Molecular states during acute COVID-19 reveal distinct etiologies of long-term sequelae

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

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

Identification of key gene expression associated with quality of life after recovery from COVID-19

Post-acute sequelae of COVID-19 (PASC) is a persistent complication of severe acute respiratory syndrome coronavirus 2 infection that includes symptoms, such as fatigue, cognitive impairment, and respiratory distress. These symptoms severely affect the quality of life of patients after their recovery from COVID-19. In this study, a group of machine learning algorithms analyzed the whole blood RNA-seq data from patients with different PASC levels. The purpose of this analysis was to identify the gene markers associated with PASC and the special expression patterns for different PASC levels. By comparing the quality of life of patients after the acute phase of COVID-19 and before the disease, samples in the dataset were divided into three groups, namely, "Better," "The Same," and "Worse." Each patient was represented by the expression levels of 58,929 genes. The machine learning-based workflow included six feature-ranking algorithms, incremental feature selection (IFS), and four classification algorithms. The feature ranking algorithms were in charge of assessing feature importance, whereas IFS with classification algorithms were used to extract essential genes and to construct efficient classifiers and classification rules. The expression of top genes in the results was associated with the immune response to viral infection, which is supported by the published literature. For example, patients with low CCDC18 expression and high CPED1 expression had good quality of life, whereas those with low CDC16 expression had poor quality of life.

PANoptosis, an indicator of COVID-19 severity and outcomes

Coronavirus disease 2019 (COVID-19) has been wreaking havoc for 3 years. PANoptosis, a distinct and physiologically relevant inflammatory programmed cell death, perpetuates cytokine storm and multi-organ injuries in COVID-19. Although PANoptosis performs indispensable roles in host defense, further investigation is needed to elucidate the exact processes through which PANoptosis modulates immunological responses and prognosis in COVID-19. This study conducted a bioinformatics analysis of online single-cell RNA sequence (scRNA-seq) and bulk RNA-seq datasets to explore the potential of PANoptosis as an indicator of COVID-19 severity. The degree of PANoptosis in bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells (PBMC) indicated the severity of COVID-19. Single-cell transcriptomics identified pro-inflammatory monocytes as one of the primary sites of PANoptosis in COVID-19. The study subsequently demonstrated the immune and metabolic characteristics of this group of pro-inflammatory monocytes. In addition, the analysis illustrated that dexamethasone was likely to alleviate inflammation in COVID-19 by mitigating PANoptosis. Finally, the study showed that the PANoptosis-related genes could predict the intensive care unit admission (ICU) and outcomes of COVID-19 patients who are hospitalized.

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.

Analysis of transcriptomics data from COVID-19 patients: a pilot research

During SARS-CoV-2 infection, the virus transforms the infected host cell into factories that produce new viral particles. As infection progresses, the infected cells undergo numerous changes in various pathways. One of these changes is the occurrence of a cytokine storm, which leads to severe symptoms. In this study, we examined the transcriptomic changes caused by COVID-19 by analyzing RNA-seq data obtained from COVID-19-positive patients as well as COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. We analyzed the first datasets, consisting of 96 samples to validate our methods. The objective of this publication is to report the pilot results. To explore potential biomarkers related to disease severity, we conducted a differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Given the large number of potential biomarkers we identified, we further performed pathway enrichment analysis with terms from Kyoto Encyclopedia of Genes and Genomics (KEGG) to obtain a more profound understanding of altered pathways. Our results indicate that pathways related to immune processes, response to infection, and multiple signaling pathways were affected. These findings align with several previous studies that also reported the influence of SARS-CoV-2 infection on these pathways.

Persistent CD8+ T cell proliferation and activation in COVID-19 adult survivors with post-acute sequelae: a longitudinal, observational cohort study of persistent symptoms and T cell markers

Introduction

Post-acute sequelae of COVID-19 affects the quality of life of many COVID-19 survivors, yet the etiology of post-acute sequelae of COVID-19 remains unknown. We aimed to determine if persistent inflammation and ongoing T-cell activation during convalescence were a contributing factor to the pathogenesis of post-acute sequelae of COVID-19.

Methods

We evaluated 67 individuals diagnosed with COVID-19 by nasopharyngeal polymerase chain reaction for persistent symptoms during convalescence at separate time points occurring up to 180 days post-diagnosis. Fifty-two of these individuals were evaluated longitudinally. We obtained whole blood samples at each study visit, isolated peripheral blood mononuclear cells, and stained for multiple T cell activation markers for flow cytometry analysis. The activation states of participants' CD4+ and CD8+ T-cells were next analyzed for each of the persistent symptoms.

