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

揭开严重新冠肺炎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，并提供更好地理解和潜在改变潜在病理生理学的机会。含有与新冠肺炎相关的先天性免疫反应候选基因的遗传基因座已经被确定。然而，系统地描述这种遗传变异的功能影响的数据很少。为了寻找有效的稀有变异，全球新冠肺炎宿主遗传学倡议(新冠肺炎；www.covid19hg.org)现在正在扩展到稀有变异关联研究(RVA)，使用大型国际队列的全部外显子和全基因组测序(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，其对新冠肺炎的影响尚未确定，很难仅根据序列进行预测。在这里，我们将(1)为纵向跟踪的新冠肺炎患者队列生成一个全面的基因组-转录组数据集，(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新冠肺炎的潜在遗传因素，(3)使用这种分析的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性免疫反应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。总的来说，这个项目将允许有重点地，SARS-CoV-2感染中先天免疫反应的假设驱动分析通过罕见变异关联研究和异常表达分析无偏见地发现新基因和变异。据我们所知，基于异常表达的基因和变体优先排序尚未应用于新冠肺炎。最终，这将导致识别与SARS-CoV-2具有功能相关性的基因变体，特别是更详细地理解天然免疫反应基因在新冠肺炎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药物或识别可重复使用的药物来治疗新冠肺炎患者(亚组)。

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.