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 Table of Contents  
Year : 2022  |  Volume : 1  |  Issue : 2  |  Page : 88-96

microRNA profiling and the effect on metabolic biomarkers and weight loss after laparoscopic sleeve gastrectomy: A prospective cohort study

1 Department of Surgery, Medical Research Institute, Alexandria University; Consultant of Bariatric Surgery Madina Women's Hospital (IFSO Center of Excellence, European Chapter) Alexandria, Egypt
2 Department of Clinical Pathology, Alexandria University, Alexandria, Egypt
3 Medical Research Institute, Alexandria University, Alexandria, Egypt
4 Department of Surgery, Medical Research Institute, Alexandria University, Alexandria, Egypt
5 Nutrition Clinic, Madina Women's Hospital, Alexandria, Egypt
6 Leiden University Medical Center, Leiden, The Netherlands

Date of Submission05-Jun-2022
Date of Acceptance08-Jul-2022
Date of Web Publication10-Aug-2022

Correspondence Address:
Dr. Mohamed Hany
Department of Surgery, Medical Research Institute, Alexandria University, 165 Horreya Avenue, Hadara, Alexandria 21561
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jbs.jbs_8_22

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Background: Epigenetic changes after bariatric surgery are of increasing interest; we evaluated the levels of two circulating microRNAs (miRNA-222 and miRNA-146a) before and after the laparoscopic sleeve gastrectomy (LSG) and the effect of weight loss on the levels of metabolic biomarkers. Materials and Methods: We prospectively evaluated patients pre- and 12 months post-LSG for percent excess weight loss (%EWL), miRNAs levels, metabolic biomarkers (leptin, ghrelin, peptide YY, and glucagon peptide-1 [GLP-1]) levels from August 2019 to September 2021. Results: Significant differences were observed in the miRNA146a-3p (median: 0.64 (0.012-2.68) vs. 1.07 (0.1-3.6); P = 0.019) and miRNA222-5p (median 1.80 (0.1–3.61) vs. 1.19 (0.1-3.68); P = 0.003) levels before and after (12 months) LSG; fasting leptin, ghrelin, insulin, total cholesterol, high- and low-density lipoproteins, fasting blood sugar (FBS), and triglyceride levels also showed significant differences. Significant changes were observed in postprandial values of glucagon-like peptide l (GLP-1) (P = 0.0001) and peptide YY (P = 0.0006) 12 months after LSG. Homeostatic model assessment of insulin resistance (IR) was significantly correlated with %EWL, miRNA146a, and miRNA222-5p (P = 0.002). Postoperatively measured miR146a-39 and miRNA222-5p showed significant coefficient of determination R2 of 0.184 (P = 0.008) and 0.259, P = 0.0007 toward %EWL, respectively. Furthermore, significant correlations of miRNA146a were observed with FBS and IR. Conclusions: LSG-mediated weight loss affected the plasma levels of miR146a and miR222-5p. Due to the simultaneous decrease of ghrelin and increase of postprandial hormones (peptide YY and GLP-1), medical problems in patients with obesity were reduced. This study identified miRNAs as the new markers in the treatment, diagnosis, and therapeutic direction of patients with obesity.

Keywords: Metabolic biomarkers, miRNA, sleeve gastrectomy

How to cite this article:
Hany M, Demerdash HM, Ahmed AA, Agayby AS, Ghaballa M, Ibrahim M, Maged P, Torensma B. microRNA profiling and the effect on metabolic biomarkers and weight loss after laparoscopic sleeve gastrectomy: A prospective cohort study. J Bariatr Surg 2022;1:88-96

How to cite this URL:
Hany M, Demerdash HM, Ahmed AA, Agayby AS, Ghaballa M, Ibrahim M, Maged P, Torensma B. microRNA profiling and the effect on metabolic biomarkers and weight loss after laparoscopic sleeve gastrectomy: A prospective cohort study. J Bariatr Surg [serial online] 2022 [cited 2023 Apr 1];1:88-96. Available from: http://www.jbsonline.org/text.asp?2022/1/2/88/353663

