Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration

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.

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Publication Details

Journal
Nature Communications
Published
2025-03-12
DOI
https://doi.org/10.1038/s41467-025-56628-w
Citations
4
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
7.27

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article

Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration

Gautam Ambegaonkar, Katalin Eszter Müller, Bianka Heinrich, Alice Dica et al.
4 citations
Nature Communications
Genomics and Rare Diseases
7.27
article

Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration

Gautam Ambegaonkar, Katalin Eszter Müller, Bianka Heinrich, Alice Dica, Chi‐Hua Chen, Paul Dimitri, Jan Fairchild, Mariano Martín, Athanasia Stoupa, Linda J. de Rooij, Cheyenne Dewey, Marcel E. Meima, Jan Lebl, Jolanta Wierzba, Peter Simm, Christine M. Armour, Alexander Chesover, Abhishek J. Kulkarni, Dana Craiu, Merel T Stegenga, tuba seven menevse, Anna Dolcetta‐Capuzzo, Juan P. Nicola, Yogen Singh, Fernando Rivadeneira, Debora S. Marks, Nicole I. Wolf, Rowen Seckold, Adri van der Walt, Marco Medici, David A. Koolen, Praveen George Paul, Zita Halász, Rosalie Sterenborg, Amy Lawson‐Yuen, Davide Tonduti, Gopinath M. Subramanian, Jonathan Gallichan, Federica Zibordi, Alexander Laemmle, Marco Cappa, Anne‐Marie van Wermeskerken, Ferdy S. van Geest, Charles Marques Lourenço, Erin Greenup, Jet van der Spek, Anna Simon, W. Edward Visser, Kenneth McCormick, Patricia Crock, Fabiano de Oliveira Poswar, Krishna Chatterjee, Anina Enderli, Stefan Groeneweg, Roelineke J. Lunsing, Lindsey Nicol, Anne McGowan, Amelia Martí, Stephen LaFranchi, Gerarda Cappuccio, Rachana Dubey, Jonathan Frazer, Evelien F. Gevers, Erica L T van den Akker, Daniel Konrad, Barbara Castellotti, Mafalda Dias, Andrew J. Bauer, Tony Huynh, Peter Christian, Carolina Medina‐Gómez, Christian de Goede, Annette Hackenberg, Klára Roženková, Anna Kłosowska, Enrico Bertini, Priyanka Bakhtiani, Francesco Porta, Marjolein H. G. Dremmen, Hao Wang, Korcan Demir, Lilla Szeifert, Diana Bârcă, Nicola Brunetti‐Pierri, Amnon Zung, Amanda van den Berge, Serap Turan, Sjoerd A.A. van den Berg, Isabelle Oliver‐Petit, Nitash Zwaveling‐Soonawala, Heiko Krude, Michel Polak, Belinda George, Amber Isaza, Ayhan Abacı, Verónica Mericq, M Linder-Lucht, Luigi Garibaldi, Alexander Teumer, Christina Reinauer, Claudia Castiglioni, Joel A. Vanderniet, I.F.M. de Coo, R. Coutant, Carla Moran, Milou A.M. Stals, Marieke M van der Knoop, Cláudia Fernandes Lorea, Ingrid M. van Beynum, Marco Spada, Selmar Leeuwenburgh, Marie‐Claire Y. de Wit, I. Bacos, Laura Paone, Michael Wurm, Anna Hurst, Doris Brunner, Jana Malíková, Edna E. Mancilla, Felipe Monti Lora, Greta Lyons, Jean‐Louis Wémeau
article en
4 citations

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.

