Examination on Risk Factors of Infertility Caused by EMT and Their Correlation with VEGF, TNF-α, IL-6, IL-10, and IL-17.

In order to explore the risk factors of infertility caused by endometriosis (EMT) and their correlation with vascular endothelial growth factor (VEGF), TNF-α, IL-6, IL-10, and IL-17, endometriosis sufferers admitted to our hospital from January 2021 to May 2022 are selected to conduct the examination. According to the pregnancy of patients, patients were included in the simple EMT set and EMT combined infertility set, with 50 cases in each group. The degree of dysmenorrhea is evaluated by the VAS score, and Luminex liquid protein is used to analyze the standards of the tumor necrosis factor (TNF-A), interleukin (IL)-10, IL-6, IL-17, and VEGF. Logistic multifactor regression decomposition is applied to analyze the risk factors of infertility in EMT sufferers. Besides, the standards of VEGF, TNF-α, IL-6, IL-10, and IL-17 in sufferers with different periods/agony degrees are evaluated, and the correlation of different periods/agony degrees with VEGF, TNF-α, IL-6, IL-10, and IL-17 is analyzed. The results show that the different R-AFS periods are notoriously positively correlated with VEGF, TNF-α, IL-6, IL-10, and IL-17 (all P < 0.05), and the VAS score is notoriously positively correlated with the abovementioned factors.

1. Introduction

Endometriosis (EMT) is a disease caused by the transfer of endometrial tissue to other parts of the uterine cavity after menstruation. The incidence rate of women of childbearing age is about 10%. Pelvic metastasis can lead to pelvic adhesion, dysmenorrhea, and infertility [1]. The pathogenesis of EMT is complex, and the medical community has not yet formed a consensus. At present, the widely accepted pathogenesis theory is the menstrual reflux endometrial implantation theory [2]. The main pathological changes of endometriosis are periodic bleeding of the ectopic endometrium and fibrosis of surrounding tissues, forming ectopic nodules. Dysmenorrhea, chronic pelvic pain, abnormal menstruation, and infertility are the main symptoms. The lesions can affect all pelvic tissues and organs, most commonly in the ovaries, uterus, rectum, and uterosacral ligaments. They can also occur in the abdomen, thorax, limbs, etc. [3, 4]. The transfer of endometrial tissue from the uterus to the pelvis and abdominal cavity needs to break through the lines of ascites, peritoneal cells, and extracellular matrix (ECM) to complete the implantation and growth of ectopic sites. To a certain extent, the inflammatory reaction of endometriosis in endometriosis is caused by the concept of intraperitoneal environment. Cytokines play an important role in the pathogenesis as immune modulators. The abnormal expression of cytokines in the abdominal cavity is related to many connections. These connections may lead to infertility by affecting egg cell development and maturation, sperm movement, and other processes [5, 6]. Examining the correlation between local cytokines in the abdominal cavity and endometriosis has an important practical value for the treatment of patients [7]. However, there is no in-depth study on the relationship between local cytokines and endometriosis in the pathogenesis of EMT [8].

Aiming to provide a basis for the therapy of EMT-complicated infertility sufferers, the risk factors of infertility caused by EMT are analyzed and the comparison with VEGF, TNF-α, and IL-6 are conducted in this study. The results show that the different R-AFS periods are notoriously positively correlated with VEGF, TNF-α, IL-6, IL-10, and IL-17 (all P < 0.05), and the VAS score is notoriously positively correlated with the abovementioned factors. For sufferers with EMT, the risk factors for infertility include the R-AFS period and the cytokines VEGF, TNF-α, IL-6, IL-10, and IL-17, and there is an extensive correlation between the agony degree of different periods and the incidence of endometriosis.

This paper is organized as follows: Section 2 discusses the related work, followed by the data and examination methods in Section 3. In Section 4, the results and analysis are presented. Finally, some concluding remarks are summarized in Section 5.

