Quantitative Craniofacial Analysis and Generation of Human Induced Pluripotent Stem Cells for Muenke Syndrome: A Case Report

• Published in: Journal of developmental biology 2021, Vol.9 (4)
• Main Authors: Kidwai, Fahad K, Mui, Byron W H, Almpani, Konstantinia, Jani, Priyam, Keyvanfar, Cyrus, Iqbal, Kulsum, Paravastu, Sriram S, Arora, Deepika, Orzechowski, Pamela, Merling, Randall K, Mallon, Barbara, Myneni, Vamsee D, Ahmad, Moaz, Kruszka, Paul, Muenke, Maximilian, Woodcock, Jeremiah, Gilman, Jeffrey W, Robey, Pamela G, Lee, Janice S
• Format: Report
• Language: English
• ISSN: 2221-3759
• DOI: 10.3390/jdb9040039

In this case report, we focus on Muenke syndrome (MS), a disease caused by the p.Pro250Arg variant in fibroblast growth factor receptor 3 (FGFR3) and characterized by uni- or bilateral coronal suture synostosis, macrocephaly without craniosynostosis, dysmorphic craniofacial features, and dental malocclusion. The clinical findings of MS are further complicated by variable expression of phenotypic traits and incomplete penetrance. As such, unraveling the mechanisms behind MS will require a comprehensive and systematic way of phenotyping patients to precisely identify the impact of the mutation variant on craniofacial development. To establish this framework, we quantitatively delineated the craniofacial phenotype of an individual with MS and compared this to his unaffected parents using three-dimensional cephalometric analysis of cone beam computed tomography scans and geometric morphometric analysis, in addition to an extensive clinical evaluation. Secondly, given the utility of human induced pluripotent stem cells (hiPSCs) as a patient-specific investigative tool, we also generated the first hiPSCs derived from a family trio, the proband and his unaffected parents as controls, with detailed characterization of all cell lines. This report provides a starting point for evaluating the mechanistic underpinning of the craniofacial development in MS with the goal of linking specific clinical manifestations to molecular insights gained from hiPSC-based disease modeling.