Inhibition of Interleukin-33 to Reduce Glomerular Endothelial Inflammation in Diabetic Kidney Disease

Abstract

Introduction: Inflammation is a significant contributor to cardiorenal morbidity and mortality in diabetic kidney disease (DKD). The pathophysiological mechanisms linking systemic, subacute inflammation and local, kidney injury-initiated immune maladaptation is partially understood.

Methods: Here, we explored the expression of proinflammatory cytokines in patients with DKD; investigated mouse models of type 1 and type 2 diabetes (T2D); evaluated glomerular signaling in vitro; performed post hoc analyses of systemic and urinary markers of inflammation; and initiated a phase 2b clinical study (FRONTIER-1; NCT04170543).

Results: Transcriptomic profiling of kidney biopsies from patients with DKD revealed significant glomerular upregulation of interleukin-33 (IL-33). Inhibition of IL-33 signaling reduced glomerular damage and albuminuria in the uninephrectomized db/db mouse model (T2D/DKD). On a cellular level, inhibiting IL-33 improved glomerular endothelial health by decreasing cellular inflammation and reducing release of proinflammatory cytokines. Therefore, FRONTIER-1 was designed to test the safety and efficacy of the IL-33-targeted monoclonal antibody tozorakimab in patients with DKD. So far, 578 patients are enrolled in FRONTIER-1. The baseline inflammation status of participants (N > 146) was assessed in blood and urine. Comparison to independent reference cohorts (N > 200) validated the distribution of urinary tumor necrosis factor receptor 1 (TNFR1) and C-C motif chemokine ligand 2 (CCL2). Treatment with dapagliflozin for 6 weeks did not alter these biomarkers significantly.

Conclusion: We show that blocking the IL-33 pathway may mitigate glomerular endothelial inflammation in DKD. The findings from the FRONTIER-1 study will provide valuable insights into the therapeutic potential of IL-33 inhibition in DKD.

Keywords: IL-33; biomarker; diabetic kidney disease; inflammation; phase 2b; tozorakimab.

Graphical abstract

Figure 1

Expression of IL-33 in patients with DKD and inhibition of IL-33 signaling in DKD mouse models. (a) Differentially expressed cytokines relevant to CKD in ascending order of the lowest P-value in the glomerular and tubulointerstitial compartments with significantly differentially expressed cytokines colored green. (b) IL-33 mRNA expression in patients with DKD relative to healthy control living donors in glomeruli (Wilcoxon, P = 7.4 × 10^–5) and tubulointerstitium (Wilcoxon, P = 4.6 × 10^–6) in the ERCB cohort. Boxes show the IQR; the middle horizontal line is the median and the whiskers indicate the minimum and maximum values. Individual data points are shown. (c) GSVA calculated signature score (–1 ≤ x ≤1) based on the redefined IL-33 signature gene set. The box plot shows the distribution of GSVA scores for each CKD condition. Boxes show the IQR; whiskers indicate the maximum, 1.5 × IQR. Outliers beyond 1.5 × IQR are plotted individually. Renal IL-33 (d) mRNA and (e) protein expression in diabetic uninephrectomized (db/db unx) and nondiabetic uninephrectomized (db/+ unx) mice at 16 weeks of age. (f) In vivo study design: mice underwent uninephrectomy at 7 weeks of age and were randomized by UACR at 10 weeks of age. Between 11 and 16 weeks of age, intraperitoneal doses of either isotype control or anti-ST2 antibodies (10 mg/kg) were administered 3 times per week. Urine samples were collected at 10, 13, and 15 weeks. Effect of anti-ST2 antibody on UACR and glomerular damage are shown in (g) and (h), respectively. The linear mixed-effect with trend model was used for the statistical assessment of albuminuria progression. Individual data points are shown, and horizontal lines represent the mean. ∗P < 0.05, ∗∗∗P < 0.001. DKD, diabetic kidney disease; ERCB, European Renal cDNA Bank; FSGS, focal segmental glomerulosclerosis; GSVA, gene-set variation analysis; HT, hypertensive nephropathy; IgA, immunoglobulin A nephropathy; IL-33, interleukin-33; IQR, interquartile range; MCD, minimal change disease; MGN, membranous glomerulonephritis; RPGN, rapidly progressive glomerulonephritis; SLE, systemic lupus erythematosus; TMD, thin basement membrane disease; TN, tumor nephrectomy; UACR, urinary albumin-to-creatinine ratio; unx, uninephrectomized.

