Seroprevalence of Cytomegalovirus and Associated Factors Among Preconception Women: A Cross-Sectional Nationwide Study in China

Background: Cytomegalovirus seroconversion during pregnancy is common and has a substantial risk of congenital infection with longterm sequale. Screening during pregnancy or vaccination have not been shown to be effective for eliminating congenital infections. Preconception screening policy has not been evaluated adequately in a large scale. This nationwide study aimed to investigate epidemiological features of cytomegalovirus seropositivity and its geographic variation among Chinese women planning a pregnancy to gather epidemiological evidence as an essential for developing novel prevention strategies. Method: This cross-sectional sero-epidemiological survey enrolled women intending to become pregnant within 6 months in mainland China during 2010–2012. The primary outcomes in this study were cytomegalovirus Immunoglobulin G and M seropositivity. Secondary outcomes were the associations between Immunoglobulin G and Immunoglobulin M, with socio-demographic characteristics, including age, occupation, education level, place of residence, and ethnicity. The overall seropositivity and regional disparity was analyzed on the individual and regional level, respectively. Results: This study included data from 1,564,649 women from 31 provinces in mainland China. Among participants, 38.6% (n = 603,511) were cytomegalovirus immunoglobulin G+, 0.4% (n = 6,747) were immunoglobulin M+, and 0.2% (n = 2,879) were immunoglobulin M+ and immunoglobulin G+. On individual level, participant's age, ethnicity, and residing region were significantly associated with IgG+, IgM+, and IgM+IgG+ (P 0.05). On regional level, cytomegalovirus immunoglobulin G and immunoglobulin M seropositivity was highest in the eastern region (49.5 and 0.5%, respectively), and lowest in the western region (26.9 and 0.4%, respectively). This geographic variation was also noted at the provincial level, characterized by higher provincial immunoglobulin M+ and immunoglobulin G+ rates associated with higher immunoglobulin G seropositivity. In the subgroup analysis of immunoglobulin G seropositivity, areas of higher immunoglobulin G positivity had a higher rate of immunoglobulin M+, indicating an expected increased risk of reinfection and primary infection. Conclusions: A substantial proportion of women (>60%) were susceptible to cytomegalovirus in preconception period in China, and immunoglobulin G seropositivity was seen at a low-medium level with substantial geographic variation. Integration of cytomegalovirus antibody testing in preconception screening program based on regional immunoglobulin G seropositivity, should be considered to promote strategies directed toward preventing sero-conversion during pregnancy to reduce the risk of this congenital infection

Single-cell RNA-seq reveals developmental deficiencies in both the placentation and the decidualization in women with late-onset preeclampsia

Preeclampsia (PE) is a leading cause of maternal and fetal morbidity and mortality. Although increasing lines of evidence suggest that both the placenta and the decidua likely play roles in the pathogenesis of PE, the molecular mechanism of PE remains elusive partly because of the heterogeneity nature of the maternal-fetal interface. In this study, we perform single-cell RNA-seq on the placenta and the decidual from patients with late-onset PE (LOPE) and women in normal pregnancy. Analyses of single-cell transcriptomes reveal that in LOPE, there are likely a global development deficiency of trophoblasts with impaired invasion of extravillous trophoblasts (EVT) and increased maternal immune rejection and inflammation in the placenta, while there are likely insufficient decidualization of decidual stromal cells (DSC), increased inflammation, and suppressed regulatory functions of decidual immune cells. These findings improve our understanding of the molecular mechanisms of PE

Optimal cutoffs of growth discordance for the risk of preeclampsia in twin pregnancies: A single-center retrospective cohort study

ObjectiveTo explore the optimal cutoffs of growth discordance for the risk of preeclampsia in twin pregnancies.MethodsA retrospective cohort study in a university hospital which included twins delivered from February 2013 to September 2020. Restrictive cubic spline (RCS) model was applied to the trend of intertwin birthweight difference (BWD) with the risk of preeclampsia. Logistic regression and subgroup analysis were performed to find the cut-off with statistical significance and clinical meaningfulness.ResultsA total of 2,631 women pregnant with twins were enrolled. RCS showed a nonlinear upward trend of preeclampsia with BWD, and the BWD of 15% was the initial rising point. With the confounders adjusted, only the group with BWD ≥ 25% was found to be significantly associated with an increased risk of preeclampsia (adjusted odds ratio [aOR], 2.44; 95% confidence interval [CI]: 1.74–3.42). Additionally, subgroup analysis showed that both monochorionic (MC) and small for gestational age (SGA) twins were more likely to complicate with preeclampsia.ConclusionThe growth discordance of 15% during pregnancy may be the preventive point of preeclampsia, and 25% may be the interventional point

