RAPID: Integrative analysis of multi-omics data to understand ACE2 regulation and cytokine storm

许多药物正在接受对抗新冠肺炎的疗效测试。人们对这些药物的副作用知之甚少。这个问题很复杂，因为一些器官系统(肺、心、肝)可能会受到感染的影响。此外，高血压、糖尿病或心血管疾病等潜在疾病会增加严重并发症或死亡的可能性。该项目旨在确定这些药物对脆弱人群器官系统的影响。这些信息将为选择和应用有效的药物提供信息，这些药物也会造成最小的负面影响。该项目还将促进STEM学科中代表性不足群体的教育和研究经验。该项目结合了对全球基因组数据集的“横向”和“纵向”分析。“水平”视角将绘制出各种条件下的基因表达图谱，这将使人们能够更广泛地考虑药物治疗可能对新冠肺炎造成的潜在变化。“垂直”视角将确定针对不同表型的特定反应(例如，不同类型和水平的细胞因子的增加或ACE2水平的降低)的可能治疗建议的调节机制。这一建议的综合方法将利用最新研究的及时结果，并将这些结果纳入基因调控网络分析，以提供潜在抗炎治疗的表型特异性指导，并洞察作为表型函数的宿主反应。该项目的科学和工程贡献是开发和应用一种综合、多尺度和多方面的方法，对细胞相互作用(信号和调节)进行建模，从而能够预测对外部刺激(包括药物和病原体)的表型反应。这一综合建模框架将适用于其他病原体和患者群体。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Many drugs are being tested for efficacy against COVID-19. The side effects of these drugs are poorly understood. The issue is complicated because a number of organ systems (lungs, heart, liver) can be affected by the infection. In addition, underlying conditions such as hypertension, diabetes, or cardiovascular disease increase the likelihood of serious complications or death. This project is designed to identify the effects of these drugs on the organ systems of vulnerable populations. This information would inform the selection and application of effective drugs that also cause minimal negative consequences. This project will also advance the education and research experience of under-represented groups in the STEM disciplines.This project combines “horizontal” and “vertical” analyses of global genomic datasets. The “horizontal” perspective will map the landscape of gene expression under various conditions that will enable broader consideration of potential changes that drug treatments could have on Covid-19. The “vertical” perspective will identify regulatory mechanisms that suggest possible treatments to target specific responses (e.g., increases in the different types and levels of cytokines or decreases in the ACE2 levels) for the different phenotypes. The integrative approach of this proposal will capitalize on the timely results from the latest studies and incorporate these results into the gene regulatory network analysis to provide phenotypic-specific guidance on potential anti-inflammatory treatments and insight into the host response as a function of the phenotype. The scientific and engineering contribution of this project is the development and application of an integrative, multi-scale, and multi-faceted approach that models cellular interactions (signaling and regulatory) to enable prediction of the phenotypic responses to external stimuli, including drugs and pathogens. This integrative modeling framework will be applicable to other pathogens and patient populations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.