RANKL Attenuates Sepsis‐Associated Acute Lung Injury Through the OPG/RANKL/RANK/TLR4 Pathway

TL;DR

This study shows that RANKL pretreatment reduces lung damage in sepsis-related lung injury by reducing inflammation through a specific signaling pathway.

Contribution

The study identifies the OPG/RANKL/RANK/TLR4 pathway as a potential therapeutic target for sepsis-associated acute lung injury.

Findings

Recombinant RANKL pretreatment reduced inflammatory cytokines in serum and lung fluid.

RANKL pretreatment alleviated lung tissue damage and modulated TLR4, RANK, and OPG levels.

Anti-RANKL antibodies reversed the protective effects of RANKL, worsening lung damage.

Abstract

Sepsis‐associated acute lung injury (SA‐ALI) is a critical disease marked by a dysregulated immune response to infection, causing organ dysfunction.

We explored the effect of receptor activator of nuclear factor‐κB ligand (RANKL) on SA‐ALI and the mechanism involving the osteoprotegerin (OPG)/RANKL/RANK (receptor activator of nuclear factor‐κB)/TLR4 (Toll‐like receptor 4) signaling pathway.

The SA‐ALI model was established in C57BL/6 mice. Recombinant RANKL or anti‐RANKL antibodies were administered intraperitoneally as pretreatment 2 h before modeling. After 24 h of modeling, ELISA measured the cytokine concentrations in the serum and bronchoalveolar lavage fluid. The TLR4, RANK, RANKL, and OPG levels in the lung tissues were analyzed using Western blot and real‐time quantitative PCR. HE staining assessed the pathological alterations in lung tissue.

Recombinant RANKL pretreatment had a protective effect on SA‐ALI mice and lowered the serum and bronchoalveolar lavage fluid concentrations of IL‐1β, TNF‐α, and IL‐6. It also reduced TLR4, RANK, and OPG levels in lung tissue while increasing RANKL levels. Moreover, lung tissue pathological changes were alleviated by recombinant RANKL. Conversely, treatment with anti‐RANKL antibodies reversed the changes in the above indicators and aggravated lung tissue pathological damage in mice.

Pretreatment with recombinant RANKL can reduce lung damage in SA‐ALI mice by inhibiting inflammation, with the underlying mechanism potentially associated with the OPG/RANKL/RANK/TLR4 pathway.

Pretreatment with recombinant RANKL can reduce lung damage in SA‐ALI mice by inhibiting inflammation. The mechanism may be related to the OPG/RANKL/RANK/TLR4 signaling pathway. These findings may provide new insights and targets for the treatment of SA‐ALI.

Figures

The levels of IL‐1β, TNF‐α, and IL‐6 in serum. ELISA was conducted to measure cytokine levels. (A) Level of IL‐1β. (B) Level of TNF‐α. (C) Level of IL‐6. *p < 0.05, *p < 0.001, p < 0.0001.

The levels of IL‐1β, TNF‐α, and IL‐6 in bronchoalveolar lavage fluid. ELISA was conducted to detect cytokine levels. (A) Level of IL‐1β. (B) Level of TNF‐α. (C) Level of IL‐6. p < 0.01, *p < 0.001, p < 0.0001.

Comparison of mRNA expression levels of TLR4, RANK, RANKL, and OPG in lung tissues of mice in each group. The mRNA levels were detected with real‐time quantitative PCR. (A) Level of RANKL mRNA. (B) Level of OPG mRNA. (C) Level of RANK mRNA. (D) Level of TLR4 mRNA. *p < 0.001, p < 0.0001.

Comparison of protein expression levels of TLR4, RANK, RANKL, and OPG in lung tissues of mice in each group. The protein levels were detected with Western blot analysis. (A) Representative Western blot results. (B) The relative protein level of RANKL. (C) The relative protein level of OPG. (D) The relative protein level of RANK. (E) The relative protein level of TLR4. *p < 0.05, p < 0.0001.

