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The trusted data resource for craniofacial researchers worldwide
FaceBase is a collaborative NIDCR-funded project .

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  1. Dynamic enhancer landscapes in human craniofacial development

    Rajderkar, Sudha Sunil; Paraiso, Kitt; Amaral, Maria Luisa; Kosicki, Michael; Cook, Laura E.; Darbellay, Fabrice; Spurrell, Cailyn H.; Osterwalder, Marco; Zhu, Yiwen; Wu, Han; Afzal, Sarah Yasmeen; Blow, Matthew J.; Kelman, Guy; Barozzi, Iros; Fukuda-Yuzawa, Yoko; Akiyama, Jennifer A.; Afzal, Veena; Tran, Stella; Plajzer-Frick, Ingrid; Novak, Catherine S.; Kato, Momoe; Hunter, Riana D.; Von Maydell, Kianna; Wang, Allen; Lin, Lin; Preissl, Sebastian; Lisgo, Steven; Ren, Bing; Dickel, Diane E.; Pennacchio, Len A.; Visel, Axel. Nature Communications. vol. 15(1), 2030. March 2024.

    The genetic basis of human facial variation and craniofacial birth defects remains poorly understood. Distant-acting transcriptional enhancers control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development. However, a lack of accurate maps of the genomic locations and cell type-resolved activities of craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combine histone modification, chromatin accessibility, and gene expression profiling of human craniofacial development with single-cell analyses of the developing mouse face to define the regulatory landscape of facial development at tissue- and single cell-resolution. We provide temporal activity profiles for 14,000 human developmental craniofacial enhancers. We find that 56% of human craniofacial enhancers share chromatin accessibility in the mouse and we provide cell population- and embryonic stage-resolved predictions of their in vivo activity. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.

  2. Comparing 2D and 3D representations for face-based genetic syndrome diagnosis

    Bannister, Jordan J.; Wilms, Matthias; Aponte, J. David; Katz, David C.; Klein, Ophir D.; Bernier, Francois P.; Spritz, Richard A.; Hallgrímsson, Benedikt; Forkert, Nils D.. European Journal of Human Genetics. vol. 31(9), 1010–1016. September 2023.

  3. Privacy, bias and the clinical use of facial recognition technology: A survey of genetics professionals

    Aboujaoude, Elias; Light, Janice; Brown, Julia E. H.; Boscardin, W. John; Hallgrímsson, Benedikt; Klein, Ophir D.. American Journal of Medical Genetics Part C: Seminars in Medical Genetics. vol. 193(3), e32035. September 2023.

    Abstract Facial recognition technology (FRT) has been adopted as a precision medicine tool. The medical genetics field highlights both the clinical potential and privacy risks of this technology, putting the discipline at the forefront of a new digital privacy debate. Investigating how geneticists perceive the privacy concerns surrounding FRT can help shape the evolution and regulation of the field, and provide lessons for medicine and research more broadly. Five hundred and sixty‐two genetics clinicians and researchers were approached to fill out a survey, 105 responded, and 80% of these completed. The survey consisted of 48 questions covering demographics, relationship to new technologies, views on privacy, views on FRT, and views on regulation. Genetics professionals generally placed a high value on privacy, although specific views differed, were context‐specific, and covaried with demographic factors. Most respondents (88%) agreed that privacy is a basic human right, but only 37% placed greater weight on it than other values such as freedom of speech. Most respondents (80%) supported FRT use in genetics, but not necessarily for broader clinical use. A sizeable percentage (39%) were unaware of FRT’s lower accuracy rates in marginalized communities and of the mental health effects of privacy violations (62%), but most (76% and 75%, respectively) expressed concern when informed. Overall, women and those who self‐identified as politically progressive were more concerned about the lower accuracy rates in marginalized groups (88% vs. 64% and 83% vs. 63%, respectively). Younger geneticists were more wary than older geneticists about using FRT in genetics (28% compared to 56% “strongly” supported such use). There was an overall preference for more regulation, but respondents had low confidence in governments’ or technology companies’ ability to accomplish this. Privacy views are nuanced and context‐dependent. Support for privacy was high but not absolute, and clear deficits existed in awareness of crucial FRT‐related discrimination potential and mental health impacts. Education and professional guidelines may help to evolve views and practices within the field.

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