Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data

The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank

Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits. These GWAS have discovered many genetic variants seemingly protective from disease and are often different from disease-associated variants (i.e., they are not just alternative alleles at disease-associated loci) and suggest that many health-positive traits also have a polygenic basis. This observation has led to an interest in "polygenic longevity scores (PLS)" that quantify the "risk" or genetic predisposition of an individual towards health. We derived 11 different PLS from 4 different available GWAS on lifespan and then investigated the properties of these PLS using data from the UK Biobank (UKB). Tests of association between the PLS and population structure, parental lifespan, and several cancerous and non-cancerous diseases, including death from COVID-19, were performed. Based on the results of our analyses, we argue that PLS are made up of variants not only robustly associated with parental lifespan, but that also contribute to the genetic architecture of disease susceptibility, morbidity, and mortality.

Correlation between Genomic Variants and Worldwide COVID-19 Epidemiology

COVID-19 is a systemic disease caused by the etiologic agent SARS-CoV-2, first reported in Hubei Province in Wuhan, China, in late 2019. The SARS-CoV-2 virus has evolved over time with distinct transmissibility subvariants from ancestral lineages. The clinical manifestations of the disease vary according to their severity and can range from asymptomatic to severe. Due to the rapid evolution to a pandemic, epidemiological studies have become essential to understand and effectively combat COVID-19, as the incidence and mortality of this disease vary between territories and populations. This study correlated epidemiological data on the incidence and mortality of COVID-19 with frequencies of important SNPs in GWAS studies associated with the susceptibility and mortality of this disease in different populations. Our results indicated significant correlations for 11 genetic variants (rs117169628, rs2547438, rs2271616, rs12610495, rs12046291, rs35705950, rs2176724, rs10774671, rs1073165, rs4804803 and rs7528026). Of these 11 variants, 7 (rs12046291, rs117169628, rs1073165, rs2547438, rs2271616, rs12610495 and rs35705950) were positively correlated with the incidence rate, these variants were more frequent in EUR populations, suggesting that this population is more susceptible to COVID-19. The rs2176724 variant was inversely related to incidence rates; therefore, the higher the frequency of the allele is, the lower the incidence rate. This variant was more frequent in the AFR population, which suggests a protective factor against SARS-CoV-2 infection in this population. The variants rs10774671, rs4804803, and rs7528026 showed a significant relationship with mortality rates. SNPs rs10774671 and rs4804803 were inversely related to mortality rates and are more frequently present in the AFR population. The rs7528026 variant, which is more frequent in the AMR population, was positively related to mortality rates. The study has the potential to identify and correlate the genetic profile with epidemiological data, identify populations that are more susceptible to severe forms of COVID-19, and relate them to incidence and mortality.

Predictors of mortality in hospitalised patients with COVID-19: a 1-year case-control study

BACKGROUND

A paucity of predictive models assessing risk factors for COVID-19 mortality that extend beyond age and gender in Latino population is evident in the current academic literature.

OBJECTIVES

To determine the associated factors with mortality, in addition to age and sex during the first year of the pandemic.

DESIGN

A case-control study with retrospective revision of clinical and paraclinical variables by systematic revision of clinical records was conducted. Multiple imputations by chained equation were implemented to account for missing variables. Classification and regression trees (CART) were estimated to evaluate the interaction of associated factors on admission and their role in predicting mortality during hospitalisation. No intervention was performed.

SETTING

High-complexity centre above 2640 m above sea level (masl) in Colombia.

PARTICIPANTS

A population sample of 564 patients admitted to the hospital with confirmed COVID-19 by PCR. Deceased patients (n=282) and a control group (n=282), matched by age, sex and month of admission, were included.

MAIN OUTCOME MEASURE

Mortality during hospitalisation.

MAIN RESULTS

After the imputation of datasets, CART analysis estimated 11 clinical profiles based on respiratory distress, haemoglobin, lactate dehydrogenase, partial pressure of oxygen to inspired partial pressure of oxygen ratio, chronic kidney disease, ferritin, creatinine and leucocytes on admission. The accuracy model for prediction was 80.4% (95% CI 71.8% to 87.3%), with an area under the curve of 78.8% (95% CI 69.63% to 87.93%).

CONCLUSIONS

This study discloses new interactions between clinical and paraclinical features beyond age and sex influencing mortality in COVID-19 patients. Furthermore, the predictive model could offer new clues for the personalised management of this condition in clinical settings.

Identification and validation of supervariants reveal novel loci associated with human white matter microstructure

As an essential part of the central nervous system, white matter coordinates communications between different brain regions and is related to a wide range of neurodegenerative and neuropsychiatric disorders. Previous genome-wide association studies (GWASs) have uncovered loci associated with white matter microstructure. However, GWASs suffer from limited reproducibility and difficulties in detecting multi-single-nucleotide polymorphism (multi-SNP) and epistatic effects. In this study, we adopt the concept of supervariants, a combination of alleles in multiple loci, to account for potential multi-SNP effects. We perform supervariant identification and validation to identify loci associated with 22 white matter fractional anisotropy phenotypes derived from diffusion tensor imaging. To increase reproducibility, we use United Kingdom (UK) Biobank White British (n = 30,842) data for discovery and internal validation, and UK Biobank White but non-British (n = 1927) data, Europeans from the Adolescent Brain Cognitive Development study (n = 4399) data, and Europeans from the Human Connectome Project (n = 319) data for external validation. We identify 23 novel loci on the discovery set that have not been reported in the previous GWASs on white matter microstructure. Among them, three supervariants on genomic regions 5q35.1, 8p21.2, and 19q13.32 have P-values lower than 0.05 in the meta-analysis of the three independent validation data sets. These supervariants contain genetic variants located in genes that have been related to brain structures, cognitive functions, and neuropsychiatric diseases. Our findings provide a better understanding of the genetic architecture underlying white matter microstructure.

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways.

Development trends of human organoid-based COVID-19 research based on bibliometric analysis

Coronavirus disease 2019 (COVID-19), a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has posed a catastrophic threat to human health worldwide. Human stem cell-derived organoids serve as a promising platform for exploring SARS-CoV-2 infection. Several review articles have summarized the application of human organoids in COVID-19, but the research status and development trend of this field have seldom been systematically and comprehensively studied. In this review, we use bibliometric analysis method to identify the characteristics of organoid-based COVID-19 research. First, an annual trend of publications and citations, the most contributing countries or regions and organizations, co-citation analysis of references and sources and research hotspots are determined. Next, systematical summaries of organoid applications in investigating the pathology of SARS-CoV-2 infection, vaccine development and drug discovery, are provided. Lastly, the current challenges and future considerations of this field are discussed. The present study will provide an objective angle to identify the current trend and give novel insights for directing the future development of human organoid applications in SARS-CoV-2 infection.

