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
Matrix Metallopeptidase 8
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