Disease's type
GDM
Experimental grouping
GDM(n=13),Normal Glucose Tolerance(n=99)
GPT's summary
The study explores the potential of cell-free DNA and RNA from maternal plasma as biomarkers for predicting adverse pregnancy outcomes (APOs), including gestational diabetes, preeclampsia, and other placental disorders. By applying a new deconvolution method, researchers identified changes in placenta-specific DNA and differentially expressed genes in early pregnancy that correlate with APOs. They developed a predictive classifier showing high accuracy for APOs and moderate accuracy specifically for gestational diabetes.
RF's name
S100 Calcium Binding Protein A8
Sample's type
Maternal plasma and cord blood plasma
Gestational weeks
During the first trimester of pregnancy
Experiemental methods
qRT-PCR
Machine learning algorithms
Expectation-Maximization
Title
Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes
Evidence's type
Risk factor
Year
2021
Journal
Epigenetics
PMID