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

项目总结 口面部裂(OFC)是人类头面部畸形中最常见的一组，影响 全世界大约每1000名活产儿中就有一名。OFC包括唇裂(CL)、腭裂(CP)和唇裂 腭裂(CLP)，可作为孤立畸形、伴有其他畸形或作为 公认的畸形综合征(常为孟德尔综合征，外露不全)。离岸金融中心通常 根据胚胎学和流行病学，在解剖学和胚胎学上分为两个截然不同的实体 类型：唇裂伴或不伴腭裂(CL/P)和单纯腭裂(CP)。在所有出生时患有AFP的婴儿中 OFC中，70%的CL/P病例和50%的CP病例发生为孤立的非综合征性畸形。 非综合征性CL/P发生在男性多于女性(比例为2：1)，而非综合征性CP发生在男性 女性更常见(比例约为1：1.14)。非老年人出生患病率有很大差异 综合征CL/P在所有人群中都有报道，亚洲人群的出生率更高 与欧洲人口的出生率相比，非洲人口的出生率最低。 对OFC的风险显示出基因控制的强有力证据，估计遗传力高达90%。最新的基因组- 广泛的关联研究清楚地表明，多个基因在OFCS的病因中起作用，但与 家庭之间和人口之间的巨大异质性。迄今为止，大约有50种不同的基因 在这种对OFCs的全基因组研究中被确定为重要的，大约有20多个 大量的复制和/或功能研究。然而，尽管对这一问题的科学研究历史悠久 OFC的遗传控制，大部分遗传力仍未解释(这可能反映了遗传异质性 影响OFC的风险，其中许多具有罕见和常见变异的不同基因控制风险)，以及 仍然很难清楚地确定潜在的原因基因。此外，OFC和OFC的风险存在性别差异 亲本效应历来不是遗传学研究的重点，而X染色体变异则是 很大程度上被忽视了。在这个应用程序中，我们使用了来自不同家庭研究的现有基因组数据 种族群体专门研究OFC风险在性别之间的差异的潜在机制。 具体地说，我们将(I)使用病例-父母三重组来检测不同的遗传OFC风险效应大小和起源的父母 影响，(Ii)使用一种新的方法来表征离岸金融中心会计遗传结构中的性别差异 潜在的裂隙类型差异和相似之处，以及(Iii)对X上的变异进行关联测试 染色体。此外，我们将使用来自扩展的多个家系的基因组数据来鉴定高度 穿透性基因组X连锁变异体。基于家族的设计让我们能够研究常见和罕见的变体， 亲本效应，并使我们能够评估从头变异的影响。在所有目标中，我们将尝试使用 来自外部数据库的功能数据对我们的发现进行“电子计算机”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.