Could sestrin protein in serum be a new marker of oxidative stress in patients with polycystic ovary syndrome?

Abstract

Objective

PCOS (polycystic ovary syndrome) is one of the most common endocrinological disorders and it is the threshold of many systemic disorders. There are many studies in the literature on the mechanisms that cause increased oxidation in PCOS. Sestrin protein is known to regulate the oxidation. In this study, it is aimed to examine the changes in the level of sestrin protein in women with PCOS.

Methods

A total of 60 women participated the study, 30 of whom were diagnosed with PCOS according to the Rotterdam criteria. Also, 30 women were included in the study as the control group. Demographic information, biochemical analysis results, and sestrin levels of the patients in each group were compared.

Results

The median sestrin level was 6.2 ± 0.8 in the PCOS group and 3.38 ± 0.4 in the control group (p < 0.001). As a result of the evaluation made with ROC analysis, it is observed that serum sestrin levels may be meaningful in the diagnosis of polycystic ovary syndrome. The area under the curve (AUC) value for the 4.69 level was 99.4% (p < 0.001, 95% CI: 96.7% vs. 100%, sensitivity: 100%, specificity: 96.7%).

Conclusions

Sestrin protein is associated with oxidative stress. Sestrin protein can be used as an indicator of increased oxidative stress in PCOS.

摘要

目的

PCOS（多囊卵巢综合征）是最常见的内分泌疾病之一, 可引起许多全身性疾病。学术界有许多关于PCOS患者氧化增加机制的研究, 我们已知sestrin蛋白可以调节氧化, 在这项研究中, 目的是调查PCOS妇女sestrin蛋白水平的变化。

方法

共有60名女性参与了这项研究, 其中30名女性根据鹿特丹标准诊断为PCOS, 此外30名女性在这项研究中作为对照组, 比较两组的人口统计学资料、生化分析结果和sestrin蛋白水平。

结果

PCOS组中位sestrin蛋白水平为6.2±0.8, 对照组为3.38±0.4(P<0.001), ROC分析结果结果表明, 血清sestrin蛋白水平对多囊卵巢综合征的诊断有一定意义, 值为4.69水平时曲线下面积（AUC）为99.4%(P<0.001, 95% CI：96.7% vs. 100%, 灵敏度：100%, 特异度：96.7%).

结论

Sestrin蛋白与氧化应激有关, Sestrin蛋白可作为PCOS患者氧化应激增加的指标。

Keywords:

• Hyperandrogenemia
• menstrual irregularity
• oxidative stress
• polycystic ovary
• sestrin

关键词:

• 高雄激素血症
• 月经失调
• 氧化应激
• 多囊卵巢
• sestrin蛋白

Introduction

Polycystic Ovary Syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age [1]. Many systemic disorders accompany PCOS. It is of significant importance due to its association with cardiological and metabolic disorders [2]. Insulin resistance in PCOS is thought to increase the signs of hyperandrogenism and causes clinical effects [3]. Moreover, follicle development is negatively affected in PCOS by insulin resistance due to effects on luteinizing hormone (LH) in theca cells [4,5].

Insulin resistance seen in PCOS is also thought to be one of the causes of oxidative stress [6]. Studies have shown that oxidative stress increases due to insulin resistance and disruption of endothelial and mitochondrial oxidative metabolism in PCOS patients [6]. Oxidative stress occurs when the ratio between pro-oxidants and antioxidants changes to favor pro-oxidants. The increase in reactive oxygen radicals and reactive nitrogen species causes oxidative stress [7]. Oxidative stress may be an important factor promoting hyperandrogenemia in PCOS by inhibiting the expression of various proteins [8]. In another study, circulating oxidative stress markers were abnormal in women with PCOS. This finding suggests that oxidative stress may play a role in the pathophysiology of this common disorder [9].

Sestrin molecule is a protein that acts as a regulator against DNA damage, oxidative stress, and hypoxia. Sestrin 2 exerts this effect via p53 [10]. Sestrin protein is also known to be associated with insulin resistance. Autophagy caused by Sestrin protein protects insulin sensitivity and glucose metabolism [11].

