Killer-cell immunoglobulin-like receptor polymorphism is associated with COVID-19 outcome: Results of a pilot observational study.

The pathogenesis of COVID-19 warrants unravelling. Genetic polymorphism analysis may help answer the variability in disease outcome. To determine the role of KIR and HLA polymorphisms in susceptibility, progression, and severity of SARS-CoV-2 infection, 458 patients and 667 controls enrolled in this retrospective observational study from April to December 2020. Mild/moderate and severe/death study groups were established. HLA-A, -B, -C, and KIR genotyping were performed using the Lifecodes® HLA-SSO and KIR-SSO kits on the Luminex® 200™ xMAP fluoroanalyser. A probability score using multivariate binary logistic regression analysis was calculated to estimate the likelihood of severe COVID-19. ROC analysis was used to calculate the best cut-off point for predicting a worse clinical outcome with high sensitivity and specificity. A p ≤ 0.05 was considered statistically significant. KIR AA genotype protected positively against severity/death from COVID-19. Furthermore, KIR3DL1, KIR2DL3 and KIR2DS4 genes protected patients from severe forms of COVID-19. KIR Bx genotype, as well as KIR2DL2, KIR2DS2, KIR2DS3 and KIR3DS1 were identified as biomarkers of severe COVID-19. Our logistic regression model, which included clinical and KIR/HLA variables, categorised our cohort of patients as high/low risk for severe COVID-19 disease with high sensitivity and specificity (Se = 94.29%, 95% CI [80.84-99.30]; Sp = 84.55%, 95% CI [79.26-88.94]; OR = 47.58, 95%CI [11.73-193.12], p < 0.0001). These results illustrate an association between KIR/HLA ligand polymorphism and different COVID-19 outcomes and remarks the possibility of use them as a surrogate biomarkers to detect severe patients in possible future infectious outbreaks.

Global research on emerging trends of obstetrics during the COVID-19 pandemic: A bibliometric analysis.

Coronavirus disease-2019 (COVID-19) has caused continuous effects on the global public, especially for susceptible and vulnerable populations like pregnant women. COVID-19-related studies and publications have shown blowout development, making it challenging to identify development trends and hot areas by using traditional review methods for such massive data. Aimed to perform a bibliometric analysis to explore the status and hotspots of COVID-19 in obstetrics. An online search was conducted in the Web of Science Core Collection (WOSCC) database from January 01, 2020 to November 31, 2022, using the following search expression: (((TS= ("COVID 19" OR "coronavirus 2019" OR "coronavirus disease 2019" OR "SARS-CoV-2" OR "2019-nCoV" OR "2019 novel coronavirus" OR "SARS coronavirus 2" OR "Severe Acute Respiratory Syndrome Coronavirus-2" OR "SARS-COV2")) AND TS= ("obstetric*" OR "pregnancy*" OR "pregnant" OR "parturition*" OR "puerperium"))). VOSviewer version 1.6.18, CiteSpace version 6.1.R6, R version 4.2.0, and Rstudio were used for the bibliometric and visualization analyses. 4144 articles were included in further analysis, including authors, titles, number of citations, countries, and author affiliations. The United States has contributed the most significant publications with the leading position. "Sahin, Dilek" has the largest output, and "Khalil, Asma" was the most influential author with the highest citations. Keywords of "Cov," "Experience," and "Neonate" with the highest frequency, and "Systematic Review" might be the new research hotspots and frontiers. The top 3 concerned genes included ACE2, CRP, and IL6. The new research hotspot is gradually shifting from the COVID-19 mechanism and its related clinical research to reviewing treatment options for pregnant women. This research uniquely delves into specific genes related to COVID-19's effects on obstetrics, a focus that has not been previously explored in other reviews. Our research enables clinicians and researchers to summarize the overall point of view of the existing literature and obtain more accurate conclusions.

SARS-CoV-2 N protein-induced Dicer, XPO5, SRSF3, and hnRNPA3 downregulation causes pneumonia.

