Frailty assessment in the emergency department (ED) is essential but challenging. The Clinical Frailty Scale (CFS) is widely used, although inter-rater variability has been reported across assessors and assessment methods. To assess agreement between ED-assigned and retrospectively assigned CFS scores, and to explore characteristics associated with changes in frailty classification. We included 500 patients aged ≥ 65 years admitted with suspected pneumonia to Haukeland University Hospital (2019–2023). CFS was initially scored by nurses in the ED and reassessed retrospectively by a geriatric-trained physician using chart review. The retrospective assessment had access to broader and more objective information, including formal documentation from care services on daily function. CFS scores were categorized as fit (1–3), prefrail (4) and frail (5–9). Agreement was measured by Intraclass Correlation Coefficient (ICC). CFS scores changed numerically in 252 (50.4

IntroductionAchieving the goal of the End TB Strategy depends on new tools, preferably blood-based point-of-care (POC) tests, to identify individuals at risk of progression from M. tuberculosis infection to subclinical or clinical tuberculosis (TB). A decade of signature discovery and validation has resulted in several transcriptional signatures with promising capacity for predicting TB progression within the next 3–6 months, but evaluation of signature performance in Asian populations is lacking.MethodsNested within a prospective observational cohort study of Indian household contacts (HHC study), we adapted the RISK6 and Sweeney3 along with our locally derived INDIA11 signature to the microfluidic RT-qPCR platform (Fluidigm) and evaluated their capacity to predict TB progression during a 12-month follow-up in a head-to-head comparison. As readily available in our dataset, the recently published single-gene signatures GBP2, FCGR1B, and SERPING1 were also assessed.ResultsOf the 525 recruited household contacts, 12 (6 cases in children aged 5–14 years) progressed to TB (5 at 6 months, 7 at 12 months) as defined by growth of M. tuberculosis in respiratory specimens. RISK6 and Sweeney3 were successfully adapted to the Fluidigm platform. One gene in the INDIA11 assay failed, resulting in the INDIA10 signature with an overall failure rate of 5.7%. RISK6, Sweeney3, and INDIA10 demonstrated comparable but statistically non-significant predictive performance for TB progression, with AUCs: RISK6 0.61 (95%CI 0.41–0.82), Sweeney3 0.61 (95%CI 0.41–0.80), INDIA10 0.59 (95%CI 0.46–0.72). Applying a fixed value of sensitivity 75% corresponding to the WHO minimum target for TB prediction resulted in the corresponding specificities RISK6 0.49 (95%CI 0.41–0.56), Sweeney3 0.32 (95%CI 0.25–0.39), and INDIA10 0.42 (95%CI 0.35–0.50). Of single-gene signatures, the AUCs of FCGR1B and GBP2 were significant with specificities of FCGR1B 0.56 (95%CL 0.49–0.64) and GBP 0.50 (95%CL 0.43–0.58).DiscussionThe expression of interferon-gamma–inducible gene signatures were able to discriminate between TB progressors and non-progressors in an hitherto underexplored Indian population, supporting the generalizability of RNA technology to this setting. Given the limited sensitivity and specificity of current biosignatures in all populations, exploration of integrated diagnostic algorithms relying on established and novel tools in a multidisciplinary approach is warranted.

The repeated emergence of highly transmissive SARS-CoV-2 variants requires a broadly protective vaccine. We developed a T-cell vaccine VB10.2210 that targets SARS-CoV-2 viral antigens to antigen presenting cells comprising 96 validated immunogenic T-cell epitopes covering a global HLA diversity. We report results from a first in human open-label dose-escalation phase 1/2 clinical trial evaluating safety, reactogenicity and immunogenicity of VB10.2210. The study investigated three dose levels (0.3, 1.0 and 3.0 mg), delivered intramuscularly as DNA plasmid by jet injection (NCT05069623), in 34 healthy adults previously vaccinated with mRNA SARS-CoV-2 vaccines. The safety profile was favorable with no observed dose-limiting toxicity. The 3 mg dose elicited the most potent immune response with enhanced breadth and a CD8+ dominated T cell response. T cell responses towards spike protein and de novo responses to non-spike antigens were confirmed by ELISpot. Expansion of VB10.2210 specific T-cell clones was confirmed by TCR sequencing. Further studies are needed to evaluate the clinical benefit of DNA vaccines inducing broad virus specific T-cell immunity in preventing severe COVID-19 or as treatment of patients with persistent infection.

