Association of the Verbal Rating Scale-Measured Dysmenorrhea with Nausea and Vomiting in Pregnancy: A Retrospective Cohort Study.

OBJECTIVES: Nausea and vomiting in pregnancy (NVP) is a common condition that reduces the quality of life by negatively affecting work and family life, physical and mental health, and economic well-being. However, its risk factors remain unclear. This study aimed to explore the association between NVP and verbal rating scale (VRS)-measured dysmenorrhea and to explore potential protective factors. METHODS: This retrospective cohort study was conducted from June 2018 to December 2020 at Tongji Hospital in Wuhan. Information on baseline characteristics, pregnancy-related history, periconceptional micronutrient supplementation, and obstetric outcomes were collected. The severity of dysmenorrhea was assessed using VRS. RESULTS: A total of 443 pregnant women were recruited and divided into the NVP group (n = 76) and the control group (n = 367). A significant association was observed between NVP and VRS-measured dysmenorrhea (c2=10.038, P = 0.007). After adjusting for covariates, the association between moderate/severe dysmenorrhea and NVP remained significant (OR 2.384; 95% CI 1.104-5.148, P = 0.004). First-trimester docosahexaenoic acid supplement (OR 0.443; 95% CI 0.205-0.960, P = 0.039) may be beneficial in reducing the risk of NVP. CONCLUSIONS: Women with moderate to severe dysmenorrhea have a higher risk of experiencing NVP during the first trimester. Periconceptional docosahexaenoic acid supplementation may play a protective role.

PINK1-mediated mitophagy induction protects against preeclampsia by decreasing ROS and trophoblast pyroptosis.

INTRODUCTION: Preeclampsia (PE) is a multisystemic disorder attributed to the excessive presentation of placenta-derived immunoinflammatory factors. PTEN-induced putative kinase 1 (PINK1)-mediated mitophagy participates in the development and persistence of the inflammation. We hypothesized that dysregulated mitophagy might be involved in the pathogenesis of PE by promoting the activation of trophoblast pyroptosis that augment inflammation. METHODS: The morphology of mitochondrial in placenta were observed by transmission electron microscopy. The localization of PINK1 in the placenta was determined by immunohistochemistry. The expression levels of PINK1, PARKIN, LC3B, and SQSTM1 and pyroptosis-related molecules were compared between normal pregnancies and PE. We used hypoxia/reoxygenation (H/R) to stimulate the trophoblast hypoxia environment. HTR-8/SVneo cells were transfected with PINK1 plasmid and si-PINK1, respectively, and then were treated with H/R, to determine whether PINK1 regulated ROS and HTR-8/Svneo pyroptosis. Finally, ROS production was inhibited by MitoTEMPO to observe whether the pro-pyroptosis effect of PINK1 knockdown is alleviated. RESULTS: Swollen mitochondrial were accumulated in the PE placentae. PINK1 is localized on villus trophoblast (VTs) and extravillous trophoblast (EVTs). PINK1-mediated mitophagy was abolished in the PE placenta, while the levels of pyroptosis were induced. H/R stimulation aggravated the downregulation of mitophagy and the up-regulation of pyroptosis. Overexpression of PINK1 mitigated H/R-induced upregulation of ROS and pyroptosis while silencing PINK1 did the opposite. Reducing ROS production can effectively resist the pro-pyroptosis effect of PINK1 knockdown. DISCUSSION: This study demonstrated that PINK1-mediated mitophagy might played a protective role in PE by reducing ROS and trophoblast pyroptosis.

New Interpretation of Neonatal Outcomes by Phenotypically Classified Preterm Syndrome: A Retrospective Cohort Study.

