review, indicating clinical overlapping and potential functional associations. Overall, our results confirm the presence of consistent facial similarities among PACS1-, PACS2-, and WDR37-related syndromes and highlight the utility of AI-driven facial phenotyping as a complementary tool for uncovering clinically relevant relationships in ultra-rare genetic disorders.
dc.description.abstract
This research was funded by Spanish Ministry of Health-ISCIII Fondo de Investigación Sanitaria (FIS) [Ref. PI23/01370, to F.J.R. and J.P.] and co-founded by European Union; Diputación General de Aragón-FEDER: European Social Fund [Reference Group B32_20R, to J.P.]; University of Zaragoza [JIUZ2023-SAL-06 to A.L.-P].
dc.format
application/pdf
dc.language
eng
dc.publisher
MDPI
dc.relation
International Journal of Molecular Sciences;26(16)
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https://doi.org/10.3390/ijms26167964
dc.rights
Attribution 4.0 International
dc.rights
http://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Scientia
dc.subject
Fenotip
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Anomalies cromosòmiques
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Discapacitat intel·lectual
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Malalties congènites
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PHENOMENA AND PROCESSES::Genetic Phenomena::Phenotype
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PHENOMENA AND PROCESSES::Genetic Phenomena::Genetic Variation::Mutation
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DISEASES::Congenital, Hereditary, and Neonatal Diseases and Abnormalities::Genetic Diseases, Inborn
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DISEASES::Pathological Conditions, Signs and Symptoms::Signs and Symptoms::Neurologic Manifestations::Neurobehavioral Manifestations::Intellectual Disability
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FENÓMENOS Y PROCESOS::fenómenos genéticos::fenotipo
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FENÓMENOS Y PROCESOS::fenómenos genéticos::variación genética::mutación
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ENFERMEDADES::enfermedades y anomalías neonatales congénitas y hereditarias::enfermedades genéticas congénitas
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ENFERMEDADES::afecciones patológicas, signos y síntomas::signos y síntomas::manifestaciones neurológicas::manifestaciones neuroconductuales::discapacidad intelectual
dc.title
AI-Based Facial Phenotyping Supports a Shared Molecular Axis in PACS1-, PACS2-, and WDR37-Related Syndromes
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion


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