The TNFRSF13C H159Y Variant Is Associated with Severe COVID-19: A Retrospective Study of 500 Patients from Southern Italy

Targeting ATP2B1 impairs PI3K/Akt/FOXO signaling and reduces SARS-COV-2 infection and replication

ATP2B1 is a known regulator of calcium (Ca2+) cellular export and homeostasis. Diminished levels of intracellular Ca2+ content have been suggested to impair SARS-CoV-2 replication. Here, we demonstrate that a nontoxic caloxin-derivative compound (PI-7) reduces intracellular Ca2+ levels and impairs SARS-CoV-2 infection. Furthermore, a rare homozygous intronic variant of ATP2B1 is shown to be associated with the severity of COVID-19. The mechanism of action during SARS-CoV-2 infection involves the PI3K/Akt signaling pathway activation, inactivation of FOXO3 transcription factor function, and subsequent transcriptional inhibition of the membrane and reticulum Ca2+ pumps ATP2B1 and ATP2A1, respectively. The pharmacological action of compound PI-7 on sustaining both ATP2B1 and ATP2A1 expression reduces the intracellular cytoplasmic Ca2+ pool and thus negatively influences SARS-CoV-2 replication and propagation. As compound PI-7 lacks toxicity in vitro, its prophylactic use as a therapeutic agent against COVID-19 is envisioned here.

Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs

By profiling gene expression in individual cells, single-cell RNA-sequencing (scRNA-seq) can resolve cellular heterogeneity and cell-type gene expression dynamics. Its application to time-series samples can identify temporal gene programs active in different cell types, for example, immune cells' responses to viral infection. However, current scRNA-seq analysis has limitations. One is the low number of genes detected per cell. The second is insufficient replicates (often 1-2) due to high experimental cost. The third lies in the data analysis-treating individual cells as independent measurements leads to inflated statistics. To address these, we explore a new computational framework, specifically whether "metacells" constructed to maintain cellular heterogeneity within individual cell types (or clusters) can be used as "replicates" for increasing statistical rigor. Toward this, we applied SEACells to a time-series scRNA-seq dataset from peripheral blood mononuclear cells (PBMCs) after SARS-CoV-2 infection to construct metacells, and used them in maSigPro for quadratic regression to find significantly differentially expressed genes (DEGs) over time, followed by clustering expression velocity trends. We showed that such metacells retained greater expression variances and produced more biologically meaningful DEGs compared to either metacells generated randomly or from simple pseudobulk methods. More specifically, this approach correctly identified the known ISG15 interferon response program in almost all PBMC cell types and many DEGs enriched in the previously defined SARS-CoV-2 infection response pathway. It also uncovered additional and more cell type-specific temporal gene expression programs. Overall, our results demonstrate that the metacell-pseudoreplicate strategy could potentially overcome the limitation of 1-2 replicates.

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.

Computational network analysis of host genetic risk variants of severe COVID-19

BACKGROUND

Genome-wide association studies have identified numerous human host genetic risk variants that play a substantial role in the host immune response to SARS-CoV-2. Although these genetic risk variants significantly increase the severity of COVID-19, their influence on body systems is poorly understood. Therefore, we aim to interpret the biological mechanisms and pathways associated with the genetic risk factors and immune responses in severe COVID-19. We perform a deep analysis of previously identified risk variants and infer the hidden interactions between their molecular networks through disease mapping and the similarity of the molecular functions between constructed networks.

RESULTS

We designed a four-stage computational workflow for systematic genetic analysis of the risk variants. We integrated the molecular profiles of the risk factors with associated diseases, then constructed protein-protein interaction networks. We identified 24 protein-protein interaction networks with 939 interactions derived from 109 filtered risk variants in 60 risk genes and 56 proteins. The majority of molecular functions, interactions and pathways are involved in immune responses; several interactions and pathways are related to the metabolic and cardiovascular systems, which could lead to multi-organ complications and dysfunction.

CONCLUSIONS

This study highlights the importance of analyzing molecular interactions and pathways to understand the heterogeneous susceptibility of the host immune response to SARS-CoV-2. We propose new insights into pathogenicity analysis of infections by including genetic risk information as essential factors to predict future complications during and after infection. This approach may assist more precise clinical decisions and accurate treatment plans to reduce COVID-19 complications.