2. Related Work

From the clinical point of view, the occurrence of many gynecological diseases has extensive correlation. The redundant endocrine hormones and their expression have been examined. It has been confirmed that the endocrine and immune systems in women can interact, regulate, and play a wide range of interactions. At the same time, the patient's body forms a more complex endocrine regulatory neuroimmune system [7, 8]. Female endocrine hormones are mainly secreted by the hypothalamus pituitary ovary. The development, maturation, and fertilization of eggs are closely related to the endocrine environment in women. Therefore, female endocrine disorders will widely destroy the endocrine environment of the body, which will seriously affect women's fertility and pregnancy. In this process, it may lead to female infertility or abortion [9]. Domestic studies have shown that infertile patients with endometriosis show different degrees of endocrine hormone disorders. Decomposing the endocrine hormone secretion standards of these patients can provide reliable data for the clinical diagnosis and treatment of patients [10].

In the incidence of gynecological clinical diseases, EMT is a disease with a high incidence rate, and female infertility often occurs after the onset [11]. Some studies have pointed out that the new angiogenesis in ectopic endometrium adhesion implants and plays an important role in the process of growth and ectopic endometrial of planting and growing new blood vessels to provide nutrition. VEGF is clinically regarded as a proangiogenic cytokine with the strongest effect and loftiest specificity [12]. The results indicated that the subjoined expression standard of VEGF can promote the formation of neovascularization, provide conditions for the planting and growth of the ectopic endometrium, and play a certain role in the occurrence and development of EMs. However, TNF-αproduces cytokines for neutrophils and T lymphocytes, and participates in a number of physiological and immune processes, with antitumor and cytotoxic effects. Many studies have found that TNF-αplays an important role in promoting the pathogenesis of EMT [13]. The increase of macrophages in the peritoneal fluid of EMT sufferers leads to the increase of interleukin and TNF-αstandards and interferes with a series of cell proliferation [14].

It is speculated that the subjoined concentration of TNF-αmay cause the jiangu of sperm activity and inhibit the grinding of endometrial interstitial cells. In addition, the lofty concentration of TNF-α may cause the subjoined standard of prostaglandin decomposition and promote the effect of inflammatory factors. The subjoined standard of VEGF secreted by mean cells in the abdominal cavity further promotes the growth of local pelvic blood vessels, increases pelvic adhesion, and aggravates EMT staging [15, 16]. Interleukin is a multieffector factor and plays an important role in immune response, etc. Abnormal expression of interleukin leads to a lessened glycoprotein signal expressed on the sperm surface and infertility. Some studies also believe that subjoined interleukin standard inhibits fallopian tube oscillation frequency and interferes with reproduction [17]. In accordance with previous reports, it is speculated that interleukin can inhibit macrophages, etc. The increase of TNF-α concentration promotes the expression of inflammatory cytokines, resulting in the increase of interleukin standard. IL-17 is produced by CD + cells and has the role of promoting inflammatory response. It may be involved in EMT lesions by inducing cell production of IL-6 and secretion of TNF-α [18].

3. Data and Examination Methods

3.1. General Information

In this study, sufferers with endometriosis treated in our hospital from January 2021 to May 2022 are selected to carry out the examination. According to whether the sufferers had infertility, the sufferers are divided into the simple EMT set (set A) and the EMT combined with infertility set (set B) according to the principle of 1 : 1 allocation, with 50 sufferers in each set. The age of set A ranged from 25 to 41 years, with an average of 30.14 ± 3.62 years, and the course of ailment ranged from 1.1 to 7 ears, with an average of 3.85 ± 1.26 years. The age of set B ranged from 26 to 42 years, with an average of 31.24 ± 3.77 years, and the course of Ailment ranged from 0.9 to 8 years, with an average of 3.75 ± 1.35 years. The general clinical data such as age and course of ailment are contrast between the two sets, α, and there is no statistical significance between the two sets. All sufferers signed informed consent and the examination is approved by the medical ethics committee of our hospital. All sufferers enrolled in the examination signed informed consent. In this examination, general information and clinical data collected will only be used for examination decomposition and will not be used for other purposes. During the therapy, if the sufferer has any discomfort, he/she should inform the competent doctor in time to decide the next therapy plan. During the whole therapy process, the doctor must be informed of the change of the patient's condition on time. During the therapy, patients are not allowed to use any other drugs or other therapy methods for the ailment. If used, the doctor must be informed.

