Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts.

IF 11.1 Q1 CELL BIOLOGY
Cell genomics Pub Date : 2024-05-08 Epub Date: 2024-04-30 DOI:10.1016/j.xgen.2024.100544
Robert F Hillary, Hong Kiat Ng, Daniel L McCartney, Hannah R Elliott, Rosie M Walker, Archie Campbell, Felicia Huang, Kenan Direk, Paul Welsh, Naveed Sattar, Janie Corley, Caroline Hayward, Andrew M McIntosh, Cathie Sudlow, Kathryn L Evans, Simon R Cox, John C Chambers, Marie Loh, Caroline L Relton, Riccardo E Marioni, Paul D Yousefi, Matthew Suderman
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引用次数: 0

Abstract

Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.

基于血液表观基因组的全人群慢性低度炎症分析。
慢性炎症是与年龄有关的疾病的标志。包括 C 反应蛋白(CRP)在内的炎症蛋白在评估长期炎症方面的有效性因其阶段性而受到阻碍。CRP的DNA甲基化(DNAm)特征可作为慢性炎症的更可靠标记。我们的研究表明,DNAm 的个体间差异可捕捉到循环 CRP 变异的 50%(N = 17936,苏格兰一代)。我们使用最先进的算法开发了一系列 CRP 的 DNAm 预测因子。在 1936 年洛锡安出生队列(LBC1936)队列中,基于弹性网回归的预测方法优于其他竞争方法,解释了 18% 的表型变异,是现有 DNAm 预测方法的两倍。DNAm 预测方法在另外四个测试队列(雅芳父母与子女纵向研究、新加坡生命健康研究、Southall 和 Brent Revisited 以及 LBC1921)中的表现不相上下,其中包括不同基因血统和不同年龄段的个体。在与 26 种健康结果的关联方面,表现最佳的预测因子超过了化验测定的 CRP 和基因评分。我们的研究结果为评估不同人群的慢性低度炎症开辟了新的途径。
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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CiteScore
7.10
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