Mining the Proteome Associated with Rheumatic and Autoimmune Diseases

Cristina Ruiz-Romero, Maggie P.Y. Lam, Peter Nilsson, Patrik Önnerfjord, Paul J. Utz, Jennifer E. Van Eyk, Vidya Venkatraman, Justyna Fert-Bober, Fiona E. Watt, Francisco J. Blanco

Research output: Contribution to journalArticlepeer-review

8 Citations (SciVal)

Abstract

A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining platforms to identify "popular" proteins closely related to RADs. The platform is based on publicly available literature. The results not only will enable the systematic prioritization of candidates to perform targeted proteomics studies but also may lead to a greater insight into the key pathogenic processes of these disorders.

Original languageEnglish
Pages (from-to)4231-4239
JournalJournal of Proteome Research
Volume18
Issue number12
Early online date2019 Oct 10
DOIs
Publication statusPublished - 2019

Subject classification (UKÄ)

  • Rheumatology and Autoimmunity

Keywords

  • autoimmune diseases
  • bioinformatics
  • Human Proteome Project
  • osteoarthritis
  • rheumatic diseases

Fingerprint

Dive into the research topics of 'Mining the Proteome Associated with Rheumatic and Autoimmune Diseases'. Together they form a unique fingerprint.

Cite this