Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function.

While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).

Blood-based Transcriptomic and Proteomic Biomarkers of Emphysema.

Rationale: Emphysema is a chronic obstructive pulmonary disease phenotype with important prognostic implications. Identifying blood-based biomarkers of emphysema will facilitate early diagnosis and development of targeted therapies. Objectives: To discover blood omics biomarkers for chest computed tomography-quantified emphysema and develop predictive biomarker panels. Methods: Emphysema blood biomarker discovery was performed using differential gene expression, alternative splicing, and protein association analyses in a training sample of 2,370 COPDGene participants with available blood RNA sequencing, plasma proteomics, and clinical data. Internal validation was conducted in a COPDGene testing sample (n = 1,016), and external validation was done in the ECLIPSE study (n = 526). Because low body mass index (BMI) and emphysema often co-occur, we performed a mediation analysis to quantify the effect of BMI on gene and protein associations with emphysema. Elastic net models with bootstrapping were also developed in the training sample sequentially using clinical, blood cell proportions, RNA-sequencing, and proteomic biomarkers to predict quantitative emphysema. Model accuracy was assessed by the area under the receiver operating characteristic curves for subjects stratified into tertiles of emphysema severity. Measurements and Main Results: Totals of 3,829 genes, 942 isoforms, 260 exons, and 714 proteins were significantly associated with emphysema (false discovery rate, 5%) and yielded 11 biological pathways. Seventy-four percent of these genes and 62% of these proteins showed mediation by BMI. Our prediction models demonstrated reasonable predictive performance in both COPDGene and ECLIPSE. The highest-performing model used clinical, blood cell, and protein data (area under the receiver operating characteristic curve in COPDGene testing, 0.90; 95% confidence interval, 0.85-0.90). Conclusions: Blood transcriptome and proteome-wide analyses revealed key biological pathways of emphysema and enhanced the prediction of emphysema.

Lung Transcriptomics Links Emphysema to Barrier Dysfunction and Macrophage Subpopulations.

RATIONALE: While many studies have examined gene expression in lung tissue, the gene regulatory processes underlying emphysema are still not well understood. Finding efficient non-imaging screening methods and disease-modifying therapies has been challenging, but knowledge of the transcriptomic features of emphysema may help in this effort. OBJECTIVES: Our goals were to identify emphysema-associated biological pathways through transcriptomic analysis of bulk lung tissue, to determine the lung cell types in which these emphysema-associated pathways are altered, and to detect unique and overlapping transcriptomic signatures in blood and lung samples. METHODS: Using RNA-sequencing data from 446 samples in the Lung Tissue Research Consortium (LTRC) and 3,606 blood samples from the COPDGene study, we examined the transcriptomic features of chest computed tomography-quantified emphysema. We also leveraged publicly available lung single-cell RNA-sequencing data to identify cell types showing COPD-associated differential expression of the emphysema pathways found in the bulk analyses. MEASUREMENTS AND MAIN RESULTS: In the bulk lung RNA-seq analysis, 1,087 differentially expressed genes and 34 dysregulated pathways were significantly associated with emphysema. We observed alternative splicing of several genes and increased activity in pluripotency and cell barrier function pathways. Lung tissue and blood samples shared differentially expressed genes and biological pathways. Multiple lung cell types displayed dysregulation of epithelial barrier function pathways, and distinct pathway activities were observed among various macrophage subpopulations. CONCLUSIONS: This study identified emphysema-related changes in gene expression and alternative splicing, cell-type specific dysregulated pathways, and instances of shared pathway dysregulation between blood and lung.

Blood Gene Expression and Immune Cell Subtypes Associated with Chronic Obstructive Pulmonary Disease Exacerbations.