Inclusion criteria are as follows: (1) meet EMT diagnostic criteria [19]; (2) 25–45 years of age [20]; (3) regular menstruation and follicular period [21]; (4) all sufferers are informed and voluntarily participated in the experimental examination [22].

Exclusion criteria are as follows: (1) prior use of hormone therapy within six months [23]; (2) sufferers with malignant tumor and adenomyosis [24]; (3) complicated with severe organ dysfunction; (4) complicated with metabolic ailments such as hypertension and diabetes; (5) with autoimmune ailment; (6) history of hormone and antibiotic therapy in the recent 6 months; (7) pregnancy and lactation; (8) complicated with severe infectious and inflammatory ailments; (9) combined with mental illness.

3.2. Diagnostic Criteria

With regard to endometriosis, the first pelvic examination shows uterine fixation and retraction. There are nodules with tenderness in the rectouterine depression, lower posterior wall of uterus, or the uterine sacral ligament. Blue spots or nodules may be palpable or visible to the naked eye in the vaginal vault. One side of the uterus or bilateral accessory area can feel the fixed or mobile mass, cystic mass, and there is light pressure agony. B-ultrasonography confirmed ectopic cysts in the endometrium of the ovary and confirmed their location, shape, and size. Occasionally, there is a lump not detected on pelvic examination. Ovarian endometriosis cyst wall was thicker, not smooth, rougher, and surrounding organs appear adhesion.

Infertility is judged as the sufferers who have had regular and normal sex for two years after marriage, have not taken any contraceptive measures, and have not been able to conceive.

3.3. Examination Methods

3.3.1. Data Collection

After admission, general information is collected on all sufferers, including age, BMI, ailment type, agony severity, and period. The sufferers are graded according to the American Fertility Society modified endometriosis (R-AFS): period I to IV. The degree of dysmenorrhea is evaluated by the VAS score: no agony(0 points), mild agony (1–3 points), moderate agony (4–7 points), severe agony (8–10 points).

3.3.2. Serum Factor Detection

The clinical data of the sufferers are collated. On the 14th to 19th day of the menstrual cycle, 2–3 mL of peritoneal fluid is extracted from the rectal depression by laparoscopy, which is placed at room temperature for 2h and stored by centrifugation. Tumor necrosis factor (TNF-A) and interleukin are measured by the Luminex liquid protein decomposition system. IL-10, IL-6, IL-17, and vascular endothelial growth factor (VEGF) are detected strictly in accordance with the instructions.

3.4. Observation Indicators

The observation indicators are as follows: (1) univariate decomposition of clinical data disparities between set A and set B; (2) logistic multifactor regression decomposition of risk factors affecting infertility in EMT sufferers; (3) standards of VEGF, TNF-α, IL-6, IL-10, and IL-17 in sufferers with different periods and agony degrees are analyzed; (4) VEGF, TNF-α, IL-6, IL-10, and IL-17 are correlated with different periods and agony degree.

3.5. Statistical Methods

In this study, all data are sorted out and corresponding databases are established. All databases are input into SPSS 26.0 for data processing, wherein the measurement data are subjected to a normal test, which is expressed as (‾x ± S). The independent sample T test is used for the data conforming to normal multiple sets, and paired sample T test is used for the data within sets. Nonconforming to normal is the Mann–Whitney U test. The rate is expressed as % and the test is χ2. Correlation is analyzed by Pearson/Spearman. The influencing factors are analyzed by multiple logistic regression. The ROC curve is used to analyze diagnostic performance. When P < 0.05, the disparity between data is considered statistically extensive.

4. Results and Analysis

4.1. Univariate Decomposition of Clinical Data Disparities

There is extensive correlation between agony degree, R-AFS period, and expression of VEGF, TNF-α, IL-6, IL-10, and IL-17 in set A and set B, mainly manifested as agony degree, R-AFS period, expression of VEGF, TNF-α, IL-6, IL-10, and IL-17 in set B are notoriously loftier than that in set A. There are extensive disparities among the data (P < 0.05), as shown in Table 1.

