Genetic regulation of OAS1 nonsense-mediated decay underlies association with COVID-19 hospitalization in patients of European and African ancestries

Robust antiviral innate immune response and miRNA regulatory network were identified in ZIKV-infected cells: implications in the pathogenesis of ZIKV infection

Zika virus (ZIKV) infection has emerged as a significant public health concern due to its association with fetal microcephaly and Guillain-Barre syndrome (GBS). Unfortunately, its detailed pathogenesis remains unclear. To better understand how ZIKV evades host antiviral immunity, we analyzed the microarray dataset (GSE98889) of ZIKV-infected primary human brain microvascular endothelial cells (hBMECs) retrieved from the gene expression omnibus (GEO). 160, 1423, 969, 829, and 600 differentially expressed genes (DEGs) were identified at 12, 24, 48, 72, and 216 hours post-ZIKV infection in hBMECs, respectively. Subsequently, 31 common DEGs across all time-points were selected for further analysis. Gene ontology (GO) functional analysis showed these 31 DEGs were mainly involved in the host antiviral innate immune responses. Protein-protein interaction (PPI) network analysis identified 10 hub genes (MX1, OAS1, OAS2, IFI44, IFI44L, IFIT1, IFIT2, IFIT3, IFIH1, and XAF1), which were all interferon-stimulated genes (ISGs) and upregulated. qRT-PCR was used to validate the expression patterns of these 10 hub genes in different ZIKV-infected cell lines. Finally, miRNA-mRNA regulatory network analysis revealed that hsa-miR-129-2-3p, hsa-miR-138-5p, hsa-miR-21-3p, hsa-miR-27a-5p, hsa-miR-449a, and hsa-miR449b-5p were key miRNAs regulating these hub genes. Our study showed that ZIKV infection activated the host innate immune response to restrict ZIKV infection. The common pathways, hub genes, and their regulatory miRNA network offer new insights into virus-host interactions, enhancing our understanding of ZIKV pathogenesis.

Structural basis for OAS2 regulation and its antiviral function

Oligoadenylate synthetase (OAS) proteins are immune sensors for double-stranded RNA and are critical for restricting viruses. OAS2 comprises two OAS domains, only one of which can synthesize 2'-5'-oligoadenylates for RNase L activation. Existing structures of OAS1 provide a model for enzyme activation, but they do not explain how multiple OAS domains discriminate RNA length. Here, we discover that human OAS2 exists in an auto-inhibited state as a zinc-mediated dimer and present a mechanism for RNA length discrimination: the catalytically deficient domain acts as a molecular ruler that prevents autoreactivity to short RNAs. We demonstrate that dimerization and myristoylation localize OAS2 to Golgi membranes and that this is required for OAS2 activation and the restriction of viruses that exploit the endomembrane system for replication, e.g., coronaviruses. Finally, our results highlight the non-redundant role of OAS proteins and emphasize the clinical relevance of OAS2 by identifying a patient with a loss-of-function mutation associated with autoimmune disease.

IFITM3 variants point to a critical role in emergent virus infections

Interferon-induced transmembrane protein 3 (IFITM3) is a cellular protein that restricts numerous viral infections by blocking virus-host membrane fusion. In humans, there are two IFITM3 single nucleotide polymorphisms (SNPs), rs12252-C and rs34481144-A, that decrease IFITM3 activity and have been associated with severe illness following influenza virus infections. Mice lacking IFITM3 show increased influenza severity, supporting this association. However, some studies do not find a consistent link between IFITM3 SNPs and infection severity, causing uncertainty about its role in vivo. Review of the literature indicates that IFITM3 SNPs are primarily associated with increased viral disease in infections with emergent influenza viruses, such as the 2009 H1N1 pandemic virus and zoonotic H7N9 virus. Similarly, IFITM3 SNPs are reported to be risk factors for increased severity in other emergent infections, including SARS-CoV-2, Hantaan virus, and HIV. In contrast, most studies that failed to find an association examined seasonal influenza. We posit that adaptive immune mechanisms, including pre-existing antibodies and memory T cells against seasonally circulating viruses, compensate for IFITM3 deficiencies, therefore masking its role in seasonal influenza. We propose that IFITM3 is most critical in defending against emergent viruses and should be a key focus of public health strategies to prevent the emergence and spread of novel pathogens, with individuals carrying IFITM3 SNPs potentially benefiting from broadened vaccine coverage, avoidance of animal reservoirs, or enhanced masking to protect themselves and the wider population.

Long-read sequencing reveals novel isoform-specific eQTLs and regulatory mechanisms of isoform expression in human B cells

BACKGROUND

Genetic variations linked to changes in gene expression are known as expression quantitative loci (eQTLs). The identification of eQTLs helps to understand the mechanisms governing gene expression. However, prior studies have primarily utilized short-read sequencing techniques, and the analysis of eQTLs on isoforms has been relatively limited.

RESULTS

In this study, we employ long-read sequencing technology (Oxford Nanopore) on B cells from 67 healthy Japanese individuals to explore genetic variations associated with isoform expression levels, referred to as isoform eQTLs (ieQTLs). Our analysis reveals 17,119 ieQTLs, with 70.6% remaining undetected by a gene-level analysis. Additionally, we identify ieQTLs that have significantly different effects on isoform expression levels within a gene. A functional feature analysis demonstrates a significant enrichment of ieQTLs at splice sites and specific histone marks, such as H3K36me3, H3K4me1, H3K4me3, and H3K79me2. Through an experimental validation using genome editing, we observe that a distant genomic region can modulate isoform-specific expression. Moreover, an ieQTL analysis and minigene splicing assays unveils functionally crucial variants in splicing that splicing prediction software did not assign a high prediction score. A comparison with GWAS data reveals a higher number of colocalizations between ieQTLs and GWAS findings compared to gene eQTLs.

CONCLUSIONS

These findings highlight the substantial contribution of ieQTLs identified through long-read analysis in our understanding of the functional implications of genetic variations and the regulatory mechanisms governing isoforms.

Genetic Predictors of Paxlovid Treatment Response: The Role of IFNAR2, OAS1, OAS3, and ACE2 in COVID-19 Clinical Course

Background: This study investigated the role of genetic polymorphisms in IFNAR2, OAS1, OAS3, and ACE2 as predictors of Paxlovid treatment response, specifically examining their influence on the clinical course and laboratory parameters of COVID-19 patients. Methods: We analyzed the impact of polymorphisms in genes associated with the interferon pathway (IFNAR2 rs2236757), antiviral response (OAS1 rs10774671, OAS3 rs10735079), and viral entry (ACE2 rs2074192) in individuals treated with Paxlovid. Results: Our findings suggest that genetic variations in these genes may modulate the immune response and coagulation pathways in the context of Paxlovid treatment during COVID-19 infection. Specifically, the IFNAR2 rs2236757 G allele was associated with alterations in inflammatory and coagulation markers, while polymorphisms in OAS1 and OAS3 influenced coagulation parameters. Furthermore, specific genotypes were linked to changes in clinical parameters such as oxygen saturation, leukocyte count, and liver function markers in Paxlovid-treated patients. Conclusions: These results highlight the potential of considering genetic factors in understanding individual responses to COVID-19 treatment with Paxlovid and informing future personalized approaches.