Results

Overall, we found that participants with persistent symptoms had significantly higher levels of inflammation at multiple time points during convalescence when compared to those who fully recovered from COVID-19. Participants with persistent dyspnea, forgetfulness, confusion, and chest pain had significantly higher levels of proliferating effector T-cells (CD8+Ki67+), and those with chest pain, joint pain, difficulty concentrating, and forgetfulness had higher levels of regulatory T-cells (CD4+CD25+). Additionally, those with dyspnea had significantly higher levels of CD8+CD38+, CD8+ Granzyme B+, and CD8+IL10+ cells. A retrospective comparison of acute phase inflammatory markers in adults with and without post-acute sequelae of COVID-19 showed that CD8+Ki67+ cells were significantly higher at the time of acute illness (up to 14 days post-diagnosis) in those who developed persistent dyspnea.

Discussion

These findings suggest continued CD8+ T-cell activation following SARS-CoV-2 infection in adults experiencing post-acute sequelae of COVID-19 and that the increase in T regulatory cells for a subset of these patients represents the ongoing attempt by the host to reduce inflammation.

Early immune factors associated with the development of post-acute sequelae of SARS-CoV-2 infection in hospitalized and non-hospitalized individuals

Background

Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to post-acute sequelae of SARS-CoV-2 (PASC) that can persist for weeks to years following initial viral infection. Clinical manifestations of PASC are heterogeneous and often involve multiple organs. While many hypotheses have been made on the mechanisms of PASC and its associated symptoms, the acute biological drivers of PASC are still unknown.

Methods

We enrolled 494 patients with COVID-19 at their initial presentation to a hospital or clinic and followed them longitudinally to determine their development of PASC. From 341 patients, we conducted multi-omic profiling on peripheral blood samples collected shortly after study enrollment to investigate early immune signatures associated with the development of PASC.

Results

During the first week of COVID-19, we observed a large number of differences in the immune profile of individuals who were hospitalized for COVID-19 compared to those individuals with COVID-19 who were not hospitalized. Differences between individuals who did or did not later develop PASC were, in comparison, more limited, but included significant differences in autoantibodies and in epigenetic and transcriptional signatures in double-negative 1 B cells, in particular.

Conclusions

We found that early immune indicators of incident PASC were nuanced, with significant molecular signals manifesting predominantly in double-negative B cells, compared with the robust differences associated with hospitalization during acute COVID-19. The emerging acute differences in B cell phenotypes, especially in double-negative 1 B cells, in PASC patients highlight a potentially important role of these cells in the development of PASC.

Persistent complement dysregulation with signs of thromboinflammation in active Long Covid

Long Covid is a debilitating condition of unknown etiology. We performed multimodal proteomics analyses of blood serum from COVID-19 patients followed up to 12 months after confirmed severe acute respiratory syndrome coronavirus 2 infection. Analysis of >6500 proteins in 268 longitudinal samples revealed dysregulated activation of the complement system, an innate immune protection and homeostasis mechanism, in individuals experiencing Long Covid. Thus, active Long Covid was characterized by terminal complement system dysregulation and ongoing activation of the alternative and classical complement pathways, the latter associated with increased antibody titers against several herpesviruses possibly stimulating this pathway. Moreover, markers of hemolysis, tissue injury, platelet activation, and monocyte-platelet aggregates were increased in Long Covid. Machine learning confirmed complement and thromboinflammatory proteins as top biomarkers, warranting diagnostic and therapeutic interrogation of these systems.

Features of acute COVID-19 associated with post-acute sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study

Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based on reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated with female sex and distinctive comorbidities. During the acute phase of disease, a higher respiratory SARS-CoV-2 viral burden and lower Receptor Binding Domain and Spike antibody titers were associated with both the physical predominant and the multidomain deficit clusters. A lower frequency of circulating B lymphocytes by mass cytometry (CyTOF) was observed in the multidomain deficit cluster. Circulating fibroblast growth factor 21 (FGF21) was significantly elevated in the mental/cognitive predominant and the multidomain clusters. Future efforts to link PASC to acute anti-viral host responses may help to better target treatment and prevention of PASC.