It is known that PCOS is associated with oxidative stress [6]. Evaluation of the relationship between oxidative stress and PCOS is important to prevent the metabolic effects of this disease. This study aimed to show the change in sestrin protein levels in women with PCOS and reveal the oxidative stress (OS) in PCOS.

Methods

The study protocol was approved by the institution’s Ethics Committee (KAEK/2021.01.30). Written and verbal informed consent was obtained from all the participants before their enrollment in the study. The study was designed as a case-control study. A total of 60 women participated in the study. The study group consisted of 30 patients who applied to the reproductive endocrinology outpatient clinic of our hospital and were diagnosed with PCOS according to the Rotterdam criteria, aged between 18 and 45 [10]. As the control group, 30 women with similar age and body mass index characteristics who applied to our hospital’s gynecology outpatient clinic for routine controls and had no signs of PCOS, were included in the study.

The simple random one-to-one sampling method was used while making this selection. Each patient was evaluated in terms of clinical and laboratory findings at the time of admission. Features such as age, parity, comorbidity, drug use, family history of PCOS, and menstrual irregularity were noted in the history of the patients. All participants included in the study were evaluated in the early follicular phase, on day 3 of a spontaneous or induced menstrual cycle. A clinical examination was performed and anthropometric measurements were recorded. The Ferriman-Gallwey scoring system was used to evaluate the presence of hirsutism [12] and body mass index (BMI) was calculated by dividing body weight (kg) by the square of height (m2). Infertility was defined as the absence of pregnancy albeit minimum one year of regular sexual intercourse [13].

According to the PCOS diagnostic criteria, hyperandrogenic symptoms (hirsutism, acne, androgenic alopecia) and oligomenorrhea (menstrual cycle more than 35 days apart)/amenorrhea (absence of menstrual cycle for at least six months) and in addition to these, polycystic appearance in the ovaries (include the presence of 12 or more follicles in either ovary measuring 2 to 9 mm in diameter and/or increased ovarian volume (>10 ml; calculated using the formula 0.5 x length x width x thickness)) is required to be observed. As the control group, non-pregnant women of reproductive age who were not diagnosed with PCOS were included in the study.

Cardiovascular diseases, infectious and autoimmune diseases, neurological disease, morbid obesity, smoking, and the use of oral contraceptives were the exclusion criteria of PCOS.

Blood samples were taken from the antecubital brachial vein of the participants into the biochemistry tube using a vacutainer. The material taken into the biochemistry tube was centrifuged at 3000× g for 10 min. The obtained serum was taken to Eppendorf and frozen to −80 °C to be used on the analysis day. The Eppendorf was warmed to room temperature on the analysis day, and the frozen serums were thawed. The biochemical evaluation is consisted of measurement of the levels of HOMA-IR (Homeostatic Model Assessment for Insulin Resistance), LH (Luteinizing Hormone), FSH (Follicle Stimulating Hormone), PRL (Prolactin), Dehydroepiandrosterone Sulfate (DHEA-S), Estradiol (E2), and Total Testosterone (total-T). Serum levels of FSH, LH, E2, PRL, Total-T, Insulin and TSH were measured with UnicelDxI 800 Immunoassay System (Beckman Coulter, Fullerton, CA, USA). Serum levels of DHEA-S were measured by radioimmunoassay. Sestrin values in serum samples were measured using the ELISA method in a plate reader (Thermo Scientific Multiscan FC, 2011-06, USA). The Human Sestrin ELISA kit (Elabscience Inc., USA, Cat Num: E-EL-H2471) was used. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using the following formula: $$\text{fasting insulin (μIU/mL) × fasting glucose (mmol/L))/22}\text{.5}\text{.}$$

Patients were considered insulin resistant when the HOMA-IR index was ≥2.6 × 10⁻⁶ mol × U/L² [14].

