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. 2014 Apr;38(3):198-208.
doi: 10.1002/gepi.21793. Epub 2014 Mar 2.

Detecting maternal-fetal genotype interactions associated with conotruncal heart defects: a haplotype-based analysis with penalized logistic regression

Ming Li  1 , Stephen W Erickson, Charlotte A Hobbs, Jingyun Li, Xinyu Tang, Todd G Nick, Stewart L Macleod, Mario A Cleves; National Birth Defect Prevention Study
Affiliations

Detecting maternal-fetal genotype interactions associated with conotruncal heart defects: a haplotype-based analysis with penalized logistic regression

Ming Li et al. Genet Epidemiol. 2014 Apr.

Abstract

Nonsyndromic congenital heart defects (CHDs) develop during embryogenesis as a result of a complex interplay between environmental exposures, genetics, and epigenetic causes. Genetic factors associated with CHDs may be attributed to either independent effects of maternal or fetal genes, or the intergenerational interactions between maternal and fetal genes. Detecting gene-by-gene interactions underlying complex diseases is a major challenge in genetic research. Detecting maternal-fetal genotype (MFG) interactions and differentiating them from the maternal/fetal main effects has presented additional statistical challenges due to correlations between maternal and fetal genomes. Traditionally, genetic variants are tested separately for maternal/fetal main effects and MFG interactions on a single-locus basis. We conducted a haplotype-based analysis with a penalized logistic regression framework to dissect the genetic effect associated with the development of nonsyndromic conotruncal heart defects (CTD). Our method allows simultaneous model selection and effect estimation, providing a unified framework to differentiate maternal/fetal main effect from the MFG interaction effect. In addition, the method is able to test multiple highly linked SNPs simultaneously with a configuration of haplotypes, which reduces the data dimensionality and the burden of multiple testing. By analyzing a dataset from the National Birth Defects Prevention Study (NBDPS), we identified seven genes (GSTA1, SOD2, MTRR, AHCYL2, GCLC, GSTM3, and RFC1) associated with the development of CTDs. Our findings suggest that MFG interactions between haplotypes in three of seven genes, GCLC, GSTM3, and RFC1, are associated with nonsyndromic conotruncal heart defects.

Keywords: National Birth Defects Prevention Study; adaptive LASSO; congenital heart defects; maternal-fetal interactions.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1. GSTA1 - Maternal Main Effect Only
Maternal haplotype H showed a dominance effect that will increase the risk of disease, while the risk of disease was unchanged by fetal genotypes.
Figure 2
Figure 2. SOD2 - Maternal Main Effect Only
Maternal haplotype H showed an additive effect that will increase the risk of disease, while the risk of disease was unchanged by fetal genotypes.
Figure 3
Figure 3. MTRR - Fetal Main Effect Only
Fetal haplotype H showed an additive effect that was protective of the disease, while the risk of disease was unchanged by maternal genotypes.
Figure 4
Figure 4. AHCYL2 - Fetal Main Effect Only
Fetal haplotype H showed an additive effect that was protective of the disease, while the risk of disease was unchanged by maternal genotypes.
Figure 5
Figure 5. GCLC – Both Maternal Main Effect and MFG Interaction Effect
Maternal and fetal genotypes showed interactive pattern in terms of disease risk, which is indicated by a pattern of “cross-over”. Maternal haplotype H also showed an additive effect that will increase the risk of disease.
Figure 6
Figure 6. RFC1 - MFG Interaction Effect Only
Maternal and fetal genotypes showed interactive pattern in terms of disease risk.
Figure 7
Figure 7. GSTM3 - MFG Interaction Effect Only
Maternal and fetal genotypes showed interactive pattern in terms of disease risk.
See this image and copyright information in PMC

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