The occurrence and development of vertebral osteoporosis regulated by IL-8

Abstract

Vertebral osteoporotic fracture is a common type of fracture, and the incidence is higher in the elderly. However, the relationship between vertebral osteoporotic fractures and interleukin-8 (IL-8) remains unclear. A total of 163 patients with osteoporotic vertebral fractures were recruited. Clinical and follow-up data were recorded, and the expression levels of IL1, MMP9, IL-8, and C-reactive protein in blood were measured. Pearson Chi-square test and Spearman correlation coefficient were used to analyze the relationship between vertebral osteoporotic fractures and related parameters. Univariate and multivariate logistic regression and univariate and multivariate Cox proportional hazards regression were used for further analysis. Pearson chi-square test, Spearman correlation coefficient and Logistic regression analysis showed that IL1 and IL-8 were significantly associated with vertebral osteoporotic fractures. Univariate Cox regression analysis showed that age and IL-8 expression level were significantly associated with maintenance time from recovery to recurrence of vertebral osteoporotic fractures. Multivariate Cox regression analysis showed that IL-8 expression level was significantly associated with maintenance time from recovery to recurrence of vertebral osteoporotic fractures. The higher the expression level of IL-8, the more likely it is to develop vertebral osteoporotic fracture, and the more likely it is to relapse in a short time.

1. Introduction

Osteoporosis (OP) is a metabolic bone disease characterized by the loss of bone tissue quality, the destruction of bone microstructure and bone density caused by a variety of factors.^[1] The elderly have a high incidence, mainly manifested as chronic pain, some patients with limited activity, and may even increase the mortality of patients.^[2] With the increasing aging, the incidence of OP in the elderly is also increasing year by year.^[3]

As an important weight-bearing and stress part of the human body, the vertebral body has a wide activity area and participates in many actions, which is one of the most vulnerable parts of the body. Vertebral osteoporotic fractures are the most common type of fracture.^[4] The patient’s bone healing process is slow, the quality of life is low, and it is easy to lead to various complications, which not only increases the risk of disability and death, but also brings a heavy economic burden to the patient’s family.^[5] Osteoporotic fractures of the vertebral body are most common in the elderly. Because of the OP of the elderly, minor violence can cause compression fractures of the vertebral body. The management of osteoporotic fractures of the vertebral body is important and can be treated conservatively. The height of the vertebral body will not be restored to the original, but the current compression will be maintained. The best outcome is that no vertebral height will continue to change. At present, minimally invasive treatment is basically adopted, which can provide rapid analgesia, improve vertebral height, shorten patients’ bed time, reduce complications, reduce mortality, and improve the quality of life of patients.^[6,7] In cases where there has been a significant improvement following treatment or complete recovery, but there is a possibility of recurrence or worsening, such as in the context of vertebral osteoporotic fractures that have been cured but later reappear as vertebral osteoporotic fractures without the occurrence of new vertebral fractures, this situation is considered a relapse. Vertebral osteoporotic fractures and their relapse may be influenced by genetic regulation, leading to an increased risk of disease occurrence, as well as changes in the maintenance time from recovery to recurrence (MTRR).^[8,9]

Interleukin-8 (IL8) is a chemokine produced primarily by mononuclear macrophages and other cell types such as epithelial cells, airway smooth muscle cells, and endothelial cells.^[10] Interleukin-8 (IL-8), with a molecular weight of about 8KD, is initially a protein consisting of 99 amino acids, which is cleaved to form the active IL-8 isoform, which is a 77-amino acid peptide in nonimmune cells and a 72-amino acid peptide in monocytes and macrophages.^[11] The amino acid sequence has high homology with many inflammatory factors, belonging to the same family. There are 2 types of IL-8 receptors: one can only bind IL-8, while the other can also bind other chemokines; both neutrophils and basophils expressed abundant IL-8 receptors on the surface. The role of IL-8 in the participation and regulation of human reproductive physiological and pathological processes has been confirmed, and one of its mechanisms is the binding of IL-8 to its specific receptor.

In recent years, studies have found that IL-8 is involved in almost the entire reproductive process of mammals, such as ovulation, luteal formation, endometrial proliferation, decidualization, embryo implantation and its growth and development.^[12] IL-8 functions by binding to its specific receptor and triggering a series of biological events. However, the relationship between IL-8 and vertebral osteoporotic fractures remains unclear.

