Multi-omics highlights ABO plasma protein as a causal risk factor for COVID-19

Multi-omics combined to investigate potential druggable therapeutic targets for stroke: A systematic Mendelian randomization study and transcriptome verification

OBJECTIVE

Stroke is a highly prevalent and disabling disease whose disease mechanisms are not fully understood. The discovery of disease-associated proteins with genetic evidence of pathogenicity provides an opportunity to identify new therapeutic targets.

METHOD

We examined the observed and causal associations of thousands of plasma and inflammatory proteins that were measured using affinity-based proteomic assays. First, we pooled >3000 relevant proteins using a fixed-effects meta-analysis of 2 population-based studies involving 48,383 participants, then investigated the causal effects of stroke and its subtype-associated proteins by forward Mendelian randomization using cis-protein quantitative locus genetic tools identified from genome-wide association studies of these >48,000 individuals. To improve the accuracy of causal estimation, we implemented a systematic Mendelian randomization model that accounts for cascading imbalances between instruments and tested the robustness of causal estimation through multi-method analyses. To further validate the hypothesis that ginsenoside Rg1 monomer acts on the five protein targets screened for drug-targeted regulation, we conducted a comparative analysis of the mRNA (gene) expression levels of a limited number of genes in the brain tissues of different groups of SD rats. The druggability of the candidate proteins was investigated and the mechanism of action and potential targeting side effects were explored by Phenome-wide MR.

RESULTS

Six circulating proteins were identified to have a significant genetic association with stroke (PFDR < 0.05). For example, in patients with cardioembolic stroke, higher genetically predicted APRT was associated with a lower risk of cardioembolic stroke (ORivw [95 % CI] = 0.641 [0.517, 0.795]; P = 5.25 × 10-5, ORSMR [95 % CI] = 0.572, [0.397, 0.825], PSMR = 0.003). Mediation analyses suggested that atrial fibrillation, angina pectoris, and heart failure may mediate the association of CD40L, LIFR, and UPA with stroke. Molecular docking revealed promising interactions between the identified proteins and glycosides. Transcriptomic sequencing in animal models indicated that ginsenoside Rg1 may act through APRT, IL15RA, and VSIR pathways, with APRT showing significant variability in mRNA sequencing expression. Phenome-wide MR of the six target proteins showed an overwhelming predominance of PFDR > 0.05, indicating less toxicity.

CONCLUSIONS

The present study provides genetic evidence to support the potential efficacy of targeting the three druggable protein targets for the treatment of stroke. This is achieved by triangulating population genomic and proteomic data. Furthermore, the study validates the pathway mechanisms by which APRT, IL15RA, and VSIR dock ginsenoside Rg1 in animal models. This will help to prioritize stroke drug development.

Cryo-EM structure of ACE2-SIT1 in complex with tiagabine

The pharmacology of amino acid transporters in the SLC6 family is poorly developed compared to that of the neurotransmitter transporters. To identify new inhibitors of the proline transporter SIT1 (SLC6A20), its expression in Xenopus laevis oocytes was optimized. Trafficking of SIT1 was augmented by co-expression of angiotensin-converting enzyme 2 (ACE2) in oocytes but there was no strict requirement for co-expression of ACE2. A pharmacophore-guided screen identified tiagabine as a potent non-competitive inhibitor of SIT1. To understand its binding mode, we determined the cryo-electron microscopy (cryo-EM) structure of ACE2-SIT1 bound with tiagabine. The inhibitor binds close to the orthosteric proline binding site, but due to its size extends into the cytosolic vestibule. This causes the transporter to adopt an inward-open conformation, in which the intracellular gate is blocked. This study provides the first structural insight into inhibition of SIT1 and generates tools for a better understanding of the ACE2-SIT1 complex. These findings may have significance for SARS-CoV-2 binding to its receptor ACE2 in human lung alveolar cells where SIT1 and ACE2 are functionally expressed.

Identification of genetic loci jointly influencing COVID-19 and coronary heart diseases

BACKGROUND

Comorbidities of coronavirus disease 2019 (COVID-19)/coronary heart disease (CHD) pose great threats to disease outcomes, yet little is known about their shared pathology. The study aimed to examine whether comorbidities of COVID-19/CHD involved shared genetic pathology, as well as to clarify the shared genetic variants predisposing risks common to COVID-19 severity and CHD risks.

