Enhancing Genetic Association Power in Endometriosis through Unsupervised Clustering of Clinical Subtypes Identified from Electronic Health Records.

Background: Endometriosis affects 10% of reproductive-age women, and yet, it goes undiagnosed for 3.6 years on average after symptoms onset. Despite large GWAS meta-analyses (N > 750,000), only a few dozen causal loci have been identified. We hypothesized that the challenges in identifying causal genes for endometriosis stem from heterogeneity across clinical and biological factors underlying endometriosis diagnosis. Methods: We extracted known endometriosis risk factors, symptoms, and concomitant conditions from the Penn Medicine Biobank (PMBB) and performed unsupervised spectral clustering on 4,078 women with endometriosis. The 5 clusters were characterized by utilizing additional electronic health record (EHR) variables, such as endometriosis-related comorbidities and confirmed surgical phenotypes. From four EHR-linked genetic datasets, PMBB, eMERGE, AOU, and UKBB, we extracted lead variants and tag variants 39 known endometriosis loci for association testing. We meta-analyzed ancestry-stratified case/control tests for each locus and cluster in addition to a positive control (Total N endometriosis cases = 10,108). Results: We have designated the five subtype clusters as pain comorbidities, uterine disorders, pregnancy complications, cardiometabolic comorbidities, and EHR-asymptomatic based on enriched features from each group. One locus, RNLS , surpassed the genome-wide significant threshold in the positive control. Thirteen more loci reached a Bonferroni threshold of 1.3 x 10 -3 (0.05 / 39) in the positive control. The cluster-stratified tests yielded more significant associations than the positive control for anywhere from 5 to 15 loci depending on the cluster. Bonferroni significant loci were identified for four out of five clusters, including WNT4 and GREB1 for the uterine disorders cluster, RNLS for the cardiometabolic cluster, FSHB for the pregnancy complications cluster, and SYNE1 and CDKN2B-AS1 for the EHR-asymptomatic cluster. This study enhances our understanding of the clinical presentation patterns of endometriosis subtypes, showcasing the innovative approach employed to investigate this complex disease.

Multiplexed Serum Biomarkers to Discriminate Nonviable and Ectopic Pregnancy.

OBJECTIVE: The use of multiplexed biomarkers may improve the diagnosis of normal and abnormal early pregnancies. In this study we assessed 24 markers with multiple machine learning-based methodologies to evaluate combinations of top candidates to develop a multiplexed prediction model for identification of 1) viability and 2) location of an early pregnancy. DESIGN: A nested case-control design evaluating the predictive ability and discrimination of biomarkers in patients at risk of early pregnancy failure in the first trimester to classify viability and location SUBJECTS: 218 individuals with a symptomatic (pain and/or bleeding) early pregnancy: 75 with an ongoing intrauterine gestation, 68 ectopic pregnancies, and 75 miscarriages. INTERVENTIONS: Serum values of 24 biomarkers were assessed in the same patients. Multiple machine learning-based methodologies to evaluate combinations of these top candidates to develop a multiplexed prediction model for identification of 1) a nonviable pregnancy (ongoing intrauterine pregnancy vs miscarriage or ectopic pregnancy) and 2) an ectopic pregnancy (ectopic pregnancy vs ongoing intrauterine pregnancy or miscarriage). MAIN OUTCOME MEASURES: The predicted classification by each model was compared to actual diagnosis and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), conclusive classification, and accuracy were calculated. RESULTS: Models using classification regression tree analysis using three markers (PSG3, CG-Alpha and PAPPA) were able to predict a maximum sensitivity 93.3%, a maximum specificity 98.6%. The model with the highest accuracy was 97.4% (with 70.2% receiving classification). Models using an overlapping group of three markers (sFLT, PSG3 and TFP12) achieved a maximum sensitivity of 98.5%. and a maximum specificity of 95.3%. The model with the highest accuracy was 94.4% (with 65.6% receiving classification). When the models were used simultaneously the conclusive classification increased to 72.7% with an accuracy 95.9%. The predictive ability of the biomarkers random forest produced similar test characteristics when using 11 predictive markers. CONCLUSION: We have demonstrated a pool of biomarkers from divergent biological pathways that can be used to classify individuals with potential early pregnancy loss. The biomarkers CG-Alpha, PAPPA and PSG3 can be used to predict viability and sFLT, TPFI2 and PSG3 can be used to predict pregnancy location.

