A genetic variant in IL-6 lowering its expression is protective for critical patients with COVID-19

MIR218 polygenic risk score is associated with cognitive function and neurochemical metabolites among patients with depressed bipolar disorders

BACKGROUNDS

Evidence from animal and population studies has consistently revealed that microRNA 218 (MIR218) is involved in susceptibility to depression and cognitive functions. Nevertheless, few studies have evaluated the association between MIR218 and clinical features in patients with depressed bipolar disorder (BD).

METHODS

A total of 66 patients with depressed BD and 49 healthy controls (HCs) were recruited for this study. MIR218 polygenic risk score (PRS) was used to assess the addictive effects of the MIR218 regulated genes. We compared the MIR218 PRS between patients with depressed BD and HCs to investigate whether it can be used to predict the risk of BD, and further explored the association between MIR218 PRS and cognitive performance as well as neurochemical metabolites among depressed BD.

RESULTS

We found that there was a significant difference in MIR218 PRS between patients with depressed BD and HCs. The correlation analysis indicated that MIR218 PRS was negative associated with the number of disease onset (r = -0.311, P = 0.033) and choline (Cho)/creatine (Cr) in right thalamus (r = -0.285, P = 0.021). Additionally, as supported by previous findings, patients with lower MIR218 PRS presented more domains of impaired cognitive function than those with higher scores.

CONCLUSION

These findings suggested MIR218 PRS might be useful in differentiating patients with depressed BD from HCs. Moreover, depressed BD with lower MIR218 PRS showed more pronounced cognitive impairment than those with higher scores, which may be associated with disease recurrence and Cho metabolism in right thalamus.

Study of TNF-α, IFN-γ, IL-10, TGF-β and IL-6 Gene Polymorphisms in a Cohort of Professionals Who Worked in the First Pandemic Wave in the Brazilian Amazon

Genetic polymorphisms in genes that enable the production of an effective host immune response, such as single nucleotide polymorphisms (SNPS) in the IL-6, INF-alpha, IFN-gamma, IL-10, TGF-beta genes can cause unfavorable clinical conditions or susceptibility to pathologies. The objective of this work is to evaluate the epidemiological and genetic profile of professionals from health institutions during the first pandemic wave. A case-control study was performed with convenience sampling from health institutions (HI) workers from Belém-PA, Northern Brazil (N = 213), divided into symptomatology groups (Asymptomatic-AS, n = 91; and Symptomatic-SI, n = 122); and severity groups classified by chest computerized tomography-CCT data (symptomatic with pulmonary involvement-SCP, n = 37; symptomatic without pulmonary involvement-SSP, n = 8). Genotyping was performed by sanger sequencing for SNP TNF-α -308 G/A (rs1800629), IFN-γ +874 T/A (rs2430561), TGF-β codon 10 (rs1982073), codon 25 (rs1800471), IL-6 - 174 G/C (rs180079), IL-10 - 1082 A/T (rs1800896), -819 C/T (rs1800871), and -592 A/C (rs1800872), and statistical analysis through the Epilfo program. Significant association was observed between the presence of comorbidities and poor prognosis of COVID-19 (especially between COVID-19 and overweight and obesity). Only the TNF-α 308 G/A snp was significantly associated with the symptoms and severity of COVID-19. These findings about this TNF-α SNP passed in the multiple testing correction at a false discovery rate (FDR)< 0.05. These data can help medicine and the scientific community understand the influence of genetics and epidemiological parameters in combating COVID-19.

