SLC9B1 methylation predicts fetal intolerance of labor

ABSTRACT

Fetal intolerance of labor is a common indication for delivery by Caesarean section. Diagnosis is based on the presence of category III fetal heart rate tracing, which is an abnormal heart tracing associated with increased likelihood of fetal hypoxia and metabolic acidemia. This study analyzed data from 177 unique women who, during their prenatal visits (7-15 weeks and/or 24–32 weeks) to Atlanta area prenatal care clinics, consented to provide blood samples for DNA methylation (HumanMethylation450 BeadChip) and gene expression (Human HT-12 v4 Expression BeadChip) analyses. We focused on 57 women aged 18–36 (mean 25.4), who had DNA methylation data available from their second prenatal visit. DNA methylation patterns at CpG sites across the genome were interrogated for associations with fetal intolerance of labor. Four CpG sites (P value <8.9 × 10⁻⁹, FDR <0.05) in gene SLC9B1, a Na⁺/H⁺ exchanger, were associated with fetal intolerance of labor. DNA methylation and gene expression were negatively associated when examined longitudinally during pregnancy using a linear mixed-effects model. Positive predictive values of methylation of these four sites ranged from 0.80 to 0.89, while negative predictive values ranged from 0.91 to 0.92. The four CpG sites were also associated with fetal intolerance of labor in an independent cohort (the Johns Hopkins Prospective PPD cohort). Therefore, fetal intolerance of labor could be accurately predicted from maternal blood samples obtained between 24–32 weeks gestation. Fetal intolerance of labor may be accurately predicted from maternal blood samples obtained between 24–32 weeks gestation by assessing DNA methylation patterns of SLC9B1. The identification of pregnant women at elevated risk for fetal intolerance of labor may allow for the development of targeted treatments or management plans.

KEYWORDS:

• Biomarker, complication
• delivery
• fetal distress; NHEDC1; pregnancy; SLC9B1; sodium hydrogen exchanger

Disclosure of potential conflicts of interest

No potential conflicts of interest were disclosed

Acknowledgements

We thank the Emory Integrated Genomics Core for processing DNA and RNA samples. We thank Samantha Resin for technical assistance. We also are grateful to the participants enrolled in this cohort who provided samples and medical records for this study.

Additional information

Funding

This work was supported by the National Institute on Minority Health and Health Disparities (NIMHD) of the National Institutes of Health, under [grant number R01MD009064]; the National Institute of Nursing Research (NINR) of the National Institutes of Health, under [grant number R01NR014800]. Salary support for AKK was provided by the National Institute of General Medical Sciences (T32GM008490).