Prior Vaccination Exceeds Prior Infection in Eliciting Innate and Humoral Immune Responses in Omicron Infected Outpatients

Disease-Associated Mutations of the STAT5B SH2 Domain Regulate Cytokine-Driven Enhancer Function and Mammary Development

Mammary gland development during pregnancy is controlled by lactogenic hormones via the JAK2-STAT5 pathway. Gene deletion studies in mice have revealed the crucial roles of both STAT5A and STAT5B in establishing the genetic programs necessary for the development of mammary epithelium and successful lactation. Several hundred single nucleotide polymorphisms (SNPs) have been identified in human STAT5B, although their pathophysiological significance remains largely unknown. The SH2 domain is vital for STAT5B activation, and this study focuses on the impact of two specific missense mutations identified in T cell leukemias, the substitution of tyrosine 665 with either phenylalanine (Y665F) or histidine (Y665H). By introducing these human mutations into the mouse genome, we uncovered distinct and opposite functions. Mice harboring the STAT5BY665H mutation failed to develop functional mammary tissue, resulting in lactation failure, while STAT5BY665F mice exhibited accelerated mammary development during pregnancy. Transcriptomic and epigenomic analyses identified STAT5BY665H as Loss-Of-Function (LOF) mutation, impairing enhancer establishment and alveolar differentiation, whereas STAT5BY665F acted as a Gain-Of-Function (GOF) mutation, elevating enhancer formation. Persistent hormonal stimulation through two pregnancies led to the establishment of enhancer structures, gene expression and successful lactation in STAT5BY665H mice. Lastly, we demonstrate that Olah, a gene known to drive life-threatening viral disease in humans, is regulated by STAT5B through a candidate four-partite super-enhancer. In conclusion, our findings underscore the role of human STAT5B variants in modulating mammary gland homeostasis and their critical impact on lactation.

Lethal COVID-19 associates with RAAS-induced inflammation for multiple organ damage including mediastinal lymph nodes

Lethal COVID-19 outcomes are attributed to classic cytokine storm. We revisit this using RNA sequencing of nasopharyngeal and 40 autopsy samples from patients dying of SARS-CoV-2. Subsets of the 100 top-upregulated genes in nasal swabs are upregulated in the heart, lung, kidney, and liver, but not mediastinal lymph nodes. Twenty-two of these are "noncanonical" immune genes, which we link to components of the renin-angiotensin-activation-system that manifest as increased fibrin deposition, leaky vessels, thrombotic tendency, PANoptosis, and mitochondrial dysfunction. Immunohistochemistry of mediastinal lymph nodes reveals altered architecture, excess collagen deposition, and pathogenic fibroblast infiltration. Many of the above findings are paralleled in animal models of SARS-CoV-2 infection and human peripheral blood mononuclear and whole blood samples from individuals with early and later SARS-CoV-2 variants. We then redefine cytokine storm in lethal COVID-19 as driven by upstream immune gene and mitochondrial signaling producing downstream RAAS (renin-angiotensin-aldosterone system) overactivation and organ damage, including compromised mediastinal lymph node function.

Deciphering the molecular nexus between Omicron infection and acute kidney injury: a bioinformatics approach

Background

The ongoing global health crisis of COVID-19, and particularly the challenges posed by recurrent infections of the Omicron variant, have significantly strained healthcare systems worldwide. There is a growing body of evidence indicating an increased susceptibility to Omicron infection in patients suffering from Acute Kidney Injury (AKI). However, the intricate molecular interplay between AKI and Omicron variant of COVID-19 remains largely enigmatic.

Methods

This study employed a comprehensive analysis of human RNA sequencing (RNA-seq) and microarray datasets to identify differentially expressed genes (DEGs) associated with Omicron infection in the context of AKI. We engaged in functional enrichment assessments, an examination of Protein-Protein Interaction (PPI) networks, and advanced network analysis to elucidate the cellular signaling pathways involved, identify critical hub genes, and determine the relevant controlling transcription factors and microRNAs. Additionally, we explored protein-drug interactions to highlight potential pharmacological interventions.

Results

Our investigation revealed significant DEGs and cellular signaling pathways implicated in both Omicron infection and AKI. We identified pivotal hub genes, including EIF2AK2, PLSCR1, GBP1, TNFSF10, C1QB, and BST2, and their associated regulatory transcription factors and microRNAs. Notably, in the murine AKI model, there was a marked reduction in EIF2AK2 expression, in contrast to significant elevations in PLSCR1, C1QB, and BST2. EIF2AK2 exhibited an inverse relationship with the primary AKI mediator, Kim-1, whereas PLSCR1 and C1QB demonstrated strong positive correlations with it. Moreover, we identified potential therapeutic agents such as Suloctidil, Apocarotenal, 3'-Azido-3'-deoxythymidine, among others. Our findings also highlighted a correlation between the identified hub genes and diseases like myocardial ischemia, schizophrenia, and liver cirrhosis. To further validate the credibility of our data, we employed an independent validation dataset to verify the hub genes. Notably, the expression patterns of PLSCR1, GBP1, BST2, and C1QB were consistent with our research findings, reaffirming the reliability of our results.

Conclusion

Our bioinformatics analysis has provided initial insights into the shared genetic landscape between Omicron COVID-19 infections and AKI, identifying potential therapeutic targets and drugs. This preliminary investigation lays the foundation for further research, with the hope of contributing to the development of innovative treatment strategies for these complex medical conditions.

A T-Cell-Derived 3-Gene Signature Distinguishes SARS-CoV-2 from Common Respiratory Viruses

Research on the host responses to respiratory viruses could help develop effective interventions and therapies against the current and future pandemics from the host perspective. To explore the pathogenesis that distinguishes SARS-CoV-2 infections from other respiratory viruses, we performed a multi-cohort analysis with integrated bioinformatics and machine learning. We collected 3730 blood samples from both asymptomatic and symptomatic individuals infected with SARS-CoV-2, seasonal human coronavirus (sHCoVs), influenza virus (IFV), respiratory syncytial virus (RSV), or human rhinovirus (HRV) across 15 cohorts. First, we identified an enhanced cellular immune response but limited interferon activities in SARS-CoV-2 infection, especially in asymptomatic cases. Second, we identified a SARS-CoV-2-specific 3-gene signature (CLSPN, RBBP6, CCDC91) that was predominantly expressed by T cells, could distinguish SARS-CoV-2 infection, including Omicron, from other common respiratory viruses regardless of symptoms, and was predictive of SARS-CoV-2 infection before detectable viral RNA on RT-PCR testing in a longitude follow-up study. Thereafter, a user-friendly online tool, based on datasets collected here, was developed for querying a gene of interest across multiple viral infections. Our results not only identify a unique host response to the viral pathogenesis in SARS-CoV-2 but also provide insights into developing effective tools against viral pandemics from the host perspective.

STAT5B SH2 variants disrupt mammary enhancers and the stability of genetic programs during pregnancy

During pregnancy, mammary tissue undergoes expansion and differentiation, leading to lactation, a process regulated by the hormone prolactin through the JAK2-STAT5 pathway. STAT5 activation is key to successful lactation making the mammary gland an ideal experimental system to investigate the impact of human missense mutations on mammary tissue homeostasis. Here, we investigated the effects of two human variants in the STAT5B SH2 domain, which convert tyrosine 665 to either phenylalanine (Y665F) or histidine (Y665H), both shown to activate STAT5B in cell culture. We ported these mutations into the mouse genome and found distinct and divergent functions. Homozygous Stat5bY665H mice failed to form functional mammary tissue, leading to lactation failure, with impaired alveolar development and greatly reduced expression of key differentiation genes. STAT5BY665H failed to recognize mammary enhancers and impeded STAT5A binding. In contrast, mice carrying the Stat5bY665F mutation exhibited abnormal precocious development, accompanied by an early activation of the mammary transcription program and the induction of otherwise silent genetic programs. Physiological adaptation was observed in Stat5bY665H mice as continued exposure to pregnancy hormones led to lactation. In summary, our findings highlight that human STAT5B variants can modulate their response to cytokines and thereby impact mammary homeostasis and lactation.