METHODS

By leveraging publicly available summary statistics, we assessed the genetically determined causality between COVID-19 and CHD with bidirectional Mendelian randomization. To further quantify the causality contributed by shared genetic variants, we interrogated their genetic correlation with the linkage disequilibrium score regression method. Bayesian colocalization analysis coupled with conditional/conjunctional false discovery rate analysis was applied to decipher the shared causal single nucleotide polymorphisms (SNPs).

FINDINGS

Briefly, we observed that the incident CHD risks post COVID-19 infection were partially determined by shared genetic variants. The shared genetic variants contributed to the causality at a proportion of 0.18 (95% CI 0.18-0.19) to 0.23 (95% CI 0.23-0.24). The SNP (rs10490770) located near LZTFL1 suggested direct causality (SNPs → COVID-19 → CHD), and SNPs in ABO (rs579459, rs495828), ILRUN(rs2744961), and CACFD1(rs4962153, rs3094379) may simultaneously influence COVID-19 severity and CHD risks.

INTERPRETATION

Five SNPs located near LZTFL1 (rs10490770), ABO (rs579459, rs495828), ILRUN (rs2744961), and CACFD1 (rs4962153, rs3094379) may simultaneously influence their risks. The current study suggested that there may be shared mechanisms predisposing to both COVID-19 severity and CHD risks. Genetic predisposition to COVID-19 is a causal risk factor for CHD, supporting that reducing the COVID-19 infection risk or alleviating COVID-19 severity among those with specific genotypes might reduce their subsequent CHD adverse outcomes. Meanwhile, the shared genetic variants identified may be of clinical implications for identifying the target population who are more vulnerable to adverse CHD outcomes post COVID-19 and may also advance treatments of 'Long COVID-19.'

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.

Association of IFNAR2 rs2236757 and OAS3 rs10735079 Polymorphisms with Susceptibility to COVID-19 Infection and Severity in Palestine

The clinical course and severity of COVID-19 vary among patients. This study aimed to investigate the potential correlation between the gene polymorphisms of the interferon receptor (IFNAR2) rs2236757 and oligoadenylate synthetase 3 (OAS3) rs10735079 with the risk of COVID-19 infection and its severity among Palestinian patients. The study was conducted between April and May 2021 on 154 participants who were divided into three groups: the control group (RT-PCR-negative, n = 52), the community cases group (RT-PCR-positive, n = 70), and the critically ill cases (ICU group; n = 32). The genotyping of the investigated polymorphisms was performed using amplicon-based next-generation sequencing. The genotypes distribution for the IFNAR2 rs2236757 was significantly different among the study groups (P = 0.001), while no statistically significant differences were found in the distribution of genotypes for the OAS3 rs10735079 (P = 0.091). Logistic regression analysis adjusted for possible confounding factors revealed a significant association between the risk allele rs2236757A and critical COVID-19 illness (P  <  0.025). Among all patients, those who carried the rs2236757GA were more likely to have a sore throat (OR, 2.52 (95% CI 1.02-6.24); P = 0.011); the presence of the risk allele rs2236757A was associated with an increased risk to dyspnea (OR, 4.70 (95% CI 1.80-12.27); P  <  0.001), while the rs10735079A carriers were less likely to develop muscle aches (OR, 0.34 (95% CI 0.13-0.88); P = 0.0248) and sore throat (OR, 0.17 (95% CI 0.05-0.55); P  <  0.001). In conclusion, our results revealed that the rs2236757A variant was associated with critical COVID-19 illness and dyspnea, whereas the rs10735079A variant was protective for muscle aches and sore throat.

A large-scale genome-wide cross-trait analysis for the effect of COVID-19 on female-specific cancers

Little is known regarding the long-term adverse effects of COVID-19 on female-specific cancers, nor the shared genetic influences underlying these conditions. We performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture between COVID-19 (infection, hospitalization, and critical illness) with three female-specific cancers (breast cancer (BC), epithelial ovarian cancer (EOC), and endometrial cancer (EC)). We identified significant genome-wide genetic correlations with EC for both hospitalization (r g  = 0.19, p = 0.01) and critical illness (r g  = 0.29, p = 3.00 × 10-4). Mendelian randomization demonstrated no valid association of COVID-19 with any cancer of interest, except for suggestive associations of genetically predicted hospitalization (ORIVW = 1.09, p = 0.04) and critical illness (ORIVW = 1.06, p = 0.04) with EC risk, none withstanding multiple correction. Cross-trait meta-analysis identified 20 SNPs shared between COVID-19 with BC, 15 with EOC, and 5 with EC; and transcriptome-wide association studies revealed multiple shared genes. Findings support intrinsic links underlying these complex traits, highlighting shared mechanisms rather than causal associations.