Pathological changes in lung tissue. Lung tissues were stained with HE staining to observe the pathological changes. (A) Representative HE staining images are shown. (B) Comparison of the lung injury score. p < 0.0001. HE, Hematoxylin‐Eosin.

Tables

TABLE 1. Primer sequences.

Gene	GeneBank ID	Primer sequence (5′−3′)		Tm	CG%	Product length (bp)
GAPDH	NM_008084.3	Sense	TGAAGGGTGGAGCCAAAAG	58.3	52.6	227
		Antisense	AGTCTTCTGGGTGGCAGTGAT	58.4	52.4
OPG	NM_008764.3	Sense	GGAGGAAGACATTGTGTGTCCC	60.6	54.5	157
		Antisense	TCCTCACACTCACACACTCGGT	60	54.5
RANKL	NM_011613.3	Sense	CAGGACTCGACTCTGGAGAGTG	58.7	59.1	152
		Antisense	AACCATGAGCCTTCCATCATAG	58.5	45.5
RANK	NM_009399.3	Sense	CTTGGACCAACTGCACCCTC	60	60	201
		Antisense	CCTTCCTGTAGTAAACGCCGA	59.8	52.4
TLR4	NM_021297.3	Sense	ACACTTTATTCAGAGCCGTTGGT	60	43.5	297
		Antisense	CAGGTCCAAGTTGCCGTTTC	60.4	55

Full text

Introduction

1

Sepsis is a serious condition characterized by organ dysfunction stemming from an uncontrolled response to infection. This condition poses a significant threat to life, with excessive inflammation and multiple organ failures contributing to its high mortality rates [1]. During sepsis, the activated inflammatory cells release numerous inflammatory mediators, causing severe damage to tissues and organs. The lungs are frequently affected, making sepsis‐associated acute lung injury (SA‐ALI) a common complication [1, 2]. Despite advances in mechanical ventilation support and symptomatic treatment, the mortality rate of SA‐ALI patients remains high, with a poor prognosis [3].

The OPG (osteoprotegerin)/RANKL (receptor activator of nuclear factor‐κB ligand)/RANK (receptor activator of nuclear factor‐κB) pathway is essential for the development of mammary epithelial cells, immune response, and bone metabolism [4, 5, 6, 7]. OPG competes with RANKL and functions through the OPG/RANKL/RANK pathway [8]. It is a sepsis biomarker and can predict mortality rates of systemic inflammatory response syndrome [9, 10]. The OPG/RANKL/RANK pathway malfunction can disrupt the immune cell responses and exacerbate the inflammatory cascade in sepsis [11]. Understanding the function of this pathway is essential for developing targeted therapeutic strategies to modulate immune responses and mitigate tissue damage in sepsis and SA‐ALI.

Toll‐like receptor 4 (TLR4) plays a significant role in innate immunity, and through recognizing bacterial endotoxins such as lipopolysaccharides (LPS), it can trigger inflammatory responses [12]. Overactivation of TLR4 can participate in diseases such as rheumatoid arthritis, cardiovascular diseases, and SA‐ALI via inducing the release of various inflammatory factors [13, 14, 15]. Studies have shown that the OPG/RANKL/RANK pathway participates in the pathophysiology of various inflammatory diseases [9, 10], and RANKL/RANK can protect mice from LPS‐induced death by inhibiting TLR4 signaling, thus holding great potential for prevention in acute inflammatory diseases [16]. However, studies on this pathway in SA‐ALI are limited [17].

Despite advancements in the understanding and treatment of SA‐ALI, the precise mechanisms underlying its pathogenesis remain inadequately defined, and its prognosis remains poor. Given that the OPG/RANKL/RANK pathway plays a significant role in regulating inflammatory responses, our study investigated the specific effects of RANKL on the development of SA‐ALI. The objectives of this research are to elucidate the protective mechanisms of RANKL in SA‐ALI and to clarify how it influences inflammation and lung tissue damage by modulating the OPG/RANKL/RANK/TLR4 pathway. This study seeks to provide a deeper understanding of the potential therapeutic targets for managing SA‐ALI in clinical settings.

