A systematic review on papers that study on Single Nucleotide Polymorphism that affects coronavirus 2019 severity

Next-generation sequencing of host genetics risk factors associated with COVID-19 severity and long-COVID in Colombian population

Coronavirus disease 2019 (COVID-19) was considered a major public health burden worldwide. Multiple studies have shown that susceptibility to severe infections and the development of long-term symptoms is significantly influenced by viral and host factors. These findings have highlighted the potential of host genetic markers to identify high-risk individuals and develop target interventions to reduce morbimortality. Despite its importance, genetic host factors remain largely understudied in Latin-American populations. Using a case-control design and a custom next-generation sequencing (NGS) panel encompassing 81 genetic variants and 74 genes previously associated with COVID-19 severity and long-COVID, we analyzed 56 individuals with asymptomatic or mild COVID-19 and 56 severe and critical cases. In agreement with previous studies, our results support the association between several clinical variables, including male sex, obesity and common symptoms like cough and dyspnea, and severe COVID-19. Remarkably, thirteen genetic variants showed an association with COVID-19 severity. Among these variants, rs11385942 (p < 0.01; OR = 10.88; 95% CI = 1.36-86.51) located in the LZTFL1 gene, and rs35775079 (p = 0.02; OR = 8.53; 95% CI = 1.05-69.45) located in CCR3 showed the strongest associations. Various respiratory and systemic symptoms, along with the rs8178521 variant (p < 0.01; OR = 2.51; 95% CI = 1.27-4.94) in the IL10RB gene, were significantly associated with the presence of long-COVID. The results of the predictive model comparison showed that the mixed model, which incorporates genetic and non-genetic variables, outperforms clinical and genetic models. To our knowledge, this is the first study in Colombia and Latin-America proposing a predictive model for COVID-19 severity and long-COVID based on genomic analysis. Our study highlights the usefulness of genomic approaches to studying host genetic risk factors in specific populations. The methodology used allowed us to validate several genetic variants previously associated with COVID-19 severity and long-COVID. Finally, the integrated model illustrates the importance of considering genetic factors in precision medicine of infectious diseases.

CRISPR-powered optothermal nanotweezers: Diverse bio-nanoparticle manipulation and single nucleotide identification

Optothermal nanotweezers have emerged as an innovative optical manipulation technique in the past decade, which revolutionized classical optical manipulation by efficiently capturing a broader range of nanoparticles. However, the optothermal temperature field was merely employed for in-situ manipulation of nanoparticles, its potential for identifying bio-nanoparticles remains largely untapped. Hence, based on the synergistic effect of optothermal manipulation and CRIPSR-based bio-detection, we developed CRISPR-powered optothermal nanotweezers (CRONT). Specifically, by harnessing diffusiophoresis and thermo-osmotic flows near the substrate upon optothermal excitation, we successfully trapped and enriched DNA functionalized gold nanoparticles, CRISPR-associated proteins, as well as DNA strands. Remarkably, we built an optothermal scheme for enhancing CRISPR-based single-nucleotide polymorphism (SNP) detection at single molecule level, while also introducing a novel CRISPR methodology for observing nucleotide cleavage. Therefore, this innovative approach has endowed optical tweezers with DNA identification ability in aqueous solution which was unattainable before. With its high specificity and feasibility for in-situ bio-nanoparticle manipulation and identification, CRONT will become a universal tool in point-of-care diagnosis, biophotonics, and bio-nanotechnology.

The Single-Nucleotide Polymorphism (SNP) Validity to Detect Omicron Variants

Introduction

Mutation of SARS-CoV-2 has generated several variants of concern (VOC) which spread promptly worldwide. These emerging variants affected global strategies to overcome COVID-19. Variants of SARS-CoV-2 are determined by the whole genome sequencing (WGS) assay, which is time-consuming, with limited availability (only in several laboratories). Hence, a faster and more accessible examination is needed. The single-nucleotide polymorphism (SNP) method is one of the options for genomic variation surveillance that can help provide an answer to this challenge. This study aims to determine the validity of the SNP method with PCR to detect omicron variants of SARS-CoV-2 compared with the gold standard, WGS.

Methods

This is a diagnostic analysis of 140 confirmed COVID-19 nasopharyngeal samples taken from the Kemayoran COVID Emergency Hospital Laboratory and the West Java Provincial Health Laboratory from April to October 2022. Data analysis was carried out to determine conformity and validity values.