Modulation of innate immune response to mRNA vaccination after SARS-CoV-2 infection or sequential vaccination in humans

mRNA vaccines are likely to become widely used for the prevention of infectious diseases in the future. Nevertheless, a notable gap exists in mechanistic data, particularly concerning the potential effects of sequential mRNA immunization or preexisting immunity on the early innate immune response triggered by vaccination. In this study, healthy adults, with or without documented prior SARS-CoV-2 infection, were vaccinated with the BNT162b2/Comirnaty mRNA vaccine. Prior infection conferred significantly stronger induction of proinflammatory and type I IFN-related gene signatures, serum cytokines, and monocyte expansion after the prime vaccination. The response to the second vaccination further increased the magnitude of the early innate response in both study groups. The third vaccination did not further increase vaccine-induced inflammation. In vitro stimulation of PBMCs with TLR ligands showed no difference in cytokine responses between groups, or before or after prime vaccination, indicating absence of a trained immunity effect. We observed that levels of preexisting antigen-specific CD4 T cells, antibody, and memory B cells correlated with elements of the early innate response to the first vaccination. Our data thereby indicate that preexisting memory formed by infection may augment the innate immune activation induced by mRNA vaccines.

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we propose that RNA-seq should be considered a diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 196 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that-combined with sequence alignments and BLASTp-they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.

Diverging humoral and cellular immune responses due to Omicron-a national study from the Faroe Islands

IMPORTANCE

The immunity following infection and vaccination with the SARS-CoV-2 Omicron variant is poorly understood. We investigated immunity assessed with antibody and T-cell responses under different scenarios in vaccinated and unvaccinated individuals with and without Omicron infection. We found that the humoral response was higher among vaccinated-naïve than unvaccinated convalescent. Unvaccinated with and without infection had comparable low humoral responses, whereas vaccinated with a second or third dose, independent of infection status, had increasingly higher levels. Only a minor fraction of unvaccinated individuals had detectable humoral responses following Omicron infection, while almost all had positive T-cell responses. In conclusion, primary Omicron infection mounts a low humoral immune response, enhanced by prior vaccination. Omicron infection induced a robust T-cell response in both unvaccinated and vaccinated, demonstrating that immune evasion of primary Omicron infection affects humoral immunity more than T-cell immunity.

Omicron induced distinct immune respiratory transcriptomics signatures compared to pre-existing variants in critically ill COVID-19 patients

Severe coronavirus disease 2019 (COVID-19) is related to dysregulated immune responses. We aimed to explore the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants on the immune response by nasopharyngeal transcriptomic in critically-ill patients. This prospective monocentric study included COVID-19 patients requiring intensive care unit (ICU) admission between March 2020 and 2022. Patients were classified according to VOC (ancestral, Alpha, Delta, and Omicron). Eighty-eight patients with severe COVID-19 were included after matching (on prespecified clinical criteria). Profiling of gene expression markers of innate and adaptive immune responses were investigated by respiratory transcriptomics at ICU admission. Eighty-eight patients were included in the study after matching (ancestral [n = 24], Alpha [n = 24], Delta [n = 22], and Omicron [n = 18] variants). Respiratory transcriptomic analysis revealed distinct innate and adaptive immune profiling between variants. In comparison with the ancestral variant, there was a reduced expression of neutrophil degranulation, T cell activation, cytokines signalling pathways in patients infected with Alpha and Delta variants. In contrast, there was a higher expression of neutrophil degranulation, T and B cells activation, and inflammatory interleukins pathways in patients infected with Omicron. To conclude, Omicron induced distinct immune respiratory transcriptomics signatures compared to pre-existing variants in patients with severe COVID-19, pointing to an evolving pathophysiology of severe COVID-19 in the Omicron era.

