一项基于基因的母婴基因型相互作用关联测试确定了与非综合征性先天性心脏缺陷相关的基因。

IF 1.7 4区 医学 Q3 GENETICS & HEREDITY
Manyan Huang, Chen Lyu, Nianjun Liu, Wendy N. Nembhard, John S. Witte, Charlotte A. Hobbs, Ming Li, the National Birth Defects Prevention Study
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引用次数: 0

摘要

先天性心脏缺陷(CHDs)的风险可能受到母体基因、胎儿基因及其相互作用的影响。现有的方法通常一次一个地测试母体和胎儿变异的影响,并且可能降低了检测具有较低次要等位基因频率的遗传变异的统计能力。在这篇文章中,我们提出了一种基于基因的母婴基因型相互作用关联测试(GATI-MFG),使用病例-母亲和对照-母亲设计。GATI-MFG可以整合基因或基因组区域内多种变体的影响,并评估母体和胎儿基因型的联合效应,同时考虑它们的相互作用。在模拟研究中,GATI-MFG比其他方法提高了统计能力,如在各种疾病情况下的单一变体测试和功能数据分析(FDA)。我们进一步将GATI-MFG应用于CHD的两阶段全基因组关联研究,以测试常见变异和罕见变异,使用来自国家出生缺陷预防研究(NBDPS)的947对CHD病例母婴对和1306对对照母婴对。在对23035个基因进行Bonferroni调整后,17号染色体TMEM107上的两个基因(p = 1.64e-06)和CTC1(p = 2.0e-06)在常见变异分析中被鉴定为与CHD显著相关。TMEM107基因调节纤毛生成和纤毛蛋白组成,并被发现与异位相关。CTC1基因在保护端粒免受降解方面发挥着重要作用,这被认为与心脏发生有关。总体而言,GATI-MFG在模拟中优于单一变体测试和美国食品药品监督管理局,应用于NBDPS样本的结果与支持TMEM107和CTC1与CHDs关联的现有文献一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A gene-based association test of interactions for maternal–fetal genotypes identifies genes associated with nonsyndromic congenital heart defects

A gene-based association test of interactions for maternal–fetal genotypes identifies genes associated with nonsyndromic congenital heart defects

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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来源期刊
Genetic Epidemiology
Genetic Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
4.40
自引率
9.50%
发文量
49
审稿时长
6-12 weeks
期刊介绍: Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations. Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.
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