Materials and Methods

2

Study Animals

2.1

Twenty‐four SPF‐grade healthy male C57BL/6 mice (weighing 18 to 22 g; aged 6–8 weeks) were provided by the Animal Experimental Center of Xinjiang Medical University. They were housed under a 12‐h light‐dark cycle, with 50%–75% humidity, and at 22°C–26°C temperature. Before modeling, the mice were acclimated for 1 week. The animal experiments in this study were conducted following the guidelines. This study obtained approval from the Ethics Committee of Xinjiang Medical University (approval number: IACUC‐20230217‐18; approval date: February 17, 2023).

Establishment of the SA‐ALI Model

2.2

Mice (n = 18) underwent a 12‐h fasting period before the SA‐ALI model establishment, during which they were deprived of food but had access to water. As previously described [18, 19], the cecal ligation and perforation (CLP) technique was used to establish the SA‐ALI model. In detail, following anesthesia with 3% sodium pentobarbital (i.p.; 1 mL/kg body weight, the mice were placed in a supine position, and a midline abdominal incision measuring 1–1.5 cm was created. The cecum was exposed and ligated using a 4–0 surgical suture, leaving approximately 50% of the cecum unligated. Three punctures were made in the distal end of the cecum using a triangular needle (diameter 2.6 mm). A small volume of intestinal contents was expelled. After smooth drainage, the abdomen was closed. The Control group (n = 6) received sham surgery. Specifically, mice were subjected to conventional abdominal anesthesia and skin disinfection, followed by a midline incision of 1–1.5 cm in the lower abdomen. The cecum was exposed following the opening of the abdominal cavity. However, the CLP was not conducted. Then, the abdomen was subsequently closed. As previously described [20], the SA‐ALI model was considered successful if the mice survived 24 h post‐surgery and exhibited signs such as rapid breathing, increased secretion in the eye and nose, piloerection, and lethargy. Power calculations using a power of 80% and an alpha level of 0.05 indicated that a sample size of six animals per group was sufficient to detect statistically significant differences between groups.

Animal Grouping and Treatment

2.3

C57BL/6 mice were randomly assigned to 4 groups (n = 6 each). 2 h before modeling, pretreatment was conducted, where the CLP+anti‐RANKL and CLP + RANKL groups received anti‐RANKL antibodies (i.p.; 200 μg; Bio X cell) or recombinant RANKL (i.p.; 5 μg; ABclonal). The Control and CLP groups were administered normal saline. Subsequently, the SA‐ALI was induced in mice of the CLP, CLP + RANKL, and CLP+anti‐RANKL groups, while the Control group underwent a sham operation.

Sample Collection

2.4

All mice were euthanized with cervical dislocation 24 h post‐surgery. Serum samples were obtained after centrifuging orbital blood. The bronchoalveolar lavage fluid was also collected and then centrifuged to collect the supernatant. After lavage, both lungs were dissected.

ELISA

2.5

The IL‐1β, TNF‐α, and IL‐6 concentrations in both bronchoalveolar lavage fluid supernatant and serum were assessed using specific ELISA kits (ELK Biotechnology Co. Ltd.). A microplate reader (Diatek, DR‐200Bs) was utilized to measure the optical densities of the samples and standards at 450 nm. The cytokine quantification was determined by referencing the standard curve.