Background and objectives:The MeMed BV® test distinguishes bacterial from viral infections by integrating circulating levels of TRAIL, IP-10, and CRP into a likelihood score. Pre-COVID studies reported high diagnostic accuracy in respiratory infections, but evidence in adults hospitalized with SARS-CoV-2 is sparse. To evaluate the ability of MeMed BV to identify hospitalized COVID-19 patients who could be safely managed without antibiotics. Methods:We included adults with PCR-confirmed SARS-CoV-2 infection from two prospective Norwegian cohorts (October 2020-April 2023). The reference standard for true viral infection was a composite safety outcome: 30-day survival, no readmission within 30 days, and no antibiotic exposure before, during, or after hospitalization. MeMed BV performance was assessed using sensitivity, specificity, predictive values, and area under the ROC curve (AUC). Results:Of 90 patients, 28 (31%) met the reference standard for safe antibiotic avoidance. Median MeMed BV scores were 38 (IQR 1-66) in the safely managed group versus 96 (IQR 78-99) in others (P  < 0.001). Sensitivity for identifying safe antibiotic avoidance was 50.0% (95% CI 32.6-67.4), specificity 88.7% (95% CI 78.5-94.4), PPV 66.7%, NPV 79.7%, and AUC 0.69 (95% CI 0.59-0.80). Patients safely managed without antibiotics misclassified as bacterial/equivocal had markedly lower TRAIL (median 38 versus 177 pg/mL, P  < 0.001) and higher CRP. Conclusions:In hospitalized adults with COVID-19, MeMed BV showed reasonable specificity but limited sensitivity for identifying patients who could safely avoid antibiotics, with performance considerably lower than that observed in pre-COVID studies. These findings highlight the need for context-specific validation of host-response diagnostics.

Community-acquired pneumonia [CAP] is a leading cause of morbidity and mortality, often complicated by diagnostic uncertainty and antibiotic overuse. This study evaluated the MeMed BV® host-response test in adults with suspected CAP, using clinical management and molecular detection as reference standards. Among 744 patients presenting with suspected CAP at Haukeland University Hospital, Bergen, Norway (2019-2023), across three prospective studies, 453 were included in the present study. Patients were classified using: [1] clinical management [antibiotic timing/duration], and [2] molecular detection via BioFire® FilmArray Pneumonia Plus panel on lower respiratory tract samples. MeMed BV® testing was performed retrospectively on stored serum/plasma, categorising results as bacterial, viral, or equivocal. Healthy controls [n = 20] were also tested. Among 442 patients classified by clinical management, the MeMed BV® test demonstrated a positive percent agreement [PPA] of 90.0% (95% CI: 86.4-92.7) and a negative percent agreement [NPA] was 44.1% (95% CI: 34.4-54.2). In 370 patients classified by molecular testing, PPA was 88.2% (95% CI: 83.6-91.7) and NPA was 30.1% (95% CI: 20.8-41.4. Equivocal results occurred in 7.5%. The test agreed with clinical management in 96.1% of cases with no detected pathogen. None of the healthy controls had bacterial scores. CONCLUSION: MeMed BV® demonstrated high sensitivity in identifying bacterial infections but limited specificity in viral infections, notably SARS-CoV-2. It may aid early triage when combined with clinical and microbiological data. TRIAL REGISTRATION: ClinicalTrials.gov NCT04660084.