Evaluation of novel biomarkers for early pregnancy outcome prediction†.

OBJECTIVE: To assess performance and discriminatory capacity of commercially available enzyme-linked immunosorbent assays of biomarkers for predicting first trimester pregnancy outcome in a multi-center cohort. DESIGN: In a case-control study at three academic centers of women with pain and bleeding in early pregnancy, enzyme-linked immunosorbent assays of biomarkers were screened for assay performance. Performance was assessed via functional sensitivity, assay reportable range, recovery/linearity, and intra-assay precision (%Coefficient of Variation). Top candidates were analyzed for discriminatory capacity for viability and location among 210 women with tubal ectopic pregnancy, viable intrauterine pregnancy, or miscarriage. Assay discrimination was assessed by visual plots, area under the curve with 95% confidence intervals, and measures of central tendency with two-sample t-tests. RESULTS: Of 25 biomarkers evaluated, 22 demonstrated good or acceptable assay performance. Transgelin-2, oviductal glycoprotein, and integrin-linked kinase were rejected due to poor performance. The best biomarkers for discrimination of pregnancy location were pregnancy-specific beta-1-glycoprotein 9, pregnancy-specific beta-1-glycoprotein 1, insulin-like growth factor binding protein 1, kisspeptin (KISS1), pregnancy-specific beta-1-glycoprotein 3, and beta parvin (PARVB). The best biomarkers for discrimination of pregnancy viability were pregnancy-specific beta-1-glycoprotein 9, pregnancy-specific beta-1-glycoprotein 3, EH domain-containing protein 3, KISS1, WAP four-disulfide core domain protein 2 (HE4), quiescin sulfhydryl oxidase 2, and pregnancy-specific beta-1-glycoprotein 1. CONCLUSION: Performance of commercially available enzyme-linked immunosorbent assays was acceptable for a panel of novel biomarkers to predict early pregnancy outcome. Of these, six and seven candidates demonstrated good discriminatory capacity of pregnancy location and viability, respectively, when validated in a distinct external population. Four markers demonstrated good discrimination for both location and viability.

Identification and verification of plasma protein biomarkers that accurately identify an ectopic pregnancy.

BACKGROUND: Differentiating between a normal intrauterine pregnancy (IUP) and abnormal conditions including early pregnancy loss (EPL) or ectopic pregnancy (EP) is a major clinical challenge in early pregnancy. Currently, serial ß-human chorionic gonadotropin (ß-hCG) and progesterone are the most commonly used plasma biomarkers for evaluating pregnancy prognosis when ultrasound is inconclusive. However, neither biomarker can predict an EP with sufficient and reproducible accuracy. Hence, identification of new plasma biomarkers that can accurately diagnose EP would have great clinical value. METHODS: Plasma was collected from a discovery cohort of 48 consenting women having an IUP, EPL, or EP. Samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by a label-free proteomics analysis to identify significant changes between pregnancy outcomes. A panel of 14 candidate biomarkers were then verified in an independent cohort of 74 women using absolute quantitation by targeted parallel reaction monitoring mass spectrometry (PRM-MS) which provided the capacity to distinguish between closely related protein isoforms. Logistic regression and Lasso feature selection were used to evaluate the performance of individual biomarkers and panels of multiple biomarkers to predict EP. RESULTS: A total of 1391 proteins were identified in an unbiased plasma proteome discovery. A number of significant changes (FDR ≤ 5%) were identified when comparing EP vs. non-EP (IUP + EPL). Next, 14 candidate biomarkers (ADAM12, CGA, CGB, ISM2, NOTUM, PAEP, PAPPA, PSG1, PSG2, PSG3, PSG9, PSG11, PSG6/9, and PSG8/1) were verified as being significantly different between EP and non-EP in an independent cohort (FDR ≤ 5%). Using logistic regression models, a risk score for EP was calculated for each subject, and four multiple biomarker logistic models were identified that performed similarly and had higher AUCs than models with single predictors. CONCLUSIONS: Overall, four multivariable logistic models were identified that had significantly better prediction of having EP than those logistic models with single biomarkers. Model 4 (NOTUM, PAEP, PAPPA, ADAM12) had the highest AUC (0.987) and accuracy (96%). However, because the models are statistically similar, all markers in the four models and other highly correlated markers should be considered in further validation studies.

