Differences between the sexes among genetic variants affecting orofacial cleft birth defect risk

项目摘要 口面裂（OFC）是人类最常见的颅面畸形， 全球每千名活产婴儿中约有一人死亡。OFC包括唇裂（CL）、腭裂（CP）和唇裂伴 腭裂（CLP），它可以作为孤立的畸形发生，与另一个畸形或作为一个畸形的一部分， 公认的畸形综合征（通常为孟德尔畸形，伴有不完全的遗传）。OFC通常 根据胚胎学和流行病学分类为两种解剖学和胚胎学上不同的实体 类型：唇腭裂（CL/P）和单纯腭裂（CP）。在所有出生时患有 在OFC中，70%的CL/P病例和50%的CP病例是孤立的、非综合征性畸形。 非综合征型CL/P在男性中的发生率高于女性（比例为2：1），而非综合征型CP则发生在 更常见于女性（比例约为1：1.14）。非出生人口的出生率差异很大， 综合征性CL/P在人群中均有报告，亚洲人群的出生患病率较高 与欧洲人口相比，非洲人口的出生率最低。 OFC的风险显示出强有力的遗传控制证据，估计遗传力高达90%。最近的基因组- 广泛的关联研究已经清楚地表明，多个基因在OFC的病因学中起作用， 家庭和人群之间的巨大差异。到目前为止，大约有50种不同的基因 在全基因组的OFC研究中， 大量的复制和/或功能研究。然而，尽管科学研究的历史很长， 尽管OFC的遗传控制，但大部分遗传力仍然无法解释（这可能反映了遗传异质性 影响OFC的风险，其中具有罕见和常见变体的许多不同基因控制风险），以及 仍然很难清楚地确定潜在的致病基因。此外，OFC风险的性别差异， 传统上，父母的起源效应不是遗传学研究的重点，X染色体变异已经成为遗传学研究的重点。 基本上被忽略了。在这个应用程序中，我们正在使用现有的基因组数据，从家庭为基础的研究，在不同的 种族群体，专门研究潜在的机制，差异风险OFC之间的性别。 具体而言，我们将（i）使用病例-亲本三重奏来检测不同的遗传OFC风险效应大小和亲本来源 影响，（ii）使用一种新的方法来表征OFCs会计遗传结构的性别差异 潜在的裂缝类型差异和相似性，以及（iii）对X上的变体进行关联测试 染色体此外，我们将使用来自扩展的多重家系的基因组数据来鉴定高度 渗透性基因组X连锁变异体。基于家族的设计使我们能够研究常见和罕见的变异， 父母的原产地的影响，并允许我们评估从头变异的影响。在所有目标中，我们将尝试使用 从外部数据库中获取功能数据，对我们的发现进行“计算机模拟”验证。

PROJECT SUMMARY Orofacial clefts (OFCs) represent the most common group of craniofacial malformations in humans affecting approximately one per 1,000 live births worldwide. OFCs include cleft lip (CL), cleft palate (CP) and cleft lip with cleft palate (CLP), which can occur as isolated malformations, with another malformation or as part of a recognized malformation syndrome (often Mendelian with incomplete penetrance). OFCs are commonly categorized into two anatomically and embryologically distinct entities based on embryologic and epidemiologic patterns: cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP). Among all infants born with an OFC, 70 percent of CL/P cases and 50 percent of CP cases occur as isolated, non-syndromic malformations. Non-syndromic CL/P occurs more frequently in males than females (ratio 2:1) whereas non-syndromic CP occurs more often in females (ratio approximately 1:1.14). Substantial variation in birth prevalence rates of non- syndromic CL/P has been reported across populations, with Asian populations having higher birth prevalence rates compared to European populations, and African populations having the lowest birth prevalence rates. Risk to OFC shows strong evidence of genetic control with estimated heritability up to 90%. Recent genome- wide association studies have clearly shown multiple genes play a role in the etiology of OFCs, but with substantial heterogeneity among families and across populations. To date, approximately 50 different genes have been identified as significant in such genome-wide studies of OFCs, with about two dozen having substantial replication and/or functional studies. However, despite a long history of scientific research into the genetic control of OFC, much of the heritability remains unexplained (which may reflect the genetic heterogeneity influencing risk to OFC, where a number of different genes with both rare and common variants control risk), and it remains difficult to clearly identify underlying causal genes. Moreover, sex differences in risk to OFC and parent-of-origin effects traditionally have not been the focus of genetic studies, and X chromosome variants have largely been ignored. In this application, we are using existing genomic data from family-based studies in different ethnic groups to specifically study the underlying mechanisms for differential risk to OFC between the sexes. Specifically, we will (i) use case-parent trios to detect different genetic OFC risk effect sizes and parent of origin effects, (ii) use a novel method to characterize sex differences in the genetic architecture of OFCs accounting for potential cleft type differences and similarities, and (iii) conduct association tests for variants on the X chromosome. In addition, we will use genomic data from extended multiplex pedigrees to identify highly penetrant genomic X-linked variants. The family-based designs allow us to study common and rare variants, parent-of origin effects, and allow us to assess the impact of de novo variants. In all aims, we will attempt to use functional data from external data bases to conduct an “in silico” validation of our findings.