Real‐Time Quantitative PCR

2.6

Briefly, 15–20 mg of lung tissues were homogenized in 1 mL of RNAiso Plus reagent (ELK Biotech). Then, the homogenate was incubated with chloroform for 10 min at room temperature. This was followed by centrifugation for 15 min at 12,000 rpm at 4°C, which separated the mixture into aqueous and organic phases. The RNA‐containing upper aqueous phase was mixed with isopropanol and incubated for 10 min at room temperature. Following this, centrifugation was performed for 10 min at 12,000 rpm at 4°C, leading to RNA precipitation, which was then resuspended in a suitable amount of DEPC‐treated water. RNA purity and concentration were measured with a NanoDrop spectrophotometer (Thermo Fisher Scientific). For the reverse transcription process, the M‐MLV reverse transcriptase kit (ELK Biotech) was employed. The reaction mixture included 1 µL of Oligo (dT) primer, 1 µL of a 10 mM dNTP solution, 0.5 µL of RNase inhibitor, 0.5 µL of reverse transcriptase, 0.5 µL of 5× reverse transcription buffer, and 1–2 µg of RNA, with the addition of nuclease‐free water to achieve a final volume of 10 µL. The reverse transcription protocol involved incubation at 25°C for 5 min, followed by 42°C for 1 h, then 70°C for 5 min before concluding at 4°C. Subsequent real‐time quantitative PCR was performed using the SYBR Green PCR SuperMix Kit (ELK Biotech) on the ABI QuantStudio 6 Flex System (Life Technologies). Table 1 lists the primer sequences. The PCR reaction system comprised 0.5 µL of both forward and reverse primers, 5 µL of 2× mix, 1 µL of cDNA, and 3 µL of ddH2O, totaling 10 µL. The target gene underwent amplification with cycling conditions of 95°C for 10 s, 58°C for 30 s, and 72°C for 30 s, repeated for 40 cycles. Relative gene levels were determined using the 2^−△△Ct^ method, with GAPDH as the internal control.

Western Blot Analysis

2.7

Lung tissues were washed, minced, homogenized, lysed, and centrifuged to obtain proteins. The BCA kit (AS1086; ASPEN Biotechnology Co. Ltd) quantified protein concentration. The proteins were subjected to electrophoresis and transfer, followed by a 1‐h blocking. After that, the pre‐diluted primary antibodies against OPG (cat# DF6824; Affinity Bioscience), RANKL (cat# 23408‐1‐AP; Proteintech Group Inc.), RANK (cat# ab222215; Abcam), TLR4 (cat# 19811‐1‐AP; Proteintech Group Inc.), and β‐actin (cat# TDY051; Tiandeyue Biotechnology Co. Ltd) were added and probed overnight at 4°C. The next day, incubation with the pre‐diluted goat anti‐rabbit HRP‐conjugated secondary antibody (cat# AS1107; ASPEN Biotechnology Co. Ltd) was conducted. A chemiluminescence kit (cat# AS1059; ASPEN) was used for visualization. The band grayscale values were measured using the ImageJ image analysis software, with β‐actin as an internal reference.

Hematoxylin‐Eosin (HE) Staining

2.8

Lung specimens were fixed with 4% paraformaldehyde for 24 h, after which they underwent dehydration, embedding, and slicing. The sections were then stained with hematoxylin and eosin staining. The pathological changes were observed. Specifically, the severity of lung injury was assessed by a trained pathologist who has experience in evaluating histopathological samples. The scoring was performed based on a standardized scoring system that evaluates several criteria, including neutrophil infiltration, alveolar hemorrhage, pulmonary edema, and alveolar septal widening [21]. The scoring criteria were: 0 points: no lesion; 1 point: mild lesion; 2 points: moderate lesion; 3 points: severe lesion; and 4 points: very severe lesion. The cumulative score represents the lung injury score of mice.

Statistical Analysis

2.9

GraphPad Prism 9.0 software and SPSS 26.0 were utilized for data analysis. The Shapiro–Wilk Test was conducted to assess the normal distribution of the data. Measurement data of normal distribution are presented as mean ± standard deviation. For data with homogeneous variance, an independent sample t‐test was conducted. Welch's test was applied when the data had a non‐normal distribution or heterogeneity of variance. To compare multiple groups, ANOVA was applied, and Tukey's post hoc test was subsequently employed for further comparisons. Statistical significance was determined at p < 0.05.