Sample collection and preparation

Blood samples were collected in tubes containing heparin. Serum samples were removed by centrifugation for 10 at 3000 x rpm. The samples were stored at −80 °C before performing assays. Samples were thawed and Human Sestrin (SESN2) (Catalog No: MBS2024978, Mybiosource Inc., USA,) levels were measured in serum samples. Briefly, the samples and standards were poured to appropriate wells which were pre-coated with anti-Human monoclonal antibodies before incubation. Biotin was added to all wells and combined with Streptavidin-HRP to form an immune complex, then incubation was performed again and washed to remove the uncombined enzyme. Then Chromogen Solution A and B were added for the color of the liquid changes into blue. At the effect of acid, the color finally becomes yellow. Optical density was read on a standard automated plate reader at 450 nm (Thermo Scientific Microplate Reader, USA). The detection range of the kit of SESN2 was between 0.156 and 10 ng/mL. SESN2 kit’s sensitivity was < 0.054 ng/mL.

Statistical analysis was performed using SPSS version 21. The conformity of the variables to the normal distribution was evaluated with the Shapiro Wilk test, Q-Q plot and histogram plots. Data were presented as median (quartile 25–75) or (minimum-maximum) for non-normally distributed data. Categorical data were presented as frequency (percentage), Fisher’s Exact Test and Pearson Chi-Square test were used for pairwise comparisons. The Mann-Whitney U test was used for the variables which did not show normal distribution in pairwise comparisons of continuous variables. The correlations were assessed using Spearman’s correlation coefficient, along with the related p-values. Logistic and linear regression analyses were used to determine the independent variables. ROC curve analysis was performed to estimate the best threshold Sestrin level. The control group and all PCOS were compared. p < 0.05 was considered significant. Power analysis was performed using G*Power 3.1.9.6.

Results

The mean age of the PCOS group was 29.4 ± 6.6, and the control group was 26.4 ± 4.2, with no statistically significant difference between the groups. (p = 0.146) (Table 1). None of the patients in the control group had an ultrasonographic appearance of polycystic ovaries.

Table 1. Comparison of the demographic characteristics of the participants according to the groups.

	PCOS group	Control group	p
Demographic characteristics	(n = 30)	(n = 30)
Age (year)			0.146^a
Median ± IQR	29.5 ± 12	26 ± 5
(Min-max)	(20–40)	(21–41)
BMI (kg/m^2)			0.636^a
Median (IQR)	23.3 ± 10	22.7 ± 4.3
(Min-max)	(16.6–31.2)	(19.0–30.9)
Parity			0.143^a
Median ± IQR	0 ± 2	0 ± 0
(min-max)	(0–3)	(0–2)
Additional illness			0.371^b
Yes (%)	9 (30%)	6 (20%)
No (%)	21 (70%)	24 (80%)
Drug use (because of Additional illness)			0.542^b
Yes (%)	8 (26.7%)	6 (20%)
No (%)	22 (73.3%)	24 (80%)
PCOS in the family			0.026^c
Yes (%)	8 (26.7%)	1 (3.3)
No (%)	22 (73.3%)	29 (96.7)

^a Mann Whitney U test, ^bPearson Chi-Square test, ^c Fisher’s Exact Test.

Different letters indicate statistical differences at the p < 0.05 level between columns. Bold Value indicate statistical significance.

BMI: Body mass index, PCOS: Polycystic ovary syndrome.

Hyperandrogenemia was seen in 6.7% (n = 2) of the control group, and 50% (n = 15) of the PCOS group. The rate of hyperandrogenemia in the control group was statistically lower than in the PCOS groups (p < 0.001). Menstrual irregularity was present in 6.7% (n = 2) of the control group, and 90% (n = 27) of the PCOS group, and the difference between the two groups was statistically significant (p < 0.001). The Ferriman Gallwey score (median 0) of the control group was lower than the PCOS group (median 6 ± 8), and the difference between the control group and the PCOS group was statistically significant (p < 0.001).

