Unraveling Risk Genes of COVID-19 by Multi-Omics Integrative Analyses

Chemokine receptors in COVID-19 infection

Chemokine receptors play diverse roles in the immune response against pathogens by recruiting innate and adaptive immune cells to sites of infection. However, their involvement could also be detrimental, causing tissue damage and exacerbating respiratory diseases by triggering histological alterations such as fibrosis and remodeling. This chapter reviews the role of chemokine receptors in the immune defense against SARS-CoV-2 infection. In COVID-19, CXCR3 is expressed mainly in T cells, and its upregulation is related to an increase in SARS-CoV-2-specific antibodies but also to COVID-19 severity. CCR5 is a key player in T-cell recruitment, and its suppression leads to reduced inflammation and viremia levels. Conversely, CXCR6 is implicated in the aberrant migration of memory T cells within airways. On the other hand, increased CCR4+ cells in the blood and decreased CCR4+ cells in lung cells are associated with severe COVID-19. Additionally, CCR2 is associated with an increase in macrophage recruitment to lung tissues. Elevated levels of CXCR1 and CXCR2, which are predominantly expressed in neutrophils, are associated with the severity of the disease, and finally, the expression of CX3CR1 in cytotoxic T lymphocytes affects the retention of these cells in lung tissues, thereby impacting the severity of COVID-19. Despite the efforts of many clinical trials to find effective therapies for COVID-19 using chemokine receptor inhibitors, no conclusive results have been found due to the small number of patients, redundancy, and co-expression of chemokine receptors by immune cells, which explains the difficulty in finding a single therapeutic target or effective treatment.

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.

Genetic justification of COVID-19 patient outcomes using DERGA, a novel data ensemble refinement greedy algorithm

Complement inhibition has shown promise in various disorders, including COVID-19. A prediction tool including complement genetic variants is vital. This study aims to identify crucial complement-related variants and determine an optimal pattern for accurate disease outcome prediction. Genetic data from 204 COVID-19 patients hospitalized between April 2020 and April 2021 at three referral centres were analysed using an artificial intelligence-based algorithm to predict disease outcome (ICU vs. non-ICU admission). A recently introduced alpha-index identified the 30 most predictive genetic variants. DERGA algorithm, which employs multiple classification algorithms, determined the optimal pattern of these key variants, resulting in 97% accuracy for predicting disease outcome. Individual variations ranged from 40 to 161 variants per patient, with 977 total variants detected. This study demonstrates the utility of alpha-index in ranking a substantial number of genetic variants. This approach enables the implementation of well-established classification algorithms that effectively determine the relevance of genetic variants in predicting outcomes with high accuracy.

[Association of polymorphic variants of hemostatic system genes with the course of COVID-19]

INTRODUCTION

  COVID-19 is characterized by a varied clinical course. The aim of the work was to identify associations of SNPs of hemostatic system genes with COVID-19.

MATERIALS AND METHODS

DNA was isolated from patients (n=117) and healthy participants (n=104). All infected patients were divided into 3 groups, depending on disease severity assessment, which was appreciated by NEWS2. Another group consisted of participants, who had asymptomatic infection in the past. Determination of SNPs of the genes FGB (-455 G/A), FII (20210 G/A), FV (1691 G/A), FVII (10976 G/A), FXIIIA1 (103 G/T), ITGA2 (807 C/T), ITGB3 (1565 T/C), SERPINE1 (-675 5G/4G) were performed by PCR using the "Genetics of Hemostasis" kit ("DNA-Technology", Russia).

RESULTS

In analyzed SNPs, no significant differences were detected between the group of infected patients and healthy participants. But significant association was revealed in gene SERPINE1 (-675 5G/4G), when patient groups, differing in the disease severity, were analyzed relative to the group of participants with asymptomatic infection (p=0.0381; p=0 .0066; p=0.0009). It was found, that as COVID-19 severity scores increased, the proportion of 5G allele of gene SERPINE1 decreased, and the proportion of the 4G allele increased (p=0.005; p=0.009; p=0.0005). Similar processes were observed for genotypes 5G/5G and 4G/4G.

