T1D:Investigating the Gut Microbiome, Urinary Proteome and Metabolome

T1D：研究肠道微生物组、尿液蛋白质组和代谢组

• 批准号: 8241486
• 负责人: REMBERT PIEPER
• 金额: $ 470.09万
• 依托单位: J. CRAIG VENTER INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-30 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8241486
• 关键词: Adolescent; Affect; Antibodies; Antigens; Autoimmune Diseases; Autoimmune Process; Autoimmunity; Beta Cell; Biological; Biological Assay; Biological Markers; Biometry; Blood; Blood Glucose; C-Type Lectins; Cells; Cessation of life; Child; Chronic; Classification; Clinic; Clinical; Clinical Data; Cohort Studies; Complex; Cytotoxic T-Lymphocyte-Associated Protein 4; Data; Data Set; Detection; Development; Diabetes Mellitus; Diagnosis; Diagnostic; Diagnostic tests; Disease; Disease Progression; Distal; Early Diagnosis; Enterovirus; Environmental Risk Factor; Epidemiologic Studies; Equipment and supply inventories; Etiology; Family; Feces; Functional disorder; Genes; Genetic; Genetic Predisposition to Disease; Genetic Variation; Genomics; Genotype; Goals; Gold; Immune system; Incidence; Individual; Infection; Inflammation; Insulin; Insulin-Dependent Diabetes Mellitus; Interleukin 2 Receptor; Intervention; Intestines; Islets of Langerhans; Lead; Left; Link; Machine Learning; Metabolic; Metabolism; Metadata; Metagenomics; Methods; Microbe; Molecular; Molecular Profiling; Mucosal Immune Responses; Onset of illness; Pancreas; Pathogenesis; Patients; Pattern; Phase; Phylogeny; Pilot Projects; Play; Populations at Risk; Predictive Value; Protein Tyrosine Phosphatase; Proteome; Proteomics; Publishing; Recording of previous events; Resolution; Ribosomal RNA; Risk; Risk Assessment; Role; Sampling; Siblings; Staging; Surveys; Susceptibility Gene; Taxonomy; Techniques; Technology Transfer; Testing; Therapeutic Intervention; Time; Urinary tract; Urine; Viral; base; biosignature; cell injury; clinical Diagnosis; cohort; disorder risk; gut microbiota; insight; insulin dependent diabetes mellitus onset; islet; loss of function; metabolomics; metagenomic sequencing; microbial; microbiome; multiple reaction monitoring; novel; patient population; prospective; protein metabolite; trait; urinary

DESCRIPTION (provided by applicant): Type 1 Diabetes (T1D) is an autoimmune disorder characterized by the loss of function of insulin producing pancreatic cells leading to myriad manifestations of the disease in affected individuals. When left untreated this can lead to death. Many studies have shown that development of the disease is the result of interactions between immunological, genetic, and environmental factors. Although, many environmental factors have been implicated, the mechanisms of involvement or major determinants are yet to be clearly identified. Published studies have suggested that T1D results from environmental triggers acting on genetically susceptible individuals and that microbial infection and their immunological consequences are suspected to take part in the pathogenesis. Several mechanisms have been proposed for the causation of beta-cell damage by microbes. Data from retrospective and prospective epidemiological studies strongly suggest the involvement of enteroviruses in the development of T1D. Altered microbial diversity in the gut microbiota has been shown to trigger an abnormal mucosal immune response to further the progression of T1D. Genetic susceptibility traits for T1D are becoming more numerous, including loci for HLA, insulin, protein tyrosine phosphatase-22, cytotoxic T-lymphocyte-associated protein 4, the interleukin-2 receptor and C- type lectin. This complexity renders them less desirable as predictive tests. Although genetic susceptibility genes are known to play a substantial role in the development of T1D, cellular changes as well as environmental triggers may serve as excellent, potentially more universal biomarkers for risk assessment. For this study, we propose to analyze blood, stool and urine samples from children and adolescent patient populations who have been recently diagnosed with T1D, their siblings, and at-risk cohorts from the TrialNet network (www.diabetestrialnet.org). We propose to apply high-throughput genomics, proteomics and metabolomics techniques to identify molecular signatures discriminating these cohorts. By deconvolution of high-resolution molecular data, we expect to identify viral-microbial specific correlated patterns of proteins and metabolites. Our aim is to discover and verify candidate biomarkers from a large number of biological constituents; from genomic, proteomic and metabolomic datasets through correlation of host microbiome data and genotype. Our purpose is to advance non-invasive clinical tests by applying novel molecular methods to correlate disease status for early diagnosis and prediction of T1D onset, setting the stage for potential therapies or intervention strategies. PUBLIC HEALTH RELEVANCE: The incidence of Type I Diabetes (T1D) has been rising rapidly in children and adolescents over the last 20 years. T1D is an autoimmune disease that occurs when a child's body cannot produce insulin, and genetics as well as environmental factors play a role in the development of this disease. We propose to study the complex interplay of environmental, immunological and genetic factors to discover molecular signatures with a potential to advance clinical diagnosis and therapy at or before the onset of T1D.

描述（由申请人提供）：1型糖尿病（T1D）是一种自身免疫性疾病，其特征是产生胰岛素的胰腺细胞功能丧失，导致患者出现多种疾病表现。如果不及时治疗，这可能导致死亡。许多研究表明，该病的发展是免疫、遗传和环境因素相互作用的结果。虽然牵涉到许多环境因素，但其参与机制或主要决定因素尚未明确确定。已发表的研究表明，T1D是由环境因素对遗传易感个体的影响引起的，微生物感染及其免疫后果被怀疑参与了发病机制。已经提出了微生物引起β细胞损伤的几种机制。来自回顾性和前瞻性流行病学研究的数据强烈提示肠病毒参与了T1D的发展。肠道菌群中微生物多样性的改变已被证明可引发异常的粘膜免疫反应，进一步促进T1D的进展。T1D的遗传易感性状越来越多，包括HLA、胰岛素、蛋白酪氨酸磷酸酶-22、细胞毒性t淋巴细胞相关蛋白4、白细胞介素-2受体和C型凝集素的基因座。这种复杂性使得它们不太适合作为预测性测试。虽然已知遗传易感基因在T1D的发展中起着重要作用，但细胞变化和环境触发因素可能是风险评估的优秀、潜在的更通用的生物标志物。在这项研究中，我们建议分析最近被诊断为T1D的儿童和青少年患者群体、他们的兄弟姐妹以及来自TrialNet网络（www.diabetestrialnet.org）的高危队列的血液、粪便和尿液样本。我们建议应用高通量基因组学、蛋白质组学和代谢组学技术来识别区分这些队列的分子特征。通过高分辨率分子数据的反褶积，我们期望确定病毒-微生物特异性相关模式的蛋白质和代谢物。我们的目标是从大量生物成分中发现和验证候选生物标志物；从基因组，蛋白质组学和代谢组学数据集通过宿主微生物组数据和基因型的相关性。我们的目的是通过应用新的分子方法来促进非侵入性临床测试，以早期诊断和预测T1D的发病，为潜在的治疗或干预策略奠定基础。