Whole-genome sequencing reveals host factors underlying critical COVID-19

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.

PLSCR1 suppresses SARS-CoV-2 infection by downregulating cell surface ACE2

Type I interferons exert their antiviral effects against SARS-CoV-2 by inducing the expression of interferon-stimulated genes (ISGs), including but not limited to LY6E, CH25H, IFITM2/3, and IFIH1. However, the antiviral effect and underlying mechanisms of action of most ISGs in SARS-CoV-2 infection are not yet fully understood. By screening 109 ISG-knockout cell lines, we identify that phospholipid scramblase 1 (PLSCR1), an interferon-inducible protein, acts as a crucial restriction factor against SARS-CoV-2 infection. Cells lacking PLSCR1 are highly susceptible to SARS-CoV-2 infection. Conversely, overexpression of PLSCR1 inhibits SARS-CoV-2 infection. Depletion of PLSCR1 enhances cellular entry of both pseudotyped and authentic SARS-CoV-2. Mechanistically, PLSCR1 inhibits SARS-CoV-2 entry by specifically downregulating plasma membrane expression of ACE2, the virus's receptor, without affecting the overall levels of ACE2 within the cell. As such, we unraveled previously unappreciated mechanisms by which PLSCR1 exerts its restrictive effect on SARS-CoV-2. These data provide new insights into the interplay between host innate antiviral immunity and SARS-CoV-2 and shed light on novel antiviral therapeutics.

IMPORTANCE

Phospholipid scramblase 1 (PLSCR1) has been identified as a critical host restriction factor against SARS-CoV-2 infection. In this study, we demonstrated that PLSCR1 inhibited SARS-CoV-2 entry by downregulating the plasma membrane expression of ACE2, the primary receptor for viral entry. Our findings elucidate a novel host-pathogen interaction that not only deepens our understanding of the innate immune response to SARS-CoV-2 but offers potential strategies for therapeutic interventions against COVID-19.

Single-cell transcriptome-wide Mendelian randomization and colocalization reveals immune-mediated regulatory mechanisms and drug targets for COVID-19

BACKGROUND

COVID-19 continues to show long-term impacts on our health. Limited effective immune-mediated antiviral drugs have been launched.

METHODS

We conducted a Mendelian randomization (MR) and colocalization analysis using 26,597 single-cell expression quantitative trait loci (sc-eQTL) to proxy effects of expressions of 16,597 genes in 14 peripheral blood immune cells and tested them against four COVID-19 outcomes from COVID-19 Genetic Housing Initiative GWAS meta-analysis Round 7. We also carried out additional validations including colocalization, linkage disequilibrium check and host-pathogen interactome predictions. We integrated MR findings with clinical trial evidence from several drug gene related databases to identify drugs with repurposing potential. Finally, we developed a tier system and identified immune-cell-based prioritized drug targets for COVID-19.

FINDINGS

We identified 132 putative causal genes in 14 immune cells (343 MR associations) for COVID-19, with 58 genes that were not reported previously. 145 (73%) gene-COVID-19 pairs showed effects on COVID-19 in only one immune cell type, which implied widespread immune-cell specific effects. For pathway analyses, we found the putative causal genes were enriched in natural killer (NK) recruiting cells but de-enriched in NK cells. Using a deep learning model, we found 107 (81%) of the putative causal genes (41 novel genes) were predicted to interact with SARS-COV-2 proteins. Integrating the above evidence with drug trial information, we developed a tier system and prioritized 37 drug targets for COVID-19.

INTERPRETATION

Our study showcased the central role of immune-mediated regulatory mechanisms for COVID-19 and prioritized drug targets that might inform interventions for viral infectious diseases.

FUNDING

This work was supported by grants from the National Key Research and Development Program of China (2022YFC2505203).

Advancing health and fostering community involvement in medical research through the Genes & Health study

The Genes & Health study, an initiative focused on British-Pakistani and British-Bangladeshi volunteers, is at the forefront of diversifying genetic research and driving scientific innovation. Here, we explore how this study has propelled scientific advancements and positively impacted communities, emphasizing its collaborative ethos, dedication to societal needs, and accomplishments.

Genetic Variants in Genes Related to Lung Function and Interstitial Lung Diseases Are Associated with Worse Outcomes in Severe COVID-19 and Lung Performance in the Post-COVID-19 Condition

Genetic variants related to susceptibility to chronic respiratory conditions such as interstitial lung disease (ILD) could share critical pathways in the pathogenesis of COVID-19 and be implicated in COVID-19 outcomes and post-COVID-19. We aimed to identify the participation of genetic variants in lung function and ILD genes in severe COVID-19 outcomes and post-COVID-19 condition. We studied 936 hospitalized patients with COVID-19. The requirement of invasive mechanical ventilation (IMV) and the acute respiratory distress syndrome (ARDS) classification were considered. The mortality was assessed as the in-hospital death. The post-COVID-19 group included 102 patients evaluated for pulmonary function tests four times during the year after discharge. Five variants (FAM13A rs2609255, DSP rs2076295, TOLLIP rs111521887, TERT rs2736100, and THSD4 rs872471) were genotyped using TaqMan assays. A multifactor dimensionality reduction method (MDR) was performed for epistasis estimation. The TERT rs2736100 and THSD4 rs872471 variants were associated with differential risk for ARDS severity (moderate vs. severe, CC + CA, p = 0.044, OR = 0.66, 95% CI = 0.44-0.99; and GG p = 0.034, OR = 2.22, 95% CI = 1.04-4.72, respectively). These variants and FAM13A rs2609255 were also related to pulmonary function post-COVID-19. The MDR analysis showed differential epistasis and correlation of the genetic variants included in this study. The well-known variants in recognized genes related to pulmonary function worsening and interstitial disorders are related to the severity and mortality of COVID-19 and lung performance in the post-COVID-19 condition.

Analysis-ready VCF at Biobank scale using Zarr

Background

Variant Call Format (VCF) is the standard file format for interchanging genetic variation data and associated quality control metrics. The usual row-wise encoding of the VCF data model (either as text or packed binary) emphasises efficient retrieval of all data for a given variant, but accessing data on a field or sample basis is inefficient. Biobank scale datasets currently available consist of hundreds of thousands of whole genomes and hundreds of terabytes of compressed VCF. Row-wise data storage is fundamentally unsuitable and a more scalable approach is needed.

Results

Zarr is a format for storing multi-dimensional data that is widely used across the sciences, and is ideally suited to massively parallel processing. We present the VCF Zarr specification, an encoding of the VCF data model using Zarr, along with fundamental software infrastructure for efficient and reliable conversion at scale. We show how this format is far more efficient than standard VCF based approaches, and competitive with specialised methods for storing genotype data in terms of compression ratios and single-threaded calculation performance. We present case studies on subsets of three large human datasets (Genomics England: n=78,195; Our Future Health: n=651,050; All of Us: n=245,394) along with whole genome datasets for Norway Spruce (n=1,063) and SARS-CoV-2 (n=4,484,157). We demonstrate the potential for VCF Zarr to enable a new generation of high-performance and cost-effective applications via illustrative examples using cloud computing and GPUs.

Conclusions

Large row-encoded VCF files are a major bottleneck for current research, and storing and processing these files incurs a substantial cost. The VCF Zarr specification, building on widely-used, open-source technologies has the potential to greatly reduce these costs, and may enable a diverse ecosystem of next-generation tools for analysing genetic variation data directly from cloud-based object stores, while maintaining compatibility with existing file-oriented workflows.