The role of inflammatory gene polymorphisms in severe COVID-19: a review

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has profoundly impacted global healthcare systems and spurred extensive research efforts over the past three years. One critical aspect of the disease is the intricate interplay between the virus and the host immune response, particularly the role of inflammatory gene expression in severe COVID-19. While numerous previous studies have explored the role of genetic polymorphisms in COVID-19, research specifically focusing on inflammatory genes and their associations with disease severity remains limited. This review explores the relationship between severe COVID-19 outcomes and genetic polymorphisms within key inflammatory genes. By investigating the impact of genetic variations on immune responses, which include cytokine production and downstream signalling pathways, we aim to provide a comprehensive overview of how genetic polymorphisms contribute to the variability in disease presentation. Through an in-depth analysis of existing literature, we shed light on potential therapeutic targets and personalized approaches that may enhance our understanding of disease pathogenesis and treatment strategies.

Pathway-Based Mendelian Randomization for Pre-Infection IL-6 Levels Highlights Its Role in Coronavirus Disease

OBJECTIVES

Interleukin 6 (IL-6) levels at hospital admission have been suggested for disease prognosis, and IL-6 antagonists have been suggested for the treatment of patients with severe COVID-19. However, less is known about the relationship between pre-COVID-19 IL-6 levels and the risk of severe COVID-19. To fill in this gap, here we extensively investigated the association of genetically instrumented IL-6 pathway components with the risk of severe COVID-19.

METHODS

We used a two-sample Mendelian randomization study design and retrieved genetic instruments for blood biomarkers of IL-6 activation, including IL-6, soluble IL-6 receptor, IL-6 signal transducer, and CRP, from respective large available GWASs. To establish associations of these instruments with COVID-19 outcomes, we used data from the Host Genetics Initiative and GenOMICC studies.

RESULTS

Our analyses revealed inverse associations of genetically instrumented levels of IL-6 and its soluble receptor with the risk of developing severe disease (OR = 0.60 and 0.94, respectively). They also demonstrated a positive association of severe disease with the soluble signal transducer level (OR = 1.13). Only IL-6 associations with severe COVID-19 outcomes reached the significance threshold corrected for multiple testing (p < 0.003; with COVID-19 hospitalization and critical illness).

CONCLUSIONS

These potential causal relationships for pre-COVID-19 IL-6 levels with the risk of developing severe symptoms provide opportunities for further evaluation of these factors as prognostic/preventive markers of severe COVID-19. Further studies will need to clarify whether the higher risk for a severe disease course with lower baseline IL-6 levels may also extend to other infectious diseases.

Proteome analysis develops novel plasma proteins classifier in predicting the mortality of COVID-19

COVID-19 has been a global concern for 3 years, however, consecutive plasma protein changes in the disease course are currently unclear. Setting the mortality within 28 days of admission as the main clinical outcome, plasma samples were collected from patients in discovery and independent validation groups at different time points during the disease course. The whole patients were divided into death and survival groups according to their clinical outcomes. Proteomics and pathway/network analyses were used to find the differentially expressed proteins and pathways. Then, we used machine learning to develop a protein classifier which can predict the clinical outcomes of the patients with COVID-19 and help identify the high-risk patients. Finally, a classifier including C-reactive protein, extracellular matrix protein 1, insulin-like growth factor-binding protein complex acid labile subunit, E3 ubiquitin-protein ligase HECW1 and phosphatidylcholine-sterol acyltransferase was determined. The prediction value of the model was verified with an independent patient cohort. This novel model can realize early prediction of 28-day mortality of patients with COVID-19, with the area under curve 0.88 in discovery group and 0.80 in validation group, superior to 4C mortality and E-CURB65 scores. In total, this work revealed a potential protein classifier which can assist in predicting the outcomes of COVID-19 patients and providing new diagnostic directions.

Comprehensive bioinformatics analysis and systems biology approaches to identify the interplay between COVID-19 and pericarditis

Background

Increasing evidence indicating that coronavirus disease 2019 (COVID-19) increased the incidence and related risks of pericarditis and whether COVID-19 vaccine is related to pericarditis has triggered research and discussion. However, mechanisms behind the link between COVID-19 and pericarditis are still unknown. The objective of this study was to further elucidate the molecular mechanisms of COVID-19 with pericarditis at the gene level using bioinformatics analysis.

