Journal article
Detecting Maternal-Fetal Genotype Interactions Associated With Conotruncal Heart Defects: A Haplotype-Based Analysis With Penalized Logistic Regression
Genetic epidemiology, Vol.38(3), pp.198-208
04/2014
DOI: 10.1002/gepi.21793
PMCID: PMC4043210
PMID: 24585533
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.
Details
- Title: Subtitle
- Detecting Maternal-Fetal Genotype Interactions Associated With Conotruncal Heart Defects: A Haplotype-Based Analysis With Penalized Logistic Regression
- Creators
- Ming Li - Department of Pediatrics University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaStephen W Erickson - Department of Biostatistics, University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaCharlotte A Hobbs - Department of Pediatrics University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaJingyun Li - Department of Pediatrics University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaXinyu Tang - Department of Pediatrics University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaTodd G Nick - Department of Pediatrics University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaStewart L Macleod - Department of Pediatrics University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaMario A Cleves - Department of Pediatrics University of Arkansas for Medical Sciences, Arkansas, Little Rock, United States of AmericaNational Birth Defect Prevention Study
- Contributors
- Paul A Romitti (Contributor) - University of Iowa, Epidemiology
- Resource Type
- Journal article
- Publication Details
- Genetic epidemiology, Vol.38(3), pp.198-208
- Publisher
- Blackwell Publishing Ltd
- DOI
- 10.1002/gepi.21793
- PMID
- 24585533
- PMCID
- PMC4043210
- ISSN
- 0741-0395
- eISSN
- 1098-2272
- Number of pages
- 11
- Grant note
- name: National Institute of Child Health and Human Development (NICHD), award: 5R01HD039054-12; name: National Center on Birth Defects and Developmental Disabilities (NCBDDD), award: 5U01DD000491-05; DOI: 10.13039/100008231, name: Arkansas Biosciences Institute
- Language
- English
- Date published
- 04/2014
- Academic Unit
- Epidemiology; Biostatistics
- Record Identifier
- 9984214826002771
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