Compromised SARS-CoV-2-specific placental antibody transfer.

SARS-CoV-2 infection causes more severe disease in pregnant women compared to age-matched non-pregnant women. Whether maternal infection causes changes in the transfer of immunity to infants remains unclear. Maternal infections have previously been associated with compromised placental antibody transfer, but the mechanism underlying this compromised transfer is not established. Here, we used systems serology to characterize the Fc profile of influenza-, pertussis-, and SARS-CoV-2-specific antibodies transferred across the placenta. Influenza- and pertussis-specific antibodies were actively transferred. However, SARS-CoV-2-specific antibody transfer was significantly reduced compared to influenza- and pertussis-specific antibodies, and cord titers and functional activity were lower than in maternal plasma. This effect was only observed in third-trimester infection. SARS-CoV-2-specific transfer was linked to altered SARS-CoV-2-antibody glycosylation profiles and was partially rescued by infection-induced increases in IgG and increased FCGR3A placental expression. These results point to unexpected compensatory mechanisms to boost immunity in neonates, providing insights for maternal vaccine design.

Aspiring toward equitable benefits from genomic advances to individuals of ancestrally diverse backgrounds.

Advancements in genomic technologies have shown remarkable promise for improving health trajectories. The Human Genome Project has catalyzed the integration of genomic tools into clinical practice, such as disease risk assessment, prenatal testing and reproductive genomics, cancer diagnostics and prognostication, and therapeutic decision making. Despite the promise of genomic technologies, their full potential remains untapped without including individuals of diverse ancestries and integrating social determinants of health (SDOHs). The NHGRI launched the 2020 Strategic Vision with ten bold predictions by 2030, including "individuals from ancestrally diverse backgrounds will benefit equitably from advances in human genomics." Meeting this goal requires a holistic approach that brings together genomic advancements with careful consideration to healthcare access as well as SDOHs to ensure that translation of genetics research is inclusive, affordable, and accessible and ultimately narrows rather than widens health disparities. With this prediction in mind, this review delves into the two paramount applications of genetic testing-reproductive genomics and precision oncology. When discussing these applications of genomic advancements, we evaluate current accessibility limitations, highlight challenges in achieving representativeness, and propose paths forward to realize the ultimate goal of their equitable applications.

Risk of Autism after Prenatal Topiramate, Valproate, or Lamotrigine Exposure.

BACKGROUND: Maternal use of valproate during pregnancy has been associated with an increased risk of neurodevelopmental disorders in children. Although most studies of other antiseizure medications have not shown increased risks of these disorders, there are limited and conflicting data regarding the risk of autism spectrum disorder associated with maternal topiramate use. METHODS: We identified a population-based cohort of pregnant women and their children within two health care utilization databases in the United States, with data from 2000 through 2020. Exposure to specific antiseizure medications was defined on the basis of prescription fills from gestational week 19 until delivery. Children who had been exposed to topiramate during the second half of pregnancy were compared with those unexposed to any antiseizure medication during pregnancy with respect to the risk of autism spectrum disorder. Valproate was used as a positive control, and lamotrigine was used as a negative control. RESULTS: The estimated cumulative incidence of autism spectrum disorder at 8 years of age was 1.9% for the full population of children who had not been exposed to antiseizure medication (4,199,796 children). With restriction to children born to mothers with epilepsy, the incidence was 4.2% with no exposure to antiseizure medication (8815 children), 6.2% with exposure to topiramate (1030 children), 10.5% with exposure to valproate (800 children), and 4.1% with exposure to lamotrigine (4205 children). Propensity score-adjusted hazard ratios in a comparison with no exposure to antiseizure medication were 0.96 (95% confidence interval [CI], 0.56 to 1.65) for exposure to topiramate, 2.67 (95% CI, 1.69 to 4.20) for exposure to valproate, and 1.00 (95% CI, 0.69 to 1.46) for exposure to lamotrigine. CONCLUSIONS: The incidence of autism spectrum disorder was higher among children prenatally exposed to the studied antiseizure medications than in the general population. However, after adjustment for indication and other confounders, the association was substantially attenuated for topiramate and lamotrigine, whereas an increased risk remained for valproate. (Funded by the National Institute of Mental Health.).

Buprenorphine versus Methadone for Opioid Use Disorder in Pregnancy.

BACKGROUND: Opioid agonist therapy is strongly recommended for pregnant persons with opioid use disorder. Buprenorphine may be associated with more favorable neonatal and maternal outcomes than methadone, but existing data are limited. METHODS: We conducted a cohort study involving pregnant persons who were enrolled in public insurance programs in the United States during the period from 2000 through 2018 in which we examined outcomes among those who received buprenorphine as compared with those who received methadone. Exposure to the two medications was assessed in early pregnancy (through gestational week 19), late pregnancy (gestational week 20 through the day before delivery), and the 30 days before delivery. Risk ratios for neonatal and maternal outcomes were adjusted for confounders with the use of propensity-score overlap weights. RESULTS: The data source for the study consisted of 2,548,372 pregnancies that ended in live births. In early pregnancy, 10,704 pregnant persons were exposed to buprenorphine and 4387 to methadone. In late pregnancy, 11,272 were exposed to buprenorphine and 5056 to methadone (9976 and 4597, respectively, in the 30 days before delivery). Neonatal abstinence syndrome occurred in 52.0% of the infants who were exposed to buprenorphine in the 30 days before delivery as compared with 69.2% of those exposed to methadone (adjusted relative risk, 0.73; 95% confidence interval [CI], 0.71 to 0.75). Preterm birth occurred in 14.4% of infants exposed to buprenorphine in early pregnancy and in 24.9% of those exposed to methadone (adjusted relative risk, 0.58; 95% CI, 0.53 to 0.62); small size for gestational age in 12.1% and 15.3%, respectively (adjusted relative risk, 0.72; 95% CI, 0.66 to 0.80); and low birth weight in 8.3% and 14.9% (adjusted relative risk, 0.56; 95% CI, 0.50 to 0.63). Delivery by cesarean section occurred in 33.6% of pregnant persons exposed to buprenorphine in early pregnancy and 33.1% of those exposed to methadone (adjusted relative risk, 1.02; 95% CI, 0.97 to 1.08), and severe maternal complications developed in 3.3% and 3.5%, respectively (adjusted relative risk, 0.91; 95% CI, 0.74 to 1.13). Results of exposure in late pregnancy were consistent with results of exposure in early pregnancy. CONCLUSIONS: The use of buprenorphine in pregnancy was associated with a lower risk of adverse neonatal outcomes than methadone use; however, the risk of adverse maternal outcomes was similar among persons who received buprenorphine and those who received methadone. (Funded by the National Institute on Drug Abuse.).

Development and validation of claims-based algorithms for estimating gestational age of spontaneous abortion and termination.

To study the risk of spontaneous abortion (SAB) or termination using healthcare utilization databases, algorithms to estimate the gestational age (GA) are needed. Using Medicaid data, we developed a hierarchical algorithm to classify pregnancy outcomes. We identified the subset of potential SAB and termination cases, and abstracted the GA from linked electronic medical records (gold standard). We developed three approaches: (1) assign median GA for SAB and termination cases in the US; (2) draw a random GA from the population distributions; (3) estimate GA based on regression models. Algorithm performance was assessed based on the proportion of pregnancies with estimated GA within 1-4 weeks of the gold standard, the mean squared error (MSE) and the R-squared. Approach 1 and Approach 3 had similar performance, though approach 3 using random forest models with variables selected via the Boruta algorithm had better MSE and R-squared. For SAB, 58.0% of pregnancies were correctly classified within 2 weeks of the gold standard (MSE: 8.7, R-squared: 0.09). For termination, the proportions were 66.3% (MSE: 11.7; R-squared: 0.35). SABs and terminations can be studied in healthcare utilization data with careful implementation of validated algorithms though higher level of GA misclassification is expected compared to live births.

Hierarchical Clustering Analysis to Inform Classification of Congenital Malformations for Surveillance of Medication Safety in Pregnancy.

There is growing interest in the secondary use of healthcare data to evaluate medication safety in pregnancy. Tree-based scan statistics (TBSS) offer an innovative approach to help identify potential safety signals. TBSS utilize hierarchically organized outcomes, generally based on existing clinical coding systems that group outcomes by organ system. When assessing teratogenicity, such groupings often lack a sound embryologic basis given the etiologic heterogeneity of congenital malformations. The study objective was to enhance the grouping of congenital malformations to be used in scanning approaches through implementation of hierarchical clustering analysis (HCA) and to pilot test an HCA-enhanced TBSS approach for medication safety surveillance in pregnancy in two test cases using >4.2 million mother-child dyads from two US-nationwide databases. HCA identified (1) malformation combinations belonging to the same organ system already grouped in existing classifications, (2) known combinations across different organ systems not previously grouped, (3) unknown combinations not previously grouped, and (4) malformations seemingly standing on their own. Testing the approach with valproate and topiramate identified expected signals, and a signal for an HCA-cluster missed by traditional classification. Augmenting existing classifications with clusters identified through large data exploration may be promising when defining phenotypes for surveillance and causal inference studies.