Community-acquired pneumonia (CAP) causes substantial morbidity and mortality, particularly in patients with chronic obstructive pulmonary disease (COPD). This study compares the microbial detections in CAP patients with and without COPD using culture based and molecular diagnostic methods. This prospective study included 412 hospitalized pneumonia patients (136 with COPD). Lower respiratory tract samples were analysed with traditional cultures and a multiplex PCR panel (FilmArray Pneumonia Panel Plus). Multivariable Poisson regression identified predictors of Pseudomonas aeruginosa detection, and logistic regression estimated detection probability using the top predictors. Overall pathogen detection rates were similar between groups, but P. aeruginosa was significantly more common in COPD patients (12.5

BACKGROUND:Current tuberculosis treatment regimens could be improved by adjunct host-directed therapies (HDT) targeting host responses. We investigated the antimycobacterial capacity of macrophages from patients with tuberculosis in a phase 1/2 randomized clinical trial (TBCOX2) of the cyclooxygenase-2 inhibitor etoricoxib. METHODS:Peripheral blood mononuclear cells from 15 patients with tuberculosis treated with adjunctive COX-2i and 18 controls (standard therapy) were collected on day 56 after treatment initiation. The ex vivo capacity of macrophages to control mycobacterial infection was assessed by challenge with Mycobacterium avium, using an in vitro culture model. Macrophage inflammatory responses were analyzed by gene expression signatures, and concentrations of cytokines were analyzed in supernatants by multiplex. RESULTS:Macrophages from patients receiving adjunctive COX-2i treatment had higher M. avium loads than controls after 6 days, suggesting an impaired capacity to control mycobacterial infection compared to macrophages from the control group. Macrophages from the COX-2i group had lower gene expression of TNF, IL-1B, CCL4, CXCL9, and CXCL10 and lowered production of cytokines IFN-β and S100A8/A9 than controls. CONCLUSIONS:Our data suggest potential unfavorable effects with impaired macrophage capacity to control mycobacterial growth in patients with tuberculosis receiving COX-2i treatment. Larger clinical trials are required to analyze the safety of COX-2i as HDT in patients with tuberculosis. CLINICAL TRIALS REGISTRATION:NCT02503839.

ABSTRACT Lower respiratory tract infections (LRTIs) remain a significant global cause of infectious disease-related mortality. Accurate discrimination between acute bacterial and viral LRTIs is crucial for optimal patient care, prevention of unnecessary antibiotic prescriptions, and resource allocation. Plasma samples from LRTI patients with bacterial ( n = 36), viral ( n = 27; excluding SARS-CoV-2), SARS-CoV-2 ( n = 22), and mixed bacterial–viral ( n = 38) etiology were analyzed for protein profiling. Whole-blood RNA samples from a subset of patients (bacterial, n = 8; viral, n = 8; and SARS-CoV-2, n = 8) were analyzed for transcriptional profiling. Lasso regression modeling identified a seven-protein signature (CRP, IL4, IL9, IP10, MIP1α, MIP1β, and TNFα) that discriminated between patients with bacterial ( n = 36) vs viral ( n = 27) infections with an area under the curve (AUC) of 0.98. When comparing patients with bacterial and mixed bacterial–viral infections (antibiotics clinically justified; n = 74) vs patients with viral and SARS-CoV-2 infections (antibiotics clinically not justified; n = 49), a 10-protein signature (CRP, bFGF, eotaxin, IFNγ, IL1β, IL7, IP10, MIP1α, MIP1β, and TNFα) with an AUC of 0.94 was identified. The transcriptional profiling analysis identified 232 differentially expressed genes distinguishing bacterial ( n = 8) from viral and SARS-CoV-2 ( n = 16) etiology. Protein–protein interaction enrichment analysis identified 20 genes that could be useful in the differentiation between bacterial and viral infections. Finally, we examined the performance of selected published gene signatures for bacterial–viral differentiation in our gene set, yielding promising results. Further validation of both protein and gene signatures in diverse clinical settings is warranted to establish their potential to guide the treatment of acute LRTIs. IMPORTANCE Accurate differentiation between bacterial and viral lower respiratory tract infections (LRTIs) is vital for effective patient care and resource allocation. This study investigated specific protein signatures and gene expression patterns in plasma and blood samples from LRTI patients that distinguished bacterial and viral infections. The identified signatures can inform the design of point-of-care tests that can aid healthcare providers in making informed decisions about antibiotic prescriptions in order to reduce unnecessary use, thereby contributing to reduced side effects and antibiotic resistance. Furthermore, the potential for faster and more accurate diagnoses for improved patient management in acute LRTIs is compelling.