Characterizing temporal and global host innate immune responses against SARS-CoV-1 and -2 infection in pathologically relevant human lung epithelial cells

Severe acute respiratory syndrome coronavirus-1 (SARS-CoV-1) and -2 (SARS-CoV-2) are beta-coronaviruses (β-CoVs) that have caused significant morbidity and mortality worldwide. Therefore, a better understanding of host responses to β-CoVs would provide insights into the pathogenesis of these viruses to identify potential targets for medical countermeasures. In this study, our objective is to use a systems biology approach to explore the magnitude and scope of innate immune responses triggered by SARS-CoV-1 and -2 infection over time in pathologically relevant human lung epithelial cells (Calu-3/2B4 cells). Total RNA extracted at 12, 24, and 48 hours after β-CoVs or mock infection of Calu-3/2B4 cells were subjected to RNA sequencing and functional enrichment analysis to select genes whose expressions were significantly modulated post-infection. The results demonstrate that SARS-CoV-1 and -2 stimulate similar yet distinct innate antiviral signaling pathways in pathologically relevant human lung epithelial cells. Furthermore, we found that many genes related to the viral life cycle, interferons, and interferon-stimulated genes (ISGs) were upregulated at multiple time points. Based on their profound modulation upon infection by SARS-CoV-1, SARS-CoV-2, and Omicron BA.1, four ISGs, i.e., bone marrow stromal cell antigen 2 (BST2), Z-DNA Binding Protein 1 (ZBP1), C-X-C Motif Chemokine Ligand 11 (CXCL11), and Interferon Induced Transmembrane Protein 1 (IFITM1), were identified as potential drug targets against β-CoVs. Our findings suggest that these genes affect both pathogens directly and indirectly through the innate immune response, making them potential targets for host-directed antivirals. Altogether, our results demonstrate that SARS-CoV-1 and SARS-CoV-2 infection induce differential effects on host innate immune responses.

Context-specific eQTLs provide deeper insight into causal genes underlying shared genetic architecture of COVID-19 and idiopathic pulmonary fibrosis

Most genetic variants identified through genome-wide association studies (GWASs) are suspected to be regulatory in nature, but only a small fraction colocalize with expression quantitative trait loci (eQTLs, variants associated with expression of a gene). Therefore, it is hypothesized but largely untested that integration of disease GWAS with context-specific eQTLs will reveal the underlying genes driving disease associations. We used colocalization and transcriptomic analyses to identify shared genetic variants and likely causal genes associated with critically ill COVID-19 and idiopathic pulmonary fibrosis. We first identified five genome-wide significant variants associated with both diseases. Four of the variants did not demonstrate clear colocalization between GWAS and healthy lung eQTL signals. Instead, two of the four variants colocalized only in cell type- and disease-specific eQTL datasets. These analyses pointed to higher ATP11A expression from the C allele of rs12585036, in monocytes and in lung tissue from primarily smokers, which increased risk of idiopathic pulmonary fibrosis (IPF) and decreased risk of critically ill COVID-19. We also found lower DPP9 expression (and higher methylation at a specific CpG) from the G allele of rs12610495, acting in fibroblasts and in IPF lungs, and increased risk of IPF and critically ill COVID-19. We further found differential expression of the identified causal genes in diseased lungs when compared to non-diseased lungs, specifically in epithelial and immune cell types. These findings highlight the power of integrating GWASs, context-specific eQTLs, and transcriptomics of diseased tissue to harness human genetic variation to identify causal genes and where they function during multiple diseases.

Human genetic and immunological determinants of SARS-CoV-2 infection and multisystem inflammatory syndrome in children

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces pneumonia and acute respiratory failure in coronavirus disease 2019 (COVID-19) patients with inborn errors of immunity to type I interferon (IFN-I). The impact of SARS-CoV-2 infection varies widely, ranging from mild respiratory symptoms to life-threatening illness and organ failure, with a higher incidence in men than in women. Approximately 3-5% of critical COVID-19 patients under 60 and a smaller percentage of elderly patients exhibit genetic defects in IFN-I production, including X-chromosome-linked TLR7 and autosomal TLR3 deficiencies. Around 15-20% of cases over 70 years old, and a smaller percentage of younger patients, present with preexisting autoantibodies neutralizing type I interferons. Additionally, innate errors affecting the control of the response to type I interferon have been associated with pediatric multisystem inflammatory syndrome (MIS-C). Several studies have described rare errors of immunity, such as XIAP deficiency, CYBB, SOCS1, OAS1/2, and RNASEL, as underlying factors in MIS-C susceptibility. However, further investigations in expanded patient cohorts are needed to validate these findings and pave the way for new genetic approaches to MIS-C. This review aims to present recent evidence from the scientific literature on genetic and immunological abnormalities predisposing individuals to critical SARS-CoV-2 infection through IFN-I. We will also discuss multisystem inflammatory syndrome in children (MIS-C). Understanding the immunological mechanisms and pathogenesis of severe COVID-19 may inform personalized patient care and population protection strategies against future serious viral infections.

Patterns of population structure and genetic variation within the Saudi Arabian population

The Arabian Peninsula is considered the initial site of historic human migration out of Africa. The modern-day indigenous Arabians are believed to be the descendants who remained from the ancient split of the migrants into Eurasia. Here, we investigated how the population history and cultural practices such as endogamy have shaped the genetic variation of the Saudi Arabians. We genotyped 3,352 individuals and identified twelve genetic sub-clusters that corresponded to the geographical distribution of different tribal regions, differentiated by distinct components of ancestry based on comparisons to modern and ancient DNA references. These sub-clusters also showed variation across ranges of the genome covered in runs of homozygosity, as well as differences in population size changes over time. Using 25,488,981 variants found in whole genome sequencing data (WGS) from 302 individuals, we found that the Saudi tend to show proportionally more deleterious alleles than neutral alleles when compared to Africans/African Americans from gnomAD (e.g. a 13% increase of deleterious alleles annotated by AlphaMissense between 0.5 - 5% frequency in Saudi, compared to 7% decrease of the benign alleles; P < 0.001). Saudi sub-clusters with greater inbreeding and lower effective population sizes showed greater enrichment of deleterious alleles as well. Additionally, we found that approximately 10% of the variants discovered in our WGS data are not observed in gnomAD; these variants are also enriched with deleterious annotations. To accelerate studying the population-enriched deleterious alleles and their health consequences in this population, we made available the allele frequency estimates of 25,488,981 variants discovered in our samples. Taken together, our results suggest that Saudi's population history impacts its pattern of genetic variation with potential consequences to the population health. It further highlights the need to sequence diverse and unique populations so to provide a foundation on which to interpret medical- and pharmaco- genomic findings from these populations.

Mucosal immune response in biology, disease prevention and treatment

The mucosal immune system, as the most extensive peripheral immune network, serves as the frontline defense against a myriad of microbial and dietary antigens. It is crucial in preventing pathogen invasion and establishing immune tolerance. A comprehensive understanding of mucosal immunity is essential for developing treatments that can effectively target diseases at their entry points, thereby minimizing the overall impact on the body. Despite its importance, our knowledge of mucosal immunity remains incomplete, necessitating further research. The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has underscored the critical role of mucosal immunity in disease prevention and treatment. This systematic review focuses on the dynamic interactions between mucosa-associated lymphoid structures and related diseases. We delve into the basic structures and functions of these lymphoid tissues during disease processes and explore the intricate regulatory networks and mechanisms involved. Additionally, we summarize novel therapies and clinical research advances in the prevention of mucosal immunity-related diseases. The review also addresses the challenges in developing mucosal vaccines, which aim to induce specific immune responses while maintaining tolerance to non-pathogenic microbes. Innovative therapies, such as nanoparticle vaccines and inhalable antibodies, show promise in enhancing mucosal immunity and offer potential for improved disease prevention and treatment.