Consequences of collagen induced inflammatory arthritis on circadian regulation of the gut microbiome.

The gut microbiota is important for host health and immune system function. Moreover autoimmune diseases, such as rheumatoid arthritis, are associated with significant gut microbiota dysbiosis, although the causes and consequences of this are not fully understood. It has become clear that the composition and metabolic outputs of the microbiome exhibit robust 24 h oscillations, a result of daily variation in timing of food intake as well as rhythmic circadian clock function in the gut. Here, we report that experimental inflammatory arthritis leads to a re-organization of circadian rhythmicity in both the gut and associated microbiome. Mice with collagen induced arthritis exhibited extensive changes in rhythmic gene expression in the colon, and reduced barrier integrity. Re-modeling of the host gut circadian transcriptome was accompanied by significant alteration of the microbiota, including widespread loss of rhythmicity in symbiont species of Lactobacillus, and alteration in circulating microbial derived factors, such as tryptophan metabolites, which are associated with maintenance of barrier function and immune cell populations within the gut. These findings highlight that altered circadian rhythmicity during inflammatory disease contributes to dysregulation of gut integrity and microbiome function.

Prescription medication use during pregnancy in the United States from 2011 to 2020: trends and safety evidence.

BACKGROUND: Medication use during pregnancy has increased in the United States despite the lack of safety data for many medications. OBJECTIVE: This study aimed to inform research priorities by examining trends in medication use during pregnancy and identifying gaps in safety information on the most commonly prescribed medications. STUDY DESIGN: We identified population-based cohorts of commercially (MarketScan 2011-2020) and publicly (Medicaid Analytic eXtract/Transformed Medicaid Statistical Information System Analytic Files 2011-2018) insured pregnancies ending in live birth from 2 health care utilization databases. Medication use was based on filled prescriptions between the date of last menstrual period through delivery, as well as the period before the last menstrual period and during specific trimesters. We also included a cross-sectional representative sample of pregnancies ascertained by the National Health and Nutrition Examination Survey (2011-2020), with information on prescription medication use during the preceding month obtained through maternal interviews. Teratogen Information System was used to classify the available evidence on teratogenic risk. RESULTS: Among over 3 million pregnancies, the medications most commonly dispensed at any time during pregnancy were analgesics, antibiotics, and antiemetics. The top medications were ondansetron (16.8%), amoxicillin (13.5%), and azithromycin (12.4%) in MarketScan, nitrofurantoin (22.2%), acetaminophen (21.3%; mostly as part of acetaminophen-hydrocodone products), and ondansetron (19.5%) in Medicaid Analytic eXtract/Transformed Medicaid Statistical Information System Analytic Files, and levothyroxine (5.0%), sertraline (2.9%), and insulin (2.9%) in the National Health and Nutrition Examination Survey group. The most commonly dispensed suspected teratogens during the first trimester were antithyroid medications. The use of antidiabetic and psychotropic medications has continued to increase in the United States during the last decade, opioid dispensation has decreased by half, and antibiotics and antiemetics continue to be common. For one-quarter of medications, there is insufficient evidence available to characterize their safety profile in pregnancy. CONCLUSION: There is a need for more drug research in pregnant patients. Future research should focus on anti-infectives with high utilization and limited level of evidence on safety for use during pregnancy. Although lack of evidence is not evidence of safety concerns, it does not indicate risk either. In many instances, the benefits outweigh the risks when these medications are used clinically, and some of the medications with no proven safety may be necessary to treat patients.

Deep survival analysis for interpretable time-varying prediction of preeclampsia risk.

