{"paper_id":"e9d262c7-aaa0-4e41-91ec-d46f8ccc1af6","body_text":"Although the prevalence of infertility is not clearly known, it is estimated that\nfemale infertility affects 15% of all women worldwide ( Nik Hazlina  et al ., 2022 ), and 37% of\ninfertile couples struggle with female infertility ( Maharlouei  et al ., 2021 ). Several leading causes have\nbeen reported for female infertility, including ovarian factors (e.g., polycystic\novary syndrome), body weight (either underweight or overweight), emotional stress,\ntubal and peritoneal factors (e.g., inflammatory disease), endometriosis, Fallopian\ntube obstruction, anomalies (uterine, tubule, ovarian or cervical anomalies),\nadvanced ages (>35 yr), hormonal disorders, smoking, genetic factors ( Mustafa  et al ., 2019 ).\nAmong the causes of female infertility, emotional stress is an essential factor that\nhas been discussed in previous studies in this study. Stress influences the\nhypothalamic-pituitary-adrenal axis, leading to impairment of gonadotropin-releasing\nhormone, prolactin, luteinizing hormone, and follicular stimulating hormone ( Direkvand-Moghadam  et al .,\n2013 ;  Rooney & Domar, 2018 ). As\nthe primary glucocorticoid secreted in the adrenal cortex’s zona fasciculate,\nCortisol is affected by factors associated with the hypothalamic-pituitary-adrenal\naxis ( García-León  et\nal ., 2019 ). Several studies have introduced Cortisol as the\n“stress hormone” and its adverse effect on female fertility ( Alam  et al ., 2020 ;  More  et al ., 2022 ;  Wdowiak  et al ., 2020 ).\nAs one of the most critical stages of pregnancy, implantation is susceptible to\nstress ( Deaton  et al ., 2018 ).\nThe blastocyst must penetrate the endometrium for implantation to occur. The\nepithelial cells of the endometrium, like other epithelial cells, contain desmosomal\nproteins Desmoglein-1 (DSG1), adherens junction proteins Cadherin-1 (CDH1), and\ntight junction proteins (Zonula Occludens-1 (ZO-1), and claudin-4 (CLDN4)) ( Ye, 2020 ). There are alterations in the\nexpression of these proteins at specific sites of the endometrium known as the\nimplantation window. These alterations contribute to blastocyst implantation ( Grund & Grümmer, 2018 ). In some\nstudies, Cortisol has been reported to increase Claudin-4, occludin, and E-cadherin\nexpression in junctional proteins ( Huang  et\nal ., 2020 ;  Welcome &\nMastorakis, 2020 ).\nThis study aimed to the effect of exogenous synthetic Cortisol (Hydrocortisone) on\nthe expression of specific genes encoding several junctional proteins in the\nendometrial epithelial cells. To assess this interaction, the expression of specific\ngenes encoding junctional proteins in the endometrial epithelial cells was analyzed\nwith and without exposure to Cortisol as a marker for stress.\n\nAfter confluence, cells were treated with 50, 100, and 200 nM hydrocortisone\nlevels and incubated for 24, 48, and 72 hr with repeated treatments every 24 hr.\nQuantitative polymerase chain reaction (qPCR) analysis of 5 tight junction\ngenes, including Claudin-3 (CLDN3), CLDN4, ZO-1, DSG1, and CDH1 was performed.\nGene expressions were reported using a relative quantification method.\nThe culture medium, Dulbecco’s Modified Eagle Medium (DMEM/F12) (Gibco, Scotland,\nUK), fetal bovine serum (FBS) and L-Glutamine (Invitrogen, Grand Island, US),\npenicillin/streptomycin (Sigma-Aldrich, Steinheim, Germany) were used for cell\nculture, and Hydrocortisone (Sigma-Aldrich, Tauf- Kirchen, Germany) was used for\ncell treatment. TAKARA PCR Thermal Cycler Dice (TakaRa, Otsu, Japan), Trizol\nreagent (Sigma-Aldrich, Pool, UK), Stratagene Mx3005 P, Strata Script\nFirst-Strand Synthesis System and Velocity-SYBR Green QPCR master mix\n(STRATA-GENE Company, Cedar Greek, TX, USA) were used for quantitative real-time\nPCR.