Deciphering the role of neuronal and peripheral DNA methylation in suicide and bipolar disorder

解读神经元和外周 DNA 甲基化在自杀和双相情感障碍中的作用

• 批准号: 10165832
• 负责人: Gabriel Rodrigo Fries
• 金额: $ 17.48万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10165832
• 关键词: Accounting; Address; Adult; Affect; Autopsy; Award; Bioinformatics; Biology; Bipolar Disorder; Blood; Brain; Cause of Death; Cell Nucleus; Cessation of life; Clinical; Collection; Communities; DNA Methylation; Data; Data Set; Development; Diagnosis; Disease; Early Intervention; Early identification; Ensure; Environment; Enzymes; Epigenetic Process; Faculty; Fluorescence; Foundations; Generations; Genetic; Genetic Risk; Genotype; Goals; Health Professional; Health Sciences; Human; Individual; Intervention; Knowledge; Lead; Light; Masks; Mediating; Medical center; Mental Health; Mental disorders; Mentors; Methodology; Methylation; Mission; Molecular; Mood Disorders; National Institute of Mental Health; Neurons; Pathway Analysis; Pathway interactions; Patients; Peripheral; Phenotype; Play; Population; Prefrontal Cortex; Prevention; Research; Resources; Risk; Role; Sampling; Sorting - Cell Movement; Stress; Suicide; Suicide attempt; Testing; Texas; Tissues; Training; United States National Institutes of Health; Universities; Variant; Vulnerable Populations; bead chip; bioinformatics tool; biological adaptation to stress; biomarker identification; biosignature; bisulfite; career; cell type; clinical biomarkers; clinically relevant; clinically significant; cohort; completed suicide; epigenomics; genome wide methylation; genome-wide analysis; high risk; machine learning algorithm; methylation biomarker; methylome; methylomics; mortality; multidisciplinary; peripheral blood; polygenic risk score; prediction algorithm; prophylactic; pyrosequencing; statistics; success; suicidal behavior; suicidal risk; tool; translational study

Project Summary/Abstract Prevention of suicidal behavior, especially among patients with mood disorders, is of uttermost importance among mental health professionals. Patients with bipolar disorder (BD), which affects around 1-2% of the population, are at a particularly high risk for developing suicidal behavior, with 25-50% of patients making at least one suicide attempt in their lifetime. In addition, although there is evidence that BD and suicide share a genetic risk and that stress may play a key role in suicidality, the mechanisms by which some patients are more vulnerable to suicidal behavior than others are vastly unknown. Guided by strong preliminary data, we hypothesize that epigenetic mechanisms, including DNA methylation, may underlie suicide risk among BD patients. Moreover, DNA methylation markers may provide clinically-relevant biomarkers for the identification of patients at highest risk for suicidal behavior. These hypotheses will be tested by completing three specific aims. In Aim 1, we will characterize DNA methylation alterations with the latest-generation Illumina MethylationEPIC BeadChip 850K platform in a discovery sample of neurons isolated from post-mortem dorsolateral prefrontal cortex tissues from patients with BD that committed suicide or died of other causes and controls. Promising markers will be validated by oxidative bisulfite pyrosequencing and further explored by pathway analyses. In Aim 2, we will investigate the coordinated changes between genetic risk for BD and suicide attempt and DNA methylation alterations in post-mortem prefrontal cortex using the same cohort as Aim 1 and a replication cohort from the UTHealth Brain Collection for Research in Psychiatric Disorders. In Aim 3, we will analyze the clinical correlates of methylome markers of suicide in an independent cohort of adult patients with BD that have previously attempted to commit suicide or not, compared to healthy controls, from which a comprehensive dataset with demographic, clinical, and neuroanatomical data is available, as well as genome-wide methylation and genotyping data. Specific targets and pathways predicting suicidal behavior will be further explored by sophisticated statistics and bioinformatics tools while controlling for co-variables known to associate with suicidal risk, followed by the development of machine learning algorithms for the prediction of suicidality at the individual level. Of note, the overarching goal of this K01 is to further the PI’s expertise in the biology and clinical aspects of suicide, bioinformatics, post-mortem analyses, and epigenomics, which will ensure a methodologically strong foundation to launch an independent lab in psychiatric epigenetics. Importantly, a strong group of mentors and collaborators with a remarkable track record in training junior faculty has been selected to provide intellectual and technical input during the award period. In addition, the outstanding resources, facilities, and multidisciplinary scientific community at the University of Texas Health Science Center at Houston and the Texas Medical Center represent an ideal environment to ensure that the PI accomplishes his research and career objectives. This proposal is well aligned with the mission of the NIMH, and it will not only provide the PI with crucial training required to his transition to full independence, but also address important, testable questions regarding the poorly understood risk for suicide among BD patients and the lack of specific tools for the identification of vulnerable subjects.

项目总结/摘要 预防自杀行为，特别是在有情绪障碍的患者中， 卫生专业人员。双相情感障碍（BD）患者影响约1-2%的人口， 自杀行为的高风险，25-50%的患者一生中至少有一次自杀企图。在 此外，尽管有证据表明BD和自杀具有遗传风险，并且压力可能在自杀倾向中起关键作用， 一些病人比其他人更容易产生自杀行为的机制还很不清楚。指导 根据强有力的初步数据，我们假设包括DNA甲基化在内的表观遗传机制可能是自杀的基础 BD患者的风险。此外，DNA甲基化标志物可以为癌症的发生提供临床相关的生物标志物。 确定自杀行为风险最高的患者。这些假设将通过完成三个具体的 目标。在目标1中，我们将使用最新一代的Illumina MethylationEPIC来表征DNA甲基化改变。 BeadChip 850 K平台在从死后背外侧前额叶皮层组织分离的神经元发现样本中的应用 自杀或死于其他原因的BD患者和对照组。有希望的标记将由以下人员验证 氧化亚硫酸氢盐焦磷酸测序并通过途径分析进一步探索。在目标2中，我们将研究协调的 BD遗传风险与自杀企图之间的变化及死后前额皮质DNA甲基化改变 使用与Aim 1相同的队列和来自UTHealth精神病学研究脑集合的复制队列 精神失常。在目标3中，我们将在一个独立的队列中分析自杀甲基化标志物的临床相关性。 与健康对照组相比，既往曾试图自杀或未尝试自杀的BD成人患者， 一个包含人口统计学、临床和神经解剖学数据的综合数据集是可用的， 甲基化和基因分型数据。预测自杀行为的具体目标和途径将进一步探讨， 复杂的统计学和生物信息学工具，同时控制已知与自杀风险相关的协变量， 其次是机器学习算法的发展，用于预测个人层面的自杀倾向。的 请注意，本K 01的总体目标是促进PI在自杀生物学和临床方面的专业知识， 生物信息学、死后分析和表观基因组学，这将确保发射的方法学基础 一个独立的精神病学实验室重要的是，一群强大的导师和合作者具有出色的 在奖励计划期间，在培训初级教员方面的往绩已获挑选，以提供知识和技术方面的投入。 此外，德克萨斯大学的优秀资源、设施和多学科科学界 休斯顿健康科学中心和德克萨斯医疗中心提供了一个理想的环境，以确保PI 完成他的研究和职业目标。这一建议与NIMH的使命是一致的， 不仅为PI提供过渡到完全独立所需的关键培训，而且还解决重要的，可测试的 关于BD患者中自杀风险知之甚少以及缺乏特定工具的问题 识别弱势群体。