Rationale: Acute exacerbations of chronic obstructive pulmonary disease (AE-COPDs) are associated with a significant disease burden. Blood immune phenotyping may improve our understanding of a COPD endotype at increased risk of exacerbations. Objective: To determine the relationship between the transcriptome of circulating leukocytes and COPD exacerbations. Methods: Blood RNA sequencing data (n = 3,618) from the COPDGene (Genetic Epidemiology of COPD) study were analyzed. Blood microarray data (n = 646) from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study were used for validation. We tested the association between blood gene expression and AE-COPDs. We imputed the abundance of leukocyte subtypes and tested their association with prospective AE-COPDs. Flow cytometry was performed on blood in SPIROMICS (Subpopulations and Intermediate Outcomes in COPD Study) (n = 127), and activation markers for T cells were tested for association with prospective AE-COPDs. Measurements and Main Results: Exacerbations were reported 4,030 and 2,368 times during follow-up in COPDGene (5.3 ± 1.7 yr) and ECLIPSE (3 yr), respectively. We identified 890, 675, and 3,217 genes associated with a history of AE-COPDs, persistent exacerbations (at least one exacerbation per year), and prospective exacerbation rate, respectively. In COPDGene, the number of prospective exacerbations in patients with COPD (Global Initiative for Chronic Obstructive Lung Disease stage ⩾2) was negatively associated with circulating CD8+ T cells, CD4+ T cells, and resting natural killer cells. The negative association with naive CD4+ T cells was replicated in ECLIPSE. In the flow-cytometry study, an increase in CTLA4 on CD4+ T cells was positively associated with AE-COPDs. Conclusions: Individuals with COPD with lower circulating lymphocyte counts, particularly decreased CD4+ T cells, are more susceptible to AE-COPDs, including persistent exacerbations.

Alternative poly-adenylation modulates α1-antitrypsin expression in chronic obstructive pulmonary disease.

α1-anti-trypsin (A1AT), encoded by SERPINA1, is a neutrophil elastase inhibitor that controls the inflammatory response in the lung. Severe A1AT deficiency increases risk for Chronic Obstructive Pulmonary Disease (COPD), however, the role of A1AT in COPD in non-deficient individuals is not well known. We identify a 2.1-fold increase (p = 2.5x10-6) in the use of a distal poly-adenylation site in primary lung tissue RNA-seq in 82 COPD cases when compared to 64 controls and replicate this in an independent study of 376 COPD and 267 controls. This alternative polyadenylation event involves two sites, a proximal and distal site, 61 and 1683 nucleotides downstream of the A1AT stop codon. To characterize this event, we measured the distal ratio in human primary tissue short read RNA-seq data and corroborated our results with long read RNA-seq data. Integrating these results with 3' end RNA-seq and nanoluciferase reporter assay experiments we show that use of the distal site yields mRNA transcripts with over 50-fold decreased translation efficiency and A1AT expression. We identified seven RNA binding proteins using enhanced CrossLinking and ImmunoPrecipitation precipitation (eCLIP) with one or more binding sites in the SERPINA1 3' UTR. We combined these data with measurements of the distal ratio in shRNA knockdown experiments, nuclear and cytoplasmic fractionation, and chemical RNA structure probing. We identify Quaking Homolog (QKI) as a modulator of SERPINA1 mRNA translation and confirm the role of QKI in SERPINA1 translation with luciferase reporter assays. Analysis of single-cell RNA-seq showed differences in the distribution of the SERPINA1 distal ratio among hepatocytes, macrophages, αß-Tcells and plasma cells in the liver. Alveolar Type 1,2, dendritic cells and macrophages also vary in their distal ratio in the lung. Our work reveals a complex post-transcriptional mechanism that regulates alternative polyadenylation and A1AT expression in COPD.

Heterogeneity and Progression of Chronic Obstructive Pulmonary Disease: Emphysema-Predominant and Non-Emphysema-Predominant Disease.