Nature CommunicationsVol. 16(1)
Semmelweis University (HU), Délégation Paris 5 (FR), Lancashire Teaching Hospitals NHS Foundation Trust (GB), Universidade Federal do Rio Grande do Sul (BR), Royal Children's Hospital (AU), MultiCare Health System (US), University Medical Center Groningen (NL), Children's Hospital of Philadelphia (US), Children's Hospital of Los Angeles (US), Faculdade de Medicina de São José do Rio Preto (BR), Kaiser Permanente (US), Harvard University (US), University of Louisville (US), Radboud University Nijmegen (NL), Consejo Nacional de Investigaciones Científicas y Técnicas (AR), University of Ottawa (CA), Carol Davila University of Medicine and Pharmacy (RO), The University of Melbourne (AU), Queen Mary University of London (GB), Universidad Nacional de Córdoba (AR), Universidade Federal de Pelotas (BR), University of Groningen (NL), Universitat Pompeu Fabra (ES), Christian Medical College, Vellore (IN), Université Fédérale de Toulouse Midi-Pyrénées (FR), Baylor College of Medicine (US), University of Toronto (CA), University of Milan (IT), Dokuz Eylül University (TR), Hebrew University of Jerusalem (IL), University of Zurich (CH), Université Paris Cité (FR), Charles University (CZ), Université de Lille (FR), University of Cambridge (GB), Universitätsmedizin Greifswald (DE), Children's Hospital of Eastern Ontario (CA), Kaplan Medical Center (IL), Great Ormond Street Hospital (GB), Arnold Palmer Hospital for Children (US), University Hospital of Bern (CH), University Medical Center Freiburg (DE), Women's and Children's Hospital (AU), Hospital for Sick Children (CA), Erasmus MC (NL), Cambridge University Hospitals NHS Foundation Trust (GB), East Kent Hospitals University NHS Foundation Trust (GB), Radboud University Medical Center (NL), University Hospital Regensburg (DE), University of Alabama at Birmingham (US), Maastricht University (NL), University of California San Diego (US), Heim Pál Országos Gyermekgyógyászati Intézet (HU), Clínica Las Condes (CL), Azienda Ospedaliera Citta' della Salute e della Scienza di Torino (IT), Hunter Medical Research Institute (AU), Kaiser Permanente Washington Health Research Institute (US), Düsseldorf University Hospital (DE), Indo-US Super Speciality Hospital (IN), Emma Kinderziekenhuis (NL), Hospital de Clínicas de Porto Alegre (BR), Amsterdam Neuroscience (NL), Finis Terrae University (CL), Wellcome/MRC Institute of Metabolic Science (GB), Federico II University Hospital (IT), Flevoziekenhuis (NL), Bambino Gesù Children's Hospital (IT), German Centre for Cardiovascular Research (DE), University Children's Hospital Zurich (CH), Children's Hospital of Pittsburgh (US), Centre for Genomic Regulation (ES), John Hunter Children's Hospital (AU), SickKids Foundation (CA), Erasmus MC - Sophia Children’s Hospital (NL), St.John's Medical College Hospital (IN), Institute for Bioengineering of Catalonia (ES), Scuola Superiore Meridionale (IT), Amsterdam University Medical Centers (NL), Telethon Institute Of Genetics And Medicine (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Center for Systems Biology (US), Doernbecher Children's Hospital (US), Addenbrooke's Hospital (GB), SRCC Children’s Hospital (IN), Right to Care (ZA), Hospital São Paulo (BR), UC Davis Children's Hospital (US), Plymouth Hospital (GB), Fondazione IRCCS Istituto Neurologico Carlo Besta (IT), Institut des Maladies Génétiques Imagine (FR), University Hospitals Plymouth NHS Trust (GB), Children's Health Queensland Hospital and Health Service (AU), Heinrich Heine University Düsseldorf (DE), University College London (GB), Université d'Angers (FR), University of Regensburg (DE), University of Chile (CL), University of Naples Federico II (IT), Marmara University (TR), Gdańsk Medical University (PL), Charité - Universitätsmedizin Berlin (DE), Vrije Universiteit Amsterdam (NL), Wellcome Trust (GB), University of Amsterdam (NL), Medical Research Council (GB), University of Sheffield (GB), Erasmus University Rotterdam (NL)
Wellcome Trust, NIHR Cambridge Biomedical Research Centre, National Institute of Mental Health, Eurostars
Good health and well-being
Openalex Percentile: Top 3%
Genomics and Rare Diseases
7.27
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