Associations of the COVID-19 burden and various comorbidities of different ethnic groups in Israel: a cross-sectional study

Coronavirus disease (COVID-19) is highly transmissible between human beings. We examined differences in the core families with COVID-19 severity and mortality and comorbidities between Arab and Jews and explored the factors associated with COVID-19 severity and mortality to find a genetic component. A cross-sectional study was conducted among 2240 COVID-19 patients (> 18 years of age) randomly selected by online panels and questionnaires in the native language (Hebrew or Arabic) during March 2021-June 2022. Multivariable linear regression models were used to assess correlations with COVID-19 disease severity and mortality. Overall, 1549 (69%) were Arabs and 691 (31%) were Jews. The proportion of participants who died from COVID-19 was higher among Arabs compared with Jews (66% vs. 59%), P < 0.001. The mean number of deaths from COVID-19 and patients with severe COVID-19 was higher in ultra-Orthodox Jewish, non-academic core families and those who lived in the city residence compared with secular, academic core families and who live in the village residence, P < 0.001. A multivariable linear regression model showed a significant association between metabolic, kidney, cardiovascular, and respiratory diseases with COVID-19 severity (B coefficient - 0.43, B coefficient - 0.53, B coefficient - 0.53, B coefficient - 0.42, respectively) and COVID-19 mortality (B coefficient - 0.51, B coefficient - 0.64, B coefficient - 0.67, B coefficient - 0.34, respectively), P < 0.001. COVID-19 severity and mortality were highly associated with comorbidities, ethnicity, social and environmental factors. Furthermore, we believe that genetic factors also contribute to the increase in COVID-19 severity and mortality and the differences rates of these between Arabs and Jews in Israel.

Single Nucleus RNA Sequencing of Remnant Kidney Biopsies and Urine Cell RNA Sequencing Reveal Cell Specific Markers of Covid-19 Acute Kidney Injury

Acute kidney injury (AKI) in COVID-19 patients is associated with high mortality and morbidity. Critically ill COVID-19 patients are at twice the risk of in-hospital mortality compared to non-COVID AKI patients. We know little about the cell-specific mechanism in the kidney that contributes to worse clinical outcomes in these patients. New generation single cell technologies have the potential to provide insights into physiological states and molecular mechanisms in COVID-AKI. One of the key limitations is that these patients are severely ill posing significant risks in procuring additional biopsy tissue. We recently generated single nucleus RNA-sequencing data using COVID-AKI patient biopsy tissue as part of the human kidney atlas. Here we describe this approach in detail and report deeper comparative analysis of snRNAseq of 4 COVID-AKI, 4 reference, and 6 non-COVID-AKI biopsies. We also generated and analyzed urine transcriptomics data to find overlapping COVID-AKI-enriched genes and their corresponding cell types in the kidney from snRNA-seq data. We identified all major and minor cell types and states by using by using less than a few cubic millimeters of leftover tissue after pathological workup in our approach. Differential expression analysis of COVID-AKI biopsies showed pathways enriched in viral response, WNT signaling, kidney development, and cytokines in several nephron epithelial cells. COVID-AKI profiles showed a much higher proportion of altered TAL cells than non-COVID AKI and the reference samples. In addition to kidney injury and fibrosis markers indicating robust remodeling we found that, 17 genes overlap between urine cell COVID-AKI transcriptome and the snRNA-seq data from COVID-AKI biopsies. A key feature was that several of the distal nephron and collecting system cell types express these markers. Some of these markers have been previously observed in COVID-19 studies suggesting a common mechanism of injury and potentially the kidney as one of the sources of soluble factors with a potential role in disease progression.

Translational Statement

The manuscript describes innovation, application and discovery that impact clinical care in kidney disease. First, the approach to maximize use of remnant frozen clinical biopsies to inform on clinically relevant molecular features can augment existing pathological workflow for any frozen tissue without much change in the protocol. Second, this approach is transformational in medical crises such as pandemics where mechanistic insights are needed to evaluate organ injury, targets for drug therapy and diagnostic and prognostic markers. Third, the cell type specific and soluble markers identified and validated can be used for diagnoses or prognoses in AKI due to different etiologies and in multiorgan injury.

Association between cyclin-dependent kinase inhibitor 2B antisense RNA 1 and zinc finger homeobox 3 gene polymorphisms and COVID-19 severity

BACKGROUND

There is no doubt about the cardiovascular complications of coronavirus disease 2019 (COVID-19). Several genetic studies have demonstrated an association between genetic variants in a region on chromosome 9p21 and in a region on chromosome 16q22 with myocardial infarction (MI) and atrial fibrillation (AF) accompanied by cerebral infarction (CI), respectively.

OBJECTIVES

MI and CI susceptibility in patients with CDKN2B-AS1 and ZFHX3 polymorphisms, respectively, may have an effect on COVID-19 severity. We aimed to investigate whether there is an association between the cyclin-dependent kinase inhibitor 2B antisense RNA 1 (CDKN2B-AS1) rs1333049 and zinc finger homeobox 3 (ZFHX3) rs2106261 single nucleotide polymorphisms (SNPs) and the degree of COVID-19 severity.

SUBJECTS AND METHODS

This current work was carried out on 360 subjects. They were classified into three groups: 90 severe COVID-19 cases, 90 moderate COVID-19 cases and 180 age- and gender-matched healthy controls. All subjects underwent genotyping of CDKN2B-AS1 (rs1333049) and ZFHX3 (rs2106261) by real-time PCR.

RESULTS

The frequency of G/C in CDKN2B-AS1 (rs1333049) was higher in severe and moderate COVID-19 patients than in controls (71.1% and 53.3% vs. 37.8%). The frequency of the C/C of CDKN2B-AS1 (rs1333049) was higher in moderate COVID-19 patients than in controls (26.7% vs. 13.3%). There were no significant differences regarding genotype frequency and allelic distribution of ZFHX3 (rs2106261) between COVID-19 patients and healthy controls.

CONCLUSION

CDKN2B-AS1 (rs1333049) gene polymorphism may play a role in determining the degree of COVID-19 severity. Further studies on its effect on cyclins and cyclin-dependent kinases (CDKs) [not measured in our study] may shed light on new treatment options for COVID-19.

A shared genetic contribution to osteoarthritis and COVID-19 outcomes: a large-scale genome-wide cross-trait analysis

Background

Patients with osteoarthritis (OA) are exposed to an increased risk of adverse outcomes of COVID-19, and they tend to experience disruption in access to healthcare services and exercise facilities. However, a deep understanding of this comorbidity phenomenon and the underlying genetic architecture of the two diseases is still unclear. In this study, we aimed to untangle the relationship between OA and COVID-19 outcomes by conducting a large-scale genome-wide cross-trait analysis.

Methods

Genetic correlation and causal relationships between OA and COVID-19 outcomes (critical COVID-19, COVID-19 hospitalization, and COVID-19 infection) were estimated by linkage disequilibrium score regression and Mendelian Randomization approaches. We further applied Multi-Trait Analysis of GWAS and colocalization analysis to identify putative functional genes associated with both OA and COVID-19 outcomes.

Results

Significant positive genetic correlations between OA susceptibility and both critical COVID-19 (rg=0.266, P=0.0097) and COVID-19 hospitalization (rg=0.361, P=0.0006) were detected. However, there was no evidence to support causal genetic relationships between OA and critical COVID-19 (OR=1.17[1.00-1.36], P=0.049) or OA and COVID-19 hospitalization OR=1.08[0.97-1.20], P=0.143). These results were robustly consistent after the removal of obesity-related single nucleotide polymorphisms (SNPs). Moreover, we identified a strong association signal located near the FYCO1 gene (lead SNPs: rs71325101 for critical COVID-19, Pmeta=1.02×10-34; rs13079478 for COVID-19 hospitalization, Pmeta=1.09×10-25).

Conclusion

Our findings further confirmed the comorbidity of OA and COVID-19 severity, but indicate a non-causal impact of OA on COVID-19 outcomes. The study offers an instructive perspective that OA patients did not generate negative COVID-19 outcomes during the pandemic in a causal way. Further clinical guidance can be formulated to enhance the quality of self-management in vulnerable OA patients.