\nEndometrial sampling was performed in women meeting the inclusion criteria to\nextract human endometrial cells. 25-35 yr-old women referred to the infertility\nclinic due to male factor infertility were included in the study at about the\n19th-23rd day of their menstrual cycle. An experienced gynecologist extracted\nall the samples under aseptic conditions. Informed consent was obtained from all\nparticipants. Due to ethical issues and limitation in human sample, this sample\nsize was chosen.\nThe biopsied endometrium was washed in Phosphate-buffered saline (PBS) containing\npenicillin/streptomycin three times ( Huang\n et al ., 2020 ;  Lee  et al ., 2020 ). Subsequently, the tissue was cut\ninto 2-3 mm pieces and incubated in a digesting solution containing 1mg/ml\ncollagenase type 1A, DMEM, and 10% FBS for 45 minutes. The resulting suspension\nwas treated with red blood cell lysis buffer (ammonium chloride), potassium\nbicarbonate (Sigma-Aldrich, Steinheim, Germany), and Ethylenediaminetetraacetic\nacid (EDTA) (500 mM, Teknova, California, USA)) for 5 min. Afterward, it was\nfiltered through a 40 and 70 µm cell strainer to separate the suspension\ninto stromal and epithelial compartments, respectively. The suspension\ncontaining epithelial cells was centrifuged at 1300 Revolutions Per Minute (RPM)\nfor 5 min, then 5 ml of DMEM-F12, FBS 5%, L-Glutamine 1%, and\npenicillin/streptomycin 1% was added to the cell pellet and incubated in a 25ml\nculture flask at 95% humidity, 5% Co2, and 37oC. Following confluency, cells\nwere treated with 50, 100, and 200 nM hydrocortisone and incubated for 24, 48,\nand 72 hr while repeating the treatment every 24 hr.\nFollowing the manufacturer’s instructions, Trizol reagent was utilized to extract\nthe total Ribonucleic acid (RNA) ( Zong\n et al ., 2019 ). The TAKARA PCR Thermal Cycler\nDice was employed for PCR amplification. For synthesizing complementary\nDeoxyribonucleic acid (DNA) (cDNA), the Strata Script First-Strand Synthesis\nSystem with an oligo-dT primer was employed, using 50 ng of total\nsingle-stranded RNA template. To perform quantitative real-time PCR (RT-PCR)\nanalysis, the Stratagene Mx3005 P instrument with Full Velocity-SYBR Green QPCR\nmaster mix was utilized, following the manufacturer’s protocols ( Yu  et al ., 2020 ). The\nprimer sequences used in the study can be found in  Table 1 . The human β-actin gene served as an internal\ncontrol for normalization. The β-actin is commonly used as a housekeeping\ngene for RT-PCR and Western Blot because it is regarded as a highly stable\nhousekeeping gene ( Ruan & Lai, 2007 ).\nThe amplification process followed a specific temperature profile: an initial\nstep at 95°C for 10 min, followed by cycles of denaturation at 95°C for 15 sec,\nand annealing/extension at 60°C for 1 min, repeated for 40 cycles. Each sample\nwas tested in triplicate. A melting curve analysis was performed to determine\nthe specificity of the PCR fragments, resulting in a single peak for each PCR\nproduct. Standard curves were generated by performing logarithmic serial\ndilutions of total cDNA. The cycle threshold (CT) values were normalized against\nthe CT value of the human β-actin gene. The comparative CT method was\nemployed to analyze the qPCR data.\nPrimer sequences and traits.\nIn essence, the difference in cycle time (DCT) represents the disparity between\nthe number of cycles required for amplifying the target gene and the reference\ngene, which in this case was human β-actin. The DDCT value was determined\nby calculating the difference between the experimental groups. The fold-change\n(FC) was computed using the formula FC = 2^DDCT.