  Introduction Top

Obesity is a complex, chronic relapsing disorder that devastates the well-being of approximately 650 million adults worldwide.[1] Bariatric surgery is an efficient procedure that can result in considerable sustained weight loss in patients with obesity and improve associated medical problems and quality of life.[2] Weight loss after bariatric surgery results in improvements in health, cellular processes, metabolic biomarkers, and associated medical problems.[3],[4],[5]

Recently, studies on the relationship between epigenetic changes and bariatric surgery outcomes have increased, including publications on microRNAs (miRNAs),[6],[7],[8],[9] as a specific marker. miRNAs are small (19–23 nucleotides) single-stranded noncoding RNA molecules involved in the posttranscriptional regulation of gene expression by binding to the conforming sequences within the 3'untranslated regions of the target mRNAs.[9] Circulating miRNAs are packaged in high-density lipoproteins, protein aggregates such as argonaut 2, and cell-derived lipid vesicles such as exosomes.[10]

Furthermore, hormonal communication pathways deliver signals to the brain (principally to the hypothalamus) to regulate metabolism and energy homeostasis. Glucagon peptide-1 (GLP-1) and peptide YY from the gastrointestinal tract provoke satiety, whereas ghrelin stimulates appetite and leptin is secreted almost exclusively by fat and serves to repress food intake and promote energy expenditure. Adipose tissue transmits signals to the brain via leptin and insulin.[11] Consequently, postsurgical amendments to these hormones may modify brain activation feedback to appetite and satiety signals.[12]

The effects of bariatric surgery on miRNAs, weight loss, and combined metabolic biomarkers are unknown. Since specific metabolic biomarkers in patients with obesity and associated medical problems have improved after surgery,[13] their relationship with epigenetic changes is unknown.

Some miRNAs influence obesity-related pathways, and changes in miRNAs are associated with obesity and associated medical problems in patients with obesity.[14],[15],[16],[17],[18] Therefore, we aimed to evaluate the relationship between the two most common circulating miRNAs (miRNA-146a and miRNA-222-5p)[19] and what is linked between obesity and metabolic biomarkers and hormones after bariatric surgery-induced weight loss (SIWL). These hormones influence obesity and body weight through satiety and appetite stimulation. In addition, these hormones may be associated with insulin resistance (IR) before and after laparoscopic sleeve gastrectomy (LSG). This study also tested weight loss and its effects on the levels of metabolic biomarkers, including leptin, ghrelin, peptide YY, and GLP-1.

  Materials and Methods Top

Study design

This was a prospective cohort study conducted between August 2019 and September 2021. Written and oral informed consents were obtained from all the patients, and data were analyzed anonymously. The study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the ethical committee board.

Patient selection

Patients aged 18–65 years with the American Society of Anesthesiology classes 1–3 were screened according to the National Institutes of Health criteria[20] before LSG surgery. Patients with chronic inflammatory bowel disease, malignancy, or psychiatric illnesses were excluded. The LSG was performed by the same team throughout the study. Dissection was started 6 cm from the pylorus (antrum preserving) until the gastroesophageal junction, followed by gastric transaction over 40F bougie through sequential stapler firings.

Data collection

The baseline characteristics of the patients, including medical data, body mass index (BMI; determined using the weight measured before surgery), %excess weight loss (%EWL), and laboratory data, were collected before and 12 months after surgery.

Preoperative diet

All patients had a liver-shrinking diet 2 weeks before surgery for better surgical conditions.

Laboratory investigations

Peripheral blood samples were collected before and 12 months postoperatively to measure the fasting levels of hormones (ghrelin, leptin, and insulin) and postprandial levels of GLP-1 and peptide YY.

Laboratory procedures were performed using sterile ethylenediaminetetraacetic acid tubes to determine the miRNAs and plain tubes for measuring hormones homeostatic model assessment of IR (HOMA-IR) and lipids. Serum samples were allowed to clot at room temperature for 30 min and subsequently centrifuged at 4000 rpm for 10 min at 4°C. The plasma and serum were removed and stored at −80°C until analysis. The lipid profile was determined using a 7600 Hitachi automatic analyzer.

Blood sampling sequence

Blood sampling was performed 1 week before surgery. First, fasting samples were obtained to measure the levels of metabolic biomarkers, including leptin, ghrelin, insulin, total cholesterol, high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), fasting blood sugar (FBS), HOMA-IR, and triglycerides. The patients were subsequently provided with the standard meal (300 kcal) that contained pasta (30 g), ground lean meat (30 g), olive oil (5 g), almonds (n = 6), yogurt (80 g), and dried prune (n = 1), providing 45% carbohydrates, 20% protein, and 35% fat. The meal duration was 15 min. Blood samples were collected for the postprandial determination of GLP-1 and peptide YY after ingestion and 120 min later of the standard meal.

Hormonal measurements

Serum insulin levels were analyzed using enzyme-linked immunoassay ELISA (EIA-2935) (DRG International, Inc. software (Springfield, NJ, USA). IR was assessed using HOMA-IR according to the formula: fasting plasma glucose (mmol/L) fasting serum insulin (mU/L) divided by 22.5.

The fasting blood glucose levels were determined using a Hitachi automatic analyzer based on the glucose oxidase method. Serum ghrelin, serum leptin, GLPs, and human peptide YY levels were analyzed using an ELISA kit (Cloud-Clone Corp; cat no: E-01720 hu) (W. Fernhurst Dr., Unit 2201, Katy, TX 77494, USA).

MicroRNAs Quantification by the real-time polymerase chain reaction

RNA extraction and cDNA synthesis

Total RNA was extracted from 200 μL of plasma using a mini RNeasy extraction kit (Qiagen, Valencia, CA, USA). The RNA purity was quantified using a NanoDrop spectrophotometer (Nanodrop ND-1000, United States) and analyzed using a 2% agarose gel electrophoresis. Reverse transcription was performed for cDNA synthesis using the mini RNeasy Plasma Reverse Transcription Kit (Qiagen, Valencia, CA, USA), according to the manufacturer's protocol.

Amplification and quantification

The levels of miRNAs are expressed as fold changes.

A complete description is shown in Appendix 1.

Statistical methods

Descriptive and inferential statistics were used for analyses. All data were first tested for normality using the Kolmogorov–Smirnov test, Q-Q plot, and Levene's test. Categorical variables are expressed as numbers and percentages. Continuous normally and nonnormally distributed variables are presented as means and standard deviations (SD) and medians and interquartile ranges (for skewed distributions), respectively. When appropriate, categorical variables were tested using Pearson's Chi-square test or Fisher's exact test. Normally distributed continuous data were tested with the dependent samples using the Student's t-test for pre- and post-operative results. For skewed (nonparametric) data, The Wilcoxon signed-rank test was used. The correlation between the biomarkers, miRNAs, and %EWL was determined using the Pearson product-moment correlation coefficient for normally distributed data or Spearman's rank correlation coefficient for nonnormally distributed data. Predictors were evaluated using univariate and multivariate linear and logistic regression analysis. All independent variables, counting more than ten events and showing P < 0.1, were eligible for multivariable analysis, which was achieved through backward selection. The optimal prediction model was evaluated with a 2 log-likelihood. P < 0.05 were considered statistically significant. Statistical analyses were performed using R (version 4.0.4) packages.[13],[20]

G * power version was used for sample size calculation. Our main end-point was the change Δ miRNA preoperatively and postoperatively within a patient. Reflecting previous studies that changes of a minimal 50% were reached, a minimal mean difference of 0.8-1 point on the miRNA and SD of 2.0 would be needed, with an alpha of 0.05 and a beta >0.8, we needed 33–52 patients. With a possible loss to follow-up of 10%, recruitment of a minimal of 37 and a maximal of 57 patients were obtained.

  Results Top

Baseline characteristics

A total of 55 patients (19 and 36 were male and female, respectively; mean age ± SD = 34.2 ± 11.3 years) completed the follow-up period after LSG with no loss to follow-up. The preoperative and 12 months postoperative BMIs (mean ± SD) were 44.9 ± 6.8 and 31.9 ± 4.7 kg/m2, respectively. The 12 months postoperative %EWL (mean ± SD) was 59.9 ± 15.7 [Table 1]. Common obesity-associated medical conditions identified in patients were asthma (5.5%), diabetes (11%), hypertension (7.4%), hypothyroidism (16.6%), and history of cancer (3.7%).
Table 1: Descriptive demographic characteristics

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Levels of microRNAs and metabolic markers

Plasma miR146a and miR222

Significant differences were observed in the levels of miRNA146a-3p (median: 0.26 (0.012–2.68) vs. (1.10 (0.1–3.6); P = 0.009) and miRNA222-5p (median: 2.11 (0.1–3.68) vs. 1.01 (0.1–3.61); P = 0.008) before and 12 months after surgery.

