The human gene damage index as a gene-level approach to prioritizing exome variants
The human gene damage index as a gene-level approach to prioritizing exome variants
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DOI：
10.1073/pnas.1518646112
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发表时间：
2015-11-03
影响因子：
11.1
通讯作者：
Casanova, Jean-Laurent
中科院分区：
文献类型：
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作者：
Itan, Yuval;Shang, Lei;Casanova, Jean-Laurent
患有单基因疾病的患者的蛋白质编码外显子组包含大约20,000个变体，其中只有一两个是致病的。我们发现，在普通人群的蛋白质编码外显子组中，58%的罕见变异仅位于2%的基因中。根据这一观察结果，我们的目标是开发一种基因水平的方法来预测给定的人类蛋白质编码基因是否可能携带致病突变。为此，我们导出了基因损伤指数（GDI）：一种全基因组、基因水平的突变损伤指标，在一般人群中积累。我们发现GDI与选择进化压力、蛋白质复杂性、编码序列长度和相似物数量相关。我们将GDI与主要的基因水平方法、基因不耐受和从头过量进行了比较，并证明GDI在检测假阳性（即去除与疾病无关的基因的外显子组变异）方面表现最好，而基因不耐受和从头过量在检测真阳性（即评估可能导致疾病的基因的从头突变）方面表现更好。
The protein-coding exome of a patient with a monogenic disease contains about 20,000 variants, only one or two of which are disease causing. We found that 58% of rare variants in the protein-coding exome of the general population are located in only 2% of the genes. Prompted by this observation, we aimed to develop a gene-level approach for predicting whether a given human protein-coding gene is likely to harbor disease-causing mutations. To this end, we derived the gene damage index (GDI): a genome-wide, gene-level metric of the mutational damage that has accumulated in the general population. We found that the GDI was correlated with selective evolutionary pressure, protein complexity, coding sequence length, and the number of paralogs. We compared GDI with the leading gene-level approaches, genic intolerance, and de novo excess, and demonstrated that GDI performed best for the detection of false positives (i.e., removing exome variants in genes irrelevant to disease), whereas genic intolerance and de novo excess performed better for the detection of true positives (i.e., assessing de novo mutations in genes likely to be disease causing).