COVID-19 genetic risk variants are associated with expression of multiple genes in diverse immune cell types

Identifying genetic variants associated with chromatin looping and genome function

Here we present a comprehensive HiChIP dataset on naïve CD4 T cells (nCD4) from 30 donors and identify QTLs that associate with genotype-dependent and/or allele-specific variation of HiChIP contacts defining loops between active regulatory regions (iQTLs). We observe a substantial overlap between iQTLs and previously defined eQTLs and histone QTLs, and an enrichment for fine-mapped QTLs and GWAS variants. Furthermore, we describe a distinct subset of nCD4 iQTLs, for which the significant variation of chromatin contacts in nCD4 are translated into significant eQTL trends in CD4 T cell memory subsets. Finally, we define connectivity-QTLs as iQTLs that are significantly associated with concordant genotype-dependent changes in chromatin contacts over a broad genomic region (e.g., GWAS SNP in the RNASET2 locus). Our results demonstrate the importance of chromatin contacts as a complementary modality for QTL mapping and their power in identifying previously uncharacterized QTLs linked to cell-specific gene expression and connectivity.

Interferon-stimulated genes and their antiviral activity against SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic remains an international health problem caused by the recent emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of May 2024, SARS-CoV-2 has caused more than 775 million cases and over 7 million deaths globally. Despite current vaccination programs, infections are still rapidly increasing, mainly due to the appearance and spread of new variants, variations in immunization rates, and limitations of current vaccines in preventing transmission. This underscores the need for pan-variant antivirals and treatments. The interferon (IFN) system is a critical element of the innate immune response and serves as a frontline defense against viruses. It induces a generalized antiviral state by transiently upregulating hundreds of IFN-stimulated genes (ISGs). To gain a deeper comprehension of the innate immune response to SARS-CoV-2, its connection to COVID-19 pathogenesis, and the potential therapeutic implications, this review provides a detailed overview of fundamental aspects of the diverse ISGs identified for their antiviral properties against SARS-CoV-2. It emphasizes the importance of these proteins in controlling viral replication and spread. Furthermore, we explore methodological approaches for the identification of ISGs and conduct a comparative analysis with other viruses. Deciphering the roles of ISGs and their interactions with viral pathogens can help identify novel targets for antiviral therapies and enhance our preparedness to confront current and future viral threats.

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.

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.

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.

Type I interferon pathway genetic variants in severe COVID-19

Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by SARS-CoV-2. According to the World Health Organization (WHO), there have been over 760 million reported cases and over 6 million deaths caused by this disease worldwide. The severity of COVID-19 is based on symptoms presented by the patient and is divided as asymptomatic, mild, moderate, severe, and critical. The manifestations are interconnected with genetic variations. The innate immunity is the quickest response mechanism of an organism against viruses. Type I interferon pathway plays a key role in antiviral responses due to viral replication inhibition in infected cells and adaptive immunity stimulation induced by interferon molecules. Thus, variants in type I interferon pathway's genes are being studied in different COVID-19 manifestations. This review summarizes the role of variants in type I interferon pathway's genes on prognosis and severity progression of COVID-19.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.

Evaluating the effects of circulating inflammatory proteins as drivers and therapeutic targets for severe COVID-19

Objective

The relationships between circulating inflammatory proteins and COVID-19 have been observed in previous cohorts. However, it is not unclear which circulating inflammatory proteins may boost the risk of or protect against COVID-19.

Methods

We performed Mendelian randomization (MR) analysis using GWAS summary result of 91 circulating inflammation-related proteins (N = 14,824) to assess their causal impact on severe COVID-19. The COVID-19 phenotypes encompassed both hospitalized (N = 2,095,324) and critical COVID-19 (N = 1,086,211). Moreover, sensitivity analyses were conducted to evaluate the robustness and reliability.

