Placental and immune cell DNA methylation reference panel for bulk tissue cell composition estimation in epidemiological studies.

IF 2.9 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Epigenetics Pub Date : 2024-12-01 Epub Date: 2024-12-08 DOI:10.1080/15592294.2024.2437275
Kyle A Campbell, Justin A Colacino, John Dou, Dana C Dolinoy, Sung Kyun Park, Rita Loch-Caruso, Vasantha Padmanabhan, Kelly M Bakulski
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引用次数: 0

Abstract

To distinguish DNA methylation (DNAm) from cell proportion changes in whole placental villous tissue research, we developed a robust cell type-specific DNAm reference to estimate cell composition. We collated new and existing cell type DNAm profiles quantified via Illumina EPIC or 450k microarrays. To estimate cell composition, we deconvoluted whole placental samples (n = 36) with robust partial correlation based on the top 30 hyper- and hypomethylated sites identified per cell type. To test deconvolution performance, we evaluated root mean square error in predicting principal components of DNAm variation in 204 external placental samples. We analyzed DNAm profiles (n = 368,435 sites) from 12 cell types: cytotrophoblasts (n = 18), endothelial cells (n = 19), Hofbauer cells (n = 26), stromal cells (n = 21), syncytiotrophoblasts (n = 4), six lymphocyte types (n = 36), and nucleated red blood cells (n = 11). Median cell composition was consistent with placental biology: 60.9% syncytiotrophoblast, 17.3% stromal, 8.8% endothelial, 3.7% cytotrophoblast, 3.7% Hofbauer, 1.7% nucleated red blood cells, and 1.2% neutrophils. Our expanded reference outperformed an existing reference in predicting DNAm variation (PC1, 15.4% variance explained, IQR = 21.61) with cell composition estimates (mean square error of prediction: 8.62 vs. 10.79, p-value < 0.001). This cell type reference can robustly estimate cell composition from whole placental DNAm data to detect important cell types, reveal biological mechanisms, and improve causal inference.

流行病学研究中用于估计大块组织细胞组成的胎盘和免疫细胞DNA甲基化参考面板。
为了在整个胎盘绒毛组织研究中区分DNA甲基化(DNAm)和细胞比例变化,我们开发了一个强大的细胞类型特异性DNAm参考来估计细胞组成。我们整理了通过Illumina EPIC或450k微阵列定量的新的和现有的细胞类型dna谱。为了估计细胞组成,我们对整个胎盘样本(n = 36)进行了反卷积,并基于每种细胞类型鉴定的前30个高甲基化和低甲基化位点进行了部分相关性分析。为了测试反褶积性能,我们评估了预测204个外胎盘样本中DNAm变异主成分的均方根误差。我们分析了12种细胞类型的DNAm谱(n = 368,435个位点):细胞滋养层细胞(n = 18)、内皮细胞(n = 19)、霍夫鲍尔细胞(n = 26)、基质细胞(n = 21)、合胞滋养层细胞(n = 4)、6种淋巴细胞(n = 36)和有核红细胞(n = 11)。细胞组成中位数与胎盘生物学一致:60.9%的合胞滋养细胞、17.3%的间质细胞、8.8%的内皮细胞、3.7%的细胞滋养细胞、3.7%的霍夫鲍尔细胞、1.7%的有核红细胞和1.2%的中性粒细胞。我们的扩展参考文献在预测DNAm变异(PC1, 15.4%方差解释,IQR = 21.61)与细胞组成估计(预测均方误差:8.62 vs. 10.79, p值< 0.001)方面优于现有参考文献。这种细胞类型参考可以从整个胎盘dna数据中可靠地估计细胞组成,以检测重要的细胞类型,揭示生物学机制,并改进因果推理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Epigenetics
Epigenetics 生物-生化与分子生物学
CiteScore
6.80
自引率
2.70%
发文量
82
审稿时长
3-8 weeks
期刊介绍: Epigenetics publishes peer-reviewed original research and review articles that provide an unprecedented forum where epigenetic mechanisms and their role in diverse biological processes can be revealed, shared, and discussed. Epigenetics research studies heritable changes in gene expression caused by mechanisms others than the modification of the DNA sequence. Epigenetics therefore plays critical roles in a variety of biological systems, diseases, and disciplines. Topics of interest include (but are not limited to): DNA methylation Nucleosome positioning and modification Gene silencing Imprinting Nuclear reprogramming Chromatin remodeling Non-coding RNA Non-histone chromosomal elements Dosage compensation Nuclear organization Epigenetic therapy and diagnostics Nutrition and environmental epigenetics Cancer epigenetics Neuroepigenetics
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