COVID-19 progression towards ARDS: a genome wide study reveals host factors underlying critical COVID-19

Coronavirus disease 2019 (COVID-19) is a viral infection produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus epidemic, which was declared a global pandemic in March 2020. The World Health Organization has recorded around 43.3 billion cases and 59.4 million casualties to date, posing a severe threat to global health. Severe COVID-19 indicates viral pneumonia caused by the SARS-CoV-2 infections, which can induce fatal consequences, including acute respiratory distress syndrome (ARDS). The purpose of this research is to better understand the COVID-19 and ARDS pathways, as well as to find targeted single nucleotide polymorphism. To accomplish this, we retrieved over 100 patients' samples from the Sequence Read Archive, National Center for Biotechnology Information. These sequences were processed through the Galaxy server next generation sequencing pipeline for variant analysis and then visualized in the Integrative Genomics Viewer, and performed statistical analysis using t-tests and Bonferroni correction, where six major genes were identified as DNAH7, CLUAP1, PPA2, PAPSS1, TLR4, and IFITM3. Furthermore, a complete understanding of the genomes of COVID-19-related ARDS will aid in the early identification and treatment of target proteins. Finally, the discovery of novel therapeutics based on discovered proteins can assist to slow the progression of ARDS and lower fatality rates.

Interactome-Based Machine Learning Predicts Potential Therapeutics for COVID-19

COVID-19, the disease caused by SARS-CoV-2, has been disrupting our lives for more than two years now. SARS-CoV-2 interacts with human proteins to pave its way into the human body, thereby wreaking havoc. Moreover, the mutating variants of the virus that take place in the SARS-CoV-2 genome are also a cause of concern among the masses. Thus, it is very important to understand human-spike protein-protein interactions (PPIs) in order to predict new PPIs and consequently propose drugs for the human proteins in order to fight the virus and its different mutated variants, with the mutations occurring in the spike protein. This fact motivated us to develop a complete pipeline where PPIs and drug-protein interactions can be predicted for human-SARS-CoV-2 interactions. In this regard, initially interacting data sets are collected from the literature, and noninteracting data sets are subsequently created for human-SARS-CoV-2 by considering only spike glycoprotein. On the other hand, for drug-protein interactions both interacting and noninteracting data sets are considered from DrugBank and ChEMBL databases. Thereafter, a model based on a sequence-based feature is used to code the protein sequences of human and spike proteins using the well-known Moran autocorrelation technique, while the drugs are coded using another well-known technique, viz., PaDEL descriptors, to predict new human-spike PPIs and eventually new drug-protein interactions for the top 20 predicted human proteins interacting with the original spike protein and its different mutated variants like Alpha, Beta, Delta, Gamma, and Omicron. Such predictions are carried out by random forest as it is found to perform better than other predictors, providing an accuracy of 90.53% for human-spike PPI and 96.15% for drug-protein interactions. Finally, 40 unique drugs like eicosapentaenoic acid, doxercalciferol, ciclesonide, dexamethasone, methylprednisolone, etc. are identified that target 32 human proteins like ACACA, DST, DYNC1H1, etc.

Effects of Epitranscriptomic RNA Modifications on the Catalytic Activity of the SARS-CoV-2 Replication Complex

SARS-CoV-2 causes individualized symptoms. Many reasons have been given. We propose that an individual's epitranscriptomic system could be responsible as well. The viral RNA genome can be subject to epitranscriptomic modifications, which can be different for different individuals, and thus epitranscriptomics can affect many events including RNA replication differently. In this context, we studied the effects of modifications including pseudouridine (Ψ), 5-methylcytosine (m5 C), N6-methyladenosine (m6 A), N1-methyladenosine (m1 A) and N3-methylcytosine (m3 C) on the activity of SARS-CoV-2 replication complex (SC2RC). We found that Ψ, m5 C, m6 A and m3 C had little effect, whereas m1 A inhibited the enzyme. Both m1 A and m3 C disrupt canonical base pairing, but they had different effects. The fact that m1 A inhibits SC2RC implies that the modification can be difficult to detect. This fact also implies that individuals with upregulated m1 A including cancer, obesity and diabetes patients might have milder symptoms. However, this contradicts clinical observations. Relevant discussions are provided.

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data (28,097 affected cases and 1656 deaths). We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (odds ratio [OR] = 1.594, p = 5.47 × 10-9 ) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050, and rs12540488. We also discover a super variant (OR = 1.353, p = 2.87 × 10-8 ) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G, and rs180899355.

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.

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.

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.

The Clinical Characteristics and Outcomes of COVID-19 Patients with Pre-Existing Thyroid Dysfunction: A Nationwide Study

To which extent the pre-existing hypothyroidism or hyperthyroidism has an impact on coronavirus infection 2019 (COVID-19) outcomes remains unclear. The objective of this study was to evaluate COVID-19 morbidity and mortality in patients with pre-existing thyroid dysfunction. A retrospective cohort of patients with a polymerase chain reaction (PCR)-confirmed COVID-19 infection (n=14 966) from March 11 to May 30, 2020, was established using the database of the Turkish Ministry of Health. We compared the morbidity and mortality rates of COVID-19 patients with pre-existing hypothyroidism (n=8813) and hyperthyroidism (n=1822) to those patients with normal thyroid function (n=4331). Univariate and multivariate regression analyses were performed to identify the factors associated with mortality. Mortality rates were higher in patients with hyperthyroidism (7.7%) and hypothyroidism (4.4%) than those with normal thyroid function (3.4%) (p<0.001 and p=0.008, respectively). Pre-existing hyperthyroidism was significantly associated with an increased risk of mortality (OR 1.54; 95% CI, 1.02-2.33; p=0.042) along with advanced age, male gender, lymphopenia and chronic kidney disease (p<0.001 for all). Although a potential trend was noted, the association between pre-existing hypothyroidism and mortality was not significant (OR 1.36; 95% CI, 0.99-1.86; p=0.055). In conclusion, this study showed an association between pre-existing hyperthyroidism with higher COVID-19 mortality. A potential trend towards increased mortality was also observed for hypothyroidism. The risk was more pronounced in patients with hyperthyroidism.

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.

Analysis of Gene Single Nucleotide Polymorphisms in COVID-19 Disease Highlighting the Susceptibility and the Severity towards the Infection

Many factors may influence the risk of being infected by SARS-CoV-2, the coronavirus responsible for coronavirus disease 2019 (COVID-19). Exposure to the virus cannot explain the variety of an individual's responses to the virus and the high differences of effect that the virus may cause to some. While a person's preexisting condition and their immune defenses have been confirmed to play a major role in the disease progression, there is still much to learn about hosts' genetic makeup towards COVID-19 susceptibility and risk. The host genetic makeup may have direct influence on the grade of predisposition and outcomes of COVID-19. In this study, we aimed to investigate the presence of relevant genetic single nucleotide polymorphisms (SNPs), the peripheral blood level of IL6, vitamin D and arterial blood gas (ABG) markers (pH, oxygen-SpO₂ and carbon dioxide-SpCO₂) on two groups, COVID-19 (n = 41, study), and the healthy (n = 43, control). We analyzed cytokine and interleukin genes in charge of both pro-inflammatory and immune-modulating responses and those genes that are considered involved in the COVID-19 progression and complications. Thus, we selected major genes, such as IL1β, IL1RN (IL-1 β and α receptor) IL6, IL6R (IL-6 receptor), IL10, IFNγ (interferon gamma), TNFα (tumor necrosis factor alpha), ACE2 (angiotensin converting enzyme), SERPINA3 (Alpha-1-Antiproteinase, Antitrypsin member of Serpin 3 family), VDR (vitamin D receptor Tak1, Bsm1 and Fok1), and CRP (c-reactive protein). Though more research is needed, these findings may give a better representation of virus pleiotropic activity and its relation to the immune system.

