Statistical Methods for Enhanced Mapping of Microbiome Relationships

增强微生物组关系图谱的统计方法

• 批准号: 10719129
• 负责人: MICHAEL Chiao-An WU
• 金额: $ 33.06万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10719129
• 关键词: Address; Area; Automobile Driving; Back; Cardiovascular Diseases; Clinical; Computer software; Data; Detection; Development; Diabetes Mellitus; Dimensions; Disease; Disease Outcome; Ensure; Etiology; Failure; Genetic; Genomics; Heterogeneity; Human; Human Microbiome; Individual; Infection; Intervention; Joints; Knowledge; Link; Literature; Lung; Malignant Neoplasms; Maps; Mendelian randomization; Methodology; Methods; Microbe; Modeling; Neurodegenerative Disorders; Outcome; Patients; Pregnancy; Process; Quantitative Trait Loci; Research Personnel; Risk Reduction; Role; Sample Size; Scientific Advances and Accomplishments; Statistical Methods; Taxon; Taxonomy; Testing; Therapeutic Intervention; Work; burden of illness; cancer immunotherapy; cohort; computerized tools; flexibility; genetic variant; gut microbiome; improved; instrument; microbial; microbiome; novel; novel therapeutics; open source; preventive intervention; rare variant; risk mitigation; success; tool; translational barrier; user friendly software; vaginal microbiome

PROJECT SUMMARY/ABSTRACT The human microbiome is integrally related to a vast range of human disorders and represents an imperative gateway toward mitigating the burden of these diseases, particularly as the microbiome is eminently modifiable. This has culminated in microbially oriented risk reduction and clinical interventions, which have proven efficacious in diverse situations ranging from infections to cancer immunotherapy. However, despite some high- profile successes, many other studies have failed. A central theme underlying these failures, and even many of the success stories, is our fundamentally limited understanding of how microbes interact with each other, with host genomics, and with outcomes. Recently, efforts to assess and map these relationships are taking place within large-scale profiling studies, but unfortunately, the tools used for elucidating these connections may be underpowered, difficult to interpret, or even subject to severe false positives due to strong underlying assumptions. Therefore, motivated by problems within three of the largest and richest microbiome profiling studies, this proposal seeks to fill critical gaps in the methodological literature by addressing four major areas. Specifically, we aim to develop a comprehensive suite of tools for (1) enhanced microbial co-occurrence network construction; (2) enhanced discovery of SNPs and rare variants associated with individual microbial taxa; and (3) assessing the role of microbes through Mendelian Randomization. These approaches are all based on rigorous prior data emphasizing the importance of the problems as well as the limitations of existing strategies. Our work is motivated by and will directly enable analyses in three of the largest and richest microbiome profiling studies, including the MEC and SOL cohorts which study the gut microbiome, and the PIN cohort, which explores the vaginal microbiome in pregnancy. Accordingly, the methods we develop have the potential to improve our fundamental knowledge of the microbiome and propel the field towards enhanced risk reduction and clinical interventions.

项目概要/摘要 人类微生物组与多种人类疾病密切相关，是迫切需要解决的问题 减轻这些疾病负担的门户，特别是因为微生物组是明显可以改变的。 这最终导致了以微生物为导向的风险降低和临床干预，这已被证明 在从感染到癌症免疫治疗等多种情况下均有效。然而，尽管有一些高 尽管取得了成功，但许多其他研究都失败了。这些失败甚至许多失败背后的一个中心主题 成功的故事是我们对微生物如何相互作用的基本有限的理解 宿主基因组学和结果。最近，正在努力评估和绘制这些关系 在大规模分析研究中，但不幸的是，用于阐明这些联系的工具可能是 动力不足，难以解释，甚至由于强大的潜在因素而受到严重误报 假设。因此，受到三个最大、最丰富的微生物组分析中的问题的推动 研究中，该提案旨在通过解决四个主要领域来填补方法论文献中的关键空白。 具体来说，我们的目标是开发一套全面的工具，用于 (1) 增强微生物共现网络 建造; (2) 加强与单个微生物类群相关的 SNP 和稀有变异的发现；和 (3)通过孟德尔随机化评估微生物的作用。这些方法都是基于 严格的先前数据强调了问题的重要性以及现有策略的局限性。 我们的工作受到三个最大、最丰富的微生物组分析的推动，并将直接实现这些分析 研究，包括研究肠道微生物组的 MEC 和 SOL 队列，以及探索肠道菌群的 PIN 队列 怀孕期间的阴道微生物组。因此，我们开发的方法有可能改善我们的 微生物组的基础知识，推动该领域加强风险降低和临床 干预措施。