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Background: Plasma microbial cell-free DNA (mcfDNA) sequencing can establish the etiology of multiple infectious syndromes by identifying microbial DNA in plasma. However, data are needed to define the clinical scenarios where this tool offers the highest clinical benefit. Methods: We conducted a prospective multicenter observational study that evaluated the impact of plasma mcfDNA sequencing compared with usual care testing among adults with hematologic malignancies. This is a secondary analysis of an expanded cohort that evaluated the clinical utility of plasma mcfDNA sequencing across prespecified and adjudicated outcomes. We examined the percentage of participants for whom plasma mcfDNA sequencing identified a probable cause of pneumonia or clinically relevant nonpneumonia infection. We then assessed potential changes in antimicrobial therapy based on plasma mcfDNA sequencing results and the potential for early mcfDNA testing to avoid bronchoscopy and its associated adverse events. Results: Of 223 participants, at least 1 microbial detection by plasma mcfDNA sequencing was adjudicated as a probable cause of pneumonia in 57 (25.6%) and a clinically relevant nonpneumonia infection in 88 (39.5%). A probable cause of pneumonia was exclusively identified by plasma mcfDNA sequencing in 23 (10.3%) participants. Antimicrobial therapy would have changed for 41 (18.4%) participants had plasma mcfDNA results been available in real time. Among the 57 participants with a probable cause of pneumonia identified by plasma mcfDNA sequencing, bronchoscopy identified no additional probable cause of pneumonia in 52 (91.2%). Conclusions: Plasma mcfDNA sequencing could improve management of both pneumonia and other concurrent infections in immunocompromised patients with suspected pneumonia.
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Introduction: Influenza virus infections are a major global health problem. Influenza can result in mild/moderate disease or progress to more severe disease, leading to high morbidity and mortality. Severity is thought to be primarily driven by immunopathology, but predicting which individuals are at a higher risk of being hospitalized warrants investigation into host genetics and the molecular signatures of the host response during influenza infections. Methods: Here, we performed transcriptome and genotype analysis in healthy controls and patients exhibiting mild/moderate or severe influenza (ICU patients). A unique aspect of our study was the genotyping of all participants, which allowed us to assign ethnicities based on genetic variation and assess whether the variation was correlated with expression levels. Results: We identified 169 differentially expressed genes and related molecular pathways between patients in the ICU and those who were not in the ICU. The transcriptome/genotype association analysis identified 871 genes associated to a genetic variant and 39 genes distinct between African-Americans and Caucasians. We also investigated the effects of age and sex and found only a few discernible gene effects in our cohort. Discussion: Together, our results highlight select risk factors that may contribute to an increased risk of ICU admission for influenza-infected patients. This should help to develop better diagnostic tools based on molecular signatures, in addition to a better understanding of the biological processes in the host response to influenza.
Subject(s)
Influenza, Human , Severity of Illness Index , Transcriptome , Humans , Influenza, Human/genetics , Influenza, Human/immunology , Female , Male , Middle Aged , Adult , Gene Expression Profiling , Aged , Genotype , Genetic Predisposition to Disease , Host-Pathogen Interactions/genetics , Host-Pathogen Interactions/immunologyABSTRACT
BACKGROUND: Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection. METHODS: We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae, Mycoplasma pneumoniae, influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust. RESULTS: Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96. DISCUSSION: This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes.