Low-dose aspirin in the prevention of preeclampsia in twin pregnancies: A real-world study

BackgroundThe use of low-dose aspirin for women with twin pregnancies remains controversial. This study was to describe the frequency of preeclampsia and aspirin use in twin pregnancies in real practice.MethodsThis retrospective cohort study based on real-world data was conducted in the Obstetrics and Gynecology Hospital of Fudan University between 2013 and 2020. Women with twin pregnancies who received prenatal care before 20 weeks of gestational age were included. They were divided into those using low-dose aspirin (LDA group) and those not using aspirin group (N-LDA group). The primary outcome was the frequency of preeclampsia, and secondary outcomes included early-onset and preterm mild and severe preeclampsia.ResultsA total of 2,946 women had twin pregnancies, and 241 were excluded due to missing information. Of 2,705 eligible women, 291 (10.75%) were administered aspirin and the other 2,414 (89.25%) did not. The patients in the LDA group were significantly more likely to be older, have a higher rate of use of ART, have a previous history of hypertension, and have gestational diabetes (p < 0.05). In the LDA group, aspirin compliance ≥50% was relatively low (14.43%, 42/291). Preeclampsia occurred in 106 of 291 participants (36.43%) in the LDA group, as compared to 449 of 2,411 (18.62%) in the N-LDA group (OR: 2.15, 95% CI: 1.62–2.82; p < 0.01). The association was confirmed (OR: 1.74, 95% CI: 1.26–2.4; p < 0.01) in the 1:2 case-matched analysis. Higher odds of ratio in the LDA group were demonstrated (aORs > 1, p < 0.01), except for early-onset and preterm mild preeclampsia (p > 0.05). This association was confirmed in a subgroup analysis of methods of conception (aORs ≥ 1, p > 0.05).ConclusionAspirin prescription of 75 to 100 mg in twin pregnancies was associated with no significant reduction of preeclampsia, which may be due to poor compliance with the aspirin used. Further randomized controlled or prospective cohort studies are required

Lower gestational age is associated with lower cortical volume and cognitive and educational performance in adolescence

Background: Gestational age (GA) is associated with later cognition and behavior. However, it is unclear how specific cognitive domains and brain structural development varies with the stepwise change of gestational duration. Methods: This large-scale longitudinal cohort study analyzed 11,878 early adolescents’ brain volume maps at 9–10 years (baseline) and 5685 at 11–12 years (a 2-year follow-up) from the Adolescent Brain Cognitive Development (ABCD) study. According to gestational age, adolescents were divided into five categorical groups: ≤ 33 weeks, 34–35 weeks, 36 weeks, 37–39 weeks, and ≥ 40 weeks. The NIH Toolbox was used to estimate neurocognitive performance, including crystallized and fluid intelligence, which was measured for 11,878 adolescents at baseline with crystallized intelligence and relevant subscales obtained at 2-year follow-up (with participant numbers ranging from 6185 to 6310 depending on the cognitive domain). An additional large population-based cohort of 618,070 middle adolescents at ninth-grade (15–16 years) from the Danish national register was utilized to validate the association between gestational age and academic achievements. A linear mixed model was used to examine the group differences between gestational age and neurocognitive performance, school achievements, and grey matter volume. A mediation analysis was performed to examine whether brain structural volumes mediated the association between GA and neurocognition, followed with a longitudinal analysis to track the changes. Results: Significant group differences were found in all neurocognitive scores, school achievements, and twenty-five cortical regional volumes (P < 0.05, Bonferroni corrected). Specifically, lower gestational ages were associated with graded lower cognition and school achievements and with smaller brain volumes of the fronto-parieto-temporal, fusiform, cingulate, insula, postcentral, hippocampal, thalamic, and pallidal regions. These lower brain volumes mediated the association between gestational age and cognitive function (P = 1 × 10−8, β = 0.017, 95% CI: 0.007–0.028). Longitudinal analysis showed that compared to full term adolescents, preterm adolescents still had smaller brain volumes and crystallized intelligence scores at 11–12 years. Conclusions: These results emphasize the relationships between gestational age at birth and adolescents’ lower brain volume, and lower cognitive and educational performance, measured many years later when 9–10 and 11–12 years old. The study indicates the importance of early screening and close follow-up for neurocognitive and behavioral development for children and adolescents born with gestational ages that are even a little lower than full term