Though RNAi and RNA-splicing machineries are involved in regulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication, their precise roles in coronavirus disease 2019 (COVID-19) pathogenesis remain unclear. Herein, we show that decreased RNAi component (Dicer and XPO5) and splicing factor (SRSF3 and hnRNPA3) expression correlate with increased COVID-19 severity. SARS-CoV-2 N protein induces the autophagic degradation of Dicer, XPO5, SRSF3, and hnRNPA3, inhibiting miRNA biogenesis and RNA splicing and triggering DNA damage, proteotoxic stress, and pneumonia. Dicer, XPO5, SRSF3, and hnRNPA3 knockdown increases, while their overexpression decreases, N protein-induced pneumonia's severity. Older mice show lower expression of Dicer, XPO5, SRSF3, and hnRNPA3 in their lung tissues and exhibit more severe N protein-induced pneumonia than younger mice. PJ34, a poly(ADP-ribose) polymerase inhibitor, or anastrozole, an aromatase inhibitor, ameliorates N protein- or SARS-CoV-2-induced pneumonia by restoring Dicer, XPO5, SRSF3, and hnRNPA3 expression. These findings will aid in developing improved treatments for SARS-CoV-2-associated pneumonia.

Clinical and Genomic Perspective of SARS CoV-2 Infection in Liver Disease Patients: A Single-Centre Retrospective Study.

The limited literature on the clinical course of COVID-19 among patients with underlying liver disease (LD) is available from India. The present study aimed to evaluate the clinical and mutational profile of SARS-CoV-2 among LD cases. This was a retrospective study including admitted LD cases in whom SARS-CoV-2 RT-PCR testing was performed. Complete demographic and clinical details were retrieved from Hospital Information System. Detailed mutational analysis was performed by comparing LD COVID-19 positive study group, i.e. LD-CoV(+) with COVID-19 positive outpatients without any underlying LD as control, i.e. NLD-CoV(+). Out of 232 enrolled LD cases, 137 (59.1%) were LD-CoV(+). LD cases with existing co-morbidities were affected more (P = 0.002) and had 2.29 times (OR 2.29, CI 95%, 1.25-4.29) higher odds of succumbing to COVID-19 (P = 0.006). On multivariate regression analysis, ascites (P = 0.05), severe COVID-19 pneumonia (P = 0.046), and an increased levels of bilirubin (P = 0.005) and alkaline phosphatase (P = 0.003) were found to be associated with adverse outcome in LD-CoV(+).On mutational analysis, we found certain differences between LD- and NLD-CoV(+) infected with Delta [LD- and NLD-CoV (+ /D)] and Omicron [LD- and NLD-CoV(+/O)]. More mutations were shared between LD- and NLD-CoV(+/O) compared to LD- and NLD-CoV(+/D). There were differences in prevalence of indel mutations specific to LD-CoV ( +) for both Delta and Omicron. Moreover, we also reported an interesting genic bias between LD- and NLD-CoV( +) in harbouring deleterious/tolerated mutations. To conclude, LD cases with comorbidities were affected more and had higher odds of mortality due to COVID-19. The definite difference between LD- and NLD-CoV(+) groups with respect to frequency of harboured mutations and an inherent genic bias between them is of noteworthy importance.

A MULTI-HIT MODEL OF LONG COVID PATHOPHYSIOLOGY: THE INTERACTION BETWEEN IMMUNE TRIGGERS AND NERVOUS SYSTEM SIGNALING.

Early in the pandemic, clinicians recognized an overlap between Long COVID symptoms and dysautonomia, suggesting autonomic nervous system (ANS) dysfunction. Our clinical experience at Johns Hopkins with primary dysautonomia suggested heritability of sympathetic dysfunction, manifesting primarily as hyperhidrosis and as other dysautonomia symptoms. Whole exome sequencing revealed mutations in genes regulating electrical signaling in the nervous system, thus providing a genetic basis for the sympathetic overdrive observed. We hypothesize that dysautonomia in Long COVID requires two molecular hits: a genetic vulnerability to prime the ANS and a SARS-CoV-2 infection, as an immune trigger, to further disrupt ANS function resulting in increased sympathetic activity. Indeed, Long COVID patients show signs of chronic inflammation and autoimmunity. We have translated this two-hit concept to the clinic using ion channel inhibitors to target genetic susceptibility and immunomodulators to treat inflammation. This multi-hit hypothesis shows promise for managing Long COVID and merits further study.

MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts.

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.

Potential Transcriptional Enhancers in Coronaviruses: From Infectious Bronchitis Virus to SARS-CoV-2.