While variation in emphysema severity between patients with chronic obstructive pulmonary disease (COPD) is well-recognized, clinically applicable definitions of the emphysema-predominant disease (EPD) and non-emphysema-predominant disease (NEPD) subtypes have not been established. To study the clinical relevance of the EPD and NEPD subtypes, we tested the association of these subtypes with prospective decline in forced expiratory volume in 1 second (FEV1) and mortality among 3,427 subjects with Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometric grade 2-4 COPD at baseline in the Genetic Epidemiology of COPD (COPDGene) Study, an ongoing national multicenter study that started in 2007. NEPD was defined as airflow obstruction with less than 5% computed tomography (CT) quantitative densitometric emphysema at -950 Hounsfield units, and EPD was defined as airflow obstruction with 10% or greater CT emphysema. Mixed-effects models for FEV1 demonstrated larger average annual FEV1 loss in EPD subjects than in NEPD subjects (-10.2 mL/year; P < 0.001), and subtype-specific associations with FEV1 decline were identified. Cox proportional hazards models showed higher risk of mortality among EPD patients versus NEPD patients (hazard ratio = 1.46, 95% confidence interval: 1.34, 1.60; P < 0.001). To determine whether the NEPD/EPD dichotomy is captured by previously described COPDGene subtypes, we used logistic regression and receiver operating characteristic (ROC) curve analysis to predict NEPD/EPD membership using these previous subtype definitions. The analysis generally showed excellent discrimination, with areas under the ROC curve greater than 0.9. The NEPD and EPD COPD subtypes capture important aspects of COPD heterogeneity and are associated with different rates of disease progression and mortality.

Studying the Adsorption of Gas Molecules and Defects on Modulating the Electronic Transport Characteristics of Monolayer Penta-BN2-Based Devices.

Two-dimensional atomic layer materials, as an important part of the post-Moore era, have recently become an ideal choice for the preparation of high-efficiency, low-power, and miniaturized gas sensors. In this work, our study utilized density functional theory and the nonequilibrium Green's function method to investigate the electronic properties of the pentagonal BN2 (P-BN2) monolayer, as well as its gas-sensing properties for organic and inorganic gases. We also investigated how defects affect the quantum transport properties of the P-BN2-based device. Our findings demonstrate that the CO, H2S, NH3, SO2, C2H5OH, C3H6OH, CH3OH, and CH4 undergo physisorption on the P-BN2 monolayer, while NO, NO2, C2H2, C2H4, and HCHO undergo chemisorption. Then, we analyzed the impact of gas molecules chemisorbed on the P-BN2 monolayer on the electronic transport properties of the P-BN2-based gas sensor. When these five gas molecules are adsorbed, the current of the P-BN2-based gas sensor is greatly reduced. In addition, the effect of defects on the quantum transport properties of the P-BN2-based device is investigated. The results indicate that defects of N, B, and BN atoms lead to a decrease in the current of P-BN2-based nanodevices. Moreover, both the adsorption of gas molecules and the formation of vacancy defects leading to a decrease in device current can be revealed by the local device density of states near the zero-bias Fermi level, elucidating their microscopic mechanisms. Finally, gas molecules can also cause a decrease in the current of defect systems. These theoretical studies are of great significance for exploring two-dimensional atomic layer materials as high-efficiency gas sensors.

Development of a Blood-based Transcriptional Risk Score for Chronic Obstructive Pulmonary Disease.

Rationale: The ability of peripheral blood biomarkers to assess chronic obstructive pulmonary disease (COPD) risk and progression is unknown. Genetics and gene expression may capture important aspects of COPD-related biology that predict disease activity. Objectives: Develop a transcriptional risk score (TRS) for COPD and assess the contribution of the TRS and a polygenic risk score (PRS) for disease susceptibility and progression. Methods: We randomly split 2,569 COPDGene (Genetic Epidemiology of COPD) participants with whole-blood RNA sequencing into training (n = 1,945) and testing (n = 624) samples and used 468 ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points) COPD cases with microarray data for replication. We developed a TRS using penalized regression (least absolute shrinkage and selection operator) to model FEV1/FVC and studied the predictive value of TRS for COPD (Global Initiative for Chronic Obstructive Lung Disease 2-4), prospective FEV1 change (ml/yr), and additional COPD-related traits. We adjusted for potential confounders, including age and smoking. We evaluated the predictive performance of the TRS in the context of a previously derived PRS and clinical factors. Measurements and Main Results: The TRS included 147 transcripts and was associated with COPD (odds ratio, 3.3; 95% confidence interval [CI], 2.4-4.5; P < 0.001), FEV1 change (ß, -17 ml/yr; 95% CI, -28 to -6.6; P = 0.002), and other COPD-related traits. In ECLIPSE cases, we replicated the association with FEV1 change (ß, -8.2; 95% CI, -15 to -1; P = 0.025) and the majority of other COPD-related traits. Models including PRS, TRS, and clinical factors were more predictive of COPD (area under the receiver operator characteristic curve, 0.84) and annualized FEV1 change compared with models with one risk score or clinical factors alone. Conclusions: Blood transcriptomics can improve prediction of COPD and lung function decline when added to a PRS and clinical risk factors.

