Campbell Kyle A, Colacino Justin A, Dou John, Dolinoy Dana C, Park Sung Kyun, Loch-Caruso Rita, Padmanabhan Vasantha, Bakulski Kelly M
Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Epigenetics. 2024 Dec;19(1):2437275. doi: 10.1080/15592294.2024.2437275. Epub 2024 Dec 8.
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 ( = 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 ( = 368,435 sites) from 12 cell types: cytotrophoblasts ( = 18), endothelial cells ( = 19), Hofbauer cells ( = 26), stromal cells ( = 21), syncytiotrophoblasts ( = 4), six lymphocyte types ( = 36), and nucleated red blood cells ( = 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, -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.
为了在全胎盘绒毛组织研究中区分DNA甲基化(DNAm)与细胞比例变化,我们开发了一种强大的细胞类型特异性DNAm参考物来估计细胞组成。我们整理了通过Illumina EPIC或450k微阵列量化的新的和现有的细胞类型DNAm图谱。为了估计细胞组成,我们基于每种细胞类型鉴定出的前30个高甲基化和低甲基化位点,用稳健的偏相关对全胎盘样本(n = 36)进行反卷积分析。为了测试反卷积性能,我们评估了预测204个外部胎盘样本中DNAm变异主成分时的均方根误差。我们分析了来自12种细胞类型的DNAm图谱(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)、合体滋养层细胞(n = 4)、六种淋巴细胞类型(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:合体滋养层细胞占60.9%、基质细胞占17.3%、内皮细胞占8.8%、细胞滋养层细胞占3.7%、霍夫鲍尔细胞占3.7%、有核红细胞占1.7%,中性粒细胞占1.2%。我们扩展后的参考物在预测DNAm变异(PC1,解释方差15.4%,四分位距 = 21.61)时,其细胞组成估计值优于现有的参考物(预测均方误差:8.62对10.79,P值<0.001)。这种细胞类型参考物可以从全胎盘DNAm数据中稳健地估计细胞组成,以检测重要的细胞类型、揭示生物学机制并改善因果推断。