GestaltMatcher Database - A global reference for the facial phenotypic variability of rare human diseases.

Hellen Lesmann,Alexander Hustinx,Shahida Moosa,Elaine Marchi,Pilar Caro, Ibrahim M Abdelrazek,Jean Tori Pantel,Hannah Klinkhammer, Merle Ten Hagen,Tom Kamphans, Wolfgang Meiswinkel,Jing-Mei Li,Behnam Javanmardi,Alexej Knaus,Annette Uwineza, Cordula Knopp,Tinatin Tkemaladze,Miriam Elbracht, Larissa Mattern,Rami Abou Jamra,Clara Velmans,Vincent Strehlow,Himanshu Goel, Beatriz Carvalho Nunes, Thainá Vilella, Isabel Furquim Pinheiro,Chong Ae Kim,Maria Isabel Melaragno,Tahsin Stefan Barakat,Amira Nabil, Julia Suh,Luisa Averdunk, Ekanem Ekure,Claudio Graziano, Prasit Phowthongkum, Nergis Güzel,Tobias B Haack,Theresa Brunet,Sabine Rudnik-Schöneborn,Konrad Platzer, Artem Borovikov, Franziska Schnabel, Lara Heuft, Vera Herrmann, Antonio F Martinez-Monseny, Matthias Höller, Khoshoua Alaaeldin,Aleksandra Jezela-Stanek, Amal Mohamed,Amaia Lasa-Aranzasti, John A Sayer,Ping Hu,Suzanna E Ledgister Hanchard, Gehad Elmakkawy, Sylvia Safwat,Frédéric Ebstein,Elke Krüger,Sébastien Küry, Annabelle Arlt,Felix Marbach, Christian Netzer, Sophia Kaptain, Hannah Weiland,Dong Li,Lucie Dupuis,Roberto Mendoza-Londono,Sofia Douzgou Houge,Denisa Weis, Brian Hon-Yin Chung, Christopher C Y Mak, Koen Devriendt,Karen W Gripp,Martin Mücke,Alain Verloes,Christian P Schaaf,Christoffer Nellåker,Benjamin D Solomon,Rebekah L Waikel,Markus M Nöthen,Ebtesam Abdalla,Gholson J Lyon,Peter M Krawitz,Tzung-Chien Hsieh

medRxiv : the preprint server for health sciences(2024)

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摘要
Dysmorphologists sometimes encounter challenges in recognizing disorders due to phenotypic variability influenced by factors such as age and ethnicity. Moreover, the performance of Next Generation Phenotyping Tools such as GestaltMatcher is dependent on the diversity of the training set. Therefore, we developed GestaltMatcher Database (GMDB) - a global reference for the phenotypic variability of rare diseases that complies with the FAIR-principles. We curated dysmorphic patient images and metadata from 2,224 publications, transforming GMDB into an online dynamic case report journal. To encourage clinicians worldwide to contribute, each case can receive a Digital Object Identifier (DOI), making it a citable micro-publication. This resulted in a collection of 2,312 unpublished images, partly with longitudinal data. We have compiled a collection of 10,189 frontal images from 7,695 patients representing 683 disorders. The web interface enables gene- and phenotype-centered queries for registered users (https://db.gestaltmatcher.org/). Despite the predominant European ancestry of most patients (59%), our global collaborations have facilitated the inclusion of data from frequently underrepresented ethnicities, with 17% Asian, 4% African, and 6% with other ethnic backgrounds. The analysis has revealed a significant enhancement in GestaltMatcher performance across all ethnic groups, incorporating non-European ethnicities, showcasing a remarkable increase in Top-1-Accuracy by 31.56% and Top-5-Accuracy by 12.64%. Importantly, this improvement was achieved without altering the performance metrics for European patients. GMDB addresses dysmorphology challenges by representing phenotypic variability and including underrepresented groups, enhancing global diagnostic rates and serving as a vital clinician reference database.
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