Potential associations of selected polymorphic genetic variants with COVID-19 disease susceptibility and severity

In this study, we analyzed the potential associations of selected laboratory and anamnestic parameters, as well as 12 genetic polymorphisms (SNPs), with clinical COVID-19 occurrence and severity in 869 hospitalized patients. The SNPs analyzed by qPCR were selected based on population-wide genetic (GWAS) data previously indicating association with the severity of COVID-19, and additional SNPs that have been shown to be important in cellular processes were also examined. We confirmed the associations of COVID-19 with pre-existing diabetes and found an unexpected association between less severe disease and the loss of smell and taste. Regarding the genetic polymorphisms, a higher allele frequency of the LZTFL1 and IFNAR2 minor variants significantly correlated with greater COVID-19 disease susceptibility (hospitalization) and severity, and a similar tendency was observed for the RAVER1 and the MUC5B variants. Interestingly, the ATP2B4 minor haplotype, protecting against malaria, correlated with an increased disease susceptibility, while in diabetic patients disease susceptibility was lower in the presence of a reduced-function ABCG2 transporter variant. Our current results, which should be reinforced by larger studies, indicate that together with laboratory and anamnestic parameters, genetic polymorphisms may have predictive value for the clinical occurrence and severity of COVID-19.

Tofacitinib Mitigates the Increased SARS-CoV-2 Infection Susceptibility Caused by an IBD Risk Variant in the PTPN2 Gene

BACKGROUND & AIMS

Coronavirus disease (COVID-19), caused by severe acquired respiratory syndrome-Coronavirus-2 (SARS-CoV-2), triggered a global pandemic with severe medical and socioeconomic consequences. Although fatality rates are higher among the elderly and those with underlying comorbidities, host factors that promote susceptibility to SARS-CoV-2 infection and severe disease are poorly understood. Although individuals with certain autoimmune/inflammatory disorders show increased susceptibility to viral infections, there is incomplete knowledge of SARS-CoV-2 susceptibility in these diseases. The aim of our study was to investigate whether the autoimmunity risk gene, PTPN2, which also confers elevated risk to develop inflammatory bowel disease, affects susceptibility to SARS-CoV-2 viral uptake.

METHODS

Using samples from PTPN2 genotyped patients with inflammatory bowel disease, PTPN2-deficient mice, and human intestinal and lung epithelial cell lines, we investigated how PTPN2 affects expression of the SARS-CoV-2 receptor angiotensin converting enzyme 2 (ACE2), and uptake of virus-like particles expressing the SARS-CoV2 spike protein and live SARS-CoV-2 virus.

RESULTS

We report that the autoimmune PTPN2 loss-of-function risk variant rs1893217 promotes expression of the SARS-CoV-2 receptor, ACE2, and increases cellular entry of SARS-CoV-2 spike protein and live virus. Elevated ACE2 expression and viral entry were mediated by increased Janus kinase-signal transducers and activators of transcription signaling and were reversed by the Janus kinase inhibitor, tofacitinib.

CONCLUSION

Collectively, our findings uncover a novel risk biomarker for increased expression of the SARS-CoV-2 receptor and viral entry, and identify a clinically approved therapeutic agent to mitigate this risk.

PLASMA PROTEOME, METABOLOME MENDELIAN RANDOMIZATION IDENTIFIES SEPSIS THERAPEUTIC TARGETS

ABSTRACT

Background : The interrelation between the plasma proteome and plasma metabolome with sepsis presents a multifaceted dynamic that necessitates further research to elucidate the underlying causal mechanisms. Methods : Our investigation used public genome-wide association study data to explore the relationships among the plasma proteome, metabolome, and sepsis, considering different sepsis subgroup. Initially, two-sample Mendelian randomization established causal connections between the plasma proteome and metabolome with sepsis. Subsequently, multivariate and iterative Mendelian randomization analyses were performed to understand the complex interactions in plasma during sepsis. The validity of these findings was supported by thorough sensitivity analyses. Result : The study identified 25 plasma proteins that enhance risk and 34 that act as protective agents in sepsis. After P value adjustment (0.05/1306), ICAM5 emerged with a positive correlation to sepsis susceptibility ( P value = 2.14E-05, OR = 1.10, 95% CI = 1.05-1.15), with this significance preserved across three sepsis subgroup examined. Additionally, 29 plasma metabolites were recognized as risk factors, and 15 as protective factors for sepsis outcomes. After P value adjustment (0.05/997), elevated levels of 1,2,3-benzenetriol sulfate (2) was significantly associated with increased sepsis risk ( P value = 3.37E-05, OR = 1.18, 95% CI = 1.09-1.28). Further scrutiny revealed that this plasma metabolite notably augments the abundance of ICAM5 protein ( P value = 3.52E-04, OR = 1.11, 95% CI = 1.04-1.17), devoid of any detected heterogeneity, pleiotropy, or reverse causality. Mediated Mendelian randomization revealed ICAM5 mediated 11.9% of 1,2,3-benzenetriol sulfate (2)'s total effect on sepsis progression. Conclusion : This study details the causal link between the plasma proteome and metabolome with sepsis, highlighting the roles of ICAM5 and 1,2,3-benzenetriol sulfate (2) in sepsis progression, both independently and through crosstalk.

Association study of the JAK/STAT signaling pathway with susceptibility to COVID-19 in moroccan patient and in-silico analysis of rare variants

The goal of our study was to explore the association of the polymorphisms in the JAK/STAT pathway among Moroccan COVID-19 patients, using a case-control approach. Next-generation sequencing was employed to investigate the IFNAR1, IFNAR2, JAK1, TYK2, STAT2, and IRF9 genes within the JAK/STAT pathway. We also performed an in silico study to examine the rare variants in this pathway. Statistical analyses were conducted using MedCalc software. Protein 3D structures were determined via the I-TASSER server, with variant structures generated using PyMOL. YASARA View allowed local 3D analysis comparing native and variant structures for pathogenic rare variants. The study encompassed 206 COVID-19 patients, averaging 45.70 ± 12.73 years and a control group (N=118). Among the examined genes, 15 common polymorphisms and 7 rare variants were identified. Adjustment for age and gender revealed a significant association between TYK2 p.Gly363Ser (p=0.036) and COVID-19 infection, where the GA variant exhibited protective effects (0.6361 [0.3405-1.1884], p=0.035). Additionally, STAT2 p.Met594Ile showed an association to COVID-19 risk (p=0.042), with heterozygous GC being linked to infection (p=0.037, OR=2.7135 [0.5684 -12.9532]). Notably, IFNAR1 p.Val168Leu mutated C allele was significantly associated with reduced susceptibility to COVID-19 severity (p=0.028, OR=0.5936 [0.3725 - 0.9461]), under the additive model (p=0.045, OR=0.626 [0.3958 - 0.9899]). Rare variants IFNAR1 p.Trp318Cys, p.Ser476Phe, and IFNAR2 p.Cys271Tyr were predicted deleterious, impacting protein structure via hydrogen bond and hydrophobic interaction alterations. Burden analysis of rare variants revealed a protective cumulative effect against COVID-19 severity for TYK2 (p=0.0013, OR=0.1438 [0.04237 - 0.4803]) under the dominant model. This study underscores the role of genetic factors in COVID-19 susceptibility and advocates further explorations regarding functional impacts of JAK/STAT pathway rare variants.

Gastroesophageal reflux disease increases predisposition to severe COVID-19: Insights from integrated Mendelian randomization and genetic analysis

OBJECTIVE

This study aims to investigate the potential causal relationship, shared genomic loci, as well as potential molecular pathways and tissue-specific expression patterns between gastroesophageal reflux disease (GERD) and the risk of hospitalized/severe 2019 coronavirus disease (COVID-19).