Results

3

RANKL Pretreatment Decreases IL‐1β, TNF‐α, and IL‐6 Levels in Serum and Bronchoalveolar Lavage Fluid

3.1

We detected cytokine levels in serum by using ELISA. In the CLP group, the concentrations of IL‐1β (Figure 1A), TNF‐α (Figure 1B), and IL‐6 (Figure 1C) were markedly elevated compared to the Control group (p < 0.05). Interestingly, these cytokine concentrations showed notable declines after recombinant RANKL pretreatment (p < 0.05). Conversely, their concentrations after anti‐RANKL pretreatment exhibited substantial elevations (p < 0.05).

*The levels of IL‐1β, TNF‐α, and IL‐6 in serum. ELISA was conducted to measure cytokine levels. (A) Level of IL‐1β. (B) Level of TNF‐α. (C) Level of IL‐6. *p < 0.05, ***p < 0.001, ***p < 0.0001.

We further validated their changes in bronchoalveolar lavage fluid. Consistently, mice in the CLP group exhibited a significant increase in IL‐1β, TNF‐α, and IL‐6 (Figure 2A–C) concentrations in bronchoalveolar lavage fluid than the Control group (p < 0.05). Conversely, recombinant RANKL pretreatment induced a notable decrease in these cytokine concentrations (p < 0.05). On the other hand, mice in the CLP+anti‐RANKL group demonstrated a considerable increase in these cytokine levels (p < 0.05).

*The levels of IL‐1β, TNF‐α, and IL‐6 in bronchoalveolar lavage fluid. ELISA was conducted to detect cytokine levels. (A) Level of IL‐1β. (B) Level of TNF‐α. (C) Level of IL‐6. **p < 0.01, ***p < 0.001, ***p < 0.0001.

These results indicate that the modulation of the RANKL pathway caused significant alterations in cytokine levels in serum and bronchoalveolar lavage fluid, indicating its crucial role in modulating inflammatory responses in SA‐ALI.

RANKL Pretreatment Upregulates RANKL mRNA While Downregulating the OPG, TLR4, and RANK mRNAs in Lung Tissues

3.2

To analyze the changes in TLR4, RANK, RANKL, and OPG mRNA levels in lung tissues, we performed real‐time quantitative PCR. In comparison to the Control group, the mRNA expression of RANKL (Figure 3A) in lung tissues showed a notable reduction in the CLP group (p < 0.05). However, there were substantial increases in OPG (Figure 3B), RANK (Figure 3C), and TLR4 (Figure 3D) (p < 0.05). Notably, recombinant RANKL pretreatment abolished these changes, with elevated RANKL while declining OPG, TLR4, and RANK. Additionally, after anti‐RANKL pretreatment, there was a notable decrease in RANKL, but significant elevations in OPG, TLR4, and RANK (p < 0.05).

*Comparison of mRNA expression levels of TLR4, RANK, RANKL, and OPG in lung tissues of mice in each group. The mRNA levels were detected with real‐time quantitative PCR. (A) Level of RANKL mRNA. (B) Level of OPG mRNA. (C) Level of RANK mRNA. (D) Level of TLR4 mRNA. ***p < 0.001, ***p < 0.0001.

RANKL Pretreatment Increases RANKL Protein and Decreases OPG, TLR4, and RANK in Lung Tissues

3.3

The protein levels in lung tissues were measured with Western blot analysis. As shown in Figure 4A,B, the RANKL protein in lung tissues significantly decreased in the CLP group, whereas that of OPG (Figure 4A,C), RANK (Figure 4A,D), and TLR4 (Figure 4A,E) notably elevated, compared with the Control group (p < 0.05). However, recombinant RANKL pre‐treatment reversed the changes of these proteins, as demonstrated by a decline in OPG, RANK, and TLR4 and an elevation in RANKL (p < 0.05). Furthermore, the RANKL after anti‐RANKL pretreatment was reduced, while the OPG, RANK, and TLR4 levels were elevated (p < 0.05). The changes at the protein levels were consistent with those at the mRNA levels. These results underscore the dynamic interplay between the RANKL signaling pathway and the inflammatory responses in SA‐ALI.