Variant- and Vaccination-Specific Alternative Splicing Profiles in SARS-CoV-2 Infections

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, and its subsequent variants has underscored the importance of understanding the host-viral molecular interactions to devise effective therapeutic strategies. A significant aspect of these interactions is the role of alternative splicing in modulating host responses and viral replication mechanisms. Our study sought to delineate the patterns of alternative splicing of RNAs from immune cells across different SARS-CoV-2 variants and vaccination statuses, utilizing a robust dataset of 190 RNA-seq samples from our previous studies, encompassing an average of 212 million reads per sample. We identified a dynamic alteration in alternative splicing and genes related to RNA splicing were highly deactivated in COVID-19 patients and showed variant- and vaccination-specific expression profiles. Overall, Omicron-infected patients exhibited a gene expression profile akin to healthy controls, unlike the Alpha or Beta variants. However, significantly, we found identified a subset of infected individuals, most pronounced in vaccinated patients infected with Omicron variant, that exhibited a specific dynamic in their alternative splicing patterns that was not widely shared amongst the other groups. Our findings underscore the complex interplay between SARS-CoV-2 variants, vaccination-induced immune responses, and alternative splicing, emphasizing the necessity for further investigations into these molecular cross-talks to foster deeper understanding and guide strategic therapeutic development.

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers vital insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 240 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that - combined with sequence alignments and pBLAST - they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.

The Longitudinal Analysis of Convergent Antibody VDJ Regions in SARS-CoV-2-Positive Patients Using RNA-Seq

Severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) is an ongoing pandemic that continues to evolve and reinfect individuals. To understand the convergent antibody responses that evolved over the course of the pandemic, we evaluated the immunoglobulin repertoire of individuals infected by different SARS-CoV-2 variants for similarity between patients. We utilized four public RNA-seq data sets collected between March 2020 and March 2022 from the Gene Expression Omnibus (GEO) in our longitudinal analysis. This covered individuals infected with Alpha and Omicron variants. In total, from 269 SARS-CoV-2-positive patients and 26 negative patients, 629,133 immunoglobulin heavy-chain variable region V(D)J sequences were reconstructed from sequencing data. We grouped samples based on the SARS-CoV-2 variant type and/or the time they were collected from patients. Our comparison of patients within each SARS-CoV-2-positive group found 1011 common V(D)Js (same V gene, J gene and CDR3 amino acid sequence) shared by more than one patient and no common V(D)Js in the noninfected group. Taking convergence into account, we clustered based on similar CDR3 sequence and identified 129 convergent clusters from the SARS-CoV-2-positive groups. Within the top 15 clusters, 4 contain known anti-SARS-CoV-2 immunoglobulin sequences with 1 cluster confirmed to cross-neutralize variants from Alpha to Omicron. In our analysis of longitudinal groups that include Alpha and Omicron variants, we find that 2.7% of the common CDR3s found within groups were also present in more than one group. Our analysis reveals common and convergent antibodies, which include anti-SARS-CoV-2 antibodies, in patient groups over various stages of the pandemic.

Identification of dynamic gene expression profiles during sequential vaccination with ChAdOx1/BNT162b2 using machine learning methods

