Dataset Information

Proteomics and metabolomics of different delivery modes in human pregnancy

ABSTRACT: This project investigates the impact of different delivery modes and labor on maternal and neonatal health by analyzing 40 participants, including 16 spontaneous vaginal deliveries (VD), 16 prelabor cesarean deliveries (CS), and 8 intrapartum cesarean sections (Intra_CS). Using label-free proteomics and untargeted metabolomics, both amniotic fluid and cord blood samples were analyzed respectively to identify variations in protein and metabolite profiles associated with the mode of delivery. The study aims to uncover biological pathways influenced by labor and delivery mode, providing insights into how these factors shape maternal and neonatal outcomes, with implications for improving perinatal care and long-term health strategies.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood

SUBMITTER: Yun Huang

LAB HEAD: Yun Huang

PROVIDER: PXD058131 | Pride | 2025-05-07

REPOSITORIES: Pride

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Publications

Integrated proteomics and metabolomics network analysis across different delivery modes in human pregnancy: a pilot study.

Huang Yun Y Ni Yanyan Y Meng Yu Y Zeng Xiaojing X He Xiaoqing X Zhang Lin L Zhang Jun J

BMC pregnancy and childbirth 20241226 1

<h4>Background</h4>Delivery mode has been linked to child health, e.g., allergic disease. However, it remains unclear whether protein and metabolite differences across different delivery modes may underlie child development.<h4>Methods</h4>A cohort comprising 16 spontaneous onset vaginal delivery (VD), 16 prelabor cesarean delivery on maternal request (CS), and 8 intrapartum cesarean section (Intra_CS) women were analyzed using label-free proteomic and untargeted metabolomics assays on amniotic ...[more]

PMID: 39725908

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Project description:<p>We performed genome-wide association studies (GWAS) to study the Spontaneous Preterm birth (SPTB).</p> <p>Maternal and neonatal DNA from 743 SPTB (20 to and less than 34 weeks), and 752 controls (39 to and less than 42 weeks) who fully consented for public research usage were collected from participants in several clinical centers in Alabama, Illinois, New York, North Carolina, Rhode Island, Texas, and Utah. Cases were 1:1-matched with controls according to race/ethnicity (White, Hispanics, African Americans, and Others), maternal age (<20, 20-29, 30-39, 40+), and parity (yes or no). To determine the case-control status for each participant, a Gestational Age (GA) was determined.</p> <p>DNA samples were taken from blood or saliva if blood was not available. Automated DNA extractions were performed on the Qiagen M48 robot, and samples were organized in 96-well plates with barcoding and sample tracking systems. Subsequent manipulations were performed on the Biomek FX liquid handling workstation with 96-channel pipetting. DNA quantitation was performed by dye-based assay on a Molecular Devices SpectraMax Plus plate reader. Samples were genotyped using Affymetrix Genome-Wide Human SNP Array 6.0. This work was conducted at the Microarray Facility at the University of Pennsylvania.</p> <p>Patient data were collected through chart reviews and patient interviews, which included Demographic information (parental age, race, ethnicity, etc.); Medical history (pre-pregnancy weight, height, medications, STD history, medical conditions, etc.); Social history (marital status, years of education, alcohol use and tobacco use); Obstetrical history including outcome of all prior pregnancies and dates of termination; History of preterm labor or premature rupture of membranes symptoms, evaluation or hospitalization for those symptoms in current pregnancy; Medications taken during current pregnancy; History of cervical evaluation (manually or ultrasonographically) or fetal fibronectin measurements; Pregnancy complications; Labor (type, indications, membrane status, and induction method); Delivery type and indications for cesarean section; Neonatal outcome (sex, weight, length, Apgar score, neonatal complications, admission to intensive care unit, etc.); and Maternal family history of SPTB.</p>

Project description:The rate of cesarean delivery (CD) in China has risen sharply and the high rate was reported to be associated with increased risk of disease in the offspring. However, there is little research on the molecular mechanism of critical pathways and gene signatures involved in the neonatal immunity of cesarean-born infants. This study was undertaken to identify unique gene signatures which was involved in the neonatal immunity of cesarean-born infants through large-scale RNA-sequencing. Genes differentially expressed in cesarean-born infants were identified and further validated through quantitative real-time PCR (RT-qPCR). Moreover, we employed weighted gene co-expression network analysis (WGCNA) to identify highly connected genes that were correlated with neonatal inflammation. In total, 73 differentially expressed genes (DEGs) were identified between cesarean-born infants and normal vagina childbirth. The results obtained by secondary validation indicated that GATM, MIF, IFI27, IL1B, CA1, and EPHB1 were significantly upregulated in phenotype CD, while CYP2A6 and DLK1 were significantly down regulated. Further, functional and pathway enrichment analysis reveals perturbation of several DEGs involved in signaling pathways pertaining to immunoregulation, inflammation, apoptosis, and nervous development. Additionally, HLA-DOB popped out as a core gene in the process of inflammation, which might indicate the risk of cesarean-born infants for inflammatory disease. Notably, our study for the first time has documented gene signatures PIK3CA, PTPRC, SOS1, IL6ST, and MALT1, which were found to be involved in neonatal inflammation. Taken together, the full expression repertoire including the differentially expressed gene sets and core differentially co-expressed genes should provide an excellent resource for identifying potential biomarkers of cesarean-born infants with inflammation, and formulating new hypotheses for physiological functions and the discovery of novel therapeutic targets for inflammatory disease.

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