3D Analysis of Normal Facial Variation: Data Repository and Genetics (Research)

正常面部变异的 3D 分析：数据存储库和遗传学（研究）

• 批准号: 7933834
• 负责人: Mary L. Marazita
• 金额: $ 39.09万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-21 至 2014-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7933834
• 关键词: Age; Appearance; Arts; Caucasians; Caucasoid Race; Cleaved cell; Clinical; Collection; Communities; Congenital Abnormality; Coupling; DNA; Data; Databases; Development; Dimensions; Disease; Face; Gender; General Population; Generations; Genes; Genetic; Genetic Determinism; Genetic Markers; Genetic Polymorphism; Genetic Research; Genotype; Goals; Housing; Human; Image; Imaging technology; Individual; Inherited; Maps; Measures; Methods; Morphogenesis; Morphology; Online Systems; Phenotype; Predisposition; Research; Research Personnel; Resource Development; Resources; Sampling; Site; Specific qualifier value; Structure; Study Subject; Surface; Testing; Three-Dimensional Image; Three-Dimensional Imaging; Three-dimensional analysis; Variant; Work; base; craniofacial; design; genetic risk factor; genome wide association study; genome-wide; improved; interest; novel; orofacial; public health relevance; repository

DESCRIPTION (provided by applicant): Although ample evidence exists that facial appearance and structure are highly heritable, there is a dearth of information regarding how variation in specific genes relates to the diversity of facial forms evident in our species. With the advent of affordable, non-invasive 3D surface imaging technology, it is now possible to capture detailed quantitative information about the face in a large number of individuals. By coupling state- of-the-art 3D imaging with advances in high-throughput genotyping, an unparalleled opportunity exists to map the genetic determinants of normal facial variation. An improved understanding of the relationship between genotype and facial phenotype may help illuminate the factors influencing liability to common craniofacial anomalies, particularly orofacial clefts, which are among the most prevalent birth defects in humans. This proposal has two major goals: (1) to construct a nonnative repository of 3D facial and genetic data and (2) to utilize this data repository to identify genes that influence normal midfacial variation. The first goal will focus on data generation and resource development and will involve the collection of 3D facial surface images and DNA samples on 3500 healthy Caucasian individuals (age 5-40) drawn from the general population. Quantitative facial measures will be extracted from the 3D images and all DNA samples will be genotyped for genome-wide SNP markers. Working in conjunction with the FaceBase hub, our intent is to create a scalable. Interactive and minable data resource available to outside investigators, which will contain facial measures, 3D images and genotypes. Ultimately, it is hoped that such a database w\\ facilitate novel research initiatives. To illustrate this potential, the second goal of this proposal will focus on identifying SNPs associated with variation in midfacial morphology, including those facial features relevant to orofacial cleft predisposition. Salient measures of midfacial morphology will be derived from 3D facial surface images, and a genome-wide association approach will then be employed to identify polymorphisms that influence quantitative variation in the facial features of interest. PUBLIC HEALTH RELEVANCE: Our proposal to establish a 3D facial and genetic marker database will benefit both the research and clinical community, by providing a resource to both test new hypotheses related to normal and abnormal craniofacial development and serve as a repository for normative control data. Furthermore, this project has the potential to identity genetic risk factors important for orofacial clefting.

描述（由申请人提供）：虽然有充分的证据表明，面部外观和结构是高度遗传的，但缺乏关于特定基因的变异如何与我们物种中明显的面部形式多样性相关的信息。随着经济实惠的非侵入性3D表面成像技术的出现，现在可以在大量个体中捕获有关面部的详细定量信息。通过将最先进的3D成像与高通量基因分型的进展相结合，存在着绘制正常面部变化的遗传决定因素的无与伦比的机会。更好地了解基因型和面部表型之间的关系可能有助于阐明影响常见颅面异常，特别是口面裂，这是人类最常见的出生缺陷的易感性的因素。该建议有两个主要目标：（1）构建3D面部和遗传数据的非本地存储库，以及（2）利用该数据存储库来识别影响正常面中部变化的基因。第一个目标将侧重于数据生成和资源开发，并将涉及从普通人群中抽取的3500名健康高加索人（5-40岁）的3D面部表面图像和DNA样本的收集。将从3D图像中提取定量面部测量，并对所有DNA样本进行全基因组SNP标记的基因分型。与FaceBase中心一起工作，我们的目的是创建一个可扩展的。可供外部研究者使用的交互式和可挖掘的数据资源，其中将包含面部测量，3D图像和基因型。最后，希望这样一个数据库将促进新的研究倡议。为了说明这一潜力，该提案的第二个目标将重点关注识别与面中部形态变化相关的SNP，包括与口面裂倾向相关的面部特征。面中部形态的显着措施将来自3D面部表面图像，然后将采用全基因组关联方法来识别影响感兴趣的面部特征的定量变化的多态性。 公共卫生相关性：我们建议建立一个三维面部和遗传标记数据库将有利于研究和临床社区，通过提供资源来测试与正常和异常颅面发育相关的新假设，并作为规范控制数据的存储库。此外，该项目有可能识别口面裂的重要遗传风险因素。