Detecting genetic association of common human facial morphological variation using high density 3D image registration.
Detecting genetic association of common human facial morphological variation using high density 3D image registration.
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使用高密度 3D 图像配准检测常见人类面部形态变异的遗传关联
DOI：
10.1371/journal.pcbi.1003375
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发表时间：
2013
影响因子：
4.3
通讯作者：
Tang K
中科院分区：
文献类型：
--
作者：
Peng S;Tan J;Hu S;Zhou H;Guo J;Jin L;Tang K
人类面部形态是许多复杂特征的组合。人们对常见面部形态变异的遗传基础知之甚少。现有的关联研究主要使用简单的地标距离作为面部复杂形态表型的替代。然而，这可能会导致统计功效降低以及形状变化的推断不清晰。在本研究中，我们应用了一种新的图像配准方法，该方法可自动识别显着地标并使用高密度像素点对齐样本面部。基于这种高密度配准，使用三种不同的表型数据方案来测试常见面部形态变异与10个候选SNP之间的关联，并比较它们的性能。第一个方案使用传统的地标距离；第二个依赖于 15 个地标的几何分析，第三个使用约 30,000 个 3D 点的密集配准的几何分析。我们发现这两种几何方法在检测形态变化方面高度一致。采用密集配准的几何方法进一步展现了在形状变化精细推断和3D人脸建模方面的优越性。几个候选 SNP 显示出与不同面部特征的潜在关联。特别是，IRF6 基因中的一个 SNP（非综合征性唇裂/腭裂的已知危险因素）rs642961 经验证可以强烈预测中国汉族女性的正常唇形变异。这项研究进一步证明，密集的面部配准可以大大改善常见面部变异中遗传关联的检测和表征。
Human facial morphology is a combination of many complex traits. Little is known about the genetic basis of common facial morphological variation. Existing association studies have largely used simple landmark-distances as surrogates for the complex morphological phenotypes of the face. However, this can result in decreased statistical power and unclear inference of shape changes. In this study, we applied a new image registration approach that automatically identified the salient landmarks and aligned the sample faces using high density pixel points. Based on this high density registration, three different phenotype data schemes were used to test the association between the common facial morphological variation and 10 candidate SNPs, and their performances were compared. The first scheme used traditional landmark-distances; the second relied on the geometric analysis of 15 landmarks and the third used geometric analysis of a dense registration of ∼30,000 3D points. We found that the two geometric approaches were highly consistent in their detection of morphological changes. The geometric method using dense registration further demonstrated superiority in the fine inference of shape changes and 3D face modeling. Several candidate SNPs showed potential associations with different facial features. In particular, one SNP, a known risk factor of non-syndromic cleft lips/palates, rs642961 in the IRF6 gene, was validated to strongly predict normal lip shape variation in female Han Chinese. This study further demonstrated that dense face registration may substantially improve the detection and characterization of genetic association in common facial variation.
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影响因子：
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作者：
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通讯作者：
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