METHODS

We employed linkage disequilibrium score regression and bidirectional Mendelian randomization (MR) analysis to explore potential genetic associations between GERD (N = 602,604) and hospitalized COVID-19 (N = 2095,324) as well as severe COVID-19 (N = 1086,211). Additionally, shared genomic loci were extracted from common pivotal regions, further confirmed through corresponding colocalization analyses. GERD-driven molecular pathway network was constructed using extensive literature data mining to understand the molecular-level impacts of GERD on COVID-19.

RESULTS

Our results revealed a significant positive genetic correlation between GERD and both hospitalized (rg  =  0.418) and severe COVID-19 (rg  =  0.314). Furthermore, the MR analysis demonstrated a unidirectional causal effect of genetic predisposition to GERD on COVID-19 outcomes, including hospitalized COVID-19 (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.27-1.44, p = 9.17e - 12) and severe COVID-19 (OR: 1.27, 95% CI: 1.18-1.37, p = 1.20e - 05). Additionally, GERD and both COVID-19 conditions shared one genomic locus with lead-SNPs rs1011407 and rs1123573, corresponding to the transcription factor BCL11A. Colocalization analysis further demonstrated a significant positive correlation between genome-wide association study and expression quantitative trait locus (eQTL) abnormalities, including rs1011407 (eQTL_p = 2.35e - 07) and rs1123573 (eQTL_p = 2.74e - 05). Molecular pathway analysis indicated that GERD might promote the progression of COVID-19 by inducting immune-activated and inflammation-related pathways.

CONCLUSION

These findings confirm that genetically determined GERD may increase the susceptibility to hospitalized/severe COVID-19. The shared genetic loci and the potential molecular pathways offer valuable insights into causal connections between GERD and COVID-19.

Unraveling genetic mysteries: A comprehensive review of GWAS and DNA insights in animal and plant pathosystems

DNA serves as the carrier of genetic information, with sequence variations playing a pivotal role in defining hereditary traits. Genome-Wide Association Studies (GWAS) facilitate the investigation of the links between genetic variations and phenotypes, significantly influencing biological research, particularly in animal and plant pathology. By identifying genetic markers associated with specific traits or diseases, GWAS enhances our understanding of host-pathogen interactions and improves disease-resistant breeding strategies. It has been vital in revealing the genetic basis of disease resistance, pinpointing key genes and DNA loci, which enrich genetic resources for breeding programs and deepen our knowledge of disease resistance mechanisms at the DNA level. Additionally, GWAS contributes to pathogen population genetics, facilitating a thorough exploration of pathogen virulence. Integrating GWAS with marker-assisted selection enhances breeding efficiency and precision in selecting for disease-resistant traits. While previous research has largely focused on host genetics, the genetic variation of pathogens is equally significant. Notably, reports integrating animal and plant pathosystems are still lacking. Given the importance of these systems, this review summarizes key advancements in this field, addresses current challenges, and proposes future directions, thereby offering a vital reference for ongoing research.

Scalable randomized kernel methods for multiview data integration and prediction with application to Coronavirus disease

There is still more to learn about the pathobiology of coronavirus disease (COVID-19) despite 4 years of the pandemic. A multiomics approach offers a comprehensive view of the disease and has the potential to yield deeper insight into the pathogenesis of the disease. Previous multiomics integrative analysis and prediction studies for COVID-19 severity and status have assumed simple relationships (ie linear relationships) between omics data and between omics and COVID-19 outcomes. However, these linear methods do not account for the inherent underlying nonlinear structure associated with these different types of data. The motivation behind this work is to model nonlinear relationships in multiomics and COVID-19 outcomes, and to determine key multidimensional molecules associated with the disease. Toward this goal, we develop scalable randomized kernel methods for jointly associating data from multiple sources or views and simultaneously predicting an outcome or classifying a unit into one of 2 or more classes. We also determine variables or groups of variables that best contribute to the relationships among the views. We use the idea that random Fourier bases can approximate shift-invariant kernel functions to construct nonlinear mappings of each view and we use these mappings and the outcome variable to learn view-independent low-dimensional representations. We demonstrate the effectiveness of the proposed methods through extensive simulations. When the proposed methods were applied to gene expression, metabolomics, proteomics, and lipidomics data pertaining to COVID-19, we identified several molecular signatures for COVID-19 status and severity. Our results agree with previous findings and suggest potential avenues for future research. Our algorithms are implemented in Pytorch and interfaced in R and available at: https://github.com/lasandrall/RandMVLearn.

Antibodies to the RBD of SARS-CoV-2 spike mediate productive infection of primary human macrophages

The role of myeloid cells in the pathogenesis of SARS-CoV-2 is well established, in particular as drivers of cytokine production and systemic inflammation characteristic of severe COVID-19. However, the potential for myeloid cells to act as bona fide targets of productive SARS-CoV-2 infection, and the specifics of entry, remain unclear. Using a panel of anti-SARS-CoV-2 monoclonal antibodies (mAbs) we performed a detailed assessment of antibody-mediated infection of monocytes/macrophages. mAbs with the most consistent potential to mediate infection were those targeting a conserved region of the receptor binding domain (RBD; group 1/class 4). Infection was closely related to the neutralising concentration of the mAbs, with peak infection occurring below the IC50, while pre-treating cells with remdesivir or FcγRI-blocking antibodies inhibited infection. Studies performed in primary macrophages demonstrated high-level and productive infection, with infected macrophages appearing multinucleated and syncytial. Infection was not seen in the absence of antibody with the same quantity of virus. Addition of ruxolitinib significantly increased infection, indicating restraint of infection through innate immune mechanisms rather than entry. High-level production of pro-inflammatory cytokines directly correlated with macrophage infection levels. We hypothesise that infection via antibody-FcR interactions could contribute to pathogenesis in primary infection, systemic virus spread or persistent infection.

Autoantibodies in hospitalised patients with COVID-19

Objectives

CD209L and its homologous protein CD209 act as alternative entry receptors for the SARS-CoV-2 virus and are highly expressed in the virally targeted tissues. We tested for the presence and clinical features of autoantibodies targeting these receptors and compared these with autoantibodies known to be associated with COVID-19.

Methods

Using banked samples (n = 118) from Johns Hopkins patients hospitalised with COVID-19, we defined autoantibodies against CD209 and CD209L by enzyme-linked immunosorbent assay (ELISA). Clinical associations of these antibodies were compared with those of patients with anti-interferon (IFN) and anti-angiotensin-converting enzyme-2 (ACE2) autoantibodies.

Results

Amongst patients hospitalised with COVID-19, 19.5% (23/118) had IgM autoantibodies against CD209L and were more likely to have coronary artery disease (44% vs 19%, P = 0.03). Antibodies against CD209 were present in 5.9% (7/118); interestingly, all 7 were male (P = 0.02). In our study, the presence of either antibody was positively associated with disease severity [OR 95% confidence interval (95% CI): 1.80 (0.69-5.03)], but the association did not reach statistical significance. In contrast, 10/118 (8.5%) had IgG autoantibodies against IFNα, and 21 (17.8%) had IgM antibodies against ACE2. These patients had significantly worse prognosis (intubation or death) and prolonged hospital stays. However, when adjusting for patient characteristics on admission, only the presence of anti-ACE2 IgM remained significant [pooled common OR (95% CI), 4.14 (1.37, 12.54)].

Conclusion

We describe IgM autoantibodies against CD209 and CD209L amongst patients hospitalised with COVID-19. These were not associated with disease severity. Conversely, patients with either anti-ACE2 IgM or anti-IFNα IgG antibodies had worse outcomes. Due to the small size of the study cohort, conclusions drawn should be considered cautiously.