Postprandial values

The mean differences in the GLP-1 and peptide YY levels 12 months after surgery (relative to before surgery) were 0.877 (P = 0.0001) and 45.188 (P = 0.0006), respectively [Table 2].
Table 2: MicroRNA and metabolic biomarkers after laparoscopic sleeve gastrectomy (n=55)

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Fasting values

Significant (P ≤ 0.05) changes were observed between the preoperative and 12-month postoperative levels of the metabolic biomarkers, with mean differences of − 30.96, −101.47, −7.52, −110.14, −10.38, −82.80, −11.87, −3.3, and −77.21 for leptin, ghrelin, insulin, total cholesterol, HDLs, LDLs, FBS, HOMA-IR, and triglyceride levels, respectively [Table 2].

Correlation of percent excess weight loss with microRNAs

After 12 months postoperatively, miRNA146a-39 and miRNA222-5p displayed significant coefficient of determination (COD) R2 of 0.184 (P = 0.008) and R2 of 0.259 (P = 0.0007) toward %EWL, respectively [Table 3].
Table 3: Correlations with microRNA, metabolic biomarkers, and percent excess weight loss postoperatively (n=55)

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Effects of percent excess weight loss and microRNAs on the levels of metabolic biomarkers

We made the following observations on the correlation of the levels of metabolic biomarkers with %EWL and miRNAs; (1) the postprandial values of peptide YY and GLP-1 at 12 months postoperatively were not significantly (P ≥ 0.05) correlated to %EWL, miRNA146a, and miRNA222-5p, (2) fasting levels of leptin and ghrelin were significantly correlated to %EWL at 12 months postoperatively (COD R2 = 0.186 and 0.074, and P = 0.029 and 0.043, respectively), but not with miRNA146a and miRNA222-5 (P ≥ 0.05), (3) fasting levels of insulin, total cholesterol, HDLs, LDLs, HOMA-IR, and triglycerides were not significantly correlated to %EWL, miRNA146a, or miRNA222-5p, (4) HOMA-IR was significantly correlated with %EWL, miRNA146a, and miRNA222-5p (COD R2 0.09, 0.336, and 0.096 and P = 0.022, 0.002, and 0.020, respectively), and (5) fasting levels of FBS was only significantly correlated with miRNA146a (COD R2 0.096; P = 0.018), but not with miRNA222-5p and %EWL (P > 0.05) [Table 3].

  Discussion Top

This study mainly revealed that the plasma miRNA146a and miRNA222-5p levels decreased both with decreasing ghrelin and leptin fasting levels and increasing levels of gut hormones (GLP-1 and peptide YY), levels of all the components changed significantly 12 months postoperatively, HOMA-IR was significantly correlated to %EWL, miRNA146a, and miRNA222-5p, and FBS was significantly correlated to miRNA146a. Therefore, this study adds and updates new insights into the postoperative behavior of hormones and miRNA after LSG. Since this is a prospective, complete 1-year follow-up, with a relatively large number of patients compared to previous studies within the same group over time.

Consistent with previous reports, we also found significant advantages of bariatric surgery (through LSG) on weight loss; the reduction in the size of the stomach was reflected by the decrease in weight (%EWL 59.9) and ghrelin levels (with a significant correlation to %EWL). This decrease in ghrelin levels is related to fundus resection during LSG. Furthermore, hormones that normally induce hunger decrease post-LSG.[21],[22]

Previous studies[14],[23] have confirmed that LSG influences gut hormones, which mainly improve insulin release and induce satiety. This study preserved the antrum, which may alter gastric emptying and hence gut hormones, as mentioned in previous studies.[14],[23] Therefore, this study confirms that anatomical changes after an LSG will induce weight loss and a change in metabolic biomarkers. In addition, the change in the postprandial gut hormones in this study, peptides YY and GLP-1, significantly contributed to SIWL.

