Human Plasma Proteome During Normal Pregnancy.
Adi Laurentiu TarcaRoberto RomeroGaurav BhattiFrancesca GotschBogdan DoneDereje W GudichaDahiana M GalloEunjung JungRoger Pique-RegiStanley M BerryTinnakorn ChaiworapongsaNardhy Gomez-LopezPublished in: Journal of proteome research (2022)
The human plasma proteome is underexplored despite its potential value for monitoring health and disease. Herein, using a recently developed aptamer-based platform, we profiled 7288 proteins in 528 plasma samples from 91 normal pregnancies (Gene Expression Omnibus identifier GSE206454). The coefficient of variation was <20% for 93% of analytes (median 7%), and a cross-platform correlation for selected key angiogenic and anti-angiogenic proteins was significant. Gestational age was associated with changes in 953 proteins, including highly modulated placenta- and decidua-specific proteins, and they were enriched in biological processes including regulation of growth, angiogenesis, immunity, and inflammation. The abundance of proteins corresponding to RNAs specific to populations of cells previously described by single-cell RNA-Seq analysis of the placenta was highly modulated throughout gestation. Furthermore, machine learning-based prediction of gestational age and of time from sampling to term delivery compared favorably with transcriptomic models (mean absolute error of 2 weeks). These results suggested that the plasma proteome may provide a non-invasive readout of placental cellular dynamics and serve as a blueprint for investigating obstetrical disease.
Keyphrases
- gestational age
- rna seq
- preterm birth
- single cell
- birth weight
- gene expression
- machine learning
- high throughput
- healthcare
- induced apoptosis
- public health
- dna methylation
- mental health
- gold nanoparticles
- magnetic resonance
- cell proliferation
- risk assessment
- pregnant women
- vascular endothelial growth factor
- endoplasmic reticulum stress
- artificial intelligence
- social media
- microbial community
- big data
- pregnancy outcomes
- cell death
- wound healing
- cell cycle arrest