DISCUSSION

The gene SERPINE1 (-675 5G/4G) is associated with the severity of COVID-19.

CONCLUSION

For the first time, it was discovered that 5G/5G genotype of gene SERPINE1 (-675 5G/4G) can be a marker of a milder course of COVID-19, and the 4G/4G genotype as a more severe one.

Causal associations and genetic overlap between COVID-19 and intelligence

OBJECTIVE

COVID-19 might cause neuroinflammation in the brain, which could decrease neurocognitive function. We aimed to evaluate the causal associations and genetic overlap between COVID-19 and intelligence.

METHODS

We performed Mendelian randomization (MR) analyses to assess potential associations between three COVID-19 outcomes and intelligence (N = 269 867). The COVID phenotypes included severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (N = 2 501 486), hospitalized COVID-19 (N = 1 965 329) and critical COVID-19 (N = 743 167). Genome-wide risk genes were compared between the genome-wide association study (GWAS) datasets on hospitalized COVID-19 and intelligence. In addition, functional pathways were constructed to explore molecular connections between COVID-19 and intelligence.

RESULTS

The MR analyses indicated that genetic liabilities to SARS-CoV-2 infection (odds ratio [OR]: 0.965, 95% confidence interval [CI]: 0.939-0.993) and critical COVID-19 (OR: 0.989, 95% CI: 0.979-0.999) confer causal effects on intelligence. There was suggestive evidence supporting the causal effect of hospitalized COVID-19 on intelligence (OR: 0.988, 95% CI: 0.972-1.003). Hospitalized COVID-19 and intelligence share 10 risk genes within 2 genomic loci, including MAPT and WNT3. Enrichment analysis showed that these genes are functionally connected within distinct subnetworks of 30 phenotypes linked to cognitive decline. The functional pathway revealed that COVID-19-driven pathological changes within the brain and multiple peripheral systems may lead to cognitive impairment.

CONCLUSIONS

Our study suggests that COVID-19 may exert a detrimental effect on intelligence. The tau protein and Wnt signaling may mediate the influence of COVID-19 on intelligence.

Colocalization of expression transcripts with COVID-19 outcomes is rare across cell states, cell types and organs

Identifying causal genes at GWAS loci can help pinpoint targets for therapeutic interventions. Expression studies can disentangle such loci but signals from expression quantitative trait loci (eQTLs) often fail to colocalize-which means that the genetic control of measured expression is not shared with the genetic control of disease risk. This may be because gene expression is measured in the wrong cell type, physiological state, or organ. We tested whether Mendelian randomization (MR) could identify genes at loci influencing COVID-19 outcomes and whether the colocalization of genetic control of expression and COVID-19 outcomes was influenced by cell type, cell stimulation, and organ. We conducted MR of cis-eQTLs from single cell (scRNA-seq) and bulk RNA sequencing. We then tested variables that could influence colocalization, including cell type, cell stimulation, RNA sequencing modality, organ, symptoms of COVID-19, and SARS-CoV-2 status among individuals with symptoms of COVID-19. The outcomes used to test colocalization were COVID-19 severity and susceptibility as assessed in the Host Genetics Initiative release 7. Most transcripts identified using MR did not colocalize when tested across cell types, cell state and in different organs. Most that did colocalize likely represented false positives due to linkage disequilibrium. In general, colocalization was highly variable and at times inconsistent for the same transcript across cell type, cell stimulation and organ. While we identified factors that influenced colocalization for select transcripts, identifying 33 that mediate COVID-19 outcomes, our study suggests that colocalization of expression with COVID-19 outcomes is partially due to noisy signals even after following quality control and sensitivity testing. These findings illustrate the present difficulty of linking expression transcripts to disease outcomes and the need for skepticism when observing eQTL MR results, even accounting for cell types, stimulation state and different organs.