OBJECTIVE: Survival analysis is widely utilized in healthcare to predict the timing of disease onset. Traditional methods of survival analysis are usually based on Cox Proportional Hazards model and assume proportional risk for all subjects. However, this assumption is rarely true for most diseases, as the underlying factors have complex, non-linear, and time-varying relationships. This concern is especially relevant for pregnancy, where the risk for pregnancy-related complications, such as preeclampsia, varies across gestation. Recently, deep learning survival models have shown promise in addressing the limitations of classical models, as the novel models allow for non-proportional risk handling, capturing nonlinear relationships, and navigating complex temporal dynamics. METHODS: We present a methodology to model the temporal risk of preeclampsia during pregnancy and investigate the associated clinical risk factors. We utilized a retrospective dataset including 66,425 pregnant individuals who delivered in two tertiary care centers from 2015 to 2023. We modeled the preeclampsia risk by modifying DeepHit, a deep survival model, which leverages neural network architecture to capture time-varying relationships between covariates in pregnancy. We applied time series k-means clustering to DeepHit's normalized output and investigated interpretability using Shapley values. RESULTS: We demonstrate that DeepHit can effectively handle high-dimensional data and evolving risk hazards over time with performance similar to the Cox Proportional Hazards model, achieving an area under the curve (AUC) of 0.78 for both models. The deep survival model outperformed traditional methodology by identifying time-varied risk trajectories for preeclampsia, providing insights for early and individualized intervention. K-means clustering resulted in patients delineating into low-risk, early-onset, and late-onset preeclampsia groups-notably, each of those has distinct risk factors. CONCLUSION: This work demonstrates a novel application of deep survival analysis in time-varying prediction of preeclampsia risk. Our results highlight the advantage of deep survival models compared to Cox Proportional Hazards models in providing personalized risk trajectory and demonstrating the potential of deep survival models to generate interpretable and meaningful clinical applications in medicine.

Comparative Safety of In Utero Exposure to Buprenorphine Combined With Naloxone vs Buprenorphine Alone.

Importance: Buprenorphine combined with naloxone is commonly used to treat opioid use disorders outside of pregnancy. In pregnancy, buprenorphine alone is generally recommended because of limited perinatal safety data on the combination product. Objective: To compare perinatal outcomes following prenatal exposure to buprenorphine with naloxone vs buprenorphine alone. Design, Settings, and Participants: Population-based cohort study using health care utilization data from Medicaid-insured beneficiaries in the US from 2000 to 2018. The cohort was restricted to pregnant individuals linked to their liveborn infants, with maternal Medicaid enrollment from 3 months before pregnancy to 1 month after delivery and infant enrollment for the first 3 months after birth, unless they died sooner. Exposure: Use of buprenorphine with naloxone vs buprenorphine alone during the first trimester based on outpatient dispensings. Main Outcomes and Measures: Outcomes included major congenital malformations, low birth weight, neonatal abstinence syndrome, neonatal intensive care unit admission, preterm birth, respiratory symptoms, small for gestational age, cesarean delivery, and maternal morbidity. Confounder-adjusted risk ratios were calculated using propensity score overlap weights. Results: This study identified 3369 pregnant individuals exposed to buprenorphine with naloxone during the first trimester (mean [SD] age, 28.8 [4.6] years) and 5326 exposed to buprenorphine alone or who switched from the combination to buprenorphine alone by the end of the first trimester (mean [SD] age, 28.3 [4.5] years). When comparing buprenorphine combined with naloxone with buprenorphine alone, a lower risk for neonatal abstinence syndrome (absolute risk, 37.4% vs 55.8%; weighted relative risk, 0.77 [95% CI, 0.70-0.84]) and a modestly lower risk for neonatal intensive care unit admission (absolute risk, 30.6% vs 34.9%; weighted relative risk, 0.91 [95% CI, 0.85-0.98]) and small for gestational age (absolute risk, 10.0% vs 12.4%; weighted relative risk, 0.86 [95% CI, 0.75-0.98]) was observed. For maternal morbidity, the comparative rates were 2.6% vs 2.9%, respectively, and the weighted relative risk was 0.90 (95% CI, 0.68-1.19). No differences were observed with respect to major congenital malformations overall, low birth weight, preterm birth, respiratory symptoms, or cesarean delivery. Results were consistent across sensitivity analyses. Conclusions and Relevance: There were similar and, in some instances, more favorable neonatal and maternal outcomes for pregnancies exposed to buprenorphine combined with naloxone compared with buprenorphine alone. For the outcomes assessed, compared with buprenorphine alone, buprenorphine with naloxone during pregnancy appears to be a safe treatment option. This supports the view that both formulations are reasonable options for the treatment of opioid use disorder in pregnancy, affirming flexibility in collaborative treatment decision-making.

Placental Origins of Preeclampsia: Insights from Multi-Omic Studies.

