Guo Xiaolong, Sulaiman Mahnoor, Neumann Alexander, Zheng Shijie C, Cecil Charlotte A M, Teschendorff Andrew E, Heijmans Bastiaan T
Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.
Department of Biomedical Data Sciences, Leiden University Medical Center, Einthovenweg 20, Leiden, 2333 ZC, The Netherlands.
Genome Med. 2025 May 27;17(1):63. doi: 10.1186/s13073-025-01489-7.
Variations in immune-cell fractions can confound or hamper interpretation of DNAm-based biomarkers in blood. Although cell-type deconvolution can address this challenge for cord and adult blood, currently there is no method applicable to blood from other age groups, including infants and children. Here we construct and extensively validate a DNAm reference panel, called UniLIFE, for 19 immune cell-types, applicable to blood tissue of any age. We use UniLIFE to delineate the dynamics of immune-cell fractions from birth to old age, and to infer disease associated immune cell fraction variations in newborns, infants, children and adults. In a prospective longitudinal study of type-1 diabetes in infants and children, UniLIFE identifies differentially methylated positions that precede type-1 diabetes diagnosis and that map to diabetes related signaling pathways. In summary, UniLIFE will improve the identification and interpretation of blood-based DNAm biomarkers for any age group, but specially for longitudinal studies that include infants and children. The UniLIFE panel and algorithms to estimate cell-type fractions are available from our EpiDISH Bioconductor R-package: https://bioconductor.org/packages/release/bioc/html/EpiDISH.html.
免疫细胞比例的变化可能会混淆或阻碍对血液中基于DNA甲基化的生物标志物的解读。尽管细胞类型反卷积可以解决脐带血和成人血液的这一挑战，但目前尚无适用于其他年龄组血液（包括婴儿和儿童）的方法。在此，我们构建并广泛验证了一个名为UniLIFE的DNA甲基化参考面板，用于19种免疫细胞类型，适用于任何年龄的血液组织。我们使用UniLIFE来描绘从出生到老年免疫细胞比例的动态变化，并推断新生儿、婴儿、儿童和成人中与疾病相关的免疫细胞比例变化。在一项针对婴幼儿1型糖尿病的前瞻性纵向研究中，UniLIFE识别出在1型糖尿病诊断之前且映射到糖尿病相关信号通路的差异甲基化位点。总之，UniLIFE将改善对任何年龄组基于血液的DNA甲基化生物标志物的识别和解读，特别是对于包括婴幼儿在内的纵向研究。UniLIFE面板和估计细胞类型比例的算法可从我们的EpiDISH Bioconductor R包中获取：https://bioconductor.org/packages/release/bioc/html/EpiDISH.html。
