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SRD5A3‐CDG : 3D structure modeling, clinical spectrum, and computer‐based dysmorphic facial recognition
Author(s) -
Ben Ayed Ikhlas,
Ouarda Wael,
Frikha Fakher,
Kammoun Fatma,
Souissi Amal,
Ben Said Mariem,
Bouzid Amal,
Elloumi Ines,
Hamdani Tarak M.,
Gharbi Nourhene,
Baklouti Nesrine,
Guirat Manel,
Mejdoub Fatma,
Kharrat Najla,
Boujelbene Imene,
Abdelhedi Fatma,
Belguith Neila,
Keskes Leila,
Gibriel Abdullah Ahmed,
Kamoun Hassen,
Triki Chahnez,
Alimi Adel M.,
Masmoudi Saber
Publication year - 2021
Publication title -
american journal of medical genetics part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.064
H-Index - 112
eISSN - 1552-4833
pISSN - 1552-4825
DOI - 10.1002/ajmg.a.62065
Subject(s) - missense mutation , phenotype , medicine , genetics , biology , gene
Pathogenic variants in Steroid 5 alpha reductase type 3 ( SRD5A3) cause rare inherited congenital disorder of glycosylation known as SRD5A3‐CDG (MIM# 612379). To date, 43 affected individuals have been reported. Despite the development of various dysmorphic features in significant number of patients, facial recognition entity has not yet been established for SRD5A3‐CDG. Herein, we reported a novel SRD5A3 missense pathogenic variant c.460 T > C p.(Ser154Pro). The 3D structural modeling of the SRD5A3 protein revealed additional transmembrane α‐helices and predicted that the p.(Ser154Pro) variant is located in a potential active site and is capable of reducing its catalytic efficiency. Based on phenotypes of our patients and all published SRD5A3‐CDG cases, we identified the most common clinical features as well as some recurrent dysmorphic features such as arched eyebrows, wide eyes, shallow nasal bridge, short nose, and large mouth. Based on facial digital 2D images, we successfully designed and validated a SRD5A3‐CDG computer based dysmorphic facial analysis, which achieved 92.5% accuracy. The current work integrates genotypic, 3D structural modeling and phenotypic characteristics of CDG‐SRD5A3 cases with the successful development of computer tool for accurate facial recognition of CDG‐SRD5A3 complex cases to assist in the diagnosis of this particular disorder globally.