Predicting risk of endometrial failure: a biomarker signature that identifies a novel disruption independent of endometrial timing in patients undergoing hormonal replacement cycles.

OBJECTIVE: To propose a new gene expression signature that identifies endometrial disruptions independent of endometrial luteal phase timing and predicts if patients are at risk of endometrial failure. DESIGN: Multicentric, prospective study. SETTING: Reproductive medicine research department in a public hospital affiliated with private fertility clinics and a reproductive genetics laboratory. PATIENTS: Caucasian women (n = 281; 39.4 ± 4.8 years old with a body mass index of 22.9 ± 3.5 kg/m2) undergoing hormone replacement therapy between July 2018 and July 2021. Endometrial samples from 217 patients met RNA quality criteria for signature discovery and analysis. INTERVENTION(S): Endometrial biopsies collected in the mid-secretory phase. MAIN OUTCOME MEASURE(S): Endometrial luteal phase timing-corrected expression of 404 genes and reproductive outcomes of the first single embryo transfer (SET) after biopsy collection to identify prognostic biomarkers of endometrial failure. RESULTS: Removal of endometrial timing variation from gene expression data allowed patients to be stratified into poor (n = 137) or good (n = 49) endometrial prognosis groups on the basis of their clinical and transcriptomic profiles. Significant differences were found between endometrial prognosis groups in terms of reproductive rates: pregnancy (44.6% vs. 79.6%), live birth (25.6% vs. 77.6%), clinical miscarriage (22.2% vs. 2.6%), and biochemical miscarriage (20.4% vs. 0%). The relative risk of endometrial failure for patients predicted as a poor endometrial prognosis was 3.3 times higher than those with a good prognosis. The differences in gene expression between both profiles were proposed as a biomarker, coined the endometrial failure risk (EFR) signature. Poor prognosis profiles were characterized by 59 upregulated and 63 downregulated genes mainly involved in regulation (17.0%), metabolism (8.4%), immune response, and inflammation (7.8%). This EFR signature had a median accuracy of 0.92 (min = 0.88, max = 0.94), median sensitivity of 0.96 (min = 0.91, max = 0.98), and median specificity of 0.84 (min = 0.77, max = 0.88), positioning itself as a promising biomarker for endometrial evaluation. CONCLUSION(S): The EFR signature revealed a novel endometrial disruption, independent of endometrial luteal phase timing, present in 73.7% of patients. This EFR signature stratified patients into 2 significantly distinct and clinically relevant prognosis profiles providing opportunities for personalized therapy. Nevertheless, further validations are needed before implementing this gene signature as an artificial intelligence (AI)-based tool to reduce the risk of patients experiencing endometrial failure.

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.

Deciphering a shared transcriptomic regulation and the relative contribution of each regulator type through endometrial gene expression signatures.

BACKGORUND: While various endometrial biomarkers have been characterized at the transcriptomic and functional level, there is generally a poor overlap among studies, making it unclear to what extent their upstream regulators (e.g., ovarian hormones, transcription factors (TFs) and microRNAs (miRNAs)) realistically contribute to menstrual cycle progression and function. Unmasking the intricacies of the molecular interactions in the endometrium from a novel systemic point of view will help gain a more accurate perspective of endometrial regulation and a better explanation the molecular etiology of endometrial-factor infertility. METHODS: An in-silico analysis was carried out to identify which regulators consistently target the gene biomarkers proposed in studies related to endometrial progression and implantation failure (19 gene lists/signatures were included). The roles of these regulators, and of genes related to progesterone and estrogens, were then analysed in transcriptomic datasets compiled from samples collected throughout the menstrual cycle (n = 129), and the expression of selected TFs were prospectively validated in an independent cohort of healthy participants (n = 19). RESULTS: A total of 3,608 distinct genes from the 19 gene lists were associated with endometrial progression and implantation failure. The lists' regulation was significantly favoured by TFs (89% (17/19) of gene lists) and progesterone (47% (8 /19) of gene lists), rather than miRNAs (5% (1/19) of gene lists) or estrogen (0% (0/19) of gene lists), respectively (FDR < 0.05). Exceptionally, two gene lists that were previously associated with implantation failure and unexplained infertility were less hormone-dependent, but primarily regulated by estrogen. Although endometrial progression genes were mainly targeted by hormones rather than non-hormonal contributors (odds ratio = 91.94, FDR < 0.05), we identified 311 TFs and 595 miRNAs not previously associated with ovarian hormones. We highlight CTCF, GATA6, hsa-miR-15a-5p, hsa-miR-218-5p, hsa-miR-107, hsa-miR-103a-3p, and hsa-miR-128-3p, as overlapping novel master regulators of endometrial function. The gene expression changes of selected regulators throughout the menstrual cycle (FDR < 0.05), dually validated in-silico and through endometrial biopsies, corroborated their potential regulatory roles in the endometrium. CONCLUSIONS: This study revealed novel hormonal and non-hormonal regulators and their relative contributions to endometrial progression and pathology, providing new leads for the potential causes of endometrial-factor infertility.

