Related Experiment Video
Updated: Jun 25, 2025
17:28
Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation
Published on: June 17, 2015
12.6K
Investigating neonatal health risk variables through cell-type specific methylome-wide association studies
Thomas L Campbell1, Lin Y Xie1, Ralen H Johnson1
1Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, P. O. Box 980533, Richmond, VA, 23298-0581, USA.
Clinical Epigenetics
|May 22, 2024
Summary
This study identifies common and unique factors in neonatal health risks using blood methylome data. These findings can improve infant health assessments and personalized care.
Area of Science:
- Neonatal Health
- Epigenetics
- Biomarker Discovery
Background:
- Adverse neonatal outcomes impact infant mortality and morbidity.
- Accurate assessment of neonatal health risks is crucial for prevention and care.
- Neonatal outcomes are often multifactorial and correlated.
Purpose of the Study:
- To enhance the assessment of neonatal health risks by identifying common and unique effects.
- To validate these effects using methylome-wide profiles from neonatal blood.
- To explore the potential of identified factors as clinical biomarkers.
Main Methods:
- Factor analysis was used to identify common and unique effects among nine neonatal risk variables.
- Methylome-wide profiles from 333 neonates' blood spots were analyzed.
- Cell-type specific methylome-wide association analyses and Gene Ontology analyses were performed for validation.
Main Results:
- Two common factors were identified: a 'size factor' and a 'disease factor'.
- Significant cell-type specific associations were found for common factors, gestational age, jaundice, and Apgar score.
- Gene Ontology analysis revealed biologically relevant terms for investigated risk variables.
Conclusions:
- Identified distinct factor effects (common and unique) in neonatal health risks.
- Biological profiles of these factors suggest their potential as clinical biomarkers.
- Findings support enhanced personalized care strategies for neonates.