Interplay between demographic, clinical and polygenic risk factors for severe COVID-19

BACKGROUND

We aimed to identify clinical, socio-demographic and genetic risk factors for severe COVID-19 (hospitalization, critical care admission or death) in the general population.

METHODS

In this observational study, we identified 9560 UK Biobank participants diagnosed with COVID-19 during 2020. A polygenic risk score (PRS) for severe COVID-19 was derived and optimized using publicly available European and trans-ethnic COVID-19 genome-wide summary statistics. We estimated the risk of hospital or critical care admission within 28 days or death within 100 days following COVID-19 diagnosis, and assessed associations with socio-demographic factors, immunosuppressant use and morbidities reported at UK Biobank enrolment (2006-2010) and the PRS. To improve biological understanding, pathway analysis was performed using genetic variants comprising the PRS.

RESULTS

We included 9560 patients followed for a median of 61 (interquartile range = 34-88) days since COVID-19 diagnosis. The risk of severe COVID-19 increased with age and obesity, and was higher in men, current smokers, those living in socio-economically deprived areas, those with historic immunosuppressant use and individuals with morbidities and higher co-morbidity count. An optimized PRS, enriched for single-nucleotide polymorphisms in multiple immune-related pathways, including the 'oligoadenylate synthetase antiviral response' and 'interleukin-10 signalling' pathways, was associated with severe COVID-19 (adjusted odds ratio 1.32, 95% CI 1.11-1.58 for the highest compared with the lowest PRS quintile).

CONCLUSION

This study conducted in the pre-SARS-CoV-2-vaccination era, emphasizes the novel insights to be gained from using genetic data alongside commonly considered clinical and socio-demographic factors to develop greater biological understanding of severe COVID-19 outcomes.

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.

Transcriptome-wide summary data-based Mendelian randomization analysis reveals 38 novel genes associated with severe COVID-19

Severe COVID-19 has a poor prognosis, while the genetic mechanism underlying severe COVID-19 remains largely unknown. We aimed to identify genes that are potentially causally associated with severe COVID-19. We conducted a summary data-based Mendelian randomization (SMR) analysis using expression quantitative trait loci (eQTL) data from 49 different tissues as the exposure and three COVID-19-phenotypes (very severe respiratory confirmed COVID-19 [severe COVID-19], hospitalized COVID-19, and SARS-CoV-2 infection) as the outcomes. SMR using multiple SNPs was used as a sensitivity analysis to reduce false positive rate. Multiple testing was corrected using the false discovery rate (FDR) q-value. We identified 309 significant gene-trait associations (FDR q value < 0.05) across 46 tissues for severe COVID-19, which mapped to 64 genes, of which 38 are novel. The top five most associated protein-coding genes were Interferon Alpha and Beta Receptor Subunit 2 (IFNAR2), 2'-5'-Oligoadenylate Synthetase 3 (OAS3), mucin 1 (MUC1), Interleukin 10 Receptor Subunit Beta (IL10RB), and Napsin A Aspartic Peptidase (NAPSA). The potential causal genes were enriched in biological processes related to type I interferons, interferon-gamma inducible protein 10 production, and chemokine (C-X-C motif) ligand 2 production. In addition, we further identified 23 genes and 5 biological processes which are unique to hospitalized COVID-19, as well as 13 genes that are unique to SARS-CoV-2 infection. We identified several genes that are potentially causally associated with severe COVID-19. These findings improve our limited understanding of the mechanism of COVID-19 and shed light on the development of therapeutic agents for treating severe COVID-19.

Host genetic diversity and genetic variations of SARS-CoV-2 in COVID-19 pathogenesis and the effectiveness of vaccination

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for the outbreak of coronavirus disease 2019 (COVID-19), has shown a vast range of clinical manifestations from asymptomatic to life-threatening symptoms. To figure out the cause of this heterogeneity, studies demonstrated the trace of genetic diversities whether in the hosts or the virus itself. With this regard, this review provides a comprehensive overview of how host genetic such as those related to the entry of the virus, the immune-related genes, gender-related genes, disease-related genes, and also host epigenetic could influence the severity of COVID-19. Besides, the mutations in the genome of SARS-CoV-2 __leading to emerging of new variants__ per se affect the affinity of the virus to the host cells and enhance the immune escape capacity. The current review discusses these variants and also the latest data about vaccination effectiveness facing the most important variants.

COVID-19 patients exhibit unique transcriptional signatures indicative of disease severity

COVID-19 manifests a spectrum of respiratory symptoms, with the more severe often requiring hospitalization. To identify markers for disease progression, we analyzed longitudinal gene expression data from patients with confirmed SARS-CoV-2 infection admitted to the intensive care unit (ICU) for acute hypoxic respiratory failure (AHRF) as well as other ICU patients with or without AHRF and correlated results of gene set enrichment analysis with clinical features. The results were then compared with a second dataset of COVID-19 patients separated by disease stage and severity. Transcriptomic analysis revealed that enrichment of plasma cells (PCs) was characteristic of all COVID-19 patients whereas enrichment of interferon (IFN) and neutrophil gene signatures was specific to patients requiring hospitalization. Furthermore, gene expression results were used to divide AHRF COVID-19 patients into 2 groups with differences in immune profiles and clinical features indicative of severe disease. Thus, transcriptomic analysis reveals gene signatures unique to COVID-19 patients and provides opportunities for identification of the most at-risk individuals.

Genome-wide association study of SARS-CoV-2 infection in Chinese population

Coronavirus disease 2019 (COVID-19) is a global public health concern. The purpose of this study was to investigate the association between genetic variants and SARS-CoV-2 infection and the COVID-19 severity in Chinese population. A total of 256 individuals including 87 symptomatic patients (tested positive for SARS-CoV-2), 84 asymptomatic cases, and 85 close contacts of confirmed patients (tested negative for SARS-CoV-2) were recruited from February 2020 to May 2020. We carried out the whole exome genome sequencing between the individuals and conducted a genetic association study for SARS-CoV-2 infection and the COVID-19 severity. In total, we analyzed more than 100,000 single-nucleotide polymorphisms. The genome-wide association study suggested potential correlation between genetic variability in POLR2A, ANKRD27, MAN1A2, and ERAP1 genes and SARS-CoV-2 infection susceptibility. The most significant gene locus associated with SARS-CoV-2 infection was located in POLR2A (p = 5.71 × 10^-6). Furthermore, genetic variants in PCNX2, CD200R1L, ZMAT3, PLCL2, NEIL3, and LINC00700 genes (p < 1 × 10^-5) were closely associated with the COVID-19 severity in Chinese population. Our study confirmed that new genetic variant loci had significant association with SARS-CoV-2 infection and the COVID-19 severity in Chinese population, which provided new clues for the studies on the susceptibility of SARS-CoV-2 infection and the COVID-19 severity. These findings may give a better understanding on the molecular pathogenesis of COVID-19 and genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

Exome-Wide Association Study Reveals Host Genetic Variants Likely Associated with the Severity of COVID-19 in Patients of European Ancestry