Intrinsic factors behind long COVID: III. Persistence of SARS-CoV-2 and its components

Considerable research has been done in investigating SARS-CoV-2 infection, its characteristics, and host immune response. However, debate is still ongoing over the emergence of post-acute sequelae of SARS-CoV-2 infection (PASC). A multitude of long-lasting symptoms have been reported several weeks after the primary acute SARS-CoV-2 infection that resemble several other viral infections. Thousands of research articles have described various post-COVID-19 conditions. Yet, the evidence around these ongoing health problems, the reasons behind them, and their molecular underpinnings are scarce. These persistent symptoms are also known as long COVID-19. The persistence of SARS-CoV-2 and/or its components in host tissues can lead to long COVID. For example, the presence of viral nucleocapsid protein and RNA was detected in the skin, appendix, and breast tissues of some long COVID patients. The persistence of viral RNA was reported in multiple anatomic sites, including non-respiratory tissues such as the adrenal gland, ocular tissue, small intestine, lymph nodes, myocardium, and sciatic nerve. Distinctive viral spike sequence variants were also found in non-respiratory tissues. Interestingly, prolonged detection of viral subgenomic RNA was observed across all tissues, sometimes in multiple tissues of the same patient, which likely reflects recent but defective viral replication. Moreover, the persistence of SARS-CoV-2 RNA was noticed throughout the brain at autopsy, as late as 230 days following symptom onset among unvaccinated patients who died of severe infection. Here, we review the persistence of SARS-CoV-2 and its components as an intrinsic factor behind long COVID. We also highlight the immunological consequences of this viral persistence.

Mast cell activation may contribute to adverse health transitions in COVID-19 patients with frailty

A prominent aspect of the post-coronavirus disease-2019 (post-COVID-19) era is long-COVID. Therefore, precise patient classification and exploration of the corresponding factors affecting long-COVID are crucial for tailored treatment strategies. Frailty is a common age-related clinical syndrome characterized by deteriorated physiological functions of multiple organ systems, which increases susceptibility to stressors. Herein, we performed an inclusion and exclusion analysis (definite COVID-19 infection diagnosis, clear underlying disease information, ≥60 years old, and repeated sampling of clinical cases) of 10,613 blood samples and identified frailty cases for further investigation. RNA-Seq data were used for differential gene expression and functional and pathway analyses. The results revealed that patients with frailty were more prone to poor health conversions and more sequelae, and the blood transcriptome had obvious disturbances in pathways associated with immune regulation, metabolism, and stress response. These adverse health transitions were significantly associated with mast cell activation. Additionally, NCAPG, MCM10, and CDC25C were identified as hub genes in the peripheral blood differential gene cluster, which could be used as diagnostic markers of poor health conversion. Our results indicate that healthcare measures should be prioritized to mitigate adverse health outcomes in this vulnerable patient group, COVID-19 patients with frailty, in post-COVID era.

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.

Genetic risk factors for severe and fatigue dominant long COVID and commonalities with ME/CFS identified by combinatorial analysis

BACKGROUND

Long COVID is a debilitating chronic condition that has affected over 100 million people globally. It is characterized by a diverse array of symptoms, including fatigue, cognitive dysfunction and respiratory problems. Studies have so far largely failed to identify genetic associations, the mechanisms behind the disease, or any common pathophysiology with other conditions such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) that present with similar symptoms.

METHODS

We used a combinatorial analysis approach to identify combinations of genetic variants significantly associated with the development of long COVID and to examine the biological mechanisms underpinning its various symptoms. We compared two subpopulations of long COVID patients from Sano Genetics' Long COVID GOLD study cohort, focusing on patients with severe or fatigue dominant phenotypes. We evaluated the genetic signatures previously identified in an ME/CFS population against this long COVID population to understand similarities with other fatigue disorders that may be triggered by a prior viral infection. Finally, we also compared the output of this long COVID analysis against known genetic associations in other chronic diseases, including a range of metabolic and neurological disorders, to understand the overlap of pathophysiological mechanisms.

RESULTS

Combinatorial analysis identified 73 genes that were highly associated with at least one of the long COVID populations included in this analysis. Of these, 9 genes have prior associations with acute COVID-19, and 14 were differentially expressed in a transcriptomic analysis of long COVID patients. A pathway enrichment analysis revealed that the biological pathways most significantly associated with the 73 long COVID genes were mainly aligned with neurological and cardiometabolic diseases. Expanded genotype analysis suggests that specific SNX9 genotypes are a significant contributor to the risk of or protection against severe long COVID infection, but that the gene-disease relationship is context dependent and mediated by interactions with KLF15 and RYR3. Comparison of the genes uniquely associated with the Severe and Fatigue Dominant long COVID patients revealed significant differences between the pathways enriched in each subgroup. The genes unique to Severe long COVID patients were associated with immune pathways such as myeloid differentiation and macrophage foam cells. Genes unique to the Fatigue Dominant subgroup were enriched in metabolic pathways such as MAPK/JNK signaling. We also identified overlap in the genes associated with Fatigue Dominant long COVID and ME/CFS, including several involved in circadian rhythm regulation and insulin regulation. Overall, 39 SNPs associated in this study with long COVID can be linked to 9 genes identified in a recent combinatorial analysis of ME/CFS patient from UK Biobank. Among the 73 genes associated with long COVID, 42 are potentially tractable for novel drug discovery approaches, with 13 of these already targeted by drugs in clinical development pipelines. From this analysis for example, we identified TLR4 antagonists as repurposing candidates with potential to protect against long term cognitive impairment pathology caused by SARS-CoV-2. We are currently evaluating the repurposing potential of these drug targets for use in treating long COVID and/or ME/CFS.

CONCLUSION

This study demonstrates the power of combinatorial analytics for stratifying heterogeneous populations in complex diseases that do not have simple monogenic etiologies. These results build upon the genetic findings from combinatorial analyses of severe acute COVID-19 patients and an ME/CFS population and we expect that access to additional independent, larger patient datasets will further improve the disease insights and validate potential treatment options in long COVID.

The long-term health outcomes, pathophysiological mechanisms and multidisciplinary management of long COVID

There have been hundreds of millions of cases of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With the growing population of recovered patients, it is crucial to understand the long-term consequences of the disease and management strategies. Although COVID-19 was initially considered an acute respiratory illness, recent evidence suggests that manifestations including but not limited to those of the cardiovascular, respiratory, neuropsychiatric, gastrointestinal, reproductive, and musculoskeletal systems may persist long after the acute phase. These persistent manifestations, also referred to as long COVID, could impact all patients with COVID-19 across the full spectrum of illness severity. Herein, we comprehensively review the current literature on long COVID, highlighting its epidemiological understanding, the impact of vaccinations, organ-specific sequelae, pathophysiological mechanisms, and multidisciplinary management strategies. In addition, the impact of psychological and psychosomatic factors is also underscored. Despite these crucial findings on long COVID, the current diagnostic and therapeutic strategies based on previous experience and pilot studies remain inadequate, and well-designed clinical trials should be prioritized to validate existing hypotheses. Thus, we propose the primary challenges concerning biological knowledge gaps and efficient remedies as well as discuss the corresponding recommendations.

Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV2 Infection

Background

Acute kidney injury (AKI) is common in hospitalized patients with SARS-CoV2 infection despite vaccination and leads to long-term kidney dysfunction. However, peripheral blood molecular signatures in AKI from COVID-19 and their association with long-term kidney dysfunction are yet unexplored.

Methods

In patients hospitalized with SARS-CoV2, we performed bulk RNA sequencing using peripheral blood mononuclear cells(PBMCs). We applied linear models accounting for technical and biological variability on RNA-Seq data accounting for false discovery rate (FDR) and compared functional enrichment and pathway results to a historical sepsis-AKI cohort. Finally, we evaluated the association of these signatures with long-term trends in kidney function.

Results

Of 283 patients, 106 had AKI. After adjustment for sex, age, mechanical ventilation, and chronic kidney disease (CKD), we identified 2635 significant differential gene expressions at FDR<0.05. Top canonical pathways were EIF2 signaling, oxidative phosphorylation, mTOR signaling, and Th17 signaling, indicating mitochondrial dysfunction and endoplasmic reticulum (ER) stress. Comparison with sepsis associated AKI showed considerable overlap of key pathways (48.14%). Using follow-up estimated glomerular filtration rate (eGFR) measurements from 115 patients, we identified 164/2635 (6.2%) of the significantly differentiated genes associated with overall decrease in long-term kidney function. The strongest associations were 'autophagy', 'renal impairment via fibrosis', and 'cardiac structure and function'.

Conclusions

We show that AKI in SARS-CoV2 is a multifactorial process with mitochondrial dysfunction driven by ER stress whereas long-term kidney function decline is associated with cardiac structure and function and immune dysregulation. Functional overlap with sepsis-AKI also highlights common signatures, indicating generalizability in therapeutic approaches.