Figure 2

IL-33 signaling and downstream effects on HGMEC. (a) IL-33 and ST2 basal mRNA expression in primary human renal cells. (b) IL-33 intracellular protein expression in HGMEC in response to several exogenous stimuli. (c) and (d) Activation of inflammatory signaling pathways; MAP kinases p38 and JNK, and NF-κB nuclear translocation in HGMEC after exogenous IL-33 stimulation. Dose-response curves of proinflammatory cytokine secretion (e) IL-8, (f) TNFR1, and (g) CCL2, in HGMEC in response to IL-33. For (a) to (c), individual data points are shown, and horizontal lines represent the mean. For (d) to (g), error bars represent the SD. CCL2, C-C motif chemokine ligand 2; HGMEC, human glomerular microvascular endothelial cells; IFN-γ, interferon-γ; IL-8, interleukin-8; IL-33, interleukin-33; JNK, c-Jun N-terminal kinase; MAP, mitogen-activated protein; NF-κB, nuclear factor κ-light-chain-enhancer of activated B cells; non stim, nonstimulated; RPTEC, renal proximal tubule epithelial cells; TNFα, tumor necrosis factor α; TNFR1, tumor necrosis factor receptor 1.

Figure 3

Tozorakimab inhibition of IL-33–induced proinflammatory response in HGMEC. Effect of tozorakimab or isotype control antibody treatment on the activation of inflammatory signaling pathways; MAP kinases (a) p38 and JNK, and (b) NF-κB nuclear translocation in HGMEC after exogenous IL-33 stimulation. Effect of tozorakimab or isotype control antibody treatment on the secretion of proinflammatory cytokines; (c) IL-8, (d) TNFR1, and (e) CCL2 in HGMEC after exogenous IL-33 stimulation. Individual data points are shown, and horizontal lines represent the mean. For (c), error bars represent the SD. ∗P < 0.05, ∗∗P < 0.01, or ∗∗∗∗P < 0.0001. CCL2, C-C motif chemokine ligand 2; HGMEC, human glomerular microvascular endothelial cells; IL-8, interleukin-8; IL-33, interleukin-33; JNK, c-Jun N-terminal kinase; MAP, mitogen-activated protein; NF-κB, nuclear factor κ-light-chain-enhancer of activated B cells; TNFR1, tumor necrosis factor receptor 1.

Figure 4

Assessment of urine inflammatory biomarkers in patients with DKD. (a) eGFR, (b) annual eGFR, (c) urine TNFR1, and (d) urine CCL2 of patients with DKD with either stable (black) or progressive loss of eGFR (red) from the Sun-MACRO study. Error bars represent the SD. Percentage change from baseline in urine (e) TNFR1/creatinine and (f) CCL2/creatinine in patients with DKD treated with dapagliflozin or placebo from the IMPROVE study. Individual data points are shown, and error bars represent SD. CCL2, C-C motif chemokine ligand 2; DKD, diabetic kidney disease; eGFR, estimated glomerular filtration rate; TNFR1, tumor necrosis factor receptor 1.

Figure 5

FRONTIER-1 phase 2b study design. Eligible patients were randomized to receive tozorakimab or placebo once every 4 weeks for 24 weeks. All participants received dapagliflozin 10 mg once daily from 12 to 24 weeks. Participants were followed-up with for 10 weeks. ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; eGFR, estimated glomerular filtration rate; Q4W, every 4 weeks; QD, once daily; SGLT2i, sodium-glucose cotransporter 2; T2D, type 2 diabetes; UACR, urinary albumin-to-creatinine ratio.

Figure 6

Inflammation profiles for participants in FRONTIER-1. Baseline expression of (a) hsCRP, (b) eosinophils, (c) TNFR1, and (d) CCL2 across participants in the FRONTIER-1 trial (black bars). (b) and (c) also show expression distributions in participants from independent cohorts for comparison (white bars). (e) Correlations between log-transformed CCL2, TNFR1, and TNFR2. (f) Correlations between log-transformed UACR and log-transformed CCL2 (Pearson’s R, 0.106), TNFR1 (−0.00859), TFR2 (−0.0257) or hsCRP (−0.118). (g) Correlation between log-transformed baseline UACR and eosinophils (Pearson’s R, 0.0555). CCL2, C-C motif chemokine ligand 2; hsCRP, high-sensitivity C-reactive protein; MCP-1, monocyte chemoattractant protein-1; TNFR1, tumor necrosis factor receptor 1; TNFR2, tumor necrosis factor receptor 2; UACR, urinary albumin-to-creatinine ratio.