A novel risk classification system for preconception health and sero-epidemiological map of Toxoplasma, Rubella and Cytomegalovirus infections among couples planning a pregnancy in rural China: A nationwide study

Objectives - The aim of this thesis was to evaluate the feasibility, effectiveness and impact of preconception health screening strategy and a novel risk classification system of China`s “National Preconception Health Care Project (NPHCP)” in identifying risk factors and stratifying couples’ preconception care (PCC), and to establish a sero-epidemiological map of TORC infections in the preconception period. Methods - This study utilized data from NPHCP, a population-based, cross-sectional, nation-wide study that was conducted during 2010–12 in 220 rural counties located in 31 provinces and province level municipalities of mainland China. Risk factors were categorized into five preconception risk classes based on their amenability to prevention and treatment. Results of TORC serology and collected socio-demographic and clinical data of the participating couples were extracted and further analyzed to estimate sero-prevalence in the sample population, explore regional differences, and identify associated risk factors. Results - Among the 2142849 couples enrolled to this study, 1463266 (68.29%) couples had one or more preconception risk factors, mainly of category A, B or C, among which 46.25% were women and 51.92% were men. 45405 (2.3%) women were IgG positive and 6884 (0.3%) were IgM positive. Advanced maternal age, occupation of a farmer, vegetarian diet and exposure to cats were significantly associated with Toxoplasma gondii IgG and IgM sero-positivity. The overall prevalence of Rubella virus IgG sero-positivity was 58.4% (n=1161129). Only 4.6% (n=91604) women reported to have had Rubella virus vaccination, and self-reported vaccination status did not correlate with Rubella virus IgG sero-positivity. 42.1% (n=850592) women were CMV IgG positive with 0.4% (n=9290) IgM positive. CMV IgG negative women were of younger age, whereas the elder women were more likely to be CMV IgM positive (P Conclusions - Preconception health screening and use of a novel risk classification system could effectively identify important risk factors and stratify couples into five different risk categories. Involvement of male partners in PCC is of equal importance. Targeted screening of TORC infections followed by referral, diagnosis, treatment, counseling, health education and vaccination before pregnancy should be considered for reducing the risk of vertical transmission during pregnancy and childbirth

Roles of apolipoprotein E (ApoE) and inducible nitric oxide synthase (iNOS) in inflammation and apoptosis in preeclampsia pathogenesis and progression.