This study hypothesized that during the development of vertebral osteoporotic fractures, higher IL-8 content would lead to a higher risk of vertebral osteoporotic fractures and a shorter time to recurrence. Based on the above hypothesis, we recruited 163 patients with osteoporotic vertebral fractures. These results may reveal IL-8 as a potential molecular target of vertebral osteoporotic fracture and provide new ideas for its molecular mechanism.

2. Methods

2.1. Patients and ethics

A total of 163 patients diagnosed with vertebral osteoporotic fracture in Beijing Rehabilitation Hospital Affiliated to Capital Medical University from March 2015 to June 2020 were selected.

Inclusion criteria: diagnosis of vertebral osteoporotic fracture; normal cardiopulmonary function; normal blood clotting.

Exclusion criteria: poor lung, heart and liver function; patients and their families did not consent to participate in the trial.

This study was approved by the Ethical Committee of Beijing Rehabilitation Hospital Affiliated to Capital Medical University, and all patients signed written informed consent.

According to research literature, MMP9, KL1, IL8, and C-reactive protein (CRP) have been found to have a certain correlation with vertebral osteoporotic fractures. Ma^[13] demonstrated that in osteoporotic and thoracolumbar vertebral patients, the levels of CDKK-1, RANKL, TRACP-5b, β-CTX, IL-2, IL-6, MMP2, MMP9, leptin, and TNF-α were higher compared to the normal control group, indicating that these genetic levels have some influence on vertebral osteoporotic fractures. MMP9 can play a crucial role in bone remodeling and repair by breaking down some matrix molecules in bone tissue. IL-1 has 2 main subtypes, IL-1α and IL-1β, both of which can stimulate inflammatory responses, leading to the activation of immune cells and the release of inflammatory mediators. Studies suggest that abnormal activation of IL-1 may be related to bone injuries and destruction associated with OP. Overexpression of IL-1 and IL-8 may lead to inflammation in bone tissue, disrupting normal bone cell function, thereby affecting bone density and quality.^[14–16] CRP is a protein produced during inflammation and tissue damage. CRP levels rise during inflammatory reactions and infections, making it a marker commonly used to detect the presence of inflammation or infection in the body. Vertebral osteoporotic fractures are typically caused by reduced bone density and OP, while chronic inflammatory states can affect bone metabolism and increase the risk of fractures. Therefore, an elevated CRP level may indirectly reflect an inflammatory state, which could be related to the occurrence of vertebral osteoporotic fractures.^[17,18] Numerous studies indicate that MMP9, KL1, IL8, and CRP are significantly associated with this disease, making them candidates for multivariate analysis.

Regarding the normal reference ranges for MMP9, KL1, IL8, and CRP, they are as follows:

MMP9 (Matrix Metalloproteinase 9): Typically, the normal reference value for MMP9 in the blood is very low, usually less than or equal to 85 ng/mL.

KL1 (Kidney Tubular Marker): KL1 is an indicator of kidney tubular function, and normal values may vary depending on the laboratory and measurement method. Typically, KL1 concentration in urine is very low, usually less than or equal to 20 mg/g creatinine.

IL8: IL8 is a cytokine, and its normal reference values may also vary depending on the laboratory. Generally, IL8 has a low normal concentration in the blood, but specific normal values can vary by lab.

CRP: CRP is an inflammation marker. Normal CRP concentrations in the blood are typically very low, usually at 0.8 mg/dL or lower. However, in situations like inflammation or infection, CRP levels can significantly rise.

2.2. The parameter

According to the clinical data, the patients were classified according to sex (male/female), age (≤65/>65), MMP9 expression (low/high), IL-1 expression (low/high), IL-8 expression (low/high), and CRP expression (low/high). Patients were followed up to record the time from recovery to recurrence.

2.3. Detection of blood related parameters

The venous blood samples of the patients were immediately submitted for detection, and the ELISA method was used to detect MMP9 (Kit: Human MMP-9 ELISA Kit), IL-1 (Kit: Human IL-1 sRI ELISA Kit), IL-8 (Kit: Human IL-8/IL-8 ELISA Kit) and CRP (Human C-reactive protein [CRP]).

2.4. ELISA methods to detect

1. Serum samples

The whole blood samples were placed at room temperature for 2 hours or overnight at 4 ℃ and separated at 3000 RPM/heart for 15 minutes at 2 to 8 ℃. The supernatant was taken for immediate detection.

