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Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) (1-3). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.
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The COVID-19 pandemic, driven by the SARS-CoV-2 virus and its variants, highlights the important role of understanding host-viral molecular interactions influencing infection outcomes. Alternative splicing post-infection can impact both host responses and viral replication. We analyzed RNA splicing patterns in immune cells across various SARS-CoV-2 variants, considering immunization status. Using a dataset of 190 RNA-seq samples from our prior studies, we observed a substantial deactivation of alternative splicing and RNA splicing-related genes in COVID-19 patients. The alterations varied significantly depending on the infecting variant and immunization history. Notably, Alpha or Beta-infected patients differed from controls, while Omicron-infected patients displayed a splicing profile closer to controls. Particularly, vaccinated Omicron-infected individuals showed a distinct dynamic in alternative splicing patterns not widely shared among other groups. Our findings underscore the intricate interplay between SARS-CoV-2 variants, vaccination-induced immunity, and alternative splicing, emphasizing the need for further investigations to deepen understanding and guide therapeutic development.
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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.
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COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/genética , COVID-19/genética , Perfilación de la Expresión Génica , Receptores de Antígenos de Linfocitos T/genética , Análisis de Secuencia de ARN/métodos , InmunidadRESUMEN
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.
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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.
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Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs)1-3. Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL is the first application that demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.
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Preclinical in vitro models play an important role in studying cancer cell biology and facilitating translational research, especially in the identification of drug targets and drug discovery studies. This is particularly relevant in breast cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (radiotherapy, chemotherapy, immunotherapy, and/or surgery) are relatively lacking. To be clinically relevant, a model must accurately replicate the biology and cellular heterogeneity of the primary tumor. Addressing these requirements and overcoming the limitations of most existing cancer cell lines, which are typically derived from a single clone, we have recently developed conditional reprogramming (CR) technology. The CR technology refers to a co-culture system of primary human normal or tumor cells with irradiated murine fibroblasts in the presence of a Rho-associated kinase inhibitor to allow the primary cells to acquire stem cell properties and the ability to proliferate indefinitely in vitro without any exogenous gene or viral transfection. This innovative approach fulfills many of these needs and offers an alternative that surpasses the deficiencies associated with traditional cancer cell lines. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have applied CR technology to conduct breast cancer research.
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Neoplasias de la Mama , Humanos , Ratones , Animales , Femenino , Neoplasias de la Mama/genética , Técnicas de Cocultivo , Línea CelularRESUMEN
Motivation: Circular RNAs (circRNAs) are long noncoding RNAs (lncRNAs) often associated with diseases and considered potential biomarkers for diagnosis and treatment. Among other functions, circRNAs have been shown to act as microRNA (miRNA) sponges, preventing the role of miRNAs that repress their targets. However, there is no pipeline to systematically assess the sponging potential of circRNAs. Results: We developed circRNA-sponging, a nextflow pipeline that (i) identifies circRNAs via backsplicing junctions detected in RNA-seq data, (ii) quantifies their expression values in relation to their linear counterparts spliced from the same gene, (iii) performs differential expression analysis, (iv) identifies and quantifies miRNA expression from miRNA-sequencing (miRNA-seq) data, (v) predicts miRNA binding sites on circRNAs, (vi) systematically investigates potential circRNA-miRNA sponging events, (vii) creates a network of competing endogenous RNAs and (viii) identifies potential circRNA biomarkers. We showed the functionality of the circRNA-sponging pipeline using RNA sequencing data from brain tissues, where we identified two distinct types of circRNAs characterized by a specific ratio of the number of the binding site to the length of the transcript. The circRNA-sponging pipeline is the first end-to-end pipeline to identify circRNAs and their sponging systematically with raw total RNA-seq and miRNA-seq files, allowing us to better indicate the functional impact of circRNAs as a routine aspect in transcriptomic research. Availability and implementation: https://github.com/biomedbigdata/circRNA-sponging. Supplementary information: Supplementary data are available at Bioinformatics Advances online.
