Published March 31, 2022 | Version v1
Other Open

93. A prospective study of NET-formation in ANCA-associated vasculitis using bioimpedance analysis

Description

Background: In ANCA-associated vasculitis (AAV), the neutrophil plays a central role. Recently, neutrophil extracellular traps (NET) have been implicated in the pathogenesis of AAV. Several groups have stated ANCAs and/or serum components of AAV patients can induce NETs. There is accumulating evidence that NET formation is increased during active AAV in contrast to remitted patients. We hypothesize that serum from active AAV patients has a higher NET-inducing activity than treated AAV patients in remission. To test this hypothesis, we developed a high content method to measure NET formation using the xCelligence Real-Time Cell Analysis.

 

Methods: Patients were included from the PROMAVAS study, i.e., a prospective longitudinal study in active AAV patients at Maastricht UMC, between April 2019 and June 2021. Clinical data were obtained from the PROMAVAS database. Serum samples were obtained at the time of active disease (T0), 6 weeks (T1) and 6 months (2) after initiating therapy. Consenting healthy donors were recruited as healthy controls (HC). For NET formation assays healthy control neutrophils were seeded in 96-wells E-plate VIEW and incubated for 4 hours with PMA (25nM, positive control), AAV serum (20% v/v) or HC serum (20% v/v) in the presence or absence of the PAD4 inhibitor (PAD4i; a NET-formation inhibitor). Cell-index (CI) reflecting NET-formation was recorded continuously per well by the xCelligence. CI was validated as NET-formation signal by (immuno)fluorescence (IF) visualizing nuclear integrity (DAPI), extracellular free DNA (SYTOX green) and citrullinated histone 3 (CitH3).

 

Results: Seventy-two patients (M:F; 46:26) were included with a mean age of 63 (±13) years. PR3-, MPO-ANCA or both were detected in 38 (53%), 33 (46%) and 1 (1%), respectively. Renal (n=41; 59%) and pulmonary (n=33; 47%) involvement were the predominant organs involved. Patients were treated either Rituximab (n=43; 60%), cyclophosphamide (n=16; 22%) or both (n=13; 18%). At 6 months 68 (96%) patients were in remission according to a BVAS of 0. Death occurred in 5 (7%) patients. ANCA serum showed increased NET formation reflected by increased nuclear swelling, cell membrane expansion and CitH3 positivity compared to HC serum (IF, both n=7). Accordingly, using bioimpedance, these ANCA and HC sera showed increased CI-max values (median, 3.44 vs. 1.35, resp., P<0.001). Incubation with PAD4i inhibited these CI-max values (median AAV vs. HC, 0.07 vs. 0.06, resp., P=0.8), indicating CI-max values reflect NET formation capacity. Using bioimpedance, active AAV sera (n=72) showed increased NET formation compared to HCs (n=12) (median, 0.38 vs. 0.11, respectively, P=0.001). In all ANCA sera, the presence of NETs was confirmed by effective inhibition with PAD4i (median AAV-uninhibited vs. AAV-PAD4i, 0.38 vs. 0.04, resp., P<0.001) and staining for extracellular free DNA. MPO-ANCA serum showed more NET-formation compared to PR3-ANCA serum (0.50 vs. 0.29, resp., P=0.006) and NET formation correlated mildly with serum creatinine (Rho=0.24, p=0.048). NET formation did not correlate with BVAS, ANCA titre or age at presentation. NET formation capacity decreased after treatment initiation after six weeks and remained low after 6 months (both P<0.001; Wilcoxon signed rank, Figure 1).

 

Conclusions: Active AAV serum shows increased NET formation capacity compared to HC. Bioimpedance is a useful technique to assess NET formation in AAV. Longitudinal serum samples from AAV patients show a decline in NET formation capacity following immunosuppressive therapy after 6 weeks and 6 months, indicating this technique can be helpful to assess treatment efficacy.

 

Disclosures: none

 

Figure 1. NET formation capacity by active AAV serum at presentation (T0), and week 6 and month 6 after treatment initiation showing an overall reduction in NET formation.

 

 

 

Files

Files (26.2 kB)

Name Size Download all
md5:42a6213fc775d49d5c55be6ed1ebc5d3
26.2 kB Download