Claes Peter, Liberton Denise K, Daniels Katleen, Rosana Kerri Matthes, Quillen Ellen E, Pearson Laurel N, McEvoy Brian, Bauchet Marc, Zaidi Arslan A, Yao Wei, Tang Hua, Barsh Gregory S, Absher Devin M, Puts David A, Rocha Jorge, Beleza Sandra, Pereira Rinaldo W, Baynam Gareth, Suetens Paul, Vandermeulen Dirk, Wagner Jennifer K, Boster James S, Shriver Mark D
Medical Image Computing, ESAT/PSI, Department of Electrical Engineering, KU Leuven, Medical Imaging Research Center, KU Leuven & UZ Leuven, iMinds-KU Leuven Future Health Department, Leuven, Belgium.
Department of Anthropology, Penn State University, University Park, Pennsylvania, United States of America.
PLoS Genet. 2014 Mar 20;10(3):e1004224. doi: 10.1371/journal.pgen.1004224. eCollection 2014 Mar.
Human facial diversity is substantial, complex, and largely scientifically unexplained. We used spatially dense quasi-landmarks to measure face shape in population samples with mixed West African and European ancestry from three locations (United States, Brazil, and Cape Verde). Using bootstrapped response-based imputation modeling (BRIM), we uncover the relationships between facial variation and the effects of sex, genomic ancestry, and a subset of craniofacial candidate genes. The facial effects of these variables are summarized as response-based imputed predictor (RIP) variables, which are validated using self-reported sex, genomic ancestry, and observer-based facial ratings (femininity and proportional ancestry) and judgments (sex and population group). By jointly modeling sex, genomic ancestry, and genotype, the independent effects of particular alleles on facial features can be uncovered. Results on a set of 20 genes showing significant effects on facial features provide support for this approach as a novel means to identify genes affecting normal-range facial features and for approximating the appearance of a face from genetic markers.
人类面部的多样性丰富、复杂，在很大程度上尚无科学解释。我们使用空间密集的准地标来测量来自三个地点（美国、巴西和佛得角）的具有西非和欧洲混合血统的人群样本的面部形状。通过基于自举重抽样响应的归因建模（BRIM），我们揭示了面部变异与性别、基因组血统以及一部分颅面候选基因的影响之间的关系。这些变量的面部效应被总结为基于响应的归因预测变量（RIP），并使用自我报告的性别、基因组血统以及基于观察者的面部评分（女性气质和比例血统）和判断（性别和人群组）进行验证。通过对性别、基因组血统和基因型进行联合建模，可以揭示特定等位基因对面部特征的独立影响。一组对面部特征有显著影响的20个基因的研究结果支持了这种方法，它是一种识别影响正常范围面部特征的基因以及从遗传标记近似面部外观的新手段。