To date, COVID-19 remains a serious global public health problem. Vaccination against SARS-CoV-2 has been adopted by many countries as an effective coping strategy. The strength of the body’s immune response in the face of viral infection correlates with the number of vaccinations and the duration of vaccination. In this study, we aimed to identify specific genes that may trigger and control the immune response to COVID-19 under different vaccination scenarios. A machine learning-based approach was designed to analyze the blood transcriptomes of 161 individuals who were classified into six groups according to the dose and timing of inoculations, including I-D0, I-D2-4, I-D7 (day 0, days 2–4, and day 7 after the first dose of ChAdOx1, respectively) and II-D0, II-D1-4, II-D7-10 (day 0, days 1–4, and days 7–10 after the second dose of BNT162b2, respectively). Each sample was represented by the expression levels of 26,364 genes. The first dose was ChAdOx1, whereas the second dose was mainly BNT162b2 (Only four individuals received a second dose of ChAdOx1). The groups were deemed as labels and genes were considered as features. Several machine learning algorithms were employed to analyze such classification problem. In detail, five feature ranking algorithms (Lasso, LightGBM, MCFS, mRMR, and PFI) were first applied to evaluate the importance of each gene feature, resulting in five feature lists. Then, the lists were put into incremental feature selection method with four classification algorithms to extract essential genes, classification rules and build optimal classifiers. The essential genes, namely, NRF2, RPRD1B, NEU3, SMC5, and TPX2, have been previously associated with immune response. This study also summarized expression rules that describe different vaccination scenarios to help determine the molecular mechanism of vaccine-induced antiviral immunity.

Weighted gene co-expression network-based identification of genetic effect of mRNA vaccination and previous infection on SARS-CoV-2 infection

To investigate the effect conferred by vaccination and previous infection against SARS-CoV-2 infection in molecular level, weighted gene co-expression network analysis was applied to screen vaccination, prior infection and Omicron infection-related gene modules in 46 Omicron outpatients and 8 controls, and CIBERSORT algorithm was used to infer the proportions of 22 subsets of immune cells. 15 modules were identified, where the brown module showed positive correlations with Omicron infection (r = 0.35, P = 0.01) and vaccination (r = 0.62, P = 1 × 10^-6). Enrichment analysis revealed that LILRB2 was the unique gene shared by both phosphatase binding and MHC class I protein binding. Pathways including "B cell receptor signaling pathway" and "FcγR-mediated phagocytosis" were enriched in the vaccinated samples of the highly correlated LILRB2. LILRB2 was also identified as the second hub gene through PPI network, after LCP2. In conclusion, attenuated LILRB2 transcription in PBMC might highlight a novel target in overcoming immune evasion and improving vaccination strategies.

Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study

Objective

Despite extensive vaccination campaigns to combat the coronavirus disease (COVID-19) pandemic, variants of concern, particularly the Omicron variant (B.1.1.529 or BA.1), may escape the antibodies elicited by vaccination against SARS-CoV-2. Therefore, this study aimed to evaluate 50% neutralizing activity (NT₅₀) against SARS-CoV-2 D614G, Delta, Omicron BA.1, and Omicron BA.2 and to develop prediction models to predict the risk of infection in a general population in Japan.

Methods

We used a random 10% of samples from 1,277 participants in a population-based cross-sectional survey conducted in January and February 2022 in Yokohama City, the most populous municipality in Japan. We measured NT₅₀ against D614G as a reference and three variants (Delta, Omicron BA.1, and BA.2) and immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG).

Results

Among 123 participants aged 20-74, 93% had received two doses of SARS-CoV-2 vaccine. The geometric means (95% confidence intervals) of NT₅₀ were 65.5 (51.8-82.8) for D614G, 34.3 (27.1-43.4) for Delta, 14.9 (12.2-18.0) for Omicron BA.1, and 12.9 (11.3-14.7) for Omicron BA.2. The prediction model with SP-IgG titers for Omicron BA.1 performed better than the model for Omicron BA.2 (bias-corrected R ² with bootstrapping: 0.721 vs. 0.588). The models also performed better for BA.1 than for BA.2 (R ² = 0.850 vs. 0.150) in a validation study with 20 independent samples.

Conclusion

In a general Japanese population with 93% of the population vaccinated with two doses of SARS-CoV-2 vaccine, neutralizing activity against Omicron BA.1 and BA.2 were substantially lower than those against D614G or the Delta variant. The prediction models for Omicron BA.1 and BA.2 showed moderate predictive ability and the model for BA.1 performed well in validation data.