GLP-1 increases satiety and reduces hunger.[24] GLP-1 also significantly increased postoperatively in this study, it can be postulated that weight loss is associated with changes in the expression of miRNA222-5p caused by an improvement in hormone levels and, consequently, the amendment of dyslipidemia and IR. Knop et al.[54] elucidated that the reduced incretin effect of GLP-1 was caused by a reduced response of β-cells to insulin sensing owing to β-cell lipotoxicity in patients with obesity and Type 2 diabetes.[25]

MicroRNAs and correlation effects

Circulating miRNAs are associated with gene expression in distant tissues and regulate metabolism during obesity. Multiple studies have reported that adipose tissue is the main source of circulating miRNAs and can improve the associated medical problems after changing miRNAs.[26],[27],[28],[29],[30],[31] Other studies have demonstrated that various plasma miRNAs are aberrantly expressed in patients with obesity as compared to healthy people without obesity and are modulated by significant weight loss following dietary or SIWL.[32],[33],[34],[35]

Langi et al.[25] performed a meta-analysis of different miRNA expression levels after bariatric surgery and reported 14 biological pathways that are predicted to be regulated by these miRNAs after bariatric surgery. However, the sample size of this study was small.

Hulsmans et al.[15] suggested that several circulating miRNAs, including miRNA221/miRNA222-5p, can promote adipogenesis and the progression of atherosclerosis. They emphasized the role of microvesicle-containing miRNAs in the interaction between inflammatory and endothelial cells within the vascular and adipose tissues.

MicroRNAs 222-5p

One study tested pretreatment values of miRNA and looked at the change over time between diet (DIWL)-and SIWL.[37] This study showed higher baseline miRNA222-5p levels in patients with morbid obesity (0.98) than that in the patients with obesity (0.52) and patients without obesity (0.51) (P ≤ 0.001). After DIWL and SIWL, all miRNA levels changed, but the effects of SIWL were significantly different. In addition, the BMI reduction was greater in the SIWL group than that of the DIWL (−32.6 vs. −16.6, [P = 0.001 vs. 0.006]).

This study observed that the expression of both measured miRNAs was significantly changed at 12 months compared to preoperatively, which is consistent with the results of other studies that reported that miRNA panels were associated with obesity and weight loss.[38],[39],[40],[41],[42] Nevertheless, multiple studies have also shown alternating results in these changes in miRNA expression after diet or SIWL. One study reported circulating levels of miRNA222-3p levels significantly increased after weight loss, while miRNA-122-5p and miR-193a-5p levels were reduced.[43] Another study found increased miRNA-222 levels after bariatric surgery compared to preoperative values.[21] Two studies from the same research group found opposite results after weight loss, with increased and decreased miRNAs 222-5p.[37],[44]

In general, it appears that a decreased postoperative miRNA222-5p is the most obvious result we see, but still, different findings suggest possible confounding factors that we do not know yet; study populations/settings may be different between the studies, and the sample size could affect the results, and the time or phase of measurement of weight loss may influence this. Further research is needed to address this variance.


Obesity-associated inflammation of white adipose tissue (WAT) is one of the factors leading to the development of related diseases such as IR.[45],[46] In subcutaneous WAT, miR-146a levels are elevated in both humans and mice with obesity.[47] When looking at the miRNA-146a in this study, these levels significantly changed after weight loss. Furthermore, a significant correlation was found between FBS and HOMA-IR, and all these metabolic markers improved over the 12 months, suggesting a possible effect and interaction between miRNA146 and obesity-related IR. Furthermore, HOMA-IR showed that weight loss might induce independent changes in peptide hormones such as ghrelin, leptin, and GLP-1, prompting an improvement in HOMA-IR.[48],[49] A previous study showed that miRNA-146a reduces the inflammatory response in human adipocytes. In a decreasing trend postoperatively, miR-146a might contribute to the regulation of inflammatory processes in WAT and possibly prevent an overwhelming inflammatory response.[49] In addition, other studies have suggested that developing miRNA mimics to enhance miRNA-146a levels could be used to treat obesity and diabetes.[26],[33]

