Maternal Multiomic Changes Could Predict Onset of Labor
By LabMedica International staff writers Posted on 18 May 2021 |

Image: Multiomic prediction of time to labor from biomarkers in maternal blood (Photo courtesy of STELZER ET AL.)
Currently, predictions of when labor will start are imprecise and based on gestational age and an average pregnancy length of 40 weeks, even though the onset of labor between week 37 and 42 of pregnancy is considered normal. Having a better idea of when labor may arrive could help with planning and managing medical concerns like fetal lung maturation.
As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is crucial to understanding these physiological transitions and identifying predictive biomarkers of delivery.
A large team of multidisciplinary scientists led by Stanford University School of Medicine (Palo Alto, CA, USA) followed more than 60 women toward the end of their pregnancies, collecting blood samples for metabolic, protein, and immune analysis. They collected a median of three blood samples from each participant within the 100 days preceding labor. Using untargeted mass spectrometry and an aptamer-based proteomic platform, the team tallied the levels of 3,529 metabolites and 1,317 proteins, while using a mass cytometry assay to gauge nearly 2,300 immune features over time.
The investigators pieces together a picture of the changes that occur in the two to four weeks prior to delivery. For instance, the levels of steroid hormones like progesterone and cortisol rose dramatically. At the same time, levels of factors involved in angiogenesis fell; a change they said could help weaken the connection between the uterus and the placenta, priming them for delivery.
Additional shifts affected the immune system. There was a rise in interleukin-1 receptor type 4 (IL-1R4) levels, which inhibits the inflammatory factor IL-33, suggesting that this change may tamp down inflammatory responses that might otherwise be triggered during labor. In addition, the increase in IL-1R4 levels could serve a labor-initiation signal. By feeding these changes into a model, the scientists developed a tool to predict when someone is about to go into labor. After training on their 53 cohort members, they tested their predictor on data from a further 10 women to find that it had high accuracy in predicting the time to labor. They further noted that the model could predict both preterm and term labor.
Virginia Winn, MD, an associate professor of obstetrics and gynecology and co-author of the study, said, “If we understand what's regulating labor, we might be able to do a better job of inducing labor.” The study was published on May 5, 2021 in the journal Science Translational Medicine.
Related Links:
Stanford University School of Medicine
As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is crucial to understanding these physiological transitions and identifying predictive biomarkers of delivery.
A large team of multidisciplinary scientists led by Stanford University School of Medicine (Palo Alto, CA, USA) followed more than 60 women toward the end of their pregnancies, collecting blood samples for metabolic, protein, and immune analysis. They collected a median of three blood samples from each participant within the 100 days preceding labor. Using untargeted mass spectrometry and an aptamer-based proteomic platform, the team tallied the levels of 3,529 metabolites and 1,317 proteins, while using a mass cytometry assay to gauge nearly 2,300 immune features over time.
The investigators pieces together a picture of the changes that occur in the two to four weeks prior to delivery. For instance, the levels of steroid hormones like progesterone and cortisol rose dramatically. At the same time, levels of factors involved in angiogenesis fell; a change they said could help weaken the connection between the uterus and the placenta, priming them for delivery.
Additional shifts affected the immune system. There was a rise in interleukin-1 receptor type 4 (IL-1R4) levels, which inhibits the inflammatory factor IL-33, suggesting that this change may tamp down inflammatory responses that might otherwise be triggered during labor. In addition, the increase in IL-1R4 levels could serve a labor-initiation signal. By feeding these changes into a model, the scientists developed a tool to predict when someone is about to go into labor. After training on their 53 cohort members, they tested their predictor on data from a further 10 women to find that it had high accuracy in predicting the time to labor. They further noted that the model could predict both preterm and term labor.
Virginia Winn, MD, an associate professor of obstetrics and gynecology and co-author of the study, said, “If we understand what's regulating labor, we might be able to do a better job of inducing labor.” The study was published on May 5, 2021 in the journal Science Translational Medicine.