Coronaviruses constitute a global threat to human and animal health. It is essential to investigate the long-distance RNA-RNA interactions that approximate remote regulatory elements in strategies, including genome circularization, discontinuous transcription, and transcriptional enhancers, aimed at the rapid replication of their large genomes, pathogenicity, and immune evasion. Based on the primary sequences and modeled RNA-RNA interactions of two experimentally defined coronaviral enhancers, we detected via an in silico primary and secondary structural analysis potential enhancers in various coronaviruses, from the phylogenetically ancient avian infectious bronchitis virus (IBV) to the recently emerged SARS-CoV-2. These potential enhancers possess a core duplex-forming region that could transition between closed and open states, as molecular switches directed by viral or host factors. The duplex open state would pair with remote sequences in the viral genome and modulate the expression of downstream crucial genes involved in viral replication and host immune evasion. Consistently, variations in the predicted IBV enhancer region or its distant targets coincide with cases of viral attenuation, possibly driven by decreased open reading frame (ORF)3a immune evasion protein expression. If validated experimentally, the annotated enhancer sequences could inform structural prediction tools and antiviral interventions.

The Association of Genetic Markers Involved in Muscle Performance Responding to Lactate Levels during Physical Exercise Therapy by Nordic Walking in Patients with Long COVID Syndrome: A Nonrandomized Controlled Pilot Study.

Several genetic markers have shown associations with muscle performance and physical abilities, but the response to exercise therapy is still unknown. The aim of this study was to test the response of patients with long COVID through an aerobic physical therapy strategy by the Nordic walking program and how several genetic polymorphisms involved in muscle performance influence physical capabilities. Using a nonrandomized controlled pilot study, 29 patients who previously suffered from COVID-19 (long COVID = 13, COVID-19 = 16) performed a Nordic walking exercise therapy program for 12 sessions. The influence of the ACE (rs4646994), ACTN3 (rs1815739), AMPD1 (rs17602729), CKM (rs8111989), and MLCK (rs2849757 and rs2700352) polymorphisms, genotyped by using single nucleotide primer extension (SNPE) in lactic acid concentration was established with a three-way ANOVA (group × genotype × sessions). For ACE polymorphism, the main effect was lactic acid (p = 0.019). In ACTN3 polymorphism, there were no main effects of lactic acid, group, or genotype. However, the posthoc analysis revealed that, in comparison with nonlong COVID, long COVID increased lactic acid concentrations in Nordic walking sessions in CT and TT genotypes (all p < 0.05). For AMPD1 polymorphism, there were main effects of lactic acid, group, or genotype and lactic acid × genotype or lactic acid × group × genotype interactions (all p < 0.05). The posthoc analysis revealed that, in comparison with nonlong COVID, long COVID increased lactic acid concentrations in Nordic walking sessions in CC and CT genotypes (all p < 0.05). Physical therapy strategy through Nordic walking enhanced physical capabilities during aerobic exercise in post-COVID19 patients with different genotypes in ACTN3 c.1729C>T and AMPD1 c.34C>T polymorphisms. These findings suggest that individuals who reported long COVID who presumably exercised less beforehand appeared to be less able to exercise, based on lactate levels, and the effect of aerobic physical exercise enhanced physical capabilities conditioned by several genetic markers in long COVID patients.

Genetic risk factors for COVID-19 and influenza are largely distinct.

Coronavirus disease 2019 (COVID-19) and influenza are respiratory illnesses caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses, respectively. Both diseases share symptoms and clinical risk factors1, but the extent to which these conditions have a common genetic etiology is unknown. This is partly because host genetic risk factors are well characterized for COVID-19 but not for influenza, with the largest published genome-wide association studies for these conditions including >2 million individuals2 and about 1,000 individuals3-6, respectively. Shared genetic risk factors could point to targets to prevent or treat both infections. Through a genetic study of 18,334 cases with a positive test for influenza and 276,295 controls, we show that published COVID-19 risk variants are not associated with influenza. Furthermore, we discovered and replicated an association between influenza infection and noncoding variants in B3GALT5 and ST6GAL1, neither of which was associated with COVID-19. In vitro small interfering RNA knockdown of ST6GAL1-an enzyme that adds sialic acid to the cell surface, which is used for viral entry-reduced influenza infectivity by 57%. These results mirror the observation that variants that downregulate ACE2, the SARS-CoV-2 receptor, protect against COVID-19 (ref. 7). Collectively, these findings highlight downregulation of key cell surface receptors used for viral entry as treatment opportunities to prevent COVID-19 and influenza.

