ACEs family genes: Important molecular links between lung cancer and COVID-19.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhang Y
PROVIDER: S-EPMC8673100 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Obesity is a risk factor for developing severe COVID-19. However, the mechanism underlying obesity-accelerated COVID-19 remains unclear. Here, we report results from a study in which K18-hACE2 mice were fed an obesity-inducing western diet (WD) for over 3 months before intranasal infection with SARS-CoV2. After infection, the WD-fed K18-hACE2 mice lost more body weight and had more severe lung inflammation than normal chow (NC)-fed mice. Bulk RNAseq analysis of lungs and adipose tissue revealed that a diverse landscape of various immune cells, inflammatory markers, and pathways are upregulated in obese COVID-19 patients or the WD-fed K18-hACE2 mice when compared with their respective control groups. When compared with infected NC-fed mice in the lung, the infected WD-fed mice had upregulation of IL-6, a well-established marker for severe COVID-19. These results indicate that obesity-accelerated severe COVID-19 caused by SARS-CoV-2 infection in the K18-hACE2 mouse model can be used for dissecting the cellular and molecular mechanisms underlying pathogenesis. Furthermore, in the transcriptome analysis of the lung and adipose tissue obtained from deceased COVID-19 patients, we found upregulation of an array of genes and pathways associated with Inflammation. Both the K18-hACE2 mouse model and human COVID-19 patient data support a link between inflammation and an obesity-accelerated COVID-19 disease phenotype.
2024-05-21 | GSE267021 | GEO
Project description:BackgroundLung cancer patients have the worst outcomes when affected by coronavirus disease 2019 (COVID-19). The molecular mechanisms underlying the association between lung cancer and COVID-19 remain unknown. The objective of this investigation was to determine whether there is crosstalk in molecular perturbation between COVID-19 and lung cancer, and to identify a molecular signature, molecular networks and signaling pathways shared by the two diseases.MethodsWe analyzed publicly available gene expression data from 52 severely affected COVID-19 human lung samples, 594 lung tumor samples and 54 normal disease-free lung samples. We performed network and pathways analysis to identify molecular networks and signaling pathways shared by the two diseases.ResultsThe investigation revealed a signature of genes associated with both diseases and signatures of genes uniquely associated with each disease, confirming crosstalk in molecular perturbation between COVID-19 and lung cancer. In addition, the analysis revealed molecular networks and signaling pathways associated with both diseases.ConclusionsThe investigation revealed crosstalk in molecular perturbation between COVID-19 and lung cancer, and molecular networks and signaling pathways associated with the two diseases. Further research on a population impacted by both diseases is recommended to elucidate molecular drivers of the association between the two diseases.
| S-EPMC8953719 | biostudies-literature
Project description:Coronavirus Disease 2019 (COVID-19) pandemic remains a major public health threat in most countries. The causative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus can lead to acute respiratory distress syndrome and result in mortality in COVID-19 patients. Vitamin D is an immunomodulator hormone with established effectiveness against various upper respiratory infections. Vitamin D can stall hyper-inflammatory responses and expedite healing process of the affected areas, primarily in the lung tissue. Thus, there are ecological and mechanistic reasons to promote exploration of vitamin D action in COVID-19 patients. As no curative drugs are available currently for COVID-19, we feel that the potential of vitamin D to alter the course of disease severity needs to be investigated. Clinical studies may be undertaken to address the value of vitamin D supplementation in deficient, high-risk COVID-19 patients.
| S-EPMC7500624 | biostudies-literature
Project description:In December 2019, a novel disease, coronavirus disease 19 (COVID-19), emerged in Wuhan, People's Republic of China. COVID-19 is caused by a novel coronavirus (SARS-CoV-2) presumed to have jumped species from another mammal to humans. This virus has caused a rapidly spreading global pandemic. To date, over 300,000 cases of COVID-19 have been reported in England and over 40,000 patients have died. While progress has been achieved in managing this disease, the factors in addition to age that affect the severity and mortality of COVID-19 have not been clearly identified. Recent studies of COVID-19 in several countries identified links between air pollution and death rates. Here, we explored potential links between major fossil fuel-related air pollutants and SARS-CoV-2 mortality in England. We compared current SARS-CoV-2 cases and deaths from public databases to both regional and subregional air pollution data monitored at multiple sites across England. After controlling for population density, age and median income, we show positive relationships between air pollutant concentrations, particularly nitrogen oxides, and COVID-19 mortality and infectivity. Using detailed UK Biobank data, we further show that PM2.5 was a major contributor to COVID-19 cases in England, as an increase of 1 m3 in the long-term average of PM2.5 was associated with a 12% increase in COVID-19 cases. The relationship between air pollution and COVID-19 withstands variations in the temporal scale of assessments (single-year vs 5-year average) and remains significant after adjusting for socioeconomic, demographic and health-related variables. We conclude that a small increase in air pollution leads to a large increase in the COVID-19 infectivity and mortality rate in England. This study provides a framework to guide both health and emissions policies in countries affected by this pandemic.