Association of blood cadmium and lead levels with self-reported reproductive lifespan and pregnancy loss: The national health and nutrition examination survey 1999-2018.

Cadmium and lead are known to interfere with the endocrine function. Thus, hormonally regulated processes such as menarche, menopause and pregnancy are likely influenced by chronic exposure to these metals. In US post-menopausal women, who already completed their reproductive lifespan, we evaluated the association between blood cadmium and lead levels with self-reported reproductive lifespan and personal history of pregnancy loss. We selected 5317 post-menopausal women participating in the National Health and Nutrition Examination Survey (NHANES), 1999-2018. Blood cadmium and lead levels were measured by inductively coupled plasma mass spectrometry. Reproductive lifespan was defined as the number of years between self-reported age at menarche and menopause. Personal history of pregnancy loss was defined as number of self-reported pregnancy losses out of the self-reported number of pregnancies. The fully adjusted mean difference in reproductive lifespan (95% confidence interval [CI]) comparing the 80th to the 20th percentiles of blood cadmium and lead distributions was, respectively, 0.50 (0.10, 0.91) and 0.72 (0.41, 1.03) years. Ever smoker showed stronger association of blood lead with reproductive lifespan. For self-reported pregnancy loss, the corresponding fully adjusted relative prevalence (95% CI) was 1.10 (0.93, 1.31) for cadmium and 1.10 (1.00, 1.21) for lead, and remained similar after additional adjustment for reproductive lifespan. In never smokers, the relative prevalence was 1.07 (1.04, 1.11) and 1.16 (1.05, 1.28) for blood cadmium and lead, respectively. These findings suggest that blood cadmium and lead exposures increase reproductive lifespan and prevalence of pregnancy loss in the general population. Additional studies are needed to improve the understanding of mechanisms and prevention potential of metals-related pregnancy outcomes.

Microbiome Preterm Birth DREAM Challenge: Crowdsourcing Machine Learning Approaches to Advance Preterm Birth Research.

Globally, every year about 11% of infants are born preterm, defined as a birth prior to 37 weeks of gestation, with significant and lingering health consequences. Multiple studies have related the vaginal microbiome to preterm birth. We present a crowdsourcing approach to predict: (a) preterm or (b) early preterm birth from 9 publicly available vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from raw sequences via an open-source tool, MaLiAmPi. We validated the crowdsourced models on novel datasets representing 331 samples from 148 pregnant individuals. From 318 DREAM challenge participants we received 148 and 121 submissions for our two separate prediction sub-challenges with top-ranking submissions achieving bootstrapped AUROC scores of 0.69 and 0.87, respectively. Alpha diversity, VALENCIA community state types, and composition (via phylotype relative abundance) were important features in the top performing models, most of which were tree based methods. This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice, and to better understand and prevent preterm birth.

VMAP: Vaginal Microbiome Atlas During Pregnancy.

The vaginal microbiome has been shown to be associated with pregnancy outcomes including preterm birth (PTB) risk. Here we present VMAP: Vaginal Microbiome Atlas during Pregnancy (http://vmapapp.org), an application to visualize features of 3,909 vaginal microbiome samples of 1,416 pregnant individuals from 11 studies, aggregated from raw public and newly generated sequences via an open-source tool, MaLiAmPi. Our visualization tool (http://vmapapp.org) includes microbial features such as various measures of diversity, VALENCIA community state types (CST), and composition (via phylotypes and taxonomy). This work serves as a resource for the research community to further analyze and visualize vaginal microbiome data in order to better understand both healthy term pregnancies and those associated with adverse outcomes.

Endometrial gene expression differences in women with coronavirus disease 2019.