Genetic Predictors of Comorbid Course of COVID-19 and MAFLD: A Comprehensive Analysis

Metabolic-associated fatty liver disease (MAFLD) and its potential impact on the severity of COVID-19 have gained significant attention during the pandemic. This review aimed to explore the genetic determinants associated with MAFLD, previously recognized as non-alcoholic fatty liver disease (NAFLD), and their potential influence on COVID-19 outcomes. Various genetic polymorphisms, including PNPLA3 (rs738409), GCKR (rs780094), TM6SF2 (rs58542926), and LYPLAL1 (rs12137855), have been investigated in relation to MAFLD susceptibility and progression. Genome-wide association studies and meta-analyses have revealed associations between these genetic variants and MAFLD risk, as well as their effects on lipid metabolism, glucose regulation, and liver function. Furthermore, emerging evidence suggests a possible connection between these MAFLD-associated polymorphisms and the severity of COVID-19. Studies exploring the association between indicated genetic variants and COVID-19 outcomes have shown conflicting results. Some studies observed a potential protective effect of certain variants against severe COVID-19, while others reported no significant associations. This review highlights the importance of understanding the genetic determinants of MAFLD and its potential implications for COVID-19 outcomes. Further research is needed to elucidate the precise mechanisms linking these genetic variants to disease severity and to develop gene profiling tools for the early prediction of COVID-19 outcomes. If confirmed as determinants of disease severity, these genetic polymorphisms could aid in the identification of high-risk individuals and in improving the management of COVID-19.

Mapping interindividual dynamics of innate immune response at single-cell resolution

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.

Role of OAS gene family in COVID-19 induced heart failure

BACKGROUND

COVID-19, the current global pandemic caused by SARS-CoV-2 infection, can damage the heart and lead to heart failure (HF) and even cardiac death. The 2',5'-oligoadenylate synthetase (OAS) gene family encode interferon (IFN)-induced antiviral proteins which is associated with the antiviral immune responses of COVID-19. While the potential association of OAS gene family with cardiac injury and failure in COVID-19 has not been determined.

METHODS

The expression levels and biological functions of OAS gene family in SARS-CoV-2 infected cardiomyocytes dataset (GSE150392) and HF dataset (GSE120852) were determined by comprehensive bioinformatic analysis and experimental validation. The associated microRNAs (miRNAs) were explored from Targetscan and GSE104150. The potential OAS gene family-regulatory chemicals or ingredients were predicted using Comparative Toxicogenomics Database (CTD) and SymMap database.

RESULTS

The OAS genes were highly expressed in both SARS-CoV-2 infected cardiomyocytes and failing hearts. The differentially expressed genes (DEGs) in the two datasets were enriched in both cardiovascular disease and COVID-19 related pathways. The miRNAs-target analysis indicated that 10 miRNAs could increase the expression of OAS genes. A variety of chemicals or ingredients were predicted regulating the expression of OAS gene family especially estradiol.

CONCLUSION

OAS gene family is an important mediator of HF in COVID-19 and may serve as a potential therapeutic target for cardiac injury and HF in COVID-19.

Impact of COVID-19 on Cardiovascular Disease

Coronavirus disease 2019 (COVID-19) is a viral infection with the novel severe acute respiratory distress syndrome corona virus 2 (SARS-CoV-2). Until now, more than 670 million people have suffered from COVID-19 worldwide, and roughly 7 million death cases were attributed to COVID-19. Recent evidence suggests an interplay between COVID-19 and cardiovascular disease (CVD). COVID-19 may serve as a yet underappreciated CVD risk modifier, including risk factors such as diabetes mellitus or arterial hypertension. In addition, recent data suggest that previous COVID-19 may increase the risk for many entities of CVD to an extent similarly observed for traditional cardiovascular (CV) risk factors. Furthermore, increased CVD incidence and worse clinical outcomes in individuals with preexisting CVD have been observed for myocarditis, acute coronary syndrome, heart failure (HF), thromboembolic complications, and arrhythmias. Direct and indirect mechanisms have been proposed by which COVID-19 may impact CVD and CV risk, including viral entry into CV tissue or by the induction of a massive systemic inflammatory response. In the current review, we provide an overview of the literature reporting an interaction between COVID-19 and CVD, review potential mechanisms underlying this interaction, and discuss preventive and treatment strategies and their interference with CVD that were evaluated since the onset of the COVID-19 pandemic.