• 2.ELISA experiment procedure
  • 2.1.Coating: The antibody was diluted with carbonate coating buffer to a protein content of 1 to 10 μg/mL. Add 100 μL to each well of polystyrene plate overnight at 4 °C. The next day, the solution in the well was discarded and washed with washing buffer 3 times, 3 minutes each time.
  • 2.2.Blocking: 200 μL of blocking solution was added to each well and incubated for 1 to 2 hours at 37°C.
  • 2.3.Washing: Carefully remove the sealing film, put it into the washing machine, and wash for 3 to 5 times. Also wash the plate manually: discard the liquid, add 300 µL of washing solution to each well, soak for 1 to 2 minutes, pat dry on absorbent paper, repeat 3 to 5 times.
  • 2.4.Sample addition: Add 100 μL of appropriate dilution of the sample to be tested to the coated reaction well. (At the same time do blank Wells, double dilution of standard Wells, can be added as negative control Wells and positive control Wells as quality control points).
  • 2.5.Incubation: Plate was sealed with plate sealing membrane and incubated at 37°C for 1 to 2 hours.
  • 2.6.Washing: The same as Step 3.
  • 2.7.Adding antibody: Add 100 μL diluted biotinylated antibody working solution to each well.
  • 2.8.Incubation: Plate was sealed with plate sealing membrane and incubated at 37°C for 1 hour.
  • 2.9.Washing: The same as Step 3.
  • 2.10.Adding enzyme conjugate: Add 100 μL of diluted enzyme conjugate working solution to each well.
  • 2.11.Incubation: Plate was sealed with plate sealing membrane and incubated at 37°C for 30 minutes in the dark.
  • 2.12.Washing: Same as Step 3.
  • 2.13.Adding chromogenic substrate: Add 100 μL of TMB substrate solution to each well, and react at 37°C for 10 to 30 minutes in the dark until obvious color gradient appears in the Wells of the multiple dilution standard.
  • 2.14.Termination of reaction: 100 μL 2M sulfuric acid was added to each reaction well, and the color changed from blue to yellow.
  • 2.15.Determination of results: Within 10 minutes, OD values of each well were measured on a microplate reader at 450 nm after zeroing a blank control well.

2.5. Method of statistics

Data are expressed as a percentage of the total. Pearson chi-square test and Spearman correlation coefficient were used to analyze the relationship between clinical parameters and vertebral osteoporotic fractures. Univariate and multivariate logistic regression analyses were used to calculate the odds ratio (OR) values of each variable of vertebral osteoporotic fracture. Univariate and multivariate Cox proportional hazards regression analyses were performed to explore the potential prognostic factors of MTRR. MTRR refers to the period during which a patient, after receiving treatment for a certain disease or symptom, remains symptom-free for a certain duration but subsequently experiences a recurrence or worsening of the condition. This time interval can be used to assess the effectiveness of treatment and the degree of disease control. Different diseases and treatment modalities may result in varying durations of time from recovery to recurrence, making it an important clinical metric to help healthcare providers and patients understand disease progression and treatment outcomes.

All statistical analyses were performed using SPSS software, version 21.0 (IBM Corporation, Armonk, NY). P < .05 was considered statistically significant.

3. Results

3.1. Pearson chi-square test was used to analyze the association between vertebral osteoporotic fractures and related factors

The relationship between vertebral osteoporotic fractures and related clinical factors was summarized by Pilsen chi-square test. IL-1 (P = .026) and IL-8 (P = .014) were significantly correlated with vertebral osteoporotic fractures. However, sex (P = .502), age (P = .828), MMP9 (P = .943), CRP (P = .669) had no significant correlation with vertebral osteoporotic fracture (Table 1).

Table 1.

Relevant characteristics of patients with osteoporotic fracture of the vertebral body.

Characteristics			Osteoporotic fracture of the vertebral body		P
			No	Yes
Sex	Male	84	36 (22.1%)	48 (29.4%)	.502
	Female	79	38 (23.3%)	41 (25.2%)
Age	≤65	72	32 (19.6%)	40 (24.5%)	.828
	>65	91	42 (25.8%)	49 (30.1%)
MMP9	Low	82	37 (22.7%)	45 (27.6%)	.943
	High	81	37 (22.7%)	44 (27.0%)
IL-1	Low	88	47 (28.8%)	41 (25.2%)	.026*
	High	75	27 (16.6%)	48 (29.4%)
CXCL8	Low	71	40 (24.5%)	31 (19.0%)	.014*
	High	92	34 (20.9%)	58 (35.6%)
CRP	Low	81	38 (23.3%)	43 (26.4%)	.669
	High	82	36 (22.1%)	46 (28.2%)

Pearson chi-square test.