RNA replication-independent, DNA linearization-dependent expression of reporter genes from a SARS-CoV-2 replicon-encoding DNA in human cells.

Replicons, derived from RNA viruses, are genetic constructs retaining essential viral enzyme genes while lacking key structural protein genes. Upon introduction into cells, the genes carried by the replicon RNA are expressed, and the RNA self-replicates, yet viral particle production does not take place. Typically, RNA replicons are transcribed in vitro and are then electroporated in cells. However, it would be advantageous for the replicon to be generated in cells following DNA transfection instead of RNA. In this study, a bacterial artificial chromosome (BAC) DNA encoding a SARS-CoV-2 replicon under control of a T7 promoter was transfected into HEK293T cells engineered to functionally express the T7 RNA polymerase (T7 RNAP). Upon transfection of the BAC DNA, we observed low, but reproducible expression of reporter proteins GFP and luciferase carried by this replicon. Expression of the reporter proteins required linearization of the BAC DNA prior to transfection. Moreover, expression occurred independently of T7 RNAP. Gene expression was also insensitive to remdesivir treatment, suggesting that it did not involve self-replication of replicon RNA. Similar results were obtained in highly SARS-CoV-2 infection-permissive Calu-3 cells. Strikingly, prior expression of the SARS-CoV-2 N protein boosted expression from transfected SARS-CoV-2 RNA replicon but not from the replicon BAC DNA. In conclusion, transfection of a large DNA encoding a coronaviral replicon led to reproducible replicon gene expression through an unidentified mechanism. These findings highlight a novel pathway toward replicon gene expression from transfected replicon cDNA, offering valuable insights for the development of methods for DNA-based RNA replicon applications.

A Novel Case of IFNAR1 Deficiency Identified a Common Canonical Splice Site Variant in DOCK8 in Western Polynesia: The Importance of Validating Variants of Unknown Significance in Under-Represented Ancestries.

Advanced genomic technologies such as whole exome or whole genome sequencing have improved diagnoses and disease outcomes for individuals with genetic diseases. Yet, variants of unknown significance (VUS) require rigorous validation to establish disease causality or modification, or to exclude them from further analysis. Here, we describe a young individual of Polynesian ancestry who in the first 13 mo of life presented with SARS-CoV-2 pneumonia, severe enterovirus meningitis and adenovirus gastroenteritis, and severe adverse reaction to MMR vaccination. Genomic analysis identified a previously reported pathogenic homozygous variant in IFNAR1 (c.1156G > T, p.Glu386* LOF), which is common in Western Polynesia. Moreover, a new and putatively deleterious canonical splice site variant in DOCK8 was also found in homozygosity (c.3234 + 2T > C). This DOCK8 variant is common in Polynesians and other under-represented ancestries in large genomic databases. Despite in silico bioinformatic predictions, extensive in vitro and ex vivo analysis revealed the DOCK8 variant likely be neutral. Thus, our study reports a novel case of IFNAR1 deficiency, but also highlights the importance of functional validation of VUS, including those predicted to be deleterious, and the pressing need to expand our knowledge of the genomic architecture and landscape of under-represented populations and ancestries.

