RETRACTED: Transcriptome study of receptive endometrium in overweight and obese women shows important expression differences in immune response and inflammatory pathways in women who do not conceive.

Successful embryo implantation requires two conditions to be met; the presence of a high-quality embryo and a receptive endometrium. Endometrial receptivity is a limited time period during the menstrual cycle when the endometrium enables embryo implantation and is also called the window of implantation (WOI) [ 1 ]. It has been estimated that one-third of embryo implantation failures occur due to an unreceptive endometrium [ 2 ]. During in vitro fertilization (IVF) procedures the transfer of highest quality embryos remains the gold standard of care and, therefore, an implantation failure remains the unresolved issue. Obesity is an increasing worldwide health problem with reports that more than half of reproductive-age women are overweight or obese [ 3 ]. Obesity causes impaired fertility and obese women take longer to conceive than normal weighing women [ 4 ]. The results on the impact of being overweight or obese on IVF procedures are conflicting, as both a negative impact [ 5 , 6 ] as well as no impact [ 7 , 8 ] have already been reported. The mechanism by which increased body weight has an effect on the success of IVF procedures is still unknown. With the emergence of ‘omics’ technologies, numerous research groups have analyzed endometrial gene expression in different phases of the menstrual cycle [ 9 , 10 ], especially during the WOI [ 11 , 12 ]. Many genes have been proposed as potential biomarkers of endometrial receptivity, however, candidate genes differ between studies and a consensus on biomarkers has to date not yet been reached [ 13 ]. Low reproducibility of results is mainly the result of differences in experimental design, patient selection criteria, day and method of endometrial sampling, transcriptome platforms, and statistical methods used. Thus, biomarkers selected from these lists would perform with varying degrees of success. Besides determining potentially differentially expressed genes, transcriptomic studies enable the analyses of enriched biological pathways and processes in tissues. A pathway analysis approach improves sensitivity and selectivity of gene expression studies as it does not focus on unrelated genes but a collection of up—and down—regulated genes obtained in the experiment [ 14 ]. This kind of an approach is advantageous, as subtle physiological changes are often not translated into large gene expression variations and many genes from the same pathway moving in a cluster are a good indication of the physiological processes that take place in the studied tissue [ 15 ]. The pathway analysis approach considers the fact that many times genes involved in the same biological process are deregulated together [ 15 ]. Furthermore, in pathway analysis minor differences in study methods are less likely to influence results and, therefore, results across different data sets are more consistent and robust [ 16 ]. Pathway analysis may, therefore, reveal novel insights about biological processes active in the examined tissue in the situation of interest [ 17 ]. Elucidating the molecular mechanisms and over-represented biological processes during the WOI is important to better understand endometrial functioning and improve success rates of IVF procedures. The present study aimed to exhibit active biological processes in the endometrium of overweight and obese women during the WOI, when the endometrium should be receptive to allow embryo implantation. We aimed to determine the differences in endometrial transcriptome between pregnant and non-pregnant groups of overweight and obese women undergoing IVF procedures. This could characterize potential endometrial mechanisms that impact endometrial receptivity in IVF procedures. Therefore, endometrial samples were obtained during the WOI and transcriptomic analysis of endometrium using RNA sequencing was performed.

Fourteen patients were recruited and stratified according to their IVF result to PG (N = 5) or non-PG (N = 9) group. The comparison of the anthropometric characteristics, endocrine parameters, and IVF cycle characteristics showed no significant differences between groups ( Table 1 ). Comparison of transcriptional differences between PG and non-PG women revealed that 1419 genes surpassed the nominal significance threshold of 0.05. The list of differentially expressed genes with an unadjusted p-value of < 0.05 was subjected to IPA. There were 253 canonical pathways that showed significant dysregulation between PG and non-PG endometrial samples ( S1 Table ). Pathways as IL -8 signaling (p = 1.3 x 10 −8 , z-score– 3.8), chemokine signaling (p = 4.06 x 10 −8 , z-score -3.1), production of nitric-oxide and reactive oxygen species in macrophages (p = 3.8 x 10 −8 , z-score -2.8), role of NFAT in regulation of immune response (p = 5.2 x 10 −7 , z-score -3.3), NRF-2 —mediated oxidative stress response (p = 9.06 x 10−5, z-score -2.4) were among the over-represented in endometrial samples of women who did not conceive ( Fig 1 ). According to IPA, 30.2% (76 of 252) of pathways were related to immune response and inflammation: 56 to cellular immune response, 5 to humoral immune response, and 15 to cellular stress and injury. Moreover, there was an over-expression of cellular immune response pathways (41 out of 56) in the non-PG compared to PG endometrium ( S2 Table ).

Despite the efforts aiming to improve IVF success rates, embryo implantation remains the most important limiting step in IVF procedures. Several different strategies and therapies, such as preimplantation genetic testing [ 59 ], endometrial receptivity analysis [ 60 ], and intentional endometrial scratch injury [ 61 , 62 ], have been proposed for increasing the chances of embryo implantation. The present study has shown that in the endometrium of overweight and obese women who do not conceive pathways associated with immune response and inflammation are overactive during the window of implantation. Considering all studies that have already proposed different genetic biomarkers of endometrial receptivity, it is becoming more or less obvious that the analysis of one or only a few genes will not be enough to determine whether the endometrium is able to provide a suitable environment for embryo implantation during the WOI. Unraveling the unbalanced pathways during the WOI will perhaps enable the correction of defects that lead to implantation failure and thus improving IVF success rates. Further studies are needed to evaluate which one of the proposed procedures for the increased chances of embryo implantation will truly have a significant impact on IVF success rates.