Prioritization of nasal polyp-associated genes by integrating GWAS and eQTL summary data

Background: Nasal polyps (NP) are benign inflammatory growths of nasal and paranasal sinus mucosa that can substantially impair patients' quality of life by various symptoms such as nasal obstruction, insomnia, and anosmia. NP often relapse even after surgical treatment, and the curative therapy would be challenging without understanding the underlying mechanisms. Genome wide association studies (GWASs) on NP have been conducted; however, few genes that are causally associated with NP have been identified. Methods: We aimed to prioritize NP associated genes for functional follow-up studies using the summary data-based Mendelian Randomization (SMR) and Bayesian colocalization (COLOC) methods to integrate the summary-level data of the GWAS on NP and the expression quantitative trait locus (eQTL) study in blood. We utilized the GWAS data including 5,554 NP cases and 258,553 controls with 34 genome-wide significant loci from the FinnGen consortium (data freeze 8) and the eQTL data from 31,684 participants of predominantly European ancestry from the eQTLGen consortium. Results: The SMR analysis identified several genes including TNFRSF18, CTSK, and IRF1 that were associated with NP due to not linkage but pleiotropy or causality. The COLOC analysis strongly suggested that these genes and the trait of NP were affected by shared causal variants, and thus were colocalized. An enrichment analysis by Metascape suggested that these genes might be involved in the biological process of cellular response to cytokine stimulus. Conclusion: We could prioritize several NP associated genes including TNFRSF18, CTSK, and IRF1 for follow-up functional studies in future to elucidate the underlying disease mechanisms.

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.

An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2

Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Semantic and Population Analysis of the Genetic Targets Related to COVID-19 and Its Association with Genes and Diseases

SARS-CoV-2 is a coronavirus responsible for one of the most serious, modern worldwide pandemics, with lasting and multifaceted effects. By late 2021, SARS-CoV-2 has infected more than 180 million people and has killed more than 3 million. The virus gains entrance to human cells through binding to ACE2 via its surface spike protein and causes a complex disease of the respiratory system, termed COVID-19. Vaccination efforts are being made to hinder the viral spread, and therapeutics are currently under development. Toward this goal, scientific attention is shifting toward variants and SNPs that affect factors of the disease such as susceptibility and severity. This genomic grammar, tightly related to the dark part of our genome, can be explored through the use of modern methods such as natural language processing. We present a semantic analysis of SARS-CoV-2-related publications, which yielded a repertoire of SNPs, genes, and disease ontologies. Population data from the 1000 Genomes Project were subsequently integrated into the pipeline. Data mining approaches of this scale have the potential to elucidate the complex interaction between COVID-19 pathogenesis and host genetic variation; the resulting knowledge can facilitate the management of high-risk groups and aid the efforts toward precision medicine.

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.

Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies

BACKGROUND

To summarize modifiable factors for coronavirus disease 2019 (COVID-19) suggested by Mendelian randomization studies.

METHODS

In this systematic review, we searched PubMed, EMBASE and MEDLINE, from inception to 15 November 2021, for Mendelian randomization studies in English. We selected studies that assessed associations of genetically predicted exposures with COVID-19-related outcomes (severity, hospitalization and susceptibility). Risk of bias of the included studies was evaluated based on the consideration of the three main assumptions for instrumental variable analyses.

RESULTS

We identified 700 studies through systematic search, of which 50 Mendelian randomization studies were included. Included studies have explored a wide range of socio-demographic factors, lifestyle attributes, anthropometrics and biomarkers, predisposition to diseases and druggable targets in COVID-19 risk. Mendelian randomization studies suggested that increases in smoking, obesity and inflammatory factors were associated with higher risk of COVID-19. Predisposition to ischaemic stroke, combined bipolar disorder and schizophrenia, attention-deficit and hyperactivity disorder, chronic kidney disease and idiopathic pulmonary fibrosis was potentially associated with higher COVID-19 risk. Druggable targets, such as higher protein expression of histo-blood group ABO system transferase (ABO), interleukin (IL)-6 and lower protein expression of 2'-5' oligoadenylate synthetase 1 (OAS1) were associated with higher risk of COVID-19. There was no strong genetic evidence supporting the role of vitamin D, glycaemic traits and predisposition to cardiometabolic diseases in COVID-19 risk.

