COVID-19(PASC)急性后遗症中的血液 DNA 甲基化:一项前瞻性队列研究。

IF 9.7 1区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
EBioMedicine Pub Date : 2024-08-01 Epub Date: 2024-07-17 DOI:10.1016/j.ebiom.2024.105251
Joseph Balnis, Andy Madrid, Lisa A Drake, Rachel Vancavage, Anupama Tiwari, Vraj J Patel, Ramon Bossardi Ramos, John J Schwarz, Recai Yucel, Harold A Singer, Reid S Alisch, Ariel Jaitovich
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引用次数: 0

摘要

背景:DNA 甲基化将环境信号与转录程序整合在一起。COVID-19 感染会诱导宿主甲基组发生变化。COVID-19急性后遗症(PASC)是急性疾病的一种长期并发症,但其与DNA甲基化的关系尚不清楚。目前还没有发现能取代单一器官功能障碍的 PASC 通用血液标志物:在这项单中心前瞻性队列研究中,PASC、无 PASC 的后 COVID 以及健康参与者都被纳入研究范围,以调查他们的症状与最先进的全基因组测序技术生成的外周血 DNA 甲基化数据之间的关联。由 PASC 引起的生活质量下降情况由经过验证的 SF-36 工具进行评分。通过分析确定了不同甲基化位点的潜在功能作用,并使用机器学习算法来判定 PASC 的严重程度:研究共招募了 103 名 PASC 患者(男性占 22.3%,女性占 77.7%)、15 名曾感染 COVID-19 但未感染 PASC 的患者(男性占 40.0%,女性占 60.0%)和 27 名健康志愿者(男性占 48.1%,女性占 51.9%)。全基因组甲基化测序发现了 39 个与 PASC 相关的特异性差异甲基化区域(DMRs),每个区域平均有 15 个连续位置,将 PASC 患者与两个对照组区分开来。对PASC调节的DMRs进行的基元分析确定了调节昼夜节律的转录因子和其他因子的结合域。一些注释为蛋白质编码基因的DMRs与RNA表达的变化有关。机器学习支持向量算法和随机森林分层聚类揭示了基因组中28个独特的差异甲基化位置(DMPs),这些位置可区分生活质量较好和较差的患者:血液DNA甲基化水平可识别PASC,对PASC的严重程度进行分层,并表明DNA图案是PASC中昼夜节律调节途径的靶标:本项目由以下机构资助:NIH-AI173035(A. Jaitovich和R. Alisch);NIH-AG066179(R. Alisch)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blood DNA methylation in post-acute sequelae of COVID-19 (PASC): a prospective cohort study.

Background: DNA methylation integrates environmental signals with transcriptional programs. COVID-19 infection induces changes in the host methylome. While post-acute sequelae of COVID-19 (PASC) is a long-term complication of acute illness, its association with DNA methylation is unknown. No universal blood marker of PASC, superseding single organ dysfunctions, has yet been identified.

Methods: In this single centre prospective cohort study, PASC, post-COVID without PASC, and healthy participants were enrolled to investigate their symptoms association with peripheral blood DNA methylation data generated with state-of-the-art whole genome sequencing. PASC-induced quality-of-life deterioration was scored with a validated instrument, SF-36. Analyses were conducted to identify potential functional roles of differentially methylated loci, and machine learning algorithms were used to resolve PASC severity.

Findings: 103 patients with PASC (22.3% male, 77.7% female), 15 patients with previous COVID-19 infection but no PASC (40.0% male, 60.0% female), and 27 healthy volunteers (48.1% male, 51.9% female) were enrolled. Whole genome methylation sequencing revealed 39 differentially methylated regions (DMRs) specific to PASC, each harbouring an average of 15 consecutive positions, that differentiate patients with PASC from the two control groups. Motif analyses of PASC-regulated DMRs identify binding domains for transcription factors regulating circadian rhythm and others. Some DMRs annotated to protein coding genes were associated with changes of RNA expression. Machine learning support vector algorithm and random forest hierarchical clustering reveal 28 unique differentially methylated positions (DMPs) in the genome discriminating patients with better and worse quality of life.

Interpretation: Blood DNA methylation levels identify PASC, stratify PASC severity, and suggest that DNA motifs are targeted by circadian rhythm-regulating pathways in PASC.

Funding: This project has been funded by the following agencies: NIH-AI173035 (A. Jaitovich and R. Alisch); and NIH-AG066179 (R. Alisch).

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来源期刊
EBioMedicine
EBioMedicine Biochemistry, Genetics and Molecular Biology-General Biochemistry,Genetics and Molecular Biology
CiteScore
17.70
自引率
0.90%
发文量
579
审稿时长
5 weeks
期刊介绍: eBioMedicine is a comprehensive biomedical research journal that covers a wide range of studies that are relevant to human health. Our focus is on original research that explores the fundamental factors influencing human health and disease, including the discovery of new therapeutic targets and treatments, the identification of biomarkers and diagnostic tools, and the investigation and modification of disease pathways and mechanisms. We welcome studies from any biomedical discipline that contribute to our understanding of disease and aim to improve human health.
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