Race, ovarian responsiveness, and live birth after in vitro fertilization.

OBJECTIVE: To determine if ovarian responsiveness to gonadotropin stimulation differs by race/ethnicity and whether this predicts live birth rates (LBRs) in non-White patients undergoing in vitro fertilization (IVF). DESIGN: Retrospective cohort study. SETTING: Academic infertility center. PATIENT(S): White, Asian, Black, and Hispanic patients undergoing ovarian stimulation for IVF. INTERVENTION(S): Self-reported race and ethnicity. MAIN OUTCOME MEASURE(S): The primary outcome was ovarian sensitivity index (OSI), defined as (the number of oocytes retrieved ÷ total gonadotropin dose) × 1,000 as a measure of ovarian responsiveness, adjusting for age, body mass index, infertility diagnosis, and cycle number. Secondary outcomes included live birth and clinical pregnancy after first retrievals, adjusting for age, infertility diagnosis, and history of fibroids, as well as miscarriage rate per clinical pregnancy, adjusting for age, body mass index, infertility diagnosis, duration of infertility, history of fibroids, and use of preimplantation genetic testing for aneuploidy. RESULT(S): The primary analysis of OSI included 3,360 (70.2%) retrievals from White patients, 704 (14.7%) retrievals from Asian patients, 553 (11.6%) retrievals from Black patients, and 168 (3.5%) retrievals from Hispanic patients. Black and Hispanic patients had higher OSIs than White patients after accounting for those with multiple retrievals and adjusting for confounders (6.08 in Black and 6.27 in Hispanic, compared with 5.25 in White). There was no difference in OSI between Asian and White patients. The pregnancy outcomes analyses included 2,299 retrievals. Despite greater ovarian responsiveness, Black and Hispanic patients had lower LBRs compared with White patients, although these differences were not statistically significant after adjusting for confounders (adjusted odds ratio, 0.83; 95% confidence interval [CI], 0.63-1.09, for Black; adjusted odds ratio, 0.93; 95% CI, 0.61-1.43, for Hispanic). Ovarian sensitivity index was modestly predictive of live birth in White and Asian patients but not in Black (area under the curve, 0.51; 95% CI, 0.38-0.64) and Hispanic (area under the curve, 0.50; 95% CI, 0.37-0.63) patients. CONCLUSION(S): Black and Hispanic patients have higher ovarian responsiveness to stimulation during IVF but do not experience a consequent increase in LBR. Factors beyond differences in responsiveness to ovarian stimulation need to be explored to address the racial/ethnic disparity established in prior literature.

Application of a Multiplex Platform to Identify Novel Biomarkers for Pregnancy Location and Viability.

Determining early pregnancy location and viability can be cumbersome, often requiring serial evaluations. This study aimed to identify novel biomarker candidates for pregnancy location and viability using a pseudodiscovery high-throughput technique. This was a case-control study among patients presenting for early pregnancy assessment, including ectopic pregnancies, early pregnancy losses, and viable intrauterine pregnancies. For pregnancy location, ectopic pregnancy was considered "case" and non-ectopic considered "control." For pregnancy viability, viable intrauterine pregnancy was considered "case" and early pregnancy loss + ectopic pregnancy were considered "control." Using Proximity Extension Assay technology from Olink Proteomics, serum levels of 1012 proteins were compared separately for pregnancy location and viability. Receiver operator characteristic curves were generated to determine a biomarker's discriminative abilities. Analysis included 13 ectopic pregnancies, 76 early pregnancy losses, and 27 viable intrauterine pregnancies. For pregnancy location, 18 markers had an area under the curve (AUC) ≥0.80, with three being expressed more in ectopic compared to non-ectopic pregnancies: thyrotropin subunit beta, carbonic anhydrase 3, and DEAD (Asp-Glu-Ala-Asp) box polypeptide 58. For pregnancy viability, two markers had an AUC ≥0.80: lutropin subunit beta and serpin B8. While some of the markers had previously been implicated in early pregnancy physiology, others were from pathways not previously explored. Using a high-throughput platform, a large number of proteins were screened as potential biomarkers for pregnancy location and viability, and twenty candidate biomarkers were identified. Further exploration of these proteins may facilitate validation as diagnostic tools for establishing early pregnancy diagnoses.