IntroductionTherapeutic vaccination in tuberculosis (TB) represents a Host Directed Therapy strategy which enhances immune responses in order to improve clinical outcomes and shorten TB treatment. Previously, we have shown that the subunit H56:IC31 vaccine induced both humoral and cellular immune responses when administered to TB patients adjunctive to standard TB treatment (TBCOX2 study, NCT02503839). Here we present the longitudinal whole blood gene expression patterns in H56:IC31 vaccinated TB patients compared to controls receiving standard TB treatment only.MethodsThe H56:IC31 group (N=11) and Control group (N=7) underwent first-line TB treatment for 182 days. The H56:IC31 group received 5 micrograms of the H56:IC31 vaccine (Statens Serum Institut; SSI, Valneva Austria GmbH) intramuscularly at day 84 and day 140. Total RNA was extracted from whole blood samples collected in PAXgene tubes on days 0, 84, 98, 140, 154, 182 and 238. The expression level of 183 immune-related genes was measured by high-throughput microfluidic qPCR (Biomark HD system, Standard BioTools).ResultsThe targeted gene expression profiling unveiled the upregulation of modules such as interferon (IFN) signalling genes, pattern recognition receptors and small nucleotide guanosine triphosphate (GTP)-ases in the vaccinated group compared to controls two weeks after administration of the first H56:IC31 vaccine. Additionally, the longitudinal analysis of the Adolescent Cohort Study-Correlation of Risk (ACS-COR) signature showed a progressive downregulation in both study arms towards the end of TB treatment, in congruence with reported treatment responses and clinical improvements. Still, two months after the end of TB treatment, vaccinated patients, and especially those developing both cellular and humoral vaccine responses, showed a lower expression of the ACS-COR genes compared to controls.DiscussionOur data report gene expression patterns following H56:IC31 vaccination which might be interpreted as a lower risk of relapse in therapeutically vaccinated patients. Further studies are needed to conclude if these gene expression patterns could be used as prognostic biosignatures for therapeutic TB vaccine responses.

Abstract Background Antimicrobial resistance (AMR) is a global health threat with millions of deaths annually attributable to bacterial resistance. Effective antimicrobial stewardship programs are crucial for optimizing antibiotic use. This study aims to identify factors contributing to deviations from antibiotic treatment guidelines in hospitalized adults with suspected community-acquired pneumonia (CAP). Methods We conducted a prospective study at Haukeland University Hospital's Emergency Department in Bergen, Norway, from September 2020 to April 2023. Patients were selected from two cohorts, with data on clinical and microbiologic test results collected. We analysed adherence of antibiotic therapy to guidelines for the choice of empirical treatment and therapy duration using multivariate regression models to identify predictors of non-adherence. Results Of the 523 patients studied, 479 (91.6%) received empirical antibiotic therapy within 48 h of admission, with 382 (79.7%) adhering to guidelines. However, among the 341 patients included in the analysis of treatment duration adherence, only 69 (20.2%) received therapy durations that were consistent with guideline recommendations. Key predictors of longer-than-recommended therapy duration included a C-reactive protein (CRP) level exceeding 100 mg/L (RR 1.37, 95% CI 1.18–1.59) and a hospital stay longer than two days (RR 1.22, 95% CI 1.04–1.43). The primary factor contributing to extended antibiotic therapy duration was planned post-discharge treatment. No significant temporal trends in adherence to treatment duration guidelines were observed following the publication of the updated guidelines. Conclusion While adherence to guidelines for the choice of empirical antibiotic therapy was relatively high, adherence to guidelines for therapy duration was significantly lower, largely due to extended post-discharge antibiotic treatment. Our findings suggest that publishing updated guidelines alone is insufficient to change clinical practice. Targeted stewardship interventions, particularly those addressing discharge practices, are essential. Future research should compare adherence rates across institutions to identify factors contributing to higher adherence and develop standardized benchmarks for optimal antibiotic stewardship. Trial registration NCT04660084.