Genetic and functional analysis of unproductive splicing using LeafCutter2

Alternative splicing commonly generates unproductive mRNA transcripts that harbor premature termination codons 1 , leading to their degradation by nonsense-mediated decay (NMD). These events reduce overall protein expression levels of affected genes, potentially contributing to gene regulation and disease mechanisms. Here, we present LeafCutter2, which enables identification and quantification of unproductive splicing from short-read RNA-seq data. LeafCutter2 requires minimal gene annotations (start and stop codons) to annotate NMD-inducing splicing events, and identifies differential unproductive splicing between groups, providing insights into its contributions to differential gene expression. Moreover, LeafCutter2 enables mapping of unproductive splicing quantitative trait loci (u-sQTLs), which often colocalize with expression QTLs and GWAS loci. Applying LeafCutter2 to RNA-seq data across human and 6 non-human species, we uncovered a broad landscape of unproductive splicing, which varies widely across tissues. Strikingly, we observed a conserved developmental-stage-specific increase in unproductive splicing during testis maturation across all species. In Alzheimer's disease (AD), we analyzed RNA-seq data from the AD Functional Genomics consortium FunGen-xQTL project and identified unproductive splicing events in 18 AD risk genes, including TSPAN14 , PICALM , and CASS4 , likely mediating genetic effects on disease risk. We performed an integrative analysis using gene expression QTLs, protein expression QTLs, and AD GWAS data, showing that unproductive splicing provides unique regulatory insights beyond traditional approaches. Thus, LeafCutter2 represents a powerful tool for understanding the functional impact of alternative splicing on gene expression and disease mechanisms.

Identification of aberrant interferon-stimulated gene associated host responses potentially linked to poor prognosis in COVID-19 during the Omicron wave

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron has demonstrated decreased pathogenicity, yet a few individuals suffer severe pneumonia from coronavirus disease 2019 (COVID-19) infection; the underlying mechanisms are unknown.

METHODS

The present work investigated the role of Interferon-stimulated genes (ISGs) in the occurrence and progression of severe Omicron infection. The expression and dynamic changes of ISGs were assessed using quantitative real-time polymerase chain reaction (qRT-PCR), and the anti-ISG15 autoantibody in infected patients was detected by ELISA. Moreover, we evaluated the correlation of ISGs with disease severity and outcomes by comparing expression of ISGs among each group.

RESULTS

Decreased expression of several ISGs such as IFI6 are potentially linked to increased severity or poor outcomes of Omicron infection. Longitudinal data also demonstrates that the dynamic variation of IFI6 in the Omicron infection phase may be linked to the prognosis of the disease. The increase of anti-ISG15 autoantibody potentially links to the disease progression and poor outcome of patients with high level of ISG15 expression.

CONCLUSIONS

These findings define aberrant Interferon-stimulated gene associated host responses and reveal potential mechanisms and therapeutic targets for Omicron or other viral infection.

Dynamic Gene Attention Focus (DyGAF): Enhancing Biomarker Identification Through Dual-Model Attention Networks

The DyGAF model, which stands for Dynamic Gene Attention Focus, is specifically designed and tailored to address the challenges in biomarker detection, progression reporting of pathogen infection, and disease diagnostics. The DyGAF model introduced a novel dual-model attention-based mechanism within neural networks, combined with machine learning algorithms to enhance the process of biomarker identification. The model transcended traditional diagnostic approaches by meticulously analyzing gene expression data. DyGAF not only identified but also ranked genes based on their significance, revealing a comprehensive list of the top genes essential for disease detection and prognosis. In addition, KEGG pathways, Wiki Pathways, and Gene Ontology-based analyses provided a multileveled evaluation of the genes' roles. In our analyses, we tailored COVID-19 gene expression profile from nasopharyngeal swabs that offer a more nuanced view of the intricate interplay between the host and the virus. The genes ranked by the DyGAF model were compared against those selected by differential expression analysis and random forest feature selection methods for further validation of our model. DyGAF demonstrated its prowess in identifying important biomarkers that could enrich gene ontologies and pathways crucial for elucidating the pathogenesis of COVID-19. Furthermore, DyGAF was also employed for diagnosing COVID-19 patients by classifying gene-expression profiles with an accuracy of 94.23%. Benchmarking against other conventional models revealed DyGAF's superior performance, highlighting its effectiveness in identifying and categorizing COVID-19 cases. In summary, DyGAF model represents a significant advancement in genomic research, providing a more comprehensive and precise tool for identifying key genetic markers and unraveling the complex biological insights of a disease. The DyGAF model is available as a software package at the following link: https://github.com/hiddenntreasure/DyGAF.

Switching of OAS1 splicing isoforms overcomes SNP-derived vulnerability to SARS-CoV-2 infection

BACKGROUND

The SARS-CoV-2 pandemic provided important insights into the relationship between infectious diseases and the human genome. A genomic region encoding the 2'-5'-oligoadenylate synthetase (OAS) family proteins that sense viral genomic RNAs and trigger an antiviral response contains single nucleotide polymorphisms (SNPs) associated with SARS-CoV-2 infection susceptibility. A high-risk SNP identified at the splice acceptor site of OAS1 exon 6-a terminal exon-alters the proportion of various splicing isoforms of OAS1 and its activity. However, the actual causality of this SNP or splicing to infection susceptibility remains unknown.

RESULTS

In this study, it was found that serine-arginine-rich splicing factor 6 (SRSF6) binds to the splice donor site of the human OAS1 exon 5. SRSF6 determines the selected alternative terminal exon when the risk allele disrupts the splice acceptor site. Subsequently, an inhibitor for CDC-like kinase was rationally selected as a candidate splicing modulator. RNA-Seq and RT-PCR analyses revealed that this inhibitor can induce splice switching of OAS1 mRNAs in the human lung adenocarcinoma cell line Calu-3. Under the inhibitor treatment, the cells exhibited reduced SARS-CoV-2 infection rates. Meanwhile, the colonic epithelial cell line Caco-2 expressed non-risk type OAS1 mRNA isoforms that did not undergo splice-switching or demonstrate altered SARS-CoV-2 sensitivity following treatment with the inhibitor.

CONCLUSIONS

These results indicate that a high-risk SNP in OAS1 influences cell susceptibility to SARS-CoV-2 infection by inducing splice-switching at its terminal exon. Additionally, chemical splicing modifiers may prove beneficial in overcoming this genomic vulnerability.

Large-scale cross-trait genetic analysis highlights shared genetic backgrounds of autoimmune diseases

Disorders associated with the immune system burden multiple organs, although the shared biology exists across the diseases. Preceding family-based studies reveal that immune diseases are heritable to varying degrees, providing the basis for immunogenomics. The recent cost reduction in genetic analysis intensively promotes biobank-scale studies and the development of frameworks for statistical genetics. The accumulating multi-layer omics data, including genome-wide association studies (GWAS) and RNA-sequencing at single-cell resolution, enable us to dissect the genetic backgrounds of immune-related disorders. Although autoimmune and allergic diseases are generally categorized into different disease categories, epidemiological studies reveal the high incidence of autoimmune and allergic disease complications, suggesting the shared genetics and biology between the disease categories. Biobank resources and consortia cover multiple immune-related disorders to accumulate phenome-wide associations of genetic variants and enhance researchers to analyze the shared and heterogeneous genetic backgrounds. The emerging post-GWAS and integrative multi-omics analyses provide genetic and biological insights into the multicategorical disease associations.

Alternative Splicing as a Modulator of the Interferon-Gamma Pathway

Interferon-gamma (IFN-γ) is a critical cytokine that plays a pivotal role in immune system regulation. It is a key mediator of both cellular defense mechanisms and antitumor immunity. As the sole member of the type II interferon family, IFN-γ modulates immune responses by activating macrophages, enhancing natural killer cell function, and regulating gene expression across multiple cellular processes. Alternative splicing is a post-transcriptional gene expression regulatory mechanism that generates multiple mature messenger RNAs from a single gene, dramatically increasing proteome diversity without the need of a proportional genome expansion. This process occurs in 90-95% of human genes, with alternative splicing events allowing for the production of diverse protein isoforms that can have distinct-or even opposing-functional properties. Alternative splicing plays a crucial role in cancer immunology, potentially generating tumor neoepitopes and modulating immune responses. However, how alternative splicing affects IFN-γ's activity is still poorly understood. This review explores how alternative splicing regulates the expression and function of both upstream regulators and downstream effectors of IFN-γ, revealing complex mechanisms of gene expression and immune response modulation. Key transcription factors and signaling molecules of the IFN-γ pathway are alternatively spliced, and alternative splicing can dramatically alter IFN-γ signaling, immune cell function, and response to environmental cues. Specific splice variants can enhance or inhibit IFN-γ-mediated immune responses, potentially influencing cancer immunotherapy, autoimmune conditions, and infectious disease outcomes. The emerging understanding of these splicing events offers promising therapeutic strategies for manipulating immune responses through targeted molecular interventions.