SIGNIFICANCE STATEMENT

Peripheral transcriptomic findings in acute and long-term kidney dysfunction after hospitalization for SARS-CoV2 infection are unclear. We evaluated peripheral blood molecular signatures in AKI from COVID-19 (COVID-AKI) and their association with long-term kidney dysfunction using the largest hospitalized cohort with transcriptomic data. Analysis of 283 hospitalized patients of whom 37% had AKI, highlighted the contribution of mitochondrial dysfunction driven by endoplasmic reticulum stress in the acute stages. Subsequently, long-term kidney function decline exhibits significant associations with markers of cardiac structure and function and immune mediated dysregulation. There were similar biomolecular signatures in other inflammatory states, such as sepsis. This enhances the potential for repurposing and generalizability in therapeutic approaches.

Serotonin reduction in post-acute sequelae of viral infection

Post-acute sequelae of COVID-19 (PASC, "Long COVID") pose a significant global health challenge. The pathophysiology is unknown, and no effective treatments have been found to date. Several hypotheses have been formulated to explain the etiology of PASC, including viral persistence, chronic inflammation, hypercoagulability, and autonomic dysfunction. Here, we propose a mechanism that links all four hypotheses in a single pathway and provides actionable insights for therapeutic interventions. We find that PASC are associated with serotonin reduction. Viral infection and type I interferon-driven inflammation reduce serotonin through three mechanisms: diminished intestinal absorption of the serotonin precursor tryptophan; platelet hyperactivation and thrombocytopenia, which impacts serotonin storage; and enhanced MAO-mediated serotonin turnover. Peripheral serotonin reduction, in turn, impedes the activity of the vagus nerve and thereby impairs hippocampal responses and memory. These findings provide a possible explanation for neurocognitive symptoms associated with viral persistence in Long COVID, which may extend to other post-viral syndromes.

Acute blood biomarker profiles predict cognitive deficits 6 and 12 months after COVID-19 hospitalization

Post-COVID cognitive deficits, including 'brain fog', are clinically complex, with both objective and subjective components. They are common and debilitating, and can affect the ability to work, yet their biological underpinnings remain unknown. In this prospective cohort study of 1,837 adults hospitalized with COVID-19, we identified two distinct biomarker profiles measured during the acute admission, which predict cognitive outcomes 6 and 12 months after COVID-19. A first profile links elevated fibrinogen relative to C-reactive protein with both objective and subjective cognitive deficits. A second profile links elevated D-dimer relative to C-reactive protein with subjective cognitive deficits and occupational impact. This second profile was mediated by fatigue and shortness of breath. Neither profile was significantly mediated by depression or anxiety. Results were robust across secondary analyses. They were replicated, and their specificity to COVID-19 tested, in a large-scale electronic health records dataset. These findings provide insights into the heterogeneous biology of post-COVID cognitive deficits.

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation

Introduction

Persistent symptoms after COVID-19 infection ("long COVID") negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID.

Methods

RNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development.

Results

Compared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The "Resolved" endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of "Suppressive" and "Unresolved" endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification.

Discussion

This study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes ("Unresolved" and "Suppressive") were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.

A study of gene expression in the living human brain

A goal of medical research is to determine the molecular basis of human brain health and illness. One way to achieve this goal is through observational studies of gene expression in human brain tissue. Due to the unavailability of brain tissue from living people, most such studies are performed using tissue from postmortem brain donors. An assumption underlying this practice is that gene expression in the postmortem human brain is an accurate representation of gene expression in the living human brain. Here, this assumption - which, until now, had not been adequately tested - is tested by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Expression levels differed significantly for nearly 80% of genes, and a systematic examination of alternative explanations for this observation determined that these differences are not a consequence of cell type composition, RNA quality, postmortem interval, age, medication, morbidity, symptom severity, tissue pathology, sample handling, batch effects, or computational methods utilized. Analyses integrating the data generated for this study with data from earlier landmark studies that used tissue from postmortem brain donors showed that postmortem brain gene expression signatures of neurological and mental illnesses, as well as of normal traits such as aging, may not be accurate representations of these gene expression signatures in the living brain. By using tissue from large cohorts living people, future observational studies of human brain biology have the potential to (1) determine the medical research questions that can be addressed using postmortem tissue as a proxy for living tissue and (2) expand the scope of medical research to include questions about the molecular basis of human brain health and illness that can only be addressed in living people (e.g., "What happens at the molecular level in the brain as a person experiences an emotion?").

