Investigating the genetic basis of human skeletal facial morphology

项目总结/摘要 人脸由独特的结构组成，这些结构构成了我们的身份。我们有有力的证据表明人类 颅面变异具有很高的遗传成分，受祖先和性别的影响。努力改善我们的 在过去的十年里，对“正常范围”面部变化的理解一直很有兴趣，因为它具有特殊的 对了解面部畸形病因的影响与疾病有关。近日一 在表型方面的进步，对使用准地标适用于3D面部扫描，丰富了我们的 与人脸有新的基因联系的知识。然而，这些和其他遗传信号可能 潜在地由于不知道皮肤下的面部骨骼信息而变得模糊。进行全面检查 人类面部结构的检查将是检查外部软组织结构和内部硬组织骨骼 同时，包括它们连接处的组织深度。从我们不断扩大的颅面 候选变异/基因，比以往任何时候都更重要的是准确地分类它们的具体贡献， 通过精确的地标位置，以及纠正内部的竞争结构， 面部结构通过这样做，我们有效地提供了一个更精确的分类的面部链接，无论是 针对组织或骨骼的变异。这一更明确的定义将有助于更有效地审查 这些变体如何串联工作以用于下游基因表达和功能分析工作。这种洞察力 还将为更准确的个性化颅面治疗干预铺平道路， 手术，更不用说更完整的面部视觉诊断。目前的建议有两个目的， 显著推进我们目前对正常范围人类颅面变化的理解：（1）我们将 通过构建一个密集的（数千个）顶点地图， 人骨骼，使用准界标有效地生成颅面骨骼掩模，其没有 还没有在实地使用。该模板将允许颅面的有效标准化定界。 骨使用MeshMonk配准;（2）利用新的锥形束计算机断层扫描面部 扫描（n=750），使我们能够将软组织与硬组织标志联系起来，确保其中一个是协变量 对照其他面部结构进行检查，并与超过350个面部结构的列表进行关联测试。 候选变体/基因。这种更精确的表型：基因型关联的方法还没有被发现。 其特征在于以这种方式从软组织矫正骨，反之亦然。我们也将首次 通过利用从这些标志收集的信息来生成准标志处的面部软组织厚度（FSTT 两个结构实体及其在空间上的连接。该项目旨在通过遗传关联确认 更完整的方法，同时面部标志的所有结构在人的脸，无论是外部 在内部，并辅以视觉效果来解释当前一些疾病的加性遗传效应 最有趣的变异/基因发现人类面部的变化。

PROJECT SUMMARY/ABSTRACT The human face consists of unique structures that form our identity. We have strong evidence that human craniofacial variation has a high genetic component, influenced by ancestry and sex. The effort to improve our understanding of ‘normal-range’ facial variation has been of great interest in the last decade as it has particular implications for understanding the etiology of malformations in the face related to disease. Recently, an advancement in phenotyping towards the use of quasi-landmarks applied to 3D facial scans has enriched our knowledge with new genetic links tied to the human face. However, these and other genetic signals may potentially be clouded by not knowing facial skeletal information underneath the skin. A complete examination of human facial structure would be to inspect both the outer soft tissue structure and the inner hard tissue bone concurrently, including the depth of tissue in their connection. From our ever-expanding list of craniofacial candidate variants/genes, it is more important than ever to accurately classify their specific contribution to the face’s development through accurate landmark placement, and correction of competing structures within the facial construct. By doing this, we effectively provide a more precise classification of the facial link, whether it is directed towards tissue or bone variation. This more explicit definition will allow a more efficient examination of how these variants work in tandem for downstream gene expression and functional analyses work. This insight would also pave the way for more accurate personalized therapeutic interventions for craniofacial treatment and surgery, not to mention a more complete face visual for diagnostics. The current proposal has two aims designed to significantly advance our current understanding of normal-range human craniofacial variation: (1) We will enhance current mesh landmarking procedures by building a dense (thousands) map of vertices across the human skeletal bone, effectively generating a craniofacial skeletal mask using quasi-landmarks, which has not yet been made available in the field. This template will allow efficient normalized landmarking of craniofacial bone using MeshMonk registration; (2) Utilizing a new collection of Cone Beam Computed Tomography facial scans (n=750), allows us to connect both soft tissue with hard tissue landmarks ensuring one is a covariate against the other facial structure being examined and perform association testing with a list of over 350 facial candidate variants/genes. This more precise method of phenotype:genotype association has not yet been characterized in such a manner, correcting bone from soft tissue and vice versa. For the first time, we shall also generate Facial Soft Tissue Thickness (FSTT) at quasi-landmarks by utilizing the information gleaned from these two structural entities and their connection in space. This project aims to confirm, with genetic association, a more complete methodology for concurrent facial landmarking of all structures in the human face, both externally and internally, and complement with visuals that explain the additive genetic effects of some of the currently most interesting variants/genes discovered for human facial variation.