Preeclampsia (PE) is a major cause of maternal and neonatal morbidity and mortality worldwide, with the placenta playing a central role in disease pathophysiology. This review synthesizes recent advancements in understanding the molecular mechanisms underlying PE, focusing on placental genes, proteins, and genetic variants identified through multi-omic approaches. Transcriptomic studies in bulk placental tissue have identified many dysregulated genes in the PE placenta, including the PE signature gene, Fms-like tyrosine kinase 1 (FLT1). Emerging single-cell level transcriptomic data have revealed key cell types and molecular signatures implicated in placental dysfunction and PE. However, the considerable variability among studies underscores the need for standardized methodologies and larger sample sizes to enhance the reproducibility of results. Proteomic profiling of PE placentas has identified numerous PE-associated proteins, offering insights into potential biomarkers and pathways implicated in PE pathogenesis. Despite significant progress, challenges such as inconsistencies in study findings and lack of validation persist. Recent fetal genome-wide association studies have identified multiple genetic loci associated with PE, with ongoing efforts to elucidate their impact on placental gene expression and function. Future directions include the integration of multi-omic data, validation of findings in diverse PE populations and clinical subtypes, and the development of analytical approaches and experimental models to study the complex interplay of placental and maternal factors in PE etiology. These insights hold promise for improving risk prediction, diagnosis, and management of PE, ultimately reducing its burden on maternal and neonatal health.

Development and Validation of Algorithms to Estimate Live Birth Gestational Age in Medicaid Analytic eXtract Data.

BACKGROUND: While healthcare utilization data are useful for postmarketing surveillance of drug safety in pregnancy, the start of pregnancy and gestational age at birth are often incompletely recorded or missing. Our objective was to develop and validate a claims-based live birth gestational age algorithm. METHODS: Using the Medicaid Analytic eXtract (MAX) linked to birth certificates in three states, we developed four candidate algorithms based on: preterm codes; preterm or postterm codes; timing of prenatal care; and prediction models - using conventional regression and machine-learning approaches with a broad range of prespecified and empirically selected predictors. We assessed algorithm performance based on mean squared error (MSE) and proportion of pregnancies with estimated gestational age within 1 and 2 weeks of the gold standard, defined as the clinical or obstetric estimate of gestation on the birth certificate. We validated the best-performing algorithms against medical records in a nationwide sample. We quantified misclassification of select drug exposure scenarios due to estimated gestational age as positive predictive value (PPV), sensitivity, and specificity. RESULTS: Among 114,117 eligible pregnancies, the random forest model with all predictors emerged as the best performing algorithm: MSE 1.5; 84.8% within 1 week and 96.3% within 2 weeks, with similar performance in the nationwide validation cohort. For all exposure scenarios, PPVs were >93.8%, sensitivities >94.3%, and specificities >99.4%. CONCLUSIONS: We developed a highly accurate algorithm for estimating gestational age among live births in the nationwide MAX data, further supporting the value of these data for drug safety surveillance in pregnancy. See video abstract at, http://links.lww.com/EDE/B989 .

COVID-19 booster dose induces robust antibody response in pregnant, lactating, and nonpregnant women.

BACKGROUND: Although emerging data during the SARS-CoV-2 pandemic have demonstrated robust messenger RNA vaccine-induced immunogenicity across populations, including pregnant and lactating individuals, the rapid waning of vaccine-induced immunity and the emergence of variants of concern motivated the use of messenger RNA vaccine booster doses. Whether all populations, including pregnant and lactating individuals, will mount a comparable response to a booster dose is not known. OBJECTIVE: This study aimed to profile the humoral immune response to a COVID-19 messenger RNA booster dose in a cohort of pregnant, lactating, and nonpregnant age-matched women. STUDY DESIGN: This study characterized the antibody response against ancestral Spike and Omicron in a cohort of 31 pregnant, 12 lactating, and 20 nonpregnant age-matched controls who received a BNT162b2 or messenger RNA-1273 booster dose after primary COVID-19 vaccination. In addition, this study examined the vaccine-induced antibody profiles of 15 maternal-to-cord dyads at delivery. RESULTS: Receiving a booster dose during pregnancy resulted in increased immunoglobulin G1 levels against Omicron Spike (postprimary vaccination vs postbooster dose; P=.03). Pregnant and lactating individuals exhibited equivalent Spike-specific total immunoglobulin G1, immunoglobulin M, and immunoglobulin A levels and neutralizing titers against Omicron compared with nonpregnant women. Subtle differences in Fc receptor binding and antibody subclass profiles were observed in the immune response to a booster dose in pregnant vs nonpregnant individuals. The analysis of maternal and cord antibody profiles at delivery demonstrated equivalent total Spike-specific immunoglobulin G1 in maternal and cord blood, yet higher Spike-specific FcγR3a-binding antibodies in the cord relative to maternal blood (P=.002), consistent with the preferential transfer of highly functional immunoglobulin. Spike-specific immunoglobulin G1 levels in the cord were positively correlated with the time elapsed since receiving the booster dose (Spearman R, .574; P=.035). CONCLUSION: Study data suggested that receiving a booster dose during pregnancy induces a robust Spike-specific humoral immune response, including against Omicron. If boosting occurs in the third trimester of pregnancy, higher Spike-specific cord immunoglobulin G1 levels are achieved with greater time elapsed between receiving the booster and delivery. Receiving a booster dose has the potential to augment maternal and neonatal immunity.

