Prevalence and predictors of antibiotic prescription among patients hospitalized with viral lower respiratory tract infections in Southern Province, Sri Lanka.

BACKGROUND: Antimicrobial overprescription is common for lower respiratory tract infections (LRTI), as viral and bacterial infections generally present with similar clinical features. Overprescription is associated with downstream antimicrobial resistance. This study aims to identify the prevalence and predictors of antibiotic prescription among patients hospitalized with viral LRTI. METHODS: A prospective cohort study was conducted among patients aged ≥1 year hospitalized with viral LRTI in a tertiary care hospital in Southern Province, Sri Lanka from 2018-2021. Demographic, clinical, and laboratory data were recorded. Nasopharyngeal and blood samples were collected for multiplex polymerase chain reaction testing for 21 respiratory pathogens and procalcitonin (PCT) detection, respectively. Demographic and clinical features associated with antibiotic prescription were identified using Chi Square and t-tests; significant variables (p<0.05) were further included in multivariable logistic regression models. The potential impact of biomarker testing on antibiotic prescription was simulated using standard c-reactive protein (CRP) and PCT cut-offs. RESULTS: Of 1217 patients enrolled, 438 (36.0%) had ≥1 respiratory virus detected, with 48.4% of these patients being male and 30.8% children. Influenza A (39.3%) and human rhinovirus/ enterovirus (28.3%) were most commonly detected. A total of 114 (84.4%) children and 266 (87.8%) adults with respiratory viruses were treated with antibiotics. Among children, neutrophil percentage (median 63.6% vs 47.6%, p = 0.04) was positively associated with antibiotic prescription. Among adults, headache (60.6% vs 35.1%, p = 0.003), crepitations/crackles (55.3% vs 21.6%, p<0.001), rhonchi/wheezing (42.9% vs 18.9%, p = 0.005), and chest x-ray opacities (27.4% vs 8.1%, p = 0.01) were associated with antibiotic prescription. Access to CRP and procalcitonin test results could have potentially decreased inappropriate antibiotic prescription in this study by 89.5% and 83.3%, respectively. CONCLUSIONS: High proportions of viral detection and antibiotic prescription were observed among a large inpatient cohort with LRTI. Increased access to point-of-care biomarker testing may improve antimicrobial prescription.

Implementation of a Prospective Index-Cluster Sampling Strategy for the Detection of Presymptomatic Viral Respiratory Infection in Undergraduate Students.

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.

Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance.

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.

Wearable Sensor-Based Detection of Influenza in Presymptomatic and Asymptomatic Individuals.

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.

Nationwide Genomic Surveillance and Response to COVID-19: The VA SeqFORCE and SeqCURE Consortiums.

Background: The US Department of Veterans Affairs (VA) has dedicated significant resources toward countering the COVID-19 pandemic. Sequencing for Research Clinical and Epidemiology (SeqFORCE) and Sequencing Collaborations United for Research and Epidemiology (SeqCURE) were developed as clinical and research consortiums, respectively, focused on the genetic COVID-19 surveillance. Observations: Through genetic sequencing, VA SeqFORCE and SeqCURE collaborations contributed to the COVID-19 pandemic response and scientific understanding. Future directions for each program include the assessment of the unique impact of COVID-19 on the veteran population, as well as the adaptation of these programs to future infectious disease threats. We foresee the use of these established platforms beyond infectious diseases. Conclusions: VA SeqFORCE and SeqCURE were established as clinical and research programs dedicated to sequencing COVID-19 as part of ongoing clinical and surveillance efforts. In the future, we anticipate that having these programs embedded within the largest integrated health care system in the US will enable the study of pathogens and pandemics beyond COVID-19 and at an unprecedented scale. The investment in these programs will form an integral part of our nation's response to emerging infectious diseases, with future applications to precision medicine and beyond.

Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion.

SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associated with mild or moderate symptoms were already robust and included severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity was marked by upregulation of classical antiviral pathways, including those regulating IRF1 and IRF7, whereas in moderate disease, these classical antiviral signals diminished, suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.

Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion.

SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associate with mild or moderate symptoms are already robust and include severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity is marked by upregulation classical antiviral pathways including those regulating IRF1 and IRF7, whereas in moderate disease these classical antiviral signals diminish suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.

Risk Factors for Ebola Exposure in Health Care Workers in Boende, Tshuapa Province, Democratic Republic of the Congo.

BACKGROUND: Health care workers (HCW) are more likely to be exposed to Ebola virus (EBOV) during an outbreak compared to people in the general population due to close physical contact with patients and potential exposure to infectious fluids. However, not all will fall ill. Despite evidence of subclinical and paucisymptomatic Ebola virus disease (EVD), prevalence and associated risk factors remain unknown. METHODS: We conducted a serosurvey among HCW in Boende, Tshuapa Province, Democratic Republic of Congo. Human anti-EBOV glycoprotein IgG titers were measured using a commercially available ELISA kit. We assessed associations between anti-EBOV IgG seroreactivity, defined as ≥2.5 units/mL, and risk factors using univariable and multivariable logistic regression. Sensitivity analyses explored a more conservative cutoff, >5 units/mL. RESULTS: Overall, 22.5% of HCWs were seroreactive for EBOV. In multivariable analyses, using any form of personal protective equipment when interacting with a confirmed, probable, or suspect EVD case was negatively associated with seroreactivity (adjusted odds ratio, 0.23; 95% confidence interval, .07-.73). DISCUSSION: Our results suggest high exposure to EBOV among HCWs and provide additional evidence for asymptomatic or minimally symptomatic EVD. Further studies should be conducted to determine the probability of onward transmission and if seroreactivity is associated with immunity.

Outcomes among children and adults at risk of severe dengue in Sri Lanka: Opportunity for outpatient case management in countries with high disease burden.

BACKGROUND: Healthcare systems in dengue-endemic countries are often overburdened due to the high number of patients hospitalized according to dengue management guidelines. We systematically evaluated clinical outcomes in a large cohort of patients hospitalized with acute dengue to support triaging of patients to ambulatory versus inpatient management in the future. METHODS/PRINCIPAL FINDINGS: From June 2017- December 2018, we conducted surveillance among children and adults with fever within the prior 7 days who were hospitalized at the largest tertiary-care (1,800 bed) hospital in the Southern Province, Sri Lanka. Patients who developed platelet count ≤100,000/µL (threshold for hospital admission in Sri Lanka) and who met at least two clinical criteria consistent with dengue were eligible for enrollment. We confirmed acute dengue by testing sera collected at enrollment for dengue NS1 antigen or IgM antibodies. We defined primary outcomes as per the 1997 and 2009 World Health Organization (WHO) classification criteria: dengue hemorrhagic fever (DHF; WHO 1997), dengue shock syndrome (DSS; WHO 1997), and severe dengue (WHO 2009). Overall, 1064 patients were confirmed as having acute dengue: 318 (17.4%) by NS1 rapid antigen testing and 746 (40.7%) by IgM antibody testing. Of these 1064 patients, 994 (93.4%) were adults ≥18 years and 704 (66.2%) were male. The majority (56, 80%) of children and more than half of adults (544, 54.7%) developed DHF during hospitalization, while 6 (8.6%) children and 22 (2.2%) adults developed DSS. Overall, 10 (14.3%) children and 113 (11.4%) adults developed severe dengue. A total of 2 (0.2%) patients died during hospitalization. CONCLUSIONS: One-half of patients hospitalized with acute dengue progressed to develop DHF and a very small number developed DSS or severe dengue. Developing an algorithm for triaging patients to ambulatory versus inpatient management should be the future goal to optimize utilization of healthcare resources in dengue-endemic countries.

Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset.