Subject(s)
Disease Models, Animal , Mycoplasma pneumoniae , Pneumonia, Mycoplasma , Streptococcus pneumoniae , Animals , Humans , Mice , Streptococcus pneumoniae/genetics , Streptococcus pneumoniae/isolation & purification , Pneumonia, Mycoplasma/diagnosis , Mycoplasma pneumoniae/genetics , Mycoplasma pneumoniae/isolation & purification , Female , Pneumonia, Pneumococcal/microbiology , Orthomyxoviridae Infections/immunology , ROC Curve , Gene Expression Profiling , Pneumonia, Viral/diagnosis , Pneumonia, Viral/immunology , Mice, Inbred C57BL , Pneumonia, Bacterial/microbiology , Pneumonia, Bacterial/diagnosis , Host-Pathogen InteractionsABSTRACT
Background: Index-cluster studies may help characterize the spread of communicable infections in the presymptomatic state. We describe a prospective index-cluster sampling strategy (ICSS) to detect presymptomatic respiratory viral illness and its implementation in a college population. Methods: We enrolled an annual cohort of first-year undergraduates who completed daily electronic symptom diaries to identify index cases (ICs) with respiratory illness. Investigators then selected 5-10 potentially exposed, asymptomatic close contacts (CCs) who were geographically co-located to follow for infections. Symptoms and nasopharyngeal samples were collected for 5 days. Logistic regression model-based predictions for proportions of self-reported illness were compared graphically for the whole cohort sampling group and the CC group. Results: We enrolled 1379 participants between 2009 and 2015, including 288 ICs and 882 CCs. The median number of CCs per IC was 6 (interquartile range, 3-8). Among the 882 CCs, 111 (13%) developed acute respiratory illnesses. Viral etiology testing in 246 ICs (85%) and 719 CCs (82%) identified a pathogen in 57% of ICs and 15% of CCs. Among those with detectable virus, rhinovirus was the most common (IC: 18%; CC: 6%) followed by coxsackievirus/echovirus (IC: 11%; CC: 4%). Among 106 CCs with a detected virus, only 18% had the same virus as their associated IC. Graphically, CCs did not have a higher frequency of self-reported illness relative to the whole cohort sampling group. Conclusions: Establishing clusters by geographic proximity did not enrich for cases of viral transmission, suggesting that ICSS may be a less effective strategy to detect spread of respiratory infection.
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To elucidate host response elements that define impending decompensation during SARS-CoV-2 infection, we enrolled subjects hospitalized with COVID-19 who were matched for disease severity and comorbidities at the time of admission. We performed combined single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on peripheral blood mononuclear cells (PBMCs) at admission and compared subjects who improved from their moderate disease with those who later clinically decompensated and required invasive mechanical ventilation or died. Chromatin accessibility and transcriptomic immune profiles were markedly altered between the two groups, with strong signals in CD4+ T cells, inflammatory T cells, dendritic cells, and NK cells. Multiomic signature scores at admission were tightly associated with future clinical deterioration (auROC 1.0). Epigenetic and transcriptional changes in PBMCs reveal early, broad immune dysregulation before typical clinical signs of decompensation are apparent and thus may act as biomarkers to predict future severity in COVID-19.
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BACKGROUND: Pneumonia is a common cause of morbidity and mortality, yet a causative pathogen is identified in a minority of cases. Plasma microbial cell-free DNA sequencing may improve diagnostic yield in immunocompromised patients with pneumonia. METHODS: In this prospective, multicenter, observational study of immunocompromised adults undergoing bronchoscopy to establish a pneumonia etiology, plasma microbial cell-free DNA sequencing was compared to standardized usual care testing. Pneumonia etiology was adjudicated by a blinded independent committee. The primary outcome, additive diagnostic value, was assessed in the Per Protocol population (patients with complete testing results and no major protocol deviations) and defined as the percent of patients with an etiology of pneumonia exclusively identified by plasma microbial cell-free DNA sequencing. Clinical additive diagnostic value was assessed in the Per Protocol subgroup with negative usual care testing. RESULTS: Of 257 patients, 173 met Per Protocol criteria. A pneumonia etiology was identified by usual care in 52/173 (30.1%), plasma microbial cell-free DNA sequencing in 49/173 (28.3%) and the combination of both in 73/173 (42.2%) patients. Plasma microbial cell-free DNA sequencing exclusively identified an etiology of pneumonia in 21/173 patients (additive diagnostic value 12.1%, 95% confidence interval [CI], 7.7% to 18.0%, P < .001). In the Per Protocol subgroup with negative usual care testing, plasma microbial cell-free DNA sequencing identified a pneumonia etiology in 21/121 patients (clinical additive diagnostic value 17.4%, 95% CI, 11.1% to 25.3%). CONCLUSIONS: Non-invasive plasma microbial cell-free DNA sequencing significantly increased diagnostic yield in immunocompromised patients with pneumonia undergoing bronchoscopy and extensive microbiologic and molecular testing. CLINICAL TRIALS REGISTRATION: NCT04047719.
Subject(s)
Pneumonia , Adult , Humans , Prospective Studies , Pneumonia/etiology , Sequence Analysis, DNA , Immunocompromised HostABSTRACT
Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.
