Integrating genomics and metabolomics data to identify molecular characteristics of Gulf War Veterans' illnesses

整合基因组学和代谢组学数据来识别海湾战争退伍军人疾病的分子特征

• 批准号: 10486532
• 负责人: Elizabeth R Hauser
• 金额: --
• 依托单位: DURHAM VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10486532
• 关键词: Affect; Award; Biological; Biological Assay; Biological Markers; Biomedical Technology; Blood; Characteristics; Chronic; Clinic; Clinical Trials; Communities; Complement; Complex; DNA Modification Process; Data; Data Set; Databases; Development; Diagnosis; Disease; Distress; Epigenetic Process; Etiology; Exanthema; Fatigue; Genes; Genetic; Genetic Markers; Genetic Variation; Genome; Genomics; Genotype; Goals; Gulf War; Gulf War veteran; Headache; Health; Individual; Inflammation; Laboratories; Life; Lipids; Machine Learning; Measures; Medical; Metabolic; Metabolic Pathway; Methods; Methylation; Modernization; Molecular; Neurocognitive; Pain; Participant; Pathway interactions; Patients; Persian Gulf; Persian Gulf Syndrome; Phenotype; Physiological; Preparation; Quality Control; Research; Research Personnel; Research Project Grants; Research Proposals; Resources; Sample Size; Science; Subgroup; Surveys; Symptoms; Systems Biology; Techniques; Testing; Therapeutic Research; Therapeutic Trials; Tissues; Treatment Efficacy; Uncertainty; Validation; Veterans; Work; affective disturbance; analytical tool; biobank; biological systems; biomarker discovery; biomarker identification; biomarker validation; cohort; comorbidity; data integration; data repository; design; effective therapy; epidemiology study; experience; experimental study; gastrointestinal; genetic variant; genome wide association study; genome-wide; immune function; instrument; liquid chromatography mass spectrometry; machine learning method; medical complication; metabolome; metabolomics; mitochondrial dysfunction; persistent symptom; programs; research and development; response; small molecule; symptom cluster

Gulf War Illness (GWI) is a chronic, debilitating illness suffered by Veterans of the first Gulf War. Patients suffering from GWI are often subject to years of medical uncertainty as they make their way through multiple clinics to try to diagnose and ultimately treat their chronic symptoms, if possible. Complicating this medical journey is the absence of biomarkers that can be used to diagnose the conditions and that might provide clues as to treatments and etiology. A recent review of the evidence for biomarkers in GWI concluded that there were no validated biomarkers for GWI. The lack of biomarkers is accompanied by a lack of treatments demonstrated to work in a large number of Veterans. Epidemiologic studies have been successful in identifying associations with exposures common to serving in the Gulf War through development of large cohorts of Gulf War Veterans. Biomarker studies in small numbers of Gulf War Veterans have identified biomarkers for testing. Among the most fruitful of these are studies of metabolomics, the analysis of all small molecules in blood or tissue measured by specialized instruments capable of detecting very small quantities of metabolites and then comparing them to known compounds. We will test a comprehensive set of metabolites assayed by the Metabolon metabolomics platform covering over 60 metabolic pathways in over 1000 Veterans in the Gulf War Era Cohort and Biorepository (GWECB), collected and made available to researchers by the VA Office of Research and Development Gulf War Program. The metabolomics dataset will join data from other assays in GWECB designed to interrogate other biological systems. Genome-wide genotyping tests how up to 1 million genetic variants across the genome contribute to differences in Veterans with Gulf War Illness versus those without. Likewise, genome-wide epigenetic assays test how up to 800,000 DNA modifications contribute different levels of activity of genes across the genome. Putting these three modern biomedical technologies together provides a comprehensive view of physiological differences in individuals. In combining these data we hope to identify biological pathways that distinguish GWI Veterans and suggest treatments and biomarkers. We also will analyze these combined datasets to test whether smaller clusters of symptoms that make up GWI can identify specific subtypes of GWI related to the pathways we find. These data will be returned to the GWECB data repository so that it can be made available to the Gulf War research community for additional research.

海湾战争病 (GWI) 是第一次海湾战争退伍军人遭受的一种慢性、使人衰弱的疾病。患者 患有 GWI 的人在经历多种疾病的过程中往往会经历多年的医疗不确定性 如果可能的话，尝试诊断并最终治疗他们的慢性症状。让这个医疗变得复杂化 旅程是缺乏可用于诊断病情并可能提供线索的生物标志物 关于治疗和病因。最近对 GWI 生物标志物证据的审查得出的结论是， 没有经过验证的 GWI 生物标志物。生物标志物的缺乏伴随着治疗的缺乏 已证明在大量退伍军人中有效。流行病学研究已成功确定 通过发展大型海湾部队，与在海湾战争中服役的常见暴露相关联 退伍军人。对少数海湾战争退伍军人进行的生物标志物研究已经确定了用于测试的生物标志物。 其中最富有成果的是代谢组学研究，即对血液或血液中所有小分子的分析。 通过能够检测极少量代谢物的专用仪器测量组织，然后 将它们与已知化合物进行比较。我们将测试一套全面的代谢物，由 Metabolon 代谢组学平台涵盖 1000 多名海湾战争退伍军人的 60 多种代谢途径 Era Cohort 和 Biorepository (GWECB)，由 VA 办公室收集并提供给研究人员 研究与开发海湾战争计划。代谢组学数据集将加入来自其他分析的数据 GWECB 旨在询问其他生物系统。全基因组基因分型测试如何达到 100 万 整个基因组的遗传变异导致患有海湾战争疾病的退伍军人与其他退伍军人之间的差异 没有。同样，全基因组表观遗传学检测可测试多达 800,000 个 DNA 修饰如何发挥作用 整个基因组中基因的不同活性水平。将这三项现代生物医学技术 共同提供了个体生理差异的全面视图。结合这些数据 我们希望找出区分 GWI 退伍军人的生物学途径，并提出治疗方法和生物标志物。 我们还将分析这些组合数据集，以测试是否存在构成 GWI 的较小症状群 可以识别与我们发现的途径相关的 GWI 特定亚型。这些数据将被返回到 GWECB 数据存储库，以便海湾战争研究界可以获取更多信息 研究。