Remote IVF: a clinical and laboratory guide to performing remote oocyte retrievals.

The aim of this guide is to describe different scenarios when remote IVF would be needed, considerations around how to plan for the procedure, proper equipment in the procedure room, and proper transportation of oocytes from the procedure room. There are two different scenarios for remote IVF: (1) IVF clinics designed knowing the embryology laboratory is nonadjacent and (2) IVF clinics that routinely provide care to patients in their clinic and want to provide care to those who are ineligible for a retrieval under anesthesia in an outpatient facility. This guide will focus on both scenarios. Much of the advice can be used for IVF clinics that routinely perform oocyte retrievals nonadjacent to their embryology laboratories. Special considerations are needed when patients with complex comorbidities require high-level of care and hospital-level monitoring while under anesthesia and/or post-oocyte retrieval, and are thus unable to be treated in the standard facility. For these reasons we have created a comprehensive guide to nonadjacent, or off-site, oocyte retrievals for reproductive endocrinology and infertility (REI) physicians, nurses, and embryologists to use when planning care for IVF patients. Going forward, we will refer to both these scenarios as remote IVF.

Leveraging electronic health record data for endometriosis research.

Endometriosis is a chronic, complex disease for which there are vast disparities in diagnosis and treatment between sociodemographic groups. Clinical presentation of endometriosis can vary from asymptomatic disease-often identified during (in)fertility consultations-to dysmenorrhea and debilitating pelvic pain. Because of this complexity, delayed diagnosis (mean time to diagnosis is 1.7-3.6 years) and misdiagnosis is common. Early and accurate diagnosis of endometriosis remains a research priority for patient advocates and healthcare providers. Electronic health records (EHRs) have been widely adopted as a data source in biomedical research. However, they remain a largely untapped source of data for endometriosis research. EHRs capture diverse, real-world patient populations and care trajectories and can be used to learn patterns of underlying risk factors for endometriosis which, in turn, can be used to inform screening guidelines to help clinicians efficiently and effectively recognize and diagnose the disease in all patient populations reducing inequities in care. Here, we provide an overview of the advantages and limitations of using EHR data to study endometriosis. We describe the prevalence of endometriosis observed in diverse populations from multiple healthcare institutions, examples of variables that can be extracted from EHRs to enhance the accuracy of endometriosis prediction, and opportunities to leverage longitudinal EHR data to improve our understanding of long-term health consequences for all patients.

Application of a Multiplex Platform to Identify Novel Biomarkers for Pregnancy Location and Viability.

Determining early pregnancy location and viability can be cumbersome, often requiring serial evaluations. This study aimed to identify novel biomarker candidates for pregnancy location and viability using a pseudodiscovery high through-put technique. This was a case-control study among patients presenting for early pregnancy assessment, including ectopic pregnancies, early pregnancy losses, and viable intrauterine pregnancies. For pregnancy location, ectopic pregnancy was considered "case" and non-ectopic considered "control." For pregnancy viability, viable intrauterine pregnancy was considered "case" and early pregnancy loss + ectopic pregnancy were considered "control." Using Proximity Extension Assay technology from Olink Proteomics, serum levels of 1012 proteins were compared separately for pregnancy location and viability. Receiver operator characteristic curves were generated to determine a biomarker's discriminative abilities. Analysis included 13 ectopic pregnancies, 76 early pregnancy losses, and 27 viable intrauterine pregnancies. For pregnancy location, 18 markers had an area under the curve (AUC) ≥ 0.80, with three being expressed more in ectopic compared to non-ectopic pregnancies: thyrotropin subunit beta, carbonic anhydrase 3, and DEAD (Asp-Glu-Ala-Asp) box polypeptide 58. For pregnancy viability, two markers had an AUC ≥ 0.80: lutropin subunit beta and serpin B8. While some of the markers were previously identified as implicated in early pregnancy physiology, others were from pathways not previously explored. Using a high through-put platform, a large number of proteins were screened as potential biomarkers for pregnancy location and viability, and twenty candidate biomarkers were identified. Further exploration of these proteins may facilitate validation as diagnostic tools for establishing early pregnancy diagnoses.