If we look at leptin. This adipocyte-derived hormone regulates energy storage in the body and is produced by adipocytes depending on the TG level. Leptin is secreted almost exclusively by fat and serves to repress food intake and promote energy expenditure.[50],[51] In this study, a significant reduction was observed 12 months after LSG compared to preoperative levels. In addition, a clear correlation between %EWL and leptin was observed (R2 0.186, P = 0.001), confirming that weight loss and fat reduction directly affect leptin levels. Leptin and insulin act on the same hypothalamic areas to decrease food intake and increase energy expenditure, thereby regulating the long-term energy balance.[12],[52]

No significant correlation was observed between leptin and miRNA146a and 222-5p in this study. A review that analyzed the role of miRNAs in obesity and IR[53] found that a possible role for the miRNA 200 family was linked to leptin levels and obesity. Further research on the roles of miRNAs in obesity needs to be conducted.

A significant decrease in insulin levels postoperatively was not associated with miRNA or %EWL. However, other studies have shown that miRNA 222-5p can influence insulin levels. This could be explained by the distorted expression of miRNA 222-5p, which can provoke hyperinsulinemia in insulin-resistant cells.[54]


This study performed no univariate and multivariate linear and logistic regression analyses. Since the dependent variables, miRNAs 222-5p and 146a were not normally distributed in a linear sense and binary logistic was not possible on these two dependents on variables, since the cutoff of miRNA is not possible, testing for bias and confounding factors were difficult and impracticable.

Weight (%EWL) has a possible limitation when examining the results. It is clear that SIWL is beneficial for health. This is well known in the literature, and this study showed the benefits of weight loss in %EWL. However, at the same time, a correlation with %EWL was not accurate. Weight is correlated with visceral fat, total body fat, and muscle mass; therefore, these variables are more suitable for a correlation model. However, this study did not have these values, and future studies must be conducted.

Furthermore, miRNA research is a time-consuming and expensive technique. The limitations of the present study are the relatively small sample size in general (but higher than normally tested for miRNA studies) and the demand for the use of larger miRNA panels, as numerous obesity-linked miRNAs could explain the possible role of miRNAs in the LSG of gut hormones. Nevertheless, a meta-analysis of different miRNA expressions in 12 studies with 9–25 subjects showed that this type of research is difficult to perform with large sample size.[55] Another study of miRNAs in 34 patients showed promising results.[33]

  Conclusions Top

This study confirmed the effect of LSG on weight loss and the effect of changing plasma miR146a and miR222-5p levels. Together with decreasing ghrelin and increasing postprandial values of the gut hormones peptide YY and GLP-1, miRNAs affect the reduction of associated medical problems. Furthermore, miRNAs have been shown to be new markers in the treatment, diagnosis, and therapeutic direction of patients with obesity, with a clear impact on IR and the correlation among miRNA146a, HOMA-IR, and FBS.

Ethical approval

All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

All patients provided written and oral informed consent.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  Appendix 1 Top

Amplification and quantification miNRA

Since the conventional term is up to 1, the housekeeping gene, as endogenous control, was subtracted from the target gene. External validation was performed using external controls (subjects without obesity).

The expression of miRNAs was reported as ΔCt values, which was calculated by subtracting the CT values of miRNA-16 (control) from the CT values of the target miRNAs as follows:

Mean cut value (ΔCt) = Ct (target miRNA) – Ct (control). The expression level was determined as follows: 2(− ΔΔCt), where ΔΔ Ct = ΔCt (target miRNA) – ∑ΔCt (control).

The expression levels of miR-222-5p and miR-146a-3p were analyzed using the RT-qPCR. The housekeeping genes contained miRNA-16 as an endogenous control. Real-time PCR of the cDNA template was performed using the SYBR Green Master Mix (Qiagen, Valencia, CA, USA).

Real-time PCR results were analyzed using the Applied Biosystems 7500 (Foster City, CA, USA) under the following conditions: initial incubation at 95°C for 15 min, followed by 40 cycles at 94°C for 15 s, 55°C for 30 s (annealing), and 70°C for 30 s (extension).

The cycle threshold (CT) was defined as the number of cycles required for the fluorescent signal to cross the threshold in real-time PCR.

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  [Table 1], [Table 2], [Table 3]


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