Table 1

Univariate decomposition of clinical data disparities.

Indicators	Set A (n = 50)	Set B (n = 50)	χ2/t	P
Age (years)	30.14 ± 3.62	31.24 ± 3.77	0.563	0.782
Course of Ailment (years)	3.85 ± 1.26	3.75 ± 1.35	0.775	0.437
Ailment types
BMI (kg/m2)	21.86 ± 2.33	21.63 ± 2.17	0.635	0.467
Ailment types			0.536	0.626
Ovary type	34 (68.00)	36 (72.00)
Peritoneal type	8 (16.00)	8 (16.00)
Deep infiltration type	6 (12.00)	5(10.00)
Other site type	2 (4.00)	1 (2.00)
The degree of agony			11.526	<0.001
There is no agony	20 (40.00)	6 (12.00)
Mild agony	15 (30.00)	10 (20.00)
Moderate agony	6 (12.00)	14 (28.00)
Severe agony	9 (18.00)	20 (40.00)
Instalment			12.635	<0.001
Phase I	23 (46.00)	7 (14.00)
II period	17 (34.00)	3 (6.00)
III period	4 (8.00)	16 (32.00)
IV period	6 (12.00)	24 (48.00)
VEGF (pg/ml)	218.59 ± 13.52	261.11 ± 18.52	19.563	<0.001
TNF-α(pg/ml)	43.87 ± 8.15	62.16 ± 10.59	15.632	<0.001
IL-6 (pg/ml)	105.38 ± 13.52	153.40 ± 17.96	13.557	<0.001
IL-17 (pg/ml)	38.20 ± 6.55	54.37 ± 6.69	10.152	<0.001
IL-10 (pg/ml)	2.35 ± 1.13	4.77 ± 1.58	7.893	<0.001

4.2. Logistic Multifactor Regression Decomposition of Risk Factors Affecting Infertility in EMT Sufferers

Multifactor decomposition assignment took infertility in EMT sufferers as the dependent variable; agony degree, R-AFS period, VEGF, TNF-α, IL-6, IL-10, and IL-17 are taken as independent variables, and the model is selected based on clinical practice. Logistic regression model decomposition shows that R-AFS period, VEGF, TNF-α, IL-6, IL-10, and IL-17 are risk factors for infertility in EMT sufferers(P < 0.05), as shown in Table 2 and Figure 1.

Table 2

Risk factors for infertility in EMT sufferers by logistic regression multivariate decomposition.

Indicators	Multivariate decomposition results
	β	Se	Wald	OR	95%CI	P
R-AFS instalment	0.826	0.325	6.613	0.482	0.316∼0.532	0.003
VEGF	0.300	0.046	40.215	0.351	0.251∼0.513	0.005
TNF-α	0.232	0.093	7.501	0.261	0.087∼0.559	0.002
IL-6	0.524	0.252	11.136	0.512	0.312∼0.755	0.001
IL-10	0.800	0.325	6.613	0.482	0.316∼0.532	0.006
IL-17	0.232	0.093	7.501	0.261	0.087∼0.559	0.010
The degree of agony	0.463	0.059	21.529	0.033	0.005∼0.054	0.068

Figure 1

Multivariate logistic regression decomposition of infertility risk factors in EMT sufferers.

4.3. Expression Standards of VEGF, TNF-α, IL-6, IL-10, and IL-17 in Sufferers with Different Periods

With a loftier period, the standards of VEGF, TNF-α, IL-6, IL-10, and IL-17 subjoined (P < 0.05), as shown in Table 3.

Table 3

Disparities in VEGF, TNF-α, IL-6, IL-10, and IL-17 standards in sufferers with different periods.

