Clusters of Epigenetic Networks at Birth and Asthma Incidence in Children

出生时的表观遗传网络簇和儿童哮喘发病率

• 批准号: 10647235
• 负责人: Hongmei Zhang
• 金额: $ 17.83万
• 依托单位: UNIVERSITY OF MEMPHIS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10647235
• 关键词: Address; Adolescence; Age; Agreement; Asthma; Birth; Child; Childhood; Childhood Asthma; Cytosine; DNA Methylation; Data; Detection; Development; Disease; Elderly; Epidemiology; Epigenetic Process; Etiology; Evaluation; Future; General Population; Genes; Guanine; Health; Heterogeneity; Incidence; Individual; Joints; Knowledge; Label; Life; Longitudinal Studies; Longitudinal cohort; Machine Learning; Malignant Neoplasms; Manuals; Mendelian randomization; Meta-Analysis; Methods; Methylation; Obesity; Parents; Participant; Pathogenesis; Patients; Population; Pregnancy; Prevention; Proteomics; Quantitative Trait Loci; Race; Recording of previous events; Risk; Role; Selection Bias; Single Nucleotide Polymorphism; Site; Specificity; Statistical Methods; Techniques; Testing; Time; Uncertainty; Validation; Work; cohort; epidemiology study; follow-up; gene network; genetic variant; genome-wide; high risk; improved; inorganic phosphate; microbiome research; multi-racial; novel strategies; prevent; screening; sex; simulation; transcriptomics; web-based tool; young adult

This is an epidemiological study on the epigenetic origins of asthma in children and young adulthood. It has been increasingly recognized that asthma is a consequence of joint activities among genes rather than of individual genes’ independent contributions. Examining individual contributions of CpGs on asthma development is biologically ungrounded and we take a high risk of concluding incomplete and/or misleading findings. Such limitations have been widely agreed upon, and methods to address joint activities among genes have been proposed, including approaches to identify differentially methylated regions (DMRs) and those for detection of gene networks. However, the DMR approach is potentially flawed, since almost all DMRs are inferred based on effects of each individual CpG rather than joint effects of CpGs. Defining networks amongst genes or CpGs allow better understanding of their concerted effects. Current network constructions, however, either focus on a population as a whole or on a specific group. Constructing one network for a general population lacks purity, since it overlooks underlying heterogeneity among subjects (e.g., heterogeneity in asthma risk). Whilst building a network for a group of disease patients will substantially limit the ability to predict and prevent disease, due to potential reverse-causation on gene activities. Currently, no methods are available that address heterogeneity while building networks. We propose an approach to detect distinct epigenetic networks (DENs) with each unique to a group of subjects via network clustering using DNA methylation (DNAm) data before disease manifestation, e.g., at-birth DNAm and childhood asthma. The constructed network in each cluster will represent unique epigenetic features of a homogeneous group of subjects. Differentiation between networks constructed under different conditions support the feasibility of network clustering in a general population. In addition, in asthma studies, we will study the longitudinal association of DENs at birth with asthma incidence in children, post-adolescence, and young adulthood, assess the role of age, sex, and race in this association, and examine the benefit of evaluating joint rather than individual activities of CpGs on asthma incidence. The findings of this study will inform to what extent CpGs work jointly and contribute to the development of asthma, and will benefit future studies on early prediction of asthma acquisition for each sex and different races. Furthermore, the method to be developed will be readily applied to other health conditions with other omics data different from DNAm. We will carry out this important study in three birth cohorts, two cohorts with whites (the IOWBC and ALSPAC birth cohorts focusing on asthma history) and one cohort with both white and black participants (the NEST birth cohort). These three birth cohorts will allow us to discover, replicate, and assess region and race specificity of DENs and their epidemiological association with asthma incidence. For CpGs in modules of a network or networks showing association with asthma incidence at one or more stages of life, we will evaluate the potential causality of the CpGs via Mendelian randomization (MR) tests using the MR-base webtool. For the statistical methods to detect DENs, we will build the method into a publicly available R package accompanied by a detailed manual with concrete examples.

这是一项关于儿童和青少年哮喘表观遗传起源的流行病学研究。它一直 人们越来越认识到哮喘是基因之间联合活动的结果，而不是单个基因的结果 独立贡献。检查 CpG 对哮喘发展的个体贡献是生物学上的 没有根据，我们很可能得出不完整和/或误导性的调查结果。此类限制已 已得到广泛商定，并提出了解决基因间联合活动的方法，包括方法 识别差异甲基化区域（DMR）以及用于检测基因网络的区域。然而，DMR 该方法可能存在缺陷，因为几乎所有 DMR 都是根据每个单独 CpG 的影响推断出来的，而不是根据 比 CpG 的联合效应。定义基因或 CpG 之间的网络可以更好地理解它们的协同作用 影响。然而，当前的网络建设要么关注整个人口，要么关注特定群体。 为一般人群构建一个网络缺乏纯度，因为它忽视了潜在的异质性 受试者（例如哮喘风险的异质性）。在为一群疾病患者建立网络的同时，将极大地 由于基因活动的潜在反向因果关系，限制了预测和预防疾病的能力。目前，没有 有一些方法可以在构建网络时解决异构性问题。我们提出了一种检测不同的方法 表观遗传网络 (DEN) 通过使用 DNA 甲基化的网络聚类，每个网络对于一组受试者都是独一无二的 (DNAm) 疾病表现前的数据，例如出生时 DNAm 和儿童哮喘。构建的网络在 每个簇将代表同质受试者组的独特表观遗传特征。之间的区别 在不同条件下构建的网络支持一般人群中网络聚类的可行性。 此外，在哮喘研究中，我们将研究出生时 DEN 与哮喘发病率的纵向关联 儿童、青春期后和成年早期，评估年龄、性别和种族在这种关联中的作用，并检查 评估 CpG 的联合活动而非个体活动对哮喘发病率的益处。这项研究的结果 将告知 CpG 在多大程度上共同发挥作用并促进哮喘的发展，并将有益于未来 关于各性别和不同种族哮喘发病早期预测的研究。此外，该方法是 开发的技术将很容易应用于其他健康状况，并使用不同于 DNAm 的其他组学数据。我们将携带 这项重要的研究针对三个出生队列，其中两个是白人队列（IOWBC 和 ASPAC 出生队列，重点关注 哮喘病史）和一个由白人和黑人参与者组成的队列（NEST 出生队列）。这三生 队列将使我们能够发现、复制和评估 DEN 的区域和种族特异性及其流行病学 与哮喘发病率的关系。对于一个或多个网络模块中的 CpG，显示与 生命中一个或多个阶段的哮喘发病率，我们将通过孟德尔法则评估 CpG 的潜在因果关系 使用基于 MR 的网络工具进行随机化 (MR) 测试。对于检测 DEN 的统计方法，我们将构建 方法放入公开可用的 R 包中，并附有带有具体示例的详细手册。