Eight-fold increased COVID-19 mortality in autosomal dominant tubulointerstitial kidney disease due to MUC1 mutations: an observational study

BACKGROUND

MUC1 and UMOD pathogenic variants cause autosomal dominant tubulointerstitial kidney disease (ADTKD). MUC1 is expressed in kidney, nasal mucosa and respiratory tract, while UMOD is expressed only in kidney. Due to haplo-insufficiency ADTKD-MUC1 patients produce approximately 50% of normal mucin-1.

METHODS

To determine whether decreased mucin-1 production was associated with an increased COVID-19 risk, we sent a survey to members of an ADTKD registry in September 2021, after the initial, severe wave of COVID-19. We linked results to previously obtained ADTKD genotype and plasma CA15-3 (mucin-1) levels and created a longitudinal registry of COVID-19 related deaths.

RESULTS

Surveys were emailed to 637 individuals, with responses from 89 ADTKD-MUC1 and 132 ADTKD-UMOD individuals. 19/83 (23%) ADTKD-MUC1 survey respondents reported a prior COVID-19 infection vs. 14/125 (11%) ADTKD-UMOD respondents (odds ratio (OR) 2.35 (95%CI 1.60-3.11, P = 0.0260). Including additional familial cases reported from survey respondents, 10/41 (24%) ADTKD-MUC1 individuals died of COVID-19 vs. 1/30 (3%) with ADTKD-UMOD, with OR 9.21 (95%CI 1.22-69.32), P = 0.03. The mean plasma mucin-1 level prior to infection in 14 infected and 27 uninfected ADTKD-MUC1 individuals was 7.06 ± 4.12 vs. 10.21 ± 4.02 U/mL (P = 0.035). Over three years duration, our longitudinal registry identified 19 COVID-19 deaths in 360 ADTKD-MUC1 individuals (5%) vs. 3 deaths in 478 ADTKD-UMOD individuals (0.6%) (P = 0.0007). Multivariate logistic regression revealed the following odds ratios (95% confidence interval) for COVID-19 deaths: ADTKD-MUC1 8.4 (2.9-29.5), kidney transplant 5.5 (1.6-9.1), body mass index (kg/m2) 1.1 (1.0-1.2), age (y) 1.04 (1.0-1.1).

CONCLUSIONS

Individuals with ADTKD-MUC1 are at an eight-fold increased risk of COVID-19 mortality vs. ADTKD-UMOD individuals. Haplo-insufficient production of mucin-1 may be responsible.

Associations Between Clinical Manifestations of SARS-CoV-2 Infection and HLA Alleles in a Caucasian Population: A Molecular HLA Typing Study

Background and Objectives: Severe COVID-19 still constitutes an important health problem. Taking into account the crucial role of HLA in immune reactions, evaluation of the impact of HLA on COVID-19 risk and clinical course seemed necessary, as the already available data are inconsistent. The aim of the present study was to compare the HLA profiles of patients with symptomatic SARS-CoV-2 infection and a healthy control group, as well as to compare HLA allele frequencies in patients with severe and non-severe courses of COVID-19. Materials and Methods: HLA classes were genotyped using a next-generation sequencing method in 2322 persons, including 2217 healthy hematopoietic stem cell potential donors and 105 patients with symptomatic COVID-19. Results: Symptomatic course of SARS-CoV-2 infection appeared to be associated with the presence of HLA-A*30:01, B*44:02, B*52:01, C*05:01, C*17:01, and DRB1*11:02, while HLA-C*07:04 and DQB1*03:03 seem to play a protective role. Moreover, we demonstrated that the severe symptomatic course of COVID-19 can be associated with the presence of HLA-B*08:01, C*04:01, DRB1*03:01, and DQB1*03:01, while HLA-DRB1*08:01 appeared to be protective against severe COVID-19 disease. Conclusions: Identification of alleles that are potentially associated with symptomatic SARS-CoV-2 infection as well as the severe course of COVID-19 broadens the knowledge on the genetic background of COVID-19 course and can constitute an important step in the development of personalized medicine.

Rare Genetic Variants of NLRP12 in Admixed Latino-American Children With SARS-CoV-2-Related Multisystem Inflammatory Syndrome

Multisystem inflammatory syndrome in children (MIS-C) is a rare, potentially fatal complication of SARS-CoV-2 infection. Genetic defects in inflammation-related pathways have been linked to MIS-C, but additional research is needed, especially in diverse ethnic groups. The present study aimed to identify genetic variants underlying MIS-C in Brazilian patients. Whole exome sequencing was performed, focusing on genes involved in the host immune response to SARS-CoV-2. Functional assays assessed the impact of selected variants on nuclear factor-κB signaling. Nine rare, potentially deleterious variants were found in 8 of 21 patients, located in the IL17RC, IFNA10, or NLRP12 gene. Unlike the wild type NLRP12 protein, which inhibits nuclear factor-κB activation in HEK 293T cells, the mutant NLRP12 proteins have significantly reduced inhibitory properties. In conclusion, our results indicate that rare autosomal variants in immune-related genes may underlie MIS-C, highlighting the potential role of NLRP12 in its predisposition. These findings provide new insights for the appropriate management of MIS-C.

Future Directions in Therapies for Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is caused by a complex interplay among hyperinflammation, endothelial dysfunction, and alveolar epithelial injury. Targeted treatments toward the underlying pathways have been unsuccessful in unselected patient populations. The first reliable biological subphenotypes reflective of these biological disease states have been identified in the past decade. Subphenotype targeted intervention studies are needed to advance the pharmacologic treatment of ARDS.

Systematic assessment of COVID-19 host genetics using whole genome sequencing data

Courses of SARS-CoV-2 infections are highly variable, ranging from asymptomatic to lethal COVID-19. Though research has shown that host genetic factors contribute to this variability, cohort-based joint analyses of variants from the entire allelic spectrum in individuals with confirmed SARS-CoV-2 infections are still lacking. Here, we present the results of whole genome sequencing in 1,220 mainly vaccine-naïve individuals with confirmed SARS-CoV-2 infection, including 827 hospitalized COVID-19 cases. We observed the presence of autosomal-recessive or likely compound heterozygous monogenic disorders in six individuals, all of which were hospitalized and significantly younger than the rest of the cohort. We did not observe any suggestive causal variants in or around the established risk gene TLR7. Burden testing in the largest population subgroup (i.e., Europeans) suggested nominal enrichments of rare variants in coding and non-coding regions of interferon immune response genes in the overall analysis and male subgroup. Case-control analyses of more common variants confirmed associations with previously reported risk loci, with the key locus at 3p21 reaching genome-wide significance. Polygenic scores accurately captured risk in an age-dependent manner. By enabling joint analyses of different types of variation across the entire frequency spectrum, this data will continue to contribute to the elucidation of COVID-19 etiology.

How to build a human: Piecing together the body's cellular puzzle

Piecing together the body's cellular puzzle.

Estimating the Number of Polygenic Diseases Among Six Mutually Exclusive Entities of Non-Tumors and Cancer

In the era of precision medicine with increasing amounts of sequenced cancer and non-cancer genomes of different ancestries, we here enumerate the resulting polygenic disease entities. Based on the cell number status, we first identified six fundamental types of polygenic illnesses, five of which are non-cancerous. Like complex, non-tumor disorders, neoplasms normally carry alterations in multiple genes, including in 'Drivers' and 'Passengers'. However, tumors also lack certain genetic alterations/epigenetic changes, recently named 'Goners', which are toxic for the neoplasm and potentially constitute therapeutic targets. Drivers are considered essential for malignant transformation, whereas environmental influences vary considerably among both types of polygenic diseases. For each form, hyper-rare disorders, defined as affecting <1/108 individuals, likely represent the largest number of disease entities. Loss of redundant tumor-suppressor genes exemplifies such a profoundly rare mutational event. For non-tumor, polygenic diseases, pathway-centered taxonomies seem preferable. This classification is not readily feasible in cancer, but the inclusion of Drivers and possibly also of epigenetic changes to the existing nomenclature might serve as initial steps in this direction. Based on the detailed genetic alterations, the number of polygenic diseases is essentially countless, but different forms of nosologies may be used to restrict the number.

