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Discovery of new myositis genetic associations through leveraging other immune-mediated diseases
G. Reales, CI. Amos, O. Benveniste, H. Chinoy, J. De Bleecker, B. De Paepe, A. Doria, PK. Gregersen, JA. Lamb, V. Limaye, IE. Lundberg, PM. Machado, B. Maurer, FW. Miller, Ø. Molberg, LM. Pachman, L. Padyukov, TR. Radstake, AM. Reed, LG. Rider,...
Language English Country United States
Document type Journal Article
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- MeSH
- Autoimmune Diseases genetics immunology MeSH
- Genome-Wide Association Study * MeSH
- Genetic Predisposition to Disease * MeSH
- Polymorphism, Single Nucleotide MeSH
- Humans MeSH
- Myositis * genetics immunology MeSH
- Immune System Diseases genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Genome-wide association studies (GWASs) have been successful at finding associations between genetic variants and human traits, including the immune-mediated diseases (IMDs). However, the requirement of large sample sizes for discovery poses a challenge for learning about less common diseases, where increasing volunteer numbers might not be feasible. An example of this is myositis (or idiopathic inflammatory myopathies [IIM]s), a group of rare, heterogeneous autoimmune diseases affecting skeletal muscle and other organs, severely impairing life quality. Here, we applied a feature engineering method to borrow information from larger IMD GWASs to find new genetic associations with IIM and its subgroups. Combining this approach with two clustering methods, we found 17 IMDs genetically close to IIM, including some common comorbid conditions, such as systemic sclerosis and Sjögren's syndrome, as well as hypo- and hyperthyroidism. All IIM subtypes were genetically similar within this framework. Next, we colocalized IIM signals that overlapped IMD signals, and found seven potentially novel myositis associations mapped to immune-related genes, including BLK, IRF5/TNPO3, and ITK/HAVCR2, implicating a role for both B and T cells in IIM. This work proposes a new paradigm of genetic discovery in rarer diseases by leveraging information from more common IMD, and can be expanded to other conditions and traits beyond IMD.
Centre for Rheumatology UCL Division of Medicine University College London London UK
Children's Hospital of Chicago Northwestern University Feinberg School of Medicine Chicago IL USA
Department of Internal Medicine and Clinical Immunology Pitié Salpêtrière Hospital Paris France
Department of Medicine Baylor College of Medicine Houston TX USA
Department of Medicine University of Cambridge Cambridge UK
Department of Neurology Ghent University Ghent Belgium
Department of Neuromuscular Diseases UCL Queen Square Institute of Neurology London UK
Department of Pediatrics Duke University Durham NC USA
Department of Rheumatology and Clinical Immunology University Medical Center Utrecht the Netherlands
Department of Rheumatology Oslo University Hospital Oslo Norway
Discipline of Medicine Adelaide University Adelaide South Australia Australia
MRC Biostatistics Unit University of Cambridge Cambridge UK
Neuromuscular Reference Center Ghent University Hospital Ghent Belgium
NIHR Biomedical Research Centre at Great Ormond Street Hospital London UK
Rheumatology Unit Department of Medicine University of Padova Padova Italy
Rheumatology Unit Royal Adelaide Hospital Adelaide South Australia Australia
The Robert S Boas Center for Genomics and Human Genetics The Feinstein Institute Manhasset NY USA
References provided by Crossref.org
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- $a Reales, Guillermo $u Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), University of Cambridge, Cambridge, UK; Department of Medicine, University of Cambridge, Cambridge, UK. Electronic address: grealesm@gmail.com
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