Investigation of the relationship between COVID-19 and pancreatic cancer using bioinformatics and systems biology approaches.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, poses a huge threat to human health. Pancreatic cancer (PC) is a malignant tumor with high mortality. Research suggests that infection with SARS-CoV-2 may increase disease severity and risk of death in patients with pancreatic cancer, while pancreatic cancer may also increase the likelihood of contracting SARS-CoV-2, but the link is unclear. METHODS: This study investigated the transcriptional profiles of COVID-19 and PC patients, along with their respective healthy controls, using bioinformatics and systems biology approaches to uncover the molecular mechanisms linking the 2 diseases. Specifically, gene expression data for COVID-19 and PC patients were obtained from the Gene Expression Omnibus datasets, and common differentially expressed genes (DEGs) were identified. Gene ontology and pathway enrichment analyses were performed on the common DEGs to elucidate the regulatory relationships between the diseases. Additionally, hub genes were identified by constructing a protein-protein interaction network from the shared DEGs. Using these hub genes, we conducted regulatory network analyses of microRNA/transcription factors-genes relationships, and predicted potential drugs for treating COVID-19 and PC. RESULTS: A total of 1722 and 2979 DEGs were identified from the transcriptome data of PC (GSE119794) and COVID-19 (GSE196822), respectively. Among these, 236 common DEGs were found between COVID-19 and PC based on protein-protein interaction analysis. Functional enrichment analysis indicated that these shared DEGs were involved in pathways related to viral genome replication and tumorigenesis. Additionally, 10 hub genes, including extra spindle pole bodies like 1, holliday junction recognition protein, marker of proliferation Ki-67, kinesin family member 4A, cyclin-dependent kinase 1, topoisomerase II alpha, cyclin B2, ubiquitin-conjugating enzyme E2 C, aurora kinase B, and targeting protein for Xklp2, were identified. Regulatory network analysis revealed 42 transcription factors and 23 microRNAs as transcriptional regulatory signals. Importantly, lucanthone, etoposide, troglitazone, resveratrol, calcitriol, ciclopirox, dasatinib, enterolactone, methotrexate, and irinotecan emerged as potential therapeutic agents against both COVID-19 and PC. CONCLUSION: This study unveils potential shared pathogenic mechanisms between PC and COVID-19, offering novel insights for future research and therapeutic strategies for the treatment of PC and SARS-CoV-2 infection.

Revealing differential expression patterns of piRNA in FACS blood cells of SARS-CoV-2 infected patients.

Non-coding RNA expression has shown to have cell type-specificity. The regulatory characteristics of these molecules are impacted by changes in their expression levels. We performed next-generation sequencing and examined small RNA-seq data obtained from 6 different types of blood cells separated by fluorescence-activated cell sorting of severe COVID-19 patients and healthy control donors. In addition to examining the behavior of piRNA in the blood cells of severe SARS-CoV-2 infected patients, our aim was to present a distinct piRNA differential expression portrait for each separate cell type. We observed that depending on the type of cell, different sorted control cells (erythrocytes, monocytes, lymphocytes, eosinophils, basophils, and neutrophils) have altering piRNA expression patterns. After analyzing the expression of piRNAs in each set of sorted cells from patients with severe COVID-19, we observed 3 significantly elevated piRNAs - piR-33,123, piR-34,765, piR-43,768 and 9 downregulated piRNAs in erythrocytes. In lymphocytes, all 19 piRNAs were upregulated. Monocytes were presented with a larger amount of statistically significant piRNA, 5 upregulated (piR-49039 piR-31623, piR-37213, piR-44721, piR-44720) and 35 downregulated. It has been previously shown that piR-31,623 has been associated with respiratory syncytial virus infection, and taking in account the major role of piRNA in transposon silencing, we presume that the differential expression patterns which we observed could be a signal of indirect antiviral activity or a specific antiviral cell state. Additionally, in lymphocytes, all 19 piRNAs were upregulated.

Single-cell transcriptomic analysis of B cells reveals new insights into atypical memory B cells in COVID-19.

Here, we performed single-cell RNA sequencing of S1 and receptor binding domain protein-specific B cells from convalescent COVID-19 patients with different clinical manifestations. This study aimed to evaluate the role and developmental pathway of atypical memory B cells (MBCs) in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The results revealed a proinflammatory signature across B cell subsets associated with disease severity, as evidenced by the upregulation of genes such as GADD45B, MAP3K8, and NFKBIA in critical and severe individuals. Furthermore, the analysis of atypical MBCs suggested a developmental pathway similar to that of conventional MBCs through germinal centers, as indicated by the expression of several genes involved in germinal center processes, including CXCR4, CXCR5, BCL2, and MYC. Additionally, the upregulation of genes characteristic of the immune response in COVID-19, such as ZFP36 and DUSP1, suggested that the differentiation and activation of atypical MBCs may be influenced by exposure to SARS-CoV-2 and that these genes may contribute to the immune response for COVID-19 recovery. Our study contributes to a better understanding of atypical MBCs in COVID-19 and the role of other B cell subsets across different clinical manifestations.