Validation of a multiple marker test for early pregnancy outcome prediction.

PURPOSE: To validate the use of a multiple biomarker test panel for predicting first trimester pregnancy outcome in a multi-center cohort. METHODS: A case-control study of women presenting with pain and bleeding in early pregnancy at 5-10 weeks gestational age was performed at three academic centers. Sera from women with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage (SAB) were analyzed via immunoassay for Activin A (AA), Progesterone (P4), A Disintegrin And Metalloprotease-12 (ADAM12), pregnancy-associated plasma protein A (PAPP-A), glycodelin (Glyc), and human chorionic gonadotropin (hCG). Biomarkers were assessed for reproducibility using medians, ranges, standard deviations, and area under receiver-operating characteristic curve (AUC) and accuracy in early pregnancy outcome classification compared to a previous derivation population. RESULTS: In 192 pregnancies, the biomarkers demonstrated good reproducibility with similar medians, ranges, and AUCs when compared to the derivation population except glycodelin. Pregnancy location was conclusively classified in 53% (n = 94) of the whole study sample with 78% accuracy. Pregnancy viability was conclusively classified in 58% (n = 112) of the new sample with 89% accuracy. Results were similar with subsequent model revisions where glycodelin was excluded and in the subgroups of subjects with a hCG below 2000 mIU/mL and a gestational age less than 6 weeks. CONCLUSION: The use of a panel of biomarkers to maximize test accuracy of a prediction of pregnancy location and prediction of pregnancy viability was reproducible and validated in an external population from which it was derived, but clinical utility is limited based on the test characteristics obtained.

Turner syndrome: fertility counselling in childhood and through the reproductive lifespan.

PURPOSE OF REVIEW: The potential for fertility in Turner syndrome has improved in recent years. Understanding of associated risks and approaches is important for the care of girls and women with this condition. This review focuses on reproductive health, fertility options and appropriate counselling for women with Turner syndrome and their families. RECENT FINDINGS: Women with Turner syndrome have rapidly declining ovarian function beginning in utero . Therefore, counselling regarding fertility concerns should begin at a young age and involve discussion of options, including ovarian tissue cryopreservation, oocyte preservation and use of nonautologous oocytes. Clinical guidance on fertility management and pregnancy risk assessment based on karyotype, associated comorbidities and fertility is still not fully data driven. Realistic expectations regarding reproductive options and associated outcomes as well as the need for multidisciplinary follow-up during pregnancy are crucial to the ethical and safe care of these patients. SUMMARY: Fertility care in women with Turner syndrome is evolving as current management techniques improve and new approaches are validated. Early counselling and active management of fertility preservation is critical to ensure positive and well tolerated reproductive outcomes.

Disrupted methylation patterns at birth persist in early childhood: a prospective cohort analysis.

BACKGROUND: Alterations in the epigenome are a risk factor in multiple disease states. We have demonstrated in the past that disruption of the epigenome during early pregnancy or periconception, as demonstrated by altered methylation, may be associated with both assisted reproductive technology and undesirable clinical outcomes at birth, such as low birth weight. We have previously defined this altered methylation, calculated based on statistical upper and lower limits of outlier CpGs compared to the population, as an 'outlier methylation phenotype' (OMP). Our aim in this study was to determine whether children thus identified as possessing an OMP at birth by DNA methylation in cord blood persist as outliers in early childhood based on salivary DNA methylation. RESULTS: A total of 31 children were included in the analysis. Among 24 children for whom both cord blood DNA and salivary DNA were available, DNA methylation patterns, analyzed using the Illumina Infinium MethylationEPIC BeadChip (850 K), between cord blood at birth and saliva in childhood at age 6-12 years remain stable (R2 range 0.89-0.97). At birth, three out of 28 children demonstrated an OMP in multiple cord blood datasets and hierarchical clustering. Overall DNA methylation among all three OMP children identified as outliers at birth was remarkably stable (individual R2 0.908, 0.92, 0.915), even when only outlier CpG sites were considered (R2 0.694, 0.738, 0.828). CONCLUSIONS: DNA methylation signatures in cord blood remain stable over time as demonstrated by a strong correlation with epigenetic salivary signatures in childhood. Future work is planned to identify whether a clinical phenotype is associated with OMP and, if so, could undesirable clinical outcomes in childhood and adulthood be predicted at birth.