Protein phosphatase 1 catalytic subunit gamma is a causative gene for meat lightness and redness

The quality of meat is important to the consumer. Color is a primary indicator of meat quality and is characterized mainly into lightness, redness, and yellowness. Here, we used the genome-wide association study (GWAS) and gene-based association analysis with whole-genome resequencing of 230 fast-growing white-feathered chickens to map genes related to meat lightness and redness to a 6.24 kb QTL region (GGA15: 6298.34-6304.58 kb). This analysis revealed that only the protein phosphatase 1 catalytic subunit gamma (PPP1CC) was associated with meat color (P = 8.65E-08). The causal relationships between PPP1CC expression and meat lightness/redness were further validated through Mendelian randomization analyses (P < 2.9E-12). Inducible skeletal muscle-specific PPP1CC knockout (PPP1CC-SSKO) mice were generated and these mice showed increased lightness and decreased myoglobin content in the limb muscles. In addition, the predominant myofiber shifted from slow-twitch to fast-twitch myofibers. Through transcriptome and targeted metabolome evidence, we found that inhibition of PPP1CC decreased the expression of typical slow-twitch myofiber and myofiber-type specification genes and enhanced the glycolysis pathway. Functional validation through a plasmid reporter assay revealed that a SNP (rs315520807, C > T) located in the intron of PPP1CC could regulate the gene transcription activity. The differences in meat color phenotypes, myoglobin content, frequency of rs315520807 variant, expression of PPP1CC and fast-twitch fiber marker genes were detected between fast-growing white-feathered chickens and local chickens. In this study, PPP1CC was identified as the causative gene for meat color, and the novel target gene and variant that can aid in the innovation of meat improvement technology were detected.

Association between FTO polymorphism and COVID-19 mortality among older adults: A population-based cohort study

OBJECTIVES

COVID-19 caused a global pandemic with millions of deaths. Fat mass and obesity-associated gene (FTO) (alias m6A RNA demethylase) and its functional rs17817449 polymorphism are candidates to influence COVID-19-associated mortality since methylation status of viral nucleic acids is an important factor influencing viral viability.

METHODS

We tested a population-based cohort of 5233 subjects (aged 63-87 years in 2020) where 70 persons died from COVID-19 and 394 from other causes during the pandemic period.

RESULTS

The frequency of GG homozygotes was higher among those who died from COVID-19 (34%) than among survivors (19%) or deaths from other causes (20%), P <0.005. After multiple adjustments, GG homozygotes had a higher risk of death from COVID-19 with odds ratio = 2.01 (95% confidence interval; 1.19-3.41, P <0.01) compared with carriers of at least one T allele. The FTO polymorphism was not associated with mortality from other causes.

CONCLUSIONS

Our results suggest that FTO variability is a significant predictor of COVID-19-associated mortality in Caucasians.

Association of pre-existing depression and anxiety with Omicron variant infection

Pre-existing psychiatric disorders were linked to an increased susceptibility to COVID-19 during the initial outbreak of the pandemic, while evidence during Omicron prevalence is lacking. Leveraging data from two prospective cohorts in China, we identified incident Omicron infections between January 2023 and April 2023. Participants with a self-reported history or self-rated symptoms of depression or anxiety before the Omicron pandemic were considered the exposed group, whereas the others were considered unexposed. We employed multivariate logistic regression models to examine the association of pre-existing depression or anxiety with the risk of any or severe Omicron infection indexed by medical interventions or severe symptoms. Further, we stratified the analyses by polygenic risk scores (PRSs) for COVID-19 and repeated the analyses using the UK Biobank data. We included 10,802 individuals from the Chinese cohorts (mean age = 51.1 years, 45.6% male), among whom 7841 (72.6%) were identified as cases of Omicron infection. No association was found between any pre-existing depression or anxiety and the overall risk of Omicron infection (odds ratio [OR] =1.04, 95% confidence interval [CI] 0.95-1.14). However, positive associations were noted for severe Omicron infection, either as infections requiring medical interventions (1.26, 1.02-1.54) or with severe symptoms (≥3: 1.73, 1.51-1.97). We obtained comparable estimates when stratified by COVID-19 PRS level. Additionally, using clustering method, we identified eight distinct symptom patterns and found associations between pre-existing depression or anxiety and the patterns characterized by multiple or complex severe symptoms including cough and taste and smell decline (ORs = 1.42-2.35). The results of the UK Biobank analyses corroborated findings of the Chinese cohorts. In conclusion, pre-existing depression and anxiety was not associated with the risk of Omicron infection overall but an elevated risk of severe Omicron infection, supporting the continued efforts on monitoring and possible early intervention in this high-risk population during Omicron prevalence.

Impact of sample processing delays on plasma markers of inflammation, chemotaxis, cell death, and blood coagulation

BACKGROUND

Biosampling studies in critically ill patients traditionally involve bedside collection of samples followed by local processing (ie. centrifugation, aliquotting, and freezing) and storage. However, community hospitals, which care for the majority of Canadian patients, often lack the infrastructure for local processing and storage of specimens. A potential solution is a "simplified" biosampling protocol whereby blood samples are collected at the bedside and then shipped to a central site for processing and storage. One potential limitation of this approach is that delayed processing may alter sample characteristics.

OBJECTIVE

To determine whether delays in blood sample processing affect the stability of cytokines (IL-6, TNF, IL-10, IFN-γ), chemokines (IL-8, IP-10, MCP-1, MCP-4, MIP-1α, MIP-1β), cell-free DNA (cfDNA) (released by dying cells), and blood clotting potential in human blood samples.

METHODS

Venous blood was collected into EDTA and citrate sample tubes and stored at room temperature (RT) or 4°C for progressive intervals up to 72 hours, prior to processing. Plasma cytokines and chemokines were quantified using single or multiplex immunoassays. cfDNA was measured using Picogreen DNA Quantification. Blood clotting potential was measured using a thrombin generation assay.

RESULTS

Blood samples were collected from 9 intensive care unit (ICU) patients and 7 healthy volunteers. Admission diagnoses for the ICU patients included sepsis, trauma, ruptured abdominal aortic aneurysm, intracranial hemorrhage, gastrointestinal bleed, and hyperkalemia. After pre-processing delays of up to 72 hours at RT or 4°C, no significant changes were observed in plasma cytokines, chemokines, cfDNA, or thrombin formation.

CONCLUSIONS

Delayed sample processing for up to 72 hours at either RT or 4°C did not significantly affect cytokines, chemokines, cfDNA, or blood clotting potential in plasma samples from healthy volunteers and ICU patients. A "simplified" biosampling protocol is a feasible solution for conducting biosampling research at hospitals without local processing capacity.

Micronutrients, Vitamin D, and Inflammatory Biomarkers in COVID-19: A Systematic Review and Meta-analysis of Causal Inference Studies

CONTEXT

Experimental and observational studies suggest that circulating micronutrients, including vitamin D (VD), may increase COVID-19 risk and its associated outcomes. Mendelian randomization (MR) studies provide valuable insight into the causal relationship between an exposure and disease outcomes.

OBJECTIVES

The aim was to conduct a systematic review and meta-analysis of causal inference studies that apply MR approaches to assess the role of these micronutrients, particularly VD, in COVID-19 risk, infection severity, and related inflammatory markers.

DATA SOURCES

Searches (up to July 2023) were conducted in 4 databases.