Host genetic variability plays a pivotal role in modulating COVID-19 clinical outcomes. Despite the functional relevance of protein-coding regions, rare variants located here are less likely to completely explain the considerable numbers of acutely affected COVID-19 patients worldwide. Using an exome-wide association approach, with individuals of European descent, we sought to identify common coding variants linked with variation in COVID-19 severity. Herein, cohort 1 compared non-hospitalized (controls) and hospitalized (cases) individuals, and in cohort 2, hospitalized subjects requiring respiratory support (cases) were compared to those not requiring it (controls). 229 and 111 variants differed significantly between cases and controls in cohorts 1 and 2, respectively. This included FBXO34, CNTN2, and TMCC2 previously linked with COVID-19 severity using association studies. Overall, we report SNPs in 26 known and 12 novel candidate genes with strong molecular evidence implicating them in the pathophysiology of life-threatening COVID-19 and post-recovery sequelae. Of these few notable known genes include, HLA-DQB1, AHSG, ALOX5AP, MUC5AC, SMPD1, SPG7, SPEG,GAS6, and SERPINA12. These results enhance our understanding of the pathomechanisms underlying the COVID-19 clinical spectrum and may be exploited to prioritize biomarkers for predicting disease severity, as well as to improve treatment strategies in individuals of European ancestry.

Molecular Mechanisms Related to Responses to Oxidative Stress and Antioxidative Therapies in COVID-19: A Systematic Review

The coronavirus disease (COVID-19) pandemic is a leading global health and economic challenge. What defines the disease’s progression is not entirely understood, but there are strong indications that oxidative stress and the defense against reactive oxygen species are crucial players. A big influx of immune cells to the site of infection is marked by the increase in reactive oxygen and nitrogen species. Our article aims to highlight the critical role of oxidative stress in the emergence and severity of COVID-19 and, more importantly, to shed light on the underlying molecular and genetic mechanisms. We have reviewed the available literature and clinical trials to extract the relevant genetic variants within the oxidative stress pathway associated with COVID-19 and the anti-oxidative therapies currently evaluated in the clinical trials for COVID-19 treatment, in particular clinical trials on glutathione and N-acetylcysteine.

COVID-19 in pediatrics: Genetic susceptibility

The uptick in SARS-CoV-2 infection has resulted in a worldwide COVID-19 pandemic, which has created troublesome health and economic problems. We performed case–control meta-analyses in both African and European ethnicity COVID-19 disease cases based on laboratory test and phenotypic criteria. The cases had laboratory-confirmed SARS-CoV-2 infection. We uniquely investigated COVID infection genetics in a pediatric population. Our cohort has a large African ancestry component, also unique to our study. We tested for genetic variant association in 498 cases vs. 1,533 controls of African ancestry and 271 cases vs. 855 controls of European ancestry. We acknowledge that the sample size is relatively small, owing to the low prevalence of COVID infection among pediatric individuals. COVID-19 cases averaged 13 years of age. Pediatric genetic studies enhance the ability to detect genetic associations with a limited possible environment impact. Our findings support the notion that some genetic variants, most notably at the SEMA6D, FMN1, ACTN1, PDS5B, NFIA, ADGRL3, MMP27, TENM3, SPRY4, MNS1, and RSU1 loci, play a role in COVID-19 infection susceptibility. The pediatric cohort also shows nominal replication of previously reported adult study results: CCR9, CXCR6, FYCO1, LZTFL1, TDGF1, CCR1, CCR2, CCR3, CCR5, MAPT-AS1, and IFNAR2 gene variants. Reviewing the biological roles of genes implicated here, NFIA looks to be the most interesting as it binds to a palindromic sequence observed in both viral and cellular promoters and in the adenovirus type 2 origin of replication.

Coronavirus Host Genetics South Africa (COHG-SA) database-a variant database for gene regions associated with SARS-CoV-2 outcomes

The SARS-CoV-2 virus is responsible for the COVID-19 global public health emergency, and the disease it causes is highly variable in its clinical presentation. Clinical phenotypes are heterogeneous both in terms of presentation of symptoms in the host and response to therapy. Several studies and initiatives have been established to analyse and review host genetic epidemiology associated with COVID-19. Our research group curated these articles into a web-based database using the python application-server framework Django. The database provides a searchable research tool describing current literature surrounding COVID-19 host genetic factors associated with disease outcome. This paper describes the COHG-SA database and provides an overview of the analyses that can be derived from these data.

Super-taxon in human microbiome are identified to be associated with colorectal cancer

Background

Microbial communities in the human body, also known as human microbiota, impact human health, such as colorectal cancer (CRC). However, the different roles that microbial communities play in healthy and disease hosts remain largely unknown. The microbial communities are typically recorded through the taxa counts of operational taxonomic units (OTUs). The sparsity and high correlations among OTUs pose major challenges for understanding the microbiota-disease relation. Furthermore, the taxa data are structured in the sense that OTUs are related evolutionarily by a hierarchical structure.

Results

In this study, we borrow the idea of super-variant from statistical genetics, and propose a new concept called super-taxon to exploit hierarchical structure of taxa for microbiome studies, which is essentially a combination of taxonomic units. Specifically, we model a genus which consists of a set of OTUs at low hierarchy and is designed to reflect both marginal and joint effects of OTUs associated with the risk of CRC to address these issues. We first demonstrate the power of super-taxon in detecting highly correlated OTUs. Then, we identify CRC-associated OTUs in two publicly available datasets via a discovery-validation procedure. Specifically, four species of two genera are found to be associated with CRC: Parvimonas micra, Parvimonas sp., Peptostreptococcus stomatis, and Peptostreptococcus anaerobius. More importantly, for the first time, we report the joint effect of Parvimonas micra and Parvimonas sp. (p = 0.0084) as well as that of Peptostrepto-coccus stomatis and Peptostreptococcus anaerobius (p = 8.21e-06) on CRC. The proposed approach provides a novel and useful tool for identifying disease-related microbes by taking the hierarchical structure of taxa into account and further sheds new lights on their potential joint effects as a community in disease development.

Conclusions

Our work shows that proposed approaches are effective to study the microbiota-disease relation taking into account for the sparsity, hierarchical and correlated structure among microbes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04786-9.

SARS-CoV-2 ORF10 impairs cilia by enhancing CUL2ZYG11B activity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causal pathogen of the ongoing global pandemic of coronavirus disease 2019 (COVID-19). Loss of smell and taste are symptoms of COVID-19, and may be related to cilia dysfunction. Here, we found that the SARS-CoV-2 ORF10 increases the overall E3 ligase activity of the CUL2^ZYG11B complex by interacting with ZYG11B. Enhanced CUL2^ZYG11B activity by ORF10 causes increased ubiquitination and subsequent proteasome-mediated degradation of an intraflagellar transport (IFT) complex B protein, IFT46, thereby impairing both cilia biogenesis and maintenance. Further, we show that exposure of the respiratory tract of hACE2 mice to SARS-CoV-2 or SARS-CoV-2 ORF10 alone results in cilia-dysfunction-related phenotypes, and the ORF10 expression in primary human nasal epithelial cells (HNECs) also caused a rapid loss of the ciliary layer. Our study demonstrates how SARS-CoV-2 ORF10 hijacks CUL2^ZYG11B to eliminate IFT46 and leads to cilia dysfunction, thereby offering a powerful etiopathological explanation for how SARS-CoV-2 causes multiple cilia-dysfunction-related symptoms specific to COVID-19.