Subject(s)
Bacterial Infections , Virus Diseases , Humans , Virus Diseases/diagnosis , Virus Diseases/genetics , Biomarkers , Bacterial Infections/diagnosis , Bacterial Infections/genetics , Cambodia , AustraliaABSTRACT
Age is among the strongest risk factors for severe outcomes from SARS-CoV-2 infection. We sought to evaluate associations between age and both mucosal and systemic host responses to SARS-CoV-2 infection. We profiled the upper respiratory tract (URT) and peripheral blood transcriptomes of 201 participants (age range of 1 week to 83 years), including 137 non-hospitalized individuals with mild SARS-CoV-2 infection and 64 uninfected individuals. Among uninfected children and adolescents, young age was associated with upregulation of innate and adaptive immune pathways within the URT, suggesting that young children are primed to mount robust mucosal immune responses to exogeneous respiratory pathogens. SARS-CoV-2 infection was associated with broad induction of innate and adaptive immune responses within the URT of children and adolescents. Peripheral blood responses among SARS-CoV-2-infected children and adolescents were dominated by interferon pathways, while upregulation of myeloid activation, inflammatory, and coagulation pathways was observed only in adults. Systemic symptoms among SARS-CoV-2-infected subjects were associated with blunted innate and adaptive immune responses in the URT and upregulation of many of these same pathways within peripheral blood. Finally, within individuals, robust URT immune responses were correlated with decreased peripheral immune activation, suggesting that effective immune responses in the URT may promote local viral control and limit systemic immune activation and symptoms. These findings demonstrate that there are differences in immune responses to SARS-CoV-2 across the lifespan, including between young children and adolescents, and suggest that these varied host responses contribute to observed differences in the clinical presentation of SARS-CoV-2 infection by age. One Sentence Summary: Age is associated with distinct upper respiratory and peripheral blood transcriptional responses among children and adults with SARS-CoV-2 infection.
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Variations in DNA methylation patterns in human tissues have been linked to various environmental exposures and infections. Here, we identified the DNA methylation signatures associated with multiple exposures in nine major immune cell types derived from peripheral blood mononuclear cells (PBMCs) at single-cell resolution. We performed methylome sequencing on 111,180 immune cells obtained from 112 individuals who were exposed to different viruses, bacteria, or chemicals. Our analysis revealed 790,662 differentially methylated regions (DMRs) associated with these exposures, which are mostly individual CpG sites. Additionally, we integrated methylation and ATAC-seq data from same samples and found strong correlations between the two modalities. However, the epigenomic remodeling in these two modalities are complementary. Finally, we identified the minimum set of DMRs that can predict exposures. Overall, our study provides the first comprehensive dataset of single immune cell methylation profiles, along with unique methylation biomarkers for various biological and chemical exposures.
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Systemic candidiasis is a common, high-mortality, nosocomial fungal infection. Unexpectedly, it has emerged as a complication of anti-complement C5-targeted monoclonal antibody treatment, indicating a critical niche for C5 in antifungal immunity. We identified transcription of complement system genes as the top biological pathway induced in candidemic patients and as predictive of candidemia. Mechanistically, C5a-C5aR1 promoted fungal clearance and host survival in a mouse model of systemic candidiasis by stimulating phagocyte effector function and ERK- and AKT-dependent survival in infected tissues. C5ar1 ablation rewired macrophage metabolism downstream of mTOR, promoting their apoptosis and enhancing mortality through kidney injury. Besides hepatocyte-derived C5, local C5 produced intrinsically by phagocytes provided a key substrate for antifungal protection. Lower serum C5a concentrations or a C5 polymorphism that decreases leukocyte C5 expression correlated independently with poor patient outcomes. Thus, local, phagocyte-derived C5 production licenses phagocyte antimicrobial function and confers innate protection during systemic fungal infection.
Subject(s)
Antifungal Agents , Candidiasis , Animals , Mice , Complement C5/metabolism , Phagocytes/metabolismABSTRACT
Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events, which have not been well characterized in pathogen infection, have potential normalization and assay platform stability advantages over gene expression for diagnosis. Here, we present a computational framework for developing AS diagnostic biomarkers. Leveraging a large prospective cohort of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whole-blood RNA sequencing (RNA-seq) data, we identify a major functional AS program switch upon viral infection. Using an independent cohort, we demonstrate the improved accuracy of AS biomarkers for SARS-CoV-2 diagnosis compared with six reported transcriptome signatures. We then optimize a subset of AS-based biomarkers to develop microfluidic PCR diagnostic assays. This assay achieves nearly perfect test accuracy (61/62 = 98.4%) using a naive principal component classifier, significantly more accurate than a gene expression PCR assay in the same cohort. Therefore, our RNA splicing computational framework enables a promising avenue for host-response diagnosis of infection.