*Comparison of protein expression levels of TLR4, RANK, RANKL, and OPG in lung tissues of mice in each group. The protein levels were detected with Western blot analysis. (A) Representative Western blot results. (B) The relative protein level of RANKL. (C) The relative protein level of OPG. (D) The relative protein level of RANK. (E) The relative protein level of TLR4. *p < 0.05, ***p < 0.0001.

Pretreatment With RANKL Attenuates the Pathological Damage in Lung Tissues Induced by CLP

3.4

To observe the histopathological changes in lung tissues, we performed HE staining. Compared to the Control group, the lung alveolar wall thickness of mice in the CLP group increased, while the number of alveoli decreased, and there was evident alveolar and interstitial hemorrhage as well as inflammatory cell infiltration (Figure 5A). Importantly, recombinant RANKL treatment induced notable improvement in alveolar and interstitial hemorrhaging, reduction of inflammatory cell infiltration, and mitigation of pulmonary pathological damage. In contrast, the anti‐RANKL pretreatment resulted in narrowed and structurally disordered alveolar septa and worsened pulmonary pathological damage. Statistically, the CLP group displayed notably elevated lung injury scores than the Control group (p < 0.05) (Figure 5B). The lung injury score lowered notably following pretreatment with recombinant RANKL, whereas it elevated after pretreatment with anti‐RANKL (p < 0.05). These findings showed that CLP induced SA‐ALI in mice and resulted in pronounced inflammatory damage in lung tissues, and pretreatment with RANKL alleviated the pulmonary pathological damage induced by CLP.

*Pathological changes in lung tissue. Lung tissues were stained with HE staining to observe the pathological changes. (A) Representative HE staining images are shown. (B) Comparison of the lung injury score. ***p < 0.0001. HE, Hematoxylin‐Eosin.

Discussion

4

The pathogenesis of SA‐ALI is complex, involving various pathways and cytokines [22]. As sepsis progresses to ALI, a significant accumulation and infiltration of immune cells into lung tissues occurs, activating intracellular signaling pathways and releasing large amounts of cytokines such as IL‐1β, TNF‐α, and IL‐6, leading to continuous activation of inflammatory cells and creating a detrimental cycle that ultimately triggers a cytokine storm [2]. Here, we have obtained consistent results. After the construction of the SA‐ALI model, the mice exhibited increased respiratory rate, more secretions, piloerection, decreased food intake and activity, lethargy, and curling behavior (data not shown). Furthermore, ELISA revealed that the concentrations of IL‐1β, TNF‐α, and IL‐6 in the CLP group showed notable elevations. Additionally, HE staining of lung tissues demonstrated that the CLP group had increased alveolar wall thickness, reduced alveoli number, enhanced inflammatory cell infiltration, and significantly elevated lung injury score. These results indicate the successful construction of the SA‐ALI model.

OPG has been validated to be a biomarker associated with sepsis, and it can predict the mortality of patients experiencing systemic inflammatory response syndrome [10]. In this study, inflammatory factors in the bronchoalveolar lavage fluid and serum of CLP group mice, as well as the OPG expression, displayed notable elevations. Lung pathology showed inflammatory cell infiltration. Recombinant RANKL pretreatment reversed these changes, while pretreatment with anti‐RANKL aggravated them. These results demonstrate that OPG may play a role in SA‐ALI progression and could worsen SA‐ALI by intensifying the inflammatory response.

