Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-1-26
pubmed:abstractText
Prenatal exposures such as polycyclic aromatic hydrocarbons and early postnatal environmental exposures are of particular concern because of the heightened susceptibility of the fetus and infant to diverse environmental pollutants. Marked inter-individual variation in response to the same level of exposure was observed in both mothers and their newborns, indicating that susceptibility might be due to genetic factors. With the mother-child pair design, existing methods developed for parent-child trio data or random sample data are either not applicable or not designed to optimally use the information. To take full advantage of this unique design, which provides partial information on genetic transmission and has both maternal and newborn outcome status collected, we developed a likelihood-based method that uses both the maternal and the newborn information together and jointly models gene-environment interactions on maternal and newborn outcomes. Through intensive simulation studies, the proposed method has demonstrated much improved power in detecting gene-environment interactions. The application on a real mother-child pair data from a study conducted in Krakow, Poland, suggested four significant gene-environment interactions after multiple comparisons adjustment.
pubmed:grant
pubmed:commentsCorrections
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pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1098-2272
pubmed:author
pubmed:copyrightInfo
2009 Wiley-Liss, Inc.
pubmed:issnType
Electronic
pubmed:volume
34
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
125-32
pubmed:dateRevised
2011-7-22
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Methods for detecting interactions between genetic polymorphisms and prenatal environment exposure with a mother-child design.
pubmed:affiliation
Department of Biostatistics, Columbia University, New York, New York 10032, USA. sw2206@columbia.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural