The Epitranscriptome as a Novel Mechanism of Arsenic-Induced Diabetes.

表观转录组作为砷诱发糖尿病的新机制。

• 批准号: 10518402
• 负责人: Andrea Baccarelli
• 金额: $ 62.25万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2025-10-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10518402
• 关键词: Adult; Affect; Albuminuria; American Indians; Arizona; Arsenic; Beta Cell; Biological; Blood; Blood Cells; Cause of Death; Cellular Stress; Childhood; Clinical; Clinical Data; Clinical Markers; Communities; DNA Methylation; Data; Development; Diabetes Mellitus; Disputes; Elderly man; Environmental Pollutants; Exposure to; Fingerprint; Food; Functional disorder; Funding; Future; Gene Expression; Gene Expression Regulation; Genes; Genetic Transcription; Glucose; Glycosylated Hemoglobin; Heart; Hepatic; Human; Immune response; Individual; Inflammation; Infrastructure; Insulin; Insulin Resistance; Intervention; Investments; Joints; Life; Link; Lipids; Liver; Longitudinal Studies; Machine Learning; Measures; Mendelian randomization; Messenger RNA; Metabolic Marker; Metabolic dysfunction; Metabolic syndrome; Modification; Names; Non-Insulin-Dependent Diabetes Mellitus; Oklahoma; Oxidative Stress Induction; Participant; Pathogenesis; Pathway interactions; Phenotype; Pilot Projects; Plasma; Play; Population; Prevalence; Preventive; Process; Proteins; RNA; RNA Stability; Reader; Recommendation; Research; Resources; Risk; Role; Schedule; Serum; Severities; Shapes; South Dakota; System; Testing; Tissues; Transcript; Translations; United States; Visit; Water; Whole Blood; blood glucose regulation; cohort; design; diabetes mellitus therapy; epigenomics; epitranscriptome; epitranscriptomics; fat mass and obesity-associated protein; follow-up; histone modification; insight; multidimensional data; novel; phenotypic data; preventive intervention; response; statistical and machine learning; systemic inflammatory response; toxicant

SUMMARY In the United States, the prevalence of type 2 diabetes mellitus (T2DM) is particularly high among American Indian (AI) communities. Arsenic (As), a pervasive environmental contaminant disproportionately affecting AI communities, may explain this increased risk. Arsenic induces oxidative stress and systemic low-grade inflammation leading to β-cell dysfunction and insulin resistance in target tissues. However, the impact of As on T2DM has been disputed due to a lack of coherent mechanism for these findings. Previous studies have focused on epigenomic mechanisms (e.g., DNA methylation, histone modifications), overlooking downstream regulatory mechanisms that can more directly shape phenotypes. We propose to investigate the RNA modification N6- methyladenosine (m6A), the most prevalent epitranscriptomic modification on messenger RNA, which is directly involved in the cellular stress response. In experimental systems, arsenic induces a m6A response. m6A also modulates key processes underlying T2DM pathogenesis, including immune response and systemic inflammation. m6A is controlled by a group of proteins called reader, writer, and erasers (RWEs), responsible for adding, interpreting, and removing m6A marks. Fat mass and obesity-associated protein (FTO) is one example of an arsenic-sensitive m6A eraser with strong ties to T2DM and glucose homeostasis. Our pilot study in elderly men exposed to low-level arsenic supported these findings. We propose to test the hypothesis that altered m6A and RWEs are plausible mechanisms for As-related T2DM in the Strong Heart Study (SHS). The SHS is an ongoing longitudinal study in AI communities in Arizona, Oklahoma, and North/South Dakota with detailed clinical data for T2DM and metabolic syndrome (MetS). The SHS has measured speciated As exposure data covering childhood and adult exposure windows, both independently associated with T2DM in previous research. Leveraging the cohort design, exposure and phenotypic data, infrastructure, and study team, we propose to conduct epitranscriptomic analysis of mRNA m6A profiles via m6A sequencing and measure mRNA expression of 20 RWEs using whole blood from 1100 participants at the upcoming SHS follow up visit (scheduled for 2022- 23). Our specific aims are to: 1) determine the association of past and current As exposure with epitranscriptomic profiles of m6A and RWEs mRNA expression levels in blood; 2) determine the association of blood m6A epitranscriptomic profiles with metabolic markers and MetS, clinical T2DM prevalence, and T2DM control (glycated hemoglobin, albuminuria); 3) develop a predictive m6A fingerprint that quantifies the risk of T2DM due to As exposure using machine learning approaches. For aims 1 and 2 we will further use Mendelian randomization to assess causal relationships. Characterization of m6A profiles in a population of AI adults highly impacted by T2DM will reveal biological features linking a pervasive toxicant such as As to diabetes. In addition to leading to interventions to reduce As exposure in the US and globally, defining the roles of m6A and RWEs in T2DM may contribute to new targets for future diabetes therapies.