| S-EPMC7571423 | biostudies-literature
Project description:The information set from which individuals make their decision on vaccination includes signals from trusted agents, such as governments, community leaders and the media. By implementing restrictions, or by relaxing them, governments can provide a signal about the underlying risk of the pandemic and indirectly affect vaccination take-up. Rather than focusing on measures specifically designed to increase vaccine acceptance, this paper studies how governments' non-pharmaceutical policy responses to the pandemic can modify the degree of preventive health behavior, including vaccination. To do so, we use repeated waves of a global survey on COVID-19 Beliefs, Behaviors and Norms covering 18 countries from October 2020 to March 2021. Controlling for the usual determinants, we explore how individuals' willingness to get vaccinated is affected by changes in government restriction measures (as measured by the Oxford Stringency Index). This relationship is mediated by individual characteristics, social norms (social pressure to conform with what most people do), and trust in government institutions. Our results point to a complex picture as the implementation of restrictions is associated with increased acceptance in some contexts and decreased acceptance in others. The stringency of government restrictions has significant positive correlations with vaccine acceptance in contexts of weak social norms of vaccine acceptance and lower trust in government. In countries or communities with tighter social norms and high trust in health authorities, vaccine acceptance is high but less sensitive to changes in policies. These results suggest that the effect of government policy stringency is stronger among individuals who report lower trust and weaker social norms of vaccine acceptance.
| S-EPMC9840231 | biostudies-literature
Project description:Considerable progress has been made in illuminating the pathological events for systemic sclerosis (SSc)-related progressive lung fibrosis. The molecular events that lead to SSc-related progressive lung fibrosis need to be defined. Some important genes have been identified from a recent study in humans. We aim to construct and compare the similarities and differences of molecular pathways between SSc-related progressive lung fibrosis and normal lungs of humans and mice.We used the analytical approach of association of key genes in SSc-related progressive lung fibrosis. We first identified the probes for genes of SSc-related progressive lung fibrosis and analyzed the pathways in human lung using data generated by microarray. We then analyzed the gene pathways in mouse lung for similar sets of probes. Gene expression data from livers were used to compare with that in lung in both humans and mice.Our analysis indicated that, in humans, the expression levels of genes for macrophage activation are more strongly associated with each other than that in mice. In both humans and mice, the associations of these genes are much greater in the lung than that in the liver. The association in gene expression between humans and mice are similar for IFN-regulated genes and profibrotic/Tgf?-regulated genes.Our analysis reveals the differences and similarities of the network of key genes between humans and mice during the molecular processes that eventually lead to fibrosis in the lung.
| S-EPMC4596290 | biostudies-literature
Project description:Although some studies reported the comprehensive mRNA expression analysis of coronavirus disease 2019 (COVID-19) using blood samples to understand its pathogenesis, the characteristics of RNA expression in COVID-19 and sepsis have not been compared. We compared the transcriptome expression of whole blood samples from patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and patients with sepsis caused by other bacteria who entered the intensive care unit to clarify the COVID-19-specific RNA expression and understand its pathogenesis. Transcriptomes related to mitochondria were upregulated in COVID-19, whereas those related to neutrophils were upregulated in sepsis. However, the transcriptomes related to neutrophils were upregulated in both COVID-19 and sepsis compared to in healthy controls, whereas the mitochondrial transcriptomes were upregulated in COVID-19 and downregulated in sepsis compared to in healthy controls. Moreover, sepsis showed sub-optimal intrinsic apoptotic features compared with COVID-19. The transcriptome expression of COVID-19 has been examined in vitro but has not been widely validated using human specimens. This study improves the understanding of the pathogenesis of COVID-19 and can contribute to the development of treatments.
2022-11-29 | GSE199816 | GEO
Project description:The etiology of severe forms of COVID19, especially in young patients, remains a salient unanswered question. Here we build on a 3-tier cohort where all individuals/patients were strictly below 50 years of age and where a number of comorbidities were excluded at study onset. Besides healthy controls (N=22), these include patients in the intensive care unit with Acute Respiratory Distress Syndrome (ARDS) (“critical group”; N=47), and those in a non-critical care ward under supplemental oxygen (“non-critical group”, N=25). This highly curated cohort allowed us to perform a deep multi-omics approach which included whole genome sequencing, whole blood RNA-sequencing, plasma and peripheral-blood mononuclear cells proteomics, multiplex cytokine profiling, mass-cytometry-based immune cell profiling in conjunction with viral parameters i.e. anti-SARS-Cov-2 neutralizing antibodies and multi-target antiviral serology. Critical patients were characterized by an exacerbated inflammatory state, perturbed lymphoid and myeloid cell compartments, signatures of dysregulated blood coagulation and active regulation of viral entry into the cells. A unique gene signature that differentiates critical from non-critical patients was identified by an ensemble machine learning, deep learning and quantum computing approach. Within this gene network, Structural Causal Modeling identified several ARDS driver genes, among which the up-regulated metalloprotease ADAM9 seems to be a key driver. Inhibition of ADAM9 ex vivo interfered with SARS-Cov-2 uptake and replication in human epithelial cells. Hence we apply a machine learning approach to identify driver genes for severe forms of COVID-19 in a small, uncluttered cohort of patients.
2021-11-25 | PXD025265 | Pride
Project description:Here we report single-cell RNA-sequencing generated from one COVID-19 lung removed at the time of organ transplant.
2020-12-29 | GSE163919 | GEO
Project description:We profiled 116,314 cells using snRNA-seq of 20 frozen lungs obtained from 19 COVID-19 decedents and seven control patients with short postmortem interval (PMI) autopsies. The COVID-19 cohort comprises seven female and 12 male decedents, including 13 patients of Hispanic ethnicity, with an age range from 58 to >89 years who had acquired SARS-CoV-2 infection and succumbed to the disease. The average time from symptom onset to death was 27.5 days (range, 4–63 days). After rapid autopsy with a median PMI of 4 hours (range 2–9 hours) collected tissues were either flash-frozen or frozen following OCT (optimal cutting temperature) embedment and subjected to snRNA-seq using a droplet-based platform (10x Genomics). All included patients had underlying hypertensive disorder and frequently one or more additional co-morbidities associated with increased risk for severe COVID-19.
2021-04-29 | GSE171524 | GEO