OBJECTIVE: The global aim to lower preterm birth rates has been hampered by the insufficient and incomplete understanding of its etiology, classification, and diagnosis. This study was designed to evaluate the association of phenotypically classified preterm syndromes with neonatal outcomes; to what extent would these outcomes be modified after the obstetric interventions, including use of glucocorticoid, magnesium sulfate, and progesterone. METHODS: This was a retrospective cohort study conducted at Tongji Hospital (composed of Main Branch, Optical Valley Branch and Sino-French New City Branch) in Wuhan. A total of 900 pregnant women and 1064 neonates were retrospectively enrolled. The outcomes were the distribution of different phenotypes among parturition signs and pathway to delivery, the association of phenotypically classified clusters with short-term unfavorable neonatal outcomes, and to what extent these outcomes could be modified by obstetric interventions. RESULTS: Eight clusters were identified using two-step cluster analysis, including premature rupture of fetal membranes (PPROM) phenotype, abnormal amniotic fluid (AF) phenotype, placenta previa phenotype, mixed condition phenotype, fetal distress phenotype, preeclampsia-eclampsia & hemolysis, elevated liver enzymes, and low platelets syndrome (PE-E&HELLP) phenotype, multiple fetus phenotype, and no main condition phenotype. Except for no main condition phenotype, the other phenotypes were associated with one or more complications, which conforms to the clinical practice. Compared with no main condition phenotype, some phenotypes were significantly associated with short-term adverse neonatal outcomes. Abnormal AF phenotype, mixed condition phenotype, PE-E&HELLP phenotype, and multiple fetus phenotype were risk factors for neonatal small-for gestation age (SGA); placenta previa phenotype was not associated with adverse outcomes except low APGAR score being 0-7 at one min; mixed condition phenotype was associated with low APGAR scores, SGA, mechanical ventilation, and grade HI-W intraventricular hemorrhage (IVH); fetal distress phenotype was frequently associated with neonatal SGA and mechanical ventilation; PE-E&HELLP phenotype was correlated with low APGAR score being 0-7 at one min, SGA and neonatal intensive care unit (NICU) admission; multiple fetus phenotype was not a risk factor for the outcomes included except for SGA. Not all neonates benefited from obstetric interventions included in this study. CONCLUSION: Our research disclosed the independent risk of different preterm phenotypes for adverse pregnancy outcomes. This study is devoted to putting forward the paradigm of classifying preterm birth phenotypically, with the ultimate purpose of defining preterm phenotypes based on multi-center studies and diving into the underlying mechanisms.

TREM-1 amplifies trophoblastic inflammation via activating NF-κB pathway during preeclampsia.

INTRODUCTION: Excessive activation of maternal systemic inflammation is one of the underlying causes of pathology during the disease course of preeclampsia (PE). The triggering receptor expressed on myeloid cells-1 (TREM-1) participates in the development and persistence of inflammation. We hypothesized that dysregulated TREM-1 may be involved in the pathogenesis of PE by promoting the secretion of trophoblastic pro-inflammatory cytokines that augment inflammation. METHODS: The localization of TREM-1 in placenta and the extravillous trophoblast cell line (TEV-1) was determined by immunohistochemical staining. The expression level of TREM-1 and pro-inflammatory cytokines in placentas were compared between normal pregnancies and PE. We used lipopolysaccharide (LPS) to simulate trophoblastic inflammation. TEV-1 cells were transfected with TREM-1 plasmid and si-TREM-1 respectively, and then were incubated with LPS. The expression levels of pro-inflammatory cytokines and key molecules featured in nuclear transcription factor-kappaB (NF-κB) pathway were detected. Transwell assays were used to detect the effects of TREM-1 on cell migration and invasion. RESULTS: TREM-1 was localized on both villous trophoblasts (VTs) and extravillous trophoblasts (EVTs). TREM-1 and pro-inflammatory cytokines were up-regulated in preeclamptic placenta. Overexpression of TREM-1 promoted the activation of NF-κB pathway and the release of pro-inflammatory factors induced by LPS, and enhanced migration and invasion of TEV-1 cells. Inhibition of TREM-1 significantly attenuated LPS-induced effects and suppressed migration and invasion. DISCUSSION: This study suggested that TREM-1 was up-regulated in PE, and may promote the production of downstream inflammatory factors by activating NF-κB pathway in trophoblastic cells, thus exerting pro-inflammatory effects in the pathogenesis of PE.

Integrated analysis of multiple microarray studies to identify potential pathogenic gene modules in preeclampsia.

