IL10RB as a key regulator of COVID-19 host susceptibility and severity

Retinol Levels and Severity of Patients with COVID-19

The new coronavirus infection represents a serious threat to global health and economies. In this sense, it is paramount to know the nutritional factors that may be related to the prognosis of the disease. Evidence shows that vitamin A may play an important preventive and therapeutic role in supporting respiratory infections as in COVID-19. The aim of our study was to evaluate the association of vitamin A (retinol) status with the prognosis of the disease. A case-control study from a cohort study was conducted in Brazil between May and October 2020. The study population was chosen by convenience, consisting of participants diagnosed with COVID-19. Recruitment was carried out using different approaches, including through dissemination on social media and in four hospitals in the city of Natal/RN, Brazil, recruiting participants from the COVID-19 ward and hospitalized participants who tested positive for the disease. The participants were allocated into two groups according to severity, with a group of mild (n = 88) or critical (n = 106) patients and compared to a control group (selected before the pandemic, n = 46). The extraction of retinol serum was performed and analyzed using the high-performance liquid chromatography method (HPLC). The retinol level was calculated in mmol/L, and levels below 0.7 μmol/L (20 µg/dL) were considered to be a vitamin A deficiency. Our findings suggest that the participants with mild and critical COVID-19 had lower retinol levels compared to the healthy controls (p = 0.03). In addition, milder cases of COVID-19 were associated with increased symptoms and prolonged symptoms after 90 days since the beginning of infection. However, the survival analysis showed no association with higher cases of death among participants with vitamin A deficiency (p = 0.509). More studies are needed to understand how nutritional status, including vitamin A levels, can influence prognosis and is a risk factor for the development of long COVID syndrome.

Translating GWAS Findings to Inform Drug Repositioning Strategies for COVID-19 Treatment

We developed a computational framework that integrates Genome-Wide Association Studies (GWAS) and post-GWAS analyses, designed to facilitate drug repurposing for COVID-19 treatment. The comprehensive approach combines transcriptomic-wide associations, polygenic priority scoring, 3D genomics, viral-host protein-protein interactions, and small-molecule docking. Through GWAS, we identified nine druggable host genes associated with COVID-19 severity and SARS-CoV-2 infection, all of which show differential expression in COVID-19 patients. These genes include IFNAR1, IFNAR2, TYK2, IL10RB, CXCR6, CCR9, and OAS1. We performed an extensive molecular docking analysis of these targets using 553 small molecules derived from five therapeutically enriched categories, namely antibacterials, antivirals, antineoplastics, immunosuppressants, and anti-inflammatories. This analysis, which comprised over 20,000 individual docking analyses, enabled the identification of several promising drug candidates. All results are available via the DockCoV2 database (https://dockcov2.org/drugs/). The computational framework ultimately identified nine potential drug candidates: Peginterferon alfa-2b, Interferon alfa-2b, Interferon beta-1b, Ruxolitinib, Dactinomycin, Rolitetracycline, Irinotecan, Vinblastine, and Oritavancin. While its current focus is on COVID-19, our proposed computational framework can be applied more broadly to assist in drug repurposing efforts for a variety of diseases. Overall, this study underscores the potential of human genetic studies and the utility of a computational framework for drug repurposing in the context of COVID-19 treatment, providing a valuable resource for researchers in this field.

Spatial transcriptomic profiling of coronary endothelial cells in SARS-CoV-2 myocarditis

OBJECTIVES

Our objective was to examine coronary endothelial and myocardial programming in patients with severe COVID-19 utilizing digital spatial transcriptomics.

BACKGROUND

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has well-established links to thrombotic and cardiovascular events. Endothelial cell infection was initially proposed to initiate vascular events; however, this paradigm has sparked growing controversy. The significance of myocardial infection also remains unclear.

METHODS

Autopsy-derived cardiac tissue from control (n = 4) and COVID-19 (n = 8) patients underwent spatial transcriptomic profiling to assess differential expression patterns in myocardial and coronary vascular tissue. Our approach enabled transcriptional profiling in situ with preserved anatomy and unaltered local SARS-CoV-2 expression. In so doing, we examined the paracrine effect of SARS-CoV-2 infection in cardiac tissue.

RESULTS

We observed heterogeneous myocardial infection that tended to colocalize with CD31 positive cells within coronary capillaries. Despite these differences, COVID-19 patients displayed a uniform and unique myocardial transcriptional profile independent of local viral burden. Segmentation of tissues directly infected with SARS-CoV-2 showed unique, pro-inflammatory expression profiles including upregulated mediators of viral antigen presentation and immune regulation. Infected cell types appeared to primarily be capillary endothelial cells as differentially expressed genes included endothelial cell markers. However, there was limited differential expression within the endothelium of larger coronary vessels.

CONCLUSIONS

Our results highlight altered myocardial programming during severe COVID-19 that may in part be associated with capillary endothelial cells. However, similar patterns were not observed in larger vessels, diminishing endotheliitis and endothelial activation as key drivers of cardiovascular events during COVID-19.

CONDENSED ABSTRACT

SARS-CoV-2 is linked to thrombotic and cardiovascular events; however, the mechanism remains uncertain. Our objective was to examine coronary endothelial and myocardial programming in patients with severe COVID-19 utilizing digital spatial transcriptomics. Autopsy-derived coronary arterial and cardiac tissues from control and COVID-19 patients underwent spatial transcriptomic profiling. Our approach enabled transcriptional profiling in situ with preserved anatomy and unaltered local SARS-CoV-2 expression. We observed unique, pro-inflammatory expression profiles among all COVID-19 patients. While heterogeneous viral expression was noted within the tissue, SARS-CoV-2 tended to colocalize with CD31 positive cells within coronary capillaries and was associated with unique expression profiles. Similar patterns were not observed in larger coronary vessels. Our results highlight altered myocardial programming during severe COVID-19 that may in part be associated with capillary endothelial cells. Such results diminish coronary arterial endotheliitis and endothelial activation as key drivers of cardiovascular events during COVID-19 infection.