Results

We found that seven circulating inflammatory proteins confer positive causal effects on severe COVID-19. Among them, serum levels of IL-10RB, FGF-19, and CCL-2 positively contributed to both hospitalized and critical COVID-19 conditions (OR: 1.10~1.16), while the other 4 proteins conferred risk on critical COVID-19 only (OR: 1.07~1.16), including EIF4EBP1, IL-7, NTF3, and LIF. Meanwhile, five proteins exert protective effects against hospitalization and progression to critical COVID-19 (OR: 0.85~0.95), including CXCL11, CDCP1, CCL4/MIP, IFNG, and LIFR. Sensitivity analyses did not support the presence of heterogeneity in the majority of MR analyses.

Conclusions

Our study revealed risk and protective inflammatory proteins for severe COVID-19, which may have vital implications for the treatment of the disease.

Predicting the spread of SARS-CoV-2 variants: An artificial intelligence enabled early detection

During more than 3 years since its emergence, SARS-CoV-2 has shown great ability to mutate rapidly into diverse variants, some of which turned out to be very infectious and have spread throughout the world causing waves of infections. At this point, many countries have already experienced up to six waves of infections. Extensive academic work has focused on the development of models to predict the pandemic trajectory based on epidemiological data, but none has focused on predicting variant-specific spread. Moreover, important scientific literature analyzes the genetic evolution of SARS-CoV-2 variants and how it might functionally affect their infectivity. However, genetic attributes have not yet been incorporated into existing epidemiological modeling that aims to capture infection trajectory. Thus, this study leverages variant-specific genetic characteristics together with epidemiological information to systematically predict the future spread trajectory of newly detected variants. The study describes the analysis of 9.0 million SARS-CoV-2 genetic sequences in 30 countries and identifies temporal characteristic patterns of SARS-CoV-2 variants that caused significant infection waves. Using this descriptive analysis, a machine-learning-enabled risk assessment model has been developed to predict, as early as 1 week after their first detection, which variants are likely to constitute the new wave of infections in the following 3 months. The model's out-of-sample area under the curve (AUC) is 86.3% for predictions after 1 week and 90.8% for predictions after 2 weeks. The methodology described in this paper could contribute more broadly to the development of improved predictive models for variants of other infectious viruses.

T regulatory lymphocytes specific for SARS-CoV-2 display increased functional plasticity

The study of phenotypic and functional characteristics of immune cells involved in host response to SARS-CoV-2 is relevant for understanding COVID-19 pathogenesis and individual differences in disease progression. We have analyzed chemokine receptor expression in SARS-CoV-2-specific CD4+ T lymphocytes from vaccinated donors, and have found an increase of CCR9+ and CCR6+ cells. CCR9+ specific CD4+ cells are enriched in T regulatory (Treg) lymphocytes. These cells specifically show heterogeneous regulatory activity, associated with different profiles of CCR9/CCR6 expression, individual differences in IL-10 and IL-17 production, and variable FoxP3 and Notch4 expression. A higher heterogeneity in FoxP3 is selectively observed in convalescent individuals within vaccinated population. Accordingly, SARS-CoV-2-specific CD4+ lymphocytes from COVID-19 patients are also enriched in CCR9+ and CCR6+ cells. CCR6+ specific Treg lymphocytes are mainly increased in critically ill individuals, indicating a preferential role for these cells in lung injury pathogenesis. We provide experimental evidence for a SARS-CoV-2-specific Treg population with increased plasticity, which may contribute to the differential pathogenic response against SARS-CoV-2 among individuals, and underlie the development of autoimmune conditions following SARS-CoV-2 infection.

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.

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.

Early Transcriptional Responses of Human Nasal Epithelial Cells to Infection with Influenza A and SARS-CoV-2 Virus Differ and Are Influenced by Physiological Temperature