Investigating the Hepcidin Gene Polymorphisms in COVID-19-Associated Mucormycosis Susceptibility: A Clinical-Laboratory Study.

Background: Following the coronavirus disease 2019 outbreak (COVID-19), it became a worrisome health burden worldwide. COVID-19-associated mucormycosis emergence, characterized by dysregulated inflammation and iron metabolism, exacerbated the prognosis of affected patients. Given the significance of hepcidin in regulating inflammation and iron metabolism, this study investigated the significance of hepcidin single nucleotide polymorphisms (SNP) in COVID-19-associated mucormycosis development, along with the association between the clinical and laboratory factors and COVID-19-associated mucormycosis. Methods: From September 2021 to November 2021, COVID-19 patients with and without mucormycosis were enrolled in this cross-sectional study. Their medical records and laboratory results were investigated. SNP genotyping was performed using Sanger sequencing. Hardy-Weinberg Equilibrium, Pearson's Chi square, and student t test were used for analyzing the data using SPSS software version 25. P<0.05 was regarded as statistically significant. Results: Here, 110 COVID-19 patients with and without mucormycosis were investigated. Elevated levels of urea, aspartate aminotransferase, lactate dehydrogenase, and increased ratio of polymorphonuclear neutrophil to lymphocytes were associated with decreased risk of COVID-19-associated mucormycosis in patients (all P<0.05). Moreover, diabetes mellitus increased the risk of mucormycosis (P=0.028). In contrast to patients without mucormycosis, patients with mucormycosis did not display 442 GA and SNP335 GT genotypes. Unlike patients without mucormycosis, none of the patients with mucormycosis had SNP442 GA and SNP335 GT genotypes. Regarding SNP 443 C>T, and the combination of SNPs 582 A>G and 443 C>T, CC genotype and AA+CC genotypes were associated with increased lactate dehydrogenase levels in COVID-19 patients, respectively. Conclusion: Regarding SNP 443 C>T, the CC genotype was associated with increased lactate dehydrogenase levels in COVID-19 patients. In terms of SNP 582 A>G and SNP 443 C>T, COVID-19 patients with AA+CC genotypes had higher levels of LDH. None of the patients with mucormycosis had SNP442 GA and SNP335 GT genotypes.

Association between Methylenetetrahydrofolate Reductase (MTHFR) and 5-Methyltetrahydrofolate-Homocysteine Methyltransferase Reductase (MTRR) Polymorphisms in Iraqi Patients with COVID-19.

Background: The methylenetetrahydrofolate reductase (MTHFR) gene is an essential gene in the metabolism of folate-homocysteine. Recently, the level of homocysteine was found to be a significant marker in the follow-up of COVID-19 infection. Thus, this study aimed to detect the effect of genetic polymorphisms for single nucleotide polymorphisms (SNPs) (c.66A>G, c.1298A>C, and c.677CT) on COVID-19 infection. Methods: Blood samples were collected from 270 patients with COVID-19 in the medical center of Al-Shifa (Baghdad, Iraq) from November 2020 to March 2021. Tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) technique was used for the detection of genotypes of SNPs. The odds ratio (OR) was used to detect the relationship between SNPs and COVID-19 infections. Haplotype analysis was performed by SHEsis software. Results: There was a significant difference between mild/moderate cases and severe/critical cases for ages (35-45), (46-55), and (56-65) years (P<0.0001, P=0.01, and P=0.006, respectively). The results showed significant differences in the T allele for SNP c.677>C (P<0.0001 and OR=4.58). The C allele for SNP c.1298A>C indicated significant differences (P<0.001 and OR=3.15). Besides, the G allele for SNP c.677C>T showed significant differences (P<0.001 and OR=6.64). Consequently, these SNPs showed a predisposition to the development of COVID-19 infection. With regard to the C-A-A, T-A-A and T-C-G haplotypes indicated significant differences between the control and patient groups. The C-A-A was related to a decreased risk and indicated a protective effect against COVID-19 infection development (P<0.0001 and OR=0.218). The increased risk was associated with T-A-A and T-C-G haplotypes and indicated the risk impact on COVID-19 infection development (P<0.0001, P=0.004, and OR=15.5, OR=6.772, respectively). Furthermore, the linkage disequilibrium (LD) for SNPs was studied, and the complete D' value was 99. Conclusion: The genetic polymorphisms of SNPs (c.66A>G, c.1298A>C, and c.677C>T) in the Iraqi population were associated with COVID-19 infection.

nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework.

