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A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects.
Huang, Manyan; Lyu, Chen; Liu, Nianjun; Nembhard, Wendy N; Witte, John S; Hobbs, Charlotte A; Li, Ming.
Afiliação
  • Huang M; Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA.
  • Lyu C; Department of Population Health, New York University Grossman School of Medicine, New York City, New York, USA.
  • Liu N; Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA.
  • Nembhard WN; Department of Epidemiology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
  • Witte JS; Department of Epidemiology and Population Health, Stanford University, Stanford, California, USA.
  • Hobbs CA; Department of Biomedical Data Sciences, Stanford University, Stanford, California, USA.
  • Li M; Rady Children's Institute for Genomic Medicine, San Diego, California, USA.
Genet Epidemiol ; 47(7): 475-495, 2023 10.
Article em En | MEDLINE | ID: mdl-37341229
ABSTRACT
The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estudo de Associação Genômica Ampla / Cardiopatias Congênitas Tipo de estudo: Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estudo de Associação Genômica Ampla / Cardiopatias Congênitas Tipo de estudo: Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article