An interferon-inducible signature of airway disease from blood gene expression profiling.

BACKGROUND: The molecular basis of airway remodelling in chronic obstructive pulmonary disease (COPD) remains poorly understood. We identified gene expression signatures associated with chest computed tomography (CT) scan airway measures to understand molecular pathways associated with airway disease. METHODS: In 2396 subjects in the COPDGene Study, we examined the relationship between quantitative CT airway phenotypes and blood transcriptomes to identify airway disease-specific genes and to define an airway wall thickness (AWT) gene set score. Multivariable regression analyses were performed to identify associations of the AWT score with clinical phenotypes, bronchial gene expression and genetic variants. RESULTS: Type 1 interferon (IFN)-induced genes were consistently associated with AWT, square root wall area of a hypothetical airway with 10 mm internal perimeter (Pi10) and wall area percentage, with the strongest enrichment in AWT. A score derived from 18 genes whose expression was associated with AWT was associated with COPD-related phenotypes including reduced lung function (forced expiratory volume in 1 s percentage predicted ß= -3.4; p<0.05) and increased exacerbations (incidence rate ratio 1.7; p<0.05). The AWT score was reproducibly associated with AWT in bronchial samples from 23 subjects (ß=3.22; p<0.05). The blood AWT score was associated with genetic variant rs876039, an expression quantitative trait locus for IKZF1, a gene that regulates IFN signalling and is associated with inflammatory diseases. CONCLUSIONS: A gene expression signature with IFN-stimulated genes from peripheral blood and bronchial brushings is associated with CT AWT, lung function and exacerbations. Shared genes and genetic associations suggest viral responses and/or autoimmune dysregulation as potential underlying mechanisms of airway disease in COPD.

Lung tissue shows divergent gene expression between chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are characterized by shared exposures and clinical features, but distinct genetic and pathologic features exist. These features have not been well-studied using large-scale gene expression datasets. We hypothesized that there are divergent gene, pathway, and cellular signatures between COPD and IPF. METHODS: We performed RNA-sequencing on lung tissues from individuals with IPF (n = 231) and COPD (n = 377) compared to control (n = 267), defined as individuals with normal spirometry. We grouped the overlapping differential expression gene sets based on direction of expression and examined the resultant sets for genes of interest, pathway enrichment, and cell composition. Using gene set variation analysis, we validated the overlap group gene sets in independent COPD and IPF data sets. RESULTS: We found 5010 genes differentially expressed between COPD and control, and 11,454 genes differentially expressed between IPF and control (1% false discovery rate). 3846 genes overlapped between IPF and COPD. Several pathways were enriched for genes upregulated in COPD and downregulated in IPF; however, no pathways were enriched for genes downregulated in COPD and upregulated in IPF. There were many myeloid cell genes with increased expression in COPD but decreased in IPF. We found that the genes upregulated in COPD but downregulated in IPF were associated with lower lung function in the independent validation cohorts. CONCLUSIONS: We identified a divergent gene expression signature between COPD and IPF, with increased expression in COPD and decreased in IPF. This signature is associated with worse lung function in both COPD and IPF.

Improved prediction of smoking status via isoform-aware RNA-seq deep learning models.

Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk factor for many diseases, and it has profound effects on gene expression. Using smoking status as a prediction target, we developed deep neural network predictive models using gene, exon, and isoform level quantifications from RNA sequencing data in 2,557 subjects in the COPDGene Study. We observed that models using exon and isoform quantifications clearly outperformed gene-level models when using data from 5 genes from a previously published prediction model. Whereas the test set performance of the previously published model was 0.82 in the original publication, our exon-based models including an exon-to-isoform mapping layer achieved a test set AUC (area under the receiver operating characteristic) of 0.88, which improved to an AUC of 0.94 using exon quantifications from a larger set of genes. Isoform variability is an important source of latent information in RNA-seq data that can be used to improve clinical prediction models.

High gas sensing performance of inorganic and organic molecule sensing devices based on the BC3N2 monolayer.

Recently, a novel two-dimensional (2D) BC3N2 monolayer has gained a lot of attention due to its graphene-like structure, and it was first reported by using the particle swarm optimization algorithm and ab initio calculations. Combining density functional theory with the non-equilibrium Green's function method, a 2D BC3N2-based nanodevice has been theoretically constructed and the gas sensing performance of the BC3N2 monolayer for inorganic and organic molecules has been extensively investigated. The results revealed that the BC3N2 monolayer remains metallic with thermodynamic stability. Meanwhile, the results of sensing performance analysis show that the inorganic molecules CO, NO, and NO2 and organic molecules C2H2 and HCHO have strong chemical interactions with BC3N2 and were chemically adsorbed onto BC3N2. In contrast, the interactions between NH3, SO2, CH4, C2H4 and CH3OH and BC3N2 are very weak and these molecules adopt physical adsorption. In the case of chemisorption, the electronic transport behaviors of the 2D BC3N2 devices are sensitive to molecules, and the gas sensitivity of BC3N2 is strongly anisotropic, especially for organic C2H2 with the gas sensing ratios from 7.30 to 10.43 (from 2.51 to 2.79) under different bias voltages along the zigzag (armchair) direction. For inorganic molecules, the gas sensing device is not particularly sensitive, and the maximum gas sensing ratio is only 1.36 for CO. Meanwhile, the large anisotropic gas sensitivity can reach up to 2.66/6.22 for electron transport along the armchair and zigzag directions for CO/C2H2 in the BC3N2-based sensing devices. Accordingly, the high gas sensitivity can be disclosed by displaying the scattering state around the Fermi level at different bias voltages during the transport process. As a result, BC3N2 could be used in 2D gas sensing devices, especially for sensing organic molecule C2H2.

Cigarette smoking-associated isoform switching and 3' UTR lengthening via alternative polyadenylation.

Cigarette smoking induces a profound transcriptomic and systemic inflammatory response. Previous studies have focused on gene level differential expression of smoking, but the genome-wide effects of smoking on alternative isoform regulation have not yet been described. We conducted RNA sequencing in whole-blood samples of 454 current and 767 former smokers in the COPDGene Study, and we analyzed the effects of smoking on differential usage of isoforms and exons. At 10% FDR, we detected 3167 differentially expressed genes, 945 differentially used isoforms and 160 differentially used exons. Isoform switch analysis revealed widespread 3' UTR lengthening associated with cigarette smoking. The lengthening of these 3' UTRs was consistent with alternative usage of distal polyadenylation sites, and these extended 3' UTR regions were significantly enriched with functional sequence elements including microRNA and RNA-protein binding sites. These findings warrant further studies on alternative polyadenylation events as potential biomarkers and novel therapeutic targets for smoking-related diseases.

Proteoglycans: Systems-Level Insight into Their Expression in Healthy and Diseased Placentas.

Proteoglycan macromolecules play key roles in several physiological processes (e.g., adhesion, proliferation, migration, invasion, angiogenesis, and apoptosis), all of which are important for placentation and healthy pregnancy. However, their precise roles in human reproduction have not been clarified. To fill this gap, herein, we provide an overview of the proteoglycans' expression and role in the placenta, in trophoblast development, and in pregnancy complications (pre-eclampsia, fetal growth restriction), highlighting one of the most important members of this family, syndecan-1 (SDC1). Microarray data analysis showed that of 34 placentally expressed proteoglycans, SDC1 production is markedly the highest in the placenta and that SDC1 is the most upregulated gene during trophoblast differentiation into the syncytiotrophoblast. Furthermore, placental transcriptomic data identified dysregulated proteoglycan genes in pre-eclampsia and in fetal growth restriction, including SDC1, which is supported by the lower concentration of syndecan-1 in maternal blood in these syndromes. Overall, our clinical and in vitro studies, data analyses, and literature search pointed out that proteoglycans, as important components of the placenta, may regulate various stages of placental development and participate in the maintenance of a healthy pregnancy. Moreover, syndecan-1 may serve as a useful marker of syncytialization and a prognostic marker of adverse pregnancy outcomes. Further studies are warranted to explore the role of proteoglycans in healthy and complicated pregnancies, which may help in diagnostic or therapeutic developments.