Abstract Background Gut microbiota alterations have been reported in hospitalized COVID-19 patients, with reduced alpha diversity and altered microbiota composition related to respiratory failure. However, data regarding gut microbiota and mortality are scarce. Methods Rectal swabs for gut microbiota analyses were collected within 48 h after hospital admission (baseline; n = 123) and three-month post-admission (n = 50) in a subset of patients included in the Norwegian SARS-CoV2 cohort study. Samples were analysed by sequencing the 16S rRNA gene. Gut microbiota diversity and composition at baseline were assessed in relation to need for intensive care unit (ICU) admission during hospitalization. The primary objective was to investigate whether the ICU-related gut microbiota was associated with 60-day mortality. Results Gut microbiota diversity (Shannon index) at baseline was lower in COVID-19 patients requiring ICU admission during hospitalization than in those managed in general wards. A dysbiosis index representing a balance of enriched and reduced taxa in ICU compared with ward patients, including decreased abundance of butyrate-producing microbes and enrichment of a partly oral bacterial flora, was associated with need of ICU admission independent of antibiotic use, dexamethasone use, chronic pulmonary disease, PO2/FiO2 ratio, C-reactive protein, neutrophil counts or creatinine levels (adjusted p < 0.001). The ICU-related dysbiosis index at baseline correlated with systemic inflammation and was associated with 60-day mortality in univariate analyses (Hazard ratio 3.70 [2.00–8.6], p < 0.001), as well as after separate adjustment for covariates. At the three-month follow-up, the dysbiosis index remained elevated in ICU patients compared with ward patients (adjusted p = 0.007). Conclusions Although our data should be regarded as exploratory due to low number of clinical end points, they suggest that gut microbiota alterations during hospitalization could be related to poor prognosis after severe COVID-19. Larger studies of gut involvement during COVID-19 in relation to long-term clinical outcome are warranted. Trial registration NCT04381819 . Retrospectively registered May 11, 2020.