OBJECTIVES: To investigate potential roles of inducible nitric oxide synthase (iNOS) and apolipoprotein (apoE) in inflammation and apoptosis promoting pathological changes in preeclampsia in pregnant mice with apoE and/or iNOS knock out. METHODS: B6.129 mice were crossed to produce WT, apoE(-/-), apoE(+/-), iNOS(-/-), iNOS(+/-) and apoE(-/-)iNOS(-/-) groups. Variants were confirmed by PCR. Serum lipid parameters (triglycerides, TG; total cholesterol, TC; high density lipoprotein, HDL; and low density lipoprotein, LDL), NO levels and placental electronic microscopic ultrastructures were evaluated, and blood pressure (BP), 24-hour urine protein and pregnancy outcomes were recorded for pregnant F1 generation mice. Placental expressions of inflammatory (tumor necrosis factor-α, TNF-α; interleukin-6, IL-6; nuclear factor-κB, NF-κb) and apoptotic markers (Bcl-2 associated X protein, Bax, B-cell lymphoma/leukemia-2, Bcl-2, and Caspase-3) were evaluated via Western blot. RESULTS: Serum lipids, BP and 24-hour urine protein levels were shown to be significantly higher and parturition and placenta weights were lower in apoE(-/-) and apoE(-/-)iNOS(-/-) groups (p<0.05). NO levels were lower in the apoE(-/-)iNOS(-/-) group. In addition, inflammatory/apoptosis parameters, including TNF-α, IL-6, NF-κb, Bax, Bcl-2 and Caspase-3 in the apoE(-/-)iNOS(-/-) group (p<0.01), as well as in the apoE(-/-) group (p<0.05), and NF-κB, Bax in iNOS(-/-) group (p<0.05) were higher compared with WT group. However, most of the inflammatory/apoptosis parameters in the iNOS(+/-) and the apoE(+/-) groups (p>0.05) showed no differences. In addition, placenta vascular endothelial and trophoblast cell morphological changes were demonstrated in both the apoE(-/-)iNOS(-/-) and apoE(-/-) groups. CONCLUSION: Elevated lipid metabolism and inflammatory/apoptosis parameters suggest a potentially significant role of apoE in preeclampsia pathology, as well as a relationship between iNOS and preeclampsia progression

Decreased placental IL9 and IL9R in preeclampsia impair trophoblast cell proliferation, invasion, and angiogenesis

Objective Our study aimed to investigate IL9 and IL9R expression in preeclampsia and assess their effects on trophoblast biological behaviors. Methods IL9 and IL9R expression of placenta tissue were evaluated by immunochemistry and q-PCR. Using transwell, CCK-8, and tubule formation assays measured invasion, proliferation and angiogenesis of trophoblast with adding IL9 or anti-IL9R antibody. Results IL9 and IL9R levels were significantly decreased in preeclampsia. IL9 improved trophoblast activities. Blocking IL9/IL9R resulted in decreased proliferation, invasion, and tube-formation capability of trophoblast. Conclusions IL9 and IL9R contribute to the pathogenesis of preeclampsia. IL9/IL9R signaling provides a new potential therapeutic target for preventing preeclampsia

Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study

Background. Gestational diabetes mellitus (GDM) contributes to adverse pregnancy and birth outcomes. In recent decades, extensive research has been devoted to the early prediction of GDM by various methods. Machine learning methods are flexible prediction algorithms with potential advantages over conventional regression. Objective. The purpose of this study was to use machine learning methods to predict GDM and compare their performance with that of logistic regressions. Methods. We performed a retrospective, observational study including women who attended their routine first hospital visits during early pregnancy and had Down’s syndrome screening at 16-20 gestational weeks in a tertiary maternity hospital in China from 2013.1.1 to 2017.12.31. A total of 22,242 singleton pregnancies were included, and 3182 (14.31%) women developed GDM. Candidate predictors included maternal demographic characteristics and medical history (maternal factors) and laboratory values at early pregnancy. The models were derived from the first 70% of the data and then validated with the next 30%. Variables were trained in different machine learning models and traditional logistic regression models. Eight common machine learning methods (GDBT, AdaBoost, LGB, Logistic, Vote, XGB, Decision Tree, and Random Forest) and two common regressions (stepwise logistic regression and logistic regression with RCS) were implemented to predict the occurrence of GDM. Models were compared on discrimination and calibration metrics. Results. In the validation dataset, the machine learning and logistic regression models performed moderately (AUC 0.59-0.74). Overall, the GBDT model performed best (AUC 0.74, 95% CI 0.71-0.76) among the machine learning methods, with negligible differences between them. Fasting blood glucose, HbA1c, triglycerides, and BMI strongly contributed to GDM. A cutoff point for the predictive value at 0.3 in the GBDT model had a negative predictive value of 74.1% (95% CI 69.5%-78.2%) and a sensitivity of 90% (95% CI 88.0%-91.7%), and the cutoff point at 0.7 had a positive predictive value of 93.2% (95% CI 88.2%-96.1%) and a specificity of 99% (95% CI 98.2%-99.4%). Conclusion. In this study, we found that several machine learning methods did not outperform logistic regression in predicting GDM. We developed a model with cutoff points for risk stratification of GDM