Coexisting diseases in Table 1 were Glaucoma, Mediterranean anemia, IBS (Irritable Bowel Syndrome), Migraine, Vertigo, Hypothyroidism, and regulated Diabetes Mellitus. Drugs used for coexisting diseases which are indicated in Table 1 were glifor, vertiserc, and euthyrox.

Excluded and included patients are shown in Figure 2.

The incidence of infertility was lower in the control group (0%) compared to the PCOS group (13.3%), and the difference between them was statistically significant (p < 0.001). There was no statistically significant difference between the groups regarding the incidence of insulin resistance and diabetes mellitus (p = 0.317, p = 0.076, respectively). The incidence of oligo anovulation, PCO, hyperandrogenemia, menstrual irregularity, infertility, insulin resistance and diabetes mellitus, Ferriman Gallwey score, and statistical analysis results of all three groups are presented in Table 2.

Table 2. Comparison of the clinical characteristics of the participants according to the groups.

	PCOS group	Control group	p
Clinical characteristics	(n = 30)	(n = 30)
PCOS			<0.001^a
Yes (%)	30 (100%)	0 (0%)
No (%)	0 (0%)	30 (100%)
Hyperandrogenemia			<0.001^a
Yes (%)	15 (50%)	2 (6.7%)
No (%)	15 (50%)	28 (93.3%)
Menstrual irregularity			<0.001^a
Yes (%)	27 (90%)	2 (6.7%)
No (%)	3 (10%)	28 (93.3%)
Ferriman Gallwey score			<0.001^b
Median ± IQR	6 ± 8	0 ± 0
Infertility			<0.001^c
Yes (%)	4 (13.3%)	0 (0)
No (%)	23 (76.7%)	10 (33.3%)
Single (%)	3 (10%)	20 (66.7%)
Diabetes mellitus	3 (10%)	0 (0%)	0.076^a
Yes (%)	27 (90%)	30 (100%)
No (%)

Categorical results are presented as frequency and percentage.

IQR: Interquartile range (25. – 75. quarters), PCOS: Polycystic ovary syndrome.

Different letters indicate statistical differences at the p < 0.05 level between columns. Bold Values indicate statistical significance.

^aFisher’s Exact Test, ^bMann Whitney U test, ^cPearson Chi-Square.

The biochemical parameters of the participants were examined. Accordingly, there was no statistically significant difference between the groups regarding FSH, DHEAS, and Estradiol levels (p < 0.05). A statistically significant difference was found in the multi-group analysis of the levels of Prolactin (p = 0.031) and LH (p = 0.014).

When the HOMA-IR values were examined, no statistically significant difference was found between the groups (p = 0.673) (Table 3).

Table 3. Comparison of the biochemistry values of the study groups.

Parameters	PCOS group (n = 30) Median ± IQR	Control group (n = 30) Median ± IQR	p
HOMA-IR	2.4 ± 2.6	2,7 ± 5,1	0.673
LH (mIU/ml)	7.8 ± 8.3	5.5 ± 3.5	0.014
FSH (mIU/ml)	6.0 ± 2.0	6.1 ± 2.1	0.363
PRL (ng/mL)	14.9 ± 9.0	12.3 ± 6.5	0.035
DHEAS (μg/ml)	215.5 ± 178.3	229 ± 183.5	0.734
E2 (pg/mL)	51.0 ± 38	48.5 ± 26	0.124
Total Testosterone	0,32 ± 0,3	0,25 ± 0,2	0.038
Sestrin	6,2 ± 0,8	3,38 ± 0,4	<0.001
LH/FSH	1.4 ± 1.2	0.9 ± 0.7	0.001

Mann Whitney U test. Bold Values indicate statistical significance.

HOMA-IR: Homeostatic Model Assessment for Insulin Resistance, LH: Luteinizing Hormone, FSH: Follicle Stimulating Hormone, PRL: Prolactin, DHEA-S: Dehydroepiandrosterone Sulfate, E2: Estradiol, and Total-T: Total Testosterone.