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Patients with chronic lymphocytic leukemia (CLL) treated with B-cell pathway inhibitors and anti-CD20 antibodies exhibit low humoral response rates following SARS-CoV-2 vaccination. To investigate this observation, a prospective single-institution study was conducted comparing peripheral blood mononuclear cell transcriptional response with antibody and T-cell response rates following heterologous BNT162b2/ChAdOx1 vaccination of 15 patients with CLL/small lymphocytic lymphoma (SLL). Two-dose antibody response rate was 40%, increasing to 53% after booster. Patients on Bruton tyrosine kinase inhibitor (BTKi) and venetoclax ± anti-CD20 antibody within 12 months of vaccination responded inferiorly compared with those under BTKi alone. The 2-dose-T-cell response rate was 80%, which increased to 93% after the booster dose. Key transcriptional findings were that interferon-mediated signaling activation including activation of the JAK-STAT pathway generally occurred within days of vaccination, but was independent from the magnitude of the antibody response. Increasing counts of IGHV genes were associated with B-cell reconstitution and improved humoral response rate in the vaccinated patients. T-cell responses in patients with CLL appeared independent of treatment status, whereas higher humoral response rate was associated with BTKi treatment and B-cell reconstitution. Boosting was particularly effective when intrinsic immune status was improved by CLL treatment. Limitations included studying a relatively small cohort, with different treatments and vaccination schedules.
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COVID-19 , Leucemia Linfocítica Crónica de Células B , Humanos , Leucemia Linfocítica Crónica de Células B/tratamiento farmacológico , Vacunas contra la COVID-19 , Vacuna BNT162 , Quinasas Janus , Leucocitos Mononucleares , Estudios Prospectivos , COVID-19/prevención & control , SARS-CoV-2 , Factores de Transcripción STAT , Transducción de Señal , Anticuerpos , InmunidadRESUMEN
Molecular-level analyses of breast carcinogenesis benefit from vivo disease models. Estrogen receptor 1 (Esr1) and cytochrome P450 family 19 subfamily A member 1 (CYP19A1) overexpression targeted to mammary epithelial cells in genetically engineered mouse models induces largely similar rates of proliferative mammary disease in prereproductive senescent mice. Herein, with natural reproductive senescence, Esr1 overexpression compared with CYP19A1 overexpression resulted in significantly higher rates of preneoplasia and cancer. Before reproductive senescence, Esr1, but not CYP19A1, overexpressing mice are tamoxifen resistant. However, during reproductive senescence, Esr1 mice exhibited responsiveness. Both Esr1 and CYP19A1 are responsive to letrozole before and after reproductive senescence. Gene Set Enrichment Analyses of RNA-sequencing data sets showed that higher disease rates in Esr1 mice were accompanied by significantly higher expression of cell proliferation genes, including members of prognostic platforms for women with early-stage hormone receptor-positive disease. Tamoxifen and letrozole exposure induced down-regulation of these genes and resolved differences between the two models. Both Esr1 and CYP19A1 overexpression induced abnormal developmental patterns of pregnancy-like gene expression. This resolved with progression through reproductive senescence in CYP19A1 mice, but was more persistent in Esr1 mice, resolving only with tamoxifen and letrozole exposure. In summary, genetically engineered mouse models of Esr1 and CYP19A1 overexpression revealed a diversion of disease processes resulting from the two distinct molecular pathophysiological mammary gland-targeted intrusions into estrogen signaling during reproductive senescence.