OBJECTIVE: To study the potential effect of coronavirus disease (COVID-19) on the endometrial transcriptome of affected, symptomatic women for the detection of altered gene expression. DESIGN: Pilot study of the endometrial transcriptomes of women manifesting COVID-19 compared with those of women without COVID-19 undergoing hysteroscopic procedures for benign gynecologic disorders using RNA sequencing. SETTING: Hospital and university laboratories. PATIENT(S): Women with (n = 14) and without a COVID-19 (n = 10) diagnosis based on a nasopharyngeal swab analysis using quantitative reverse-transcription polymerase chain reaction. The endometrium of the patients with COVID-19 had previously been tested for severe acute respiratory syndrome coronavirus 2 infection, revealing the absence of the virus in this tissue. INTERVENTION(S): Endometrial biopsy sample collection. MAIN OUTCOMES MEASURE(S): Endometrial gene expression and functional analysis of symptomatic patients with COVID-19 vs. individuals without the infection. RESULT(S): The systemic disease COVID-19 altered endometrial gene expression in 75% of the women, with the patients exhibiting a preponderance of 163 up-regulated (e.g., UTS2, IFI6, IFIH1, and BNIP3) and 72 down-regulated genes (e.g., CPZ, CDH3, and IRF4) (false discovery rate<0.05). A total of 161 dysregulated functions (36 up-regulated and 125 down-regulated) were typically enriched in the endometria of the patients with COVID-19, including up-regulation in pathways involved in the development of immune responses to viruses and cytokine inflammation, reflecting elicitation of a COVID-19 response pathway. CONCLUSION(S): Coronavirus disease 2019 affects endometrial gene expression despite the absence of severe acute respiratory syndrome coronavirus 2 RNA in endometrial tissues.

Use of the endometrial receptivity array to guide personalized embryo transfer after a failed transfer attempt was associated with a lower cumulative and per transfer live birth rate during donor and autologous cycles.

OBJECTIVE: To determine whether personalized embryo transfer (pET) guided by endometrial receptivity array (ERA) test improves reproductive outcomes for fresh embryo transfers (fsETs) or frozen embryo transfers (FETs) during autologous and donor cycles. DESIGN: A retrospective, observational, multicenter cohort study. SETTING: University-affiliated in vitro fertilization center. PATIENT(S): The study included patients with a single previous failed transfer and yielded 3,239 autologous transfers and 2,133 donor transfers. Among autologous transfers, 255 were pET guided by ERA; among unguided autologous transfers, 1,122 and 1,862 transfers involved fresh or previously frozen embryos, respectively. Among donor transfers, 319 were ERA-guided; among unguided donor transfers, 1,175 and 639 involved fsETs or FETs, respectively. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Primary outcomes were live birth rate per embryo transfer and cumulative live birth rate on consecutive transfers until live birth or cessation of pregnancy. Secondary outcomes were implantation, pregnancy rate, clinical pregnancy rates per embryo transfer, and miscarriage rate per pregnancy. RESULT(S): During both autologous or donor transfers, live birth rate and cumulative live birth rate were higher in FET and fsET than in pET groups, even with euploid transfers. Logistic regression analysis, considering possible confounders, indicated patients receiving pET had poorer outcomes than those undergoing FET and fsET in autologous and donor cycles. Implantation, pregnancy, and clinical pregnancy rates were lower in patients undergoing pET. CONCLUSION(S): Using ERA to guide pET during either autologous or donor cycles after a failed transfer attempt did not improve reproductive outcomes. Conversely, worse outcomes were detected when ERA was used.

Machine Learning-Based Approach Highlights the Use of a Genomic Variant Profile for Precision Medicine in Ovarian Failure.

Ovarian failure (OF) is a common cause of infertility usually diagnosed as idiopathic, with genetic causes accounting for 10-25% of cases. Whole-exome sequencing (WES) may enable identifying contributing genes and variant profiles to stratify the population into subtypes of OF. This study sought to identify a blood-based gene variant profile using accumulation of rare variants to promote precision medicine in fertility preservation programs. A case-control (n = 118, n = 32, respectively) WES study was performed in which only non-synonymous rare variants <5% minor allele frequency (MAF; in the IGSR) and coverage ≥ 100× were considered. A profile of 66 variants of uncertain significance was used for training an unsupervised machine learning model to separate cases from controls (97.2% sensitivity, 99.2% specificity) and stratify the population into two subtypes of OF (A and B) (93.31% sensitivity, 96.67% specificity). Model testing within the IGSR female population predicted 0.5% of women as subtype A and 2.4% as subtype B. This is the first study linking OF to the accumulation of rare variants and generates a new potential taxonomy supporting application of this approach for precision medicine in fertility preservation.