Fetal weight estimation by automated three-dimensional limb volume model in late third trimester compared to two-dimensional model: a cross-sectional prospective observational study.

BACKGROUND: Accurate estimation of fetal weight is important for prenatal care and for detection of fetal growth abnormalities. Prediction of fetal weight entails the indirect measurement of fetal biometry by ultrasound that is then introduced into formulae to calculate the estimated fetal weight. The aim of our study was to evaluate the accuracy of fetal weight estimation of Chinese fetuses in the third trimester using an automated three-dimensional (3D) fractional limb volume model, and to compare this model with the traditional two-dimensional (2D) model. METHODS: Prospective 2D and 3D ultrasonography were performed among women with singleton pregnancies 7 days before delivery to obtain 2D data, including fetal biparietal diameter, abdominal circumference and femur length, as well as 3D data, including the fractional arm volume (AVol) and fractional thigh volume (TVol). The fetal weight was estimated using the 2D model and the 3D fractional limb volume model respectively. Percentage error was defined as (estimated fetal weight - actual birth weight) divided by actual birth weight and multiplied by 100. Systematic errors (accuracy) were evaluated as the mean percentage error (MPE). Random errors (precision) were calculated as ±1 SD of percentage error. The intraclass correlation coefficient (ICC) was used to analyze the inter-observer reliability of the 3D ultrasound measurements of fractional limb volume. RESULTS: Ultrasound examination was performed on 56 fetuses at 39.6 ± 1.4 weeks' gestation. The average birth weight of the newborns was 3393 ± 530 g. The average fetal weight estimated by the 2D model was 3478 ± 467 g, and the MPE was 3.2 ± 8.9. The average fetal weights estimated by AVol and TVol of the 3D model were 3268 ± 467 g and 3250 ± 485 g, respectively, and the MPEs were - 3.3 ± 6.6 and - 3.9 ± 6.1, respectively. For the 3D TVol model, the proportion of fetuses with estimated error ≤ 5% was significantly higher than that of the 2D model (55.4% vs. 33.9%, p < 0.05). For fetuses with a birth weight < 3500 g, the accuracy of the AVol and TVol models were better than the 2D model (- 0.8 vs. 7.0 and - 2.8 vs. 7.0, both p < 0.05). Moreover, for these fetuses, the proportions of estimated error ≤ 5% of the AVol and TVol models were 58.1 and 64.5%, respectively, significantly higher than that of the 2D model (19.4%) (both p < 0.05). The inter-observer reliability of measuring fetal AVol and TVol were high, with the ICCs of 0.921 and 0.963, respectively. CONCLUSION: In this cohort, the automated 3D fractional limb volume model improves the accuracy of weight estimation in most third-trimester fetuses. Prediction accuracy of the 3D model for neonatal BW, particularly < 3500 g was higher than that of the traditional 2D model.

Impact of different conditions of breath-holding on the results of renal artery Doppler sonography: A pilot study.

PURPOSE: To investigate the impact of different breath-holding conditions on the results of renal artery Doppler ultrasonography (RADS). METHODS: In 45 healthy volunteers, we performed RADS examination during breath-holding while breathing naturally and after a deep inspiration. We measured and compared peak systolic flow velocity (PSV), end diastolic velocity (EDV), and resistance index (RI) of the right (RRA) and left (LRA) renal artery, and PSV, EDV, RI, acceleration time and acceleration index (AI) of the right and left interlobar arteries. RESULTS: The RRA and LRA PSV were, respectively, 76 ± 13 cm/s and 77 ± 15 cm/s under natural breathing and 93 ± 18 cm/s and 89 ± 24 cm/s after deep inspiration (P ≤ .001). The RRA and LRA EDV were also greater at deep inspiration (P < .001 and P = .019, respectively). There was no significant difference in RRA or LRA RI. The PSV, RI, and AI of the right and left interlobar arteries were greater after deep inspiration (P ≤ .001), without difference in AI. CONCLUSION: Breath-holding conditions may influence Doppler measurements of renal artery flow velocity and should be reported and taken into account.