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets.

SARS-CoV-2 population dynamics in immunocompetent individuals in a closed transmission chain shows genomic diversity over the course of infection.

BACKGROUND: SARS-CoV-2 remains rapidly evolving, and many biologically important genomic substitutions/indels have characterised novel SARS-CoV-2 lineages, which have emerged during successive global waves of the pandemic. Worldwide genomic sequencing has been able to monitor these waves, track transmission clusters, and examine viral evolution in real time to help inform healthcare policy. One school of thought is that an apparent greater than average divergence in an emerging lineage from contemporary variants may require persistent infection, for example in an immunocompromised host. Due to the nature of the COVID-19 pandemic and sampling, there were few studies that examined the evolutionary trajectory of SARS-CoV-2 in healthy individuals. METHODS: We investigated viral evolutionary trends and participant symptomatology within a cluster of 16 SARS-CoV-2 infected, immunocompetent individuals with no co-morbidities in a closed transmission chain. Longitudinal nasopharyngeal swab sampling allowed characterisation of SARS-CoV-2 intra-host variation over time at both the dominant and minor genomic variant levels through Nimagen-Illumina sequencing. RESULTS: A change in viral lineage assignment was observed in individual infections; however, there was only one indel and no evidence of recombination over the period of an acute infection. Minor and dominant genomic modifications varied between participants, with some minor genomic modifications increasing in abundance to become the dominant viral sequence during infection. CONCLUSIONS: Data from this cohort of SARS-CoV-2-infected participants demonstrated that long-term persistent infection in an immunocompromised host was not necessarily a prerequisite for generating a greater than average frequency of amino acid substitutions. Amino acid substitutions at both the dominant and minor genomic sequence level were observed in immunocompetent individuals during infection showing that viral lineage changes can occur generating viral diversity.

In-silico discovery of common molecular signatures for which SARS-CoV-2 infections and lung diseases stimulate each other, and drug repurposing.

COVID-19 caused by SARS-CoV-2 is a global health issue. It is yet a severe risk factor to the patients, who are also suffering from one or more chronic diseases including different lung diseases. In this study, we explored common molecular signatures for which SARS-CoV-2 infections and different lung diseases stimulate each other, and associated candidate drug molecules. We identified both SARS-CoV-2 infections and different lung diseases (Asthma, Tuberculosis, Cystic Fibrosis, Pneumonia, Emphysema, Bronchitis, IPF, ILD, and COPD) causing top-ranked 11 shared genes (STAT1, TLR4, CXCL10, CCL2, JUN, DDX58, IRF7, ICAM1, MX2, IRF9 and ISG15) as the hub of the shared differentially expressed genes (hub-sDEGs). The gene ontology (GO) and pathway enrichment analyses of hub-sDEGs revealed some crucial common pathogenetic processes of SARS-CoV-2 infections and different lung diseases. The regulatory network analysis of hub-sDEGs detected top-ranked 6 TFs proteins and 6 micro RNAs as the key transcriptional and post-transcriptional regulatory factors of hub-sDEGs, respectively. Then we proposed hub-sDEGs guided top-ranked three repurposable drug molecules (Entrectinib, Imatinib, and Nilotinib), for the treatment against COVID-19 with different lung diseases. This recommendation is based on the results obtained from molecular docking analysis using the AutoDock Vina and GLIDE module of Schrödinger. The selected drug molecules were optimized through density functional theory (DFT) and observing their good chemical stability. Finally, we explored the binding stability of the highest-ranked receptor protein RELA with top-ordered three drugs (Entrectinib, Imatinib, and Nilotinib) through 100 ns molecular dynamic (MD) simulations with YASARA and Desmond module of Schrödinger and observed their consistent performance. Therefore, the findings of this study might be useful resources for the diagnosis and therapies of COVID-19 patients who are also suffering from one or more lung diseases.

Single cell multi-omic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients.

Introduction: Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing. Methods: To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omics approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls. Results: We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC. Discussion: Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.