Functional Consequence of IRF6 Variants in Van der Woude Syndrome.
15 affiliations
- 1Iowa Institute for Oral Health Research, University of Iowa, Iowa City, IA 52242, USA.
- 2Department of Oral Pathology, Radiology and Medicine, College of Dentistry, University of Iowa, Iowa City, IA 52242, USA.
- 3Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA.
- 4GKT School of Medical Education, King's College London, London WC2R 2LS, UK.
- 5College of Dentistry, University of Iowa, Iowa City, IA 52242, USA.
- 6School of Dentistry, University of Michigan, Ann Arbor, MI 48109, USA.
- 7Department of Orthodontics, College of Dentistry, University of Iowa, Iowa City, IA 52242, USA.
- 8Department of General Dentistry, School of Dentistry, Creighton University, Omaha, NE 68178, USA.
- 9Department of Pediatrics, University of KwaZulu-Natal, Pinetown 3605, South Africa.
- 10Department of Biochemistry and Biotechnology, Kwame Nkrumah University of Science and Technology, Kumasi 00233, Ghana.
- 11Surgical Department, School of Medicine, Addis Ababa University, Addis Ababa P.O. Box 9086, Ethiopia.
- 12Department of Oral and Maxillofacial Surgery, University of Lagos, Lagos 100254, Nigeria.
- 13Department of Anatomy and Cell Biology, Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA.
- 14Dental and Craniofacial Genomics Core, School of Dental Medicine, University of Puerto Rico, San Juan, PR 00936, USA.
- 15School of Dentistry, University of Dundee, Dundee DD1 4HN, UK.
Abstract
Van der Woude syndrome (VWS) is the most common syndromic form of orofacial clefts (OFCs). The heritability of VWS is largely (~70%) explained by variants in the IRF6 gene. Experimental studies to confirm genetic variant effects are essential but are time intensive and expensive. Advancing next-generation sequencing techniques has made it possible to identify genetic variation quicker than their causal effects in disease processes can be ascertained. Therefore, employing computational tools to reliably predict their causal effects is crucial for advancing translational research. We conducted Sanger sequencing of the IRF6 gene in 46 VWS cases across 34 families to identify likely causal missense variants. We then assessed structure-informed stability changes to the IRF6 protein when these variants were incorporated into the protein, using DDGun3D. We compared DDGun3D predictions to results from previous experimental studies. Among four variants previously shown to prevent functional rescue in zebrafish, only the variant IRF6(NM_006147.4):c.881T>C, shown to cause rupture of zebrafish embryo, exhibited a high free energy change (∆∆Gfold = 3.5 kcal/mol), indicating that substantial predicted thermodynamic destabilization does not capture all disruptive function of IRF6. Our study demonstrates the utility of a protein structure-based computational approach for functional variant interpretation, providing a complementary method for studying genetic variation. Integrating computational predictions with experimental data can enhance our understanding of genetic conditions. However, success depends on fully elucidating protein structures, which is an active area of research.
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BibTeX
@article{olujitan2026functional,
title = {{Functional Consequence of IRF6 Variants in Van der Woude Syndrome.}},
author = {Mojisola Olujitan and Rose Gogal and Tamara Busch and Chloe Ovel and Anjolaoluwa Awe and Jorge Ceballos and Kikanwa Okiosor and Natalie Ibarra and Emmanuel Aladenika and Waheed Awotoye and Veronica Sule and Babatunde Faparusi and Benjamin Bass and Rishitha Gadde and Thirona Naicker and Lord J J Gowans and Mekonen Eshete and Wasiu Lanre Adeyemo and Aline Petrin and Martine Dunnwald and Carmen J Buxo and Peter Mossey and Michael Schnieders and Azeez Butali},
journal = {Genes},
year = {2026},
month = oct,
doi = {10.3390/genes17101223},
url = {https://europepmc.org/article/MED/42938339},
note = {CC BY},
}
RIS
TY - JOUR
TI - Functional Consequence of IRF6 Variants in Van der Woude Syndrome.
AU - Mojisola Olujitan
AU - Rose Gogal
AU - Tamara Busch
AU - Chloe Ovel
AU - Anjolaoluwa Awe
AU - Jorge Ceballos
AU - Kikanwa Okiosor
AU - Natalie Ibarra
AU - Emmanuel Aladenika
AU - Waheed Awotoye
AU - Veronica Sule
AU - Babatunde Faparusi
AU - Benjamin Bass
AU - Rishitha Gadde
AU - Thirona Naicker
AU - Lord J J Gowans
AU - Mekonen Eshete
AU - Wasiu Lanre Adeyemo
AU - Aline Petrin
AU - Martine Dunnwald
AU - Carmen J Buxo
AU - Peter Mossey
AU - Michael Schnieders
AU - Azeez Butali
PY - 2026
DA - 2026/10/02
JO - Genes
DO - 10.3390/genes17101223
UR - https://europepmc.org/article/MED/42938339
AB - Van der Woude syndrome (VWS) is the most common syndromic form of orofacial clefts (OFCs). The heritability of VWS is largely (~70%) explained by variants in the IRF6 gene. Experimental studies to confirm genetic variant effects are essential but are time intensive and expensive. Advancing next-generation sequencing techniques has made it possible to identify genetic variation quicker than their causal effects in disease processes can be ascertained. Therefore, employing computational tools to reliably predict their causal effects is crucial for advancing translational research. We conducted Sanger sequencing of the IRF6 gene in 46 VWS cases across 34 families to identify likely causal missense variants. We then assessed structure-informed stability changes to the IRF6 protein when these variants were incorporated into the protein, using DDGun3D. We compared DDGun3D predictions to results from previous experimental studies. Among four variants previously shown to prevent functional rescue in zebrafish, only the variant IRF6(NM_006147.4):c.881T>C, shown to cause rupture of zebrafish embryo, exhibited a high free energy change (∆∆Gfold = 3.5 kcal/mol), indicating that substantial predicted thermodynamic destabilization does not capture all disruptive function of IRF6. Our study demonstrates the utility of a protein structure-based computational approach for functional variant interpretation, providing a complementary method for studying genetic variation. Integrating computational predictions with experimental data can enhance our understanding of genetic conditions. However, success depends on fully elucidating protein structures, which is an active area of research.
SN - 2073-4425
ER -