Importance: Currently, there are no presymptomatic screening methods to identify individuals infected with a respiratory virus to prevent disease spread and to predict their trajectory for resource allocation. Objective: To evaluate the feasibility of using noninvasive, wrist-worn wearable biometric monitoring sensors to detect presymptomatic viral infection after exposure and predict infection severity in patients exposed to H1N1 influenza or human rhinovirus. Design, Setting, and Participants: The cohort H1N1 viral challenge study was conducted during 2018; data were collected from September 11, 2017, to May 4, 2018. The cohort rhinovirus challenge study was conducted during 2015; data were collected from September 14 to 21, 2015. A total of 39 adult participants were recruited for the H1N1 challenge study, and 24 adult participants were recruited for the rhinovirus challenge study. Exclusion criteria for both challenges included chronic respiratory illness and high levels of serum antibodies. Participants in the H1N1 challenge study were isolated in a clinic for a minimum of 8 days after inoculation. The rhinovirus challenge took place on a college campus, and participants were not isolated. Exposures: Participants in the H1N1 challenge study were inoculated via intranasal drops of diluted influenza A/California/03/09 (H1N1) virus with a mean count of 106 using the median tissue culture infectious dose (TCID50) assay. Participants in the rhinovirus challenge study were inoculated via intranasal drops of diluted human rhinovirus strain type 16 with a count of 100 using the TCID50 assay. Main Outcomes and Measures: The primary outcome measures included cross-validated performance metrics of random forest models to screen for presymptomatic infection and predict infection severity, including accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). Results: A total of 31 participants with H1N1 (24 men [77.4%]; mean [SD] age, 34.7 [12.3] years) and 18 participants with rhinovirus (11 men [61.1%]; mean [SD] age, 21.7 [3.1] years) were included in the analysis after data preprocessing. Separate H1N1 and rhinovirus detection models, using only data on wearble devices as input, were able to distinguish between infection and noninfection with accuracies of up to 92% for H1N1 (90% precision, 90% sensitivity, 93% specificity, and 90% F1 score, 0.85 [95% CI, 0.70-1.00] AUC) and 88% for rhinovirus (100% precision, 78% sensitivity, 100% specificity, 88% F1 score, and 0.96 [95% CI, 0.85-1.00] AUC). The infection severity prediction model was able to distinguish between mild and moderate infection 24 hours prior to symptom onset with an accuracy of 90% for H1N1 (88% precision, 88% sensitivity, 92% specificity, 88% F1 score, and 0.88 [95% CI, 0.72-1.00] AUC) and 89% for rhinovirus (100% precision, 75% sensitivity, 100% specificity, 86% F1 score, and 0.95 [95% CI, 0.79-1.00] AUC). Conclusions and Relevance: This cohort study suggests that the use of a noninvasive, wrist-worn wearable device to predict an individual's response to viral exposure prior to symptoms is feasible. Harnessing this technology would support early interventions to limit presymptomatic spread of viral respiratory infections, which is timely in the era of COVID-19.

Innate-like Gene Expression of Lung-Resident Memory CD8+ T Cells during Experimental Human Influenza: A Clinical Study.

Rationale: Suboptimal vaccine immunogenicity and antigenic mismatch, compounded by poor uptake, means that influenza remains a major global disease. T cells recognizing peptides derived from conserved viral proteins could enhance vaccine-induced cross-strain protection. Objectives: To investigate the kinetics, phenotypes, and function of influenza virus-specific CD8+ resident memory T (Trm) cells in the lower airway and infer the molecular pathways associated with their response to infection in vivo. Methods: Healthy volunteers, aged 18-55, were inoculated intranasally with influenza A/California/4/09(H1N1). Blood, upper airway, and (in a subgroup) lower airway samples were obtained throughout infection. Symptoms were assessed by using self-reported diaries, and the nasal viral load was assessed by using quantitative PCR. T-cell responses were analyzed by using a three-color FluoroSpot assay, flow cytometry with MHC I-peptide tetramers, and RNA sequencing, with candidate markers being confirmed by using the immunohistochemistry results for endobronchial biopsy specimens. Measurements and Main Results: After challenge, 57% of participants became infected. Preexisting influenza-specific CD8+ T cells in blood correlated strongly with a reduced viral load, which peaked at Day 3. Influenza-specific CD8+ T cells in BAL fluid were highly enriched and predominantly expressed the Trm markers CD69 and CD103. Comparison between preinfection CD8+ T cells in BAL fluid and blood by using RNA sequencing revealed 3,928 differentially expressed genes, including all major Trm-cell markers. However, gene set enrichment analysis of BAL-fluid CD8+ T cells showed primarily innate cell-related pathways and, during infection, included upregulation of innate chemokines (Cxcl1, Cxcl10, and Cxcl16) that were also expressed by CD8+ cells in bronchial tissues. Conclusions: CD8+ Trm cells in the human lung display innate-like gene and protein expression that demonstrates blurred divisions between innate and adaptive immunity. Clinical study registered with www.clinicaltrials.gov (NCT02755948).

Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.

OBJECTIVES: Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test. DESIGN: Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results. SETTING: Four U.S. emergency departments. PATIENTS: Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis. INTERVENTIONS: Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes. MEASUREMENTS AND MAIN RESULTS: Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance. CONCLUSIONS: The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.

Colonization with multidrug-resistant Enterobacteriaceae among infants: an observational study in southern Sri Lanka.

BACKGROUND: The timing of and risk factors for intestinal colonization with multidrug-resistant Enterobacteriaceae (MDRE) are still poorly understood in areas with high MDRE carriage. We determined the prevalence, timing, and risk factors associated with MDRE intestinal colonization among infants in southern Sri Lanka. METHODS: Women and their newborn children were enrolled within 48 h after delivery in southern Sri Lanka. Rectal swabs were collected from women and infants at enrollment and 4-6 weeks later. Enterobacteriaceae were isolated and identified as MDRE (positive for extended-spectrum ß-lactamases or carbapenem resistant) using standard microbiologic procedures. We used exact methods (Fisher's exact and Kruskal-Wallis tests) and multivariable logistic regression to identify sociodemographic and clinical features associated with MDRE intestinal colonization. Whole-genome sequencing was performed on selected MDRE isolates to identify phylogroups and antibiotic resistance-encoding genes were identified with NCBI's AMRfinder tool. RESULTS: Overall, 199 post-partum women and 199 infants were enrolled; 148/199 (74.4%) women and 151/199 (75.9%) infants were reassessed later in the community. Twenty-four/199 (12.1%) women and 3/199 (1.5%) infants displayed intestinal colonization with MDRE at enrollment, while 26/148 (17.6%) women and 24/151 (15.9%) infants displayed intestinal colonization with MDRE at the reassessment. While there were no risk factors associated with infant colonization at enrollment, multivariable analysis indicated that risk factors for infant colonization at reassessment included mother colonized at enrollment (aOR = 3.62) or reassessment (aOR = 4.44), delivery by Cesarean section (aOR = 2.91), and low birth weight (aOR = 5.39). Of the 20 MDRE isolates from infants that were sequenced, multilocus sequence typing revealed that 6/20 (30%) were clustered on the same branch as MDRE isolates found in the respective mothers. All sequenced isolates for mothers (47) and infants (20) had at least one ESBL-producing gene. Genes encoding fosfomycin resistance were found in 33/47 (70%) of mothers' isolates and 16/20 (80%) of infants' isolates and genes encoding resistance to colistin were found in one (2%) mother's isolate. CONCLUSIONS: Our results suggest that a substantial proportion of infants undergo MDRE intestinal colonization within 6 weeks of birth, potentially due to postnatal rather than intranatal transmission.

Dysregulated transcriptional responses to SARS-CoV-2 in the periphery.

