Omic Determinants of Longitudinal Lung Function in Asthma

项目总结 哮喘患者成年期纵向肺功能(LLF)的进一步特征至关重要 重要的是，因为低肺功能与病情恶化、发病率和死亡率增加相关。精确 LLF轨迹背后的生物机制的基因组和代谢概况将是 有助于了解和改善肺功能恶化。MicroRNAs(miRs；短非编码 RNA)对炎症级联反应具有广泛的影响，导致呼吸道重塑和慢性呼吸道 梗阻，以及特定的代谢物提供了反映两者的实时炎症变化的测量 遗传和环境的影响。因此，MIR和代谢物的联合使用具有很大的意义。 有可能提供对疾病生理学的重要洞察，并确定调节、诊断和 预测LLF。这项建议的目的是确定LLF的miRNA和代谢决定因素 使用电子病历(EMR)的纵向肺活量测量进行分类的模式， 准确识别有最大风险进展为更严重慢性肺部疾病的哮喘患者 障碍物。我们的中心假设是LLF轨迹受特定的一组基因，miRNAs， 和代谢物可以1)告知潜在的生物失调和2)作为生物标志物 区分临床上可操作的LLF模式，通过 多组体治疗靶点的确定。我们将通过生成小说来探索这一假设 哮喘患者纵向肺功能(BALLF)队列的独特生物库；其中包括严格的LLF 根据电子病历生成的表型鉴定(目标1a)和全球代谢组学概况和 MiRNA测序(目标1b)补充现有的遗传和表型数据。我们将鉴定代谢物 (Aim2a)和miRNAs(Aim2b)与这些LLF相关；利用我们丰富的初步数据 神经鞘脂脂和二十烷类化合物的生物合成来指导我们的分析。最后，我们将利用我们广泛的系统 整合这些多组数据的生物学专业知识，以提高我们对LLF(Aim3a)和 开发临床可翻译的生物标志物(目标3b)。至关重要的是，我们有能力同时验证这些 并评估其在现有的两个独立的哮喘患者队列中的普适性。这将是 代表了第一个关于哮喘LLF轨迹的综合经济学研究，重点是独特的 MIR、代谢物和基因；因此，这项创新提案的发现具有巨大的潜力 阐明肺功能下降的生物学机制及对哮喘患者治疗的影响 出现这种毁灭性的并发症的风险。

PROJECT SUMMARY Further characterization of longitudinal lung function (LLF) throughout adulthood in asthmatics is critically important, as low lung function correlates with increased exacerbations, morbidity, and mortality. Precise genomic and metabolomic profiling of the biological mechanisms underlying LLF trajectories will be instrumental in understanding and ameliorating lung function deterioration. MicroRNAs (miRs; short non-coding RNAs) exhibit broad impact on inflammatory cascades, leading to airway remodeling and chronic airway obstruction, and specific metabolites provide a measure of real-time inflammatory changes that reflect both genetic and environmental influences. Therefore, the combined use of miRs and metabolites has great potential to provide critical insight into disease physiology and identify mechanisms to regulate, diagnose, and prognosticate LLF. The objective of this proposal is to identify miRNA and metabolomic determinants of LLF patterns, classified using longitudinal spirometry measures from electronic medical records (EMRs), that accurately identify individuals with asthma at the greatest risk of progression to more serious chronic lung obstruction. Our central hypothesis is that LLF trajectories are regulated by specific sets of genes, miRNAs, and metabolites that can 1) inform on underlying biological dysregulation and 2) serve as biomarkers to distinguish clinically actionable patterns of LLF, enabling personalized medicine approaches through the identification of multiomic therapeutic targets. We will explore this hypothesis by generating the novel and unique Biobank of Asthmatics with Longitudinal Lung Function (BALLF) cohort; which includes rigorous LLF phenotyping generated from electronic medical records (Aim 1a) and global metabolomics profiling and miRNA sequencing (Aim 1b) supplementing existing genetic and phenotypic data. We will identify metabolites (Aim2a) and miRNAs (Aim2b) associated with these LLF; capitalizing on our rich preliminary data implicating sphingolipid and eicosanoid biosynthesis to guide our analyses. Finally, we will leverage our extensive systems biology expertise to integrate this multiomic data to improve our biological understanding of LLF (Aim3a) and to develop clinically translatable biomarkers (Aim 3b). Crucially, we have the ability to both validate these findings and to assess their generalizability in two existing independent cohorts of asthmatics. This will represent the first integrative omic study of LLF trajectories in asthma focusing on the unique combination of miRs, metabolites, and genes; as such the findings of this innovative proposal have tremendous potential to elucidate the biological mechanisms of lung function decline and to influence the management of asthmatics at risk of this devastating complication.