Clinical characteristics and risk factors for a prolonged length of stay of patients with asymptomatic and mild COVID-19 during the wave of Omicron from Shanghai, China

BACKGROUND

This study aims to investigate the clinical characteristics and the length of hospital stay (LOS), as well as risk factors for prolonged LOS in a cohort of asymptomatic and mild COVID-19 patients infected with the Omicron variant.

METHODS

A total of 1166 COVID-19 patients discharged from the inpatient ward of the largest makeshift hospital (May 8-10, 2022) in Shanghai, China, were included. The demographics, medical history, and the lowest and admission cycle threshold (Ct) values of the RT-PCR tests for SARS-CoV-2 genes of the open reading frame 1ab (Ct-ORF) and the nucleocapsid protein (Ct-N) during hospitalization were recorded. Patients with LOS > 7 days, or LOS ≤ 7 days were included in the Prolonged group or the Control group, separately. The clinical characteristics and LOS of the participants in the two groups were described and compared. Multivariate Logistic and linear regression analyses were applied to explore the risk factors for prolonged LOS. The diagnostic efficacy of the lowest and admission Ct values for the Prolonged group was tested via the receiver operating characteristic (ROC) curve analysis.

RESULTS

The median LOS was 6 days in the total study population. The age was older (45.52 ± 14.78 vs. 42.54 ± 15.30, P = 0.001), while both the lowest and admission Ct-ORF (27.68 ± 3.88 vs. 37.00 ± 4.62, P < 0.001; 30.48 ± 5.03 vs. 37.79 ± 3.81, P < 0.001) and Ct-N (25.79 ± 3.60 vs. 36.06 ± 5.39, P < 0.001; 28.71 ± 4.95 vs. 36.95 ± 4.59, P < 0.001) values were significantly lower in the Prolonged group. There were more mild cases in the Prolonged group (23.8% vs. 11.5%, P < 0.001). The symptom spectrum differed between the two groups. In multivariate analyses, age, disease category, and the lowest Ct-N values were shown to be associated with prolonged LOS. Besides, both the lowest and admission Ct-ORF (AUC = 0.911 and 0.873) and Ct-N (AUC = 0.912 and 0.874) showed robust diagnostic efficacy for prolonged LOS.

CONCLUSIONS

Our study firstly reports the clinical characteristics and risk factors for prolonged LOS during the wave of the Omicron epidemic in Shanghai, China. These findings provide evidence for the early identification of asymptomatic and mild COVID-19 patients at a high risk of prolonged hospitalization who may require early intervention, and long-term monitoring and management.

Strong Neutralizing Antibody Responses to SARS-CoV-2 Variants Following a Single Vaccine Dose in Subjects With Previous SARS-CoV-2 Infection

BACKGROUND

Previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection primes the immune system; thus individuals who have recovered from infection have enhanced immune responses to subsequent vaccination (hybrid immunity). However, it remains unclear how well hybrid immunity induced by severe or mild infection can cross-neutralize emerging variants. We aimed to compare the strength and breadth of antibody responses in vaccinated recovered and uninfected subjects.

METHODS

We measured spike-specific immunoglobulin (Ig)G and neutralizing antibodies (NAbs) from vaccinated subjects including 320 with hybrid immunity and 20 without previous infection. From 29 subjects with a previous severe or mild infection, we also measured NAb responses against Alpha (B.1.1.7), Beta (B.1.351), Delta (B.1.617.2), and Omicron (B.1.1.529/BA.1) variants following vaccination.

RESULTS

A single vaccine dose induced 2-fold higher anti-spike IgG concentrations and up to 4-fold higher neutralizing potency of antibodies in subjects with a previous infection compared with vaccinated subjects without a previous infection. Hybrid immunity was more enhanced after a severe than a mild infection, with sequentially decreasing NAb titers against Alpha, Beta, Delta, and Omicron variants. We found similar IgG concentrations in subjects with a previous infection after 1 or 2 vaccine doses.

