Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients

Bando, Sílvia Yumi; Bertonha, Fernanda Bernardi; Vieira, Sandra Elisabete; Oliveira, Danielle Bruna Leal; Chalup, Vanessa Nascimento; Durigon, Edison Luíz; Palmeira, Patricia; Curi, Ana Cristina P.; Faria, Caroline Silvério; Antonângelo, Leila; Lauterbach, Gerhard da Paz; Regalio, Fabiane Aliotti; César, Roberto M.; Moreira-Filho, Carlos Alberto

doi:10.1038/s41598-023-28227-6

Cited by 3 publications

(2 citation statements)

References 111 publications

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“…Increased p53-dependent apoptosis has also been observed in response to vesicular stomatitis virus (VSV), which was associated with reduced viral replication [15]. Recent studies on SARS-CoV-2 infection reveal a close association between COVID-19, p53 function, and signaling [72,73]. Importantly, RNA viruses have evolved mechanisms designed to abrogate p53 responses [11], suggesting that p53 has a broad role in antiviral defense.…”

Section: Discussionmentioning

confidence: 99%

APOBEC3G Is a p53-Dependent Restriction Factor in Respiratory Syncytial Virus Infection of Human Cells Included in the p53/Immune Axis

Gladwell,

Yost,

et al. 2023

IJMS

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Identifying and understanding genetic factors that influence the propagation of the human respiratory syncytial virus (RSV) can lead to health benefits and possibly augment recent vaccine approaches. We previously identified a p53/immune axis in which the tumor suppressor p53 directly regulates the expression of immune system genes, including the seven members of the APOBEC3 family of DNA cytidine deaminases (A3), which are innate immune sentinels against viral infections. Here, we examined the potential p53 and A3 influence in RSV infection, as well as the overall p53-dependent cellular and p53/immune axis responses to infection. Using a paired p53 model system of p53+ and p53- human lung tumor cells, we found that RSV infection activates p53, leading to the altered p53-dependent expression of A3D, A3F, and A3G, along with p53 site-specific binding. Focusing on A3G because of its 10-fold-greater p53 responsiveness to RSV, the overexpression of A3G can reduce RSV viral replication and syncytial formation. We also observed that RSV-infected cells undergo p53-dependent apoptosis. The study was expanded to globally address at the transcriptional level the p53/immune axis response to RSV. Nearly 100 genes can be directly targeted by the p53/immune axis during RSV infection based on our p53BAER analysis (Binding And Expression Resource). Overall, we identify A3G as a potential p53-responsive restriction factor in RSV infection. These findings have significant implications for RSV clinical and therapeutic studies and other p53-influenced viral infections, including using p53 adjuvants to boost the response of A3 genes.

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Section: Discussionmentioning

confidence: 99%

APOBEC3G Is a p53-Dependent Restriction Factor in Respiratory Syncytial Virus Infection of Human Cells Included in the p53/Immune Axis

Gladwell,

Yost,

et al. 2023

IJMS

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“…P53 is involved in cell-cycle control as part of the DDR, including the decision ‘DNA repair versus elimination of cells’ ( 295 , 296 ). Correspondingly, p53-controlled genes were overexpressed in leukocytes from patients with severe COVID-19 ( 297 ). Moreover, SARS-CoV-2 degrades checkpoint kinase (CHK)1 ( 190 ), an effector downstream to Ataxia telangiectasia and Rad3 related protein (ATR) that earlier had been demonstrated to be induced in SARS-CoV-2-infected Vero-6 cells ( 284 ).…”

Section: Spike and Dsdna Sensors In The Adverse Events After Covid-19...mentioning

confidence: 99%

Self-DNA driven inflammation in COVID-19 and after mRNA-based vaccination: lessons for non-COVID-19 pathologies

Heil

2024

Front. Immunol.

