| Title: | Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration |
| Journal: | Nature Communications |
| Published: | 12 Mar 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40075072/ |
| DOI: | https://doi.org/10.1038/s41467-025-56628-w |
| URL: | https://www.nature.com/articles/s41467-025-56628-w.pdf |
Publication 15871
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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.</p>
13 Keywords
- Deep Learning
- Female
- Genomics
- Humans
- Loss of Function Mutation
- Male
- Monocarboxylic Acid Transporters
- Muscle Hypotonia
- Muscular Atrophy
- Phenotype
- Symporters
- Thyroid Hormones
- X-Linked Intellectual Disability
122 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
3 Applications
| Application ID | Title |
|---|---|
| 20272 | GWAS of kidney function related traits and kidney disease |
| 27412 | Boosting the power of GWAS using novel statistical tools |
| 67864 | Polygenic risk score transportability across populations and complex traits: characterizing clinical applications of risk profiles within the context of the Genotyping Of ALL (GOALL) project |
Enabling scientific discoveries that improve human health