Regulatory Noncoding and Predicted Pathogenic Coding Variants of CCR5 Predispose to Severe COVID-19

Special Issue "Molecular and Genetic Aspects of SARS-CoV-2 Infection and COVID-19 Disease"

We are pleased to present the first and second editions of this Special Issue, titled "Molecular and Genetic Aspects of SARS-CoV-2 Infection and COVID-19 Disease", of the International Journal of Molecular Sciences [...].

Host Genetic Impact on Infectious Diseases among Different Ethnic Groups

Infectious diseases such as malaria, tuberculosis (TB), human immunodeficiency virus (HIV), and the coronavirus disease of 2019 (COVID-19) are problematic globally, with high prevalence particularly in Africa, attributing to most of the death rates. There have been immense efforts toward developing effective preventative and therapeutic strategies for these pathogens globally, however, some remain uncured. Disease susceptibility and progression for malaria, TB, HIV, and COVID-19 vary among individuals and are attributed to precautionary measures, environment, host, and pathogen genetics. While studying individuals with similar attributes, it is suggested that host genetics contributes to most of an individual's susceptibility to disease. Several host genes are identified to associate with these pathogens. Interestingly, many of these genes and polymorphisms are common across diseases. This paper analyzes genes and genetic variations within host genes associated with HIV, TB, malaria, and COVID-19 among different ethnic groups. The differences in host-pathogen interaction among these groups, particularly of Caucasian and African descent, and which gene polymorphisms are prevalent in an African population that possesses protection or risk to disease are reviewed. The information in this review could potentially help develop personalized treatment that could effectively combat the high disease burden in Africa.

Adverse effect of VEGFR-2 (rs1870377) polymorphism on the clinical course of COVID-19 in females and males in an age-dependent manner

The COVID-19 pandemic has affected people worldwide with varying clinical presentations ranging from mild to severe or fatal, and studies have found that age, gender, and some comorbidities can influence the severity of the disease. It would be valuable to have genetic markers that might help predict the likely outcome of infection. For this objective, genes encoding VEGFR-2 (rs1870377), CCR5Δ32 (rs333), and TLR3 (rs5743313) were analyzed for polymorphisms in the peripheral blood of 160 COVID-19 patients before COVID-19 vaccine was available in Türkiye. We observed that possession of the VEGFR-2 rs1870377 mutant allele increased the risk of severe/moderate disease in females and subjects ≥65 years of age, but was protective in males <65 years of age. Other significant results were that the CCR5Δ32 allele was protective against severe disease in subjects ≥65 years of age, while TLR3 rs5743313 polymorphism was found to be protective against severe/moderate illness in males <65 years of age. The VEGFR-2 rs1870377 mutant allele was a risk factor for severe/moderate disease, particularly in females over the age of 65. These findings suggest that genetic polymorphisms have an age- and sex-dependent influence on the severity of COVID-19, and the VEGFR-2 rs1870377 mutant allele could be a potential predictor of disease severity.

Evaluation and limitations of different approaches among COVID-19 fatal cases using whole-exome sequencing data

BACKGROUND

COVID-19 caused by the SARS-CoV-2 infection may result in various disease symptoms and severity, ranging from asymptomatic, through mildly symptomatic, up to very severe and even fatal cases. Although environmental, clinical, and social factors play important roles in both susceptibility to the SARS-CoV-2 infection and progress of COVID-19 disease, it is becoming evident that both pathogen and host genetic factors are important too. In this study, we report findings from whole-exome sequencing (WES) of 27 individuals who died due to COVID-19, especially focusing on frequencies of DNA variants in genes previously associated with the SARS-CoV-2 infection and the severity of COVID-19.

RESULTS

We selected the risk DNA variants/alleles or target genes using four different approaches: 1) aggregated GWAS results from the GWAS Catalog; 2) selected publications from PubMed; 3) the aggregated results of the Host Genetics Initiative database; and 4) a commercial DNA variant annotation/interpretation tool providing its own knowledgebase. We divided these variants/genes into those reported to influence the susceptibility to the SARS-CoV-2 infection and those influencing the severity of COVID-19. Based on the above, we compared the frequencies of alleles found in the fatal COVID-19 cases to the frequencies identified in two population control datasets (non-Finnish European population from the gnomAD database and genomic frequencies specific for the Slovak population from our own database). When compared to both control population datasets, our analyses indicated a trend of higher frequencies of severe COVID-19 associated risk alleles among fatal COVID-19 cases. This trend reached statistical significance specifically when using the HGI-derived variant list. We also analysed other approaches to WES data evaluation, demonstrating its utility as well as limitations.

