Identification of host genetic variation predisposing to severe COVID-19 by genetics, transcriptomics and functional analyses

通过遗传学、转录组学和功能分析鉴定易患严重 COVID-19 的宿主遗传变异

• 批准号: 466168909
• 负责人: Professor Dr. Julien Gagneur
• 金额: --
• 依托单位: Institut für Virologie (aufgelöst)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2021
• 资助国家: 德国
• 起止时间: 2020-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/466168909?language=en
• 关键词: Identification; host; genetic; variation; predisposing

Unraveling genetic predispositions to severe COVID-19 promises to shed light onto the heterogeneity of the immune response to SARS-CoV-2 infection and to yield opportunities to better understand and potentially alter the underlying pathophysiology. Genetic loci harboring candidate genes related to innate immune response associate with COVID-19 have been identified. However, data systematically characterizing the functional impact of such genetic variation are sparse. In search for rare variants of strong effect, the global COVID-19 Host Genetics Initiative (COVID-19 HGI; www.covid19hg.org) is now expanding into rare variant association studies (RVAS) using whole exome and whole genome sequencing (WES/WGS) of large international cohorts. However, the identification and functional validation of these variants requires complementary data and analyses. This is particularly true for regulatory variants (e.g. variants effecting splicing) whose impacts are not yet defined for COVID-19 and hard to predict from sequence alone. Here, we will (1) generate a comprehensive genomics-transcriptomics data set for a longitudinally-followed cohort of individuals with COVID-19, (2) use a novel bioinformatics algorithm to identify aberrant splicing and expression as well as underlying genetic factors contributing to severe COVID-19 and (3) employ the results from this analysis as well as already existing large-scale genetic and functional annotation data to prioritize genes and genetic variants of innate-immune response pathways for (4) functional analysis by in vitro complementation.Overall, this project will allow for focused, hypothesis-driven analyses of innate immune-response in SARS-CoV-2 infection with unbiased discovery of novel genes and variants by rare-variant association study and aberrant expression analysis. To our knowledge, aberrant expression-based gene and variant prioritization has not been applied to COVID-19 so far. Ultimately, this will lead to the identification of genetic variants with functional relevance to SARS-CoV-2 and, in particular, to a more detailed understanding of the role of innate-immune-response genes in COVID-19 pathophysiology. This fundamental understanding bears the potential to generate new models to study SARS-CoV-2 infection and to develop highly specific novel or identify repurposable drugs to treat (subgroups of) individuals with COVID-19.

揭示严重COVID-19的遗传易感性有望揭示对SARS-CoV-2感染的免疫反应的异质性，并为更好地理解和潜在地改变潜在的病理生理学提供机会。已确定含有与COVID-19相关的先天免疫应答相关的候选基因的遗传位点。然而，系统地描述这种遗传变异对功能影响的数据很少。为了寻找具有强烈影响的罕见变异，全球COVID-19宿主遗传学倡议（COVID-19 HGI; www.covid19hg.org）目前正在扩展到罕见变异关联研究（RVAS），使用大型国际队列的全外显子组和全基因组测序（WES/WGS）。然而，这些变异的识别和功能验证需要补充数据和分析。对于调控变异体（例如影响剪接的变异体）来说尤其如此，这些变异体对COVID-19的影响尚未确定，而且很难仅从序列来预测。在这里，我们将(1)为纵向随访的COVID-19个体队列生成全面的基因组学-转录组学数据集；(2)使用一种新的生物信息学算法来识别异常剪接和表达以及导致严重COVID-19的潜在遗传因素；(3)利用该分析结果以及已经存在的大规模遗传和功能注释数据来优先考虑先天免疫应答途径的基因和遗传变异，以便(4)通过体外互补进行功能分析。总体而言，该项目将允许对SARS-CoV-2感染的先天免疫反应进行集中、假设驱动的分析，通过罕见变异关联研究和异常表达分析公正地发现新的基因和变异。据我们所知，基于异常表达的基因和变异优先级尚未应用于COVID-19。最终，这将导致鉴定与SARS-CoV-2功能相关的遗传变异，特别是更详细地了解先天免疫反应基因在COVID-19病理生理学中的作用。这一基本认识有可能产生新的模型来研究SARS-CoV-2感染，并开发高度特异性的新型或确定可重复使用的药物来治疗COVID-19个体（亚组）。