Identification of Novel Genomic Variants in COVID-19 Patients Using Whole-Exome Sequencing: Exploring the Plausible Targets of Functional Genomics.

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Rashid Mir, Faisal A Altemani, Naseh A Algehainy, Mohammad A Alanazi, Imadeldin Elfaki, Badr A Alsayed, Mohammad Muzaffar Mir, Syed Khalid Mustafa, Mamdoh S Moawadh, Faris J Tayeb, Jaber Alfailfi, Sael M Alatawi, Mohammed Saad Alhiwety, Mohammad Fahad Ullah
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引用次数: 0

Abstract

Covid-19 caused by SARS-CoV-2 virus has emerged as an immense burden and an unparalleled global health challenge in recorded human history. The clinical characteristics and risk factors of COVID-19 exhibit considerable variability, leading to a spectrum of clinical severity. Moreover, the likelihood of exposure to the virus may differ based on comorbidity status as comorbid illnesses have mechanisms that can considerably increase mortality by reducing the body's ability to withstand injury. The mammalian target of rapamycin (mTOR) pathway is essential for orchestrating innate immune cell defense, including cytokine production and is dysregulated in severe Coronavirus Disease 2019 (COVID-19) individuals. Through genome-wide, association studies, numerous genetic variants in the human host have been identified that have a significant impact on the immune response to SARS-CoV-2. To identify potentially significant genetic variants in Covid-19 patients that could affect the risk, severity, and clinical outcome of the infection, this study has used whole-exome sequencing (WES) on the 16 COVID-19 patients with varying comorbidities and severity of the disease including fatal outcomes. Among them, 8 patients made a full recovery and were discharged, while 8 patients unfortunately did not survive due to the severity of the illness and majority of them were males. The study identified 10,204 variants in the patients. From 1120 variants, which were chosen for novel variant analysis using mutation, function prediction tools to identify deleterious variants that could affect normal gene function, 116 variants of 57 genes were found to be deleterious. These variants were further classified as likely pathogenic and variants of uncertain significance. The data showed that among the likely pathogenic variants five genes were identified in connection to immune response whereas two were related to respiratory system. The common variants associated with the covid-19 phenotype showed the top 10 significant genes identified in this study such as ERCC2, FBXO5, HTR3D, FAIM, DNAH17, MTOR, IGHMBP2, ZNF530, QSER1, and FOXRED2 with variant rs1057079 of the MTOR gene representing the highest odds ratio (1.7, p = 8.7e-04). The mammalian target of rapamycin (mTOR) pathway variant rs1057079 was reported with high odds ratio, may orchestrate innate immune cell defense, including cytokine production, and is dysregulated. This study concluded that the mTOR signaling gene variant (rs1057079) is associated with different degrees of covid-19 severity and is essential for orchestrating innate immune cell defense including cytokine production. Inhibiting mTOR and its corresponding deleterious immune responses with medicinal approaches may provide a novel avenue for treating severe COVID-19 illness. Besides the PPI network exhibited a significantly high local clustering coefficient of 0.424 (p = 0.000536), suggesting the presence of tightly knit functional modules. These findings enhance our comprehension of the intricate interactions between genetic factors and COVID-19 disease.

利用全基因组测序鉴定 COVID-19 患者的新型基因组变异:探索功能基因组学的合理靶点
由 SARS-CoV-2 病毒引起的 COVID-19 已成为人类有史以来的巨大负担和前所未有的全球健康挑战。COVID-19 的临床特征和风险因素有很大的差异,导致临床严重程度不同。此外,由于合并症的机制会降低机体抵御伤害的能力,从而大大增加死亡率,因此感染病毒的可能性也会因合并症的状况而异。哺乳动物雷帕霉素靶标(mTOR)通路对于协调先天性免疫细胞防御(包括细胞因子的产生)至关重要,而在严重的冠状病毒病2019(COVID-19)患者中,mTOR通路失调。通过全基因组关联研究,已发现人类宿主中的许多遗传变异对 SARS-CoV-2 的免疫反应有重大影响。为了在 Covid-19 患者中发现可能影响感染风险、严重程度和临床结果的潜在重要基因变异,本研究对 16 名 COVID-19 患者进行了全外显子组测序(WES),这些患者具有不同的合并症和疾病严重程度,包括致命结果。其中,8 名患者完全康复出院,8 名患者因病情严重而不幸死亡,其中大部分为男性。这项研究在患者中发现了 10204 个变异体。研究人员利用突变、功能预测工具对其中的1120个变异进行了新型变异分析,以确定可能影响正常基因功能的有害变异,结果发现57个基因中的116个变异是有害的。这些变异体被进一步分为可能致病的变异体和意义不确定的变异体。数据显示,在可能致病的变异基因中,有五个基因与免疫反应有关,两个与呼吸系统有关。与covid-19表型相关的常见变异显示了本研究中发现的前10个重要基因,如ERCC2、FBXO5、HTR3D、FAIM、DNAH17、MTOR、IGHMBP2、ZNF530、QSER1和FOXRED2,其中MTOR基因的变异rs1057079代表了最高的几率(1.7,p = 8.7e-04)。据报道,哺乳动物雷帕霉素靶标(mTOR)通路变异体 rs1057079 的几率很高,它可能协调先天性免疫细胞的防御,包括细胞因子的产生,并且调节失调。本研究得出结论,mTOR 信号转导基因变异体(rs1057079)与不同程度的 covid-19 严重程度相关,并且对于协调先天性免疫细胞防御(包括细胞因子的产生)至关重要。用药物方法抑制 mTOR 及其相应的有害免疫反应可能会为治疗严重的 COVID-19 疾病提供一条新途径。此外,PPI 网络的局部聚类系数高达 0.424 (p=0.000536),表明存在紧密联系的功能模块。这些发现加深了我们对遗传因素与 COVID-19 疾病之间错综复杂的相互作用的理解。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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