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The coronavirus disease 2019 (COVID-19) pandemic triggered an unprecedented concentration of economic and research efforts to generate knowledge at unequalled speed on deregulated interferon type I signalling and nuclear factor kappa light chain enhancer in B-cells (NF-κB)-driven interleukin (IL)-1β, IL-6, IL-18 secretion causing cytokine storms. The translation of the knowledge on how the resulting systemic inflammation can lead to life-threatening complications into novel treatments and vaccine technologies is underway. Nevertheless, previously existing knowledge on the role of cytoplasmatic or circulating self-DNA as a pro-inflammatory damage-associated molecular pattern (DAMP) was largely ignored. Pathologies reported ‘de novo’ for patients infected with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2 to be outcomes of self-DNA-driven inflammation in fact had been linked earlier to self-DNA in different contexts, e.g., the infection with Human Immunodeficiency Virus (HIV)-1, sterile inflammation, and autoimmune diseases. I highlight particularly how synergies with other DAMPs can render immunogenic properties to normally non-immunogenic extracellular self-DNA, and I discuss the shared features of the gp41 unit of the HIV-1 envelope protein and the SARS-CoV 2 Spike protein that enable HIV-1 and SARS-CoV-2 to interact with cell or nuclear membranes, trigger syncytia formation, inflict damage to their host’s DNA, and trigger inflammation – likely for their own benefit. These similarities motivate speculations that similar mechanisms to those driven by gp41 can explain how inflammatory self-DNA contributes to some of most frequent adverse events after vaccination with the BNT162b2 mRNA (Pfizer/BioNTech) or the mRNA-1273 (Moderna) vaccine, i.e., myocarditis, herpes zoster, rheumatoid arthritis, autoimmune nephritis or hepatitis, new-onset systemic lupus erythematosus, and flare-ups of psoriasis or lupus. The hope is to motivate a wider application of the lessons learned from the experiences with COVID-19 and the new mRNA vaccines to combat future non-COVID-19 diseases.

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Severity prediction in COVID-19 patients using clinical markers and explainable artificial intelligence: A stacked ensemble machine learning approach

Chadaga,

Prabhu,

Sampathila

et al. 2023

IDT

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The recent COVID-19 pandemic had wreaked havoc worldwide, causing a massive strain on already-struggling healthcare infrastructure. Vaccines have been rolled out and seem effective in preventing a bad prognosis. However, a small part of the population (elderly and people with comorbidities) continues to succumb to this deadly virus. Due to a lack of available resources, appropriate triaging and treatment planning are vital to improving outcomes for patients with COVID-19. Assessing whether a patient requires the hospital’s Intensive Care Unit (ICU) is very important since these units are not available for every patient. In this research, we automate this assessment with stacked ensemble machine learning models that predict ICU admission based on general patient laboratory data. We have built an explainable decision support model which automatically scores the COVID-19 severity for individual patients. Data from 1925 COVID-19 positive patients, sourced from three top-tier Brazilian hospitals, were used to design the model. Pearson’s correlation and mutual information were utilized for feature selection, and the top 24 features were chosen as input for the model. The final stacked model could provide decision support on whether an admitted COVID-19 patient would require the ICU or not, with an accuracy of 88%. Explainable Artificial Intelligence (EAI) was used to undertake system-level insight discovery and investigate various clinical variables’ impact on decision-making. It was found that the most critical factors were respiratory rate, temperature, blood pressure, lactate dehydrogenase, hemoglobin, and age. Healthcare facilities can use the proposed approach to categorize COVID-19 patients and prevent COVID-19 fatalities.

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Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients

Cited by 3 publications

References 111 publications

APOBEC3G Is a p53-Dependent Restriction Factor in Respiratory Syncytial Virus Infection of Human Cells Included in the p53/Immune Axis

APOBEC3G Is a p53-Dependent Restriction Factor in Respiratory Syncytial Virus Infection of Human Cells Included in the p53/Immune Axis

Self-DNA driven inflammation in COVID-19 and after mRNA-based vaccination: lessons for non-COVID-19 pathologies

Severity prediction in COVID-19 patients using clinical markers and explainable artificial intelligence: A stacked ensemble machine learning approach

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