Pathways and factors regulated by bone marrow-derived stem cells in human ovarian tissue.

OBJECTIVE: To describe molecular and paracrine signaling changes produced by human bone marrow-derived stem cells (BMDSC) in human ovarian cortex. DESIGN: Experimental study. SETTING: University hospital research laboratories. PATIENT(S): Ovarian cortex from poor responder women (n = 7). ANIMALS: Immunodeficient NOD/SCID female mice (n = 18). INTERVENTION(S): Human ovarian cortex strips were xenografted into ovariectomized NOD/SCID female mice. A week later, mice were infused with phosphate-buffered saline, 1 × 106 BMDSC, or 3 × 105 CD133+ cells via tail vein. Gene expression changes and enriched pathways were assessed by RT2 Profiler Arrays. Several upregulated genes were validated in individual samples by real-time quantitative PCR, and transcriptomic results were reinforced by a proteomic assessment. MAIN OUTCOME MEASURE(S): Gene expression changes, enriched Kyoto Encyclopedia of Genes and Genomes pathways, and paracrine factors. RESULT(S): Seventy-four Kyoto Encyclopedia of Genes and Genomes pathways were upregulated, with the PI3K-Akt signaling pathway the most enriched after BMDSC and CD133 treatments. The greatest transcriptomic changes were seen on day 14 in the BMDSC group, affecting the regulation of paracrine factors such as KITLG, THBS1, SERPINF1, and TIMP2. Proteomics data verified changes in FoxO signaling, actin cytoskeleton remodeling, and apoptosis by BMDSC. CONCLUSION(S): We identified paracrine factors and pathways regulated by BMDSC that may be future targets of treatment for the increasing number of poor responder women. Our findings suggest that BMDSC upregulated soluble factors such as KITLG, THBS1, SERPINF1, and TIMP2 as well as PI3K-Akt signaling and regulation of actin cytoskeleton pathways. The identification of these putative underlying mechanisms informs future experiments aiming to optimizing clinical application of BMDSC.

Guidelines for biomarker discovery in endometrium: correcting for menstrual cycle bias reveals new genes associated with uterine disorders.

Transcriptomic approaches are increasingly used in reproductive medicine to identify candidate endometrial biomarkers. However, it is known that endometrial progression in the molecular biology of the menstrual cycle is a main factor that could affect the discovery of disorder-related genes. Therefore, the aim of this study was to systematically review current practices for considering the menstrual cycle effect and to demonstrate its bias in the identification of potential biomarkers. From the 35 studies meeting the criteria, 31.43% did not register the menstrual cycle phase. We analysed the menstrual cycle effect in 11 papers (including 12 studies) from Gene Expression Omnibus: three evaluating endometriosis, two evaluating recurrent implantation failure, one evaluating recurrent pregnancy loss, one evaluating uterine fibroids and five control studies, which collected endometrial samples throughout menstrual cycle. An average of 44.2% more genes were identified after removing menstrual cycle bias using linear models. This effect was observed even if studies were balanced in the proportion of samples collected at different endometrial stages or only in the mid-secretory phase. Our bias correction method increased the statistical power by retrieving more candidate genes than per-phase independent analyses. Thanks to this practice, we discovered 544 novel candidate genes for eutopic endometriosis, 158 genes for ectopic ovarian endometriosis and 27 genes for recurrent implantation failure. In conclusion, we demonstrate that menstrual cycle progression masks molecular biomarkers, provides new guidelines to unmask them and proposes a new classification that distinguishes between biomarkers of disorder or/and menstrual cycle progression.

Evaluation of the endometrial receptivity assay and the preimplantation genetic test for aneuploidy in overcoming recurrent implantation failure.

PURPOSE: To evaluate the clinical usefulness of the endometrial receptivity array (ERA) and the preimplantation genetic test for aneuploidy (PGT-A) in patients with severe and moderate recurrent implantation failure (RIF). DESIGN: A retrospective multicenter cohort study was conducted in patients who failed to achieve implantation following transfer of 3 or more or 5 or more embryos in at least three single embryo transfers; patients were classified as moderate or severe RIF, respectively. Patients with previous RIF were compared based on the testing they received: PGT-A, ERA, or PGT-A+ERA versus a control group with no testing. Mean implantation rate and ongoing pregnancy rates per embryo transfer were considered primary outcomes. Multiple logistic regression analysis was performed and adjusted ORs were calculated to control possible bias. RESULTS: Of the 2110 patients belonging to the moderate RIF group, those who underwent transfer of euploid embryos after PGT-A had a higher implantation rate than those who did not. Additionally, the PGT-A group had a significantly higher rate of ongoing pregnancy. The same outcomes measured for the 488 patients in the severe RIF group did not reveal any statistically significant improvements. The use of the ERA test did not appear to significantly improve outcomes in either group. CONCLUSIONS: PGT-A may be beneficial for patients with moderate recurrent implantation failure but not for severe cases. At its current level of development, ERA does not appear to be clinically useful for patients with RIF.