The median sestrin level was 6.2 ± 0.8 in the PCOS group and 3.38 ± 0.4 in the control group (p < 0.001) (Table 3).

ROC analysis was used to evaluate sestrin measurement to predict polycystic ovary syndrome. Two separate groups were formed as PCOS and control groups. As a result of the evaluation made with ROC analysis, it is observed that serum sestrin levels are measurement is meaningful indicators for the diagnosis of polycystic ovary syndrome (Figure 1). The area under the curve (AUC) value for the 4.69 level was 99.4% (p < 0.001, 95% CI: 96.4% vs. 100%, sensitivity: 100%, specificity: 96.7% (Figure 1, Table 6).

Figure 1. ROC curve associated with the risk-scoring model. The area under the curve (AUC) was 0.994 (95% CI 1 to 0.967; p <.0001).

Table 6. Areas Under the ROC Curve (AUC), sensitivity and specificity by the optimized cutoff points for Polikistic over syndrome.

AUC (95% Cl)	p	SE	Cut off	Sensitivity	Specificity
0.994	<0.001	0.006	4.69	100%	96.7%
(0.982–1.0)

AUC: Areas Under the ROC Curve, Cl: Confidence interval, SD: Standard Error.

In addition, there was no correlation between serum Sestrin levels and FSH, LH, prolactin (PRL), testosterone, DHEAS, and estradiol, while a positive correlation was found between LH/FSH and sestrin levels (Tables 4 and 5, Figure 2).

Figure 2. Flow chart of patients excluded in the study.

Table 4. Multiple linear regression analysis (n = 60).

		Standardized
Parameters	Unstandardized ß	Coefficient ß	t	p	95% Confidence Interval
HOMAIR	.009	.041	.341	.735	(−.044 − .063)
LH	.065	.225	.411	.683	(−252 − .382)
FSH	−.231	−.294	−1.332	.189	(−.578 − .117)
PRL (prolactin)	.035	.140	1.074	.288	(−.030 − .100)
DHEAS	−.001	−.110	−.884	.381	(−.005 − .002)
Estradiol	.001	.012	.087	.931	(−.015 − .017)
LH/FSH	.103	.058	.105	.917	(−1.876 − 2.082)

Logistic and linear regression analyses were used to determine the independent variables.

A p-value of <0.05 was considered statistically significant.

HOMA-IR: Homeostatic Model Assessment for Insulin Resistance, LH: Luteinizing Hormone, FSH: Follicle Stimulating Hormone, PRL: Prolactin, DHEA-S: Dehydroepiandrosterone Sulfate, E2: Estradiol, and Total-T: Total Testosterone.

Table 5. Correlation analyses between the maternal serum sestrin and other parameters.

Parameters	Sestrin
	r	p
HOMAIR	.069	.601
LH	.212	.104
FSH	-.189	.148
PRL (prolactin)	.213	.102
DHEAS	-.095	.469
Estradiol	.203	.119
LH/FSH	.336	.004

r: Spearman’s rank correlation.

HOMA-IR: Homeostatic Model Assessment for Insulin Resistance, LH: Luteinizing Hormone, FSH: Follicle Stimulating Hormone, PRL: Prolactin, DHEA-S: Dehydroepiandrosterone Sulfate, E2: Estradiol, and Total-T: Total Testosterone. Bold Value indicate statistical significance.

Discussion

This study evaluated the cause of oxidative stress in polycystic ovary syndrome through various biochemical markers. As a result of the studies, it is known that oxidative stress decreases with the decrease of sestrin protein [15]. This study reveals that serum sestrin levels of patients with polycystic ovary syndrome are higher than control group. The primary outcome of the study was the effect of sestrin, which is known to have a regulatory role in oxidative stress. The serum levels of sestrin were evaluated in polycystic ovary syndrome and the presence of oxidative stress in this disease was determined (Table 6).