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Aromatasa , Células Epiteliales , Receptor alfa de Estrógeno , Glándulas Mamarias Animales , Animales , Femenino , Ratones , Embarazo , Células Epiteliales/metabolismo , Receptor alfa de Estrógeno/genética , Receptor alfa de Estrógeno/metabolismo , Estrógenos , Letrozol , Tamoxifeno/farmacología , Expresión Génica , Glándulas Mamarias Animales/metabolismo , Aromatasa/genética , Aromatasa/metabolismoRESUMEN
Age is a risk factor for human estrogen receptor-positive breast cancer, with highest prevalence following menopause. While transcriptome risk profiling is available for human breast cancers, it is not yet developed for prognostication for primary or secondary breast cancer development utilizing at-risk breast tissue. Both estrogen receptor α (ER) and aromatase overexpression have been linked to human breast cancer. Herein, conditional genetically engineered mouse models of estrogen receptor 1 (Esr1) and cytochrome P450 family 19 subfamily A member 1 (CYP19A1) were used to show that induction of Esr1 overexpression just before or with reproductive senescence and maintained through age 30 months resulted in significantly higher prevalence of estrogen receptor-positive adenocarcinomas than CYP19A1 overexpression. All adenocarcinomas tested showed high percentages of ER+ cells. Mammary cancer development was preceded by a persistent proliferative transcriptome risk signature initiated within 1 week of transgene induction that showed parallels to the Prosigna/Prediction Analysis of Microarray 50 human prognostic signature for early-stage human ER+ breast cancer. CYP19A1 mice also developed ER+ mammary cancers, but histology was more divided between adenocarcinoma and adenosquamous, with one ER- adenocarcinoma. Results demonstrate that, like humans, generation of ER+ adenocarcinoma in mice was facilitated by aging mice past the age of reproductive senescence. Esr1 overexpression was associated with a proliferative estrogen pathway-linked signature that preceded appearance of ER+ mammary adenocarcinomas.
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Adenocarcinoma , Neoplasias de la Mama , Glándulas Mamarias Animales , Animales , Femenino , Ratones , Adenocarcinoma/genética , Adenocarcinoma/metabolismo , Adenocarcinoma/patología , Envejecimiento/genética , Envejecimiento/metabolismo , Neoplasias de la Mama/genética , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , Receptor alfa de Estrógeno/genética , Receptor alfa de Estrógeno/metabolismo , Glándulas Mamarias Animales/metabolismo , Glándulas Mamarias Animales/patología , Expresión Génica , Aromatasa/genética , Aromatasa/metabolismo , Reproducción/genética , Reproducción/fisiologíaRESUMEN
Omicron is currently the dominant SARS-CoV-2 variant and several sublineages have emerged. Questions remain about the impact of previous SARS-CoV-2 exposure on cross-variant immune responses elicited by the SARS-CoV-2 Omicron sublineage BA.2 compared to BA.1. Here we show that without previous history of COVID-19, BA.2 infection induces a reduced immune response against all variants of concern (VOC) compared to BA.1 infection. The absence of ACE2 binding in sera of previously naïve BA.1 and BA.2 patients indicates a lack of meaningful neutralization. In contrast, anti-spike antibody levels and neutralizing activity greatly increased in the BA.1 and BA.2 patients with a previous history of COVID-19. Transcriptome analyses of peripheral immune cells showed significant differences in immune response and specific antibody generation between BA.1 and BA.2 patients as well as significant differences in the expression of specific immune genes. In summary, prior infection status significantly impacts the innate and adaptive immune response against VOC following BA.2 infection.
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Patients with chronic lymphocytic leukemia (CLL) treated with B-cell pathway inhibitors and anti-CD20 antibodies exhibit low humoral response rate (RR) following SARS-CoV-2 vaccination. To investigate the relationship between the initial transcriptional response to vaccination with ensuing B and T cell immune responses, we performed a comprehensive immune transcriptome analysis flanked by antibody and T cell assays in peripheral blood prospectively collected from 15 CLL/SLL patients vaccinated with heterologous BNT162b2/ChAdOx1 with follow up at a single institution. The two-dose antibody RR was 40% increasing to 53% after booster. Patients on BTKi, venetoclax ± anti-CD20 antibody within 12 months of vaccination responded less well than those under BTKi alone. The two-dose T cell RR was 80% increasing to 93% after booster. Transcriptome studies revealed that seven patients showed interferon-mediated signaling activation within 2 days and one at 7 days after vaccination. Increasing counts of COVID-19 specific IGHV genes correlated with B-cell reconstitution and improved humoral RR. T cell responses in CLL patients appeared after vaccination regardless of treatment status. A higher humoral RR was associated with BTKi treatment and B-cell reconstitution. Boosting was particularly effective when intrinsic immune status was improved by CLL-treatment.
