Increased Type I Interferon Activity with Concurrent Plasmablast Expansion Identifies Systemic Lupus Erythematosus...

Area of Science:

• Immunology
• Rheumatology
• Clinical Medicine

Background:

• Type I interferon (IFN) activity is increasingly recognized for its prognostic significance in systemic lupus erythematosus (SLE).
• Elevated peripheral blood plasmablast (PB) levels are a key feature of lupus pathophysiology.
• Combining these biomarkers may improve the prediction of clinical outcomes in SLE patients.

Purpose of the Study:

• To investigate if combining type I interferon (IFN) activity with elevated peripheral blood plasmablast (PB) levels improves risk stratification for poor clinical outcomes in SLE.
• To assess Sialic acid-binding Immunoglobulin-like Lectin 1 (SIGLEC-1) as a surrogate marker for IFN activity.
• To analyze the association of combined IFN and PB activity with clinical outcomes and treatment requirements in SLE.

Main Methods:

• Prospective collection of clinical data from a single lupus center.
• Flow cytometry analysis of peripheral blood mononuclear cells to measure SIGLEC-1 (IFN activity marker) and PB frequencies.
• Analysis of 1276 samples from 121 SLE patients.

Main Results:

• 48.8% of patients had high IFN activity at baseline, with 27.3% showing concurrent high IFN and PB activity.
• Patients with simultaneous IFN and PB activity had higher anti-dsDNA levels, lower remission rates (24.2%), and higher prednisolone doses (6.3 mg) compared to isolated IFN activity.
• Concurrent IFN and PB activity was associated with more flares, longer time to remission, and higher median time-adjusted prednisolone doses during follow-up.

Conclusions:

• Concurrent elevation in type I interferon and plasmablast activity identifies SLE patients with a poorer prognosis compared to isolated IFN activity.
• Combined IFN and PB assessment may enhance prognostic stratification in SLE.
• These findings support the development of personalized treatment strategies for SLE patients based on combined biomarker analysis.