Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China.
Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
Forensic Sci Int Genet. 2021 Jan;50:102395. doi: 10.1016/j.fsigen.2020.102395. Epub 2020 Sep 24.
Predicting appearance phenotypes from genotypes is relevant for various areas of human genetic research and applications such as genetic epidemiology, human history, anthropology, and particularly in forensics. Many appearance phenotypes, and thus their underlying genotypes, are highly correlated, with pigmentation traits serving as primary examples. However, all available genetic prediction models, including those for pigmentation traits currently used in forensic DNA phenotyping, ignore phenotype correlations. Here, we investigated the impact of appearance phenotype correlations on genetic appearance prediction in the exemplary case of three pigmentation traits. We used data for categorical eye, hair and skin colour as well as 41 DNA markers utilized in the recently established HIrisPlex-S system from 762 individuals with complete phenotype and genotype information. Based on these data, we performed genetic prediction modelling of eye, hair and skin colour via three different strategies, namely the established approach of predicting phenotypes solely based on genotypes while not considering phenotype correlations, and two novel approaches that considered phenotype correlations, either incorporating truly observed correlated phenotypes or DNA-predicted correlated phenotypes in addition to the DNA predictors. We found that using truly observed correlated pigmentation phenotypes as additional predictors increased the DNA-based prediction accuracies for almost all eye, hair and skin colour categories, with the largest increase for intermediate eye colour, brown hair colour, dark to black skin colour, and particularly for dark skin colour. Outcomes of dedicated computer simulations suggest that this prediction accuracy increase is due to the additional genetic information that is implicitly provided by the truly observed correlated pigmentation phenotypes used, yet not covered by the DNA predictors applied. In contrast, considering DNA-predicted correlated pigmentation phenotypes as additional predictors did not improve the performance of the genetic prediction of eye, hair and skin colour, which was in line with the results from our computer simulations. Hence, in practical applications of DNA-based appearance prediction where no phenotype knowledge is available, such as in forensic DNA phenotyping, it is not advised to use DNA-predicted correlated phenotypes as predictors in addition to the DNA predictors. In the very least, this is not recommended for the pigmentation traits and the established pigmentation DNA predictors tested here.
从基因型预测表型与人类遗传研究和应用的多个领域相关，例如遗传流行病学、人类历史、人类学，特别是法医学。许多表型，及其潜在的基因型，高度相关，以色素沉着特征为例。然而，所有现有的遗传预测模型，包括目前用于法医 DNA 表型分析的色素沉着特征预测模型，都忽略了表型相关性。在这里，我们以三种色素沉着特征为例，研究了表型相关性对遗传外观预测的影响。我们使用了 762 名个体的分类眼睛、头发和皮肤颜色以及 41 个 DNA 标记的数据，这些个体具有完整的表型和基因型信息，这些数据来自最近建立的 HIrisPlex-S 系统。基于这些数据，我们通过三种不同的策略对眼睛、头发和皮肤颜色进行了遗传预测建模，即仅基于基因型预测表型而不考虑表型相关性的既定方法，以及两种考虑表型相关性的新方法，一种是将真正观察到的相关表型，另一种是将 DNA 预测的相关表型与 DNA 预测器结合起来。我们发现，使用真正观察到的相关色素沉着表型作为附加预测因子，几乎可以提高所有眼睛、头发和皮肤颜色类别的 DNA 预测准确性，对于中间眼睛颜色、棕色头发颜色、深至黑色皮肤颜色，尤其是深色皮肤颜色，增加幅度最大。专门的计算机模拟结果表明，这种预测准确性的提高是由于真正观察到的相关色素沉着表型所提供的额外遗传信息，但这些信息不受应用的 DNA 预测器覆盖。相反，将 DNA 预测的相关色素沉着表型视为附加预测因子并不能提高眼睛、头发和皮肤颜色的遗传预测性能，这与我们的计算机模拟结果一致。因此，在没有表型知识的情况下，例如在法医 DNA 表型分析中，在实际的基于 DNA 的外观预测应用中，不建议将 DNA 预测的相关表型作为 DNA 预测器的附加预测因子。至少，对于这里测试的色素沉着特征和现有的色素沉着 DNA 预测器，不建议这样做。
