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

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.