Weighted Gene Co-Expression Network Analysis Combined with Machine Learning Validation to Identify Key Modules and Hub Genes Associated with SARS-CoV-2 Infection.
Weighted Gene Co-Expression Network Analysis Combined with Machine Learning Validation to Identify Key Modules and Hub Genes Associated with SARS-CoV-2 Infection.
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DOI：
10.3390/jcm10163567
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发表时间：
2021-08-13
影响因子：
3.9
通讯作者：
Safarpour H
中科院分区：
文献类型：
--
作者：
Karami H;Derakhshani A;Ghasemigol M;Fereidouni M;Miri-Moghaddam E;Baradaran B;Tabrizi NJ;Najafi S;Solimando AG;Marsh LM;Silvestris N;De Summa S;Paradiso AV;Racanelli V;Safarpour H
2019冠状病毒病（COVID-19）大流行造成了巨大的生命损失。世界各地正在进行各种疫苗和药物的临床试验;然而，截至目前，还没有针对COVID-19的有效药物。确定这种疾病的关键基因和途径可能会导致发现潜在的药物靶点和生物标志物。在这里，我们应用加权基因共表达网络分析和LIME作为一种可解释的人工智能算法，以全面表征严重急性呼吸综合征冠状病毒2（SARS-CoV-2）感染期间支气管上皮细胞（原代人肺上皮细胞（NHBE）和转化肺泡（A549）细胞）的转录变化。我们的研究基于在每个细胞系中分别鉴定的枢纽基因检测到与COVID-19感染的致病性显著相关的网络。在我们的研究中检测到的新的枢纽基因签名，包括PGLYRP 4和HEPHL 1，可能揭示COVID-19的发病机制，为未来的预后和治疗方法带来希望。hub基因的富集分析表明，与KEGG通路最相关的生物学过程是I型干扰素信号通路、IL-17信号通路、烟碱介导的信号通路和对病毒种类的防御反应，它们在限制病毒感染中发挥重要作用。此外，根据药物靶点网络，我们确定了17种FDA批准的新型候选药物，这些药物可能通过调节共表达网络的四个枢纽基因来治疗COVID-19患者。这些基因在转化医学中具有潜在的应用价值，有望成为治疗肿瘤的靶点。需要进一步的体外和体内实验研究来评估这些枢纽基因在COVID-19中的作用。
The coronavirus disease-2019 (COVID-19) pandemic has caused an enormous loss of lives. Various clinical trials of vaccines and drugs are being conducted worldwide; nevertheless, as of today, no effective drug exists for COVID-19. The identification of key genes and pathways in this disease may lead to finding potential drug targets and biomarkers. Here, we applied weighted gene co-expression network analysis and LIME as an explainable artificial intelligence algorithm to comprehensively characterize transcriptional changes in bronchial epithelium cells (primary human lung epithelium (NHBE) and transformed lung alveolar (A549) cells) during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our study detected a network that significantly correlated to the pathogenicity of COVID-19 infection based on identified hub genes in each cell line separately. The novel hub gene signature that was detected in our study, including PGLYRP4 and HEPHL1, may shed light on the pathogenesis of COVID-19, holding promise for future prognostic and therapeutic approaches. The enrichment analysis of hub genes showed that the most relevant biological process and KEGG pathways were the type I interferon signaling pathway, IL-17 signaling pathway, cytokine-mediated signaling pathway, and defense response to virus categories, all of which play significant roles in restricting viral infection. Moreover, according to the drug–target network, we identified 17 novel FDA-approved candidate drugs, which could potentially be used to treat COVID-19 patients through the regulation of four hub genes of the co-expression network. In conclusion, the aforementioned hub genes might play potential roles in translational medicine and might become promising therapeutic targets. Further in vitro and in vivo experimental studies are needed to evaluate the role of these hub genes in COVID-19.
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影响因子：
5.2
作者：
Derakhshani A;Hashemzadeh S;Asadzadeh Z;Shadbad MA;Rasibonab F;Safarpour H;Jafarlou V;Solimando AG;Racanelli V;Singh PK;Najafi S;Javadrashid D;Brunetti O;Silvestris N;Baradaran B
通讯作者：
Baradaran B
影响因子：
64.5
作者：
Daniloski Z;Jordan TX;Wessels HH;Hoagland DA;Kasela S;Legut M;Maniatis S;Mimitou EP;Lu L;Geller E;Danziger O;Rosenberg BR;Phatnani H;Smibert P;Lappalainen T;tenOever BR;Sanjana NE
通讯作者：
Sanjana NE
影响因子：
7.7
作者：
Barh D;Tiwari S;Weener ME;Azevedo V;Góes-Neto A;Gromiha MM;Ghosh P
通讯作者：
Ghosh P
影响因子：
168.9
作者：
Chan, Jasper Fuk-Woo;Yuan, Shuofeng;Yuen, Kwok-Yung
通讯作者：
Yuen, Kwok-Yung
影响因子：
4.4
作者：
Asokananthan, N;Graham, PT;Stewart, GA
通讯作者：
Stewart, GA