Oxidative stress may have a role in the pathophysiology of PCOS but the cause of oxidative stress in PCOS is not completely understood [16]. Oxidative stress defined as an imbalance between the production of ROS and the antioxidant defense system is an important mechanism for women with PCOS [17]. In other studies, it has been reported that sestrin protein is activated when exposed to oxidative stress [15]. Therefore, sestrin protein plays a critical role in situations that cause oxidative stress [18]. In addition, some studies have shown that sestrin 2 inhibits the inflammatory pathway and reduces the formation of atherosclerosis by reducing inflammation in macrophages [19,20]. These studies explain the long-term cardiovascular complications of the PCOS and sestrin relationship due to oxidative stress.

PCOS patients have demonstrated oxidative stress due to hyperglycemia, insulin resistance, and also chronic inflammation. Oxidative stress is increased due to insulin resistance as hyperglycemia and higher levels of free fatty acid lead to excess production of ROS. Hyperglycemia also plays a role in inflammation by producing Tumor Necrosis Factor. A study suggests that excess androgen increases the generation of ROS from leukocytes. Oxidative stress and chronic inflammation are cyclical consequences of each other. The presence of oxidative stress in the absence of obesity may be due to diet as well as being a progenitor of hyperandrogenism [21]. Excess levels of androgen hormones, which was found to be significant in the PCOS group in our study, may be one of the causes of increased oxidative stress.

It has been reported that oxidative stress, which is thought to play a role in the pathogenesis of PCOS, is caused by reactive oxygen species (ROS) that accumulate excessively in vivo [22,23]. The familial predisposition to obesity and diabetes has been proven in previous studies [24]. In our study, similar to the literature, the possibility of PCOS was found to be significantly higher in patients with a family history of PCOS [25]. Due to the increased oxidative stress and endothelial damage in these patients, especially considering the long-term risks, the patients should be followed closely in terms of hypertension, diabetes mellitus, and hyperlipidemia. The patient should be informed about the increase in morbidity and mortality. Although it is known that environmental and genetic factors are influential in the pathogenesis of PCOS, the effect at the molecular level is not apparent. Due to familial predisposition, this risky group should be cautious about weight control and minimizing other environmental risk factors.

Sestrin 2 protein is thought to play an important role in the adaptation process to stress conditions by inducing and stimulating the anti-oxidation process [26]. Sestrins are known to play a role in anti-oxidation reactions through different mechanisms such as p53 and NMDA receptor pathway [27]. Sestrins are proteins induced in environmental stressful situations [28].

These molecules are known to protect against various harmful stimuli such as DNA damage, oxidative stress, starvation and hypoxia [27]. It is reported that these patients are at high risk for cardiovascular diseases if the level of sestrin 2 is not sufficiently increased in diseases in which the activation of the endoplasmic reticulum stress response is observed [29]. Studies have reported that the sestrin 2 level plays a regulatory role in oxidative stress conditions in diseases such as coronary artery disease and atherosclerosis [30].

In our study, it is observed that disorders in the oxidation mechanisms are increased in PCOS patients, which supports the literature. Sestrin protein has been evaluated in terms of its role in various diseases. This study is the first to use the sestrin molecule in the evaluation of oxidative stress in PCOS. In this respect, it can be used as a marker for oxidative stress and is thought to shed light on future studies. By considering the outcomes of additional studies to be carried out in the future, it is expected that oxidative damage in PCOS patients can be prevented, and morbidity and mortality can be reduced with treatments targeting the activation of sestrin 2 protein.

Author contributions

A.B.: Study design, data acquisition, data analysis, and data interpretation; critical revision and final approval of the manuscript.

B.E.: Study design, data interpretation; critical revision and final approval of the manuscript.

O.S.G.: Data interpretation, statistical analysis, critical revision and final approval of the manuscript.

M.B.: Data interpretation, statistical analysis.

P.Y.B.: Data collection, statistical analysis.

Conflicts of interest

The consent of the patients were obtained for the research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

The author(s) reported there is no funding associated with the work featured in this article.