SARS-CoV-2 infection risk assessment in the endometrium: viral infection-related gene expression across the menstrual cycle.

OBJECTIVE: To determine the susceptibility of the endometrium to infection by-and thereby potential damage from-SARS-CoV-2. DESIGN: Analysis of SARS-Cov-2 infection-related gene expression from endometrial transcriptomic data sets. SETTING: Infertility research department affiliated with a public hospital. PATIENT(S): Gene expression data from five studies in 112 patients with normal endometrium collected throughout the menstrual cycle. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Gene expression and correlation between viral infectivity genes and age throughout the menstrual cycle. RESULT(S): Gene expression was high for TMPRSS4, CTSL, CTSB, FURIN, MX1, and BSG; medium for TMPRSS2; and low for ACE2. ACE2, TMPRSS4, CTSB, CTSL, and MX1 expression increased toward the window of implantation. TMPRSS4 expression was positively correlated with ACE2, CTSB, CTSL, MX1, and FURIN during several cycle phases; TMPRSS2 was not statistically significantly altered across the cycle. ACE2, TMPRSS4, CTSB, CTSL, BSG, and MX1 expression increased with age, especially in early phases of the cycle. CONCLUSION(S): Endometrial tissue is likely safe from SARS-CoV-2 cell entry based on ACE2 and TMPRSS2 expression, but susceptibility increases with age. Further, TMPRSS4, along with BSG-mediated viral entry into cells, could imply a susceptible environment for SARS-CoV-2 entry via different mechanisms. Additional studies are warranted to determine the true risk of endometrial infection by SARS-CoV-2 and implications for fertility treatments.

Uterine disorders affecting female fertility: what are the molecular functions altered in endometrium?

OBJECTIVE: To determine the molecular functions of genes exhibiting altered expression in the endometrium of women with uterine disorders affecting fertility. DESIGN: Retrospective analysis integrating case and control data from multiple cohorts with endometrium gene expression in women with uterine disorders. SETTING: Infertility research department affiliated with a university hospital. PATIENT(S): Two hundred and forty women, 121 of whom were controls, 119 of whom had endometrial adenocarcinoma (ADC), recurrent implantation failure (RIF), recurrent pregnancy loss (RPL), or stage II-IV endometriosis. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Genomewide gene expression and altered molecular functions in the endometrium of each uterine disorder. RESULT(S): Using robust analysis methods, we identified statistically significantly altered endometrial functions in all the uterine disorders. Cell cycle alterations were shared among all the pathologies investigated. Endometriosis was characterized by the down-regulation of ciliary processes. Among the endometriosis, ADC, and RIF samples, mitochondrial dysfunction and protein degradation were shared dysregulated processes. In addition, RPL had the most distinct functional profile, and 95% of affected functions were down-regulated. CONCLUSION(S): The most robust functions dysregulated in the endometrium of patients with uterine disorders across sample cohorts implicated an endometrial factor at the gene expression level. This shared endometrial factor affects endometrial receptivity processes.

Cumulus cells have longer telomeres than leukocytes in reproductive-age women.

OBJECTIVE: To investigate whether telomere length (TL) in granulosa cells (GC) or cumulus cells (CC) correlates with TL in leukocytes (L). DESIGN: Prospective noninterventional study. SETTING: Private assisted reproductive technology center. PATIENT(S): Thirty-five egg donors were included in the study. INTERVENTIONS(S): None. MAIN OUTCOME MEASURE(S): Average relative leukocyte telomere length (LTL), cumulus cell telomere length (CCTL), and granulosa cell telomere length (GCTL) measurements from each study subject. RESULT(S): Participants had a mean age of 25.43 ± 4.57 years, antimüllerian hormone level of 1.90 ± 0.92 ng/mL, antral follicle count of 23.29 ± 5.11, and the mean number of mature oocytes retrieved was 23.29 ± 9.13. No significant association between these variables and GCTL, CCTL, or LTL was found. In addition, no correlation was observed between TL measurements of L vs. CC, L vs. GC, or CC vs. GC. Interestingly, CCTL was significantly higher than LTL (1.54-fold), although no significant differences were found between GCTL vs. CCTL or GCTL vs. LTL. CONCLUSION(S): CC from mature follicles have significantly longer telomeres than L, suggesting that the follicular environment could possess different mechanisms to cope against telomere shortening compared with other somatic tissues. Furthermore, these data do not support the utility of telomere DNA measurement in L as an estimate of TL in follicular cells.