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Mammographic density is associated with increased breast cancer risk. Conventional visual assessment of murine mouse models does not include quantified total density analysis. A bifurcated method was sufficient to obtain relative density scores on a broad range of two-dimensional whole mount images that contained both normal and abnormal findings. Image processing techniques, including a ridge operator and a gaussian denoising method, were used to isolate background away from mammary epithelium and use mean pixel intensity to represent mammary density on genetically engineered mouse models for breast cancer in mice 4 to 29 months of age. The bifurcated method allowed for application of an optimal image processing approach for the structural elements present in the whole mount images. Gaussian denoising was the optimal approach when more dense lobular growth and tertiary branching dominate and a ridge operator when epithelial growth was more sparse and secondary branching was the more dominant structural feature. The two processing approaches were combined in a single experimental flow program using an initial image density measurement as the decision point between the two approaches. Higher density was associated with lobular growth, tertiary branching, fibrotic stroma, and presence of cancer. The significance of the study is development of a readily accessible program for digital assessment of mammary gland whole mount density across a range of mammary gland morphologies.
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Procesamiento de Imagen Asistido por Computador , Glándulas Mamarias Animales , Animales , Modelos Animales de Enfermedad , Epitelio , Procesamiento de Imagen Asistido por Computador/métodos , Glándulas Mamarias Animales/diagnóstico por imagen , RatonesRESUMEN
Antibody response following Omicron infection is reported to be less robust than that to other variants. Here we investigated how prior vaccination and/or prior infection modulates that response. Disease severity, antibody responses and immune transcriptomes were characterized in four groups of Omicron-infected outpatients (n=83): unvaccinated/no prior infection, vaccinated/no prior infection, unvaccinated/prior infection and vaccinated/prior infection. The percentage of patients with asymptomatic or mild disease was highest in the vaccinated/no prior infection group (87%) and lowest in the unvaccinated/no prior infection group (47%). Significant anti-Omicron spike antibody levels and neutralizing activity were detected in the vaccinated group immediately after infection but were not present in the unvaccinated/no prior infection group. Within two weeks, antibody levels against Omicron, increased. Omicron neutralizing activity in the vaccinated group exceeded that of the prior infection group. No increase in neutralizing activity in the unvaccinated/no prior infection group was seen. The unvaccinated/prior infection group showed an intermediate response. We then investigated the early transcriptomic response following Omicron infection in these outpatient populations and compared it to that found in unvaccinated hospitalized patients with Alpha infection. Omicron infected patients showed a gradient of transcriptional response dependent upon whether or not they were previously vaccinated or infected. Vaccinated patients showed a significantly blunted interferon response as compared to both unvaccinated Omicron infected outpatients and unvaccinated Alpha infected hospitalized patients typified by the response of specific gene classes such as OAS and IFIT that control anti-viral responses and IFI27, a predictor of disease outcome.
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Inmunidad Humoral , Pacientes Ambulatorios , Anticuerpos Antivirales , Humanos , VacunaciónRESUMEN
Heterologous ChAdOx1-BNT162b2 vaccination induces a stronger immune response than BNT162b2-BNT162b2. Here, we investigated the molecular transcriptome, germline allelic variants of immunoglobulin loci, and anti-Omicron antibody levels in 46 office and lab workers from the Republic of Korea following ChAdOx1-BNT162b2 vaccination. Anti-spike-specific IgG antibody levels against the ancestral SARS-CoV-2 strain increased from 70 AU/ml to 14,000 AU/ml to 142,000 AU/ml one, three and seven days following the second vaccination. Titers against VOC, including Omicron, were two-fold to three-fold lower, yet higher than those measured following BNT162b2-BNT162b2 vaccination. RNA-seq of peripheral immune cells demonstrated activation of interferon pathways with increased IGHV clonal transcripts encoding neutralizing antibodies. scRNA-seq revealed enriched B cell and CD4+ T cell responses in both ChAdOx1-BNT162b2 and BNT162b2-BNT162b2 recipients, but a stronger clonal expansion of memory B cells with ChAdOx1-BNT162b2. In summary, heterologous ChAdOx1-BNT162b2 provides an innate and adaptive immune response that exceeds homologous BNT162b2 vaccination.