Comprehensive mapping of genetic variation at Epromoters reveals pleiotropic association with multiple disease traits

There is growing evidence that a wide range of human diseases and physiological traits are influenced by genetic variation of cis-regulatory elements. We and others have shown that a subset of promoter elements, termed Epromoters, also function as enhancer regulators of distal genes. This opens a paradigm in the study of regulatory variants, as single nucleotide polymorphisms (SNPs) within Epromoters might influence the expression of several (distal) genes at the same time, which could disentangle the identification of disease-associated genes. Here, we built a comprehensive resource of human Epromoters using newly generated and publicly available high-throughput reporter assays. We showed that Epromoters display intrinsic and epigenetic features that distinguish them from typical promoters. By integrating Genome-Wide Association Studies (GWAS), expression Quantitative Trait Loci (eQTLs) and 3D chromatin interactions, we found that regulatory variants at Epromoters are concurrently associated with more disease and physiological traits, as compared with typical promoters. To dissect the regulatory impact of Epromoter variants, we evaluated their impact on regulatory activity by analyzing allelic-specific high-throughput reporter assays and provided reliable examples of pleiotropic Epromoters. In summary, our study represents a comprehensive resource of regulatory variants supporting the pleiotropic role of Epromoters.

The role of candidate genetic polymorphisms in covid-19 susceptibility and outcomes

BACKGROUND

This study aims to investigate the association between candidate host genetic polymorphisms and COVID-19 susceptibility, severity, hospitalization, hypoxia, and their combined effect, measured by the polygenic risk score (PRS).

METHODS

Three hundred and seventy-six Lebanese participants, comprising 151 controls and 225 cases, were included. Clinical data were obtained from questionnaires and medical records. DNA isolated from peripheral blood was genotyped for ACE1 rs1799752, ACE2 rs2074192, TMPRSS2 rs75603675 and OAS1 rs107746771 using TaqMan assays, and for TMPRSS2 rs35074065 using Sanger Sequencing. Candidate genetic variants were analyzed in association with COVID-19 susceptibility, severity, hospitalization and hypoxia, using univariate and multivariate models. PRS constructed from the weighted sum of variants was evaluated in association with COVID-19 outcomes.

RESULTS

In this study, there were no statistically significant differences in the frequencies of candidate variant alleles between cases, controls and within disease outcomes subgroups, after adjustment for confounders. PRS was not associated with COVID-19 susceptibility and hospitalization, it however significantly predicted COVID-19 severity (P = 0.01).

CONCLUSION

This study highlights the importance of genetic testing for key host genes involved in COVID-19 life cycle and eventually measuring the PRS which proves to be an important tool for prognosis assessment in vulnerable individuals, potentially enhancing patient care.

Regulation of protein abundance in normal human tissues

We report a systematic quantification of 10,841 unique proteins from over 700 GTEx samples, representing five human tissues. Sex, age and genetic factors are associated with variation in protein abundance. In total, 1981 cis-protein quantitative trait loci (cis-pQTL) are identified, of which a majority of protein targets have not been assayed in the recent plasma-based proteogenomic studies. Integrating transcriptomic information from matching tissues delineates concordant as well as discordant expression patterns at RNA and protein levels. Juxtaposition of data from different tissues indicates both shared and tissue-specific genetic architecture that underlie protein abundance. Complementing genomic annotation, RNA-based eQTL studies, as well as the recent establishment of plasma-based proteogenomic characterization, tissue-pQTLs shed light on biology underlying genotype-phenotype association of complex traits and diseases.

OAS1: A Protective Mechanism for Alzheimer's Disease? An Exploration of Data and Possible Mechanisms

The immune system and neuroinflammation are now well established in the aetiology of neurodegeneration. Previous studies of transcriptomic and gene association studies have highlighted the potential of the 2'-5' oligoadenylate synthetase 1 (OAS1) to play a role in Alzheimer's disease. OAS1 is a viral response gene, interferon-induced, dsRNA activated enzyme, which binds RNase L to degrade dsRNA, and has been associated with COVID-19 response. This study explores whether a viral defence gene could play a vital role in neurodegeneration pathology. The genotyping of five SNPs across the OAS1 locus was conducted in the Brains for Dementia Research (BDR) Cohort for association with AD. RNA-sequencing data were explored for differences in OAS1 gene expression between phenotypes and genotypes. Finally, levels of dsRNA were measured in control cell lines, prior to and after exposure to amyloid oligomers and in cells harbouring a dementia-relevant mutation. No association of any of the OAS1 SNPs investigated were associated with the AD phenotype in the BDR cohort. However, gene expression data supported the previous observation that the minor allele haplotype was associated with higher levels of the OAS1 gene expression and the presence of an alternative transcript. Further to this, the presence of endogenous dsRNA was found to increase with exposure to amyloid oligomers and in the cell line with a dementia-relevant mutation. The data presented here suggest further exploration of the OAS1 gene in relation to dementia is warranted. Investigations of whether carriers of the protective OAS1 haplotype lower dsRNA presence and in turn lower inflammation and cell death are required to support the role of the gene as a moderator of neurodegeneration.

Integrating Whole Genome and Transcriptome Sequencing to Characterize the Genetic Architecture of Isoform Variation and its Implications for Health and Disease

We created a comprehensive whole blood splice variation quantitative trait locus (sQTL) resource by analyzing isoform expression ratio (isoform-to-gene) in Framingham Heart Study (FHS) participants (discovery: n=2,622; validation: n=1,094) with whole genome (WGS) and transcriptome sequencing (RNA-seq) data. External replication was conducted using WGS and RNA-seq from the Jackson Heart Study (JHS, n=1,020). We identified over 3.5 million cis -sQTL-isoform pairs ( p <5e-8), comprising 1,176,624 cis -sQTL variants and 10,883 isoform transcripts from 4,971 sGenes, with significant change in isoform-to-gene ratio due to allelic variation. We validated 61% of these pairs in the FHS validation sample ( p <1e-4). External validation ( p <1e-4) in JHS for the top 10,000 and 100,000 most significant cis -sQTL-isoform pairs was 88% and 69%, respectively, while overall pairs validated at 23%. For 20% of cis -sQTLs in the FHS discovery sample, allelic variation did not significantly correlate with overall gene expression. sQTLs are enriched in splice donor and acceptor sites, as well as in GWAS SNPs, methylation QTLs, and protein QTLs. We detailed several sentinel cis -sQTLs influencing alternative splicing, with potential causal effects on cardiovascular disease risk. Notably, rs12898397 (T>C) affects splicing of ULK3 , lowering levels of the full-length transcript ENST00000440863.7 and increasing levels of the truncated transcript ENST00000569437.5, encoding proteins of different lengths. Mendelian randomization analysis demonstrated that a lower ratio of the full-length isoform is causally associated with lower diastolic blood pressure and reduced lymphocyte percentages. This sQTL resource provides valuable insights into how transcriptomic variation may influence health outcomes.