Related Links:
Stanford University School of Medicine
Latest Immunology News
- Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer
- Machine Learning-Enabled Blood Test Predicts Immunotherapy Response in Lymphoma Patients
- Post-Treatment Blood Test Could Inform Future Cancer Therapy Decisions
- Cerebrospinal Fluid Test Predicts Dangerous Side Effect of Cancer Treatment
- New Test Measures Preterm Infant Immunity Using Only Two Drops of Blood
- Simple Blood Test Could Help Choose Better Treatments for Patients with Recurrent Endometrial Cancer
- Novel Analytical Method Tracks Progression of Autoimmune Diseases
- 3D Bioprinted Gastric Cancer Model Uses Patient-Derived Tissue Fragments to Predict Drug Response
- Blood Test for Fungal Infections Could End Invasive Tissue Biopsies
- Cutting-Edge Microscopy Technology Enables Tailored Rheumatology Therapies
- New Discovery in Blood Immune Cells Paves Way for Parkinson's Disease Diagnostic Test
- AI Tool Uses Routine Blood Tests to Predict Immunotherapy Response for Various Cancers
- Blood Test Can Predict How Long Vaccine Immunity Will Last
- Microfluidic Chip-Based Device to Measure Viral Immunity
Channels
Molecular Diagnostics
view channel
Blood Biomarker Test Could Detect Genetic Predisposition to Alzheimer’s
New medications for Alzheimer’s disease, the most common form of dementia, are now becoming available. These treatments, known as “amyloid antibodies,” work by promoting the removal of small deposits from... Read more
Novel Autoantibody Against DAGLA Discovered in Cerebellitis
Autoimmune cerebellar ataxias are strongly disabling disorders characterized by an impaired ability to coordinate muscle movement. Cerebellar autoantibodies serve as useful biomarkers to support rapid... Read more
Gene-Based Blood Test Accurately Predicts Tumor Recurrence of Advanced Skin Cancer
Melanoma, an aggressive form of skin cancer, becomes extremely difficult to treat once it spreads to other parts of the body. For patients with metastatic melanoma tumors that cannot be surgically removed... Read moreHematology
view channel
New Scoring System Predicts Risk of Developing Cancer from Common Blood Disorder
Clonal cytopenia of undetermined significance (CCUS) is a blood disorder commonly found in older adults, characterized by mutations in blood cells and a low blood count, but without any obvious cause or... Read more
Non-Invasive Prenatal Test for Fetal RhD Status Demonstrates 100% Accuracy
In the United States, approximately 15% of pregnant individuals are RhD-negative. However, in about 40% of these cases, the fetus is also RhD-negative, making the administration of RhoGAM unnecessary.... Read moreImmunology
view channel
Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer
Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more
Machine Learning-Enabled Blood Test Predicts Immunotherapy Response in Lymphoma Patients
Chimeric antigen receptor (CAR) T-cell therapy has emerged as one of the most promising recent developments in the treatment of blood cancers. However, over half of non-Hodgkin lymphoma (NHL) patients... Read moreMicrobiology
view channel
Handheld Device Delivers Low-Cost TB Results in Less Than One Hour
Tuberculosis (TB) remains the deadliest infectious disease globally, affecting an estimated 10 million people annually. In 2021, about 4.2 million TB cases went undiagnosed or unreported, mainly due to... Read more
New AI-Based Method Improves Diagnosis of Drug-Resistant Infections
Drug-resistant infections, particularly those caused by deadly bacteria like tuberculosis and staphylococcus, are rapidly emerging as a global health emergency. These infections are more difficult to treat,... Read more
Breakthrough Diagnostic Technology Identifies Bacterial Infections with Almost 100% Accuracy within Three Hours
Rapid and precise identification of pathogenic microbes in patient samples is essential for the effective treatment of acute infectious diseases, such as sepsis. The fluorescence in situ hybridization... Read morePathology
view channel
Novel UV and Machine Learning-Aided Method Detects Microbial Contamination in Cell Cultures
Cell therapy holds great potential in treating diseases such as cancers, inflammatory conditions, and chronic degenerative disorders by manipulating or replacing cells to restore function or combat disease.... Read more
New Error-Corrected Method to Help Detect Cancer from Blood Samples Alone
"Liquid biopsy" technology, which relies on blood tests for early cancer detection and monitoring cancer burden in patients, has the potential to transform cancer care. However, detecting the mutational... Read more
"Metal Detector" Algorithm Hunts Down Vulnerable Tumors
Scientists have developed an algorithm capable of functioning as a "metal detector" to identify vulnerable tumors, marking a significant advancement in personalized cancer treatment. This breakthrough... Read more
Novel Technique Uses ‘Sugar’ Signatures to Identify and Classify Pancreatic Cancer Cell Subtypes
Pancreatic cancer is often asymptomatic in its early stages, making it difficult to detect until it has progressed. Consequently, only 15% of pancreatic cancers are diagnosed early enough to allow for... Read moreTechnology
view channel
Disposable Microchip Technology Could Selectively Detect HIV in Whole Blood Samples
As of the end of 2023, approximately 40 million people globally were living with HIV, and around 630,000 individuals died from AIDS-related illnesses that same year. Despite a substantial decline in deaths... Read more
Pain-On-A-Chip Microfluidic Device Determines Types of Chronic Pain from Blood Samples
Chronic pain is a widespread condition that remains difficult to manage, and existing clinical methods for its treatment rely largely on self-reporting, which can be subjective and especially problematic... Read more
Innovative, Label-Free Ratiometric Fluorosensor Enables More Sensitive Viral RNA Detection
Viruses present a major global health risk, as demonstrated by recent pandemics, making early detection and identification essential for preventing new outbreaks. While traditional detection methods are... Read moreIndustry
view channel
Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions
Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more
Grifols and Tecan’s IBL Collaborate on Advanced Biomarker Panels
Grifols (Barcelona, Spain), one of the world’s leading producers of plasma-derived medicines and innovative diagnostic solutions, is expanding its offer in clinical diagnostics through a strategic partnership... Read more