Next-generation sequencing (NGS) became an effective approach for finding novel causative genomic variants of genetic disorders and is increasingly used for diagnostic purposes. Public variant databases that gather data of pathogenic variants are being relied upon as a source for clinical diagnosis. However, research of pathogenic variants using public databases data could be carried out not only in patients, but also in healthy people. This could provide insights into the most common recessive disorders in populations. The study aim was to use NGS and data from the ClinVar database for the identification of pathogenic variants in the exomes of healthy individuals from the Lithuanian population. To achieve this, 96 exomes were sequenced. An average of 42 139 single-nucleotide variants (SNVs) and 2306 short INDELs were found in each individual exome. Pooled data of study exomes provided a total of 243 192 unique SNVs and 31 623 unique short INDELs. Three hundred and twenty-one unique SNVs were classified as pathogenic. Comparison of the European data from the 1000 Genomes Project with our data revealed five pathogenic genomic variants that are inherited in an autosomal recessive pattern and that statistically significantly differ from the European population data.

中文翻译：

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使用下一代测序对健康人的ClinVar数据库中的病原体变异进行分析。

下一代测序（NGS）成为发现遗传疾病的新型致病基因组变体的有效方法，并且越来越多地用于诊断目的。收集致病变体数据的公共变体数据库被用作临床诊断的来源。但是，不仅可以在患者中而且可以在健康人群中使用公共数据库数据进行病原体变异研究。这可以提供有关人群中最常见的隐性疾病的见解。该研究的目的是利用NGS和ClinVar数据库中的数据来鉴定立陶宛人群健康个体外显子组中的致病变异。为此，对96个外显子组进行了测序。在每个外显子组中平均发现42 139个单核苷酸变异（SNV）和2306个短INDEL。研究外显子组的汇总数据提供了总共243192个独特的SNV和31623个独特的短INDEL。312个独特的SNV被归类为致病性。将来自1000个基因组计划的欧洲数据与我们的数据进行比较，我们发现了五个致病基因组变异体，它们以常染色体隐性模式遗传，并且在统计学上与欧洲人口数据存在显着差异。