A proteomic clock of human pregnancy

Area of Science:

• Proteomics and Molecular Biology
• Reproductive Medicine and Immunology

Background:

• Early detection of pregnancy pathologies requires molecular markers for timely intervention.
• Previous proteomic analyses were limited by assay technology, hindering comprehensive plasma protein examination.
• Developing predictive proteomic signatures for pregnancy outcomes has been challenging.

Purpose of the Study:

• To identify plasma proteins that precisely track gestational age during term pregnancy.
• To establish a proteomic model for predicting gestational age using a highly multiplexed platform.
• To investigate the functional attributes of identified proteins and their link to immunological changes.

Main Methods:

• Longitudinal plasma collection from pregnant women across trimesters and postpartum.
• Analysis using a highly multiplexed aptamer-based platform measuring 1310 plasma proteins.
• Application of elastic net algorithm, bootstrapping, and piecewise regression for model development and reduction.
• Gene ontology analysis to infer molecular functions and link to immune features.

Main Results:

• A 74-protein model accurately predicted gestational age (R=0.97), reducible to 8 proteins without significant loss of predictive power (R=0.91).
• Top predictive proteins included glypican 3, chorionic somatomammotropin hormone, and granulins.
• Proteins involved in the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway were enriched; chorionic somatomammotropin hormone showed strong correlation with STAT5 signaling in CD4 T cells.

Conclusions:

• Plasma proteome changes during term pregnancy function as a 'proteomic clock', enabling early diagnosis of pathologies.
• Combined analysis of multiple plasma proteins is crucial for accurate gestational age prediction.
• Chorionic somatomammotropin hormone is hypothesized to play a critical role in regulating T-cell function during pregnancy.