Set	VEGF (pg/ml)	TNF-α(pg/ml)	IL-6 (pg/ml)	IL-10 (pg/ml)	IL-17 (pg/ml)
Phase I (n = 26)	211.53 ± 11.52	35.52 ± 8.52	90.15 ± 11.56	30.22 ± 7.15	2.52 ± 0.92
Phase II (n = 25)	233.52 ± 16.72	46.15 ± 9.17	121.52 ± 15.82	38.66 ± 5.29	3.38 ± 1.05
Phase III (n = 19)	246.81 ± 17.29	55.26 ± 9.53	139.66 ± 17.57	43.55 ± 7.45	4.20 ± 1.33
Phase IV (n = 29)	277.63 ± 18.16	69.85 ± 10.77	156.55 ± 18.19	52.71 ± 5.26	5.63 ± 1.57
F	17.852	22.156	19.536	21.051	20.558
P	<0.001	<0.001	<0.001	<0.001	<0.001

4.4. Expression of VEGF, TNF-α, IL-6, IL-10, and IL-17 in Sufferers with Different Agony Standards

With the aggravation of agony, the standards of VEGF, TNF-α, IL-6, IL-10, and IL-17 subjoined (P < 0.05), as shown in Table 4.

Table 4

Expressions of VEGF, TNF-α, IL-6, IL-10, and IL-17 in sufferers with different agony standards.

Set	VEGF (pg/ml)	TNF-α (pg/ml)	IL-6 (pg/ml)	IL-10 (pg/ml)	IL-17 (pg/ml)
No agony (n = 30)	209.36 ± 12.62	32.31 ± 7.56	91.25 ± 12.67	29.63 ± 7.67	2.37 ± 0.96
Mild agony (n = 20)	230.25 ± 15.82	41.57 ± 8.54	122.68 ± 14.19	37.98 ± 6.37	3.45 ± 1.17
Moderate agony (n = 30)	243.91 ± 17.37	54.63 ± 9.38	138.74 ± 18.34	43.58 ± 7.63	4.62 ± 1.22
Severe agony (n = 20)	275.14 ± 18.56	68.25 ± 11.67	158.61 ± 19.58	53.66 ± 5.58	5.89 ± 1.46
F	20.156	19.552	17.159	18.654	19.527
P	<0.001	<0.001	<0.001	<0.001	<0.001

4.5. Correlation of Different Periods of Sufferers with VEGF, TNF-α, IL-6, IL-10, and IL-17

Different R-AFS periods are notoriously positively correlated with VEGF, TNF-α, IL-6, IL-10, and IL-17 (all P < 0.05), as shown in Table 5.

Table 5

Correlation of different periods with VEGF, TNF-α, IL-6, IL-10, and IL-17.

Items	r-AFS phase
	r	P
VEGF	0.635	<0.001
TNF-α	0.715	<0.001
IL-6	0.622	<0.001
IL-17	0.592	<0.001
IL-10	0.585	<0.001

4.6. VAS Scores of Sufferers with Different Agony Degrees

The VAS score of agony severity is notoriously positively correlated with VEGF, TNF-α, IL-6, IL-10, and IL-17 (all P < 0.05), as shown in Figure 2.

Figure 2

Correlation between the VAS score and various factors in different agony degrees: (a) VEGF; (b) TNF-α; (c) IL-6; (d) IL-10; (e) IL-17.

5. Conclusions

In this study, the risk factors of infertility caused by EMT and their correlation with VEGF, TNF-α, IL-6, IL-10, and IL-17 are explored. Endometriosis sufferers admitted to our hospital from January 2021 to May 2022 are selected to conduct the examination. According to the pregnancy of patients, patients were included in the simple EMT set and EMT combined infertility set, with 50 cases in each group. The degree of dysmenorrhea is evaluated by the VAS score, and Luminex liquid protein is used to analyze the standards of tumor necrosis factor (TNF-A), interleukin (IL)-10, IL-6, IL-17 and vascular endothelial growth factor (VEGF). Logistic multifactor regression decomposition is applied to analyze the risk factors of infertility in EMT sufferers. Besides, the standards of VEGF, TNF-α, IL-6, IL-10, and IL-17 in sufferers with different periods/agony degree are evaluated, and the correlation of different periods/agony degree with VEGF, TNF-α, IL-6, IL-10, and IL-17 is analyzed. The observations can provide a basis for clinical therapy in the future. Although certain examination results have been achieved, there are still some limitations. Too few cases may lead to certain bias in the results, and the sample size should be further expanded in future studies.