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Molecular Profiling of Axial Spondyloarthritis Patients Reveals an Association between Innate and Adaptive Cell

Daniel Sobral1, Ana Filipa Fernandes2, Miguel Bernardes3,4

  • 1Applied Molecular Biosciences Unit, Life Sciences Department, Sciences and Technology School, NOVA University of Lisbon, 2829-516 Caparica, Portugal.

Biomolecules
|March 28, 2024
PubMed

Insights

Biomarkers predict response to Tumor Necrosis Factor inhibitors (TNFi) in axial spondyloarthritis (axSpA). Baseline immune cell profiles and gene expression accurately predict treatment success, aiding personalized medicine approaches.

Area of Science:

  • Immunology
  • Genetics
  • Rheumatology

Background:

  • Axial spondyloarthritis (axSpA) is a chronic inflammatory disease.
  • Tumor Necrosis Factor inhibitors (TNFi) are effective treatments, but patient response varies.
  • Identifying predictive biomarkers is crucial for personalized treatment strategies.

Purpose of the Study:

  • To identify molecular biomarkers that differentiate responders from non-responders to TNFi treatment in axSpA.
  • To explore baseline immune cell composition and gene expression profiles associated with treatment response.
  • To develop a predictive model for TNFi response in axSpA patients.

Main Methods:

  • Analysis of whole blood mRNA and plasma proteins in biologic-naïve axSpA patients (n=35) pre- and post-adalimumab treatment.
  • Differential gene and protein expression analysis to identify treatment-associated signatures and enriched pathways.
  • Development of a logistic regression model incorporating clinical and gene expression data for response prediction.

Main Results:

  • Responders showed distinct transcriptomic and proteomic profiles at baseline and after 14 weeks of TNFi treatment.
  • C-reactive protein (CRP) and Haptoglobin (HP) decreased, while apolipoproteins increased in responders.
  • Higher baseline innate immunity markers and lower adaptive immunity markers (B-cells) were observed in responders.
  • A predictive model combining clinical factors (ASDAS-CRP, gender) and the gene AFF3 achieved high accuracy (AUC=0.97).

Conclusions:

  • Baseline immune cell composition significantly influences adalimumab response in axSpA.
  • A combined model of clinical and gene expression variables can accurately predict TNFi treatment response.
  • These findings support the potential for personalized medicine approaches in axSpA management.
Keywords:
RNA-seqTNF inhibitor (adalimumab)adaptive immune systemaxial spondyloarthritisdisease activityinnate immune systemperipheral bloodproteomicstreatment response

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