| Title: |
Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration |
| Authors: |
Groeneweg, Stefan; van Geest, Ferdy S; Martín, Mariano; Dias, Mafalda; Frazer, Jonathan; Medina-Gomez, Carolina; Sterenborg, Rosalie BTM; Wang, Hao; Dolcetta-Capuzzo, Anna; de Rooij, Linda J; Teumer, Alexander; Abaci, Ayhan; van den Akker, Erica LT; Ambegaonkar, Gautam P; Armour, Christine M; Bacos, Iiuliu; Bakhtiani, Priyanka; Barca, Diana; Bauer, Andrew J; van den Berg, Sjoerd AA; van den Berge, Amanda; Bertini, Enrico; van Beynum, Ingrid M; Brunetti-Pierri, Nicola; Brunner, Doris; Cappa, Marco; Cappuccio, Gerarda; Castellotti, Barbara; Castiglioni, Claudia; Chatterjee, Krishna; Chesover, Alexander; Christian, Peter; Coenen-van der Spek, Jet; de Coo, Irenaeus FM; Coutant, Regis; Craiu, Dana; Crock, Patricia; DeGoede, Christian; Demir, Korcan; Dewey, Cheyenne; Dica, Alice; Dimitri, Paul; Dremmen, Marjolein HG; Dubey, Rachana; Enderli, Anina; Fairchild, Jan; Gallichan, Jonathan; Garibaldi, Luigi; George, Belinda; Gevers, Evelien F; Greenup, Erin; Hackenberg, Annette; Halász, Zita; Heinrich, Bianka; Hurst, Anna C; Huynh, Tony; Isaza, Amber R; Klosowska, Anna; van der Knoop, Marieke M; Konrad, Daniel; Koolen, David A; Krude, Heiko; Kulkarni, Abhishek; Laemmle, Alexander; LaFranchi, Stephen H; Lawson-Yuen, Amy; Lebl, Jan; Leeuwenburgh, Selmar; Linder-Lucht, Michaela; López Martí, Anna; Lorea, Cláudia F; Lourenço, Charles M; Lunsing, Roelineke J; Lyons, Greta; Malikova, Jana Krenek; Mancilla, Edna E; McCormick, Kenneth L; McGowan, Anne; Mericq, Veronica; Lora, Felipe Monti; Moran, Carla; Muller, Katalin E; Nicol, Lindsey E; Oliver-Petit, Isabelle; Paone, Laura; Paul, Praveen G; Polak, Michel; Porta, Francesco; Poswar, Fabiano O; Reinauer, Christina; Rozenkova, Klara; Seckold, Rowen; Seven Menevse, Tuba; Simm, Peter; Simon, Anna; Singh, Yogen; Spada, Marco; Stals, Milou AM; Stegenga, Merel T; Stoupa, Athanasia |
| Source: |
Nature Communications, vol 16, iss 1 |
| Publisher Information: |
eScholarship, University of California |
| Publication Year: |
2025 |
| Collection: |
University of California: eScholarship |
| Subject Terms: |
31 Biological Sciences (for-2020); 32 Biomedical and Clinical Sciences (for-2020); 3105 Genetics (for-2020); Rare Diseases (rcdc); Machine Learning and Artificial Intelligence (rcdc); Genetics (rcdc); Clinical Research (rcdc); Human Genome (rcdc); 2.1 Biological and endogenous factors (hrcs-rac); 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac); 2.4 Surveillance and distribution (hrcs-rac); 3 Good Health and Well Being (sdg); Humans (mesh); Monocarboxylic Acid Transporters (mesh); Deep Learning (mesh); Male (mesh); Symporters (mesh); Phenotype (mesh); X-Linked Intellectual Disability (mesh); Female (mesh); Muscular Atrophy (mesh); Muscle Hypotonia (mesh); Thyroid Hormones (mesh); Loss of Function Mutation (mesh); Genomics (mesh) |
| Time: |
2479 |
| Description: |
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 in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
qt5cx2d4hr; https://escholarship.org/uc/item/5cx2d4hr; https://escholarship.org/content/qt5cx2d4hr/qt5cx2d4hr.pdf |
| DOI: |
10.1038/s41467-025-56628-w |
| Availability: |
https://escholarship.org/uc/item/5cx2d4hr; https://escholarship.org/content/qt5cx2d4hr/qt5cx2d4hr.pdf; https://doi.org/10.1038/s41467-025-56628-w |
| Rights: |
public |
| Accession Number: |
edsbas.ED1CD56F |
| Database: |
BASE |