The role of the oral cavity in SARS-CoV-2- and other viral infections

OBJECTIVE

This study aims to review the role of the oral cavity in SARS-CoV-2- and other viral upper respiratory tract infections.

MATERIAL AND METHODS

Data reviewed in the text have been researched online and also reflect personal expertise.

RESULTS

Numerous respiratory and other viruses replicate in the oral cavity and are transmitted via aerosols (< 5 µm) and droplets (> 5 µm). SARS-CoV-2 replication has been documented in the upper airways as well as in oral mucosa and salivary glands. These sites are also virus reservoirs that can infect other organs, e.g., the lungs and gastrointestinal tract, as well as other individuals. Laboratory diagnosis of viruses in the oral cavity and upper airways focuses on real-time PCR; antigen tests are less sensitive. For screening and monitoring infections, nasopharyngeal and oral swabs are tested; saliva is a good and more comfortable alternative. Physical means like social distancing or masks have been proven successful to reduce the risk of infection. Both wet-lab and clinical studies confirm that mouth rinses are effective against SARS-CoV-2 and other viruses. Antiviral mouth rinses can inactivate all viruses that replicate in the oral cavity.

CONCLUSIONS

The oral cavity plays an important role in viral infections of the upper respiratory tract: it serves as a portal of entry, a site of replication, and a source of infection by droplets and aerosols. Physical means but also antiviral mouth rinses can help reduce the spread of viruses and contribute to infection control.

Early Transcriptional Responses of Human Nasal Epithelial Cells to Infection with Influenza A and SARS-CoV-2 Virus Differ and Are Influenced by Physiological Temperature

Influenza A (IAV) and SARS-CoV-2 (SCV2) viruses represent an ongoing threat to public health. Both viruses target the respiratory tract, which consists of a gradient of cell types, receptor expression, and temperature. Environmental temperature has been an understudied contributor to infection susceptibility and understanding its impact on host responses to infection could help uncover new insight into severe disease risk factors. As the nasal passageways are the initial site of respiratory virus infection, in this study we investigated the effect of temperature on host responses in human nasal epithelial cells (hNECs) utilizing IAV and SCV2 in vitro infection models. We demonstrate that temperature affected SCV2, but not IAV, viral replicative fitness and that SCV2-infected cultures were slower to mount an infection-induced response, likely due to suppression by the virus. Additionally, we show that that temperature not only changed the basal transcriptomic landscape of epithelial cells, but that it also impacted the response to infection. The induction of interferon and other innate immune responses was not drastically affected by temperature, suggesting that while the baseline antiviral response at different temperatures remained consistent, there may be metabolic or signaling changes that affect how well the cultures were able to adapt to new pressures, such as infection. Finally, we show that hNECs responded differently to IAV and SCV2 infection in ways that give insight into how the virus is able to manipulate the cell to allow for replication and release. Taken together, these data give new insight into the innate immune response to respiratory infections and can assist in identifying new treatment strategies for respiratory infections.

Early transcriptional responses of human nasal epithelial cells to infection with Influenza A and SARS-CoV-2 virus differ and are influenced by physiological temperature

Influenza A (IAV) and SARS-CoV-2 (SCV2) viruses represent an ongoing threat to public health. Both viruses target the respiratory tract, which consists of a gradient of cell types, receptor expression, and temperature. Environmental temperature has been an un-derstudied contributor to infection susceptibility and understanding its impact on host responses to infection could help uncover new insights into severe disease risk factors. As the nasal passageways are the initial site of respiratory virus infection, in this study we investigated the effect of temperature on host responses in human nasal epithelial cells (hNECs) utilizing IAV and SCV2 in vitro infection models. We demonstrate that temperature affects SCV2, but not IAV, viral replicative fitness and that SCV2 infected cultures are slower to mount an infection-induced response, likely due to suppression by the virus. Additionally, we show that that temperature not only changes the basal transcriptomic landscape of epithelial cells, but that it also impacts the response to infection. The induction of interferon and other innate immune responses were not drastically affected by temperature, suggesting that while the baseline antiviral response at different temperatures remains consistent, there may be metabolic or signaling changes that affect how well the cultures are able to adapt to new pressures such as infection. Finally, we show that hNECs respond differently to IAV and SCV2 infection in ways that give insight into how the virus is able to manipulate the cell to allow for replication and release. Taken together, these data give new insight into the innate immune response to respiratory infections and can assist in identifying new treatment strategies for respiratory infections.