MDA5 Is a Major Determinant of Developing Symptoms in Critically Ill COVID-19 Patients

Apart from the skin and mucosal immune barrier, the first line of defense of the human immune system includes MDA5 (ifih1 gene) which acts as a cellular sensor protein for certain viruses including SARS-CoV-2. Upon binding with viral RNA, MDA5 activates cell-intrinsic innate immunity, humoral responses, and MAVS (mitochondrial antiviral signaling). MAVS signaling induces type I and III interferon (IFN) expressions that further induce ISGs (interferon stimulatory genes) expressions to initiate human cell-mediated immune responses and attenuate viral replication. SARS-CoV-2 counteracts by producing NSP1, NSP2, NSP3, NSP5, NSP7, NSP12, ORF3A, ORF9, N, and M protein and directs anti-MDA5 antibody production presumably to antagonize IFN signaling. Furthermore, COVID-19 resembles several diseases that carry anti-MDA5 antibodies and the current COVID-19 vaccines induced anti-MDA5 phenotypes in healthy individuals. GWAS (genome-wide association studies) identified several polymorphisms (SNPs) in the ifih1-ifn pathway genes including rs1990760 in ifih1 that are strongly associated with COVID-19, and the associated risk allele is correlated with reduced IFN production. The genetic association of SNPs in ifih1 and ifih1-ifn pathway genes reinforces the molecular findings of the critical roles of MDA5 in sensing SARS-CoV-2 and subsequently the IFN responses to inhibit viral replication and host immune evasion. Thus, MDA5 or its pathway genes could be targeted for therapeutic development of COVID-19.

Current update on the neurological manifestations of long COVID: more questions than answers

Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting with prolonged or late-onset debilitating sequelae of SARS-CoV-2 infection, colloquially termed long COVID. This narrative review provides an updated synthesis of the latest evidence on the neurological manifestations of long COVID, discussing its clinical phenotypes, underlying pathophysiology, while also presenting the current state of diagnostic and therapeutic approaches. Approximately one-third of COVID-19 survivors experience prolonged neurological sequelae that persist for at least 12-months post-infection, adversely affecting patients' quality of life. Core neurological manifestations comprise fatigue, post-exertional malaise, cognitive impairment, headache, lightheadedness ('brain fog'), sleep disturbances, taste or smell disorders, dysautonomia, anxiety, and depression. Some of these features overlap substantially with those reported in post-intensive-care syndrome, myalgic encephalomyelitis/chronic fatigue syndrome, fibromyalgia, and postural-orthostatic-tachycardia syndrome. Advances in data-driven research utilizing electronic-health-records combined with machine learning and artificial intelligence have propelled the identification of long COVID sub-phenotypes. Furthermore, the evolving definitions reflect the dynamic conceptualization of long COVID in both research and clinical contexts. Although the underlying pathophysiology remains incompletely elucidated, neuroinflammatory responses, endotheliopathy, and metabolic imbalances, rather than direct viral neuroinvasion, are implicated in neurological sequelae. Genetic susceptibility has also emerged as a potential risk factor. While major limitations remain with existing definitions, collaborative strategies to standardize diagnostic approaches are needed. Current therapeutic paradigms advocate for multimodal approaches, integrating pharmacological and non-pharmacological interventions along with comprehensive rehabilitation programs. Although preliminary evidence of therapeutic efficacy has been provided by a number of clinical trials, methodological constraints limit the generalizability of this evidence. Preventive measures, notably vaccination, have proven integral for reducing the global burden of long COVID. Considering the healthcare and socioeconomic repercussions incurred by long COVID worldwide, international collaborative initiatives are warranted to address the remaining challenges in diagnosing and managing patients presenting with neurological sequelae. See also the graphical abstract(Fig. 1).

The Unusual Role of Ribonuclease L in Innate Immunity

Ribonuclease L is an endonuclease that is activated as part of the dsRNA-driven innate immune response. Active RNase L cleaves pathogenic RNAs as a way to eliminate infections. However, there are additional and unexpected ways that RNase L causes changes in the host that promote an immune response and contribute to its role in host defense. Central to these unconventional mechanisms is the observation that RNase L also degrades the mRNA of the host. In turn, mRNA fragments that RNase L generates can be translated. This causes activation of a ribosome collision sensor that leads to downstream signaling and cell death. Additionally, the liberation of RNA binding proteins after RNA decay appears to affect gene expression. In this review, we discuss these and other recent advances that focus on novel and unusual ways RNase L contributes to innate immunity.

OmicPredict: a framework for omics data prediction using ANOVA-Firefly algorithm for feature selection

High-throughput technologies and machine learning (ML), when applied to a huge pool of medical data such as omics data, result in efficient analysis. Recent research aims to apply and develop ML models to predict a disease well in time using available omics datasets. The present work proposed a framework, 'OmicPredict', deploying a hybrid feature selection method and deep neural network (DNN) model to predict multiple diseases using omics data. The hybrid feature selection method is developed using the Analysis of Variance (ANOVA) technique and firefly algorithm. The OmicPredict framework is applied to three case studies, Alzheimer's disease, Breast cancer, and Coronavirus disease 2019 (COVID-19). In the case study of Alzheimer's disease, the framework predicts patients using GSE33000 and GSE44770 dataset. In the case study of Breast cancer, the framework predicts human epidermal growth factor receptor 2 (HER2) subtype status using Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset. In the case study of COVID-19, the framework performs patients' classification using GSE157103 dataset. The experimental results show that DNN model achieved an Area Under Curve (AUC) score of 0.949 for the Alzheimer's (GSE33000 and GSE44770) dataset. Furthermore, it achieved an AUC score of 0.987 and 0.989 for breast cancer (METABRIC) and COVID-19 (GSE157103) datasets, respectively, outperforming Random Forest, Naïve Bayes models, and the existing research.

Functional and dynamic profiling of transcript isoforms reveals essential roles of alternative splicing in interferon response

Type I interferon (IFN-I) plays an important role in the innate immune response through inducing IFN-I-stimulated genes (ISGs). However, how alternative splicing (AS) events, especially over time, affect their function remains poorly understood. We generated an annotation (113,843 transcripts) for IFN-I-stimulated human B cells called isoISG using high-accuracy long-read sequencing data from PacBio Sequel II/IIe. Transcript isoform profiling using isoISG revealed that isoform switching occurred in the early response to IFN-I so that ISGs would gain functional domains (e.g., C4B) or higher protein production (e.g., IRF3). Conversely, isoforms lacking functional domains increased during the late phase of IFN-I response, mainly due to intron retention events. This suggests that isoform switching both triggers and terminates IFN-I responses at the translation and protein levels. Furthermore, genetic variants influencing the isoform ratio of ISGs were associated with immunological and infectious diseases. AS has essential roles in regulating innate immune response and associated diseases.

Genetic variants regulating the immune response improve the prediction of COVID-19 severity provided by clinical variables

The characteristics of the host are crucial in the final outcome of COVID-19. Herein, the influence of genetic and clinical variants in COVID-19 severity was investigated in a total of 1350 patients. Twenty-one single nucleotide polymorphisms of genes involved in SARS-CoV-2 sensing as Toll-like-Receptor 7, antiviral immunity as the type I interferon signalling pathway (TYK2, STAT1, STAT4, OAS1, SOCS) and the vasoactive intestinal peptide and its receptors (VIP/VIPR1,2) were studied. To analyse the association between polymorphisms and severity, a model adjusted by age, sex and different comorbidities was generated by ordinal logistic regression. The genotypes rs8108236-AA (OR 0.12 [95% CI 0.02-0.53]; p = 0.007) and rs280519-AG (OR 0.74 [95% CI 0.56-0.99]; p = 0.03) in TYK2, and rs688136-CC (OR 0.7 [95% CI 0.5-0.99]; p = 0.046) in VIP, were associated with lower severity; in contrast, rs3853839-GG in TLR7 (OR 1.44 [95% CI 1.07-1.94]; p = 0.016), rs280500-AG (OR 1.33 [95% CI 0.97-1.82]; p = 0.078) in TYK2 and rs1131454-AA in OAS1 (OR 1.29 [95% CI 0.95-1.75]; p = 0.110) were associated with higher severity. Therefore, these variants could influence the risk of severe COVID-19.