Validation of parental recall questionnaire to classify preterm delivery subtypes: Spontaneous preterm labour, preterm premature rupture of membranes and clinician-initiated preterm delivery.

BACKGROUND: Preterm delivery (PTD) includes three main presenting subtypes: spontaneous preterm labour (sPTL), preterm premature rupture of membranes (pPROM) and clinician-initiated preterm delivery (ciPTD). PTD subtype data are rarely available from birth registries and are onerous to derive from medical records. OBJECTIVES: To develop and test the validity of a questionnaire to classify PTD subtype based on birthing parent recall of labour and delivery events. METHODS: The questionnaire was sent in 2022 to 581 patients with PTD history documented in the LIFECODES study, a hospital-based birth cohort in Boston, Massachusetts. Eighty-two respondents reported 94 PTDs that could be linked to medical records. Data on PTD subtype were extracted from medical records as the reference standard. RESULTS: Medical records indicated 47 spontaneous (24 sPTL, 23 pPROM) and 47 ciPTD deliveries occurring a median eight years earlier. The sensitivity and specificity of the recall questionnaire were 88% (95% confidence interval: 68, 97%) and 89% (79, 95%) for sPTL; 96% (78, 100%) and 94% (86, 98%) for pPROM; and 83% (69, 92%) and 100% (92, 100%) for ciPTD, respectively. Greater time since pregnancy did not degrade the sensitivity or specificity of the parental recall questionnaire. CONCLUSIONS: Although derived from a modest sample, the moderate-to-high sensitivity and specificity of the parental recall questionnaire to classify sPTL, pPROM and ciPTD demonstrates its potential for large studies of PTD and for correction of misclassification bias. Future studies are required to test the questionnaire in a variety of populations.

Validation of claims-based algorithms to identify non-live birth outcomes.

PURPOSE: Perinatal epidemiology studies using healthcare utilization databases are often restricted to live births, largely due to the lack of established algorithms to identify non-live births. The study objective was to develop and validate claims-based algorithms for the ascertainment of non-live births. METHODS: Using the Mass General Brigham Research Patient Data Registry 2000-2014, we assembled a cohort of women enrolled in Medicaid with a non-live birth. Based on ≥1 inpatient or ≥2 outpatient diagnosis/procedure codes, we identified and randomly sampled 100 potential stillbirth, spontaneous abortion, and termination cases each. For the secondary definitions, we excluded cases with codes for other pregnancy outcomes within ±5 days of the outcome of interest and relaxed the definitions for spontaneous abortion and termination by allowing cases with one outpatient diagnosis only. Cases were adjudicated based on medical chart review. We estimated the positive predictive value (PPV) for each outcome. RESULTS: The PPV was 71.0% (95% CI, 61.1-79.6) for stillbirth; 79.0% (69.7-86.5) for spontaneous abortion, and 93.0% (86.1-97.1) for termination. When excluding cases with adjacent codes for other pregnancy outcomes and further relaxing the definition, the PPV increased to 80.6% (69.5-88.9) for stillbirth, 86.6% (80.5-91.3) for spontaneous abortion and 94.9% (91.1-97.4) for termination. The PPV for the composite outcome using the relaxed definition was 94.4% (92.3-96.1). CONCLUSIONS: Our findings suggest non-live birth outcomes can be identified in a valid manner in epidemiological studies based on healthcare utilization databases.

Postnatal genetic testing on cord blood for prenatally identified high-probability cases.