Methods

Genes associated with COVID-19 and pericarditis were collected from databases using limited screening criteria and intersected to identify the common genes of COVID-19 and pericarditis. Subsequently, gene ontology, pathway enrichment, protein-protein interaction, and immune infiltration analyses were conducted. Finally, TF-gene, gene-miRNA, gene-disease, protein-chemical, and protein-drug interaction networks were constructed based on hub gene identification.

Results

A total of 313 common genes were selected, and enrichment analyses were performed to determine their biological functions and signaling pathways. Eight hub genes (IL-1β, CD8A, IL-10, CD4, IL-6, TLR4, CCL2, and PTPRC) were identified using the protein-protein interaction network, and immune infiltration analysis was then carried out to examine the functional relationship between the eight hub genes and immune cells as well as changes in immune cells in disease. Transcription factors, miRNAs, diseases, chemicals, and drugs with high correlation with hub genes were predicted using bioinformatics analysis.

Conclusions

This study revealed a common gene interaction network between COVID-19 and pericarditis. The screened functional pathways, hub genes, potential compounds, and drugs provided new insights for further research on COVID-19 associated with pericarditis.

Implication of IL-12A, IL-12B, IL-6, and TNF single-nucleotide polymorphisms in severity and susceptibility to COVID-19

BACKGROUND

The Coronavirus Disease 2019 (COVID-19) pandemic has led to significant global morbidity and mortality. Understanding the genetic factors that influence disease outcomes can provide critical insights into pathogenesis and potential therapeutic targets.

OBJECTIVE

This study aimed to investigate the potential correlation between single nucleotide polymorphisms (SNPs) in Interleukin 12 Subunit Alpha (IL-12A), Interleukin 12 Subunit Beta (IL-12B), Interleukin 6 (IL-6), and Tumor Necrosis Factor (TNF) genes and the severity as well as susceptibility to COVID-19 among Moroccan patients.

PATIENTS AND METHODS

Next-Generation sequencing (NGS) was conducted on 325 Moroccan participants, 207 patients with PCR-confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and 118 controls. Among these patients, 51% presented moderate to severe symptoms requiring hospitalization, while 49% were asymptomatic or experienced mild symptoms and did not require hospitalization. Statistical analysis was performed using codominant, dominant, and recessive logistic regression models to assess correlations with the severity and susceptibility to COVID-19 infection.

RESULTS

No association was found between SNPs of IL-12A, IL-12B, IL-6 or TNF and COVID-19 severity and susceptibility. However, our results unveiled a noteworthy association with IL-6 rs2069840, which exhibited a negative correlation (OR = 0.21, 95% CI = 0.07-0.69, p = .006), suggesting a protective effect against SARS-CoV-2 infection.

CONCLUSION

Polymorphisms in IL-12A, IL-12B, IL-6, and TNF genes are not correlated to the severity and susceptibility of COVID-19.

Serine deficiency exacerbates psoriatic skin inflammation by regulating S-adenosyl methionine-dependent DNA methylation and NF-κB signalling activation in keratinocytes

BACKGROUND

Serine metabolism is crucial for tumour oncogenesis and immune responses. S-adenosyl methionine (SAM), a methyl donor, is typically derived from serine-driven one-carbon metabolism. However, the involvement of serine metabolism in psoriatic skin inflammation remains unclear.

OBJECTIVES

To investigate the association between serine metabolism and psoriatic skin inflammation.

METHODS

Clinical samples were collected from patients with psoriasis and the expression of serine biosynthesis enzymes was evaluated. The HaCaT human keratinocyte cell line was transfected with small interfering RNA (siRNA) of key enzyme or treated with inhibitors. RNA sequencing and DNA methylation assays were performed to elucidate the mechanisms underlying serine metabolism-regulated psoriatic keratinocyte inflammation. An imiquimod (IMQ)-induced psoriasis mouse model was established to determine the effect of the SAM administration on psoriatic skin inflammation.