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Omicron is currently the dominant SARS-CoV-2 variant and several sublineages have emerged. Questions remain about the impact of previous SARS-CoV-2 exposure on cross-variant immune responses elicited by BA.2 infection compared to BA.1. Here we show that without previous history of COVID-19, BA.2 infection induces a reduced immune response against all variants of concern (VOC) compared to BA.1 infection. The absence of ACE2 binding in sera of previously naïve BA.1 and BA.2 patients indicates a lack of meaningful neutralization. In contrast, anti-spike antibody levels and neutralizing activity greatly increased in the BA.1 and BA.2 patients with a previous history of COVID-19. Transcriptome analyses of peripheral immune cells showed significant differences in immune response and specific antibody generation between BA.1 and BA.2 patients as well as significant differences in expression of specific immune genes. In summary, prior infection status significantly impacts the innate and adaptive immune response against VOC following BA.2 infection.
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Background: SARS-CoV-2 infection activates interferon-controlled signaling pathways and elicits a wide spectrum of immune responses and clinical manifestations in human patients. Methods: Here, we investigate the impact of prior vaccination on the innate immune response of hospitalized COVID-19 patients infected with the SARS-CoV-2 Beta variant through RNA sequencing of peripheral blood immune cells. Four patients had received the first dose of BNT162b2 about 11 days prior to the onset of COVID-19 symptoms and five patients were unvaccinated. Patients had received dexamethasone treatment. Immune transcriptomes were obtained at days 7-13, 20-32 and 42-60 after first symptomology. Results: RNA-seq reveals an enhanced JAK-STAT-mediated immune transcriptome response at day 10 in vaccinated patients as compared to unvaccinated ones. This increase subsides by day 35. Expression of the gene encoding the antiviral protein oligoadenylate synthetase (OAS) 1, which is inversely correlated with disease severity, and other key antiviral proteins increases in the vaccinated group. We also investigate the immune transcriptome in naïve individuals receiving their first dose of BNT162b2 and identify a gene signature shared with the vaccinated COVID-19 patients. Conclusions: Our study demonstrates that RNA-seq can be used to monitor molecular immune responses elicited by the BNT162b2 vaccine, both in naïve individuals and in COVID-19 patients, and it provides a biomarker-based approach to systems vaccinology.
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Knowledge about the impact of prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of the elderly on mRNA vaccination response is needed to appropriately address the demand for additional vaccinations in this vulnerable population. Here, we show that octogenarians, a high-risk population, mount a sustained SARS-CoV-2 spike-specific immunoglobulin G (IgG) antibody response for 15 months following infection. This response boosts antibody levels 35-fold upon receiving a single dose of BNT162b2 mRNA vaccine 15 months after recovery from coronavirus disease 2019 (COVID-19). In contrast, antibody responses in naive individuals boost only 6-fold after a second vaccine. Spike-specific angiotensin-converting enzyme 2 (ACE2) antibody binding responses in the previously infected octogenarians following two vaccine doses exceed those found in a naive cohort after two doses. RNA sequencing (RNA-seq) demonstrates activation of interferon-induced genetic programs, which persist only in the previously infected. A preferential increase of specific immunoglobulin G heavy chain variable (IGHV) clonal transcripts that are the basis of neutralizing antibodies is observed only in the previously infected nuns.