Influenza A (IAV) and SARS-CoV-2 (SCV2) viruses represent an ongoing threat to public health. Both viruses target the respiratory tract, which consists of a gradient of cell types, receptor expression, and temperature. Environmental temperature has been an understudied contributor to infection susceptibility and understanding its impact on host responses to infection could help uncover new insight into severe disease risk factors. As the nasal passageways are the initial site of respiratory virus infection, in this study we investigated the effect of temperature on host responses in human nasal epithelial cells (hNECs) utilizing IAV and SCV2 in vitro infection models. We demonstrate that temperature affected SCV2, but not IAV, viral replicative fitness and that SCV2-infected cultures were slower to mount an infection-induced response, likely due to suppression by the virus. Additionally, we show that that temperature not only changed the basal transcriptomic landscape of epithelial cells, but that it also impacted the response to infection. The induction of interferon and other innate immune responses was not drastically affected by temperature, suggesting that while the baseline antiviral response at different temperatures remained consistent, there may be metabolic or signaling changes that affect how well the cultures were able to adapt to new pressures, such as infection. Finally, we show that hNECs responded differently to IAV and SCV2 infection in ways that give insight into how the virus is able to manipulate the cell to allow for replication and release. Taken together, these data give new insight into the innate immune response to respiratory infections and can assist in identifying new treatment strategies for respiratory infections.

Early transcriptional responses of human nasal epithelial cells to infection with Influenza A and SARS-CoV-2 virus differ and are influenced by physiological temperature

Influenza A (IAV) and SARS-CoV-2 (SCV2) viruses represent an ongoing threat to public health. Both viruses target the respiratory tract, which consists of a gradient of cell types, receptor expression, and temperature. Environmental temperature has been an un-derstudied contributor to infection susceptibility and understanding its impact on host responses to infection could help uncover new insights into severe disease risk factors. As the nasal passageways are the initial site of respiratory virus infection, in this study we investigated the effect of temperature on host responses in human nasal epithelial cells (hNECs) utilizing IAV and SCV2 in vitro infection models. We demonstrate that temperature affects SCV2, but not IAV, viral replicative fitness and that SCV2 infected cultures are slower to mount an infection-induced response, likely due to suppression by the virus. Additionally, we show that that temperature not only changes the basal transcriptomic landscape of epithelial cells, but that it also impacts the response to infection. The induction of interferon and other innate immune responses were not drastically affected by temperature, suggesting that while the baseline antiviral response at different temperatures remains consistent, there may be metabolic or signaling changes that affect how well the cultures are able to adapt to new pressures such as infection. Finally, we show that hNECs respond differently to IAV and SCV2 infection in ways that give insight into how the virus is able to manipulate the cell to allow for replication and release. Taken together, these data give new insight into the innate immune response to respiratory infections and can assist in identifying new treatment strategies for respiratory infections.

JAML immunotherapy targets recently activated tumor-infiltrating CD8+ T cells

Junctional adhesion molecule-like protein (JAML) serves as a co-stimulatory molecule in γδ T cells. While it has recently been described as a cancer immunotherapy target in mice, its potential to cause toxicity, specific mode of action with regard to its cellular targets, and whether it can be targeted in humans remain unknown. Here, we show that JAML is induced by T cell receptor engagement, reveal that this induction is linked to cis-regulatory interactions between the CD3D and JAML gene loci. When compared with other immunotherapy targets plagued by low target specificity and end-organ toxicity, we find JAML to be mostly restricted to and highly expressed by tissue-resident memory CD8+ T cells in multiple cancer types. By delineating the key cellular targets and functional consequences of agonistic anti-JAML therapy in a murine melanoma model, we show its specific mode of action and the reason for its synergistic effects with anti-PD-1.

Genetic Ethnic Differences in Human 2'-5'-Oligoadenylate Synthetase and Disease Associations: A Systematic Review

Recently, several studies have highlighted a skewed prevalence of infectious diseases within the African continent. Furthermore, a growing number of studies have demonstrated unique genetic variants found within the African genome are one of the contributing factors to the disease severity of infectious diseases within Africa. Understanding the host genetic mechanisms that offer protection against infectious diseases provides an opportunity to develop unique therapeutic interventions. Over the past two decades, several studies have linked the 2'-5'-oligoadenylate synthetase (OAS) family with a range of infectious diseases. More recently, the OAS-1 gene has also been associated with disease severity caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which led to a global pandemic. The OAS family serves as an antiviral factor through the interaction with Ribonuclease-Latent (RNase-L). This review explores the genetic variants observed within the OAS genes and the associations with various viral infections and how previously reported ethnic-specific polymorphisms drive clinical significance. This review provides an overview of OAS genetic association studies with a particular focus on viral diseases affecting individuals of African descent.

Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals

Individuals infected with the SARS-CoV-2 virus present with a wide variety of symptoms ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe response to COVID-19. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the genetic predisposition to severe COVID-19 outcomes. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform a locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify four introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. Using reporter assays in the presence/absence of SARS-CoV-2, we find evidence that these variants respond to viral infection. These variants likely drive the locus' impact on severity by modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.

An NMR-Based Model to Investigate the Metabolic Phenoreversion of COVID-19 Patients throughout a Longitudinal Study

After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts.

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 whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection.

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.

ANANASTRA: annotation and enrichment analysis of allele-specific transcription factor binding at SNPs

We present ANANASTRA, https://ananastra.autosome.org, a web server for the identification and annotation of regulatory single-nucleotide polymorphisms (SNPs) with allele-specific binding events. ANANASTRA accepts a list of dbSNP IDs or a VCF file and reports allele-specific binding (ASB) sites of particular transcription factors or in specific cell types, highlighting those with ASBs significantly enriched at SNPs in the query list. ANANASTRA is built on top of a systematic analysis of allelic imbalance in ChIP-Seq experiments and performs the ASB enrichment test against background sets of SNPs found in the same source experiments as ASB sites but not displaying significant allelic imbalance. We illustrate ANANASTRA usage with selected case studies and expect that ANANASTRA will help to conduct the follow-up of GWAS in terms of establishing functional hypotheses and designing experimental verification.

p53/NF-kB Balance in SARS-CoV-2 Infection: From OMICs, Genomics and Pharmacogenomics Insights to Tailored Therapeutic Perspectives (COVIDomics)

SARS-CoV-2 infection affects different organs and tissues, including the upper and lower airways, the lung, the gut, the olfactory system and the eye, which may represent one of the gates to the central nervous system. Key transcriptional factors, such as p53 and NF-kB and their reciprocal balance, are altered upon SARS-CoV-2 infection, as well as other key molecules such as the virus host cell entry mediator ACE2, member of the RAS-pathway. These changes are thought to play a central role in the impaired immune response, as well as in the massive cytokine release, the so-called cytokine storm that represents a hallmark of the most severe form of SARS-CoV-2 infection. Host genetics susceptibility is an additional key side to consider in a complex disease as COVID-19 characterized by such a wide range of clinical phenotypes. In this review, we underline some molecular mechanisms by which SARS-CoV-2 modulates p53 and NF-kB expression and activity in order to maximize viral replication into the host cells. We also face the RAS-pathway unbalance triggered by virus-ACE2 interaction to discuss potential pharmacological and pharmacogenomics approaches aimed at restoring p53/NF-kB and ACE1/ACE2 balance to counteract the most severe forms of SARS-CoV-2 infection.

Colocalization analysis of pancreas eQTLs with risk loci from alcoholic and novel non-alcoholic chronic pancreatitis GWAS suggests potential disease causing mechanisms

BACKGROUND

Previous genome-wide association studies (GWAS) identified genome-wide significant risk loci in chronic pancreatitis and investigated underlying disease causing mechanisms by simple overlaps with expression quantitative trait loci (eQTLs), a procedure which may often result in false positive conclusions.

METHODS

We conducted a GWAS in 584 non-alcoholic chronic pancreatitis (NACP) patients and 6040 healthy controls. Next, we applied Bayesian colocalization analysis of identified genome-wide significant risk loci from both, our recently published alcoholic chronic pancreatitis (ACP) and the novel NACP dataset, with pancreas eQTLs from the GTEx V8 European cohort to prioritize candidate causal genes and extracted credible sets of shared causal variants.