SARS-CoV-2 infection has been shown to trigger a wide spectrum of immune responses and clinical manifestations in human hosts. Here, we sought to elucidate novel aspects of the host response to SARS-CoV-2 infection through RNA sequencing of peripheral blood samples from 46 subjects with COVID-19 and directly comparing them to subjects with seasonal coronavirus, influenza, bacterial pneumonia, and healthy controls. Early SARS-CoV-2 infection triggers a powerful transcriptomic response in peripheral blood with conserved components that are heavily interferon-driven but also marked by indicators of early B-cell activation and antibody production. Interferon responses during SARS-CoV-2 infection demonstrate unique patterns of dysregulated expression compared to other infectious and healthy states. Heterogeneous activation of coagulation and fibrinolytic pathways are present in early COVID-19, as are IL1 and JAK/STAT signaling pathways, which persist into late disease. Classifiers based on differentially expressed genes accurately distinguished SARS-CoV-2 infection from other acute illnesses (auROC 0.95 [95% CI 0.92-0.98]). The transcriptome in peripheral blood reveals both diverse and conserved components of the immune response in COVID-19 and provides for potential biomarker-based approaches to diagnosis.

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study.

BACKGROUND: Early and accurate identification of individuals with viral infections is crucial for clinical management and public health interventions. We aimed to assess the ability of transcriptomic biomarkers to identify naturally acquired respiratory viral infection before typical symptoms are present. METHODS: In this index-cluster study, we prospectively recruited a cohort of undergraduate students (aged 18-25 years) at Duke University (Durham, NC, USA) over a period of 5 academic years. To identify index cases, we monitored students for the entire academic year, for the presence and severity of eight symptoms of respiratory tract infection using a daily web-based survey, with symptoms rated on a scale of 0-4. Index cases were defined as individuals who reported a 6-point increase in cumulative daily symptom score. Suspected index cases were visited by study staff to confirm the presence of reported symptoms of illness and to collect biospecimen samples. We then identified clusters of close contacts of index cases (ie, individuals who lived in close proximity to index cases, close friends, and partners) who were presumed to be at increased risk of developing symptomatic respiratory tract infection while under observation. We monitored each close contact for 5 days for symptoms and viral shedding and measured transcriptomic responses at each timepoint each day using a blood-based 36-gene RT-PCR assay. FINDINGS: Between Sept 1, 2009, and April 10, 2015, we enrolled 1465 participants. Of 264 index cases with respiratory tract infection symptoms, 150 (57%) had a viral cause confirmed by RT-PCR. Of their 555 close contacts, 106 (19%) developed symptomatic respiratory tract infection with a proven viral cause during the observation window, of whom 60 (57%) had the same virus as their associated index case. Nine viruses were detected in total. The transcriptomic assay accurately predicted viral infection at the time of maximum symptom severity (mean area under the receiver operating characteristic curve [AUROC] 0·94 [95% CI 0·92-0·96]), as well as at 1 day (0·87 [95% CI 0·84-0·90]), 2 days (0·85 [0·82-0·88]), and 3 days (0·74 [0·71-0·77]) before peak illness, when symptoms were minimal or absent and 22 (62%) of 35 individuals, 25 (69%) of 36 individuals, and 24 (82%) of 29 individuals, respectively, had no detectable viral shedding. INTERPRETATION: Transcriptional biomarkers accurately predict and diagnose infection across diverse viral causes and stages of disease and thus might prove useful for guiding the administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious diseases. FUNDING: US Defense Advanced Research Projects Agency.

Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity.

SARS-CoV-2 infection triggers highly variable host responses and causes varying degrees of illness in humans. We sought to harness the peripheral blood mononuclear cell (PBMC) response over the course of illness to provide insight into COVID-19 physiology. We analyzed PBMCs from subjects with variable symptom severity at different stages of clinical illness before and after IgG seroconversion to SARS-CoV-2. Prior to seroconversion, PBMC transcriptomes did not distinguish symptom severity. In contrast, changes in chromatin accessibility were associated with symptom severity. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif occupancy for individual PBMC cell types. The most extensive remodeling occurred in CD14+ monocytes where sub-populations with distinct chromatin accessibility profiles were associated with disease severity. Our findings indicate that pre-seroconversion chromatin remodeling in certain innate immune populations is associated with divergence in symptom severity, and the identified transcription factors, regulatory elements, and downstream pathways provide potential prognostic markers for COVID-19 subjects.