A cross-tissue transcriptome association study identifies key genes in essential hypertension

Genome-wide association study (GWAS) have identified over 1,000 loci associated with blood pressure. However, these loci only explain 6% of heritability. Transcriptome-wide association studies (TWAS) combine GWAS summary data with expression quantitative trait loci (eQTL) to provide a better approach to finding genes associated with complex traits. GWAS summary data (N = 450,584) for essential hypertension originating from European samples were subjected to Post-GWAS analysis using FUMA software and then combined with eQTL data from Genotype-Tissues Expression Project (GTEx) v8 for TWAS analysis using UTMOST, FUSION software, and then validated the results with SMR. FUMA identified 346 significant genes associated with hypertension, FUSION identified 461, and UTMOST cross-tissue analysis identified 34, of which 5 were common. SMR validation identified 3 key genes: ENPEP, USP38, and KCNK3. In previous GWAS studies on blood pressure regulation, the association of ENPEP and KCNK3 with hypertension has been established, and the association between USP38 and blood pressure regulation still needs further validation.

Diagnosis and Stratification of COVID-19 Infections Using Differential Plasma Levels of D-Dimer: A Two-Center Study from Saudi Arabia

Background: D-dimer, generated upon the degradation of fibrin, is extensively used to detect thrombosis in various diseases. It is also explored as a marker for thrombosis in cases with COVID-19 disease. Few studies have confirmed its utility as a marker for assessing disease severity. Objectives: The current research was undertaken to determine the role of D-dimer in patients with COVID-19 and to investigate any association with the progression and severity of the disease in the Saudi population. Methods: Clinical indices in confirmed COVID-19 patients were collected from tertiary care hospitals in Aljouf and Qassim regions. The plasma D-dimer levels were quantified directly in the samples collected from COVID-19 patients (n = 148) using an immunofluorescence assay, and the data were presented in Fibrinogen Equivalent Units (mg/L). The collected data of D-dimer were analyzed based on COVID-19 severity, age, and the gender of patients. Results: The findings show that the plasma D-dimer concentrations were significantly (p = 0.0027) elevated in COVID-19 cases (n = 148), compared to in the normal healthy uninfected controls (n = 309). Moreover, the D-dimer levels were analyzed according to the severity of the disease in the patients. The data revealed that D-dimer concentrations were significantly increased in patients with mild infection to moderate disease, and the levels were the highest in patients with severe COVID-19 disease (p < 0.05). Our analysis demonstrates that the D-dimer levels have no association with the age or gender of COVID-19 patients (p > 0.05) in the study population. Conclusions: D-dimer can serve as a biomarker not only for the detection of COVID-19 infection, but also for determining the severity of infection of COVID-19 disease.

PIGN-Related Disease in Two Lithuanian Families: A Report of Two Novel Pathogenic Variants, Molecular and Clinical Characterisation

Background and Objectives: Pathogenic variants of PIGN are a known cause of multiple congenital anomalies-hypotonia-seizures syndrome 1 (MCAHS1). Many affected individuals have clinical features overlapping with Fryns syndrome and are mainly characterised by developmental delay, congenital anomalies, hypotonia, seizures, and specific minor facial anomalies. This study investigates the clinical and molecular data of three individuals from two unrelated families, the clinical features of which were consistent with a diagnosis of MCAHS1. Materials and Methods: Next-generation sequencing (NGS) technology was used to identify the changes in the DNA sequence. Sanger sequencing of gDNA of probands and their parents was used for validation and segregation analysis. Bioinformatics tools were used to investigate the consequences of pathogenic or likely pathogenic PIGN variants at the protein sequence and structure level. Results: The analysis of NGS data and segregation analysis revealed a compound heterozygous NM_176787.5:c.[1942G>T];[1247_1251del] PIGN genotype in family 1 and NG_033144.1(NM_176787.5):c.[932T>G];[1674+1G>C] PIGN genotype in family 2. In silico, c.1942G>T (p.(Glu648Ter)), c.1247_1251del (p.(Glu416GlyfsTer22)), and c.1674+1G>C (p.(Glu525AspfsTer68)) variants are predicted to result in a premature termination codon that leads to truncated and functionally disrupted protein causing the phenotype of MCAHS1 in the affected individuals. Conclusions: PIGN-related disease represents a wide spectrum of phenotypic features, making clinical diagnosis inaccurate and complicated. The genetic testing of every individual with this phenotype provides new insights into the origin and development of the disease.