RESULTS

Variants at the CTRC (p = 1.22 × 10^-21) and SPINK1 (p = 6.59 × 10^-47) risk loci reached genome-wide significance in NACP. CTRC risk variants colocalized with CTRC eQTLs in ACP (PP4 = 0.99, PP4/PP3 = 95.51) and NACP (PP4 = 0.99, PP4/PP3 = 95.46). For both diseases, the 95% credible set of shared causal variants consisted of rs497078 and rs545634. CLDN2-MORC4 risk variants colocalized with CLDN2 eQTLs in ACP (PP4 = 0.98, PP4/PP3 = 42.20) and NACP (PP4 = 0.67, PP4/PP3 = 7.18), probably driven by the shared causal variant rs12688220.

CONCLUSIONS

A shared causal CTRC risk variant might unfold its pathogenic effect in ACP and NACP by reducing CTRC expression, while the CLDN2-MORC4 shared causal variant rs12688220 may modify ACP and NACP risk by increasing CLDN2 expression.

Insights into Cardiovascular Defects and Cardiac Epigenome in the Context of COVID-19

Although few in number, studies on epigenome of the heart of COVID-19 patients show that epigenetic signatures such as DNA methylation are significantly altered, leading to changes in expression of several genes. It contributes to pathogenic cardiac phenotypes of COVID-19, e.g., low heart rate, myocardial edema, and myofibrillar disarray. DNA methylation studies reveal changes which likely contribute to cardiac disease through unknown mechanisms. The incidence of severe COVID-19 disease, including hospitalization, requiring respiratory support, morbidity, and mortality, is disproportionately higher in individuals with co-morbidities. This poses unprecedented strains on the global healthcare system. While their underlying conditions make patients more susceptible to severe COVID-19 disease, strained healthcare systems, lack of adequate support, or sedentary lifestyles from ongoing lockdowns have proved detrimental to their underlying health conditions, thus pushing them to severe risk of congenital heart disease (CHD) itself. Prophylactic vaccines against COVID-19 have ushered new hope for CHD. A common connection between COVID-19 and CHD is SARS-CoV-2’s host receptor ACE2, because ACE2 regulates and protects organs, including the heart, in various ways. ACE2 is a common therapeutic target against cardiovascular disease and COVID-19 which damages organs. Hence, this review explores the above regarding CHDs, cardiovascular damage, and cardiac epigenetics, in COVID-19 patients.

Targeting Specific Checkpoints in the Management of SARS-CoV-2 Induced Cytokine Storm

COVID-19-infected patients require an intact immune system to suppress viral replication and prevent complications. However, the complications of SARS-CoV-2 infection that led to death were linked to the overproduction of proinflammatory cytokines known as cytokine storm syndrome. This article reported the various checkpoints targeted to manage the SARS-CoV-2-induced cytokine storm. The literature search was carried out using PubMed, Embase, MEDLINE, and China National Knowledge Infrastructure (CNKI) databases. Journal articles that discussed SARS-CoV-2 infection and cytokine storm were retrieved and appraised. Specific checkpoints identified in managing SARS-CoV-2 induced cytokine storm include a decrease in the level of Nod-Like Receptor 3 (NLRP3) inflammasome where drugs such as quercetin and anakinra were effective. Janus kinase-2 and signal transducer and activator of transcription-1 (JAK2/STAT1) signaling pathways were blocked by medicines such as tocilizumab, baricitinib, and quercetin. In addition, inhibition of interleukin (IL)-6 with dexamethasone, tocilizumab, and sarilumab effectively treats cytokine storm and significantly reduces mortality caused by COVID-19. Blockade of IL-1 with drugs such as canakinumab and anakinra, and inhibition of Bruton tyrosine kinase (BTK) with zanubrutinib and ibrutinib was also beneficial. These agents' overall mechanisms of action involve a decrease in circulating proinflammatory chemokines and cytokines and or blockade of their receptors. Consequently, the actions of these drugs significantly improve respiration and raise lymphocyte count and PaO₂/FiO₂ ratio. Targeting cytokine storms' pathogenesis genetic and molecular apparatus will substantially enhance lung function and reduce mortality due to the COVID-19 pandemic.

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types.