An M1-like Macrophage Polarization in Decidual Tissue during Spontaneous Preterm Labor That Is Attenuated by Rosiglitazone Treatment.

Decidual macrophages are implicated in the local inflammatory response that accompanies spontaneous preterm labor/birth; however, their role is poorly understood. We hypothesized that decidual macrophages undergo a proinflammatory (M1) polarization during spontaneous preterm labor and that PPARγ activation via rosiglitazone (RSG) would attenuate the macrophage-mediated inflammatory response, preventing preterm birth. In this study, we show that: 1) decidual macrophages undergo an M1-like polarization during spontaneous term and preterm labor; 2) anti-inflammatory (M2)-like macrophages are more abundant than M1-like macrophages in decidual tissue; 3) decidual M2-like macrophages are reduced in preterm pregnancies compared with term pregnancies, regardless of the presence of labor; 4) decidual macrophages express high levels of TNF and IL-12 but low levels of peroxisome proliferator-activated receptor γ (PPARγ) during spontaneous preterm labor; 5) decidual macrophages from women who underwent spontaneous preterm labor display plasticity by M1↔M2 polarization in vitro; 6) incubation with RSG reduces the expression of TNF and IL-12 in decidual macrophages from women who underwent spontaneous preterm labor; and 7) treatment with RSG reduces the rate of LPS-induced preterm birth and improves neonatal outcomes by reducing the systemic proinflammatory response and downregulating mRNA and protein expression of NF-κB, TNF, and IL-10 in decidual and myometrial macrophages in C57BL/6J mice. In summary, we demonstrated that decidual M1-like macrophages are associated with spontaneous preterm labor and that PPARγ activation via RSG can attenuate the macrophage-mediated proinflammatory response, preventing preterm birth and improving neonatal outcomes. These findings suggest that the PPARγ pathway is a new molecular target for future preventative strategies for spontaneous preterm labor/birth.

Invariant NKT Cell Activation Induces Late Preterm Birth That Is Attenuated by Rosiglitazone.

Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality worldwide. Although intra-amniotic infection is a recognized cause of spontaneous preterm labor, the noninfection-related etiologies are poorly understood. In this article, we demonstrated that the expansion of activated CD1d-restricted invariant NKT (iNKT) cells in the third trimester by administration of α-galactosylceramide (α-GalCer) induced late PTB and neonatal mortality. In vivo imaging revealed that fetuses from mice that underwent α-GalCer-induced late PTB had bradycardia and died shortly after delivery. Yet, administration of α-GalCer in the second trimester did not cause pregnancy loss. Peroxisome proliferator-activated receptor (PPAR)γ activation, through rosiglitazone treatment, reduced the rate of α-GalCer-induced late PTB and improved neonatal survival. Administration of α-GalCer in the third trimester suppressed PPARγ activation, as shown by the downregulation of Fabp4 and Fatp4 in myometrial and decidual tissues, respectively; this suppression was rescued by rosiglitazone treatment. Administration of α-GalCer in the third trimester induced an increase in the activation of conventional CD4(+) T cells in myometrial tissues and the infiltration of activated macrophages, neutrophils, and mature dendritic cells to myometrial and/or decidual tissues. All of these effects were blunted after rosiglitazone treatment. Administration of α-GalCer also upregulated the expression of inflammatory genes at the maternal-fetal interface and systemically, and rosiglitazone treatment partially attenuated these responses. Finally, an increased infiltration of activated iNKT-like cells in human decidual tissues is associated with noninfection-related preterm labor/birth. Collectively, these results demonstrate that iNKT cell activation in vivo leads to late PTB by initiating innate and adaptive immune responses and suggest that the PPARγ pathway has potential as a target for prevention of this syndrome.