Systematic review and meta-analysis of human genetic variants contributing to COVID-19 susceptibility and severity

The COVID-19 pandemic has spawned global health crisis of unprecedented magnitude, claiming millions of lives and pushing healthcare systems in many countries to the brink. Among several factors that contribute to an increased risk of COVID-19 and progression to exacerbated manifestations, host genetic landscape is increasingly being recognized as a critical determinant of susceptibility/resistance to infection and a prognosticator of clinical outcomes in infected individuals. Recently, several case-control association studies investigated the influence of human gene variants on COVID-19 susceptibility and severity to identify the culpable mutations. However, a comprehensive synthesis of the recent advances in COVID-19 host genetics research was lacking, and the inconsistent findings of the association studies required reliable evaluation of the strength of association with greater statistical power. In this study, we embarked on a systematic search of all possible reports of genetic association with COVID-19 till April 07, 2022, and performed meta-analyses of all the genetic polymorphisms that were examined in at least three studies. After identifying a total of 84 studies that investigated the association of 130 polymorphisms in 61 genes, we performed meta-analyses of all the eligible studies. Seven genetic polymorphisms involving 15,550 cases and 444,007 controls were explored for association with COVID-19 susceptibility, of which, ACE1 I/D rs4646994/rs1799752, APOE rs429358, CCR5 rs333, and IFITM3 rs12252 showed increased risk of infection. Meta-analyses of 11 gene variants involving 6702 patients with severe COVID-19 and 8640 infected individuals with non-severe manifestations revealed statistically significant association of ACE2 rs2285666, ACE2 rs2106809, ACE2 rs2074192, AGTR1 rs5186, and TNFA rs1800629 with COVID-19 severity. Overall, our study presents a synthesis of evidence on all the genetic determinants implicated in COVID-19 to date, and provides evidence of correlation between the above polymorphisms with COVID-19 susceptibility and severity.

Association of and polymorphisms with sarcoidosis in a Greek patient cohort

INTRODUCTION

Sarcoidosis is a disease that results from a combination of environmental and genetic factors. Its genetic basis however, is yet to be clarified. The purpose of this study is to determine whether single nucleotide polymorphisms (SNPs) of the B-cell activating factor (BAFF) and its receptor (BAFF-R) are associated with sarcoidosis.

MATERIAL AND METHODS

Blood samples from one hundred and seventy-three sarcoidosis patients and one hundred and sixty-four controls were collected. All samples were genotyped for BAFF rs2893321, rs1041569 and rs9514828, and for BAFF-R rs61756766.

RESULTS

Out of the three BAFF polymorphisms, none genotype had any significant association with sarcoidosis, although the T allele in rs1041569 and rs9514828 was overrepresented in sarcoidosis patients. A marginally significant association with sarcoidosis was found in the case of the CT genotype and T allele of BAFF-R rs61756766. Haplotype analysis of the BAFF polymorphisms was also performed, revealing an overrepresentation of the ATT, GTA and GTT haplotypes in the group of patients with cardiac involvement.

CONCLUSIONS

Taken together, the results of this study suggest a possible relationship between BAFF SNPs, rs1041569 and rs9514828, and BAFF-R SNP rs61756766 with sarcoidosis susceptibility and their potential as biomarkers for the disease.

Genetics of COVID-19 and myalgic encephalomyelitis/chronic fatigue syndrome: a systematic review

COVID‐19 and ME/CFS present with some similar symptoms, especially physical and mental fatigue. In order to understand the basis of these similarities and the possibility of underlying common genetic components, we performed a systematic review of all published genetic association and cohort studies regarding COVID‐19 and ME/CFS and extracted the genes along with the genetic variants investigated. We then performed gene ontology and pathway analysis of those genes that gave significant results in the individual studies to yield functional annotations of the studied genes using protein analysis through evolutionary relationships (PANTHER) VERSION 17.0 software. Finally, we identified the common genetic components of these two conditions. Seventy‐one studies for COVID‐19 and 26 studies for ME/CFS were included in the systematic review in which the expression of 97 genes for COVID‐19 and 429 genes for ME/CFS were significantly affected. We found that ACE, HLA‐A, HLA‐C, HLA‐DQA1, HLA‐DRB1, and TYK2 are the common genes that gave significant results. The findings of the pathway analysis highlight the contribution of inflammation mediated by chemokine and cytokine signaling pathways, and the T cell activation and Toll receptor signaling pathways. Protein class analysis revealed the contribution of defense/immunity proteins, as well as protein‐modifying enzymes. Our results suggest that the pathogenesis of both syndromes could involve some immune dysfunction.