RESULTS

The expression of serine synthesis pathway enzymes, including the first rate-limiting enzyme in serine biosynthesis, phosphoglycerate dehydrogenase (PHGDH), was downregulated in the epidermal lesions of patients with psoriasis compared with that in healthy controls. Suppressing PHGDH in keratinocytes promoted the production of proinflammatory cytokines and enrichment of psoriatic-related signalling pathways, including the tumour necrosis factor-alpha (TNF-α) signalling pathway, interleukin (IL)-17 signalling pathway and NF-κB signalling pathway. In particular, PHGDH inhibition markedly promoted the secretion of IL-6 in keratinocytes with or without IL-17A, IL-22, IL-1α, oncostatin M and TNF-α (mix) stimulation. Mechanistically, PHGDH inhibition upregulated the expression of IL-6 by inhibiting SAM-dependent DNA methylation at the promoter and increasing the binding of myocyte enhancer factor 2A. Furthermore, PHGDH inhibition increased the secretion of IL-6 by increasing the activation of NF-κB via SAM inhibition. SAM treatment effectively alleviated IMQ-induced psoriasis-like skin inflammation in mice.

CONCLUSIONS

Our study revealed the crucial role of PHGDH in antagonising psoriatic skin inflammation and indicated that targeting serine metabolism may represent a novel therapeutic strategy for treating psoriasis.

Mitochondrial mass of circulating NK cells as a novel biomarker in severe SARS-CoV-2 infection

BACKGROUND

Severe SARS-CoV-2 infection results in lymphopenia and impaired function of T, B, and NK (TBNK-dominant) lymphocytes. Mitochondria are essential targets of SARS-CoV-2 and the efficacy of lymphocyte mitochondrial function for immunosurveillance in COVID-19 patients has not been evaluated.

METHODS

Multi-parametric flow cytometry was used to characterize mitochondrial function, including mitochondrial mass (MM) and low mitochondrial membrane potential (MMPlow), in TBNK-dominant lymphocytes from severe (n = 93) and moderate (n = 77) hospitalized COVID-19 patients. We compared the role of novel lymphocyte mitochondrial indicators and routine infection biomarkers as early predictors of severity and death in COVID-19 patients. We then developed a mortality decision tree prediction model based on immunosurveillance indicators through machine learning.

RESULTS

At admission, the MM of circulating NK cells (NK-MM) was the best discriminator of severe/moderate disease (AUC = 0.8067) compared with the routine infection biomarkers. The NK cell count and NK-MM displayed superior diagnostic effects to distinguish patients with non-fatal or fatal outcomes. Interestingly, NK-MM was significantly polarized in non-survivors, with some patients showing a decrease and others showing an abnormal increase. Kaplan-Meier analysis showed that NK-MM had the optimal predictive efficacy (hazard ratio = 11.66). The decision tree model has the highest proportion of importance for NK-MM, which is superior to the single diagnostic effect of the above indicators (AUC = 0.8900).

CONCLUSION

NK-MM was not only associated with disease severity, its abnormal increases or decreases also predicted mortality risk. The resulting decision tree prediction model is the first to focus on immune monitoring indicators to provide decision-making clues for COVID-19 clinical management.

Spotlight on contributory role of host immunogenetic profiling in SARS-CoV-2 infection: Susceptibility, severity, mortality, and vaccine effectiveness

BACKGROUND

The SARS-CoV-2 virus has spread continuously worldwide, characterized by various clinical symptoms. The immune system responds to SARS-CoV-2 infection by producing Abs and secreting cytokines. Recently, numerous studies have highlighted that immunogenetic factors perform a putative role in COVID-19 pathogenesis and implicate vaccination effectiveness.

AIM

This review summarizes the relevant articles and evaluates the significance of mutation and polymorphism in immune-related genes regarding susceptibility, severity, mortality, and vaccination effectiveness of COVID-19. Furthermore, the correlation between host immunogenetic and SARS-CoV-2 reinfection is discussed.

