Tailored therapeutic decision of rheumatoid arthritis using proteomic strategies: how to start and when to stop?

Shuo Fu Chen, Fu Chiang Yeh, Ching Yun Chen, Hui Yin Chang

Research output: Contribution to journalReview articlepeer-review

Abstract

Unpredictable treatment responses have been an obstacle for the successful management of rheumatoid arthritis. Although numerous serum proteins have been proposed, there is a lack of integrative survey to compare their relevance in predicting treatment outcomes in rheumatoid arthritis. Also, little is known about their applications in various treatment stages, such as dose modification, drug switching or withdrawal. Here we present an in-depth exploration of the potential usefulness of serum proteins in clinical decision-making and unveil the spectrum of immunopathology underlying responders to different drugs. Patients with robust autoimmunity and inflammation are more responsive to biological treatments and prone to relapse during treatment de-escalation. Moreover, the concentration changes of serum proteins at the beginning of the treatments possibly assist early recognition of treatment responders. With a better understanding of the relationship between the serum proteome and treatment responses, personalized medicine in rheumatoid arthritis will be more achievable in the near future.

Original languageEnglish
Article number22
JournalClinical Proteomics
Volume20
Issue number1
DOIs
StatePublished - Dec 2023

Keywords

  • Biomarkers
  • Prediction
  • Proteomics
  • Rheumatoid arthritis
  • Treatment response

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