Outbreak of severe acute respiratory infection in Southern Province, Sri Lanka in 2018: a cross-sectional study.

OBJECTIVES: To determine aetiology of illness among children and adults presenting during outbreak of severe respiratory illness in Southern Province, Sri Lanka, in 2018. DESIGN: Prospective, cross-sectional study. SETTING: 1600-bed, public, tertiary care hospital in Southern Province, Sri Lanka. PARTICIPANTS: 410 consecutive patients, including 371 children and 39 adults, who were admitted with suspected viral pneumonia (passive surveillance) or who met case definition for acute respiratory illness (active surveillance) in May to June 2018. RESULTS: We found that cocirculation of influenza A (22.6% of cases), respiratory syncytial virus (27.8%) and adenovirus (AdV) (30.7%; type B3) was responsible for the outbreak. Mortality was noted in 4.5% of paediatric cases identified during active surveillance. Virus type and viral coinfection were not significantly associated with mortality. CONCLUSIONS: This is the first report of intense cocirculation of multiple respiratory viruses as a cause of an outbreak of severe acute respiratory illness in Sri Lanka, and the first time that AdV has been documented as a cause of a respiratory outbreak in the country. Our results emphasise the need for continued vigilance in surveying for known and emerging respiratory viruses in the tropics.

Dysregulated transcriptional responses to SARS-CoV-2 in the periphery support novel diagnostic approaches.

In order to elucidate novel aspects of the host response to SARS-CoV-2 we performed RNA sequencing on peripheral blood samples across 77 timepoints from 46 subjects with COVID-19 and compared them to subjects with seasonal coronavirus, influenza, bacterial pneumonia, and healthy controls. Early SARS-CoV-2 infection triggers a conserved transcriptomic response in peripheral blood that is heavily interferon-driven but also marked by indicators of early B-cell activation and antibody production. Interferon responses during SARS-CoV-2 infection demonstrate unique patterns of dysregulated expression compared to other infectious and healthy states. Heterogeneous activation of coagulation and fibrinolytic pathways are present in early COVID-19, as are IL1 and JAK/STAT signaling pathways, that persist into late disease. Classifiers based on differentially expressed genes accurately distinguished SARS-CoV-2 infection from other acute illnesses (auROC 0.95). The transcriptome in peripheral blood reveals unique aspects of the immune response in COVID-19 and provides for novel biomarker-based approaches to diagnosis.

Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population.

BACKGROUND: Pathogen-based diagnostics for acute respiratory infection (ARI) have limited ability to detect etiology of illness. We previously showed that peripheral blood-based host gene expression classifiers accurately identify bacterial and viral ARI in cohorts of European and African descent. We determined classifier performance in a South Asian cohort. METHODS: Patients ≥15 years with fever and respiratory symptoms were enrolled in Sri Lanka. Comprehensive pathogen-based testing was performed. Peripheral blood ribonucleic acid was sequenced and previously developed signatures were applied: a pan-viral classifier (viral vs nonviral) and an ARI classifier (bacterial vs viral vs noninfectious). RESULTS: Ribonucleic acid sequencing was performed in 79 subjects: 58 viral infections (36 influenza, 22 dengue) and 21 bacterial infections (10 leptospirosis, 11 scrub typhus). The pan-viral classifier had an overall classification accuracy of 95%. The ARI classifier had an overall classification accuracy of 94%, with sensitivity and specificity of 91% and 95%, respectively, for bacterial infection. The sensitivity and specificity of C-reactive protein (>10 mg/L) and procalcitonin (>0.25 ng/mL) for bacterial infection were 100% and 34%, and 100% and 41%, respectively. CONCLUSIONS: Previously derived gene expression classifiers had high predictive accuracy at distinguishing viral and bacterial infection in South Asian patients with ARI caused by typical and atypical pathogens.