Patient attitudes and preferences for the management of pregnancy of unknown location.

Objective: To understand patient attitudes and preferences when faced with the uncertainty of pregnancy of unknown location (PUL). Design: Qualitative, interview-based study. Setting: University Hosptial. Patients: Patients aged >18 years sampled from the emergency department and a subspecialty fertility practice of a university hospital system. Interventions: Six to 8 weeks after resolution of a PUL, with an ultimate clinical outcome of either an intrauterine pregnancy, spontaneous abortion, or ectopic pregnancy. Participants underwent either surgical, medical, or expectant management. Main Outcome Measures: Thematic analysis of the virtual, semistructured interviews (45-60 minutes in length) conducted with participants to identify commonly expressed priorities was performed. Results: Interviews were completed from October 2020 to March 2021 until thematic saturation was achieved (n = 15). Resolution diagnoses included intrauterine pregnancy (26.7%, n = 4), ectopic pregnancy (40.0%, (n = 6), and spontaneous abortion (33.3%, n = 5). Moreover, 66.7% (n = 10) of the patients presented to the emergency department, whereas 33.3% (n = 5) presented to a subspecialty fertility clinic. All had desired pregnancies. Thematic analyses revealed 4 related priorities around PUL management: health of pregnancy; health of self; future fertility; and diagnostic prediction and diagnostic certainty. The relative balance of these priorities was dynamic and evolved throughout the course of management with different outcomes. A second set of themes related to logistical preferences included mental health support, clarity of treatment and next steps, and continuity of care. Interrater reliability was validated with a pooled κ of >0.8. Limitations include that all participants had desired pregnancies, and the experiences of those who experienced different pregnancy outcomes may have been affected by recall bias. Conclusions: These data demonstrate novel themes around related priorities in patients with desired pregnancies diagnosed with a PUL previously underappreciated by clinicians. The balance of these priorities evolved throughout management with increasing information and clarity. Continually reevaluating relevant patient priorities and preferences is essential to the comprehensive management of PUL.

Embryo cryopreservation leads to sex-specific DNA methylation perturbations in both human and mouse placentas.

In vitro fertilization (IVF) is associated with DNA methylation abnormalities and a higher incidence of adverse pregnancy outcomes. However, which exposure(s), among the many IVF interventions, contributes to these outcomes remains unknown. Frozen embryo transfer (ET) is increasingly utilized as an alternative to fresh ET, but reports suggest a higher incidence of pre-eclampsia and large for gestational age infants. This study examines DNA methylation in human placentas using the 850K Infinium MethylationEPIC BeadChip array obtained after 65 programmed frozen ET cycles, 82 fresh ET cycles and 45 unassisted conceptions. Nine patients provided placentas following frozen and fresh ET from consecutive pregnancies for a paired subgroup analysis. In parallel, eight mouse placentas from fresh and frozen ET were analyzed using the Infinium Mouse Methylation BeadChip array. Human and mouse placentas were significantly hypermethylated after frozen ET compared with fresh. Paired analysis showed similar trends. Sex-specific analysis revealed that these changes were driven by male placentas in humans and mice. Frozen and fresh ET placentas were significantly different from controls, with frozen samples hypermethylated compared with controls driven by males and fresh samples being hypomethylated compared with controls, driven by females. Sexually dimorphic epigenetic changes could indicate differential susceptibility to IVF-associated perturbations, which highlights the importance of sex-specific evaluation of adverse outcomes. Similarities between changes in mice and humans underscore the suitability of the mouse model in evaluating how IVF impacts the epigenetic landscape, which is valuable given limited access to human tissue and the ability to isolate specific interventions in mice.

Impact of the COVID-19 pandemic on the perception of planned oocyte cryopreservation in the United States.