iTRAQ comparison of proteomic profiles of endometrial receptivity.

Endometrial receptivity is a limiting step in human reproduction. A disruption in the development of endometrial receptivity is responsible for recurrent implantation failures (RIF) of endometrial origin. To understand the molecular mechanisms behind the endometrial receptivity process, we used the isobaric tag for relative and absolute quantitation (iTRAQ) method to compare three different endometrial statuses: fertile women, intrauterine device (IUD) carriers, and RIF patients. Overall, iTRAQ allowed identified 1889 non-redundant proteins. Of these, 188 were differentially expressed proteins (DEP) (p-value < .05). Pairwise comparisons revealed 133 significant DEP in fertile vs. IUD carriers and 158 DEP in RIF vs. IUD carriers. However, no DEP were identified between fertile and RIF patients. Western blot validation of three DEP involved in endometrial receptivity (plastin 2, lactotransferrin, and lysozyme) confirmed our iTRAQ results. Moreover, functional KEGG enrichment revealed that complement and coagulation cascades and peroxisome were the two most significant pathways for the RIF vs. IUD comparison and ribosome and spliceosome for the fertile vs. IUD comparison, as possible important pathways involved in the endometrial receptivity acquisition. The lack of DEP between fertile and RIF patient endometria suggest that idiopathic RIF may not have an endometrial origin, with other as-yet-unknown factors involved. SIGNIFICANCE: A pilot study where a comparison of the endometrial protein profile from women with different endometrial receptive grade (fertile women, IUD carriers and RIF patients) during the same period of time (overlapping with the window of implantation) of a hormone replacement therapy was performed using a high-throughput proteomic technique. This approach lead us to better understand the molecular mechanisms undergoing endometrial receptivity, a time-limiting step to achieve pregnancy in humans. Moreover, the number of samples per group (10 Fertile women, 10 IUD carriers and 8 RIF patients) according to the methodology here employed (8plex iTRAQ), give more robustness to our results. Our findings confirm that an IUD introduces numerous changes in the endometrial protein profile when compared to fertile and RIF endometria, revealing some key proteins involved in endometrial receptivity. Finding no significant differences between Fertile and RIF patient endometria could suggest that other as-yet-unknown factors could be involved in the etiology of idiopathic RIF.

Transcriptomic behavior of genes associated with chromosome 21 aneuploidies in early embryo development.

OBJECTIVE: To analyze how chromosome 21 (HSA21) ploidy affects global gene expression of early human blastocysts. DESIGN: Prospective study. SETTING: University-affiliated in vitro fertilization clinic. PATIENT(S): A total of 26 high-quality donated embryos from in vitro fertilization (IVF) patients: trisomy 21 (n = 8), monosomy 21 (n = 10), and euploid (n = 8) blastocysts. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Blastocyst transcriptome changes and its associated functions. RESULT(S): Trisomy 21, monosomy 21, and euploid blastocysts were classified by comparative genomic hybridization. The global transcriptome of whole blastocysts was analyzed with small cell number RNA sequencing, and they were compared to understand the gene expression behavior at early development and its implications for embryo implantation. We identified 1,232 differentially expressed genes (false discovery rate <0.05) in monosomy 21 compared with euploid blastocysts associated with dysregulated functions in embryo development as the Rap1 signaling pathway. Curiously, Down syndrome in early development revealed fewer transcriptomic changes than expected. In addition, Down syndrome gene expression in neonates, children, and adults revealed that the number of deregulated genes increases across life stages from blastocysts to adults, suggesting a potential dosage-compensation mechanism for human chromosome 21. CONCLUSION(S): At the transcriptomic level, early development in Down syndrome is mainly dosage compensated. However, monosomy 21 is strongly transcriptionally affected because early development involving main functions is associated with embryo implantation.