\nData were presented as means ± standard error of the mean from\ntriplicates. One Way Analysis of Variance (ANOVA, post hoc Tukey) was used for\ncomparing the difference of normally distributed means in multiple tests. For\nreal-time PCR analysis, the relative quantification method was applied. Data\nwere analyzed by SPSS 16 software (SPSS, Inc., Chicago, IL, USA), and\n p  values of ≤0.05 were considered significant.\n\nFollowing 24h treatment of endometrial epithelial cells with Hydrocortisone,\nCLDN3 expression was significantly higher in the100 nM (0.95±0.08) and\n200 nM (1.05±0.12) group compared to the control group (0.68±0.05;\n p =0.01, and 0.002, respectively). After 48h of\nHydrocortisone treatment, CLDN3 expression was significantly increased in 100 nM\ngroup (1.08±0.1) compared to the control (0.64±0.08) group\n( p =0.002). Finally, following 72h of treatment, CLDN3\nexpression was increased significantly in the 100nM group (1.08±0.06)\ncompared to the control group (0.74±0.12,  p =0.04).\nThrough the study course, CLDN3 expression was evaluated at three-time points of\ntreatment. Alterations of CLDN3 expression at these time points in each group\nwere not significant, except for the 200nM group showing significantly higher\nexpression at 24 hr compared to 48 hr ( p =0.009) and 72 hr\n( p =0.05) treatments ( Figure\n1 ).\nFigure 1 Relative expression fold change of CLDN3 at 3 different treatment\ntimes (A: 24 hr, B: 48 hr, and C: 72 hr). Gene expression results\nare normalized to β-actin mRNA amplification. A: *\n vs . control ( p =0.003); #\n vs . 50nM ( p =0.014); Ø\n vs . control and 50nM\n( p =0.002); B: *  vs . control and\n200nM ( p =0.002); C: *  vs . control\n( p =0.04); D: CLDN3 expression process within\neach group through study course; 200nM (*  vs . 48h\n( p =0.009), #  vs . 72h\n( p =0.05).\nRelative expression fold change of CLDN3 at 3 different treatment\ntimes (A: 24 hr, B: 48 hr, and C: 72 hr). Gene expression results\nare normalized to β-actin mRNA amplification. A: *\n vs . control ( p =0.003); #\n vs . 50nM ( p =0.014); Ø\n vs . control and 50nM\n( p =0.002); B: *  vs . control and\n200nM ( p =0.002); C: *  vs . control\n( p =0.04); D: CLDN3 expression process within\neach group through study course; 200nM (*  vs . 48h\n( p =0.009), #  vs . 72h\n( p =0.05).\nCLDN4 expression following 24h treatment exhibited a significant increase in\n100nM and 50nM groups (0.9±0.08) compared to the control\n(0.55±0.02) group ( p =0.01). CLDN4 expression was also\nsignificantly lower in the 200nM compared to the control\n( p =0.03). Following 48h of treatment, CLDN4 expression was\nsignificantly increased in the 100 nM (1.37±0.06) and 50nM group compared\nto the control (0.55±0.04,  p =0.000and 0.004,\nrespectively) ( Figure 2 ). After 72 hr of\ntreatment, a significant increase in CLDN4 expression was evident in 100 nM\n(0.81±0.11), 200 nM (0.7±0.11), and 50 nM (0.67±0.02)\ngroups compared to the control group (0.45±0.05) with\n p -values of 0.003, 0.02 and 0.04, respectively.\nFigure 2 Relative expression fold change of CLDN4 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. A: **vs. control\nand 200nM ( p =0.000); #  vs . 50nM\n( p =0.01); *  vs . control\n( p =0.01); Ø  vs . 200nM\n( p =0.000); α  vs . 200nM\n( p =0.03); B: **  vs  control,\n50nM, and 200nM ( p =0.000); *  vs .\ncontrol ( p =0.004); Ø  vs .\n200nM ( p =0.000); C: **  v s. control\n( p =0.003); #  vs . control\n( p =0.02); *  vs . control\n( p =0.04); D: CLDN4 expression process within\neach group through study course; control (*  vs . 