METHOD

A comprehensive search was conducted to identify relevant articles using five databases until January 2023, which resulted in 105 total articles.

KEY FINDINGS

Taken to gather this review summarized that: (a) there is a plausible correlation between immune-related genes and COVID-19 outcomes, (b) the HLAs, cytokines, chemokines, and other immune-related genes expression profiles can be a prognostic factor in COVID-19-infected patients, and (c) polymorphisms in immune-related genes have been associated with the effectiveness of vaccination.

SIGNIFICANCE

Regarding the importance of mutation and polymorphisms in immune-related genes in COVID-19 outcomes, modulating candidate genes is expected to help clinical decisions, patient outcomes management, and innovative therapeutic approach development. In addition, the manipulation of host immunogenetics is hypothesized to induce more robust cellular and humoral immune responses, effectively increase the efficacy of vaccines, and subsequently reduce the incidence rates of reinfection-associated COVID-19.

Influence of polymorphic variations of IFNL, HLA, and IL-6 genes in severe cases of COVID-19

The administration of vaccination doses to the global population has led to a decrease in the incidence of COVID-19. However, the clinical picture developed by infected individuals remains extremely concerning due to the great variability in the severity of cases even in vaccinated individuals. The clinical progression of the pathology is characterized by various influential factors such as sex, age group, comorbidities, and the genetics of the individual. The immune response to viral infections can be strongly influenced by the genetics of individuals; nucleotide variations called single-nucleotide polymorphisms (SNPs) in structures involved in the innate and adaptive immune response such as interferon (IFN)-λ, human leukocyte antigen (HLA), and interleukin (IL)-6 are frequently associated with pathological progression. In this study, we conducted a review of the main SNPs of these structures that are associated with severity in COVID-19. Searches were conducted on some platforms of the National Center for Biotechnology and Information (NCBI), and 102 studies were selected for full reading according to the inclusion criteria. IFNs showed a strong association with antiviral function, specifically, IFN-λ3 (IL-28B) demonstrated genetic variants commonly related to clinical progression in various pathologies. For COVID-19, rs12979860 and rs1298275 presented frequently described unfavorable genotypes for pathological conditions of hepatitis C and hepatocellular carcinoma. The high genetic variability of HLA was reported in the studies as a crucial factor relevant to the late immune response, mainly due to its ability to recognize antigens, with the HLA-B*46:01 SNP being associated with susceptibility to COVID-19. For IL-6, rs1554606 showed a strong relationship with the clinical progression of COVID-19. In addition, rs2069837 was identified with possible host protection relationships when linked to this infection.

Genetic susceptibility to severe COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the coronavirus disease 2019 (COVID-19) pandemic. Clinical manifestations of the disease range from an asymptomatic condition to life-threatening events and death, with more severe courses being associated with age, male sex, and comorbidities. Besides these risk factors, intrinsic characteristics of the virus as well as genetic factors of the host are expected to account for COVID-19 clinical heterogeneity. Genetic studies have long been recognized as fundamental to identify biological mechanisms underlying congenital diseases, to pinpoint genes/proteins responsible for the susceptibility to different inherited conditions, to highlight targets of therapeutic relevance, to suggest drug repurposing, and even to clarify causal relationships that make modifiable some environmental risk factors. Though these studies usually take long time to be concluded and, above all, to translate their discoveries to patients' bedside, the scientific community moved really fast to deliver genetic signals underlying different COVID-19 phenotypes. In this Review, besides a concise description of COVID-19 symptomatology and of SARS-CoV-2 mechanism of infection, we aimed to recapitulate the current literature in terms of host genetic factors that specifically associate with an increased severity of the disease.

Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections

The pandemic of COVID-19 is a severe threat to human life and the global economy. Despite the success of vaccination efforts in reducing the spread of the virus, the situation remains largely uncontrolled due to the random mutation in the RNA sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which demands different variants of effective drugs. Disease-causing gene-mediated proteins are usually used as receptors to explore effective drug molecules. In this study, we analyzed two different RNA-Seq and one microarray gene expression profile datasets by integrating EdgeR, LIMMA, weighted gene co-expression network and robust rank aggregation approaches, which revealed SARS-CoV-2 infection causing eight hub-genes (HubGs) including HubGs; REL, AURKA, AURKB, FBXL3, OAS1, STAT4, MMP2 and IL6 as the host genomic biomarkers. Gene Ontology and pathway enrichment analyses of HubGs significantly enriched some crucial biological processes, molecular functions, cellular components and signaling pathways that are associated with the mechanisms of SARS-CoV-2 infections. Regulatory network analysis identified top-ranked 5 TFs (SRF, PBX1, MEIS1, ESR1 and MYC) and 5 miRNAs (hsa-miR-106b-5p, hsa-miR-20b-5p, hsa-miR-93-5p, hsa-miR-106a-5p and hsa-miR-20a-5p) as the key transcriptional and post-transcriptional regulators of HubGs. Then, we conducted a molecular docking analysis to determine potential drug candidates that could interact with HubGs-mediated receptors. This analysis resulted in the identification of top-ranked ten drug agents, including Nilotinib, Tegobuvir, Digoxin, Proscillaridin, Olysio, Simeprevir, Hesperidin, Oleanolic Acid, Naltrindole and Danoprevir. Finally, we investigated the binding stability of the top-ranked three drug molecules Nilotinib, Tegobuvir and Proscillaridin with the three top-ranked proposed receptors (AURKA, AURKB, OAS1) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore, the findings of this study might be useful resources for diagnosis and therapies of SARS-CoV-2 infections.

Gut microbiota alters host bile acid metabolism to contribute to intrahepatic cholestasis of pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is a female pregnancy-specific disorder that is characterized by increased serum bile acid and adverse fetal outcomes. The aetiology and mechanism of ICP are poorly understood; thus, existing therapies have been largely empiric. Here we show that the gut microbiome differed significantly between individuals with ICP and healthy pregnant women, and that colonization with gut microbiome from ICP patients was sufficient to induce cholestasis in mice. The gut microbiomes of ICP patients were primarily characterized by Bacteroides fragilis (B. fragilis), and B. fragilis was able to promote ICP by inhibiting FXR signaling via its BSH activity to modulate bile acid metabolism. B. fragilis-mediated FXR signaling inhibition was responsible for excessive bile acid synthesis and interrupted hepatic bile excretion to ultimately promote the initiation of ICP. We propose that modulation of the gut microbiota-bile acid-FXR axis may be of value for ICP treatment.

Genetic polymorphisms of IL6 gene -174G > C and -597G > A are associated with the risk of COVID-19 severity

Coronavirus disease-2019 (COVID-19) is pro-inflammatory disorder characterized by acute respiratory distress syndrome. Interleukin-6, a cytokine secreted by macrophages, which mediates an inflammatory response, is frequently increased and associated with the severity in COVID-19 patients. The differential expression of IL6 cytokine in COVID-19 patients may be associated with the presence of single nucleotide polymorphisms (SNPs) in regulatory region of cytokine genes. The aim of this study is to investigate the role of two promoter polymorphisms of the IL6 gene (-597G > A and -174G > C) with the severity of COVID-19. The study included 242 patients, out of which 97 patients with severe symptoms and 145 patients with mild symptoms of COVID-19. Genotyping of two selected SNPs, rs1800795 (-174G > C) and rs1800797 (-597G > A) of promoter region of IL6 gene, was performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). In our study, individuals with GC genotypes of IL6 (-174G > C) polymorphism showed significantly higher risk of severity [adjusted odds (OR) 3.86, p <.001] but we did not observe any association of COVID-19 severity with rs1800797 (-597G > A) polymorphism. The COVID-19 severity was significantly higher in individuals having 'C' allele of IL6 (-174G > C) polymorphism (p = .014). Linkage disequilibrium between rs1800795 (-174G > C) and rs1800797 (-597G > A) showed that individuals having AC* haplotype significantly association with COVID-19 severity (p = .034). Our results suggest that 'C' allele of rs1800795 (-174G > C) polymorphism of IL6 may be the risk allele for severity of COVID-19 in North Indian population.