Genomic insight into COVID-19 severity in MAFLD patients: a single-center prospective cohort study

This study investigated the influence of single nucleotide polymorphisms (SNPs) in genes associated with the interferon pathway (IFNAR2 rs2236757), antiviral response (OAS1 rs10774671, OAS3 rs10735079), and viral entry (ACE2 rs2074192) on COVID-19 severity and their association with nonalcoholic fatty liver disease (MAFLD). We did not observe a significant association between the investigated SNPs and COVID-19 severity. While the IFNAR2 rs2236757 A allele was correlated with higher creatinine levels upon admission and the G allele was correlated with lower band neutrophils upon discharge, these findings require further investigation. The distribution of OAS gene polymorphisms (rs10774671 and rs10735079) did not differ between MAFLD patients and non-MAFLD patients. Our study population's distribution of ACE2 rs2074192 genotypes and alleles differed from that of the European reference population. Overall, our findings suggest that these specific SNPs may not be major contributors to COVID-19 severity in our patient population, highlighting the potential role of other genetic factors and environmental influences.

A genome-wide arrayed CRISPR screen identifies PLSCR1 as an intrinsic barrier to SARS-CoV-2 entry that recent virus variants have evolved to resist

Interferons (IFNs) play a crucial role in the regulation and evolution of host-virus interactions. Here, we conducted a genome-wide arrayed CRISPR knockout screen in the presence and absence of IFN to identify human genes that influence Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. We then performed an integrated analysis of genes interacting with SARS-CoV-2, drawing from a selection of 67 large-scale studies, including our own. We identified 28 genes of high relevance in both human genetic studies of Coronavirus Disease 2019 (COVID-19) patients and functional genetic screens in cell culture, with many related to the IFN pathway. Among these was the IFN-stimulated gene PLSCR1. PLSCR1 did not require IFN induction to restrict SARS-CoV-2 and did not contribute to IFN signaling. Instead, PLSCR1 specifically restricted spike-mediated SARS-CoV-2 entry. The PLSCR1-mediated restriction was alleviated by TMPRSS2 overexpression, suggesting that PLSCR1 primarily restricts the endocytic entry route. In addition, recent SARS-CoV-2 variants have adapted to circumvent the PLSCR1 barrier via currently undetermined mechanisms. Finally, we investigate the functional effects of PLSCR1 variants present in humans and discuss an association between PLSCR1 and severe COVID-19 reported recently.

RNA helicase SKIV2L limits antiviral defense and autoinflammation elicited by the OAS-RNase L pathway

The OAS-RNase L pathway is one of the oldest innate RNA sensing pathways that leads to interferon (IFN) signaling and cell death. OAS recognizes viral RNA and then activates RNase L, which subsequently cleaves both cellular and viral RNA, creating "processed RNA" as an endogenous ligand that further triggers RIG-I-like receptor signaling. However, the IFN response and antiviral activity of the OAS-RNase L pathway are weak compared to other RNA-sensing pathways. Here, we discover that the SKIV2L RNA exosome limits the antiviral capacity of the OAS-RNase L pathway. SKIV2L-deficient cells exhibit remarkably increased interferon responses to RNase L-processed RNA, resulting in heightened antiviral activity. The helicase activity of SKIV2L is indispensable for this function, acting downstream of RNase L. SKIV2L depletion increases the antiviral capacity of OAS-RNase L against RNA virus infection. Furthermore, SKIV2L loss exacerbates autoinflammation caused by human OAS1 gain-of-function mutations. Taken together, our results identify SKIV2L as a critical barrier to OAS-RNase L-mediated antiviral immunity that could be therapeutically targeted to enhance the activity of a basic antiviral pathway.

Multi-omic profiling of pathogen-stimulated primary immune cells

We performed long-read transcriptome and proteome profiling of pathogen-stimulated peripheral blood mononuclear cells (PBMCs) from healthy donors to discover new transcript and protein isoforms expressed during immune responses to diverse pathogens. Long-read transcriptome profiling reveals novel sequences and isoform switching induced upon pathogen stimulation, including transcripts that are difficult to detect using traditional short-read sequencing. Widespread loss of intron retention occurs as a common result of all pathogen stimulations. We highlight novel transcripts of NFKB1 and CASP1 that may indicate novel immunological mechanisms. RNA expression differences did not result in differences in the amounts of secreted proteins. Clustering analysis of secreted proteins revealed a correlation between chemokine (receptor) expression on the RNA and protein levels in C. albicans- and poly(I:C)-stimulated PBMCs. Isoform aware long-read sequencing of pathogen-stimulated immune cells highlights the potential of these methods to identify novel transcripts, revealing a more complex transcriptome landscape than previously appreciated.

The canonical antiviral protein oligoadenylate synthetase 1 elicits antibacterial functions by enhancing IRF1 translation

An important property of the host innate immune response during microbial infection is its ability to control the expression of antimicrobial effector proteins, but how this occurs post-transcriptionally is not well defined. Here, we describe a critical antibacterial role for the classic antiviral gene 2'-5'-oligoadenylate synthetase 1 (OAS1). Human OAS1 and its mouse ortholog, Oas1b, are induced by interferon-γ and protect against cytosolic bacterial pathogens such as Francisella novicida and Listeria monocytogenes in vitro and in vivo. Proteomic and transcriptomic analysis showed reduced IRF1 protein expression in OAS1-deficient cells. Mechanistically, OAS1 binds and localizes IRF1 mRNA to the rough endoplasmic reticulum (ER)-Golgi endomembranes, licensing effective translation of IRF1 mRNA without affecting its transcription or decay. OAS1-dependent translation of IRF1 leads to the enhanced expression of antibacterial effectors, such as GBPs, which restrict intracellular bacteria. These findings uncover a noncanonical function of OAS1 in antibacterial innate immunity.

Endonucleolytic RNA cleavage drives changes in gene expression during the innate immune response

Viral infection triggers several double-stranded RNA (dsRNA) sensors that lead to changes in gene expression in the cell. One of these sensors activates an endonuclease, ribonuclease L (RNase L), that cleaves single-stranded RNA. However, how the resultant widespread RNA fragmentation affects gene expression is not fully understood. Here, we show that this fragmentation induces the ribotoxic stress response via ZAKα, potentially through stalled ribosomes and/or ribosome collisions. The p38 and JNK pathways that are activated as part of this response promote outcomes that inhibit the virus, such as programmed cell death. We also show that RNase L limits the translation of stress-responsive genes. Intriguingly, we found that the activity of the generic endonuclease, RNase A, recapitulates many of the same molecular phenotypes as activated RNase L, demonstrating how widespread RNA cleavage can evoke an antiviral program.

TAFRO Syndrome and COVID-19

TAFRO syndrome is a systemic inflammatory disease characterized by thrombocytopenia and anasarca. It results from hyperinflammation and produces severe cytokine storms. Severe acute respiratory syndrome coronavirus 2, which led to the coronavirus disease 2019 (COVID-19) pandemic, also causes cytokine storms. COVID-19 was reported to be associated with various immune-related manifestations, including multisystem inflammatory syndrome, hemophagocytic syndrome, vasculitis, and immune thrombocytopenia. Although the pathogenesis and complications of COVID-19 have not been fully elucidated, the pathogeneses of excessive immunoreaction after COVID-19 and TAFRO syndrome both involve cytokine storms. Since the COVID-19 pandemic, there have been a few case reports about the onset of TAFRO syndrome after COVID-19 or COVID-19 vaccination. Castleman disease also presents with excessive cytokine production. We reviewed the literature about the association between TAFRO syndrome or Castleman disease and COVID-19 or vaccination against it. While the similarities and differences between the pathogeneses of TAFRO syndrome and COVID-19 have not been investigated previously, the cytokines and genetic factors associated with TAFRO syndrome and COVID-19 were reviewed by examining case reports. Investigation of TAFRO-like manifestations after COVID-19 or vaccination against COVID-19 may contribute to understanding the pathogenesis of TAFRO syndrome.