OBJECTIVE: To evaluate the utility of postnatal genetic testing on umbilical cord blood (CB) for prenatally identified high-probability fetuses. METHOD: CB for genetic testing was offered to individuals who met one of the following criteria: (i) fetal anomaly, (ii) positive non-invasive prenatal screening by cfDNA or biochemical analysis, or (iii) family history. Individuals with diagnostic testing, but not microarray, were also included when recommended by society guidelines. CB was collected at Brigham and Women's and Emerson Hospitals between 2016 and 2021. RESULTS: 448 individuals consented for cord blood testing (370 (82.6%) for fetal anomalies, 51 (11.4%) for high-probability cfDNA, and 27 (6.0%) for family history) and a total of 393 (87.7%) samples were analyzed. Genetic testing yielded a diagnosis in 92 (23.4%) neonates by karyotype (n = 37), chromosomal microarray (CMA) (n = 32), and other molecular analysis (n = 23). Testing averaged 10.3 days (range 1-118 days). 68 (73.9%) diagnoses potentially impacted neonatal management. MCC could not be definitively excluded in only 1.4% (6/418) of samples. CONCLUSION: Prenatal identification of high-probability fetuses and genetic testing on CB facilitates timely genetic diagnoses and neonatal management. Testing provides reassurance and reduces a postnatal diagnostic odyssey for high-probability neonates.

Single gene non-invasive prenatal screening for autosomal dominant conditions in a high-risk cohort.

PURPOSE: To determine the utility of single gene non-invasive prenatal screening (NIPS-SGD) in a high-risk reproductive genetics clinic. METHODS: A clinical pilot for NIPS-SGD was conducted from March 2020 to November 2021. A NIPS-SGD panel assessing pathogenic variants in 30 genes was offered to pregnant individuals for the following indications: (1) advanced sperm age ≥40 years, (2) nuchal translucency (NT) ≥ 3.5 mm, (3) fetal anomaly, or (4) family history of a condition covered by the panel. Diagnostic testing was offered concurrently. RESULTS: NIPS-SGD was ordered for 253 individuals: 88 (34.8%) for fetal anomalies, 96 (37.9%) for advanced sperm age, 37 (14.6%) for increased NT, and 5 (2.0%) for family history. Among 228 (90.1%) completed tests, 8 (3.5%) were positive. Diagnostic testing for 78 individuals revealed no false positive or negative results. Of 41 (25.9%) individuals who received a molecular diagnosis, 34 (82.9%) were outside the scope of NIPS-SGD. Positive NIPS-SGD altered medical management in five cases. CONCLUSIONS: NIPS-SGD in a high-risk population can lead to earlier prenatal diagnosis, enhanced surveillance, and targeted genetic analysis, but should not replace clinically indicated diagnostic testing. Potential incidental findings include parental diagnoses and misattributed parentage.

Trajectories of Prescription Opioid Utilization During Pregnancy Among Prepregnancy Chronic Users and Risk of Neonatal Opioid Withdrawal Syndrome.

Little is known about the impact of dose, duration, and timing of prenatal prescription opioid exposure on the risk of neonatal opioid withdrawal syndrome (NOWS). Using a cohort of 18,869 prepregnancy chronic opioid users nested within the 2000-2014 Medicaid Analytic eXtract, we assessed average opioid dosage within biweekly gestational age intervals, created group-based trajectory models, and evaluated the association between trajectory groups and NOWS risk. Women were grouped into 6 distinct opioid use trajectories which, based on observed patterns, were categorized as 1) continuous very low-dose use, 2) continuous low-dose use, 3) initial moderate-dose use with a gradual decrease to very low-dose/no use, 4) initial high-dose use with a gradual decrease to very low-dose use, 5) continuous moderate-dose use, and 6) continuous high-dose use. Absolute risk of NOWS per 1,000 infants was 7.7 for group 1 (reference group), 28.8 for group 2 (relative risk (RR) = 3.7, 95% confidence interval (CI): 2.8, 5.0), 16.5 for group 3 (RR = 2.1, 95% CI: 1.5, 3.1), 64.9 for group 4 (RR = 8.4, 95% CI: 5.6, 12.6), 77.3 for group 5 (RR = 10.0, 95% CI: 7.5, 13.5), and 172.4 for group 6 (RR = 22.4, 95% CI: 16.1, 31.2). Trajectory models-which capture information on dose, duration, and timing of exposure-are useful for gaining insight into clinically relevant groupings to evaluate the risk of prenatal opioid exposure.