CONCLUSION

This review summarizes modifiable factors for intervention (e.g. smoking, obesity and inflammatory factors) and proteomic signatures (e.g. OAS1 and IL-6) that could help identify drugs for treating COVID-19.

ABO blood group and link to COVID-19: A comprehensive review of the reported associations and their possible underlying mechanisms

ABO blood group is long known to be an influencing factor for the susceptibility to infectious diseases, and many studies have been describing associations between ABO blood types and COVID-19 infection and severity, with conflicting findings. This narrative review aims to summarize the literature regarding associations between the ABO blood group and COVID-19. Blood type O is mostly associated with lower rates of SARS-CoV-2 infection, while blood type A is frequently described as a risk factor. Although results regarding the risk of severe outcomes are more variable, blood type A is the most associated with COVID-19 severity and mortality, while many studies describe O blood type as a protective factor for the disease progression. Furthermore, genetic associations with both the risk of infection and disease severity have been reported for the ABO locus. Some underlying mechanisms have been hypothesized to explain the reported associations, with incipient experimental data. Three major hypotheses emerge: SARS-CoV-2 could carry ABO(H)-like structures in its envelope glycoproteins and would be asymmetrically transmitted due to a protective effect of the ABO antibodies, ABH antigens could facilitate SARS-CoV-2 interaction with the host' cells, and the association of non-O blood types with higher risks of thromboembolic events could confer COVID-19 patients with blood type O a lower risk of severe outcomes. The hypothesized mechanisms would affect distinct aspects of the COVID-19 natural history, with distinct potential implications to the disease transmission and its management.

Serine Protease Inhibitors Restrict Host Susceptibility to SARS-CoV-2 Infections

The coronavirus disease 2019, COVID-19, is a complex disease with a wide range of symptoms from asymptomatic infections to severe acute respiratory syndrome with lethal outcome. Individual factors such as age, sex, and comorbidities increase the risk for severe infections, but other aspects, such as genetic variations, are also likely to affect the susceptibility to SARS-CoV-2 infection and disease severity. Here, we used a human 3D lung cell model based on primary cells derived from multiple donors to identity host factors that regulate SARS-CoV-2 infection. With a transcriptomics-based approach, we found that less susceptible donors show a higher expression level of serine protease inhibitors SERPINA1, SERPINE1, and SERPINE2, identifying variation in cellular serpin levels as restricting host factors for SARS-CoV-2 infection. We pinpoint their antiviral mechanism of action to inhibition of the cellular serine protease, TMPRSS2, thereby preventing cleavage of the viral spike protein and TMPRSS2-mediated entry into the target cells. By means of single-cell RNA sequencing, we further locate the expression of the individual serpins to basal, ciliated, club, and goblet cells. Our results add to the importance of genetic variations as determinants for SARS-CoV-2 susceptibility and suggest that genetic deficiencies of cellular serpins might represent risk factors for severe COVID-19. Our study further highlights TMPRSS2 as a promising target for antiviral intervention and opens the door for the usage of locally administered serpins as a treatment against COVID-19. IMPORTANCE Identification of host factors affecting individual SARS-CoV-2 susceptibility will provide a better understanding of the large variations in disease severity and will identify potential factors that can be used, or targeted, in antiviral drug development. With the use of an advanced lung cell model established from several human donors, we identified cellular protease inhibitors, serpins, as host factors that restrict SARS-CoV-2 infection. The antiviral mechanism was found to be mediated by the inhibition of a serine protease, TMPRSS2, which results in a blockage of viral entry into target cells. Potential treatments with these serpins would not only reduce the overall viral burden in the patients, but also block the infection at an early time point, reducing the risk for the hyperactive immune response common in patients with severe COVID-19.