Results

Analysis using Cohen's kappa coefficient test showed high conformity between SNP and WGS (p value <0.001; kappa coefficient = 0.948). SNP showed great validity values on omicron BA.1 (90% sensitivity; 100% specificity), omicron BA.2 (100% sensitivity; 99% specificity), and omicron BA.4/5 (99.2% sensitivity; 100% specificity).

Conclusion

The SNP method can be a more time-efficient alternative to detect omicron variants of SARS-CoV-2 and distinguish their sublineages (BA.1, BA.2, and BA.4/5) by two different specific gene mutations in combination analysis (ΔH69/V70 and Q493R mutations).

Lack of Evidence for a Role of ACE-2 Polymorphisms as a Bedside Clinical Prognostic Marker of COVID-19

The novel SARS-CoV-2 coronavirus causes a severe respiratory syndrome referred to as coronavirus disease (COVID-19). The angiotensin-converting enzyme 2 (ACE-2) plays an important role as a cellular receptor for SARS-CoV-2 and is largely expressed in lungs, kidneys, heart and the gastrointestinal tract along with being shed in plasma. The ACE-2 gene and protein show a high level of genetic polymorphism, including simple nucleotide variation, transcriptional variation, post-transcriptional changes, and putative protein mutations that could interfere with the binding or entry of SARS-CoV-2 and affect tissue damage in lungs or other organs. Genetic polymorphisms can impact SARS-CoV-2 viral entry and COVID-19 severity. This single-center study evaluated the possible role of the main ACE-2 polymorphisms (rs143936283, rs2285666, rs41303171, rs35803318, and rs2106809) as potential prognostic markers in SARS-CoV-2-infected individuals. Frozen whole blood was used for DNA isolation and genomic DNA samples were sheared using the Covaris LE220 Focused-ultrasonicator for targeting a peak size of 410 bp. Whole-genome sequencing libraries were generated from fragmented DNA using the Illumina TruSeq DNA PCR-Free HT Library Preparation Kit and sequenced on an Illumina NovaSeq 6000. We did not identify any correlation between ACE-2 polymorphisms and COVID-19 prognosis, suggesting that the interpretation and clinical use of ACE-2 genetic polymorphisms in real-world clinical settings requires further experimental and clinical validation.

IFITM3 rs12252 polymorphism and coronavirus disease 2019 severity: A meta‑analysis

Interferon-induced transmembrane protein 3 (IFITM3) serves a critical role in the immune defense against viral infection, including that of severe acute respiratory syndrome coronavirus 2. To the best of our knowledge, the association between IFITM3 rs12252 polymorphism and coronavirus disease 2019 (COVID-19) severity has not been determined. In the present study, a meta-analysis of published case-control studies assessing the association between the IFITM3 rs12252 polymorphism and COVID-19 severity was performed. PubMed, EMBASE, China National Knowledge Infrastructure, Wanfang and preprint servers were searched up to March 30, 2022. A fixed-effect model was used to calculate odds ratio (OR) and 95% confidence interval (95% CI). Analyses were conducted for additive, dominant and recessive genetic models. A total of five studies were identified, with 1,443 mild-to-moderate cases and 667 severe cases, including 121 deaths. Overall, the CC genotype of IFITM3 rs12252 was associated with increased risk of severe COVID-19 (OR=1.97, 95% CI, 1.06-3.69) and mortality (OR=4.61, 95% CI, 1.44-14.75) compared with the CT/TT genotypes. Stratified analysis by ethnicity revealed that this association was strong in Chinese individuals (severity, OR=2.84, 95% CI, 1.34-6.04; mortality, OR=7.91, 95% CI, 1.29-48.44), but not notable in Caucasians (severity, OR=0.79, 95% CI, 0.23-2.80; mortality, OR=2.16, 95% CI, 0.37-12.55). A significant association with mortality was observed in Caucasians when comparing patients with the C allele of IFITM3 rs12252 and those without (CC/CT vs. TT: OR=1.73, 95% CI, 1.09-2.75). The results suggested that the IFTM3-rs12252 CC genotype is associated with severe COVID-19 and mortality in Chinese individuals and the IFTM3-rs12252 C allele may be associated with COVID-19 mortality in Caucasians. Large-scale studies are needed to confirm the association in different global populations.