IL‐6 and TNF‐α are recognized pro‐inflammatory cytokines that frequently increase in levels during sepsis and are involved in SA‐ALI development [23, 24, 25]. IL‐1β is another key cytokine that contributes to the inflammatory cascade and has been shown to play a significant role in lung injury models [26, 27]. Additionally, RANKL is a member of the OPG/RANKL/RANK pathway and has potential regulatory functions in immune responses and inflammation [28, 29]. The interaction between RANKL and RANK facilitates the binding of tumor necrosis factor receptor‐associated factor 6 (TRAF6) with RANK, leading to the attenuation of LPS‐induced TLR4 signaling in macrophages and the downregulation of pro‐inflammatory mediators [16]. TLR4 is considered a key regulatory factor for inflammation and immune cell apoptosis in the SA‐ALI model [30]. The transduction of TLR4 signaling in macrophages involves the recruitment of TRAF6, which may lead to inflammation in SA‐ALI [31]. Inhibiting TLR4 has a protective effect on SA‐ALI [12]. It has been reported that RANKL inhibited the body's response to LPS, and RANKL pretreatment protected mice from LPS‐induced death by reducing the expression of TLR4 pathway adaptor proteins, thereby decreasing the cytokine storm triggered by LPS‐induced septic shock [32]. Therefore, RANKL itself may not regulate the expression of inflammatory cytokines, but pre‐treatment with RANKL can prevent the LPS‐induced production of TNF‐α and IL‐6 [33]. This study demonstrated that the CLP group exhibited significantly elevated concentrations of IL‐1β, TNF‐α, and IL‐6 in mouse serum and bronchoalveolar lavage fluid than the Control group. Moreover, an increase in the expression levels of both mRNA and proteins for OPG, RANK, and TLR4 was observed in lung tissues, whereas the levels of RANKL mRNA and protein displayed a marked decrease. Additionally, a deterioration in lung tissue pathology and a significantly increased lung injury score were observed. Recombinant RANKL pretreatment resulted in a considerable decrease in IL‐1β, TNF‐α, and IL‐6 concentrations, alongside significant reductions in OPG, RANK, and TLR4 in lung tissues, as well as an increase in RANKL. Additionally, an attenuation in lung tissue pathology and a significantly decreased lung injury score were observed. Conversely, these changes were reversed by anti‐RANKL pretreatment. These findings align with earlier research [34, 35], suggesting that the OPG/RANKL/RANK/TLR4 pathway may contribute to the pathophysiology of SA‐ALI through its anti‐inflammatory properties. OPG blocks the interaction between RANK and RANKL by binding to RANKL, thus aggravating the inflammatory response of mice [36]. Mice lacking the OPG gene showed reduced LPS‐induced production of pro‐inflammatory cytokines, whereas deficiency in the RANKL gene led to elevated production of pro‐inflammatory cytokines and a notable rise in mortality rates following LPS administration [32].

The primary objective of this study was to establish the net protective effect of RANKL within the integrated and clinically relevant context of the whole organism. Our compelling in vivo data successfully achieve this, demonstrating that systemic RANKL administration confers a definitive protective advantage to the lung in sepsis. This “physiology‐first” discovery approach was indispensable, as it preserves the critical crosstalk between immune cells, the endothelium, and the lung epithelium that is central to the disease pathophysiology. While reductionist in vitro models are powerful for isolating cellular mechanisms, they cannot replicate this integrated multicellular environment, which is likely integral to the full manifestation of RANKL's effect as demonstrated here. Therefore, our in vivo findings are not a preliminary observation but rather a definitive demonstration of physiological function that provides the essential foundation and clear rationale for all subsequent mechanistic studies.