All patients were informed of the study aims and signed a written informed consent form before entering the study. The study was conducted at a tertiary care university hospital in accordance with the Declaration of Helsinki. The study was approved by the National Medical Ethics Committee of the Republic of Slovenia (approval number 0120-491-2017). The study was performed at a tertiary care facility at the Department of Human Reproduction, Division of Obstetrics and Gynecology Ljubljana, Slovenia. Clinical information and endometrial samples were collected from 14 participating infertile patients from February 2017 to February 2018. The inclusion criteria were: under 38 years of age, first or second IVF cycle, unexplained or tubal factor infertility, partner’s normal result of semen analysis. All patients underwent clinical (general and gynaecological examination), anthropometric (body mass, body mass index (BMI), waist circumference), and hormonal assessment (prolactin, LH and FSH, TSH). Blood for hormonal evaluation was drawn during the follicular phase of the menstrual cycle, i.e., between the third and the fifth day of the cycle. Patients were stratified and analyzed according to their IVF results to a pregnancy (PG; N = 5) or non-pregnancy (non-PG; N = 9) group. Endometrial biopsy was performed using a catheter (Rampipella, RI.MOS., Mirandola, Italy) under sterile conditions between the 21 st and 23 rd day of the menstrual cycle preceding the IVF procedure. All samples were snap-frozen in liquid nitrogen and stored at −80°C until further processing. Short protocol (recombinant FSH in combination with GnRH antagonist) was used for controlled ovarian hyperstimulation. Vaginal ultrasound examination was performed to monitor follicular development. Final follicular maturation was induced by administering 6500 IU of human chorionic gonadotropin (hCG) when at least three follicles measured 17 mm in diameter. Ultrasound-guided transvaginal oocyte pick-up was performed 34–36 h later. Embryo transfer was performed on day 3 or 5 after oocyte pick-up. Biochemical pregnancy was determined by measuring ßhCG 14 days after embryo transfer, and clinical pregnancy was confirmed by the presence of a gestational sac and fetal heartbeat by ultrasound examination 6 weeks after embryo transfer. Total RNA was isolated from endometrial tissues using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. In short, biological samples were first lysed and homogenized in the presence of a highly denaturizing guanidine-thiocyanate–containing buffer, which immediately inactivated RNases to ensure purification of intact RNA. Ethanol was added to provide appropriate binding conditions, and the sample was then applied to a RNeasy Mini spin column, where the total RNA bound to the membrane and contaminants were washed away. RNA was then eluted in 30–100 μl water. The purity of isolated RNA was assessed using the NanoDrop 2000c spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA) and integrity was determined on Agilent 2100 Bioanalyzer using RNA 6000 Nano LabChip kit. All of the samples had RNA integrity values greater than 7.0 and were used for library preparation. Extracted RNA samples were stored at -80°C until further processing. Library preparation was performed using TruSeq stranded total RNA sample preparation kit (Illumina), according to the manufacturer’s protocol. After Ribo-Zero rRNA depletion, the remaining RNA was purified, fragmented, and primed for first-strand cDNA synthesis with reverse transcriptase (SuperScript II) and random primers, followed by second-strand cDNA synthesis performed in the presence of dUTP. Blunt-ended double-strand DNA was 3’ adenylated and multiple indexing adapters (T-tailed) were ligated to the ends of the ds cDNA. Fragments with adapter molecules on both ends were selectively enriched with 15 cycles of PCR reaction. Prepared libraries were normalized to the final concentration of 10 nM and then pooled in equimolar concentrations. Sequencing was performed on the Illumina Hiseq 2000 sequencing system in 2x100 sequencing cycles using pair-end sequencing mode. After initial read quality filtering and demultiplexing, alignments to the human reference genome (hg19) were performed. The reads were aligned to a genome and transcript splice sites were discovered with HISAT [ 18 ]. Alignments were assembled into full and partial transcripts and the expression levels of all genes and transcripts were estimated by StringTie [ 19 ]. The transcripts and expression levels from StringTie were statistically processed by Ballgown [ 20 ], which were then estimated using read counts function in the Subread package for R 5, followed by an intersample normalization by variance modeling at the observational level (voom) approach implemented in the limma Bioconductor package. The differences in gene expression were estimated using linear modeling and significance estimation procedures in the limma [ 21 ]. Quality control analysis was done with RSeQC [ 22 ]. Functional analyses of the identified transcriptional alterations were characterized using the Ingenuity Pathway Analysis software (QIAGEN, Redwood 185 City, CA, USA). The IPA enables the analysis of functional pathway enrichment and determination of the state of upstream regulators (UR). Genes with significance values below 0.05 were included in the analyses. The remaining parameters were kept in their default setting. A right-tailed Fisher’s exact test was used for calculating a significance score for each association between genes in the experimental dataset and a biological function. To reduce false-positive results, IPA pathways were considered significant only if they were associated with a p-value 2, predicted inactivation < -2). Normal data distribution was checked with the Shapiro–Wilk test. T-test was used for the normally distributed data, and Mann-Whitney U test for non-normally distributed data. P-value of <0.05 was considered statistically significant. The results are presented as a median and interquartile range (the distance between the 25th and 75th percentiles). Statistical analysis was performed using IBM SPSS Statistics, version 24 (IBM Corp, Armonk, NY).

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