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.

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology

Genome-wide association studies (GWASs) have successfully identified thousands of genetic variants that are reliably associated with human traits. Although GWASs are restricted to certain variant frequencies, they have improved our understanding of the genetic architecture of complex traits and diseases. The UK Biobank (UKBB) has brought substantial analytical opportunity and performance to association studies. The dramatic expansion of many GWAS sample sizes afforded by the inclusion of UKBB data has improved the power of estimation of effect sizes but, critically, has done so in a context where phenotypic depth and precision enable outcome dissection and the application of epidemiological approaches. However, at the same time, the availability of such a large, well-curated, and deeply measured population-based collection has the capacity to increase our exposure to the many complications and inferential complexities associated with GWASs and other analyses. In this review, we discuss the impact that UKBB has had in the GWAS era, some of the opportunities that it brings, and exemplar challenges that illustrate the reality of using data from this world-leading resource.

Increased mRNA Levels of ADAM17, IFITM3, and IFNE in Peripheral Blood Cells Are Present in Patients with Obesity and May Predict Severe COVID-19 Evolution

Gene expression patterns in blood cells from SARS-CoV-2 infected individuals with different clinical phenotypes and body mass index (BMI) could help to identify possible early prognosis factors for COVID-19. We recruited patients with COVID-19 admitted in Hospital Universitari Son Espases (HUSE) between March 2020 and November 2021, and control subjects. Peripheral blood cells (PBCs) and plasma samples were obtained on hospital admission. Gene expression of candidate transcriptomic biomarkers in PBCs were compared based on the patients’ clinical status (mild, severe and critical) and BMI range (normal weight, overweight, and obesity). mRNA levels of ADAM17, IFITM3, IL6, CXCL10, CXCL11, IFNG and TYK2 were increased in PBCs of COVID-19 patients (n = 73) compared with controls (n = 47), independently of sex. Increased expression of IFNE was observed in the male patients only. PBC mRNA levels of ADAM17, IFITM3, CXCL11, and CCR2 were higher in those patients that experienced a more serious evolution during hospitalization. ADAM17, IFITM3, IL6 and IFNE were more highly expressed in PBCs of patients with obesity. Interestingly, the expression pattern of ADAM17, IFITM3 and IFNE in PBCs was related to both the severity of COVID-19 evolution and obesity status, especially in the male patients. In conclusion, gene expression in PBCs can be useful for the prognosis of COVID-19 evolution.

IFNAR2 relevance in the clinical outcome of individuals with severe COVID-19

Interferons (IFNs) are a group of cytokines with antiviral, antiproliferative, antiangiogenic, and immunomodulatory activities. Type I IFNs amplify and propagate the antiviral response by interacting with their receptors, IFNAR1 and IFNAR2. In COVID-19, the IFNAR2 (interferon alpha and beta receptor subunit 2) gene has been associated with the severity of the disease, but the soluble receptor (sIFNAR2) levels have not been investigated. We aimed to evaluate the association of IFNAR2 variants (rs2236757, rs1051393, rs3153, rs2834158, and rs2229207) with COVID-19 mortality and to assess if there was a relation between the genetic variants and/or the clinical outcome, with the levels of sIFNAR2 in plasma samples from hospitalized individuals with severe COVID-19. We included 1,202 subjects with severe COVID-19. The genetic variants were determined by employing Taqman® assays. The levels of sIFNAR2 were determined with ELISA in plasma samples from a subgroup of 351 individuals. The rs2236757, rs3153, rs1051393, and rs2834158 variants were associated with mortality risk among patients with severe COVID-19. Higher levels of sIFNAR2 were observed in survivors of COVID-19 compared to the group of non-survivors, which was not related to the studied IFNAR2 genetic variants. IFNAR2, both gene, and soluble protein, are relevant in the clinical outcome of patients hospitalized with severe COVID-19.

