Machine learning algorithms reveal unique gene expression profiles in muscle biopsies from patients with different types of myositis

Ann Rheum Dis. 2020 Sep;79(9):1234-1242. doi: 10.1136/annrheumdis-2019-216599. Epub 2020 Jun 16.

Abstract

Objectives: Myositis 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.

Methods: RNA-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.

Results: The 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.

Conclusions: Unique 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.

Keywords: autoantibodies; autoimmune diseases; autoimmunity; dermatomyositis; polymyositis.

Publication types

  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Animals
  • Apolipoproteins A / metabolism
  • Autoimmune Diseases / genetics*
  • Biopsy
  • Calcium-Calmodulin-Dependent Protein Kinase Type 1 / metabolism
  • Cell Adhesion Molecules / metabolism
  • Cell Culture Techniques
  • Dermatomyositis / genetics
  • Early Growth Response Transcription Factors / metabolism
  • Female
  • Humans
  • Hydroxymethylglutaryl CoA Reductases / metabolism
  • Interleukin-8 / metabolism
  • Machine Learning
  • Male
  • Mice
  • Mucoproteins / metabolism
  • Muscle, Skeletal / metabolism
  • Muscle, Skeletal / pathology
  • Muscular Diseases / genetics*
  • Myositis / genetics*
  • Myositis / pathology
  • Myositis, Inclusion Body / genetics*
  • Polymyositis / genetics
  • Transcriptome

Substances

  • Apolipoproteins A
  • CXCL8 protein, human
  • Cell Adhesion Molecules
  • EGR4 protein, human
  • Early Growth Response Transcription Factors
  • Interleukin-8
  • MADCAM1 protein, human
  • Mucoproteins
  • apolipoprotein A-IV
  • HMGCR protein, human
  • Hydroxymethylglutaryl CoA Reductases
  • CAMK1G protein, human
  • Calcium-Calmodulin-Dependent Protein Kinase Type 1

Supplementary concepts

  • Antisynthetase syndrome