Timeline Kinetics of Systemic and Airway Immune Mediator Storm for Comprehensive Analysis of Disease Outcome in Critically Ill COVID-19 Patients

In the present study, the levels of serum and airway soluble chemokines, pro-inflammatory/regulatory cytokines, and growth factors were quantified in critically ill COVID-19 patients (total n=286) at distinct time points (D0, D2-6, D7, D8-13 and D>14-36) upon Intensive Care Unit (ICU) admission. Augmented levels of soluble mediators were observed in serum from COVID-19 patients who progress to death. An opposite profile was observed in tracheal aspirate samples, indicating that systemic and airway microenvironment diverge in their inflammatory milieu. While a bimodal distribution was observed in the serum samples, a unimodal peak around D7 was found for most soluble mediators in tracheal aspirate samples. Systems biology tools further demonstrated that COVID-19 display distinct eccentric soluble mediator networks as compared to controls, with opposite profiles in serum and tracheal aspirates. Regardless the systemic-compartmentalized microenvironment, networks from patients progressing to death were linked to a pro-inflammatory/growth factor-rich, highly integrated center. Conversely, patients evolving to discharge exhibited networks of weak central architecture, with lower number of neighborhood connections and clusters of pro-inflammatory and regulatory cytokines. All in all, this investigation with robust sample size landed a comprehensive snapshot of the systemic and local divergencies composed of distinct immune responses driven by SARS-CoV-2 early on severe COVID-19.

SARS-CoV-2 Susceptibility and ACE2 Gene Variations Within Diverse Ethnic Backgrounds

There is considerable variability in the susceptibility and progression for COVID-19 and it appears to be strongly correlated with age, gender, ethnicity and pre-existing health conditions. However, to our knowledge, cohort studies of COVID-19 in clinically vulnerable groups are lacking. Host genetics has also emerged as a major risk factor for COVID-19, and variation in the ACE2 receptor, which facilitates entry of the SARS-CoV-2 virus into the cell, has become a major focus of attention. Thus, we interrogated an ethnically diverse cohort of National Health Service (NHS) patients in the United Kingdom (United Kingdom) to assess the association between variants in the ACE2 locus and COVID-19 risk. We analysed whole-genome sequencing (WGS) data of 1,837 cases who were tested positive for SARS-CoV-2, and 37,207 controls who were not tested, from the UK’s 100,000 Genomes Project (100KGP) for the presence of ACE2 coding variants and extract expression quantitative trait loci (eQTLs). We identified a splice site variant (rs2285666) associated with increased ACE2 expression with an overrepresentation in SARS-CoV-2 positive patients relative to 100KGP controls (p = 0.015), and in hospitalised European patients relative to outpatients in intra-ethnic comparisons (p = 0.029). We also compared the prevalence of 288 eQTLs, of which 23 were enriched in SARS-CoV-2 positive patients. The eQTL rs12006793 had the largest effect size (d = 0.91), which decreases ACE2 expression and is more prevalent in controls, thus potentially reducing the risk of COVID-19. We identified three novel nonsynonymous variants predicted to alter ACE2 function, and showed that three variants (p.K26R, p. H378R, p. Y515N) alter receptor affinity for the viral Spike (S) protein. Variant p. N720D, more prevalent in the European population (p < 0.001), potentially increases viral entry by affecting the ACE2-TMPRSS2 complex. The spectrum of genetic variants in ACE2 may inform risk stratification of COVID-19 patients and could partially explain the differences in disease susceptibility and severity among different ethnic groups.

An Evolutionary Insight Into the Heterogeneous Severity Pattern of the SARS-CoV-2 Infection

The ongoing pandemic of COVID-19 has elaborated an idiosyncratic pattern of SARS-CoV-2-induced symptoms in the human host. Some populations have succumbed to the SARS-CoV-2 infection in large numbers during this pandemic, whereas others have shown a resilient side by manifesting only milder or no symptoms at all. This observation has relayed the onus of the heterogeneous pattern of SARS-CoV-2-induced critical illness among different populations to the host genetic factors. Here, the evolutionary route was explored and three genetic loci, i.e., rs10735079, rs2109069, and rs2236757, associated with COVID-19 were analyzed. Among the three, the risk allele A at genetic locus rs2236757 residing in the IFNAR2 gene was observed to have undergone recent positive selection in the African population.

Risk factors for SARS-CoV-2 infection and hospitalisation in children and adolescents in Norway: a nationwide population-based study

OBJECTIVE

To determine risk factors for SARS-CoV-2 infection and hospitalisation among children and adolescents.

DESIGN

Nationwide, population-based cohort study.

SETTING

Norway from 1 March 2020 to 30 November 2021.

PARTICIPANTS

All Norwegian residents<18 years of age.

MAIN OUTCOME MEASURES

Population-based healthcare and population registries were used to study risk factors for SARS-CoV-2 infection, including socioeconomic factors, country of origin and pre-existing chronic comorbidities. All residents were followed until age 18 years, emigration, death or end of follow-up. HRs estimated by Cox regression models were adjusted for testing frequency. Further, risk factors for admission to the hospital among the infected were investigated.

RESULTS

Of 1 219 184 residents, 82 734 (6.7%) tested positive by PCR or lateral flow tests, of whom 241 (0.29%) were admitted to a hospital. Low family income (adjusted HR (aHR) 1.26, 95% CI 1.23 to 1.30), crowded housing (1.27, 1.24 to 1.30), household size, age, non-Nordic country of origin (1.63, 1.60 to 1.66) and area of living were independent risk factors for infection. Chronic comorbidity was associated with a slightly lower risk of infection (aHR 0.90, 95% CI 0.88 to 0.93). Chronic comorbidity was associated with hospitalisation (aHR 3.46, 95% CI 2.50 to 4.80), in addition to age, whereas socioeconomic status and country of origin did not predict hospitalisation among those infected.

CONCLUSIONS

Socioeconomic factors, country of origin and area of living were associated with the risk of SARS-CoV-2 infection. However, these factors did not predict hospitalisation among those infected. Chronic comorbidity was associated with higher risk of admission but slightly lower overall risk of acquiring SARS-CoV-2.

Systematic review of host genetic association with Covid-19 prognosis and susceptibility: What have we learned in 2020?

Biomarker identification may provide strategic opportunities to understand disease pathophysiology, predict outcomes, improve human health, and reduce healthcare costs. The highly heterogeneous Covid-19 clinical manifestation suggests a complex interaction of several different human, viral and environmental factors. Here, we systematically reviewed genetic association studies evaluating Covid-19 severity or susceptibility to SARS-CoV-2 infection following PRISMA recommendations. Our research comprised papers published until December 31st , 2020, in PubMed and BioRXiv databases focusing on genetic association studies with Covid-19 prognosis or susceptibility. We found 20 eligible genetic association studies, of which 11 assessed Covid-19 outcome and 14 evaluated infection susceptibility (five analyzed both effects). Q-genie assessment indicated moderate quality. Five large-scale association studies (GWAS, whole-genome, or exome sequencing) were reported with no consistent replication to date. Promising hits were found on the 3p21.31 region and ABO locus. Candidate gene studies examined ACE1, ACE2, TMPRSS2, IFITM3, APOE, Furin, IFNL3, IFNL4, HLA, TNF-ɑ genes, and ABO system. The most evaluated single locus was the ABO, and the most sampled region was the HLA with three and five candidate gene studies, respectively. Meta-analysis could not be performed. Available data showed the need for further reports to replicate claimed associations.

vFLIP-regulated competing endogenous RNA (ceRNA) networks targeting lytic induction for KSHV-associated malignancies