BACKGROUND: Preeclampsia is a life-threatening hypertensive disorder during pregnancy, while underlying pathogenesis and its diagnosis are incomplete. METHODS: In this study, we utilized the Robust Rank Aggregation method to integrate 6 eligible preeclampsia microarray datasets from Gene Expression Omnibus database. We used linear regression to assess the associations between significant differentially expressed genes (DEGs) and blood pressure. Functional annotation, protein-protein interaction, Gene Set Enrichment Analysis (GSEA) and single sample GSEA were employed for investigating underlying pathogenesis in preeclampsia. RESULTS: We filtered 52 DEGs and further screened for 5 hub genes (leptin, pappalysin 2, endoglin, fms related receptor tyrosine kinase 1, tripartite motif containing 24) that were positively correlated with both systolic blood pressure and diastolic blood pressure. Receiver operating characteristic indicated that hub genes were potential biomarkers for diagnosis and prognosis in preeclampsia. GSEA for single hub gene revealed that they were all closely related to angiogenesis and estrogen response in preeclampsia. Moreover, single sample GSEA showed that the expression levels of 5 hub genes were correlated with those of immune cells in immunologic microenvironment at maternal-fetal interface. CONCLUSIONS: These findings provide new insights into underlying pathogenesis in preeclampsia; 5 hub genes were identified as biomarkers for diagnosis and prognosis in preeclampsia.

Integrated Learning: Screening Optimal Biomarkers for Identifying Preeclampsia in Placental mRNA Samples.

Preeclampsia (PE) is a maternal disease that causes maternal and child death. Treatment and preventive measures are not sound enough. The problem of PE screening has attracted much attention. The purpose of this study is to screen placental mRNA to obtain the best PE biomarkers for identifying patients with PE. We use Limma in the R language to screen out the 48 differentially expressed genes with the largest differences and used correlation-based feature selection algorithms to reduce the dimensionality and avoid attribute redundancy arising from too many mRNA samples participating in the classification. After reducing the mRNA attributes, the mRNA samples are sorted from large to small according to information gain. In this study, a classifier model is designed to identify whether samples had PE through mRNA in the placenta. To improve the accuracy of classification and avoid overfitting, three classifiers, including C4.5, AdaBoost, and multilayer perceptron, are used. We use the majority voting strategy integrated with the differentially expressed genes and the genes filtered by the best subset method as comparison methods to train the classifier. The results show that the classification accuracy rate has increased from 79% to 82.2%, and the number of mRNA features has decreased from 48 to 13. This study provides clues for the main PE biomarkers of mRNA in the placenta and provides ideas for the treatment and screening of PE.

Microenvironment characterization and multi-omics signatures related to prognosis and immunotherapy response of hepatocellular carcinoma.

BACKGROUND: Immune cell infiltration in the tumor microenvironment (TME) affects tumor initiation, patients' prognosis and immunotherapy strategies. However, their roles and interactions with genomics and molecular processes in hepatocellular carcinoma (HCC) still have not been systematically evaluated. METHODS: We performed unsupervised clustering of total 1000 HCC samples including discovery and validation group from available public datasets. Immune heterogeneity of each subtype was explored by multi-dimension analysis. And a support vector machine (SVM) model based on multi-omics signatures was trained and tested. Finally, we performed immunohistochemistry to verify the immune role of signatures. RESULTS: We defined three immune subtypes in HCC, with diverse clinical, molecular, and genomic characteristics. Cluster1 had worse prognosis, better anti-tumor characteristics and highest immune scores, but also accompanied by immunosuppression and T cell dysfunction. Meanwhile, a better anti-PD1/CTLA4 immunotherapeutic response was predicted in cluster1. Cluster2 was enriched in TAM-M2 and stromal cells, indicating immunosuppression. Cluster3, with better prognosis, had lowest CD8 T cell but highest immune resting cells. Further, based on genomic signatures, we developed an SVM classifier to identify the patient's immunological status, which was divided into Type A and Type B, in which Type A had poorer prognosis, higher T cell dysfunction despite higher T cell infiltration, and had better immunotherapeutic response. At the same time, MMP9 may be a potential predictor of the immune characteristics and immunotherapeutic response in HCC. CONCLUSIONS: Our work demonstrated 3 immune clusters with different features. More importantly, multi-omics signatures, such as MMP9 was identified based on three clusters to help us recognize patients with different prognosis and responses to immunotherapy in HCC. This study could further reveal the immune status of HCC and provide potential predictors for immune checkpoint treatment response.