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Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain
Published on: July 12, 2012
Altered DNA methylation in neonates born large-for-gestational-age is associated with cardiometabolic risk in
Xian-Hua Lin1,2, Dan-Dan Wu1,2, Ling Gao1,2
1The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Insights
Infants born large-for-gestational-age (LGA) exhibit higher cholesterol and insulin levels, increasing cardiometabolic disease risk. Epigenetic changes in umbilical cord blood may underlie these lipid dysfunctions, identifying potential biomarkers.
Area of Science:
- Pediatric Endocrinology
- Epigenetics
- Cardiovascular Disease Risk
Background:
- Infants born large-for-gestational-age (LGA) are at increased risk for developing cardiometabolic diseases.
- The precise biological mechanisms linking LGA birth to later health issues remain largely undetermined.
Purpose of the Study:
- To investigate the association between LGA birth and cardiometabolic risk factors in early childhood.
- To explore genome-wide DNA methylation patterns in umbilical cord blood as potential mediators of LGA-associated metabolic dysfunction.
Main Methods:
- A cohort study comparing 58 LGA children and 123 appropriate-for-gestational-age (AGA) children (aged 3-6 years).
- Clinical measurements included anthropometrics, blood pressure, and metabolic assessments.
- Genome-wide DNA methylation analysis was performed on umbilical cord blood samples from LGA and AGA newborns using the 450K BeadChip.
Main Results:
- LGA children displayed significantly higher serum levels of total cholesterol (TC), LDL-c, insulin, and TC/HDL-c ratio compared to AGA children.
- Birth weight positively correlated with serum TC, LDL-c, and TC/HDL-c ratio.
- Genome-wide analysis identified 3459 methylation variable positions (MVPs), with 327 showing significant differences (≥7%) and mapping to 213 genes, including 16 linked to cardiovascular disease and 4 to hyperlipidemia.
Conclusions:
- Excess birth weight (LGA) is associated with increased risk of lipid dysfunction in young children.
- Epigenetic reprogramming of specific genes involved in cardiovascular disease may be a key mechanism.
- The identified genes represent potential biomarkers for early detection of cardiometabolic disease risk.
Background:
Infants being born Large-for-gestational-age (LGA) are prone to developing cardiometabolic disease. However, the underlying mechanisms remain unclear.
Results:
Clinical investigation showed that children born LGA had significantly higher serum level of total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-c), and insulin, ratio of TC/high-density lipoprotein-cholesterol (HDL-c) compared to children born appropriate for gestational age (AGA). Birth weight (BW) was positively correlated to TC, LDL-c, and the ratio of TC/HDL in serum. Genome-wide DNA methylation analyzed in umbilical cord blood of controls and macrosomia cases. We identified 3459 methylation variable positions (MVPs) achieving genome-wide significance (adjusted P-value < 0.05) with methylation differences of ≥ 5%. A total of 327 MVPs were filtered by methylation differences of ≥ 7% located within an island, which mapped to 213 genes. Function analysis using Ingenuity Pathway Analysis showed 16 genes enriched in "cardiovascular disease". Four genes included contributed to hyperlipidemia.
Materials And Methods:
Fifty-eight children aged 3-6 years born LGA and 123 subjects born AGA were enrolled. Anthropometric parameters and blood pressure (BP) were measured, and metabolic assessment was performed in all subjects. Genome-wide DNA methylation in umbilical blood was assayed by the 450K BeadChip in six AGA and six macrosomia newborns.
Conclusions:
Our data indicate that excess birth weight may increase the risk of lipid dysfunction in children aged 3-6 years. It might through reprogramming a group of genes correlated to cardiovascular disease. The genes identified in this study might be potential biomarker for cardiometabolic disease.
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