Relevance of HLA-DP/DQ and INF-λ4 Polymorphisms to COVID-19 Outcomes

Background: Single nucleotide polymorphisms provide information on individuals' potential reactions to environmental factors, infections, diseases, as well as various therapies. A study on SNPs that influence SARS-CoV-2 susceptibility and severity may provide a predictive tool for COVID-19 outcomes and improve the customized coronavirus treatment. Aim: To evaluate the role of human leukocyte antigens DP/DQ and IFNλ4 polymorphisms on COVID-19 outcomes among Egyptian patients. Participants and Methods: The study involved 80 patients with severe COVID-19, 80 patients with mild COVID-19, and 80 non-infected healthy volunteers. Genotyping and allelic discrimination of HLA-DPrs3077 (G/A), HLA-DQrs7453920 (A/G), and IFNλ4 rs73555604 (C/T) SNPs were performed using real-time PCR. Results: Ages were 47.9 ± 8, 44.1 ± 12.1, and 45.8 ± 10 years in severe, mild and non-infected persons. There was a statistically significant association between severe COVID-19 and male gender (p = 0.002). A statistically significant increase in the frequency of HLA-DPrs3077G, HLA-DQrs7453920A, and IFNλ4rs73555604C alleles among severe COVID-19 patients when compared with other groups (p < 0.001). Coexistence of these alleles in the same individual increases the susceptibility to severe COVID-19 by many folds (p < 0.001). Univariate and multivariate logistic regression analysis for the studied parameters showed that old age, male gender, non-vaccination, HLA-DQ rs7453920AG+AA, HLA-DPrs3077GA+GG, and IFNλ4rs73555604CT+CC genotypes are independent risk factors for severe COVID-19 among Egyptian patients. Conclusion: HLA-DQ rs7453920A, HLA-DPrs3077G, and IFNλ4rs73555604C alleles could be used as markers of COVID-19 severity.

Endogenous G-quadruplex-forming RNAs inhibit the activity of SARS-CoV-2 RNA polymerase

Replication of RNA viruses is catalysed by virus-specific polymerases, which can be targets of therapeutic strategies. In this study, we used a selection strategy to identify endogenous RNAs from a transcriptome library derived from lung cells that interact with the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. Some of the selected RNAs weakened the activity of RdRp by forming G-quadruplexes. These results suggest that certain endogenous RNAs, which potentially form G-quadruplexes, can reduce the replication of viral RNAs.

Interleukin-38 promoter variants and risk of COVID-19 among Iraqis

Coronavirus disease-19 (COVID-19) has recently emerged as a respiratory infection with a significant impact on health and society. The pathogenesis is primarily attributed to a dysregulation of cytokines, especially those with pro-inflammatory and anti-inflammatory effects. Interleukin-38 (IL-38) is a recently identified anti-inflammatory cytokine with a proposed involvement in mediating COVID-19 pathogenesis, while the association between IL38 gene variants and disease susceptibility has not been explored. Therefore, a pilot study was designed to evaluate the association of three gene variants in the promoter region of IL38 gene (rs7599662 T/A/C/G, rs28992497 T/C and rs28992498 C/A/T) with COVID-19 risk. DNA sequencing was performed to identify these variants. The study included 148 Iraqi patients with COVID-19 and 113 healthy controls (HC). Only rs7599662 showed a significant negative association with susceptibility to COVID-19. The mutant T allele was presented at a significantly lower frequency in patients compared to HC. Analysis of recessive, dominant and codominant models demonstrated that rs7599662 TT genotype frequency was significantly lower in patients than in HC. In terms of haplotypes (in order: rs7599662, rs28992497 and rs28992498), frequency of CTC haplotype was significantly increased in patients compared to HC, while TTC haplotype showed significantly lower frequency in patients. The three SNPs influenced serum IL-38 levels and homozygous genotypes of mutant alleles were associated with elevated levels. In conclusion, this study indicated that IL38 gene in terms of promoter variants and haplotypes may have important implications for COVID-19 risk.

Global distribution of ACE1 (rs4646994) and ACE2 (rs2285666) polymorphisms associated with COVID-19: A systematic review and meta-analysis

BACKGROUND

Recent studies emphasize the significant impact of the renin-angiotensin aldosterone system (RAAS) as a risk factor associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, according to the literature, the effect of rs4646994 and rs2285666 polymorphisms on susceptibility and progression to severe clinical outcomes is still controversial. Our aim was to investigate the effect of polymorphisms such as rs4646994 and rs2285666 on susceptibility to coronavirus disease-2019 (COVID-19).