Host genetic basis of COVID-19: from methodologies to genes

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is having a massive impact on public health, societies, and economies worldwide. Despite the ongoing vaccination program, treating COVID-19 remains a high priority; thus, a better understanding of the disease is urgently needed. Initially, susceptibility was associated with age, sex, and other prior existing comorbidities. However, as these conditions alone could not explain the highly variable clinical manifestations of SARS-CoV-2 infection, the attention was shifted toward the identification of the genetic basis of COVID-19. Thanks to international collaborations like The COVID-19 Host Genetics Initiative, it became possible the elucidation of numerous genetic markers that are not only likely to help in explaining the varied clinical outcomes of COVID-19 patients but can also guide the development of novel diagnostics and therapeutics. Within this framework, this review delineates GWAS and Burden test as traditional methodologies employed so far for the discovery of the human genetic basis of COVID-19, with particular attention to recently emerged predictive models such as the post-Mendelian model. A summary table with the main genome-wide significant genomic loci is provided. Besides, various common and rare variants identified in genes like TLR7, CFTR, ACE2, TMPRSS2, TLR3, and SELP are further described in detail to illustrate their association with disease severity.

Modified Hemagglutination Tests for COVID-19 Serology in Resource-Poor Settings: Ready for Prime-Time?

During the ongoing COVID-19 pandemic, serology has suffered several manufacturing and budget bottlenecks. Kode technology exposes exogenous antigens on the surface of cells; in the case of red blood cells, modified cells are called kodecytes, making antibody-antigen reactions detectable by the old-fashioned hemagglutination test. In this commentary, we review evidence supporting the utility of SARS-CoV-2 Spike kodecytes for clinical diagnostic purposes and serosurveys in resource-poor settings.

Proteomic profiling identifies novel proteins for genetic risk of severe COVID-19: the Atherosclerosis Risk in Communities Study

BACKGROUND

Genome-wide association studies have identified six genetic variants associated with severe COVID-19, yet the mechanisms through which they may affect disease remains unclear. We investigated proteomic signatures related to COVID-19 risk variants rs657152 (ABO), rs10735079 (OAS1/OAS2/OAS3), rs2109069 (DPP9), rs74956615 (TYK2), rs2236757 (IFNAR2) and rs11385942 (SLC6A20/LZTFL1/CCR9/FYCO1/CXCR6/XCR1) as well as their corresponding downstream pathways that may promote severe COVID-19 in risk allele carriers and their potential relevancies to other infection outcomes.

METHODS

A DNA aptamer-based array measured 4870 plasma proteins among 11 471 participants. Linear regression estimated associations between the COVID-19 risk variants and proteins with correction for multiple comparisons, and canonical pathway analysis was conducted. Cox regression assessed associations between proteins identified in the main analysis and risk of incident hospitalized respiratory infections (2570 events) over a 20.7-year follow-up.

RESULTS

The ABO variant rs657152 was associated with 84 proteins in 7241 white participants with 24 replicated in 1671 Black participants. The TYK2 variant rs74956615 was associated with ICAM-1 and -5 in white participants with ICAM-5 replicated in Black participants. Of the 84 proteins identified in the main analysis, seven were significantly associated with incident hospitalized respiratory infections including Ephrin type-A receptor 4 (hazard ratio (HR): 0.87; P = 2.3 × 10-11) and von Willebrand factor type A (HR: 1.17; P = 1.6x10-13).

CONCLUSIONS

Novel proteomics signatures and pathways for COVID-19-related risk variants TYK2 and ABO were identified. A subset of these proteins predicted greater risk of incident hospitalized pneumonia and respiratory infections. Further studies to examine these proteins in COVID-19 patients are warranted.

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.

Country-level factors dynamics and ABO/Rh blood groups contribution to COVID-19 mortality

The identification of factors associated to COVID-19 mortality is important to design effective containment measures and safeguard at-risk categories. In the last year, several investigations have tried to ascertain key features to predict the COVID-19 mortality tolls in relation to country-specific dynamics and population structure. Most studies focused on the first wave of the COVID-19 pandemic observed in the first half of 2020. Numerous studies have reported significant associations between COVID-19 mortality and relevant variables, for instance obesity, healthcare system indicators such as hospital beds density, and bacillus Calmette-Guerin immunization. In this work, we investigated the role of ABO/Rh blood groups at three different stages of the pandemic while accounting for demographic, economic, and health system related confounding factors. Using a machine learning approach, we found that the "B+" blood group frequency is an important factor at all stages of the pandemic, confirming previous findings that blood groups are linked to COVID-19 severity and fatal outcome.

