Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets

Abstract

Corona virus disease 2019 (COVID-19) increases the risk of cardiovascular occlusive/thrombotic events and is linked to poor outcomes. The underlying pathophysiological processes are complex, and remain poorly understood. To this end, platelets play important roles in regulating the cardiovascular system, including via contributions to coagulation and inflammation. There is ample evidence that circulating platelets are activated in COVID-19 patients, which is a primary driver of the observed thrombotic outcome. However, the comprehensive molecular basis of platelet activation in COVID-19 disease remains elusive, which warrants more investigation. Hence, we employed gene co-expression network analysis combined with pathways enrichment analysis to further investigate the aforementioned issues. Our study revealed three important gene clusters/modules that were closely related to COVID-19. These cluster of genes successfully identify COVID-19 cases, relative to healthy in a separate validation data set using machine learning, thereby validating our findings. Furthermore, enrichment analysis showed that these three modules were mostly related to platelet metabolism, protein translation, mitochondrial activity, and oxidative phosphorylation, as well as regulation of megakaryocyte differentiation, and apoptosis, suggesting a hyperactivation status of platelets in COVID-19. We identified the three hub genes from each of three key modules according to their intramodular connectivity value ranking, namely: COPE, CDC37, CAPNS1, AURKAIP1, LAMTOR2, GABARAP MT-ND1, MT-ND5, and MTRNR2L12. Collectively, our results offer a new and interesting insight into platelet involvement in COVID-19 disease at the molecular level, which might aid in defining new targets for treatment of COVID-19–induced thrombosis.

Identification of toll‐like receptor 5 and acyl‐CoA synthetase long chain family member 1 as hub genes are correlated with the severe forms of COVID‐19 by Weighted gene co‐expression network analysis

“…Several studies have applied WGCNA to identify the hub genes COVID‐19 patients, including the hub genes in the nasopharyngeal swabs between normal subjects and COVID‐19 patients, critical genes of age‐related module in the peripheral blood mononuclear cell of COVID‐19 patients, and key genes in the platelets of between health controls and COVID‐19 patients [ 24 , 25 , 26 ]. These studies explored the key genes of COVID‐19 from a variety of perspectives.…”

Mitochondrial complex I subunit MT-ND1 mutations affect disease progression

“…Extracellular vesicles or the circulating cell-free MT-ND1 content can be used as a tool to diagnose and detect cancer. MT-ND1 mRNA might also serve as a biomarker for T2D, and it has been verified to be downregulated in patients with diabetic kidney diseases [ 72 , 73 ]. In addition, mutations in MT-ND1 mutation-induced decreases in respiratory chain CI levels and/or enzyme activity are important genetic factors causing diseases such as LHON, MELAS, and T2D.…”

Identification of genes related to immune enhancement caused by heterologous ChAdOx1–BNT162b2 vaccines in lymphocytes at single-cell resolution with machine learning methods

“…In 2021, researchers found that MTRNR2L12 was upregulated in immune cells, such as CD8 + T cells, in bronchoalveolar lavage fluid from mild and severe COVID-19 patients (106), suggesting the possibility of altered expression following COVID-19 vaccination. Two recent papers published in 2022 found the differential expression of MTRNR2L12 in bronchoalveolar lavage fluid samples from patients with severe COVID-19 (107) and classification of the MTRNR2L12 gene as an important gene determining COVID-19 positive status by association classification model (108). Thus, COVID-19 vaccination may cause the differential expression of MTRNR2L12 and serve as a feature that facilitates the differentiation among the protective capacities of different vaccination strategies.…”