LIST OF HIGHLIGHTS

SARS-CoV-2 has variable expression patterns within the myocardium of COVID-19 patientsSARS-CoV-2 infection induces a unique myocardial transcriptional programming independent of local viral burdenSARS-CoV-2 myocarditis is predominantly associated with capillaritis, and tissues directly infected with SARS-CoV-2 have unique, pro-inflammatory expression profilesDiffuse endothelial activation of larger coronary vessels was absent, diminishing large artery endotheliitis as a significant contributor to cardiovascular events during COVID-19 infection.

Inflammation and immunity connect hypertension with adverse COVID-19 outcomes

Objectives: To explore the connection of hypertension and severe COVID-19 outcomes. Methods: A total of 68 observational studies recording mortality and/or general severity of COVID-19 were pooled for meta-analyses of the relationship of severe COVID-19 outcomes with hypertension as well as systolic and diastolic blood pressure. Genome-wide cross-trait meta-analysis (GWCTM) was performed to explore the genes linking between hypertension and COVID-19 severity. Results: The results of meta-analysis with the random effect model indicated that pooled risk ratios of hypertension on mortality and severity of COVID-19 were 1.80 [95% confidence interval (CI) 1.54-2.1] and 1.78 (95% confidence interval 1.56-2.04), respectively, although the apparent heterogeneity of the included studies was detected. In subgroup analysis, cohorts of severe and mild patients of COVID-19 assessed in Europe had a significant pooled weighted mean difference of 6.61 mmHg (95% CI 3.66-9.55) with no heterogeneity found (p = 0.26). The genes in the shared signature of hypertension and the COVID-19 severity were mostly expressed in lungs. Analysis of molecular networks commonly affected both by hypertension and by severe COVID-19 highlighted CCR1/CCR5 and IL10RB signaling, as well as Th1 and Th2 activation pathways, and also a potential for a shared regulation with multiple sclerosis. Conclusion: Hypertension is significantly associated with the severe course of COVID-19. Genetic variants within inflammation- and immunity-related genes may affect their expression in lungs and confer liability to both elevated blood pressure and to severe COVID-19.

Integrating 3D genomic and epigenomic data to enhance target gene discovery and drug repurposing in transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) are popular approaches to test for association between imputed gene expression levels and traits of interest. Here, we propose an integrative method PUMICE (Prediction Using Models Informed by Chromatin conformations and Epigenomics) to integrate 3D genomic and epigenomic data with expression quantitative trait loci (eQTL) to more accurately predict gene expressions. PUMICE helps define and prioritize regions that harbor cis-regulatory variants, which outperforms competing methods. We further describe an extension to our method PUMICE +, which jointly combines TWAS results from single- and multi-tissue models. Across 79 traits, PUMICE + identifies 22% more independent novel genes and increases median chi-square statistics values at known loci by 35% compared to the second-best method, as well as achieves the narrowest credible interval size. Lastly, we perform computational drug repurposing and confirm that PUMICE + outperforms other TWAS methods.

Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia

The highly heterogeneous symptomatology and unpredictable progress of COVID-19 triggered unprecedented intensive biomedical research and a number of clinical research projects. Although the pathophysiology of the disease is being progressively clarified, its complexity remains vast. Moreover, some extremely infrequent cases of thrombotic thrombocytopenia following vaccination against SARS-CoV-2 infection have been observed. The present study aimed to map the signaling pathways of thrombocytopenia implicated in COVID-19, as well as in vaccine-induced thrombotic thrombocytopenia (VITT). The biomedical literature database, MEDLINE/PubMed, was thoroughly searched using artificial intelligence techniques for the semantic relations among the top 50 similar words (>0.9) implicated in COVID-19-mediated human infection or VITT. Additionally, STRING, a database of primary and predicted associations among genes and proteins (collected from diverse resources, such as documented pathway knowledge, high-throughput experimental studies, cross-species extrapolated information, automated text mining results, computationally predicted interactions, etc.), was employed, with the confidence threshold set at 0.7. In addition, two interactomes were constructed: i) A network including 119 and 56 nodes relevant to COVID-19 and thrombocytopenia, respectively; and ii) a second network containing 60 nodes relevant to VITT. Although thrombocytopenia is a dominant morbidity in both entities, three nodes were observed that corresponded to genes (AURKA, CD46 and CD19) expressed only in VITT, whilst ADAM10, CDC20, SHC1 and STXBP2 are silenced in VITT, but are commonly expressed in both COVID-19 and thrombocytopenia. The calculated average node degree was immense (11.9 in COVID-19 and 6.43 in VITT), illustrating the complexity of COVID-19 and VITT pathologies and confirming the importance of cytokines, as well as of pathways activated following hypoxic events. In addition, PYCARD, NLP3 and P2RX7 are key potential therapeutic targets for all three morbid entities, meriting further research. This interactome was based on wild-type genes, revealing the predisposition of the body to hypoxia-induced thrombosis, leading to the acute COVID-19 phenotype, the 'long-COVID syndrome', and/or VITT. Thus, common nodes appear to be key players in illness prevention, progression and treatment.