The association of ABO blood group with the asymptomatic COVID-19 cases in India

The COVID-19 pandemic resulted in multiple waves of infection worldwide. The large variations in case fatality rate among different geographical regions suggest that the human susceptibility against this virus varies substantially. Several studies from different parts of the world showed a significant association of ABO blood group and COVID-19 susceptibility. It was demonstrated that individuals with blood group O are at the lower risk of coronavirus infection. To establish the association of ABO blood group in SARS-CoV-2 susceptibility, we for the first time analysed SARS-CoV-2 neutralising antibodies among 509 individuals, collected from three major districts of Eastern Uttar Pradesh region of India. Interestingly, we found neutralising antibodies in a significantly higher percentage of people with blood group AB (0.36) followed by B (0.31), A (0.22) and lowest in people with blood group O (0.11). We further estimated that people with blood group AB are at comparatively higher risk of infection than other blood groups. Thus, among the asymptomatic SARS-CoV-2 recovered people blood group AB has highest, whilst individuals with blood group O has lowest risk of infection.

An immunogenetic view of COVID-19

Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. Immunogenetics can help explain the heterogeneity of susceptibility and protection to the viral infection and disease progression. Here, we review the knowledge developed so far, discussing fundamental genes for triggering the innate and adaptive immune responses associated with a viral infection, especially with the SARS-CoV-2 mechanisms. We emphasize the role of the HLA and KIR genes, discussing what has been uncovered about their role in COVID-19 and addressing methodological challenges of studying these genes. Finally, we comment on questions that arise when studying admixed populations, highlighting the case of Brazil. We argue that the interplay between immunology and an understanding of genetic associations can provide an important contribution to our knowledge of COVID-19.

Host polymorphisms and COVID-19 infection

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). There is growing evidence that host genetics play an important role in COVID-19 severity. Based on current knowledge about the human protein machinery for SARS-CoV-2 entry, the host innate immune response, and virus-host interactions, the potential effects of human genetic polymorphisms, which may contribute to clinical differences in SARS-CoV-2 pathogenesis, may help to determine the individual risk for COVID-19 infection and outcome.

Association between blood groups and COVID-19 outcome in Iranian patients

Aim: Many factors have been speculated to explain the COVID-19 complex clinical phenotype. Due to the inconsistent data published on blood groups and COVID-19, we conducted a study on Iranian patients to further assess this association. Materials & methods: This retrospective study was conducted on data collected from confirmed COVID-19 hospitalized patients during March and December 2020 in a referral hospital for COVID-19, 5 Azar Hospital, Gorgan, north of Iran. A total of 1554 confirmed COVID-19 cases were enrolled in the study with blood group (ABO and Rh), demographic, and clinical data available. Results: Of 1554 patients, 1267 and 287 cases had recovered and deceased (due to COVID-19) outcomes, respectively. Most of the cases had O+ (29.6%), the least number had AB- (0.5%), and most of the deceased cases had O+ blood types (31.4%). Logistic regression analysis revealed that groups A- and B- had higher and groups B+, AB+, O+ and O- had lower odds of death than the A+ group. Conclusion: This study indicates that blood types may be related to the clinical outcome of COVID-19. Further studies with a large cohort for multiple people are required to validate this association.

ABO Blood Types and COVID-19: Spurious, Anecdotal, or Truly Important Relationships? A Reasoned Review of Available Data

Since the emergence of COVID-19, many publications have reported associations with ABO blood types. Despite between-study discrepancies, an overall consensus has emerged whereby blood group O appears associated with a lower risk of COVID-19, while non-O blood types appear detrimental. Two major hypotheses may explain these findings: First, natural anti-A and anti-B antibodies could be partially protective against SARS-CoV-2 virions carrying blood group antigens originating from non-O individuals. Second, O individuals are less prone to thrombosis and vascular dysfunction than non-O individuals and therefore could be at a lesser risk in case of severe lung dysfunction. Here, we review the literature on the topic in light of these hypotheses. We find that between-study variation may be explained by differences in study settings and that both mechanisms are likely at play. Moreover, as frequencies of ABO phenotypes are highly variable between populations or geographical areas, the ABO coefficient of variation, rather than the frequency of each individual phenotype is expected to determine impact of the ABO system on virus transmission. Accordingly, the ABO coefficient of variation correlates with COVID-19 prevalence. Overall, despite modest apparent risk differences between ABO subtypes, the ABO blood group system might play a major role in the COVID-19 pandemic when considered at the population level.