Subject(s)
COVID-19 , Communicable Diseases , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , Alternative Splicing/genetics , COVID-19 Testing , RNA , Prospective Studies , Biomarkers/analysisABSTRACT
Renal transplantation from hepatitis C (HCV) nucleic acid amplification test-positive (NAAT-positive) donors to uninfected recipients has greatly increased the organ donation pool. However, there is concern for adverse outcomes in these recipients due to dysregulated immunologic activation secondary to active inflammation from acute viremia at the time of transplantation. This includes increased rates of cytomegalovirus (CMV) DNAemia and allograft rejection. In this study, we evaluate transcriptional responses in circulating leukocytes to define the character, timing, and resolution of this immune dysregulation and assess for biomarkers of adverse outcomes in transplant patients. We enrolled 67 renal transplant recipients (30 controls, 37 HCV recipients) and performed RNA sequencing on serial samples from one, 3-, and 6-months post-transplant. CMV DNAemia and allograft rejection outcomes were measured. Least absolute shrinkage and selection operator was utilized to develop gene expression classifiers predictive of clinical outcomes. Acute HCV incited a marked transcriptomic response in circulating leukocytes of renal transplant recipients in the acute post-transplant setting, despite the presence of immunosuppression, with 109 genes significantly differentially expressed compared to controls. These HCV infection-associated genes were reflective of antiviral immune pathways and generally resolved by the 3-month timepoint after sustained viral response (SVR) for HCV. Differential gene expression was also noted from patients who developed CMV DNAemia or allograft rejection compared to those who did not, although transcriptomic classifiers could not accurately predict these outcomes, likely due to sample size and variable time-to-event. Acute HCV infection incites evidence of immune activation and canonical antiviral responses in the human host even in the presence of systemic immunosuppression. After treatment of HCV with antiviral therapy and subsequent aviremia, this immune activation resolves. Changes in gene expression patterns in circulating leukocytes are associated with some clinical outcomes, although larger studies are needed to develop accurate predictive classifiers of these events.
Subject(s)
Cytomegalovirus Infections , Hepatitis C , Humans , Hepacivirus/genetics , Tissue Donors , Antiviral Agents/therapeutic use , Kidney , Cytomegalovirus Infections/drug therapy , Transplant RecipientsABSTRACT
BACKGROUND: We evaluated the associations between baseline influenza virus-specific hemagglutination inhibition (HAI) and microneutralization (MN) titers and subsequent symptomatic influenza virus infection in a controlled human infection study. METHODS: We inoculated unvaccinated healthy adults aged 18-49 years with an influenza A/California/04/2009/H1N1pdm-like virus (NCT04044352). We collected serial safety labs, serum for HAI and MN, and nasopharyngeal swabs for reverse-transcription polymerase chain reaction (RT-PCR) testing. Analyses used the putative seroprotective titer of ≥40 for HAI and MN. The primary clinical outcome was mild-to-moderate influenza disease (MMID), defined as ≥1 postchallenge positive qualitative RT-PCR test with a qualifying symptom/clinical finding. RESULTS: Of 76 participants given influenza virus challenge, 54 (71.1%) experienced MMID. Clinical illness was generally very mild. MMID attack rates among participants with baseline titers ≥40 by HAI and MN were 64.9% and 67.9%, respectively, while MMID attack rates among participants with baseline titers <40 by HAI and MN were 76.9% and 78.3%, respectively. The estimated odds of developing MMID decreased by 19% (odds ratio, 0.81 [95% confidence interval, .62-1.06]; P = .126) for every 2-fold increase in baseline HAI. There were no significant adverse events. CONCLUSIONS: We achieved a 71.1% attack rate of MMID. High baseline HAI and MN were associated with protection from illness. Clinical Trials Registration. NCT04044352.
Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza Vaccines , Influenza, Human , Humans , Adult , Influenza, Human/prevention & control , Antibodies, Viral , Research Design , Hemagglutination Inhibition TestsABSTRACT
BACKGROUND: Lower respiratory tract infections are frequently treated with antibiotics, despite a viral cause in many cases. It remains unknown whether low procalcitonin concentrations can identify patients with lower respiratory tract infection who are unlikely to benefit from antibiotics. We aimed to compare the efficacy and safety of azithromycin versus placebo to treat lower respiratory tract infections in patients with low procalcitonin. METHODS: We conducted a randomised, placebo-controlled, double-blind, non-inferiority trial at five health centres in the USA. Adults aged 18 years or older with clinically suspected non-pneumonia lower respiratory tract infection and symptom duration from 24 h to 28 days were eligible for enrolment. Participants with a procalcitonin concentration of 0·25 ng/mL or less were randomly assigned (1:1), in blocks of four with stratification by site, to receive over-encapsulated oral azithromycin 250 mg or matching placebo (two capsules on day 1 followed by one capsule daily for 4 days). Participants, non-study clinical providers, investigators, and study coordinators were masked to treatment allocation. The primary outcome was efficacy of azithromycin versus placebo in terms of clinical improvement at day 5 in the intention-to-treat population. The non-inferiority margin was -12·5%. Solicited adverse events (abdominal pain, vomiting, diarrhoea, allergic reaction, or yeast infections) were recorded as a secondary outcome. This trial is registered with ClinicalTrials.gov, NCT03341273. FINDINGS: Between Dec 8, 2017, and March 9, 2020, 691 patients were assessed for eligibility and 499 were enrolled and randomly assigned to receive azithromycin (n=249) or placebo (n=250). Clinical improvement at day 5 was observed in 148 (63%, 95% CI 54 to 71) of 238 participants with full data in the placebo group and 155 (69%, 61 to 77) of 227 participants with full data in the azithromycin group in the intention-to-treat analysis (between-group difference -6%, 95% CI -15 to 2). The 95% CI for the difference did not meet the non-inferiority margin. Solicited adverse events and the severity of solicited adverse events were not significantly different between groups at day 5, except for increased abdominal pain associated with azithromycin (47 [23%, 95% CI 18 to 29] of 204 participants) compared with placebo (35 [16%, 12 to 21] of 221; between-group difference -7% [95% CI -15 to 0]; p=0·066). INTERPRETATION: Placebo was not non-inferior to azithromycin in terms of clinical improvement at day 5 in adults with lower respiratory tract infection and a low procalcitonin concentration. After accounting for both the rates of clinical improvement and solicited adverse events at day 5, it is unclear whether antibiotics are indicated for patients with lower respiratory tract infection and a low procalcitonin concentration. FUNDING: National Institute of Allergy and Infectious Diseases, bioMérieux.
Subject(s)
Azithromycin , Respiratory Tract Infections , Adult , Humans , Azithromycin/adverse effects , Procalcitonin , Anti-Bacterial Agents/adverse effects , Respiratory Tract Infections/drug therapy , Double-Blind Method , Treatment OutcomeABSTRACT
BACKGROUND: The COVID-19 pandemic highlighted the need for early detection of viral infections in symptomatic and asymptomatic individuals to allow for timely clinical management and public health interventions. METHODS: Twenty healthy adults were challenged with an influenza A (H3N2) virus and prospectively monitored from 7 days before through 10 days after inoculation, using wearable electrocardiogram and physical activity sensors. This framework allowed for responses to be accurately referenced to the infection event. For each participant, we trained a semisupervised multivariable anomaly detection model on data acquired before inoculation and used it to classify the postinoculation dataset. RESULTS: Inoculation with this challenge virus was well-tolerated with an infection rate of 85%. With the model classification threshold set so that no alarms were recorded in the 170 healthy days recorded, the algorithm correctly identified 16 of 17 (94%) positive presymptomatic and asymptomatic individuals, on average 58 hours postinoculation and 23 hours before the symptom onset. CONCLUSIONS: The data processing and modeling methodology show promise for the early detection of respiratory illness. The detection algorithm is compatible with data collected from smartwatches using optical techniques but needs to be validated in large heterogeneous cohorts in normal living conditions. Clinical Trials Registration. NCT04204493.
