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Published in: Journal of Assisted Reproduction and Genetics 7/2014

01-07-2014 | Genetics

Gene-environment interaction among GSTT1, PON2 polymorphisms and organic solvents on gestational age in a Chinese women cohort

Authors: Shuai Li, Kai Fang, Wenjian Wang, Yonghua Hu, Dafang Chen

Published in: Journal of Assisted Reproduction and Genetics | Issue 7/2014

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Abstract

Purpose

To investigate interactions on gestational age among two environmental risk factors and four maternal genetic polymorphisms: organic solvents, passive smoking, CYP1A1 rs4646903 (MspI), EPHX1 rs2234922 (His139Arg), GSTT1 and PON2 rs12026 (Ala148Gly).

Methods

A pregnant women cohort was conducted at Beijing Yanshan Petrochemical Corporation, and 1,097 mothers with live singleton births were included in analysis. Generalized Multifactor Dimensionality Reduction (GMDR) method was used to explore interactions among these factors with adjustment for important potential confounders. Multiple linear regression models were used to estimate the association of interaction with gestational age.

Results

A three-factor model of organic solvents, GSTT1 and PON2 rs12026 had the highest testing balanced accuracy (57.05 %) and best cross-validation consistency (10/10). Compared with organic solvents unexposed mothers with GSTT1 non-null genotype and PON2 rs12026 CC genotype, organic solvents exposed mothers with GSTT1 null genotype and PON2 rs12026 CG + GG genotype had the largest reduction in gestational age (−0.36 weeks, 95%CI: −0.70 to −0.02). The significant reductions in different groups were from 0.24 weeks to 0.36 weeks.

Conclusions

Maternal genetic susceptibility GSTT1 and PON2 rs12026 could significantly modify the association of organic solvents with gestational age.
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Metadata
Title
Gene-environment interaction among GSTT1, PON2 polymorphisms and organic solvents on gestational age in a Chinese women cohort
Authors
Shuai Li
Kai Fang
Wenjian Wang
Yonghua Hu
Dafang Chen
Publication date
01-07-2014
Publisher
Springer US
Published in
Journal of Assisted Reproduction and Genetics / Issue 7/2014
Print ISSN: 1058-0468
Electronic ISSN: 1573-7330
DOI
https://doi.org/10.1007/s10815-014-0256-6

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