Lipidomic analysis of patients with microbial invasion of the amniotic cavity reveals up-regulation of leukotriene B4.

Bioactive lipids derived from the metabolism of polyunsaturated fatty acids are important mediators of the inflammatory response. Labor per se is considered a sterile inflammatory process. Intra-amniotic inflammation (IAI) due to microorganisms (i.e., intra-amniotic infection) or danger signals (i.e., sterile IAI) has been implicated in the pathogenesis of preterm labor and clinical chorioamnionitis at term. Early and accurate diagnosis of microbial invasion of the amniotic cavity (MIAC) requires analysis of amniotic fluid (AF). It is possible that IAI caused by microorganisms is associated with a stereotypic lipidomic profile, and that analysis of AF may help in the identification of patients with this condition. To test this hypothesis, we analyzed the fatty acyl lipidome of AF by liquid chromatography-mass spectrometry from patients in spontaneous labor at term and preterm gestations. We report that the AF concentrations of proinflammatory lipid mediators of the 5-lipoxygenase pathway are significantly higher in MIAC than in cases of sterile IAI. These results suggest that the concentrations of 5-lipoxygenase metabolites of arachidonic acid, 5-hydroxyeicosatetraenoic acid, and leukotriene B4 in particular could serve as potential biomarkers of MIAC. This finding could have important implications for the rapid identification of patients who may benefit from anti-microbial treatment.-Maddipati, K. R., Romero, R., Chaiworapongsa ,T., Chaemsaithong, P., Zhou, S.-L., Xu, Z., Tarca, A. L., Kusanovic, J. P., Gomez, R., Chaiyasit, N., Honn, K. V. Lipidomic analysis of patients with microbial invasion of the amniotic cavity reveals up-regulation of leukotriene B4.

The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study.

OBJECTIVE: Pregnancy is accompanied by dramatic physiological changes in maternal plasma proteins. Characterization of the maternal plasma proteome in normal pregnancy is an essential step for understanding changes to predict pregnancy outcome. The objective of this study was to describe maternal plasma proteins that change in abundance with advancing gestational age and determine biological processes that are perturbed in normal pregnancy. STUDY DESIGN: A longitudinal study included 43 normal pregnancies that had a term delivery of an infant who was appropriate for gestational age without maternal or neonatal complications. For each pregnancy, 3 to 6 maternal plasma samples (median, 5) were profiled to measure the abundance of 1125 proteins using multiplex assays. Linear mixed-effects models with polynomial splines were used to model protein abundance as a function of gestational age, and the significance of the association was inferred via likelihood ratio tests. Proteins considered to be significantly changed were defined as having the following: (1) >1.5-fold change between 8 and 40 weeks of gestation; and (2) a false discovery rate-adjusted value of P < .1. Gene ontology enrichment analysis was used to identify biological processes overrepresented among the proteins that changed with advancing gestation. RESULTS: The following results were found: (1) Ten percent (112 of 1125) of the profiled proteins changed in abundance as a function of gestational age; (2) of the 1125 proteins analyzed, glypican-3, sialic acid-binding immunoglobulin-type lectin-6, placental growth factor, C-C motif-28, carbonic anhydrase 6, prolactin, interleukin-1 receptor 4, dual-specificity mitogen-activated protein kinase 4, and pregnancy-associated plasma protein-A had more than a 5-fold change in abundance across gestation (these 9 proteins are known to be involved in a wide range of both physiological and pathological processes, such as growth regulation, embryogenesis, angiogenesis immunoregulation, inflammation etc); and (3) biological processes associated with protein changes in normal pregnancy included defense response, defense response to bacteria, proteolysis, and leukocyte migration (false discovery rate, 10%). CONCLUSION: The plasma proteome of normal pregnancy demonstrates dramatic changes in both the magnitude of changes and the fraction of the proteins involved. Such information is important to understand the physiology of pregnancy and the development of biomarkers to differentiate normal vs abnormal pregnancy and determine the response to interventions.