Epigenetics, heritability and longitudinal analysis.
Epigenetics, heritability and longitudinal analysis.
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DOI：
10.1186/s12863-018-0648-1
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发表时间：
2018-09-17
期刊：
影响因子：
2.9
通讯作者：
Melton PE
中科院分区：
文献类型：
--
作者：
Nustad HE;Almeida M;Canty AJ;LeBlanc M;Page CM;Melton PE
表观基因组关联研究中的纵向数据和重复测量为理解表观遗传学提供了丰富的资源。我们总结了针对GAW20数据集的7种分析方法，这些方法解决了表型和表观遗传学数据的挑战和潜在应用。所有的贡献都使用了GAW20的真实数据集，并使用了线性混合效应(LME)模型或通过广义估计方程(GEE)的边际模型。这些贡献被细分为3类：(A)DNA甲基化数据的质量控制(QC)方法；(B)非诺贝特治疗前后的遗传力估计；以及(C)非诺贝特治疗前后药物反应对DNA甲基化和血脂的影响。有两篇文章涉及到质量控制，并确定了处理前和处理后DNA甲基化的巨大统计差异，这可能是批次效应的结果。两篇文章比较了治疗前后表观基因组遗传力估计，一篇使用贝叶斯最大似然估计，另一篇使用方差分量最大似然估计。比较这些研究的密度曲线表明，这些遗传力估计是相似的。另一项贡献使用方差分量LME来描述遗传和共享环境造成的遗传力的比例。通过将环境暴露纳入随机影响，作者发现遗传力估计变得更稳定，但没有显著差异。两篇论文研究了治疗反应。一项研究估计了药物相关甲基化对甘油三酯水平的影响作为反应，并确定了11个重要的胞嘧啶-磷酸-鸟嘌呤(CpG)位点，调整或不调整高密度脂蛋白。第二个贡献进行了加权基因共表达网络分析，确定了至少30个CpG位点的6个显著模块，其中包括3个处理前后拓扑差异的模块。GAW20工作组得出的四个结论是：(A)质量控制措施是调查多个时间点或重复测量的Ewas研究的重要考虑因素；(B)对于DNA甲基化研究，在各个CpG位点的时间点之间应用遗传力估计是一种有用的质量控制措施；(C)药物干预显示了两个时间点上强大的表观基因组范围的DNA甲基化模式；以及(D)需要新的统计方法来解释DNA甲基化对环境的贡献。这些贡献表明，在未来的表观遗传学研究中，存在许多分析纵向数据的机会。
Longitudinal data and repeated measurements in epigenome-wide association studies (EWAS) provide a rich resource for understanding epigenetics. We summarize 7 analytical approaches to the GAW20 data sets that addressed challenges and potential applications of phenotypic and epigenetic data. All contributions used the GAW20 real data set and employed either linear mixed effect (LME) models or marginal models through generalized estimating equations (GEE). These contributions were subdivided into 3 categories: (a) quality control (QC) methods for DNA methylation data; (b) heritability estimates pretreatment and posttreatment with fenofibrate; and (c) impact of drug response pretreatment and posttreatment with fenofibrate on DNA methylation and blood lipids. Two contributions addressed QC and identified large statistical differences with pretreatment and posttreatment DNA methylation, possibly a result of batch effects. Two contributions compared epigenome-wide heritability estimates pretreatment and posttreatment, with one employing a Bayesian LME and the other using a variance-component LME. Density curves comparing these studies indicated these heritability estimates were similar. Another contribution used a variance-component LME to depict the proportion of heritability resulting from a genetic and shared environment. By including environmental exposures as random effects, the authors found heritability estimates became more stable but not significantly different. Two contributions investigated treatment response. One estimated drug-associated methylation effects on triglyceride levels as the response, and identified 11 significant cytosine-phosphate-guanine (CpG) sites with or without adjusting for high-density lipoprotein. The second contribution performed weighted gene coexpression network analysis and identified 6 significant modules of at least 30 CpG sites, including 3 modules with topological differences pretreatment and posttreatment. Four conclusions from this GAW20 working group are: (a) QC measures are an important consideration for EWAS studies that are investigating multiple time points or repeated measurements; (b) application of heritability estimates between time points for individual CpG sites is a useful QC measure for DNA methylation studies; (c) drug intervention demonstrated strong epigenome-wide DNA methylation patterns across the 2 time points; and (d) new statistical methods are required to account for the environmental contributions of DNA methylation across time. These contributions demonstrate numerous opportunities exist for the analysis of longitudinal data in future epigenetic studies.
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WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
3.7
作者：
Day K;Waite LL;Alonso A;Irvin MR;Zhi D;Thibeault KS;Aslibekyan S;Hidalgo B;Borecki IB;Ordovas JM;Arnett DK;Tiwari HK;Absher DM
通讯作者：
Absher DM
影响因子：
3.8
作者：
Dedeurwaerder, Sarah;Defrance, Matthieu;Fuks, Francois
通讯作者：
Fuks, Francois
影响因子：
3.5
作者：
Kulkarni, Hemant;Kos, Mark Z.;Carless, Melanie A.
通讯作者：
Carless, Melanie A.
DOI：
10.1375/1369052022956
发表时间：
2002-04-01
期刊：
TWIN RESEARCH
影响因子：
--
作者：
Beekman, M;Heijmans, BT;Boomsma, DI
通讯作者：
Boomsma, DI