Objective: To assess the impact of the COVID-19 pandemic on attitudes toward planned oocyte cryopreservation (OC). Design: Cross-sectional study. Setting: Internet-based survey questionnaire distributed nationally. Patients: One thousand women aged 21-45 years, stratified by age ≤35 or >35 years. Interventions: None. Main Outcome Measures: Change in the likelihood of considering OC because of the pandemic. Results: Of the participants who reported that the pandemic altered their likelihood of considering OC (15.2%, n = 152), 52.6% (n = 80) reported an increased and 47.3% (n = 72) reported a decreased likelihood of considering OC. Vaccination status did not affect the likelihood of considering OC. In multivariable analysis, history of COVID-19 infection (odds ratio [OR] 1.57; 95% confidence interval [CI] 1.00-2.45), government-subsidized insurance (OR 1.47; 95% CI 0.97-2.21), loss of health insurance because of the pandemic (OR 2.32; 95% CI 1.15-4.66), working more (OR 2.99; 95% CI 1.62-5.51) or less (OR 2.54; 95% CI 1.65-3.90) because of the pandemic, and relationship status (divorced, separated, or widowed [OR 0.44; 95% CI 0.20-0.99]) were significantly associated with a change in the likelihood of considering OC because of the pandemic. Of those who believed that the COVID-19 pandemic influenced their childbearing plans (28.3%, n = 283), 64.0% (n = 181) deferred childbearing and 29.7% (n = 84) expedited childbearing. The pandemic's economic impact, concerns regarding safety of pregnancy/childbirth, and safety of childrearing were cited as most influential on childbearing (67%, 70%, 58%, respectively) and on the likelihood of considering OC (47%, 45%, and 34%, respectively). Conclusions: Through its negative impact on financial security and perceived safety, the COVID-19 pandemic has altered the likelihood of considering OC in >15% of reproductive-aged women and reproductive timelines in 30%. Vaccination has not significantly modified these changes.

Impact of mode of conception on early pregnancy human chorionic gonadotropin rise and birth weight.

Objective: To assess whether the mode of conception and embryo biopsy impact first-trimester human chorionic gonadotropin (hCG) dynamics and subsequent risk of small for gestational age (SGA) or large for gestational age (LGA). Design: Retrospective cohort study. Setting: University fertility center. Patients: Six hundred-two pregnant patients with singleton live births. Interventions: Serial serum hCG measurements were obtained between 10 and 28 days postconception to determine the within-woman rate of change in hCG (slope) by mode of conception (unassisted pregnancy, fresh embryo transfer (ET), frozen ET, and frozen ET following preimplantation genetic testing for aneuploidy (PGT-A). Main Outcome Measures: Primary outcomes included birth weight, SGA, and LGA. Results: Mode of conception is not independently associated with birth weight, SGA, or LGA. Mediation analysis revealed an expected one-day increase in log-transformed hCG varied by mode of conception: unassisted (0.41), fresh ET (0.39), frozen ET (0.42), PGT-A (0.44). Human chorionic gonadotropin rise has a positive effect on birth weight (55 g per SD increase in hCG slope) and is associated with SGA (odds ratio, 0.65), but not with LGA (odds ratio, 1.18). Conclusions: Human chorionic gonadotropin rise is an important mediator of the mode of conception/birth weight relationship. Preimplantation genetic testing for aneuploidy has the highest rate of hCG rise, followed by frozen ET, unassisted, and fresh ET. Faster rise is associated with higher birth weight and lower risk of SGA but does not impact LGA risk. Importantly, PGT-A does not increase the risk of extreme birth weight relative to other modes of conception evaluated.

Proteome-defined changes in cellular pathways for decidua and trophoblast tissues associated with location and viability of early-stage pregnancy.

