Low-Density Lipoprotein Receptor Gene Familial Hypercholesterolemia Variant Database: Update and Pathological Assessment
Low-Density Lipoprotein Receptor Gene Familial Hypercholesterolemia Variant Database: Update and Pathological Assessment
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DOI：
10.1111/j.1469-1809.2012.00724.x
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发表时间：
2012-09-01
影响因子：
1.9
通讯作者：
Humphries, Steve E.
中科院分区：
文献类型：
--
作者：
Usifo, Ebele;Leigh, Sarah E. A.;Humphries, Steve E.
家族性高胆固醇血症（FH）主要由低密度脂蛋白受体基因（LDLR）变异引起。我们在此报告了UCL LDLR变体数据库的更新，以纳入2008年至2010年期间文献和内部报告的变体，并将数据库转移至LOVDv.2.0平台（https：grenada.lumc.nl/LOVD2/UCL-Heart/home.php? select_db=LDLR）和致病性分析。该数据库现在包含FH患者中报告的超过1288种不同变体：55%外显子取代，22%外显子小重排（100 bp），2%启动子变体，10%内含子变体和1个3'非翻译序列变体。新报告的变异体的分布和类型与2008年数据库的分布和类型非常匹配，我们使用这些变异体（n= 223）作为代表性样本，以评估标准开放获取软件的实用性（PolyPhen、SIFT、精细SIFT、神经网络剪接位点预测工具、SplicePort和NetGene 2）和其他分析（单氨基酸多态性数据库、保守性和结构分析以及突变品尝器）用于致病性预测。结合起来，这些技术使我们能够有信心地将致病性预测分配给8/8框内小重排和8/9错义取代，这些错义取代与PolyPhen和SIFT分析的先前不一致的结果。总体而言，我们得出结论，79%的报告变异可能是致病的。
Familial hypercholesterolemia (FH) is caused predominately by variants in the low-density lipoprotein receptor gene (LDLR). We report here an update of the UCL LDLR variant database to include variants reported in the literature and in-house between 2008 and 2010, transfer of the database to LOVDv.2.0 platform (https://grenada.lumc.nl/LOVD2/UCL-Heart/home.php?select_db=LDLR) and pathogenicity analysis. The database now contains over 1288 different variants reported in FH patients: 55% exonic substitutions, 22% exonic small rearrangements (100 bp), 2% promoter variants, 10% intronic variants and 1 variant in the 3' untranslated sequence. The distribution and type of newly reported variants closely matches that of the 2008 database, and we have used these variants (n= 223) as a representative sample to assess the utility of standard open access software (PolyPhen, SIFT, refined SIFT, Neural Network Splice Site Prediction Tool, SplicePort and NetGene2) and additional analyses (Single Amino Acid Polymorphism database, analysis of conservation and structure and Mutation Taster) for pathogenicity prediction. In combination, these techniques have enabled us to assign with confidence pathogenic predictions to 8/8 in-frame small rearrangements and 8/9 missense substitutions with previously discordant results from PolyPhen and SIFT analysis. Overall, we conclude that 79% of the reported variants are likely to be disease causing.