^*P < .05.

3.2. Spearman correlation coefficient was used to analyze the association between vertebral osteoporotic fractures and related factors

Further analysis of Spearman correlation coefficient showed that vertebral osteoporotic fractures were significantly correlated with IL-1 (ρ = 0.174, P = .026) and IL-8 (ρ = 0.193, P = .014). However, Sex (ρ = 0.053, P = .505), age (ρ = 0.017, P = .829), MMP9 (ρ = 0.006, P = .943) and CRP (ρ = 0.030, P = .702) had no significant correlation with vertebral osteoporotic fracture (Table 2).

Table 2.

The relationship between characteristics of patients and osteoporotic fracture of the vertebral body.

Characteristics	Osteoporotic fracture of the vertebral body
	ρ	P
Sex	−0.053	.505
Age	−0.017	.829
MMP9	−0.006	.943
IL-1	0.174	.026*
CXCL8	0.193	.014*
CRP	0.030	.702

Spearman correlation analysis.

^*P < .05.

3.3. Univariate logistic regression analysis of vertebral osteoporotic fracture and related factors

Binary logistic regression was used to determine the relationship between related parameters and vertebral osteoporotic fracture, OR, and 95% confidence interval (95%CI). Table 3 describes the OR and 95%CI of the study subjects at the univariate logistic regression level, and the results show that IL-1 (OR = 2.038, 95%CI: 1.085–3.829, P = .027), and IL-8 (OR = 2.201, 95%CI: 1.170–4.140, P = .014) were significantly associated with vertebral osteoporotic fracture. However, sex (OR = 0.809, 95%CI: 0.436–1.501, P = .502), age (OR = 0.933, 95%CI: 0.501–1.737, P = .828), MMP9 (OR = 0.978, 95%CI: 0.528–1.812, P = .943), CRP (OR = 1.129, 95%CI: 0.609–2.093, P = .699) had no significant correlation with vertebral osteoporotic fracture (Table 3).

Table 3.

Influence of relevant parameters on osteoporotic fracture of the vertebral body based on univariate Logistic regression analysis.

Parameter			Osteoporotic fracture of the vertebral body
			OR	95%CI	P
Sex	Male	84	1		.502
	Female	79	0.809	0.436–1.501
Age	≤65	72	1		.828
	>65	91	0.933	0.501–1.737
MMP9	Low	82	1		.943
	High	81	0.978	0.528–1.812
IL-1	Low	88	1		.027*
	High	75	2.038	1.085–3.829
CXCL8	Low	71	1		.014*
	High	92	2.201	1.170–4.140
CRP	Low	81	1		.699
	High	82	1.129	0.609–2.093

95%CI = 95% confidence interval; OR = odds ratio.

^*P < .05.

3.4. Multivariate logistic regression analysis was used to analyze the related factors of vertebral osteoporotic fracture

Table 4 applies multivariate logistic regression to describe the OR and 95%CI of the study subjects at the multivariate level. IL-1 (OR = 2.108, 95%CI: 1.102–4.033, P = .024) and IL-8 (OR = 2.362, 95%CI: 1.210–4.611, P = .012) was significantly associated with vertebral osteoporotic fracture. However, sex (OR = 0.867, 95%CI: 0.452–1.663, P = .668), age (OR = 0.815, 95%CI: 0.417–1.591, P = .548), MMP9 (OR = 1.036, 95%CI: 0.542–1.978, P = .915) and CRP (OR = 1.018, 95%CI: 0.532–1.949, P = .957) had no significant correlation with vertebral osteoporotic fracture (Table 4).

Table 4.

Multivariate logistic regression analysis was used to analyze the characteristics and influence of vertebral osteoporotic fractures.

Characteristics	Osteoporotic fracture of the vertebral body
	OR	95%CI	P
Sex	0.867	0.452–1.663	.668
Age	0.815	0.417–1.591	.548
MMP9	1.036	0.542–1.978	.915
IL-1	2.108	1.102–4.033	.024*
CXCL8	2.362	1.210–4.611	.012*
CRP	1.018	0.532–1.949	.957

95%CI = 95% confidence interval; OR = odds ratio.

^*P < .05.

