Pan-disease characterization of DNA methylation dysregulation

DNA 甲基化失调的泛疾病特征

• 批准号: 10191781
• 负责人: Kendell Clement
• 金额: $ 17.04万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-12 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10191781
• 关键词: Affect; Aging; Autoimmune Diseases; Biological Assay; CRISPR screen; Characteristics; Chromatin; Clustered Regularly Interspaced Short Palindromic Repeats; Collection; Computational algorithm; DNA Methylation; DNA Methylation Regulation; DNA Sequence Alteration; Data; Data Set; Databases; Development; Diagnostic; Disease; Disease model; Early Diagnosis; Early Intervention; Elements; Enzymes; Epigenetic Process; Experimental Designs; Fingerprint; Gene Expression; Gene Mutation; Generations; Genes; Genetic; Genome; Genomics; Goals; Health; Investigation; Knowledge; Lead; Link; Machine Learning; Malignant Neoplasms; Mental disorders; Metabolic Diseases; Metabolic Pathway; Methylation; Modeling; Mutate; Pathway interactions; Patients; Pattern; Play; Process; Regulation; Regulatory Element; Reporting; Reproducibility; Research; Research Personnel; Role; Sample Size; Sampling; Scientist; Severity of illness; Technology; Therapeutic; Therapeutic Intervention; Tissue Sample; Tissues; Training; Untranslated RNA; Validation; Variant; base; cost; diagnostic biomarker; disease diagnosis; disease phenotype; epigenome; experience; genome analysis; genomic variation; high throughput screening; human disease; large datasets; methylation pattern; novel; novel strategies; therapeutic target; transcriptome; treatment response

DNA methylation is an important epigenetic mark with a regulated pattern in healthy tissues. Disruption of this pattern, called methylation dysregulation, has been reported in many diseases including cancer, autoimmune diseases, metabolic and psychological disorders, and diseases related to aging. Importantly, methylation dysregulation has been observed in pre-disease states and the degree of dysregulation correlates with disease severity and also response to treatment. These observations compel the study of methylation dysregulation because it may reveal common origins of human disease, and because genomic elements (e.g. genes, mutations, and regulatory features) associated with methylation dysregulation may be potential targets for diagnostic and early intervention therapies. However, the genomic elements that control and maintain methylation dysregulation have not been well-characterized. Understanding the mechanisms and pathways that are responsible for the establishment of epigenetic dysregulation is critical for understanding the establishment of the disease phenotype in general. We hypothesize that specific genomic elements could contribute to methylation dysregulation in reproducible ways across diseases. This research seeks to identify genomic elements that may initiate a disease state that is common across multiple diseases. This will be accomplished by the development of computational algorithms to leverage and integrate patient samples from many diseases, as well as the development of a new high-throughput genomic screen. Specifically, we propose the following specific aims: (1) Identification of genes associated with methylation dysregulation using a pan-disease machine-learning approach; (2) Exploration of the contribution of the noncoding genome to methylation dysregulation through analysis of genome variants and chromatin accessibility data; (3) Development and validation of a novel CRISPR screen to link gene perturbations to methylation landscapes in a high-throughput manner. In summary, completion of these aims will produce an in-depth characterization of the genomic elements associated with methylation dysregulation, leading to understanding of the processes and mechanisms of epigenetic dysregulation. More broadly, the proposed analysis framework and computational approach will explore the utility of integrative pan-disease studies to identify common characteristics of disease which could lead to diagnostic and therapeutic solutions. This proposal takes advantage of the applicant's expertise in genetics, genomics, and high-throughput assays. It also includes training and research experience in experimental design and execution which will advance the candidate's goal of becoming an independent research scientist capable of investigating genome function, specifically the genomic origins of human disease.

DNA甲基化是一种重要的表观遗传标记，在健康组织中具有调节模式。破坏这种 在许多疾病中，包括癌症，自身免疫性疾病， 疾病、代谢和心理障碍以及与衰老有关的疾病。重要的是， 在疾病前状态中已经观察到失调，失调的程度与疾病相关 严重程度和对治疗的反应。这些观察结果促使对甲基化失调的研究 因为它可以揭示人类疾病的共同起源，并且因为基因组元件（例如基因， 与甲基化失调相关的突变和调控特征）可能是潜在的靶点， 诊断和早期干预治疗。然而，控制和维持 甲基化失调还没有得到很好的表征。了解机制和途径 负责建立表观遗传失调是至关重要的理解， 疾病表型的建立。我们假设特定的基因组元件可以 在疾病中以可重复的方式促进甲基化失调。 这项研究旨在确定可能引发疾病状态的基因组元素，这些疾病状态在人类中很常见。 多种疾病。这将通过开发计算算法来实现， 整合来自许多疾病的患者样本，以及开发新的高通量基因组 屏幕具体而言，我们提出以下具体目标： (1)利用泛疾病机器学习识别与甲基化失调相关的基因 接近; (2)通过分析非编码基因组对甲基化失调的贡献， 基因组变体和染色质可及性数据; (3)开发和验证一种新的CRISPR筛选，将基因扰动与甲基化联系起来 以高通量的方式进行景观。 总之，这些目标的完成将产生基因组元件的深入表征 与甲基化失调相关，从而了解甲基化的过程和机制。 表观遗传失调更广泛地说，拟议的分析框架和计算方法将 探索综合性泛疾病研究的效用，以确定疾病的共同特征， 导致诊断和治疗解决方案。该提案利用了申请人在以下方面的专业知识： 遗传学、基因组学和高通量测定。它还包括培训和研究经验， 实验设计和执行，这将促进候选人成为一个独立的目标 能够研究基因组功能的研究科学家，特别是人类疾病的基因组起源。