Subject(s)
COVID-19 , Influenza A virus , Influenza, Human , Wearable Electronic Devices , Adult , Humans , COVID-19/diagnosis , COVID-19/epidemiology , Influenza A Virus, H3N2 Subtype/physiology , Influenza, Human/diagnosis , Pandemics , Prospective StudiesABSTRACT
During pandemics, individuals exhibit differences in risk and clinical outcomes. Here, we developed single-cell high-throughput human in vitro susceptibility testing (scHi-HOST), a method for rapidly identifying genetic variants that confer resistance and susceptibility. We applied this method to influenza A virus (IAV), the cause of four pandemics since the start of the 20th century. scHi-HOST leverages single-cell RNA sequencing (scRNA-seq) to simultaneously assign genetic identity to cells in mixed infections of cell lines of European, African, and Asian origin, reveal associated genetic variants for viral burden, and identify expression quantitative trait loci. Integration of scHi-HOST with human challenge and experimental validation demonstrated that a missense variant in endoplasmic reticulum aminopeptidase 1 (ERAP1; rs27895) increased IAV burden in cells and human volunteers. rs27895 exhibits population differentiation, likely contributing to greater permissivity of cells from African populations to IAV. scHi-HOST is a broadly applicable method and resource for decoding infectious-disease genetics.
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The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. A record of this paper's transparent peer review process is included in the supplemental information.
Subject(s)
COVID-19 , Virus Diseases , Humans , SARS-CoV-2ABSTRACT
OBJECTIVES: Sepsis causes significant mortality. However, most patients who die of sepsis do not present with severe infection, hampering efforts to deliver early, aggressive therapy. It is also known that the host gene expression response to infection precedes clinical illness. This study seeks to develop transcriptomic models to predict progression to sepsis or shock within 72 hours of hospitalization and to validate previously identified transcriptomic signatures in the prediction of 28-day mortality. DESIGN: Retrospective differential gene expression analysis and predictive modeling using RNA sequencing data. PATIENTS: Two hundred seventy-seven patients enrolled at four large academic medical centers; all with clinically adjudicated infection were considered for inclusion in this study. MEASUREMENTS AND MAIN RESULTS: Sepsis progression was defined as an increase in Sepsis 3 category within 72 hours. Transcriptomic data were generated using RNAseq of whole blood. Least absolute shrinkage and selection operator modeling was used to identify predictive signatures for various measures of disease progression. Four previously identified gene signatures were tested for their ability to predict 28-day mortality. There were no significant differentially expressed genes in 136 subjects with worsened Sepsis 3 category compared with 141 nonprogressor controls. There were 1,178 differentially expressed genes identified when sepsis progression was defined as ICU admission or 28-day mortality. A model based on these genes predicted progression with an area under the curve of 0.71. Validation of previously identified gene signatures to predict sepsis mortality revealed area under the receiver operating characteristic values of 0.70-0.75 and no significant difference between signatures. CONCLUSIONS: Host gene expression was unable to predict sepsis progression when defined by an increase in Sepsis-3 category, suggesting this definition is not a useful framework for transcriptomic prediction methods. However, there was a differential response when progression was defined as ICU admission or death. Validation of previously described signatures predicted 28-day mortality with insufficient accuracy to offer meaningful clinical utility.
Subject(s)
Sepsis , Humans , Retrospective Studies , ROC Curve , Hospitalization , Gene Expression , PrognosisABSTRACT
Purpose: Several cases of symptomatic reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after full recovery from a prior episode have been reported. As reinfection has become an increasingly common phenomenon, an improved understanding of the risk factors for reinfection and the character and duration of the serological responses to infection and vaccination is critical for managing the coronavirus disease 2019 (COVID-19) pandemic. Methods: We described four cases of SARS-CoV-2 reinfection in individuals representing a spectrum of healthy and immunocompromised states, including (1) a healthy 41-year-old pediatrician, (2) an immunocompromised 31-year-old with granulomatosis with polyangiitis, (3) a healthy 26-year-old pregnant woman, and (4) a 50-year-old with hypertension and hyperlipidemia. We performed confirmatory quantitative reverse transcription-polymerase chain reaction and qualitative immunoglobulin M and quantitative IgG testing on all available patient samples to confirm the presence of infection and serological response to infection. Results: Our analysis showed that patients 1 and 2, a healthy and an immunocompromised patient, both failed to mount a robust serologic response to the initial infection. In contrast, patients 3 and 4, with minimal comorbid disease, both mounted a strong serological response to their initial infection, but were still susceptible to reinfection. Conclusion: Repeat episodes of COVID-19 are capable of occurring in patients regardless of the presence of known risk factors for infection or level of serological response to infection, although this did not trigger critical illness in any instance.