Kaposi's sarcoma-associated herpesvirus (KSHV) causes life-long latent infection and malignancies, including Kaposi sarcoma (KS) commonly found in AIDS patients. Lytic replication can be induced to kill tumor cells harboring latent KSHV, through viral cytopathic effects and the subsequent antiviral immune responses. Viral FLICE-inhibitory protein (vFLIP), encoded by KSHV ORF K13, inhibits KSHV lytic reactivation, implying that the competing endogenous RNA (ceRNA) networks regulated by vFLIP can be modulated to induce the lytic reactivation of latent KSHV, a promising strategy for KSHV-associated malignancies. Here, we performed whole-transcriptome sequencing to reveal the global landscape of non-coding RNAs and mRNAs in iSLK-RGB-BAC16 cells and iSLK-RGB-K13 mutant cells. It showed that vFLIP regulated 227 differently expressed (DE) lncRNAs, 57 DE circRNAs, 20 DE miRNAs and 1371 DE mRNAs. Enrichment analysis verified that riboflavin metabolism was simultaneously enriched in DE genes related to miRNAs, lncRNAs, and circRNAs. The upregulated hsa-miR-378i and hsa-miR-3654, and downregulated miR-4467, miR-3163, miR-4451 and miR-4257 were significantly enriched in the ceRNA complex network, which contained 9 upregulated and 7 downregulated circRNAs, 5 upregulated and 85 downregulated lncRNAs, 5 upregulated and 35 downregulated mRNAs. Finally, we constructed and validated two vFLIP-regulated ceRNA networks: circRNA hsa_circ_0070049/hsa-miR-378i/SPEG/FOXQ1 and lncRNA AL031123.1/hsa-miR-378i/SPEG/FOXQ1. Taken together, the two ceRNA networks may mediate KSHV reactivation. These novel findings refreshed the present understanding of ceRNA network in KSHV lytic induction and provided potential therapeutic targets for KSHV-associated malignancies. This article is protected by copyright. All rights reserved.

Viral and Host Genetic and Epigenetic Biomarkers Related to SARS-CoV-2 Cell Entry, Infection Rate, and Disease Severity

The rapid spread of COVID-19 outbreak lead to a global pandemic declared in March 2020. The common features of corona virus family helped to resolve structural characteristics and entry mechanism of SARS-CoV-2. However, rapid mutagenesis leads to the emergence of new strains that may have different reproduction rates or infectivity and may impact the course and severity of the disease. Host related factors may also play a role in the susceptibility for infection as well as the severity and outcomes of the COVID-19. We have performed a literature and database search to summarize potential viral and host-related genomic and epigenomic biomarkers, such as genetic variability, miRNA, and DNA methylation in the molecular pathway of SARS-CoV-2 entry into the host cell, that may be related to COVID-19 susceptibility and severity. Bioinformatics tools may help to predict the effect of mutations in the spike protein on the binding to the ACE2 receptor and the infectivity of the strain. SARS-CoV-2 may also target several transcription factors and tumour suppressor genes, thus influencing the expression of different host genes and affecting cell signalling. In addition, the virus may interfere with RNA expression in host cells by exploiting endogenous miRNA and its viral RNA. Our analysis showed that numerous human miRNA may form duplexes with different coding and non-coding regions of viral RNA. Polymorphisms in human genes responsible for viral entry and replication, as well as in molecular damage response and inflammatory pathways may also contribute to disease prognosis and outcome. Gene ontology analysis shows that proteins encoded by such polymorphic genes are highly interconnected in regulation of defense response. Thus, virus and host related genetic and epigenetic biomarkers may help to predict the course of the disease and the response to treatment.

An overview of human proteins and genes involved in SARS-CoV-2 infection

As of July 2021, the outbreak of coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has led to more than 200 million infections and more than 4.2 million deaths globally. Complications of severe COVID-19 include acute kidney injury, liver dysfunction, cardiomyopathy, and coagulation dysfunction. Thus, there is an urgent need to identify proteins and genetic factors associated with COVID-19 susceptibility and outcome. We comprehensively reviewed recent findings of host-SARS-CoV-2 interactome analyses. To identify genetic variants associated with COVID-19, we focused on the findings from genome and transcriptome wide association studies (GWAS and TWAS) and bioinformatics analysis. We described established human proteins including ACE2, TMPRSS2, 40S ribosomal subunit, ApoA1, TOM70, HLA-A, and PALS1 interacting with SARS-CoV-2 based on cryo-electron microscopy results. Furthermore, we described approximately 1000 human proteins showing evidence of interaction with SARS-CoV-2 and highlighted host cellular processes such as innate immune pathways affected by infection. We summarized the evidence on more than 20 identified candidate genes in COVID-19 severity. Predicted deleterious and disruptive genetic variants with possible effects on COVID-19 infectivity have been also summarized. These findings provide novel insights into SARS-CoV-2 biology and infection as well as potential strategies for development of novel COVID therapeutic targets and drug repurposing.

Host genetic factors of COVID-19 susceptibility and disease severity in a Thai population

Host genetic factors have been shown to play a role in SARs-CoV-2 infection in diverse populations. However, the genetic landscape differs among various ethnicities; therefore, we explored the host genetic factors associated with COVID-19 disease susceptivity and disease severity in a Thai population. We recruited and genotyped 212 unrelated COVID-19 Thai patients and 36 controls using Axiom^TM Human Genotyping SARs-COV-2 array, including 847,384 single nucleotide polymorphisms related to SARs-COV-2 pathogenesis, immune response, and related comorbidity No SNPs passed the genome-wide significance threshold of p value <1 × 10^-8. However, with a threshold of p value <1 × 10^-5, a locus on chromosome 5q32 was found to have a suggestive association with COVID-19 disease susceptibility (p value 6.9 × 10^-6; Q-Q plot λ = 0.805, odds ratio 0.02). Notably, IL17B is a gene located in this linkage disequilibrium block and is previously shown to play a part in inflammation and pneumonia. Additionally, a suggestive locus on chromosome 12q22, harboring EEA1 and LOC643339, was associated with COVID-19 disease severity (p value 1.3 × 10^-6 - 4.4 × 10^-6, Q-Q plot λ = 0.997, odds ratio 0.28-0.31). EEA1 is involved in viral entry into cells, while LOC643339 is a long non-coding RNA. In summary, our study suggested loci on chromosomes 5q32 and 12q22 to be linked to COVID-19 disease susceptibility and disease severity, respectively. The small sample size of this study may lessen the likelihood that the association found is real, but it could still be true. Further study with a larger cohort is required to confirm these findings.

First and second waves among hospitalised patients with COVID-19 with severe pneumonia: a comparison of 28-day mortality over the 1-year pandemic in a tertiary university hospital in Italy

OBJECTIVE

The first COVID-19-19 epidemic wave was over the period of February-May 2020. Since 1 October 2020, Italy, as many other European countries, faced a second wave. The aim of this analysis was to compare the 28-day mortality between the two waves among COVID-19 hospitalised patients.

DESIGN

Observational cohort study. Standard survival analysis was performed to compare all-cause mortality within 28 days after hospital admission in the two waves. Kaplan-Meier curves as well as Cox regression model analysis were used. The effect of wave on risk of death was shown by means of HRs with 95% CIs. A sensitivity analysis around the impact of the circulating variant as a potential unmeasured confounder was performed.

SETTING

University Hospital of Modena, Italy. Patients admitted to the hospital for severe COVID-19 pneumonia during the first (22 February-31 May 2020) and second (1 October-31 December 2020) waves were included.