Three-year outcomes of post-acute sequelae of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes post-acute sequelae of coronavirus disease 2019 (COVID-19) (PASC) in many organ systems. Risks of these sequelae have been characterized up to 2 years after infection, but longer-term follow-up is limited. Here we built a cohort of 135,161 people with SARS-CoV-2 infection and 5,206,835 controls from the US Department of Veterans Affairs who were followed for 3 years to estimate risks of death and PASC. Among non-hospitalized individuals, the increased risk of death was no longer present after the first year of infection, and risk of incident PASC declined over the 3 years but still contributed 9.6 (95% confidence interval (CI): 0.4-18.7) disability-adjusted life years (DALYs) per 1,000 persons in the third year. Among hospitalized individuals, risk of death declined but remained significantly elevated in the third year after infection (incidence rate ratio: 1.29 (95% CI: 1.19-1.40)). Risk of incident PASC declined over the 3 years, but substantial residual risk remained in the third year, leading to 90.0 (95% CI: 55.2-124.8) DALYs per 1,000 persons. Altogether, our findings show reduction of risks over time, but the burden of mortality and health loss remains in the third year among hospitalized individuals.

SARS-CoV-2 Selectively Induces the Expression of Unproductive Splicing Isoforms of Interferon, Class I MHC, and Splicing Machinery Genes

RNA processing is a highly conserved mechanism that serves as a pivotal regulator of gene expression. Alternative processing generates transcripts that can still be translated but lead to potentially nonfunctional proteins. A plethora of respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strategically manipulate the host's RNA processing machinery to circumvent antiviral responses. We integrated publicly available omics datasets to systematically analyze isoform-level expression and delineate the nascent peptide landscape of SARS-CoV-2-infected human cells. Our findings explore a suggested but uncharacterized mechanism, whereby SARS-CoV-2 infection induces the predominant expression of unproductive splicing isoforms in key IFN signaling, interferon-stimulated (ISGs), class I MHC, and splicing machinery genes, including IRF7, HLA-B, and HNRNPH1. In stark contrast, cytokine and chemokine genes, such as IL6 and TNF, predominantly express productive (protein-coding) splicing isoforms in response to SARS-CoV-2 infection. We postulate that SARS-CoV-2 employs an unreported tactic of exploiting the host splicing machinery to bolster viral replication and subvert the immune response by selectively upregulating unproductive splicing isoforms from antigen presentation and antiviral response genes. Our study sheds new light on the molecular interplay between SARS-CoV-2 and the host immune system, offering a foundation for the development of novel therapeutic strategies to combat COVID-19.

Physiological Consequences of Nonsense-Mediated Decay and Its Role in Adaptive Responses

The evolutionarily conserved nonsense-mediated mRNA decay (NMD) pathway is a quality control mechanism that degrades aberrant mRNA containing one or more premature termination codons (PTCs). Recent discoveries indicate that NMD also differentially regulates mRNA from wild-type protein-coding genes despite lacking PTCs. Together with studies showing that NMD is involved in development and adaptive responses that influence health and longevity, these findings point to an expanded role of NMD that adds a new layer of complexity in the post-transcriptional regulation of gene expression. However, the extent of its control, whether different types of NMD play different roles, and the resulting physiological outcomes remain unclear and need further elucidation. Here, we review different branches of NMD and what is known of the physiological outcomes associated with this type of regulation. We identify significant gaps in the understanding of this process and the utility of genetic tools in accelerating progress in this area.

Prevalence of the protective OAS1 rs10774671-G allele against severe COVID-19 in Moroccans: implications for a North African Neanderthal connection

The clinical presentation of COVID-19 shows high variability among individuals, which is partly due to genetic factors. The OAS1/2/3 cluster has been found to be strongly associated with COVID-19 severity. We examined this locus in the Moroccan population for the occurrence of the critical variant rs10774671 and its respective haplotype blocks. The frequency of single-nucleotide polymorphisms (SNPs) in the cluster of OAS immunity genes in 157 unrelated individuals of Moroccan origin was determined using an in-house exome database. OAS1 exon 6 of 71 SARS-CoV-2-positive individuals with asymptomatic/mild disease and 74 with moderate/severe disease was sequenced by the Sanger method. The genotypic, allelic, and haplotype frequencies of three SNPs were compared between these two groups. Finally, males in our COVID-19 series were genotyped for the Berber-specific marker E-M81. The prevalence of the OAS1 rs10774671-G allele in present-day Moroccans was found to be 40.4%, which is similar to that found in Europeans. However, it was found equally in both the Neanderthal GGG haplotype and the African GAC haplotype, with a frequency of 20% each. These two haplotypes, and hence the rs10774671-G allele, were significantly associated with protection against severe COVID-19 (p = 0.034, p = 0.041, and p = 0.008, respectively). Surprisingly, in men with the Berber-specific uniparental markers, the African haplotype was absent, while the prevalence of the Neanderthal haplotype was similar to that in Europeans. The protective rs10774671-G allele of OAS1 was found only in the Neanderthal haplotype in Berbers, the indigenous people of North Africa, suggesting that this region may have served as a stepping-stone for the passage of hominids to other continents.

The Immune Response of OAS1, IRF9, and IFI6 Genes in the Pathogenesis of COVID-19

COVID-19 is characterized by a wide range of clinical manifestations, where aging, underlying diseases, and genetic background are related to worse outcomes. In the present study, the differential expression of seven genes related to immunity, IRF9, CCL5, IFI6, TGFB1, IL1B, OAS1, and TFRC, was analyzed in individuals with COVID-19 diagnoses of different disease severities. Two-step RT-qPCR was performed to determine the relative gene expression in whole-blood samples from 160 individuals. The expression of OAS1 (p < 0.05) and IFI6 (p < 0.05) was higher in moderate hospitalized cases than in severe ones. Increased gene expression of OAS1 (OR = 0.64, CI = 0.52-0.79; p = 0.001), IRF9 (OR = 0.581, CI = 0.43-0.79; p = 0.001), and IFI6 (OR = 0.544, CI = 0.39-0.69; p < 0.001) was associated with a lower risk of requiring IMV. Moreover, TGFB1 (OR = 0.646, CI = 0.50-0.83; p = 0.001), CCL5 (OR = 0.57, CI = 0.39-0.83; p = 0.003), IRF9 (OR = 0.80, CI = 0.653-0.979; p = 0.03), and IFI6 (OR = 0.827, CI = 0.69-0.991; p = 0.039) expression was associated with patient survival. In conclusion, the relevance of OAS1, IRF9, and IFI6 in controlling the viral infection was confirmed.

SARS-CoV-2-infected human airway epithelial cell cultures uniquely lack interferon and immediate early gene responses caused by other coronaviruses

Objectives

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a member of a class of highly pathogenic coronaviruses. The large family of coronaviruses, however, also includes members that cause only mild symptoms, like human coronavirus-229E (HCoV-229E) or OC43 (HCoV-OC43). Unravelling how molecular (and cellular) pathophysiology differs between highly and low pathogenic coronaviruses is important for the development of therapeutic strategies.

Methods

Here, we analysed the transcriptome of primary human bronchial epithelial cells (PBEC), differentiated at the air-liquid interface (ALI) after infection with SARS-CoV-2, SARS-CoV, Middle East Respiratory Syndrome (MERS)-CoV and HCoV-229E using bulk RNA sequencing.

Results

ALI-PBEC were efficiently infected by all viruses, and SARS-CoV, MERS-CoV and HCoV-229E infection resulted in a largely similar transcriptional response. The response to SARS-CoV-2 infection differed markedly as it uniquely lacked the increase in expression of immediate early genes, including FOS, FOSB and NR4A1 that was observed with all other coronaviruses. This finding was further confirmed in publicly available experimental and clinical datasets. Interfering with NR4A1 signalling in Calu-3 lung epithelial cells resulted in a 100-fold reduction in extracellular RNA copies of SARS-CoV-2 and MERS-CoV, suggesting an involvement in virus replication. Furthermore, a lack in induction of interferon-related gene expression characterised the main difference between the highly pathogenic coronaviruses and low pathogenic viruses HCoV-229E and HCoV-OC43.

Conclusion

Our results demonstrate a previously unknown suppression of a host response gene set by SARS-CoV-2 and confirm a difference in interferon-related gene expression between highly pathogenic and low pathogenic coronaviruses.

