Introduction of a multiplex amplicon sequencing assay to quantify DNA methylation in target cytosine markers underlying four selected epigenetic clocks.

IF 5.7 2区 医学 Q1 Medicine
Ewelina Pośpiech, Aleksandra Pisarek, Joanna Rudnicka, Rezvan Noroozi, Michał Boroń, Aleksander Masny, Bożena Wysocka, Kamila Migacz-Gruszka, Dagmara Lisman, Paulina Pruszkowska-Przybylska, Magdalena Kobus, Maria Szargut, Joanna Dowejko, Kamila Stanisz, Julia Zacharczuk, Piotr Zieliński, Aneta Sitek, Andrzej Ossowski, Magdalena Spólnicka, Wojciech Branicki
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引用次数: 0

Abstract

Background: DNA methylation analysis has proven to be a powerful tool for age assessment. However, the implementation of epigenetic age prediction in diagnostics or routine forensic casework requires appropriate laboratory methods. In this study, we aimed to compare the performance of large-scale DNA methylation analysis protocols that show promise in terms of accuracy, throughput, multiplexing capacity, and high sensitivity.

Results: The protocols were designed to target a predefined panel of 161 genomic CG/CA sites from four known estimators of epigenetic age-related parameters, optimized and validated using artificially methylated controls or blood samples. We successfully targeted 96% of these loci using two enrichment protocols: Ion AmpliSeq™, an amplicon-based method integrated with Ion Torrent S5, and SureSelectXT Methyl-Seq, a hybridization-based method followed by MiSeq FGx sequencing. Both protocols demonstrated high accuracy and robustness. Although hybridization assays have greater multiplexing capabilities, the best overall performance was observed for the amplicon-based protocol with the lowest variability in DNA methylation at 25 ng of starting DNA, mean observed marker coverage of ~ 6.7 k reads, and accuracy of methylation quantification with a mean absolute difference between observed and expected methylation beta value of 0.054. The Ion AmpliSeq method correlated strongly with genome-scale EPIC microarray data (R = 0.91) and showed superiority in terms of methylation measurement accuracy. Method-to-method bias was accounted for by the use of linear transformation, which provided a highly accurate prediction of calendar age with a mean absolute error of less than 5 years for the VISAGE and Hannum age clocks used. The pace of aging (PoAm) and the mortality risk score (MRS) estimators included in our panel represent next-generation clocks, were found to have low to moderate correlations with the VISAGE and Hannum models (R < 0.75), and thus may capture different aspects of epigenetic aging.

Conclusions: We propose a laboratory tool that allows the quantification of DNA methylation in cytosines underlying four different clocks, thus providing broad information on epigenetic aging while maintaining a reasonable number of CpG markers, opening the way to a wide range of applications in forensics, medicine, and healthcare.

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引入多重扩增子测序测定,以量化四种选择的表观遗传时钟下靶胞嘧啶标记的DNA甲基化。
背景:DNA甲基化分析已被证明是年龄评估的有力工具。然而,在诊断或常规法医案件工作中实施表观遗传年龄预测需要适当的实验室方法。在这项研究中,我们旨在比较大规模DNA甲基化分析方案的性能,这些方案在准确性、吞吐量、多路复用能力和高灵敏度方面表现出前景。结果:该方案旨在针对来自四个已知表观遗传年龄相关参数估计器的161个基因组CG/CA位点的预定义组,并使用人工甲基化对照或血液样本进行优化和验证。我们使用两种富集方案成功靶向了96%的这些基因座:Ion AmpliSeq™(一种基于扩增子的方法,与Ion Torrent S5集成)和SureSelectXT Methyl-Seq(一种基于杂交的方法,随后进行MiSeq FGx测序)。两种方案均具有较高的准确性和鲁棒性。尽管杂交分析具有更强的多路复制能力,但基于扩增子的方案的总体性能最好,在起始DNA 25 ng时,DNA甲基化的变异性最低,平均观察到的标记覆盖率为~ 6.7 k reads,甲基化量化的准确性,观察到的甲基化与预期的甲基化β值之间的平均绝对差为0.054。离子AmpliSeq方法与基因组尺度EPIC微阵列数据相关性强(R = 0.91),在甲基化测量精度方面具有优势。方法对方法的偏差是通过使用线性变换来解释的,线性变换为使用的VISAGE和Hannum年龄时钟提供了高度准确的日历年龄预测,平均绝对误差小于5年。我们小组中包括的衰老速度(PoAm)和死亡风险评分(MRS)估计值代表下一代时钟,被发现与VISAGE和Hannum模型具有低到中等的相关性(R结论:我们提出了一种实验室工具,可以量化四种不同时钟下胞嘧啶中的DNA甲基化,从而提供有关表观遗传衰老的广泛信息,同时保持合理数量的CpG标记,为法医、医学和医疗保健领域的广泛应用开辟道路。
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来源期刊
Clinical Epigenetics
Clinical Epigenetics Biochemistry, Genetics and Molecular Biology-Developmental Biology
CiteScore
8.90
自引率
5.30%
发文量
150
审稿时长
12 weeks
期刊介绍: Clinical Epigenetics, the official journal of the Clinical Epigenetics Society, is an open access, peer-reviewed journal that encompasses all aspects of epigenetic principles and mechanisms in relation to human disease, diagnosis and therapy. Clinical trials and research in disease model organisms are particularly welcome.
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