METHODS

We conducted a comprehensive literature search using databases such as ISI Web of Science, PubMed, Scopus, and Google Scholar to retrieve studies on the effect of two polymorphisms (rs4646994 and rs2285666) of the angiotensin-converting enzyme (ACE) gene on COVID-19. Finally, the effect of each polymorphism on SARS-CoV-2 infection was measured based on the odds ratio with 95% confidence intervals.

RESULTS

Analysis of the rs4646994 polymorphism showed that the frequency of the D allele in patients infected with COVID-19 was higher than that the I allele. Moreover, the authors found that the DD genotype increased the risk of severe disease by 1.7-fold in Asian population, whereas, this was not the case in the Western population. However, the rs4646994 II genotype plays a protective role against COVID-19 in Western countries. In the case of the rs2285666 polymorphism based on patient ethnicity, the C allele had the highest frequency. Interestingly, in people harboring the GG and TT genotypes, the risk of progression to severe disease significantly increased, while people with genotypes such as GA, AA and CC seem to be more resistant to severe Covid-19.

CONCLUSIONS

Based on geographical region, the rs4646994 DD genotype may be considered as a predictive biomarker to identify the susceptibility of human to SARS-CoV-2 infection and severe COVID-19 outcomes. We also concluded that individuals with GG and TT genotypes are significantly more susceptible to severe outcomes of disease, while conversely, individuals with GA, AA, and CC genotypes are less susceptible to severe COVID-19.

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.

Contrasting Epidemiology and Population Genetics of COVID-19 Infections Defined by Multilocus Genotypes in SARS-CoV-2 Genomes Sampled Globally

Since its emergence in 2019, SARS-CoV-2 has spread and evolved globally, with newly emerged variants of concern (VOCs) accounting for more than 500 million COVID-19 cases and 6 million deaths. Continuous surveillance utilizing simple genetic tools is needed to measure the viral epidemiological diversity, risk of infection, and distribution among different demographics in different geographical regions. To help address this need, we developed a proof-of-concept multilocus genotyping tool and demonstrated its utility to monitor viral populations sampled in 2020 and 2021 across six continents. We sampled globally 22,164 SARS-CoV-2 genomes from GISAID (inclusion criteria: available clinical and demographic data). They comprised two study populations, “2020 genomes” (N = 5959) sampled from December 2019 to September 2020 and “2021 genomes” (N = 16,205) sampled from 15 January to 15 March 2021. All genomes were aligned to the SARS-CoV-2 reference genome and amino acid polymorphisms were called with quality filtering. Thereafter, 74 codons (loci) in 14 genes including orf1ab polygene (N = 9), orf3a, orf8, nucleocapsid (N), matrix (M), and spike (S) met the 0.01 minimum allele frequency criteria and were selected to construct multilocus genotypes (MLGs) for the genomes. At these loci, 137 mutant/variant amino acids (alleles) were detected with eight VOC-defining variant alleles, including N KR203&204, orf1ab (I265, F3606, and L4715), orf3a H57, orf8 S84, and S G614, being predominant globally with > 35% prevalence. Their persistence and selection were associated with peaks in the viral transmission and COVID-19 incidence between 2020 and 2021. Epidemiologically, older patients (≥20 years) compared to younger patients (<20 years) had a higher risk of being infected with these variants, but this association was dependent on the continent of origin. In the global population, the discriminant analysis of principal components (DAPC) showed contrasting patterns of genetic clustering with three (Africa, Asia, and North America) and two (North and South America) continental clusters being observed for the 2020 and 2021 global populations, respectively. Within each continent, the MLG repertoires (range 40−199) sampled in 2020 and 2021 were genetically differentiated, with ≤4 MLGs per repertoire accounting for the majority of genomes sampled. These data suggested that the majority of SARS-CoV-2 infections in 2020 and 2021 were caused by genetically distinct variants that likely adapted to local populations. Indeed, four GISAID clade-defined VOCs - GRY (Alpha), GH (Beta), GR (Gamma), and G/GK (Delta variant) were differentiated by their MLG signatures, demonstrating the versatility of the MLG tool for variant identification. Results from this proof-of-concept multilocus genotyping demonstrates its utility for SARS-CoV-2 genomic surveillance and for monitoring its spatiotemporal epidemiology and evolution, particularly in response to control interventions including COVID-19 vaccines and chemotherapies.