Reduced Cell Surface Levels of C-C Chemokine Receptor 5 and Immunosuppression in Long Coronavirus Disease 2019 Syndrome

In an exploratory trial treating "long COVID" with the CCR5-binding antibody leronlimab, we observed significantly increased blood cell surface CCR5 in treated symptomatic responders but not in nonresponders or placebo-treated participants. These findings suggest an unexpected mechanism of abnormal immune downmodulation in some persons that is normalized by leronlimab. Clinical Trials Registration. NCT04678830.

Causal Association and Shared Genetics Between Asthma and COVID-19

Objectives

Recent studies suggest that asthma may have a protective effect on COVID-19.We aimed to investigate the causality between asthma and two COVID-19 outcomes and explore the mechanisms underlining this connection.

Methods

Summary results of GWAS were used for the analyses, including asthma (88,486 cases and 447,859 controls), COVID-19 hospitalization (6,406 hospitalized COVID-19 cases and 902,088 controls), and COVID-19 infection (14,134 COVID-19 cases and 1,284,876 controls). The Mendelian randomization (MR) analysis was performed to evaluate the causal effects of asthma on the two COVID-19 outcomes. A cross-trait meta-analysis was conducted to analyze genetic variants within two loci shared by COVID-19 hospitalization and asthma.

Results

Asthma is associated with decreased risk both for COVID-19 hospitalization (odds ratio (OR): 0.70, 95% confidence interval (CI): 0.70-0.99) and for COVID-19 infection (OR: 0.83, 95%CI: 0.51-0.95). Asthma and COVID-19 share two genome-wide significant genes, including ABO at the 9q34.2 region and OAS2 at the 12q24.13 region. The meta-analysis revealed that ABO and ATXN2 contain variants with pleiotropic effects on both COVID-19 and asthma.

Conclusion

In conclusion, our results suggest that genetic liability to asthma is associated with decreased susceptibility to SARS-CoV-2 and to severe COVID-19 disease, which may be due to the protective effects of ongoing inflammation and, possibly, related compensatory responses against COVID-19 in its early stage.

The unfavorable clinical outcome of COVID-19 in smokers is mediated by H3K4me3, H3K9me3 and H3K27me3 histone marks

Smoking could predispose individuals to a more severe COVID-19 by upregulating a particular gene known as mdig, which is mediated through a number of well-known histone modifications. Smoking might regulate the transcription-activating H3K4me3 mark, along with the transcription-repressing H3K9me3 and H3K27me3 marks, in a way to favor SARS-CoV-2 entry by enhancing the expression of ACE2, NRP1 and NRP2, AT1R, CTSD and CTSL, PGE2 receptors 2-4, SLC6A20 and IL-6, all of which interact either directly or indirectly with important receptors, facilitating viral entry in COVID-19.

Prioritisation of Candidate Genes Underpinning COVID-19 Host Genetic Traits Based on High-Resolution 3D Chromosomal Topology

Genetic variants showing associations with specific biological traits and diseases detected by genome-wide association studies (GWAS) commonly map to non-coding DNA regulatory regions. Many of these regions are located considerable distances away from the genes they regulate and come into their proximity through 3D chromosomal interactions. We previously developed COGS, a statistical pipeline for linking GWAS variants with their putative target genes based on 3D chromosomal interaction data arising from high-resolution assays such as Promoter Capture Hi-C (PCHi-C). Here, we applied COGS to COVID-19 Host Genetic Consortium (HGI) GWAS meta-analysis data on COVID-19 susceptibility and severity using our previously generated PCHi-C results in 17 human primary cell types and SARS-CoV-2-infected lung carcinoma cells. We prioritise 251 genes putatively associated with these traits, including 16 out of 47 genes highlighted by the GWAS meta-analysis authors. The prioritised genes are expressed in a broad array of tissues, including, but not limited to, blood and brain cells, and are enriched for genes involved in the inflammatory response to viral infection. Our prioritised genes and pathways, in conjunction with results from other prioritisation approaches and targeted validation experiments, will aid in the understanding of COVID-19 pathology, paving the way for novel treatments.