BACKGROUND: In early pregnancy, differentiating between a normal intrauterine pregnancy (IUP) and abnormal gestations including early pregnancy loss (EPL) or ectopic pregnancy (EP) is a major clinical challenge when ultrasound is not yet diagnostic. Clinical treatments for these outcomes are drastically different making early, accurate diagnosis imperative. Hence, a greater understanding of the biological mechanisms involved in these early pregnancy complications could lead to new molecular diagnostics. METHODS: Trophoblast and endometrial tissue was collected from consenting women having an IUP (n = 4), EPL (n = 4), or EP (n = 2). Samples were analyzed by LC-MS/MS followed by a label-free proteomics analysis in an exploratory study. For each tissue type, pairwise comparisons of different pregnancy outcomes (EPL vs. IUP and EP vs. IUP) were performed, and protein changes having a fold change ≥ 3 and a Student's t-test p-value ≤ 0.05 were defined as significant. Pathway and network classification tools were used to group significantly changing proteins based on their functional similarities. RESULTS: A total of 4792 and 4757 proteins were identified in decidua and trophoblast proteomes. For decidua, 125 protein levels (2.6% of the proteome) were significantly different between EP and IUP, whereas EPL and IUP decidua were more similar with only 68 (1.4%) differences. For trophoblasts, there were 66 (1.4%) differences between EPL and IUP. However, the largest group of 344 differences (7.2%) was observed between EP and IUP trophoblasts. In both tissues, proteins associated with ECM remodeling, cell adhesion and metabolic pathways showed decreases in EP specimens compared with IUP and EPL. In trophoblasts, EP showed elevation of inflammatory and immune response pathways. CONCLUSIONS: Overall, differences between an EP and IUP are greater than the changes observed when comparing ongoing IUP and nonviable intrauterine pregnancies (EPL) in both decidua and trophoblast proteomes. Furthermore, differences between EP and IUP were much higher in the trophoblast than in the decidua. This observation is true for the total number of protein changes as well as the extent of changes in upstream regulators and related pathways. This suggests that biomarkers and mechanisms of trophoblast function may be the best predictors of early pregnancy location and viability.

Effect of an Active vs Expectant Management Strategy on Successful Resolution of Pregnancy Among Patients With a Persisting Pregnancy of Unknown Location: The ACT or NOT Randomized Clinical Trial.

Importance: Women with an early nonviable pregnancy of unknown location are at high risk of ectopic pregnancy and its inherent morbidity and mortality. Successful and timely resolution of the gestation, while minimizing unscheduled interventions, are important priorities. Objective: To determine if active management is more effective in achieving pregnancy resolution than expectant management and whether the use of empirical methotrexate is noninferior to uterine evacuation followed by methotrexate if needed. Design, Setting, and Participants: This multicenter randomized clinical trial recruited 255 hemodynamically stable women with a diagnosed persisting pregnancy of unknown location between July 25, 2014, and June 4, 2019, in 12 medical centers in the United States (final follow up, August 19, 2019). Interventions: Eligible patients were randomized in a 1:1:1 ratio to expectant management (n = 86), active management with uterine evacuation followed by methotrexate if needed (n = 87), or active management with empirical methotrexate using a 2-dose protocol (n = 82). Main Outcomes and Measures: The primary outcome was successful resolution of the pregnancy without change from initial strategy. The primary hypothesis tested for superiority of the active groups combined vs expectant management, and a secondary hypothesis tested for noninferiority of empirical methotrexate compared with uterine evacuation with methotrexate as needed using a noninferiority margin of -12%. Results: Among 255 patients who were randomized (median age, 31 years; interquartile range, 27-36 years), 253 (99.2%) completed the trial. Ninety-nine patients (39%) declined their randomized allocation (26.7% declined expectant management, 48.3% declined uterine evacuation, and 41.5% declined empirical methotrexate) and crossed over to a different group. Compared with patients randomized to receive expectant management (n = 86), women randomized to receive active management (n = 169) were significantly more likely to experience successful pregnancy resolution without change in their initial management strategy (51.5% vs 36.0%; difference, 15.4% [95% CI, 2.8% to 28.1%]; rate ratio, 1.43 [95% CI, 1.04 to 1.96]). Among active management strategies, empirical methotrexate was noninferior to uterine evacuation followed by methotrexate if needed with regard to successful pregnancy resolution without change in management strategy (54.9% vs 48.3%; difference, 6.6% [1-sided 97.5% CI, -8.4% to ∞]). The most common adverse event was vaginal bleeding for all of the 3 management groups (44.2%-52.9%). Conclusions and Relevance: Among patients with a persisting pregnancy of unknown location, patients randomized to receive active management, compared with those randomized to receive expectant management, more frequently achieved successful pregnancy resolution without change from the initial management strategy. The substantial crossover between groups should be considered when interpreting the results. Trial Registration: ClinicalTrials.gov Identifier: NCT02152696.