Neutrophils are rapid-acting, short-lived cells, forming the first line of defense against invading microbes through various processes, including producing cytokines, releasing granules containing antimicrobial proteins (i.e., lactoferrin) and proteases (i.e., matrix metalloproteinases [MMPs]), and generating neutrophil extracellular traps (NETs). Neutrophil dysregulation, particularly increased NETosis, is linked to autoimmune diseases like systemic lupus erythematosus (SLE). In particular, a proinflammatory neutrophil subset termed low-density granulocytes (LDGs) is elevated in SLE patients (1). LDGs are transcriptionally distinct, producing more IFNγ, TNFα, type I IFNs, and NETs compared to autologous and healthy control normal-density neutrophils (referred to here as traditional neutrophils [TNs]) (2–4), suggesting possible mechanisms by which LDGs influence SLE pathogenesis.

In contrast to LDGs, NET formation is similar between SLE and healthy TNs (4), suggesting that TNs might exert different functional responses or not contribute to SLE pathogenesis. However, studies on the role of TNs in SLE pathogenesis are limited and somewhat conflicting. For example, one study suggested that TNs are pathogenic through the upregulation of IFNα mRNA (2), while another found that neutrophils may be regulatory by restricting CD4+ T cell proliferation (5). This study compares the activation and functional responses of SLE and healthy TNs to understand their contributions to SLE pathogenesis.

We found that despite reduced activation at resting, TNs from SLE patients can respond to external stimulation; however, SLE TNs exhibit different functional responses compared to control TNs. For example, resting SLE TNs produced more of the IFN-associated chemokine IP-10, which is increased right before SLE classification and flare (9, 12–14), and contributes to T cell chemoattraction and activation (15). In addition, resting SLE TNs may produce more APRIL and IL-21. Although the consequences of APRIL and IL-21 production by TNs remain unknown, previous studies have found that, in healthy individuals and during infection, neutrophils provide B cell help within the spleen through APRIL and IL-21, inducing immunoglobulin class switching, somatic hypermutation, and antibody production (10, 11). Therefore, TNs may also contribute to autoantibody production in SLE.

Interestingly, following stimulation, SLE TNs secreted less proinflammatory cytokines and NETs but released more MMP-8, while TNs from SLE patients with low or high disease activity released more lactoferrin, compared to control TNs, suggestive of increased degranulation. However, levels of the degranulation marker MMP-9 did not significantly differ. Although the role of MMP-8 in SLE is unknown, other MMPs, such as MMP-9, may play a regulatory role in SLE, potentially by cleaving autoantigens, reducing their immunogenicity and promoting immune complex clearance (16). In addition, lactoferrin may inhibit NET formation (17), consistent with the reduced NETosis we observed in SLE TNs following stimulation. Thus, SLE TNs may play a more anti-inflammatory role in the presence of G-CSF and GM-CSF, suggesting that they contribute to SLE pathogenesis differently, dependent on the inflammatory environment.

A limited number of studies have investigated the functional phenotypes of SLE compared to healthy TNs, and results have been somewhat conflicting. These studies found that at rest and following stimulation with PMA, SLE and healthy TNs exhibit similar functional responses, including ROS production, NETosis, and cytokine expression (2, 4). Consistent with these studies, we found similar CD66b expression on SLE and healthy TNs, which is a marker for granules required for ROS generation. However, in contrast to other studies, following G-CSF/GM-CSF stimulation, our data suggest that SLE TNs produce less NETs and proinflammatory cytokines compared to healthy TNs. This may be a result of different external stimulations used in our and other studies, as we did not see these differences following R848 stimulation. Consistent with functional differences, SLE and healthy TNs differ in gene expression and DNA methylation, specifically of IFN-regulated genes (2, 3, 18). Thus, our study and others demonstrate potential functional differences between SLE and healthy TNs; however, studies encompassing a more comprehensive analysis of neutrophil functional responses are needed. Although an evaluation of autologous LDGs was not included in this study, our data suggest that SLE TNs may have different functional responses compared to SLE LDGs, which are hyperresponsive and produce elevated proinflammatory cytokines and NETs compared to autologous TNs (2–4). Based on the gene expression profiles and morphology of LDGs, some studies postulate that LDGs are immature cells that are prematurely released from the bone marrow due to increased recruitment during inflammation (19), which may explain these functional differences. In addition, the increase in LDGs and excessive inflammation observed in SLE may indicate an increase in immature or exhausted SLE TNs; however, our data show that TNs express markers of mature neutrophils and retain the ability to respond to external stimuli, suggesting that SLE TNs are not immature or exhausted. Instead, we found that following stimulation, SLE TNs may be anti-inflammatory as they produce less proinflammatory cytokines and NETs. Future studies will assess whether TN functions differ based on the frequency of LDGs, providing further insight into the relationship between LDGs and TNs in SLE patients.

Our results suggest that TN responses are regulated differently in SLE compared to healthy individuals. Although the exact nature of differential regulation is unclear, we found that miRNAs implicated in neutrophil development and function (20), miR130a, miR132, miR27a, and miR223, are significantly lower in SLE neutrophils. miR130a is highly expressed in early neutrophil precursors and reduced significantly upon maturation (21); therefore, a reduction of miR-130a in SLE TNs supports the notion that SLE TNs are not more immature compared to control TNs. In contrast, miR132, miR27a, and miR223 exhibit high expression in more mature neutrophils, with a further increase of miR132 in activated neutrophils (21), suggesting that these miRNAs may instead influence the observed functional differences. For example, although the role of miR223 in neutrophils in SLE is unknown, miR223 inhibits neutrophil activation and neutrophil-driven inflammation in tuberculosis and hepatic injury mouse models (22). Thus, the reduced levels of miR223 may contribute to the increased production of proinflammatory mediators in unstimulated SLE TNs. However, future studies are needed to determine how these miRNAs contribute to TN functions in SLE.

This study was limited by the small sample size, especially in the miRNA and mRNA analyses. Furthermore, gene expression analyses were determined using targeted qPCR and the use of bulk RNA-sequencing may reveal additional differences. Finally, the SLE patients included in this study were treated and had long-standing disease, and additional differences may be revealed in populations of treatment-naïve patients.

Together, our data suggest that TNs may contribute to SLE pathogenesis; however, their contributions may differ compared to LDGs and depend on the inflammatory environment. The increased production of IP-10, APRIL, and IL-21 by SLE TNs suggest that resting SLE TNs may contribute to SLE pathogenesis through the modulation of T cell and humoral responses. In contrast, in the presence of G-CSF and GM-CSF, SLE TNs produce less inflammatory cytokines and more MMP-8 and lactoferrin, suggesting a potential regulatory role. However, future mechanistic studies are needed to determine how these functional differences impact SLE pathogenesis.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by Oklahoma Medical Research Foundation Institutional Review Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

NJ: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing. CW: Formal analysis, Visualization, Writing – original draft, Writing – review & editing. TA: Data curation, Investigation, Methodology, Writing – review & editing. EC: Data curation, Investigation, Methodology, Writing – review & editing. CA: Data curation, Investigation, Methodology, Writing – review & editing. JG: Data curation, Investigation, Methodology, Writing – review & editing. JJ: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.