CONCLUSIONS

Hybrid immunity induced strong IgG responses, particularly after severe infection. However, the NAb titers were low against heterologous variants, especially against Omicron.

Genomic Transcriptome Benefits and Potential Harms of COVID-19 Vaccines Indicated from Optimized Genomic Biomarkers

COVID-19 vaccines can be the tugboats for preventing SARS-CoV-2 infections when they are practical and, more importantly, without adverse effects. However, the reality is that they may result in short-term or long-term impacts on COVID-19-related diseases and even trigger the formation of new variants of SARS-CoV-2. Using published data, we use a set of optimized-performance COVID-19 genomic biomarkers (MND1, CDC6, ZNF282) to study the benefits and adverse effects of the BNT162b2 vaccine. We found that the vaccine lowered the expression values of genes MND1 and CDC6 while heightening the expression values of ZNF282 in individuals who are SARS-CoV-2 naïve, which is expected and satisfies the biological equivalence between the COVID-19 disease and the genomic signature patterns established in the literature. However, we also found that COVID-19-convalescent octogenarians responded reversely. The vaccine heightened the expression values of MND1 and CDC6. In addition, it lowered the expression values of ZNF282. Such adverse effects raise outstanding concerns about whether or not COVID-19-convalescent individuals should take the current vaccine or when they can take it. These findings are new at the genomic level and can provide insights into developing next-generation vaccines, antiviral drugs, and pandemic management guidance.

Genomic Biomarker Heterogeneities between SARS-CoV-2 and COVID-19

Genes functionally associated with SARS-CoV-2 infection and genes functionally related to the COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in the transcriptional response to SARS-CoV-2 infection with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with another gene in predicting disease status to achieve better-indicating accuracy than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. These two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction with their exceptional predicting accuracy. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in our earlier work, the genes and their transcriptional response and functional effects on SARS-CoV-2 infection, and the genes and their functional signature patterns on COVID-19 antibodies, are significantly different. We will use a total of fourteen cohort studies (including breakthrough infections and omicron variants) with 1481 samples to justify our results. Such significant findings can help explore the causal and pathological links between SARS-CoV-2 infection and the COVID-19 disease, and fight against the disease with more targeted genes, vaccines, antiviral drugs, and therapies.

Omicron BA.4/BA.5 escape neutralizing immunity elicited by BA.1 infection

SARS-CoV-2 Omicron (B.1.1.529) BA.4 and BA.5 sub-lineages, first detected in South Africa, have changes relative to Omicron BA.1 including substitutions in the spike receptor binding domain. Here we isolated live BA.4 and BA.5 viruses and measured BA.4/BA.5 neutralization elicited by BA.1 infection either in the absence or presence of previous vaccination as well as from vaccination without BA.1 infection. In BA.1-infected unvaccinated individuals, neutralization relative to BA.1 declines 7.6-fold for BA.4 and 7.5-fold for BA.5. In vaccinated individuals with subsequent BA.1 infection, neutralization relative to BA.1 decreases 3.2-fold for BA.4 and 2.6-fold for BA.5. The fold-drop versus ancestral virus neutralization in this group is 4.0-fold for BA.1, 12.9-fold for BA.4, and 10.3-fold for BA.5. In contrast, BA.4/BA.5 escape is similar to BA.1 in the absence of BA.1 elicited immunity: fold-drop relative to ancestral virus neutralization is 19.8-fold for BA.1, 19.6-fold for BA.4, and 20.9-fold for BA.5. These results show considerable escape of BA.4/BA.5 from BA.1 elicited immunity which is moderated with vaccination and may indicate that BA.4/BA.5 may have the strongest selective advantage in evading neutralization relative to BA.1 in unvaccinated, BA.1 infected individuals.