Study on the Mechanism of Early Delivery by Multi-Omics Analysis of Metabolites, Elements and Bacterial Flora in Amniotic Fluid

Significance of the topic

The global rate of preterm birth remains high, affecting one in ten deliveries and contributing significantly to neonatal morbidity and mortality. Amniotic fluid composition reflects fetal health, maternal environment, and the risk of early labor. Multi-omics integration provides a holistic view of biochemical, elemental, and microbial interactions that drive preterm delivery, guiding early intervention strategies.

Objectives and overview of the study

This investigation aimed to uncover mechanisms of early delivery through comprehensive multi-omics profiling of amniotic fluid from six pregnant women (three preterm, three term). Key objectives included:

• Metabolic profiling of primary metabolites and lipids.
• Quantification of trace elements and minerals.
• Characterization of microbial communities via full-length 16S rRNA sequencing.
• Integration with clinical delivery parameters to distinguish preterm from term births.

Methodology and Used instrumentation

Amniotic fluid samples were analyzed by:

• GCMS-TQ8040 NX gas chromatography–mass spectrometer: Detected ~488 metabolites, normalized with 2-isopropylmalic acid.
• EDX-7200 energy-dispersive X-ray fluorescence spectrometer: Measured 78 elements (Na to U) under helium; consistently detected Cl, K, Ca, S, P, Br.
• MinION Mk1C nanopore sequencer: Sequenced full-length 16S rRNA amplicons to identify ~396 bacterial species, ~20 per sample.

Data integration was performed using Shimadzu’s Multi-omics Analysis Package, facilitating PCA, volcano plots, and metabolic pathway mapping.

Main results and discussion

Volcano plot analysis revealed that preterm samples exhibited elevated levels of oleic acid, margaric acid, batyl alcohol, mystiphosphoric acid, and lauric acid. Elemental analysis showed increased phosphorus in a term subject with mixed infection, suggesting altered zinc-mediated antibacterial activity. Microbiome profiling grouped subjects into ureaplasma-infected, uninfected, and mixed-infection categories. Ureaplasma presence correlated with activation of glycolysis and pyrimidine metabolism, indicating enhanced ATP generation and nucleotide turnover. Correlation analyses based on product/substrate ratios further highlighted infection-associated metabolic imbalances.

Benefits and practical applications

• Identification of early biomarkers for preterm birth risk via combined metabolic, elemental, and microbial signatures.
• Potential for targeted therapies by tracking specific fatty acids and bacterial markers.
• A practical framework for integrating multi-omics in clinical diagnostics and maternal–fetal health research.

Future trends and potential uses

Emerging high-throughput multi-omics platforms and rapid sampling methods will enable real-time monitoring of pregnancy health. Integration of machine-learning algorithms with expanded datasets promises refined predictive models for preterm delivery. Inclusion of proteomics and advanced lipidomics may uncover novel therapeutic targets.

Conclusion

This study demonstrates that multi-omics analysis of amniotic fluid can reveal distinct metabolic and microbial patterns associated with preterm birth. Integrating metabolite, element, and microbiome data offers new insights into the mechanisms driving early labor and supports the development of predictive biomarkers.

Reference

1. WHO, Born too soon: decade of action on preterm birth, accessed April 9, 2024.
2. MSD, Amniotic fluid overview, accessed April 9, 2024.
3. Moony, Role of amniotic fluid in fetal protection, accessed April 9, 2024.
4. NIPT Japan, Characteristics of preterm birth risk factors, accessed April 9, 2024.
5. PubMed, Phosphate-to-zinc ratio as predictor of antibacterial activity, accessed April 9, 2024.