Performance of HLA allele prediction methods in African Americans for class II genes HLA-DRB1, -DQB1, and -DPB1.
Performance of HLA allele prediction methods in African Americans for class II genes HLA-DRB1, -DQB1, and -DPB1.
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DOI：
10.1186/1471-2156-15-72
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发表时间：
2014-06-16
期刊：
影响因子：
2.9
通讯作者：
Rybicki BA
中科院分区：
文献类型：
--
作者：
Levin AM;Adrianto I;Datta I;Iannuzzi MC;Trudeau S;McKeigue P;Montgomery CG;Rybicki BA
人类白细胞抗原（HLA）等位基因分型的成本推动了使用密集单核苷酸多态性（SNP）基因型数据和该区域单倍型结构的归算方法的发展，但这些方法在混合人群（如非洲裔美国人）中的表现尚未得到充分评估。我们将基于基因型的全基因组基因分型和靶向测序代入结果与现有的HLA-DRB1、- DQB1和-DPB1等位基因数据进行了比较。在欧美人群中，新开发的属性Bagging （Attribute Bagging， HIBAG）方法的HLA基因型插入优于HLA*IMP:02。在非裔美国人中，HLA*IMP:02的准确性略好于HIBAG预先构建的模型，但使用部分非裔美国人样本（SNP基因分型和四位数HLA II类等位基因分型）构建的HIBAG模型的准确性始终高于HLA*IMP:02。然而，HIBAG在本地血统杂合个体中的准确性明显较低（p≤0.04）。在非洲和欧洲染色体数量相等的模型中，准确性得到了提高。通过靶向测序和SNP插补增加的变异进一步提高了插补精度和高质量呼叫的比例。将HIBAG方法与本地血统和密集的变异数据相结合，可以在非裔美国人中产生高度准确的HLA II类等位基因归算。
The expense of human leukocyte antigen (HLA) allele genotyping has motivated the development of imputation methods that use dense single nucleotide polymorphism (SNP) genotype data and the region’s haplotype structure, but the performance of these methods in admixed populations (such as African Americans) has not been adequately evaluated. We compared genotype-based—derived from both genome-wide genotyping and targeted sequencing—imputation results to existing allele data for HLA–DRB1, −DQB1, and –DPB1. In European Americans, the newly-developed HLA Genotype Imputation with Attribute Bagging (HIBAG) method outperformed HLA*IMP:02. In African Americans, HLA*IMP:02 performed marginally better than HIBAG pre-built models, but HIBAG models constructed using a portion of our African American sample with both SNP genotyping and four-digit HLA class II allele typing had consistently higher accuracy than HLA*IMP:02. However, HIBAG was significantly less accurate in individuals heterozygous for local ancestry (p ≤0.04). Accuracy improved in models with equal numbers of African and European chromosomes. Variants added by targeted sequencing and SNP imputation further improved both imputation accuracy and the proportion of high quality calls. Combining the HIBAG approach with local ancestry and dense variant data can produce highly-accurate HLA class II allele imputation in African Americans.