DATA EXTRACTION AND ANALYSIS

The quality of the studies was evaluated based on the MR-STROBE guidelines. Random-effects meta-analyses were conducted where possible.

RESULTS

There were 28 studies (2 overlapped) including 12 on micronutrients (8 on VD) and COVID-19, 4 on micronutrients (all on VD) and inflammation, and 12 on inflammatory markers and COVID-19. Some of these studies reported significant causal associations between VD or other micronutrients (vitamin C, vitamin B6, iron, zinc, copper, selenium, and magnesium) and COVID-19 outcomes. Associations in terms of causality were also nonsignificant with regard to inflammation-related markers, except for VD levels below 25 nmol/L and C-reactive protein (CRP). Some studies reported causal associations between cytokines, angiotensin-converting enzyme 2 (ACE2), and other inflammatory markers and COVID-19. Pooled MR estimates showed that VD was not significantly associated with COVID-19 outcomes, whereas ACE2 increased COVID-19 risk (MR odds ratio = 1.10; 95% CI: 1.01-1.19) but did not affect hospitalization or severity of the disease. The methodological quality of the studies was high in 13 studies, despite the majority (n = 24) utilizing 2-sample MR and evaluated pleiotropy.

CONCLUSION

MR studies exhibited diversity in their approaches but do not support a causal link between VD/micronutrients and COVID-19 outcomes. Whether inflammation mediates the VD-COVID-19 relationship remains uncertain, and highlights the need to address this aspect in future MR studies exploring micronutrient associations with COVID-19 outcomes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42022328224.

Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (<60 years) cases with no reported clinical risk factors (n = 378), compared to 0.24% of controls (odds ratio [OR] = 12.3, p = 1.27 × 10-10). Incorporation of the results of either functional assays or protein modeling led to a pronounced increase in effect size (ORmax = 46.5, p = 1.74 × 10-15). Association signals for the X-chromosomal gene TLR7 were also detected in the female-only subgroup, suggesting the existence of additional mechanisms beyond X-linked recessive inheritance in males. Additionally, supporting evidence was generated for a contribution to severe COVID-19 of the previously implicated genes IFNAR2, IFIH1, and TBK1. Our results refine the genetic contribution of rare TLR7 variants to severe COVID-19 and strengthen evidence for the etiological relevance of genes in the interferon signaling pathway.

Genome-wide association studies of COVID-19 vaccine seroconversion and breakthrough outcomes in UK Biobank

Understanding the genetic basis of COVID-19 vaccine seroconversion is crucial to study the role of genetics on vaccine effectiveness. In our study, we used UK Biobank data to find the genetic determinants of COVID-19 vaccine-induced seropositivity and breakthrough infections. We conducted four genome-wide association studies among vaccinated participants for COVID-19 vaccine seroconversion and breakthrough susceptibility and severity. Our findings confirmed a link between the HLA region and seroconversion after the first and second doses. Additionally, we identified 10 genomic regions associated with breakthrough infection (SLC6A20, ST6GAL1, MUC16, FUT6, MXI1, MUC4, HMGN2P18-KRTCAP2, NFKBIZ and APOC1), and one with breakthrough severity (APOE). No significant evidence of genetic colocalisation was found between those traits. Our study highlights the roles of individual genetic make-up in the varied antibody responses to COVID-19 vaccines and provides insights into the potential mechanisms behind breakthrough infections occurred even after the vaccination.

Novel risk loci for COVID-19 hospitalization among admixed American populations

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

Gene: environment interactions in immune and inflammatory responses to severe acute respiratory syndrome coronavirus 2 infection

Despite its devastating human cost, the rapid spread and global establishment of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) pandemic had the benefit of providing unique insights into the intricate interplay between genetic, environmental, and socioeconomic factors, which collectively impact susceptibility to infection with SARS-CoV-2. Preceding the implementation of broad vaccination programs and assuming the absence of significant acquired immunity, examining the innate vulnerability to the virus becomes essential. There is indeed considerable heterogeneity observed at both the population and individual levels for various SARS-CoV-2 infection phenotypes, including emergence, progression, and survival from the coronavirus disease 2019 (COVID-19) syndrome. Particularly intriguing is the seemingly milder course of COVID-19 disease reported for the African continent early during the pandemic. This was characterized by significantly lower mortality rates in SARS-CoV-2 patients compared with the European and American continents and globally. We will discuss some of the demographic and socioeconomic factors that may have contributed to these observations. We review the mapped COVID-19 genetic architecture, including the remarkable association of type I interferon as a single protective mechanism and a major determinant of susceptibility. Furthermore, we speculate on potential 'environmental' modulators of penetrance and expressivity of intrinsic vulnerability factors, with a focus on the microbiome and associated metabolomes. Additionally, this review explores the potential immunomodulatory contribution of helminth parasites to the human host immune and inflammatory responses to respiratory viral infections.

Deciphering the role of FOXP4 in long COVID: exploring genetic associations, evolutionary conservation, and drug identification through bioinformatics analysis

Long COVID (LC) refers to a condition characterized by a variety of lingering symptoms that persist for more than 4 to 12 weeks following the initial acute SARS-CoV-2 infection. Recent research has suggested that the FOXP4 gene could potentially be a significant factor contributing to LC. Owing to that, this study investigates FOXP4's role in LC by analyzing public datasets to understand its evolution and expression in diverse human populations and searching for drugs to reduce LC symptoms. Population genetic analysis of FOXP4 across human populations unmasks distinct genetic diversity patterns and positive selection signatures, suggesting potential population-specific susceptibilities to conditions like LC. Further, we also observed that FOXP4 experiences high expression during LC. To identify potential inhibitors, drug screening analysis identifies synthetic drugs like Glisoxepide, and natural compounds Kapurimycin A3 produced from Streptomyces sp, and Cucurbitacin B from Begonia nantoensis as promising candidates. Overall, our research contributes to understanding how FOXP4 may serve as a therapeutic target for mitigating the impact of LC.

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.

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.

No evidence that ACE2 or TMPRSS2 drive population disparity in COVID risks

Early in the SARS-CoV2 pandemic, in this journal, Hou et al. (BMC Med 18:216, 2020) interpreted public genotype data, run through functional prediction tools, as suggesting that members of particular human populations carry potentially COVID-risk-increasing variants in genes ACE2 and TMPRSS2 far more often than do members of other populations. Beyond resting on predictions rather than clinical outcomes, and focusing on variants too rare to typify population members even jointly, their claim mistook a well known artifact (that large samples reveal more of a population's variants than do small samples) as if showing real and congruent population differences for the two genes, rather than lopsided population sampling in their shared source data. We explain that artifact, and contrast it with empirical findings, now ample, that other loci shape personal COVID risks far more significantly than do ACE2 and TMPRSS2-and that variation in ACE2 and TMPRSS2 per se unlikely exacerbates any net population disparity in the effects of such more risk-informative loci.

Identification of druggable host dependency factors shared by multiple SARS-CoV-2 variants of concern

The high mutation rate of SARS-CoV-2 leads to the emergence of multiple variants, some of which are resistant to vaccines and drugs targeting viral elements. Targeting host dependency factors, e.g. cellular proteins required for viral replication, would help prevent the development of resistance. However, it remains unclear whether different SARS-CoV-2 variants induce conserved cellular responses and exploit the same core host factors. To this end, we compared three variants of concern and found that the host transcriptional response was conserved, differing only in kinetics and magnitude. Clustered regularly interspaced short palindromic repeats screening identified host genes required for each variant during infection. Most of the genes were shared by multiple variants. We validated our hits with small molecules and repurposed the US Food and Drug Administration-approved drugs. All the drugs were highly active against all the tested variants, including new variants that emerged during the study (Delta and Omicron). Mechanistically, we identified reactive oxygen species production as a key step in early viral replication. Antioxidants such as N-acetyl cysteine (NAC) were effective against all the variants in both human lung cells and a humanized mouse model. Our study supports the use of available antioxidant drugs, such as NAC, as a general and effective anti-COVID-19 approach.

