Bibliographic Details
| Title: |
Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration |
| Authors: |
Stefan Groeneweg, Ferdy S. van Geest, Mariano Martín, Mafalda Dias, Jonathan Frazer, Carolina Medina-Gomez, Rosalie B. T. M. Sterenborg, Hao Wang, Anna Dolcetta-Capuzzo, Linda J. de Rooij, Alexander Teumer, Ayhan Abaci, Erica L. T. van den Akker, Gautam P. Ambegaonkar, Christine M. Armour, Iiuliu Bacos, Priyanka Bakhtiani, Diana Barca, Andrew J. Bauer, Sjoerd A. A. van den Berg, Amanda van den Berge, Enrico Bertini, Ingrid M. van Beynum, Nicola Brunetti-Pierri, Doris Brunner, Marco Cappa, Gerarda Cappuccio, Barbara Castellotti, Claudia Castiglioni, Krishna Chatterjee, Alexander Chesover, Peter Christian, Jet Coenen-van der Spek, Irenaeus F. M. de Coo, Regis Coutant, Dana Craiu, Patricia Crock, Christian DeGoede, Korcan Demir, Cheyenne Dewey, Alice Dica, Paul Dimitri, Marjolein H. G. Dremmen, Rachana Dubey, Anina Enderli, Jan Fairchild, Jonathan Gallichan, Luigi Garibaldi, Belinda George, Evelien F. Gevers, Erin Greenup, Annette Hackenberg, Zita Halász, Bianka Heinrich, Anna C. Hurst, Tony Huynh, Amber R. Isaza, Anna Klosowska, Marieke M. van der Knoop, Daniel Konrad, David A. Koolen, Heiko Krude, Abhishek Kulkarni, Alexander Laemmle, Stephen H. LaFranchi, Amy Lawson-Yuen, Jan Lebl, Selmar Leeuwenburgh, Michaela Linder-Lucht, Anna López Martí, Cláudia F. Lorea, Charles M. Lourenço, Roelineke J. Lunsing, Greta Lyons, Jana Krenek Malikova, Edna E. Mancilla, Kenneth L. McCormick, Anne McGowan, Veronica Mericq, Felipe Monti Lora, Carla Moran, Katalin E. Muller, Lindsey E. Nicol, Isabelle Oliver-Petit, Laura Paone, Praveen G. Paul, Michel Polak, Francesco Porta, Fabiano O. Poswar, Christina Reinauer, Klara Rozenkova, Rowen Seckold, Tuba Seven Menevse, Peter Simm, Anna Simon, Yogen Singh, Marco Spada, Milou A. M. Stals, Merel T. Stegenga, Athanasia Stoupa, Gopinath M. Subramanian, Lilla Szeifert, Davide Tonduti, Serap Turan, Joel Vanderniet, Adri van der Walt, Jean-Louis Wémeau, Anne-Marie van Wermeskerken, Jolanta Wierzba, Marie-Claire Y. de Wit, Nicole I. Wolf, Michael Wurm, Federica Zibordi, Amnon Zung, Nitash Zwaveling-Soonawala, Fernando Rivadeneira, Marcel E. Meima, Debora S. Marks, Juan P. Nicola, Chi-Hua Chen, Marco Medici, W. Edward Visser |
| Source: |
Nature Communications, Vol 16, Iss 1, Pp 1-21 (2025) |
| Publisher Information: |
Nature Portfolio, 2025. |
| Publication Year: |
2025 |
| Collection: |
LCC:Science |
| Subject Terms: |
Science |
| More Details: |
Abstract Predicting and quantifying phenotypic consequences of genetic variants in rare disorders is a major challenge, particularly pertinent for ‘actionable’ genes such as thyroid hormone transporter MCT8 (encoded by the X-linked SLC16A2 gene), where loss-of-function (LoF) variants cause a rare neurodevelopmental and (treatable) metabolic disorder in males. The combination of deep phenotyping data with functional and computational tests and with outcomes in population cohorts, enabled us to: (i) identify the genetic aetiology of divergent clinical phenotypes of MCT8 deficiency with genotype-phenotype relationships present across survival and 24 out of 32 disease features; (ii) demonstrate a mild phenocopy in ~400,000 individuals with common genetic variants in MCT8; (iii) assess therapeutic effectiveness, which did not differ among LoF-categories; (iv) advance structural insights in normal and mutated MCT8 by delineating seven critical functional domains; (v) create a pathogenicity-severity MCT8 variant classifier that accurately predicted pathogenicity (AUC:0.91) and severity (AUC:0.86) for 8151 variants. Our information-dense mapping provides a generalizable approach to advance multiple dimensions of rare genetic disorders. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2041-1723 |
| Relation: |
https://doaj.org/toc/2041-1723 |
| DOI: |
10.1038/s41467-025-56628-w |
| Access URL: |
https://doaj.org/article/0de7590ce33f4dff8cde3e316c92a6e6 |
| Accession Number: |
edsdoj.0de7590ce33f4dff8cde3e316c92a6e6 |
| Database: |
Directory of Open Access Journals |
