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丙型肝炎病毒深度测序在混合感染中鉴定亚基因型:真实世界经验。

Hepatitis C virus deep sequencing for sub-genotype identification in mixed infections: A real-life experience.

机构信息

UCM Digestive Diseases, Valme University Hospital, Seville, Spain; Centro de Investigación Biomédica en Red (CIBER) de Enfermedades Hepáticas y Digestivas (CIBERehd) del Instituto de Salud Carlos III, Madrid, Spain.

UCM Infectious Diseases and Microbiology, Valme University Hospital, Seville, Spain.

出版信息

Int J Infect Dis. 2018 Feb;67:114-117. doi: 10.1016/j.ijid.2017.12.016. Epub 2017 Dec 15.

Abstract

BACKGROUND

The effectiveness of the new generation of hepatitis C treatments named direct-acting antiviral agents (DAAs) depends on the genotype, subtype, and resistance-associated substitutions present in individual patients. The aim of this study was to evaluate a massive sequencing platform for the analysis of genotypes and subtypes of hepatitis C virus (HCV) in order to optimize therapy.

METHODS

A total of 84 patients with hepatitis C were analyzed. The routine genotyping methodology for HCV used at the study institution (Versant HCV Assay, LiPA) was compared with a deep sequencing platform (454/GS-Junior and Illumina MiSeq).

RESULTS

The mean viral load in these HCV patients was 6.89×10±7.02×10. Viral genotypes analyzed by LiPA were distributed as follows: 26% genotype 1a (22/84), 55% genotype 1b (46/84), 1% genotype 1 (1/84), 2.5% genotype 3 (2/84), 6% genotype 3a (5/84), 6% genotype 4a/c/d (5/84). When analyzed by deep sequencing, the samples were distributed as follows: 27% genotype 1a (23/84), 56% genotype 1b (47/84), 8% genotype 3a (7/84), 5% genotype 4d (4/84), 2.5% genotype 4f (2/84). Six of the 84 patients (7%) were infected with more than one subtype. Among these, 33% (2/6) failed DAA-based triple therapy.

CONCLUSIONS

The detection of mixed infection could explain some treatment failures. Accurate determination of viral genotypes and subtypes would allow optimal patient management and improve the effectiveness of DAA therapy.

摘要

背景

新一代被称为直接作用抗病毒药物(DAAs)的丙型肝炎治疗药物的疗效取决于个体患者的基因型、亚型和耐药相关替代物。本研究旨在评估一种大规模测序平台,用于分析丙型肝炎病毒(HCV)的基因型和亚型,以优化治疗。

方法

共分析了 84 例丙型肝炎患者。与常规 HCV 基因分型方法(即研究机构使用的 Versant HCV 检测,LiPA)相比,我们还使用了深度测序平台(454/GS-Junior 和 Illumina MiSeq)。

结果

这些 HCV 患者的平均病毒载量为 6.89×10±7.02×10。LiPA 分析的病毒基因型分布如下:26%基因型 1a(22/84)、55%基因型 1b(46/84)、1%基因型 1(1/84)、2.5%基因型 3(2/84)、6%基因型 3a(5/84)、6%基因型 4a/c/d(5/84)。而通过深度测序分析,样本分布如下:27%基因型 1a(23/84)、56%基因型 1b(47/84)、8%基因型 3a(7/84)、5%基因型 4d(4/84)、2.5%基因型 4f(2/84)。84 例患者中有 6 例(7%)感染了一种以上亚型。其中,33%(2/6)的患者对 DAA 三联疗法无效。

结论

混合感染的检测可以解释一些治疗失败的原因。准确确定病毒基因型和亚型将有助于优化患者管理并提高 DAA 治疗的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1938/5812776/8c492551a94c/gr1.jpg

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