GWAS-significant loci and severe COVID-19: analysis of associations, link with thromboinflammation syndrome, gene-gene, and gene-environmental interactions

Objective

The aim of this study was to replicate associations of GWAS-significant loci with severe COVID-19 in the population of Central Russia, to investigate associations of the SNPs with thromboinflammation parameters, to analyze gene-gene and gene-environmental interactions.

Materials and Methods

DNA samples from 798 unrelated Caucasian subjects from Central Russia (199 hospitalized COVID-19 patients and 599 controls with a mild or asymptomatic course of COVID-19) were genotyped using probe-based polymerase chain reaction for 10 GWAS-significant SNPs: rs143334143 CCHCR1, rs111837807 CCHCR1, rs17078346 SLC6A20-LLZTFL1, rs17713054 SLC6A20-LLZTFL1, rs7949972 ELF5, rs61882275 ELF5, rs12585036 ATP11A, rs67579710 THBS3, THBS3-AS1, rs12610495 DPP9, rs9636867 IFNAR2.

Results

SNP rs17713054 SLC6A20-LZTFL1 was associated with increased risk of severe COVID-19 in the entire group (risk allele A, OR = 1.78, 95% CI = 1.22-2.6, p = 0.003), obese individuals (OR = 2.31, 95% CI = 1.52-3.5, p = 0.0002, (p bonf = 0.0004)), patients with low fruit and vegetable intake (OR = 1.72, 95% CI = 1.15-2.58, p = 0.01, (p bonf = 0.02)), low physical activity (OR = 1.93, 95% CI = 1.26-2.94, p = 0.0035, (p bonf = 0.007)), and nonsmokers (OR = 1.65, 95% CI = 1.11-2.46, p = 0.02). This SNP correlated with increased BMI (p = 0.006) and worsened thrombodynamic parameters (maximum optical density of the formed clot, D (p = 0.02), delayed appearance of spontaneous clots, Tsp (p = 0.02), clot size 30 min after coagulation activation, CS (p = 0.036)). SNP rs17078346 SLC6A20-LZTFL1 was linked with increased BMI (p = 0.01) and severe COVID-19 in obese individuals (risk allele C, OR = 1.72, 95% CI = 1.15-2.58, p = 0.01, (p bonf = 0.02)). SNP rs12610495 DPP9 was associated with increased BMI (p = 0.01), severe COVID-19 in obese patients (risk allele G, OR = 1.48, 95% CI = 1.09-2.01, p = 0.01, (p bonf = 0.02)), and worsened thrombodynamic parameters (time to the start of clot growth, Tlag (p = 0.01)). For rs7949972 ELF5, a protective effect against severe COVID-19 was observed in non-obese patients (effect allele T, OR = 0.67, 95% CI = 0.47-0.95, p = 0.02, (p bonf = 0.04)), improving thrombodynamic parameters (CS (p = 0.02), stationary spatial clot growth rates, Vst (p = 0.02)). Finally, rs12585036 ATP11A exhibited a protective effect against severe COVID-19 in males (protective allele A, OR = 0.51, 95% CI = 0.32-0.83, p = 0.004). SNPs rs67579710 THBS3, THBS3-AS1, rs17713054 SLC6A20-LZTFL1, rs7949972 ELF5, rs9636867 IFNAR2-were involved in two or more of the most significant G×G interactions (p perm ≤ 0.01). The pairwise combination rs67579710 THBS3, THBS3-AS1 × rs17713054 SLC6A20-LZTFL1 was a priority in determining susceptibility to severe COVID-19 (it was included in four of the top five most significant SNP-SNP interaction models).

Conclusion

Overall, this study represents a comprehensive molecular-genetic and bioinformatics analysis of the involvement of GWAS-significant loci in the molecular mechanisms of severe COVID-19, gene-gene and gene-environmental interactions, and provides evidence of their relationship with thromboinflammation parameters in patients hospitalized in intensive care units.

Potential use of sodium glucose co-transporter 2 inhibitors during acute illness: a systematic review based on COVID-19

OBJECTIVE

SGLT-2i are increasingly recognized for their benefits in patients with cardiometabolic risk factors. Additionally, emerging evidence suggests potential applications in acute illnesses, including COVID-19. This systematic review aims to evaluate the effects of SGLT-2i in patients facing acute illness, particularly focusing on SARS-CoV-2 infection.

METHODS

Following PRISMA guidelines, a systematic search of PubMed, Scopus, medRxiv, Research Square, and Google Scholar identified 22 studies meeting inclusion criteria, including randomized controlled trials and observational studies. Data extraction and quality assessment were conducted independently.

RESULTS

Out of the 22 studies included in the review, six reported reduced mortality in DM-2 patients taking SGLT-2i, while two found a decreased risk of hospitalization. Moreover, one study demonstrated a lower in-hospital mortality rate in DM-2 patients under combined therapy of metformin plus SGLT-2i. However, three studies showed a neutral effect on the risk of hospitalization. No increased risk of developing COVID-19 was associated with SGLT-2i use in DM-2 patients. Prior use of SGLT-2i was not associated with ICU admission and need for MV. The risk of acute kidney injury showed variability, with inconsistent evidence regarding diabetic ketoacidosis.

CONCLUSION

Our systematic review reveals mixed findings on the efficacy of SGLT-2i use in COVID-19 patients with cardiometabolic risk factors. While some studies suggest potential benefits in reducing mortality and hospitalizations, others report inconclusive results. Further research is needed to clarify optimal usage and mitigate associated risks, emphasizing caution in clinical interpretation.

Olivar: towards automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 15 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer mismatches overlapping with primers and predicted PCR byproducts. We also compare Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluate Olivar on real wastewater samples and found that Olivar has up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available online as a web application at https://olivar.rice.edu  and can be installed locally as a command line tool with Bioconda. Source code, installation guide, and usage are available at https://github.com/treangenlab/Olivar .

Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection

Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.

Context-specific eQTLs reveal causal genes underlying shared genetic architecture of critically ill COVID-19 and idiopathic pulmonary fibrosis

Most genetic variants identified through genome-wide association studies (GWAS) are suspected to be regulatory in nature, but only a small fraction colocalize with expression quantitative trait loci (eQTLs, variants associated with expression of a gene). Therefore, it is hypothesized but largely untested that integration of disease GWAS with context-specific eQTLs will reveal the underlying genes driving disease associations. We used colocalization and transcriptomic analyses to identify shared genetic variants and likely causal genes associated with critically ill COVID-19 and idiopathic pulmonary fibrosis. We first identified five genome-wide significant variants associated with both diseases. Four of the variants did not demonstrate clear colocalization between GWAS and healthy lung eQTL signals. Instead, two of the four variants colocalized only in cell-type and disease-specific eQTL datasets. These analyses pointed to higher ATP11A expression from the C allele of rs12585036, in monocytes and in lung tissue from primarily smokers, which increased risk of IPF and decreased risk of critically ill COVID-19. We also found lower DPP9 expression (and higher methylation at a specific CpG) from the G allele of rs12610495, acting in fibroblasts and in IPF lungs, and increased risk of IPF and critically ill COVID-19. We further found differential expression of the identified causal genes in diseased lungs when compared to non-diseased lungs, specifically in epithelial and immune cell types. These findings highlight the power of integrating GWAS, context-specific eQTLs, and transcriptomics of diseased tissue to harness human genetic variation to identify causal genes and where they function during multiple diseases.