The antiviral state of the cell: lessons from SARS-CoV-2

In this review, we provide an overview of the intricate host-virus interactions that have emerged from the study of SARS-CoV-2 infection. We focus on the antiviral mechanisms of interferon-stimulated genes (ISGs) and their modulation of viral entry, replication, and release. We explore the role of a selection ISGs, including BST2, CD74, CH25H, DAXX, IFI6, IFITM1-3, LY6E, NCOA7, PLSCR1, OAS1, RTP4, and ZC3HAV1/ZAP, in restricting SARS-CoV-2 infection and discuss the virus's countermeasures. By synthesizing the latest research on SARS-CoV-2 and host antiviral responses, this review aims to provide a deeper understanding of the antiviral state of the cell under SARS-CoV-2 and other viral infections, offering insights for the development of novel antiviral strategies and therapeutics.

Yin and yang of interferons: lessons from the coronavirus disease 2019 (COVID-19) pandemic

The host immune response against severe acute respiratory syndrome coronavirus 2 includes the induction of a group of natural antiviral cytokines called interferons (IFNs). Although originally recognized for their ability to potently counteract infections, the mechanistic functions of IFNs in patients with varying severities of coronavirus disease 2019 (COVID-19) have highlighted a more complex scenario. Cellular and molecular analyses have revealed that timing, location, and subtypes of IFNs produced during severe acute respiratory syndrome coronavirus 2 infection play a major role in determining disease progression and severity. In this review, we summarize what the COVID-19 pandemic has taught us about the protective and detrimental roles of IFNs during the inflammatory response elicited against a new respiratory virus across different ages and its longitudinal consequences in driving the development of long COVID-19.

The inflammatory microenvironment of the lung at the time of infection governs innate control of SARS-CoV-2 replication

SARS-CoV-2 infection leads to vastly divergent clinical outcomes ranging from asymptomatic infection to fatal disease. Co-morbidities, sex, age, host genetics and vaccine status are known to affect disease severity. Yet, how the inflammatory milieu of the lung at the time of SARS-CoV-2 exposure impacts the control of viral replication remains poorly understood. We demonstrate here that immune events in the mouse lung closely preceding SARS-CoV-2 infection significantly impact viral control and we identify key innate immune pathways required to limit viral replication. A diverse set of pulmonary inflammatory stimuli, including resolved antecedent respiratory infections with S. aureus or influenza, ongoing pulmonary M. tuberculosis infection, ovalbumin/alum-induced asthma or airway administration of defined TLR ligands and recombinant cytokines, all establish an antiviral state in the lung that restricts SARS-CoV-2 replication upon infection. In addition to antiviral type I interferons, the broadly inducible inflammatory cytokines TNFα and IL-1 precondition the lung for enhanced viral control. Collectively, our work shows that SARS-CoV-2 may benefit from an immunologically quiescent lung microenvironment and suggests that heterogeneity in pulmonary inflammation that precedes or accompanies SARS-CoV-2 exposure may be a significant factor contributing to the population-wide variability in COVID-19 disease outcomes.

Oligoadenylate synthetase 1 displays dual antiviral mechanisms in driving translational shutdown and protecting interferon production

In response to viral infection, how cells balance translational shutdown to limit viral replication and the induction of antiviral components like interferons (IFNs) is not well understood. Moreover, how distinct isoforms of IFN-induced oligoadenylate synthetase 1 (OAS1) contribute to this antiviral response also requires further elucidation. Here, we show that human, but not mouse, OAS1 inhibits SARS-CoV-2 replication through its canonical enzyme activity via RNase L. In contrast, both mouse and human OAS1 protect against West Nile virus infection by a mechanism distinct from canonical RNase L activation. OAS1 binds AU-rich elements (AREs) of specific mRNAs, including IFNβ. This binding leads to the sequestration of IFNβ mRNA to the endomembrane regions, resulting in prolonged half-life and continued translation. Thus, OAS1 is an ARE-binding protein with two mechanisms of antiviral activity: driving inhibition of translation but also a broader, non-canonical function of protecting IFN expression from translational shutdown.

[Genetic factors associated with long COVID]

INTRODUCTION

The variability in expression and evolution of COVID is not completely explained by clinical factors. In fact, genetic factors play an important role. Moreover, it is unknown whether the genetic factor that contribute to susceptibility and severity are also involved in the onset and evolution of long-COVID. The objective of this review is to gather information from literature to understand which genetic factors are involved in the onset of persistent COVID.

MATERIAL AND METHODS

Systematic review in PubMed and bioRxiv and medRxiv repositories based on MeSH-descriptors and MeSH-terms related to COVID and genetic factors. Using these terms 2715 articles were pooled. An initial screening performed by authors independently, selected 205 articles of interest. A final deeper screening a total of 85 articles were chosen for complete reading and summarized in this review.

RESULTS

Although ACE2 and TMPSS6 are involved in COVID susceptibility, their involvement in long-COVID has not been found. On the other hand, the severity of the disease and the onset of long-COVID has been associated with different genes involved in the inflammatory and immune response. Particularly interesting has been the association found with the FOXP4 locus.

CONCLUSIONS

Although studies on long-COVID are insufficient to fully comprehend the cause, it is clear that the current identified genetic factors do not fully explain the progression and onset of long-COVID. Other factors such as polygenic action, pleiotropic genes, the microbiota and epigenetic changes must be considered and studied.

Polymorphisms of IFN signaling genes and FOXP4 influence the severity of COVID-19

BACKGROUND

The clinical manifestations of COVID-19 range from asymptomatic, mild to moderate, severe, and critical disease. Host genetic variants were recognized to affect the disease severity. However, the genetic landscape differs among various populations. Therefore, we explored the variants associated with COVID-19 severity in the Guangdong population.

METHODS

A total of 314 subjects were selected, of which the severe and critical COVID-19 patients were defined as "cases", and the mild and moderate patients were defined as "control". Twenty-two variants in interferon-related genes and FOXP4 were genotyped using the MassARRAY technology platform.

RESULTS

IFN signaling gene MX1 rs17000900 CA + AA genotype was correlated with a reduced risk of severe COVID-19 in males (P = 0.001, OR = 0.050, 95%CI = 0.008-0.316). The AT haplotype comprised of MX1 rs17000900 and rs2071430 was more likely to protect against COVID-19 severity (P = 6.3E-03). FOXP4 rs1886814 CC genotype (P = 0.001, OR = 3.747, 95%CI = 1.746-8.043) and rs2894439 GA + AA genotype (P = 0.001, OR = 5.703, 95% CI = 2.045-15.903) were correlated with increased risk of severe COVID-19. Haplotype CA comprised of rs1886814 and rs2894439 was found to be correlated with adverse outcomes (P = 7.0E-04). FOXP4 rs1886814 CC (P = 0.0004) and rs2894439 GA + AA carriers had higher neutralizing antibody titers (P = 0.0018). The CA + AA genotype of MX1 rs17000900 tended to be correlated with lower neutralizing antibody titers than CC genotype (P = 0.0663), but the difference was not statistically significant.

CONCLUSION

Our study found a possible association between MX1 and FOXP4 polymorphisms and the severity of COVID-19. Distinguishing high-risk patients who develop severe COVID-19 will provide clues for early intervention and individual treatment strategies.

Molecular Profile of Variants Potentially Associated with Severe Forms of COVID-19 in Amazonian Indigenous Populations

Coronavirus disease 2019 (COVID-19) is an infection caused by SARS-CoV-2. Genome-wide association studies (GWASs) have suggested a strong association of genetic factors with the severity of the disease. However, many of these studies have been completed in European populations, and little is known about the genetic variability of indigenous peoples' underlying infection by SARS-CoV-2. The objective of the study is to investigate genetic variants present in the genes AQP3, ARHGAP27, ELF5L, IFNAR2, LIMD1, OAS1 and UPK1A, selected due to their association with the severity of COVID-19, in a sample of indigenous people from the Brazilian Amazon in order to describe potential new and already studied variants. We performed the complete sequencing of the exome of 64 healthy indigenous people from the Brazilian Amazon. The allele frequency data of the population were compared with data from other continental populations. A total of 66 variants present in the seven genes studied were identified, including a variant with a high impact on the ARHGAP27 gene (rs201721078) and three new variants located in the Amazon Indigenous populations (INDG) present in the AQP3, IFNAR2 and LIMD1 genes, with low, moderate and modifier impact, respectively.