72h\n( p =0.04); 100nM (#  vs . 24h\n( p =0.001), **  vs . 72h\n( p =0.000)); 200nM (Ø\n vs . 24h and 48h ( p =0.005)).\nRelative expression fold change of CLDN4 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. A: **vs. control\nand 200nM ( p =0.000); #  vs . 50nM\n( p =0.01); *  vs . control\n( p =0.01); Ø  vs . 200nM\n( p =0.000); α  vs . 200nM\n( p =0.03); B: **  vs  control,\n50nM, and 200nM ( p =0.000); *  vs .\ncontrol ( p =0.004); Ø  vs .\n200nM ( p =0.000); C: **  v s. control\n( p =0.003); #  vs . control\n( p =0.02); *  vs . control\n( p =0.04); D: CLDN4 expression process within\neach group through study course; control (*  vs . 72h\n( p =0.04); 100nM (#  vs . 24h\n( p =0.001), **  vs . 72h\n( p =0.000)); 200nM (Ø\n vs . 24h and 48h ( p =0.005)).\nAlterations of CLDN4 expression at three-time treatment points in each group\nrevealed significantly higher expression at 24 hr and 48 hr compared to 72 hr\ntreatment ( p =0.04) in the control group. In the 100 nM group,\nsignificantly higher expression was evident at 48 hr compared to 24 hr\n( p =0.001) and 72 hr ( p =0.000) of\ntreatment. In the 200 nM group, a higher expression was detected at 72 hr\ncompared to 24 hr and 48 hr ( p =0.005) treatment ( Figure 2 ).\nAccording to  figure 3 , ZO-1 expression\nfollowing 24 hr of treatment indicated no significant difference between the\nfour groups. Following 48 hr of treatment, ZO-1 expression was significantly\nincreased in the 100 nM group (1.01±0.18) compared to the control\n(0.55±0.01,  p =0.009). After 72 hr of treatment, ZO-1\nexpression was also significantly higher in the 100 nM group (1.12±0.15)\ncompared to the control (0.55±0.06,  p =0.003). ZO-1\nexpression showed no significant change through the study course except for the\n200 nM group exhibiting significantly higher expression at 24 hr compared to 48\nhr and 72 hr ( p =0.02) treatments ( Figure 3 ).\nFigure 3 Relative expression fold change of ZO-1 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. B: *\n vs . control ( p =0.009); #\n vs . 200nM ( p =0.004); C: *\n vs . control ( p =0.003); #\n vs . 50nM ( p =0.019); Ø\n vs . 200 ( p =0.008); D: ZO-1\nexpression process within each group through study course; 200nM (*\n vs . 48h ( p =0.02)).\nRelative expression fold change of ZO-1 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. B: *\n vs . control ( p =0.009); #\n vs . 200nM ( p =0.004); C: *\n vs . control ( p =0.003); #\n vs . 50nM ( p =0.019); Ø\n vs . 200 ( p =0.008); D: ZO-1\nexpression process within each group through study course; 200nM (*\n vs . 48h ( p =0.02)).\nCDH1 expression was significantly higher in the 100 nM group compared to the\ncontrol in all three-time points of 24 hr ( p =0.007), 48 hr\n( p =0.01), and 72 hr ( p =0.05). CDH1\nexpression increased with time, revealing higher expressions at 48 hr and 72 hr\ncompared to 24 hr of treatment. In the control group, significantly higher\nexpressions were indicated at 48 hr and 72 hr compared to 24 hr\n( p =0.008 and  p =0.004, respectively)\ntreatment ( Figure 4 ). In the 50 nM group, a\nsignificant increase in CDH1 expression was evident at 48 hr and 72 hr compared\nto 24 hr ( p =0.005, and 0.007, respectively) treatment. In 100nM\nand 200nM groups, there was also a significantly higher expression at 48 hr and\n72 hr compared to 24 hr ( p =0.000) treatment. In the 200 nM\ngroup, CDH1 expression at 72 hr was significantly higher than the 48 hr\n( p =0.01) treatment.\nFigure 4 Relative expression fold change of CDH1 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. A: *\n vs . control ( p =0.007); #\n vs . 50nM ( p =0.05); Ø\n vs . 