概括 在美国，2 型糖尿病 (T2DM) 的患病率在美国人中特别高 印度（AI）社区。砷 (As)，一种普遍存在的环境污染物，对人工智能的影响尤为严重 社区，可以解释这种风险增加的原因。砷会诱发氧化应激和全身性低度氧化应激 炎症导致靶组织中的β细胞功能障碍和胰岛素抵抗。然而，As 对 由于这些发现缺乏一致的机制，T2DM 一直存在争议。之前的研究主要集中在 表观基因组机制（例如 DNA 甲基化、组蛋白修饰），忽视下游调控 可以更直接地塑造表型的机制。我们建议研究 RNA 修饰 N6- 甲基腺苷 (m6A) 是信使 RNA 上最常见的表观转录组修饰，可直接 参与细胞应激反应。在实验系统中，砷会诱导 m6A 反应。 m6A也 调节 T2DM 发病机制的关键过程，包括免疫反应和全身 炎。 m6A 由一组称为读取器、写入器和擦除器 (RWE) 的蛋白质控制，负责 添加、解释和删除 m6A 标记。脂肪量和肥胖相关蛋白 (FTO) 就是一个例子 砷敏感的 m6A 擦除器与 T2DM 和葡萄糖稳态有密切关系。我们针对老年人的试点研究 接触低浓度砷的男性支持了这些发现。我们建议检验改变 m6A 的假设 在强心脏研究 (SHS) 中，RWE 是与 As 相关的 T2DM 的可能机制。 SHS 是一个 亚利桑那州、俄克拉荷马州和北/南达科他州的人工智能社区正在进行纵向研究，并提供详细的临床研究 T2DM 和代谢综合征 (MetS) 的数据。 SHS 测量了特定砷暴露数据，涵盖 儿童和成人暴露窗口，在之前的研究中均与 T2DM 独立相关。 利用队列设计、暴露和表型数据、基础设施和研究团队，我们建议 通过 m6A 测序对 mRNA m6A 谱进行表观转录组分析并测量 mRNA 表达 20 个 RWE 在即将到来的 SHS 随访（计划于 2022 年- 23）。我们的具体目标是：1) 确定过去和当前砷暴露与表观转录组学的关联 血液中 m6A 和 RWEs mRNA 表达水平的概况； 2) 测定血液m6A的关联性 代谢标志物和 MetS 的表观转录组谱、临床 T2DM 患病率和 T2DM 控制 （糖化血红蛋白、蛋白尿）； 3) 开发预测性 m6A 指纹，量化 T2DM 的风险 作为使用机器学习方法的接触。对于目标 1 和 2，我们将进一步使用孟德尔 随机化来评估因果关系。 AI 成人群体中 m6A 谱的表征高度 受 T2DM 影响的患者将揭示与糖尿病等普遍毒物相关的生物学特征。此外 采取干预措施减少美国和全球的砷暴露，确定 m6A 和 RWE 在 T2DM 可能有助于未来糖尿病治疗的新目标。