3.5. Univariate Cox regression analysis of the proportional risk of vertebral osteoporotic fracture

Table 5 shows univariate hazard ratios (HRs) and 95% confidence intervals (95%CI) for vertebral osteoporotic fractures. In terms of overall survival, age (HR = 1.611, 95%CI: 1.134–2.288, P = .008) and IL-8 (HR = 2.398, 95%CI: 1.680–3.423, P < .001) were significantly associated with MTRR. However, sex (HR = 1.080, 95%CI: 0.744–1.526, P = .664), MMP9 (HR = 0.968, 95%CI: 0.688–1.361, P = .851), IL-1 (HR = 1.125, 95%CI: 0.795–1.592, P = .506), and CRP (HR = 1.089, 95%CI: 0.772–1.536, P = .629) had no significant correlation with MTRR (Table 5).

Table 5.

Univariate Cox proportional regression was used to analyze the related characteristics and the effects on MTRR.

Characteristics			MTRR
			HR	95%CI	P
Sex	Male	84	1		.664
	Female	79	1.080	0.764–1.526
Age	≤65	72	1		.008*
	>65	91	1.611	1.134–2.288
MMP9	Low	82	1		.851
	High	81	0.968	0.688–1.361
IL-1	Low	88	1		.506
	High	75	1.125	0.795–1.592
CXCL8	Low	71	1		<.001*
	High	92	2.398	1.680–3.423
CRP	Low	81	1		.629
	High	82	1.089	0.772–1.536

95%CI = 95% confidence interval, HR = hazard ratio, MTRR = maintenance time from recovery to recurrence.

^*P < .05.

3.6. MTRR based on multivariate Cox regression was used to analyze the proportional hazards of related characteristics

In order to effectively control the influence of confounding factors, all factors were included in the multivariate Cox regression model. Multivariate Cox proportional regression analysis showed that IL-8 expression level (HR = 2.334, 95%CI: 1.595–3.416, P < .001) was significantly correlated with MTRR. However, sex (HR = 0.902, 95%CI: 0.630–1.293, P = .575), age (HR = 1.349, 95%CI: 0.931–1.954, P = .114), MMP9 (HR = 0.981, 95%CI: 0.687–1.401, P = .915), IL-1 (HR = 1.269, 95%CI: 0.885–1.819, P = .195) and CRP (HR = 1.078, 95%CI: 0.752–1.544, P = .683) had no significant correlation with MTRR (Table 6).

Table 6.

Effect of relevant characteristics on MTRR based on multivariate Cox regression analysis.

Characteristics	MTRR
	HR	95%CI	P
Gender	0.902	0.630–1.293	.575
Age	1.349	0.931–1.954	.114
MMP9	0.981	0.687–1.401	.915
IL-1	1.269	0.885–1.819	.195
CXCL8	2.334	1.595–3.416	<.001*
CRP	1.078	0.752–1.544	.683

95%CI = 95% confidence interval, HR = hazard ratio, MTRR = maintenance time from recovery to recurrence.

^*P < .05.

4. Discussion

Pearson chi-square test, Spearman correlation coefficient and Logistic regression analysis showed that IL1 and IL-8 were significantly associated with vertebral osteoporotic fractures. In addition, univariate Cox regression analysis showed that age and IL-8 expression level were significantly associated with MTRR of vertebral osteoporotic fractures. Multivariate Cox regression analysis showed that IL-8 expression level was significantly associated with MTRR of vertebral osteoporotic fractures.

Vertebral osteoporotic fracture is the most common osteoporotic fracture, which is a relatively serious injury, mostly caused by external force. The vertebral body is caused by excessive impact force, and its clinical course is diverse.^[19] Once damaged, it will bring great inconvenience to daily life and reduce the quality of life.

According to the degree and location of the fracture, the mild degree of the fracture can be generally conservative rehabilitation, bed rest, and severe or nerve injury, should be timely to the hospital for surgical treatment.^[20] OP is a disease of bone metabolism, which is mainly manifested as the decrease of bone mineral density and bone quality, eventually leading to the decrease of human bone strength and increase of bone fragility. It is irreversible in the human aging process, so it is easy to cause fractures in daily activities, thereby increasing the risk of vertebral osteoporotic fractures.^[21]

