Distinct Pharmacodynamic Complement Biomarker Signatures Define Iptacopan and Pegcetacoplan Treatment in C3 Glomerulopathy.

INTRODUCTION

C3 glomerulopathy (C3G) is driven by alternative pathway (AP) dysregulation. Iptacopan inhibits factor B, whereas pegcetacoplan inhibits C3/C3b, suggesting distinct pharmacodynamic (PD) biomarker profiles.

METHODS

We conducted an exploratory, nonrandomized observational cohort study of patients with biopsy-confirmed C3G treated with iptacopan (n = 9) or pegcetacoplan (n = 9), using paired pretreatment and approximately 3-month posttreatment samples. Complement activity, protein levels, activation products, autoantibodies, and genetic findings were assessed. Profiles were classified as PD-concordant (PDC), largely PD-concordant (LPDC), or PD-discordant (PDD) using treatment-specific signatures.

RESULTS

Both treatments suppressed AP activity and terminal pathway activation but produced distinct profiles. The expected PDC signature for iptacopan included increases in C3, factor B, C5, properdin, and CH50 and reductions in complement activation products (C3a, C3c, C3d, Bb, and sC5b-9). The expected pegcetacoplan signature included supranormal increases in C3, C3c, and properdin, reductions in C3a, C3d, Bb, and sC5b-9, and generally preserved or increased CH50. PDC profiles occurred in 6 of 9 patients in each cohort. LPDC profiles occurred in 3 iptacopan-treated patients, all nephritic factor-positive, and 2 pegcetacoplan-treated patients with nephritic factors or a likely pathogenic C3 variant. One patient with severe factor H deficiency showed a PDD profile during pegcetacoplan treatment and again in a descriptive posttransplant sample during subsequent iptacopan treatment.

CONCLUSION

Iptacopan and pegcetacoplan produce distinct, mechanism-specific PD signatures in C3G. Pathway-based biomarker assessment may distinguish expected treatment effects from incomplete or discordant biochemical control. These categories describe PD patterns rather than clinical efficacy and require validation against clinical outcomes.