RESULTS

During the two study periods, a total of 1472 patients with severe COVID-19 pneumonia were admitted to our hospital, 449 during the first wave and 1023 during the second. Median age was 70 years (IQR 56-80), 37% women, 49% with PaO2/FiO2 <250 mm Hg, 82% with ≥1 comorbidity, median duration of symptoms was 6 days. 28-day mortality rate was 20.0% (95% CI 16.3 to 23.7) during the first wave vs 14.2% (95% CI 12.0 to 16.3) in the second (log-rank test p value=0.03). After including key predictors of death in the multivariable Cox regression model, the data still strongly suggested a lower 28-day mortality rate in the second wave (aHR=0.64, 95% CI 0.45 to 0.90, p value=0.01).

CONCLUSIONS

In our hospitalised patients with COVID-19 with severe pneumonia, the 28-day mortality appeared to be reduced by 36% during the second as compared with the first wave. Further studies are needed to identify factors that may have contributed to this improved survival.

Long-term exposure to PM10 above WHO guidelines exacerbates COVID-19 severity and mortality

BACKGROUND

Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course.

OBJECTIVES

We aimed to assess the underlying effect of long-term exposure to NO2 and PM10 on the severity and mortality of COVID-19.

METHODS

A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO2 and PM10 and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated.

RESULTS

We found that the long-term exposure to PM10 is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM10 showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM10 (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m3 in PM10 concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths.

DISCUSSION

These results demonstrate that long-term PM10 burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.

Long-term exposure to PM10 above WHO guidelines exacerbates COVID-19 severity and mortality

BACKGROUND

Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course.

OBJECTIVES

We aimed to assess the underlying effect of long-term exposure to NO₂ and PM₁₀ on the severity and mortality of COVID-19.

METHODS

A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO₂ and PM₁₀ and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated.

RESULTS

We found that the long-term exposure to PM₁₀ is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM₁₀ showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM₁₀ (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m³ in PM₁₀ concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths.

DISCUSSION

These results demonstrate that long-term PM₁₀ burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.

Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?

GWAS involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have enabled the identification of numerous genomic biomarkers in various complex human diseases, including infectious ones. However, few of these studies are relevant for clinical practice or at the bedside. In this issue of the JCI, Nakanishi et al. characterized the clinical implications of a major genetic risk factor for COVID-19 severity and its age-dependent effect, using individual-level data in a large international multicenter consortium. This study indicates that a common COVID-19 genetic risk factor (rs10490770) associates with increased risks of morbidity and mortality, suggesting potential implications for future clinical risk management. How can the genomic biomarkers identified by GWAS be associated with the clinical outcomes of an infectious disease? In this Commentary, we evaluate the advantages and limitations of this approach.

NICLOSAMIDE-EXFOLIATED ANIONIC CLAY NANOHYBRID REPURPOSED AS AN ANTIVIRAL DRUG FOR TACKLING COVID-19; ORAL FORMULATION WITH TWEEN 60/EUDRAGIT S100

The ongoing pandemic, COVID-19 (SARS-CoV-2), has afflicted millions of people around the world, necessitating that the scientific community work, diligently and promptly, on suitable medicaments. Although vaccination programs have been run globally, the new variants of COVID-19 make it difficult to restrict the spread of the virus by vaccination alone. The combination of vaccination with anti-viral drug formulation is an ideal strategy for tackling the current pandemic situation. Drugs approved by the United States Food and Drug Administration (FDA), such as Remdesivir, have been found to be of little or no benefit. On the other hand, re-purposing of FDA-approved drugs, such as niclosamide (NIC), has offered promise but its applicability is limited due to its poor aqueous solubility and, therefore, low bioavailability. With advanced nano-pharmaceutical approaches, re-purposing this drug in a suitable drug-carrier for a better outcome may be possible. In the current study, an attempt was made to explore the loading of NIC into exfoliated layered double hydroxide nanoparticles (X-LDH NPs); prepared NIC-X-LDH NPs were further modified with eudragit S100 (ES100), an enteric coating polymer, to make the final product, ES100-NIC-X-LDH NPs, to improve absorption by the gastro/intestinal tract (GIT). Furthermore, Tween 60 was added as a coating on ES100-NIC-X-LDH NPs, not just to enhance its in vitro and in vivo stability, but also to enhance its mucoadhesive property, and to obtain, ultimately, better in vivo pharmacokinetic (PK) parameters upon oral administration. Release of NIC from Tween 60-ES100-NIC-X-LDH NPs was found to be greater under gastro/intestinal solution within a shorter period of time than the uncoated samples. The in vivo analysis revealed that Tween 60-ES100-NIC-X-LDH NPs were able to maintain a therapeutically relevant NIC plasma concentration in terms of PK parameters compared to the commercially available Yomesan®, proving that the new formulation might prove to be an effective oral drug-delivery system to deal with the SARS-CoV-2 viral infections. Further studies are required to ensure their safety and anti-viral efficacy.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s42860-021-00153-6.

SARS-CoV-2 Variants Detection Using TaqMan SARS-CoV-2 Mutation Panel Molecular Genotyping Assays

PURPOSE

For rapid detection and tracking of SARS-CoV-2, a simple screening method alternative to laborious and expensive sequencing is highly desirable. Here, we evaluated performance characteristics of TaqMan SARS-CoV-2 mutation panel genotyping molecular assay for detection of most common reported SARS-CoV-2 variants using specific RT-PCR assays targeting single nucleotide polymorphisms (SNP).

PATIENTS AND METHODS

A total of 150 SARS-CoV-2 positive samples from March to July were included for this study. In addition, five controls comprised of synthetic RNA B.1.1.7_601443, B.1.351_678597, P.1_792683, B.1.617.1_1662307 and MN908947.3-Wuhan-hu-1 from Twist bioscience and B.1.1.7 (England/204820464/2020) and B.1.351 (South Africa/KRISP-K005325/2020) from Zeptometrix, NY, USA were used for validation. Total RNA from specimens was extracted using Omega Bio-Tek Mag-Bind Viral RNA Xpress Extraction Kit and tested for known SARS-CoV2 variants using ThermoFisher TaqMan SARS-CoV-2 mutation panel molecular assay on the QuantStudio 12K Flex. Nine representative samples have been compared with sequencing. Data were analyzed by genotype calling using QuantStudio™ design and analysis software v 2.5 with the genotyping analysis module.

RESULTS

All validation controls were tested in triplicate and repeated in singlet on three different days and all reported variants were matched as expected. Out of 150 SARS-CoV-2 positive specimens, 69 (46%) were B.1.617.2, 49 (32.7%) were B.1.1.7, P.1 and P.2 were 4 (2.7%) each and B.1.351 and B.1.427/B.1429 were 2 (1.3%) each. Three (2%) were B.1.526, and 17 (11.3%) have a mutation in D614G. Genotyping results from the present study showing B.1.617.2, B.1.1.7, and B.1.526 variants and their mutation genes were concordant with sequencing results.

CONCLUSION

Our study indicates that TaqMan SARS-CoV-2 mutation panel molecular genotyping assays detect and differentiate all published common variants B.1.617.2 (Delta), B.1.1.7 (Alpha), B.1.526 (Iota), B.1.351 (Beta), P.1 (Gamma), P.2 (Zeta), B.1.617.1 (Kappa) and B.1.427/B.1.429 (Epsilon) that can be used for surveillance and epidemic control and prevention.