Association between IL-6 polymorphisms and Atopic Dermatitis in Chinese Han children

Introduction

Atopic Dermatitis (AD) is a chronic inflammatory skin disease that affects almost 20% of children and 2 -10% of adults worldwide. Previous studies revealed that Interleukin-6 (IL-6) plays an essential role in autoimmune and chronic inflammatory diseases. This study aims to investigate the associations between IL-6 polymorphisms and AD.

Methods

Blood samples were collected from 132 AD patients and 100 controls, and single nucleotide polymorphisms (SNPs) in IL-6 (rs2069840 (C/G), rs2066992 (G/T), rs2069837 (A/G) and rs1800796 (G/C)) were analyzed using Multiplex PCR-Based Next Generation Sequencing (NGS).

Results

Results showed that the A/G genotype of IL-6/rs2069837 was significantly associated with a 1.933-fold increased risk of AD compared to those patients with A/A genotype (OR 1.933; 95%CI 1.086-3.438; p=0.024). The combined A/G-G/G genotype raised AD risk by 1.856 times compared to patients with the A/A genotype in dominant model (OR: 1.856; 95% CI: 1.056-3.261; p=0.030). No association was observed for 3 other SNPs and 4 haplotypes.

Discussion

These findings suggested that the A/G genotype of IL-6/rs2069837 was more susceptible to AD than A/A genotype in Chinese Han children, indicating the risk role of IL-6/rs2069837 in the occurrence of AD.

Pharmacogenetics Role of Genetic Variants in Immune-Related Factors: A Systematic Review Focusing on mCRC

Pharmacogenetics plays a key role in personalized cancer treatment. Currently, the clinically available pharmacogenetic markers for metastatic colorectal cancer (mCRC) are in genes related to drug metabolism, such as DPYD for fluoropyrimidines and UGT1A1 for irinotecan. Recently, the impact of host variability in inflammatory and immune-response genes on treatment response has gained considerable attention, opening innovative perspectives for optimizing tailored mCRC therapy. A literature review was performed on the predictive role of immune-related germline genetic biomarkers on pharmacological outcomes in patients with mCRC. Particularly, that for efficacy and toxicity was reported and the potential role for clinical management of patients was discussed. Most of the available data regard therapy effectiveness, while the impact on toxicity remains limited. Several studies focused on the effects of polymorphisms in genes related to antibody-dependent cellular cytotoxicity (FCGR2A, FCGR3A) and yielded promising but inconclusive results on cetuximab efficacy. The remaining published data are sparse and mainly hypothesis-generating but suggest potentially interesting topics for future pharmacogenetic studies, including innovative gene-drug interactions in a clinical context. Besides the tumor immune escape pathway, genetic markers belonging to cytokines/interleukins (IL-8 and its receptors) and angiogenic mediators (IGF1) seem to be the best investigated and hopefully most promising to be translated into clinical practice after validation.