200nM ( p =0.01); B: *\n vs . control ( p =0.01); #\n vs . 50nM ( p =0.05); C: *\n vs . control ( p =0.008); #\n vs . 50nM ( p =0.01); D: CDH1\nexpression process within each group through study course; control\n(*  vs . 24h ( p =0.008), #\n vs . 24h ( p =0.004)); 50nM\n(Ø  vs . 24h ( p =0.005), ϒ\n vs . 24h ( p= 0.007)); 100nM (**\n vs . 24h ( p =0.000)); 200nM\n(α  vs . 24h ( p =0.000),\nβ  vs . 48h (p=0.01)).\nRelative expression fold change of CDH1 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. A: *\n vs . control ( p =0.007); #\n vs . 50nM ( p =0.05); Ø\n vs . 200nM ( p =0.01); B: *\n vs . control ( p =0.01); #\n vs . 50nM ( p =0.05); C: *\n vs . control ( p =0.008); #\n vs . 50nM ( p =0.01); D: CDH1\nexpression process within each group through study course; control\n(*  vs . 24h ( p =0.008), #\n vs . 24h ( p =0.004)); 50nM\n(Ø  vs . 24h ( p =0.005), ϒ\n vs . 24h ( p= 0.007)); 100nM (**\n vs . 24h ( p =0.000)); 200nM\n(α  vs . 24h ( p =0.000),\nβ  vs . 48h (p=0.01)).\nAccording to  figure 5 , DSG1 expression\nfollowing 24h treatment showed a significant increase in the 200nM group\n(0.92±0.02) compared to the control (0.61±0.09,\n p =0.02). Following 48h treatment, DSG1 expression significantly\nincreased in the 100 nM group (0.78±0.12) compared to the control\n(0.18±0.02) group ( p =0.000). After 72 hr treatment,\nalthough DSG1 expression in all the groups was higher than 48 hr treatment, no\nsignificant difference was evident between groups. In the control group, DSG1\nexpression was significantly higher at 24 hr and 72 hr compared to 48 hr\n( p =0.000) treatment. In the 50 nM group, there was a\nsignificantly higher expression at 24 hr and 72 hr compared to 48 hr\n( p =0.004, and  p =0.001, respectively)\ntreatment. In the 200 nM group, there was a significant increase in DSG1\nexpression at 24 hr and 72 hr compared to 48 hr ( p =0.000, and\n p =0.001, respectively) treatment. There was also a\nsignificantly higher expression at 24 hr compared to 72 hr\n( p =0.004) treatment in the control group ( Figure 5 ).\nFigure 5 Relative expression fold change of DSG1 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. A: *\n vs . control ( p =0.02); #\n vs . 50nM ( p =0.006); B: **\n vs . control, 50nM, and 100nM\n( p =0.000). D: DSG1 expression process within\neach group through the study course; control (**\n vs . 48h ( p =0.000)); 50nM (#\n vs . 48h ( p =0.004), Ø\n vs . 48h ( p= 0.001)); 200nM (£\n vs . 48h ( p =0.000), ϒ\n vs . 72h ( p =0.004), α\n vs . 48h ( p =0.001)).\nRelative expression fold change of DSG1 at three different treatment\ntimes (A: 24h, B: 48h, and C: 72h). Gene expression results are\nnormalized to β-actin mRNA amplification. A: *\n vs . control ( p =0.02); #\n vs . 50nM ( p =0.006); B: **\n vs . control, 50nM, and 100nM\n( p =0.000). D: DSG1 expression process within\neach group through the study course; control (**\n vs . 48h ( p =0.000)); 50nM (#\n vs . 48h ( p =0.004), Ø\n vs . 48h ( p= 0.001)); 200nM (£\n vs . 48h ( p =0.000), ϒ\n vs . 72h ( p =0.004), α\n vs . 48h ( p =0.001)).\n\nAccording to the results, Hydrocortisone increases the expression of genes associated\nwith tight junctions in the human endometrial epithelium. As more tight junctions\noccur between epithelial cells in the endometrium, the more difficult it is for\nblastocysts to penetrate the endometrium, compromising implantation.