Increased prevalence of the COVID-19 associated Neanderthal mutations in the Central European Roma population

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and subsequent COVID-19 has spread world-wide and become pandemic with about 7 million deaths reported so far. Interethnic variability of the disease has been described, but a significant part of the differences remain unexplained and may be attributable to genetic factors.

AIM

To analyse genetic factors potentially influencing COVID-19 susceptibility and severity in European Roma minority.

SUBJECTS AND METHODS

Two genetic determinants, within OAS-1 (2-prime,5-prime-oligoadenylate synthetase 1, a key protein in the defence against viral infection; it activates RNases that degrade viral RNAs; rs4767027 has been analysed) and LZTFL1 (leucine zipper transcription factor-like 1, expressed in the lung respiratory epithelium; rs35044562 has been analysed) genes were screened in a population-sample of Czech Roma (N = 302) and majority population (N = 2,559).

RESULTS

For both polymorphisms, Roma subjects were more likely carriers of at least one risky allele for both rs4767027-C (p < 0.001) and rs35044562-G (p < 0.00001) polymorphism. There were only 5.3% Roma subjects without at least one risky allele in comparison with 10.1% in the majority population (p < 0.01).

CONCLUSIONS

It is possible that different genetic background plays an important role in increased prevalence of COVID-19 in the Roma minority.

Innate immune responses to RNA: sensing and signaling

Nucleic acids are among the most essential PAMPs (pathogen-associated molecular patterns). Animals have evolved numerous sensors to recognize nucleic acids and trigger immune signaling against pathogen replication, cellular stress and cancer. Many sensor proteins (e.g., cGAS, AIM2, and TLR9) recognize the molecular signature of infection or stress and are responsible for the innate immune response to DNA. Remarkably, recent evidence demonstrates that cGAS-like receptors acquire the ability to sense RNA in some forms of life. Compared with the nucleic-acid sensing by cGAS, innate immune responses to RNA are based on various RNA sensors, including RIG-I, MDA5, ADAR1, TLR3/7/8, OAS1, PKR, NLRP1/6, and ZBP1, via a broad-spectrum signaling axis. Importantly, new advances have brought to light the potential clinical application of targeting these signaling pathways. Here, we highlight the latest discoveries in the field. We also summarize the activation and regulatory mechanisms of RNA-sensing signaling. In addition, we discuss how RNA sensing is tightly controlled in cells and why the disruption of immune homeostasis is linked to disease.

Use of Machine Learning for the Identification and Validation of Immunogenic Cell Death Biomarkers and Immunophenotypes in Coronary Artery Disease

Objective

Immunogenic cell death (ICD) is part of the immune system's response to coronary artery disease (CAD). In this study, we bioinformatically evaluated the diagnostic and therapeutic utility of immunogenic cell death-related genes (IRGs) and their relationship with immune infiltration features in CAD.

Methods

We acquired the CAD-related datasets GSE12288, GSE71226, and GSE120521 from the Gene Expression Omnibus (GEO) database and the IRGs from the GeneCards database. After identifying the immune cell death-related differentially expressed genes (IRDEGs), we developed a risk model and detected immune subtypes in CAD. IRDEGs were identified using least absolute shrinkage and selection operator (LASSO) analysis. Using a nomogram, we confirmed that both the LASSO model and ICD signature genes had good diagnostic performance.

Results

There was a high degree of coincidence and immune representativeness between two CAD groups based on characteristic genes and hub genes. Hub genes were associated with the interaction of neuroactive ligands with receptors and cell adhesion receptors. The two groups differed in terms of adipogenesis, allograft rejection, and apoptosis, as well as the ICD signature and hub gene expression levels. The two CAD-ICD subtypes differed in terms of immune infiltration.

Conclusion

Quantitative real-time PCR (qRT-PCR) correlated CAD with the expression of OAS3, ITGAV, and PIBF1. The ICD signature genes are candidate biomarkers and reference standards for immune grouping in CAD and can be beneficial in precise immune-targeted therapy.

Innate Immune Activation and Mitochondrial ROS Invoke Persistent Cardiac Conduction System Dysfunction after COVID-19

Background

Cardiac risk rises during acute SARS-CoV-2 infection and in long COVID syndrome in humans, but the mechanisms behind COVID-19-linked arrhythmias are unknown. This study explores the acute and long term effects of SARS-CoV-2 on the cardiac conduction system (CCS) in a hamster model of COVID-19.

Methods

Radiotelemetry in conscious animals was used to non-invasively record electrocardiograms and subpleural pressures after intranasal SARS-CoV-2 infection. Cardiac cytokines, interferon-stimulated gene expression, and macrophage infiltration of the CCS, were assessed at 4 days and 4 weeks post-infection. A double-stranded RNA mimetic, polyinosinic:polycytidylic acid (PIC), was used in vivo and in vitro to activate viral pattern recognition receptors in the absence of SARS-CoV-2 infection.

Results

COVID-19 induced pronounced tachypnea and severe cardiac conduction system (CCS) dysfunction, spanning from bradycardia to persistent atrioventricular block, although no viral protein expression was detected in the heart. Arrhythmias developed rapidly, partially reversed, and then redeveloped after the pulmonary infection was resolved, indicating persistent CCS injury. Increased cardiac cytokines, interferon-stimulated gene expression, and macrophage remodeling in the CCS accompanied the electrophysiological abnormalities. Interestingly, the arrhythmia phenotype was reproduced by cardiac injection of PIC in the absence of virus, indicating that innate immune activation was sufficient to drive the response. PIC also strongly induced cytokine secretion and robust interferon signaling in hearts, human iPSC-derived cardiomyocytes (hiPSC-CMs), and engineered heart tissues, accompanied by alterations in electrical and Ca 2+ handling properties. Importantly, the pulmonary and cardiac effects of COVID-19 were blunted by in vivo inhibition of JAK/STAT signaling or by a mitochondrially-targeted antioxidant.

Conclusions

The findings indicate that long term dysfunction and immune cell remodeling of the CCS is induced by COVID-19, arising indirectly from oxidative stress and excessive activation of cardiac innate immune responses during infection, with implications for long COVID Syndrome.

Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Introduction

The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood.

Methods

To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs.

Results

A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol.

Conclusion

This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.

Circulating miRNA profiles in COVID-19 patients and meta-analysis: implications for disease progression and prognosis

We compared circulating miRNA profiles of hospitalized COVID-positive patients (n = 104), 27 with acute respiratory distress syndrome (ARDS) and age- and sex-matched healthy controls (n = 18) to identify miRNA signatures associated with COVID and COVID-induced ARDS. Meta-analysis incorporating data from published studies and our data was performed to identify a set of differentially expressed miRNAs in (1) COVID-positive patients versus healthy controls as well as (2) severe (ARDS+) COVID vs moderate COVID. Gene ontology enrichment analysis of the genes these miRNAs interact with identified terms associated with immune response, such as interferon and interleukin signaling, as well as viral genome activities associated with COVID disease and severity. Additionally, we observed downregulation of a cluster of miRNAs located on chromosome 14 (14q32) among all COVID patients. To predict COVID disease and severity, we developed machine learning models that achieved AUC scores between 0.81-0.93 for predicting disease, and between 0.71-0.81 for predicting severity, even across diverse studies with different sample types (plasma versus serum), collection methods, and library preparations. Our findings provide network and top miRNA feature insights into COVID disease progression and contribute to the development of tools for disease prognosis and management.