Revisiting potential value of antitumor drugs in the treatment of COVID-19

Since an outbreak started in China in 2019, coronavirus disease 2019 (COVID-19) has rapidly become a worldwide epidemic with high contagiousness and caused mass mortalities of infected cases around the world. Currently, available treatments for COVID-19, including supportive care, respiratory support and antiviral therapy, have shown limited efficacy. Thus, more effective therapeutic modalities are highly warranted. Drug repurposing, as an efficient strategy to explore a potential broader scope of the application of approved drugs beyond their original indications, accelerates the process of discovering safe and effective agents for a given disease. Since the outbreak of COVID-19 pandemic, drug repurposing strategy has been widely used to discover potential antiviral agents, and some of these drugs have advanced into clinical trials. Antitumor drugs compromise a vast variety of compounds and exhibit extensive mechanism of action, showing promising properties in drug repurposing. In this review, we revisit the potential value of antitumor drugs in the treatment of COVID-19 and systematically discuss their possible underlying mechanisms of the antiviral actions.

Human genetic basis of severe or critical illness in COVID-19

Coronavirus Disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable morbidity and mortality worldwide. The clinical manifestation of COVID-19 ranges from asymptomatic or mild infection to severe or critical illness, such as respiratory failure, multi-organ dysfunction or even death. Large-scale genetic association studies have indicated that genetic variations affecting SARS-CoV-2 receptors (angiotensin-converting enzymes, transmembrane serine protease-2) and immune components (Interferons, Interleukins, Toll-like receptors and Human leukocyte antigen) are critical host determinants related to the severity of COVID-19. Genetic background, such as 3p21.31 and 9q34.2 loci were also identified to influence outcomes of COVID-19. In this review, we aimed to summarize the current literature focusing on human genetic factors that may contribute to the observed diversified severity of COVID-19. Enhanced understanding of host genetic factors and viral interactions of SARS-CoV-2 could provide scientific bases for personalized preventive measures and precision medicine strategies.

Bioinformatics and systems biology approach to identify the pathogenetic link of Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Background

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global crisis. Although many people recover from COVID-19 infection, they are likely to develop persistent symptoms similar to those of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) after discharge. Those constellations of symptoms persist for months after infection, called Long COVID, which may lead to considerable financial burden and healthcare challenges. However, the mechanisms underlying Long COVID and ME/CFS remain unclear.

Methods

We collected the genes associated with Long COVID and ME/CFS in databases by restricted screening conditions and clinical sample datasets with limited filters. The common genes for Long COVID and ME/CFS were finally obtained by taking the intersection. We performed several advanced bioinformatics analyses based on common genes, including gene ontology and pathway enrichment analyses, protein-protein interaction (PPI) analysis, transcription factor (TF)-gene interaction network analysis, transcription factor-miRNA co-regulatory network analysis, and candidate drug analysis prediction.

Results

We found nine common genes between Long COVID and ME/CFS and gained a piece of detailed information on their biological functions and signaling pathways through enrichment analysis. Five hub proteins (IL-6, IL-1B, CD8A, TP53, and CXCL8) were collected by the PPI network. The TF-gene and TF-miRNA coregulatory networks were demonstrated by NetworkAnalyst. In the end, 10 potential chemical compounds were predicted.

Conclusion

This study revealed common gene interaction networks of Long COVID and ME/CFS and predicted potential therapeutic drugs for clinical practice. Our findings help to identify the potential biological mechanism between Long COVID and ME/CFS. However, more laboratory and multicenter evidence is required to explore greater mechanistic insight before clinical application in the future.

Hallmarks of Severe COVID-19 Pathogenesis: A Pas de Deux Between Viral and Host Factors

Two years into Coronavirus Disease 2019 (COVID-19) pandemic, a comprehensive characterization of the pathogenesis of severe and critical forms of COVID-19 is still missing. While a deep dysregulation of both the magnitude and functionality of innate and adaptive immune responses have been described in severe COVID-19, the mechanisms underlying such dysregulations are still a matter of scientific debate, in turn hampering the identification of new therapies and of subgroups of patients that would most benefit from individual clinical interventions. Here we review the current understanding of viral and host factors that contribute to immune dysregulation associated with COVID-19 severity in the attempt to unfold and broaden the comprehension of COVID-19 pathogenesis and to define correlates of protection to further inform strategies of targeted therapeutic interventions.