The production of IL-8 is closely related to mitogen-activated protein kinase (MAPK) signaling pathway.^[22] IL-8 is a cytokine secreted by macrophages and epithelial cells, and its main biological activity is to attract and activate neutrophils. It belongs to a typical chemokine of the CXC family.^[23] Chemokines are cell-secreted signaling proteins that play an important physiological role in the immune system, and their main function is to guide the movement of leukocytes to sites of inflammation.^[24] Chemokine involves coordination between cells expressing appropriate chemokine receptors that can migrate along chemokine concentration gradients to facilitate localization of individual cells to specific tissues. IL-8 is also synthesized by monocytes, macrophages, and fibroblasts.^[25] It is involved in inflammatory processes, autoimmune, and cardiovascular diseases, as well as malignant diseases, and is responsible for the recruitment and activation of neutrophils and granulocytes to sites of inflammation.^[26]

IL-8 is one of the earliest and most well-studied chemokines as a proinflammatory chemokine. Chemokine receptor CXCR1/2 and its ligand IL-8 play important roles in the activation and transport of inflammatory mediators. Chemokines and their cognate receptors also play important roles in the immune system, mediating immune cell activation and trafficking in both innate and adaptive responses, and are also involved in hematopoiesis and development by guiding and mobilizing precursor cells to the maturation site.^[27] Inflammation is a defense response caused by infection and tissue damage.^[28] IL-8 exerts chemotactic effects on neutrophils, thereby achieving its regulation of inflammatory responses, and also promotes angiogenesis and cell migration.^[29] IL-8 also stimulates airway epithelial cells, causing them to contract and increasing their permeability to inflammatory cells.^[30] Proteases secreted by neutrophils and other inflammatory cells when they accumulate cause persistent and extensive tissue damage.^[31,32]

IL-8, in combination with CXCR1/2, recruits neutrophils to the epithelium and lamina propria at the site of inflammation. Distorted and uncontrolled expression of proinflammatory cytokines and excessive recruitment of neutrophils are deleterious, and it may lead to tissue damage through the release of MMPS, reactive oxygen species, and cytokines. Some studies have shown that^[33], IL-8 plays an important role in lung inflammation, and its expression level is increased in patients. The circulation due to the continuous production of IL-8 leads to increased activation and recruitment of inflammatory cells to the lungs, which in turn leads to the pathological features of the lungs. Previous studies have also shown that IL-8 levels are significantly associated with neutrophil count, airway inflammation, and pulmonary dysfunction in patients with chronic obstructive pulmonary disease and asthma.^[34,35] Other studies have reported rapid recruitment of neutrophils to infected sites in the gut in response to IL-8. This is due to increased PMN migration capacity leading to overexpression of CXCR1/2, bacterial infection triggers the release of IL-8 from epithelial cells, which mediates PMN migration from the blood circulation.^[36] A human study by Volpin et al showed that the expression levels of IL-6 and IL-8 may be potential biomarkers for predicting the development and extent of systemic inflammatory responses in injured patients.^[37] The expression levels of proinflammatory cytokines IL-6 and IL-8 were significantly increased in all injured patients, and the levels of IL-6 and IL-8 were the highest in severely injured patients.

IL-8 is one of the initial cytokines released by multiple cell types, including T cells, endothelial cells, and fibroblasts, in response to inflammatory stimuli. It acts by recruiting neutrophils, T cells, and basophils to sites of inflammation, and its elevated levels have been associated with the development of various disease states. As an inflammatory factor, the higher the content of IL-8, the stronger the inflammatory reaction, the more prone to OP, and then lead to vertebral osteoporotic fracture.

However, there are some defects in this study. Although clinical data have been examined and analyzed, the molecular mechanism by which IL-8 expression levels contribute to vertebral osteoporotic fractures has not been validated in animal models. Therefore, future studies should focus on animal experiments to explore the molecular pathway and mechanism of IL-8 in vertebral osteoporotic fractures.

5. Conclusion

The expression level of IL-8 is significantly correlated with the incidence and recurrence time of vertebral osteoporotic fractures. The higher the expression level of IL-8, the more likely to occur vertebral osteoporotic fracture, and the higher the IL-8, the more likely to relapse vertebral osteoporotic fracture in a short time. As a potential target of vertebral osteoporotic fracture, IL-8 provides a new idea for the molecular mechanism of its occurrence and development.

Author contributions

Conceptualization: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Data curation: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Formal analysis: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Funding acquisition: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang

Investigation: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Methodology: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Project administration: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Resources: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Software: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Supervision: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Validation: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Visualization: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Writing – original draft: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.

Writing – review & editing: Danyang Ding, Hao Zhu, Xingyu Fan, Qian Yang, Ye Wang, Hui Xue, Chunbo Kang.