ArticleAnnals of the rheumatic diseases2020
Machine learning algorithms reveal unique gene expression profiles in muscle biopsies from patients with different types of myositis.
Article in Annals of the rheumatic diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05738824 (Natural History of Inflammatory Muscle Diseases), which is not on this map. Cited by 105 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Natural History of Inflammatory Muscle Diseases
Who cites it
105 citing papers in PubMed, 2 syntheses or guidelines pooled it, 150 citations in OpenAlex.
- Integrating Machine Learning into Myositis Research: a Systematic Review.Clinical reviews in allergy & immunology · 2025Pooled it
- Defining anti-synthetase syndrome: a systematic literature review.Clinical and experimental rheumatology · 2022Pooled it
- ECG Changes Through Immunosuppressive Therapy Indicate Cardiac Abnormality in Anti-MDA5 Antibody-Positive Clinically Amyopathic Dermatomyositis.Frontiers in immunology · 2021Trial
- Immunopathogenesis of Immune-Mediated Necrotizing Myopathy: Insights Drawn from Pathological Phenotypes and Mechanistic Elaboration.Biomedicines · 2026Review
- Spatial transcriptomics reveals mechanism of autoimmunity driven by internalised autoantibodies.Annals of the rheumatic diseases · 2026Article
- Myeloid dendritic cell subsets characterise muscle in patients with inclusion body myositis and correlate with the IFN-γ pathway and effector T cell markers.Annals of the rheumatic diseases · 2026Article
- Emerging roles of the metabolic regulator 3-hydroxy-3-methylglutaryl coenzyme-CoA reductase in human cancers: From biology to therapeutics.Genes & diseases · 2026Review
- Immune-Driven Expression in Inclusion Body Myositis With T-Cell Large Granular Lymphocytic Leukemia.Annals of clinical and translational neurology · 2026Article
- A skeletal muscle atlas shows neuromuscular junction adaptations to growth and atrophy.Developmental cell · 2026Article
- Brachio-cervical inflammatory myopathy: multilevel clinical, histopathological and multi-omic analyses of a syndrome variably associated with systemic sclerosis.Acta neuropathologica · 2026Article
- Spatial transcriptomics reveals mechanism of autoimmunity driven by internalized autoantibodies.medRxiv : the preprint server for health sciences · 2026Article
- Proceedings of the 2Mediterranean journal of rheumatology · 2026Article
- The Caspase-1-EGR4 axis regulates macrophage repolarization in acute myeloid leukemia cells.Scientific reports · 2026Article
- Proteomic profiles in inclusion body myositis and polymyositis with mitochondrial pathology.Acta neuropathologica communications · 2026Article
- Myositis-specific autoantibodies recognising Mi2 also target the AIRE protein at a shared PHD zinc finger.Annals of the rheumatic diseases · 2026Article
- Autoantibody internalization in myositis skeletal muscle: Emerging evidence, mechanistic insights, and therapeutic relevance.Autoimmunity reviews · 2026Review
- Dysregulation of YTHDF2 promotes the over expression of interferon beta in anti-MDA5 antibody-positive dermatomyositis.Arthritis research & therapy · 2026Article
- Identification of a distinctive gene signature associated with disease activity in granulomatous myositis.Rheumatology (Oxford, England) · 2026Article
- A neuromuscular clinician's primer on machine learning.Journal of neuromuscular diseases · 2026Review
- Vasculitic fasciitis characterizes a distinct subset of vasculitic myopathy with interferon-gamma signature.Acta neuropathologica · 2025Article
45 more citing papers are in PubMed but not listed here.
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Authors and funding
15 authors at 6 institutions in 2 countries.
Funding
Abstract
objectivesMyositis is a heterogeneous family of diseases that includes dermatomyositis (DM), antisynthetase syndrome (AS), immune-mediated necrotising myopathy (IMNM), inclusion body myositis (IBM), polymyositis and overlap myositis. Additional subtypes of myositis can be defined by the presence of myositis-specific autoantibodies (MSAs). The purpose of this study was to define unique gene expression profiles in muscle biopsies from patients with MSA-positive DM, AS and IMNM as well as IBM.
methodsRNA-seq was performed on muscle biopsies from 119 myositis patients with IBM or defined MSAs and 20 controls. Machine learning algorithms were trained on transcriptomic data and recursive feature elimination was used to determine which genes were most useful for classifying muscle biopsies into each type and MSA-defined subtype of myositis.
resultsThe support vector machine learning algorithm classified the muscle biopsies with >90% accuracy. Recursive feature elimination identified genes that are most useful to the machine learning algorithm and that are only overexpressed in one type of myositis. For example, CAMK1G (calcium/calmodulin-dependent protein kinase IG), EGR4 (early growth response protein 4) and CXCL8 (interleukin 8) are highly expressed in AS but not in DM or other types of myositis. Using the same computational approach, we also identified genes that are uniquely overexpressed in different MSA-defined subtypes. These included apolipoprotein A4 (APOA4), which is only expressed in anti-3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) myopathy, and MADCAM1 (mucosal vascular addressin cell adhesion molecule 1), which is only expressed in anti-Mi2-positive DM.
conclusionsUnique gene expression profiles in muscle biopsies from patients with MSA-defined subtypes of myositis and IBM suggest that different pathological mechanisms underly muscle damage in each of these diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.