COVID-19: impact on Public Health and hypothesis-driven investigations on genetic susceptibility and severity

COVID-19 is a new complex multisystem disease caused by the novel coronavirus SARS-CoV-2. In slightly over 2 years, it infected nearly 500 million and killed 6 million human beings worldwide, causing an unprecedented coronavirus pandemic. Currently, the international scientific community is engaged in elucidating the molecular mechanisms of the pathophysiology of SARS-CoV-2 infection as a basis of scientific developments for the future control of COVID-19. Global exome and genome analysis efforts work to define the human genetics of protective immunity to SARS-CoV-2 infection. Here, we review the current knowledge regarding the SARS-CoV-2 infection, the implications of COVID-19 to Public Health and discuss genotype to phenotype association approaches that could be exploited through the selection of candidate genes to identify the genetic determinants of severe COVID-19.

Germline rare variants of lectin pathway genes predispose to asymptomatic SARS-CoV-2 infection in elderly individuals

PURPOSE

Emerging evidence suggest that infection-dependent hyperactivation of complement system (CS) may worsen COVID-19 outcome. We investigated the role of predicted high impact rare variants - referred as qualifying variants (QVs) - of CS genes in predisposing asymptomatic COVID-19 in elderly individuals, known to be more susceptible to severe disease.

METHODS

Exploiting exome sequencing data and 56 CS genes, we performed a gene-based collapsing test between 164 asymptomatic subjects (aged ≥60 years) and 56,885 European individuals from the Genome Aggregation Database. We replicated this test comparing the same asymptomatic individuals with 147 hospitalized patients with COVID-19.

RESULTS

We found an enrichment of QVs in 3 genes (MASP1, COLEC11, and COLEC10), which belong to the lectin pathway, in the asymptomatic cohort. Analyses of complement activity in serum showed decreased activity of lectin pathway in asymptomatic individuals with QVs. Finally, we found allelic variants associated with asymptomatic COVID-19 phenotype and with a decreased expression of MASP1, COLEC11, and COLEC10 in lung tissue.

CONCLUSION

This study suggests that genetic rare variants can protect from severe COVID-19 by mitigating the activity of lectin pathway and prothrombin. The genetic data obtained through ES of 786 asymptomatic and 147 hospitalized individuals are publicly available at http://espocovid.ceinge.unina.it/.

Genetic polymorphisms associated with susceptibility to COVID-19 disease and severity: A systematic review and meta-analysis

Although advanced age and presence of comorbidities significantly impact the variation observed in the clinical symptoms of COVID-19, it has been suggested that genetic variants may also be involved in the disease. Thus, the aim of this study was to perform a systematic review with meta-analysis of the literature to identify genetic polymorphisms that are likely to contribute to COVID-19 pathogenesis. Pubmed, Embase and GWAS Catalog repositories were systematically searched to retrieve articles that investigated associations between polymorphisms and COVID-19. For polymorphisms analyzed in 3 or more studies, pooled OR with 95% CI were calculated using random or fixed effect models in the Stata Software. Sixty-four eligible articles were included in this review. In total, 8 polymorphisms in 7 candidate genes and 74 alleles of the HLA loci were analyzed in 3 or more studies. The HLA-A*30 and CCR5 rs333Del alleles were associated with protection against COVID-19 infection, while the APOE rs429358C allele was associated with risk for this disease. Regarding COVID-19 severity, the HLA-A*33, ACE1 Ins, and TMPRSS2 rs12329760T alleles were associated with protection against severe forms, while the HLA-B*38, HLA-C*6, and ApoE rs429358C alleles were associated with risk for severe forms of COVID-19. In conclusion, polymorphisms in the ApoE, ACE1, TMPRSS2, CCR5, and HLA loci appear to be involved in the susceptibility to and/or severity of COVID-19.

The association of COVID-19 severity and susceptibility and genetic risk factors: A systematic review of the literature

Background

COVID-19 is associated with several risk factors such as distinct ethnicities (genetic ancestry), races, sexes, age, pre-existing comorbidities, smoking, and genetics. The authors aim to evaluate the correlation between variability in the host genetics and the severity and susceptibility towards COVID-19 in this study.

Methods

Following the PRISMA guidelines, we retrieved all the relevant articles published until September 15, 2021, from two online databases: PubMed and Scopus.

Findings

High-risk HLA haplotypes, higher expression of ACE polymorphisms, and several genes of cellular proteases such as TMPRSS2, FURIN, TLL-1 increase the risk of susceptibility and severity of COVID-19. In addition, upregulation of several genes encoding for both innate and acquired immune systems proteins, mainly CCR5, IFNs, TLR, DPPs, and TNF, positively correlate with COVID-19 severity. However, reduced expression or polymorphisms in genes affecting TLR and IFNλ increase COVID-19 severity.

Conclusion

Higher expression, polymorphisms, mutations, and deletions of several genes are linked with the susceptibility, severity, and clinical outcomes of COVID-19. Early treatment and vaccination of individuals with genetic predisposition could help minimize the severity and mortality associated with COVID-19.