\nTight junction molecules are presented on epithelial cells’ lateral and basolateral\nsurfaces. As reported in several in vitro studies, glucocorticoids increase the\nexpression of their receptors upon entering the cytoplasm. The increased receptors\nresult in a greater concentration of ligand-receptor complexes acting as direct and\nindirect transcription factors, promoting gene expression associated with tight\njunctions ( Lee  et al ., 2020 ;\n Zong  et al ., 2019 ). This\nincrease in the tight junctions makes the epithelium less penetrable, improving the\nfunction of the epithelium as a barrier and an integrated structure. The formation\nof an alveolocapillary barrier in human lung epithelial cell lines was also reported\nfollowing glucocorticoid treatment and its effect on CDH1 expression ( Atherly  et al ., 2019 ;  Yu  et al ., 2020 ).\nIn this study, higher cortisol concentration was directly associated with the\nupregulation of tight junction proteins, reaching its maximum at 100nm cortisol\nlevels. However, Hydrocortisone’s tight junction-associated gene expression is\ndecreased in 200nm concentrations. There are two isoforms of glucocorticoid\nreceptors, glucocorticoid receptor (GRα) and glucocorticoid receptor\n(GRβ) ( Hutter  et al .,\n2019 ;  Ramos-Ramírez & Tliba,\n2021 ). GRα binds to DNA and other transcription factors, altering\nspecific gene regulations. In contrast, GRβ binds to DNA and forms a\nhomodimer, preventing the binding of GRα and inhibiting transcription. Thus,\nthe balance between these two receptors determines the sensitivity of cells to\nglucocorticoids. An increased amount of GRβ in the cells leads to\nglucocorticoid resistance. Therefore, it is probable that high ligand concentrations\nand GRβ receptors’ saturation result in decreased gene expression ( Ramos-Ramírez & Tliba, 2021 ). Our\nstudy also revealed decreased gene expression at a high Hydrocortisone (200 nm)\nconcentration. Glucocorticoid-derived downregulation of glucocorticoid receptors was\nreported in another study in which a 100nM concentration of dexamethasone was\nreported as the most efficient dose of this glucocorticoid ( Díez-Tercero  et al ., 2022 ).\nGlucocorticoids can have a double-edged sword role on implantation since they may\nadversely affect implantation by upregulating tight junctions. Conversely, they may\nsuppress immunologic rejection of embryos during implantation by reducing natural\nkiller cells ( Buck  et al .,\n2012 ). This study revealed that the most efficient dosage and treatment\nduration with Hydrocortisone was 100 nm in 48 hours, whereas, in 200 nm\nhydrocortisone, the expression of junctional molecule genes decreased after 72\nhours. These results indicate that higher concentrations for a prolonged duration\nmay conversely affect tight-junction genes. Studies have reported a higher amount of\nNK cells in women experiencing recurrent abortions, and when these women were\ntreated with methylprednisolone (which suppresses NK cells), conception rates were\nincreased ( Andreescu  et al .,\n2023 ;  Fu  et al .,\n2021 ). It has also been reported that NK cells are responsible for\nglucocorticoid receptor expression ( Capellino\n et al ., 2020 ;  Quatrini  et al ., 2021 ). Another recent study ( Zhaeentan  et al ., 2018 ) showed\nthat upon treatment of fallopian tube epithelial cells with Hydrocortisone, tight\njunction molecule expression was significantly increased, leading to a lower chance\nof implantation, which is essential in reducing ectopic implantation in the\nfallopian tube.\n\nGlucocorticoids (Hydrocortisone) influence gene expression associated with tight\njunction molecules in a concentration and time-dependent manner. It was revealed\nthat the highest tight junction molecule expression was at 100nm for 48hr of\ntreatment. The conflicting role of glucocorticoids on implantation must be\nconsidered when specialists prescribe them.","source_license":"public-domain-us","license_restricted":false}