Colonoscopist Performance and Colorectal Cancer Risk After Adenoma Removal to Stratify Surveillance: Two Nationwide Observational Studies.

BACKGROUND AND AIMS: Colonoscopy surveillance after adenoma removal is an increasing burden in many countries. Surveillance recommendations consider characteristics of removed adenomas, but not colonoscopist performance. We investigated the impact of colonoscopist performance on colorectal cancer risk after adenoma removal. METHODS: We compared colorectal cancer risk after removal of high-risk adenomas, low-risk adenomas, and after negative colonoscopy for all colonoscopies performed by colonoscopists with low vs high performance quality (adenoma detection rate <20% vs ≥20%) in the Polish screening program between 2000 and 2011, with follow-up until 2017. Findings were validated in the Austrian colonoscopy screening program. RESULTS: A total of 173,288 Polish colonoscopies were included in the study. Of 262 colonoscopists, 160 (61.1%) were low performers, and 102 (38.9%) were high performers; 11.1% of individuals had low-risk and 6.6% had high-risk adenomas removed at screening; 82.2% had no adenomas. During 10 years of follow-up, 443 colorectal cancers were diagnosed. For low-risk adenoma individuals, colorectal cancer incidence was 0.55% (95% confidence interval [CI] 0.40-0.75) with low-performing colonoscopists vs 0.22% (95% CI 0.14-0.34) with high-performing colonoscopists (hazard ratio [HR] 2.35; 95% CI 1.31-4.21; P = .004). For individuals with high-risk adenomas, colorectal cancer incidence was 1.14% (95% CI 0.87-1.48) with low-performing colonoscopists vs 0.43% (95% CI 0.27-0.69) with high-performing colonoscopists (HR 2.69; 95% CI 1.62-4.47; P < .001). After negative colonoscopy, colorectal cancer incidence was 0.30% (95% CI 0.27-0.34) for individuals examined by low-performing colonoscopists, vs 0.15% (95% CI 0.11-0.20) for high-performing (HR 2.10; 95% CI 1.52-2.91; P < .001). The observed trends were reproduced in the Austrian validation cohort. CONCLUSIONS: Our results suggest that endoscopist performance may be an important contributor in addition to polyp characteristics in determining colorectal cancer risk after colonoscopy screening.

Preserved recognition of Omicron spike following COVID-19 messenger RNA vaccination in pregnancy.

BACKGROUND: SARS-CoV-2 infection is associated with enhanced disease severity in pregnant women. Despite the potential of COVID-19 vaccines to reduce severe disease, vaccine uptake remained relatively low among pregnant women. Just as coordinated messaging from the Centers for Disease Control and Prevention and leading obstetrics organizations began to increase vaccine confidence in this vulnerable group, the evolution of SARS-CoV-2 variants of concerns, including the Omicron variant, raised new concerns about vaccine efficacy because of their ability to escape vaccine-induced neutralizing antibodies. Early data point to a milder disease course following infection with the Omicron variant in vaccinated individuals. Thus, these data suggest that alternate vaccine-induced immunity beyond neutralization may continue to attenuate Omicron variant-induced disease, such as Fc-mediated antibody activity. OBJECTIVE: This study aimed to test whether vaccine-induced antibodies raised during pregnancy continue to bind to and leverage Fc receptors to protect against variants of concern including the Omicron variant. STUDY DESIGN: The receptor binding domain or whole spike-specific antibody isotype binding titers and Fc gamma receptor binding directed toward variants of concern, including the Omicron variant, were analyzed in pregnant women after receiving the full dose regimen of either the Pfizer/BioNTech BNT62b2 (n=10) or Moderna mRNA-1273 (n=10) vaccination using a multiplexing Luminex assay. RESULTS: Reduced isotype recognition of the Omicron receptor binding domain was observed following administration of either vaccine with relatively preserved, albeit reduced, recognition of the whole Omicron spike by immunoglobulin M and G antibodies. Despite the near complete loss of Fc receptor binding to the Omicron receptor binding domain, Fc receptor binding to the Omicron spike was more variable but largely preserved. CONCLUSION: Reduced binding titers to the Omicron receptor binding domain aligns with the observed loss of neutralizing activity. Despite the loss of neutralization, preserved, albeit reduced, Omicron spike recognition and Fc receptor binding potentially continue to attenuate disease severity in pregnant women.