Research Support Core C: Computational Biology in Substance Use

研究支持核心 C：物质使用中的计算生物学

• 批准号: 10632097
• 负责人: MARK R CHANCE
• 金额: $ 73.51万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10632097
• 关键词: Address; Area; Automobile Driving; Behavioral; Bioinformatics; Biological; Biological Assay; Biometry; Biomimetics; Blood - brain barrier anatomy; Cannabis; Cell model; Cells; Clinical; Cocaine; Color; Comprehensive Cancer Center; Computational Biology; Constipation; Data; Data Analyses; Data Set; Data Storage and Retrieval; Databases; Dedications; Defect; Development; Dimensions; Disease; Disease Progression; Doctor of Medicine; Doctor of Philosophy; Drug usage; Experimental Designs; Faculty; Fentanyl; Flow Cytometry; Functional disorder; Funding; Genes; Genetic Transcription; Genomics; HIV; Health; Heroin; Homeostasis; Immune; Immune system; Immunologics; Intestinal permeability; Knowledge; Maps; Mass Spectrum Analysis; Measures; Meta-Analysis; Metabolism; Methamphetamine; Methods; Modeling; Molecular; Mucous Membrane; Multiomic Data; National Institute of Drug Abuse; Neurocognitive; Neurologic; Neurological outcome; Opioid; Pathology; Pathway interactions; Patients; Persons; Pharmaceutical Preparations; Physiological; Plasma; Post-Translational Protein Processing; Postdoctoral Fellow; Preparation; Proteome; Proteomics; Protocols documentation; Reporting; Research; Research Personnel; Research Support; Resolution; Resource Sharing; Resources; Risk; Sampling; Services; Severity of illness; Small RNA; Source; Specimen; Structure; Substance Use Disorder; Substance of Abuse; System; Technology; Tissue Model; Tissues; Training; Untranslated RNA; Viral; Virus Latency; arm; bacterial community; biomarker identification; biomarker validation; body system; cohort; complex data; computational pipelines; computing resources; cytokine; data acquisition; data curation; data dissemination; data integration; data management; design; drug testing; epigenome; gastrointestinal; gastrointestinal function; graduate student; gut dysbiosis; in vivo; longitudinal analysis; member; metabolome; metabolomics; microbial; microbiome; multiple omics; new technology; novel therapeutic intervention; personalized approach; professor; programs; public database; response; role model; single-cell RNA sequencing; stem; substance use; therapeutic development; transcriptome sequencing; transcriptomics

Project Summary - Computational Biology in Substance Use Core C A large number of studies have been performed to identify the impact of drug use on the mechanisms that govern the integrity of the innate and adaptive arms of the immune system, gastrointestinal (GI) function, and neurocognitive disease in the context of HIV persistence. Such studies have led to conflicting results largely because of the complexity of these systems and the low resolution of assays aimed at measuring the different arms, cells, and functions. The lack of assays that can provide an accurate assessment of substance use is also at the source of these conflicting results that have attempted to associate mechanisms downstream of substance use. on HIV disease severity. To address these issues, and in support of the NIDA funded projects at CWRU and nationwide, the CWRU Center for Excellence on the Impact of Substance Use on HIV will rely on the Computational Biology in Substance Use Research Support Core C. This core is a comprehensive shared resource that provides advanced transcriptomics, genomics, functional microbiome, metabolomics, proteomics, bioinformatics, and computational biology resources to Center investigators. This shared resource leverages multiple technologies under the direction of Drs. Mark Chance, Adam Burgener, Saba Valadkhan, and Konstantin Leskov that provide that provide advanced computational and experimental platforms to serve the Substance Use program and the Center’s investigators. Core C will provide a centralized data management and analysis resource to all Center investigators making the navigation of the ‘omics’ landscape seamless and driving appropriate choices of a wide array of ‘omics’ technologies for specific experimental designs. It will be focused on ‘omics’ data acquisition and storage (Aim 1), training and data analysis (Aim 2), and data integration, biomarker validation, and modeling of these datasets (Aim 3). The deliverables of Core C will be an iterative database of all experimental datasets, including protocols and sample identifiers (Aim 1), state of the art analysis of all datasets stemming from all ‘omics’ platforms as well as assays that can provide quantitative assessment of drug levels (Aim 2). Aim 3 will focus on integrating and performing meta-analysis of all datasets across all cohorts and physiological systems to define generalizable and distinct mechanisms that underlie the impact of cocaine, methamphetamine, opioids, and cannabis on HIV latency, neurocognitive dysfunction, constipation, intestinal permeability, damage to the blood brain barrier, and loss of immune homeostasis and function. This integrated approach will identify predictors of HIV disease progression specific to single and poly-users of each drug for each organ system, which could lead to the development of therapeutic approaches tailored to correct the GI, neurological, and immunological pathologies in persons with drug use and HIV.

项目摘要-计算生物学在物质使用中的核心C 已经进行了大量的研究，以确定药物使用对 管理免疫系统先天和适应性手臂完整性的机制， 胃肠(GI)功能，以及艾滋病毒持续背景下的神经认知疾病。是这样的 研究导致了相互矛盾的结果，很大程度上是因为这些系统和 旨在测量不同手臂、细胞和功能的分析分辨率低。缺乏 能够提供对物质使用情况的准确评估的分析也是这些问题的根源 相互矛盾的结果，试图将药物使用的下游机制联系起来。 关于艾滋病的严重程度。为了解决这些问题，并支持NIDA资助的项目 在CWRU和全国范围内，CWRU卓越中心关于物质使用对 艾滋病毒将依靠计算生物学在物质使用方面的研究支持核心C。 这个核心是一个全面的共享资源，它提供高级转录组学， 基因组学、功能微生物组、代谢组学、蛋白质组学、生物信息学和计算 给中心的调查人员提供生物资源。这种共享资源利用了多种技术 在Mark Chance博士、Adam Burgener博士、Saba Valadkhan博士和Konstantin博士的指导下 Leskov提供了提供高级计算和实验平台 物质使用计划和该中心的调查人员。核心C将提供集中的 向所有中心调查人员提供数据管理和分析资源，以导航 “组学”格局天衣无缝，推动了一系列“组学”的适当选择 用于特定实验设计的技术。它将专注于“经济学”的数据获取和 储存(目标1)、培训和数据分析(目标2)、数据整合、生物标志物验证、 以及对这些数据集进行建模(目标3)。核心C的交付成果将是一个迭代数据库 在所有实验数据集中，包括方案和样本识别符(目标1)，最新水平 分析来自所有“组学”平台的所有数据集，以及能够提供 药物水平的定量评估(目标2)。目标3将专注于整合和执行 对所有队列和生理系统的所有数据集进行荟萃分析，以确定 可卡因、甲基苯丙胺、 阿片类药物和大麻对艾滋病毒潜伏期、神经认知功能障碍、便秘、肠道的影响 通透性，对血脑屏障的破坏，免疫平衡和功能的丧失。 这一综合方法将确定艾滋病毒疾病进展的预测因子，具体为单项和 每种药物对每个器官系统的多用户，这可能导致 为纠正胃肠道、神经和免疫病理而量身定做的治疗方法 对于吸毒者和艾滋病毒携带者。