Study Limitations

4.1

It is important to acknowledge several limitations. Firstly, the sample size is limited, which may affect the generalizability of our findings and reduce the statistical power of certain analyses. Secondly, the exclusive use of male mice, while controlling for the confounding effects of the female estrous cycle on immune responses [37], precludes the examination of potential sex‐specific effects. Thirdly, while we focused on specific cytokines such as IL‐1β, TNF‐α, and IL‐6, the absence of additional cytokines and established lung injury markers restricts a comprehensive understanding of the inflammatory response and lung damage linked with RANKL and anti‐RANKL treatments. Furthermore, the analysis at a single 24‐h time point captures the acute phase but does not define the kinetic profile of the inflammatory response. Fourthly, the study did not evaluate the long‐term effects of RANKL treatment, limiting our ability to conclude the chronic implications of this intervention. Additionally, we did not sufficiently validate neutrophil status, nor did we explore the effects of RANKL and anti‐RANKL on neutrophil dynamics, which prevents an in‐depth understanding of neutrophil activation and behavior post‐treatment. Finally, the methodologies used, including the timing of interventions and the translation of animal data to human contexts, present inherent challenges, and potential interactions with other therapeutic agents were not examined.

Future Directions

4.2

To address these limitations, future research should aim to increase sample sizes to improve the statistical power and generalizability of findings. Importantly, studies incorporating both sexes are needed to validate our findings and explore potential sex‐based differences. Incorporating measurements of additional inflammatory cytokines and established lung injury markers, such as macrophage inflammatory protein‐2 and lactate dehydrogenase, will provide a more thorough understanding of the inflammatory response and the impact of RANKL and anti‐RANKL treatments on lung injury. A detailed time‐course analysis is also essential to elucidate the temporal dynamics of RANKL's protective effects. Moreover, assessing the long‐term effects of RANKL treatment would be essential for elucidating the chronic implications on lung function and pathology. Future studies should also focus on investigating neutrophil status in SA‐ALI samples (such as lungs, bronchoalveolar lavage fluid, and blood) using techniques like immunohistochemistry and flow cytometry to understand neutrophil activation in detail. Additionally, investigating the effects of RANKL and anti‐RANKL on neutrophil dynamics (such as neutrophil extracellular trap formation, neutrophil migration, and apoptosis) will enhance the understanding of neutrophil‐related mechanisms in ALI. Building directly upon the physiological foundation established here, future work will be guided to dissect the cell‐specific mechanisms. This will involve employing advanced in vitro models, such as LPS‐stimulated human lung epithelial cells (e.g., BEAS‐2B) pre‐treated with RANKL or anti‐RANKL antibody. Specific analyses will include qPCR for pathway genes, ELISA for cytokine secretion, and imaging for epithelial barrier integrity. To accurately model the immune‐epithelial interactions central to ALI, this work will progress to co‐culture systems. Notably, bridging findings from animal models to human studies will be crucial for developing novel therapeutic strategies aimed at reducing lung injury and improving survival rates in sepsis, thereby enhancing the relevance and applicability of the research outcomes. Finally, exploring potential interactions between RANKL and other therapeutic agents may provide insights into comprehensive treatment strategies for SA‐ALI, guiding future therapeutic interventions.

Conclusion

5

In summary, RANKL is crucial for preventing SA‐ALI, likely by inhibiting the TLR4 signaling pathway through its interaction with RANK. This process helps to reduce inflammation, mitigate lung tissue damage, and improve lung function. Consequently, the OPG/RANKL/RANK/TLR4 pathway could represent a promising target for therapeutic intervention in SA‐ALI, offering a foundational approach for clinical diagnostic and treatment strategies.

Author Contributions

Xinrong Niu: conceptualization, data curation, formal analysis, funding acquisition, investigation, software, supervision, writing – original draft, writing – review and editing. Nurmaimeti Turson: data curation, formal analysis, investigation, software, writing – review and editing. Weilin Chen: data curation, formal analysis, investigation, software, writing – review and editing. Hui Li: data curation, formal analysis, investigation, software, writing – review and editing.

Ethics Statement

The animal experiments in this study were conducted following the guidelines and were approved by the Ethics Committee of Xinjiang Medical University (approval number: IACUC‐20230217‐18; approval date: February 17, 2023).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Author Checklist ‐ Full.