T Cell Epitope Discovery in the Context of Distinct and Unique Indigenous HLA Profiles

CD8+ T cells are a pivotal part of the immune response to viruses, playing a key role in disease outcome and providing long-lasting immunity to conserved pathogen epitopes. Understanding CD8+ T cell immunity in humans is complex due to CD8+ T cell restriction by highly polymorphic Human Leukocyte Antigen (HLA) proteins, requiring T cell epitopes to be defined for different HLA allotypes across different ethnicities. Here we evaluate strategies that have been developed to facilitate epitope identification and study immunogenic T cell responses. We describe an immunopeptidomics approach to sequence HLA-bound peptides presented on virus-infected cells by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Using antigen presenting cell lines that stably express the HLA alleles characteristic of Indigenous Australians, this approach has been successfully used to comprehensively identify influenza-specific CD8+ T cell epitopes restricted by HLA allotypes predominant in Indigenous Australians, including HLA-A*24:02 and HLA-A*11:01. This is an essential step in ensuring high vaccine coverage and efficacy in Indigenous populations globally, known to be at high risk from influenza disease and other respiratory infections.

Identification of Genetic Risk Factors of Severe COVID-19 Using Extensive Phenotypic Data: A Proof-of-Concept Study in a Cohort of Russian Patients

The COVID-19 pandemic has drawn the attention of many researchers to the interaction between pathogen and host genomes. Over the last two years, numerous studies have been conducted to identify the genetic risk factors that predict COVID-19 severity and outcome. However, such an analysis might be complicated in cohorts of limited size and/or in case of limited breadth of genome coverage. In this work, we tried to circumvent these challenges by searching for candidate genes and genetic variants associated with a variety of quantitative and binary traits in a cohort of 840 COVID-19 patients from Russia. While we found no gene- or pathway-level associations with the disease severity and outcome, we discovered eleven independent candidate loci associated with quantitative traits in COVID-19 patients. Out of these, the most significant associations correspond to rs1651553 in MYH14p = 1.4 × 10^-7), rs11243705 in SETX (p = 8.2 × 10^-6), and rs16885 in ATXN1 (p = 1.3 × 10^-5). One of the identified variants, rs33985936 in SCN11A, was successfully replicated in an independent study, and three of the variants were found to be associated with blood-related quantitative traits according to the UK Biobank data (rs33985936 in SCN11A, rs16885 in ATXN1, and rs4747194 in CDH23). Moreover, we show that a risk score based on these variants can predict the severity and outcome of hospitalization in our cohort of patients. Given these findings, we believe that our work may serve as proof-of-concept study demonstrating the utility of quantitative traits and extensive phenotyping for identification of genetic risk factors of severe COVID-19.

The Role of Genetic Factors in the Development of Acute Respiratory Viral Infection COVID-19: Predicting Severe Course and Outcomes

The aim of this study was to identify single nucleotide variants in genes associated with susceptibility to or severe outcomes of COVID-19. A total of 319 genomic DNA samples from patients with varying degrees of disease severity and 78 control DNA samples from people who had regular or prolonged contact with patients with COVID-19 but did not have clinical manifestations and/or antibodies to SARS-CoV-2. Seven SNPs were identified that were statistically associated with disease risk or severe course, rs1799864 in the CCR2 gene (OR = 2.21), rs1990760 in the IFIH1 gene (OR = 2.41), rs1800629 in the TNF gene (OR = 1.98), rs75603675 in the TMPRSS2 gene (OR = 1.86), rs7842 in the C3AR1 gene (OR = 2.08), rs179008 in the gene TLR7 (OR = 1.85), rs324011 in the C3AR1 gene (OR = 2.08), rs179008 in the TLR7 gene (OR = 1.85), and rs324011 in the STAT6 gene (OR = 1.84), as well as two variants associated with protection from COVID-19, rs744166 in the STAT3 gene (OR = 0.36) and rs1898830 in the TLR2 gene (OR = 0.47). The genotype in the region of these markers can be the criterion of the therapeutic approach for patients with COVID-19.