Toggle Main Menu Toggle Search

Open Access padlockePrints

Two novel genetic variants in the mineralocorticoid receptor gene associated with spontaneous preterm birth

Lookup NU author(s): Dr Inge Christiaens



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Background: Preterm birth is the leading cause of mortality and morbidity in newborn infants. Its etiology is multifactorial with genes and environmental factors, including chronic maternal stress, contributing to its risk. Our objective was to investigate whether single nucleotide polymorphisms (SNPs) in genes involved in the stress response are associated with spontaneous preterm birth using a candidate gene approach.Methods: A total of 210 cases (singleton spontaneous preterm birth at < 37 weeks) and 412 controls (singleton term birth at 38-42 weeks without a history of preterm birth) were studied. High quality maternal DNA was available from saliva samples of 190 cases and 369 controls and compared. Sociodemographic and medical data were collected. Sixteen SNPs, either tag SNPs located in key genes involved in the stress response identified in the Preterm Birth Genome Project database or SNPs found to be associated with adverse mental health outcomes in the published literature, were selected for genotyping and sequencing. SNPs were genotyped using Taqman (R) SNP genotyping assays. Univariate and multivariate logistic regression were performed.Results: Multivariate analysis showed that two SNPs located in the mineralocorticoid receptor gene were significantly associated with spontaneous preterm birth: rs17484063 (OR 0.50, p = 0.038) and rs2883929 (OR 0.49, p = 0.017), regardless of maternal age, smoking, alcohol use, educational status, and history of spontaneous miscarriage.Conclusion: This report demonstrates an association between mineralocorticoid receptor gene polymorphisms, rs17484063 and rs2883929, and preterm birth, supporting a role for genetics in the association between chronic maternal stress and preterm birth. Potentially, this information may be used to predicting the risk of having a preterm delivery.

Publication metadata

Author(s): Christiaens I, Ang QW, Gordon LN, Fang X, Williams SM, Pennell CE, Olson DM

Publication type: Article

Publication status: Published

Journal: BMC Medical Genetics

Year: 2015

Volume: 16

Online publication date: 11/08/2015

Acceptance date: 21/07/2015

Date deposited: 01/10/2015

ISSN (electronic): 1471-2350

Publisher: BioMed Central Ltd.


DOI: 10.1186/s12881-015-0205-y


Altmetrics provided by Altmetric