Moving towards a molecular taxonomy of autoimmune rheumatic diseases

Nat Rev Rheumatol. 2018 Jan 24;14(2):75-93. doi: 10.1038/nrrheum.2017.220.


Autoimmune rheumatic diseases pose many problems that have, in general, already been solved in the field of cancer. The heterogeneity of each disease, the clinical similarities and differences between different autoimmune rheumatic diseases and the large number of patients that remain without a diagnosis underline the need to reclassify these diseases via new approaches. Knowledge about the molecular basis of systemic autoimmune diseases, along with the availability of bioinformatics tools capable of handling and integrating large volumes of various types of molecular data at once, offer the possibility of reclassifying these diseases. A new taxonomy could lead to the discovery of new biomarkers for patient stratification and prognosis. Most importantly, this taxonomy might enable important changes in clinical trial design to reach the expected outcomes or the design of molecularly targeted therapies. In this Review, we discuss the basis for a new molecular taxonomy for autoimmune rheumatic diseases. We highlight the evidence surrounding the idea that these diseases share molecular features related to their pathogenesis and development and discuss previous attempts to classify these diseases. We evaluate the tools available to analyse and combine different types of molecular data. Finally, we introduce PRECISESADS, a project aimed at reclassifying the systemic autoimmune diseases.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Autoimmune Diseases / classification
  • Autoimmune Diseases / diagnosis*
  • Autoimmune Diseases / drug therapy
  • Autoimmune Diseases / immunology
  • Biomarkers / metabolism*
  • Computational Biology
  • Early Diagnosis
  • Humans
  • Molecular Targeted Therapy / methods
  • Precision Medicine
  • Rheumatic Diseases / classification
  • Rheumatic Diseases / diagnosis*
  • Rheumatic Diseases / drug therapy
  • Rheumatic Diseases / immunology


  • Biomarkers