CONCLUSIONS

Although our results proved the likely involvement of host genetic factors pointed out by previous studies looking into severity of COVID-19 disease, careful considerations of the molecular-testing strategies and the evaluated genomic positions may have a strong impact on the utility of genomic testing.

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.

Naming the Barriers between Anti-CCR5 Therapy, Breast Cancer and Its Microenvironment

Breast cancer represents the most common malignancy among women in the world. Although immuno-, chemo- and radiation therapy are widely recognized as the therapeutic trifecta, new strategies in the fight against breast cancer are continually explored. The local microenvironment around the tumor plays a great role in cancer progression and invasion, representing a promising therapeutic target. CCL5 is a potent chemokine with a physiological role of immune cell attraction and has gained particular attention in R&D for breast cancer treatment. Its receptor, CCR5, is a well-known co-factor for HIV entry through the cell membrane. Interestingly, biology research is unusually unified in describing CCL5 as a pro-oncogenic factor, especially in breast cancer. In silico, in vitro and in vivo studies blocking the CCL5/CCR5 axis show cancer cells become less invasive and less malignant, and the extracellular matrices produced are less oncogenic. At present, CCR5 blocking is a mainstay of HIV treatment, but despite its promising role in cancer treatment, CCR5 blocking in breast cancer remains unperformed. This review presents the role of the CCL5/CCR5 axis and its effector mechanisms, and names the most prominent hurdles for the clinical adoption of anti-CCR5 drugs in cancer.

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.

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.

DeepLUCIA: predicting tissue-specific chromatin loops using Deep Learning-based Universal Chromatin Interaction Annotator

MOTIVATION

The importance of chromatin loops in gene regulation is broadly accepted. There are mainly two approaches to predict chromatin loops: transcription factor (TF) binding-dependent approach and genomic variation-based approach. However, neither of these approaches provides an adequate understanding of gene regulation in human tissues. To address this issue, we developed a deep learning-based chromatin loop prediction model called DeepLUCIA (Deep Learning-based Universal Chromatin Interaction Annotator).

RESULTS

Although DeepLUCIA does not use TF binding profile data which previous TF binding-dependent methods critically rely on, its prediction accuracies are comparable to those of the previous TF binding-dependent methods. More importantly, DeepLUCIA enables the tissue-specific chromatin loop predictions from tissue-specific epigenomes that cannot be handled by genomic variation-based approach. We demonstrated the utility of the DeepLUCIA by predicting several novel target genes of SNPs identified in genome-wide association studies targeting Brugada syndrome, COVID-19 severity, and age-related macular degeneration.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Severe COVID-19 represents an undiagnosed primary immunodeficiency in a high proportion of infected individuals

Since the emergence of the COVID-19 pandemic in early 2020, a key challenge has been to define risk factors, other than age and pre-existing comorbidities, that predispose some people to severe disease, while many other SARS-CoV-2-infected individuals experience mild, if any, consequences. One explanation for intra-individual differences in susceptibility to severe COVID-19 may be that a growing percentage of otherwise healthy people have a pre-existing asymptomatic primary immunodeficiency (PID) that is unmasked by SARS-CoV-2 infection. Germline genetic defects have been identified in individuals with life-threatening COVID-19 that compromise local type I interferon (IFN)-mediated innate immune responses to SARS-CoV-2. Remarkably, these variants - which impact responses initiated through TLR3 and TLR7, as well as the response to type I IFN cytokines - may account for between 3% and 5% of severe COVID-19 in people under 70 years of age. Similarly, autoantibodies against type I IFN cytokines (IFN-α, IFN-ω) have been detected in patients' serum prior to infection with SARS-CoV-2 and were found to cause c. 20% of severe COVID-19 in the above 70s and 20% of total COVID-19 deaths. These autoantibodies, which are more common in the elderly, neutralise type I IFNs, thereby impeding innate antiviral immunity and phenocopying an inborn error of immunity. The discovery of PIDs underlying a significant percentage of severe COVID-19 may go some way to explain disease susceptibility, may allow for the application of targeted therapies such as plasma exchange, IFN-α or IFN-β, and may facilitate better management of social distancing, vaccination and early post-exposure prophylaxis.