This prospective study assessed the value of initial microscopy evaluation of sputum samples submitted for rapid syndromic PCR-based testing. Bacterial detections by the BioFire FilmArray Pneumonia Panel plus in 126 high- and 108 low-quality sputum samples, based on initial microscopy evaluation in samples from patients with lower respiratory tract infections were compared. We found that high-quality samples had a higher proportion of bacterial detections compared to low-quality samples (P = 0.013). This included a higher proportion of detections of bacteria deemed clinically relevant by predefined criteria (70% and 55%, P = 0.016), as well as a higher proportion of detections of Haemophilus influenzae (36% and 20%, P = 0.010). High-quality samples also had more detections of bacteria with high semi-quantitative values. The study found no significant difference between high- and low-quality samples in the proportions of samples with a single species of bacteria detected, samples with a bacteria treated by the clinician, samples with detection of a proven etiology of community-acquired pneumonia by predefined criteria, the number of bacterial species detected, or the detection of Streptococcus pneumoniae, Moraxella catarrhalis, or Staphylococcus aureus. The results showed that 40% (95% CI 35%-47%) of the bacterial detections would have been missed if only high-quality samples were analyzed. This included 41% (27%-56%) of detections of S. pneumoniae, 33% (23%-45%) of detections of H. influenzae, 42% (28%-58%) of detections of S. aureus, and 37% (23%-54%) of detections of M. catarrhalis. These findings suggest that all sputum samples submitted for rapid syndromic PCR testing should be analyzed, regardless of initial microscopy quality assessment. (This study has been registered at ClinicalTrials.gov under registration no. NCT04660084.) IMPORTANCE Microscopic quality assessment of sputum samples was originally designed for sputum culture, and its applicability in today's workflow, which includes syndromic PCR testing, may differ. Addressing this crucial gap, our study emphasizes the need to optimize the use and workflow of syndromic PCR panels, like the BioFire FilmArray Pneumonia plus (FAP plus), in microbiology laboratories. These advanced PCR-based tests offer rapid and comprehensive pathogen detection for respiratory infections, yet their full potential remains uncertain. By comparing bacterial detections in high- and low-quality sputum samples, we underscore the importance of including low-quality samples in testing. Our findings reveal a significant proportion of potentially clinically relevant bacterial detections that would have been missed if only high-quality samples were analyzed. These insights support the efficient implementation of syndromic PCR panels, ultimately enhancing patient care and outcomes.

A large proportion of the global tuberculosis (TB) burden is asymptomatic and not detectable by symptom-based screening, driving the TB epidemic through continued M. tuberculosis transmission. Currently, no validated tools exist to diagnose incipient and subclinical TB. Nested within a large prospective study in household contacts of pulmonary TB cases in Southern India, we assessed 35 incipient TB and 12 subclinical TB cases, along with corresponding household active TB cases (n=11), and household controls (n=39) using high throughput methods for transcriptional and protein profiling. We split the data into training and test sets and applied a support vector machine classifier followed by a Lasso regression model to identify signatures. The Lasso regression model identified an 11-gene signature (ABLIM2, C20orf197, CTC-543D15.3, CTD-2503O16.3, HLADRB3, METRNL, RAB11B-AS1, RP4-614C10.2, RNA5SP345, RSU1P1, and UACA) that distinguished subclinical TB from incipient TB with a very good discriminatory power by AUCs in both training and test sets. Further, we identified an 8-protein signature comprising b-FGF, IFNγ, IL1RA, IL7, IL12p70, IL13, PDGF-BB, and VEGF that differentiated subclinical TB from incipient TB with good and moderate discriminatory power by AUCs in the training and test sets, respectively. The identified 11-gene signature discriminated well between the distinct stages of the TB disease spectrum, with very good discriminatory power, suggesting it could be useful for predicting TB progression in household contacts. However, the high discriminatory power could partly be due to over-fitting, and validation in other studies is warranted to confirm the potential of the immune biosignatures for identifying subclinical TB.

BACKGROUND: Current approaches for pathogen identification in community-acquired pneumonia (CAP) remain suboptimal, leaving most patients without a microbiological diagnosis. If better diagnostic tools were available for differentiating between viral and bacterial CAP. unnecessary antibacterial therapy could be avoided in viral CAP patients. METHODS: In 156 adults hospitalized with CAP classified to have bacterial. viral, or mixed viral-bacterial infection based on microbiological testing or both microbiological testing and procalcitonin (PCT) levels, we aimed to identify discriminatory host transcriptional signatures in peripheral blood samples acquired at hospital admission, by applying Dual-color-Reverse-Transcriptase-Multiplex-Ligation-dependent-Probe-Amplification (dc-RT MLPA). RESULTS: In patients classified by microbiological testing, a 9-transcript signature showed high accuracy for discriminating bacterial from viral CAP (AUC 0.91. 95% CI 0.85-0.96). while a 10-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.91, 95% CI 0.86-0.96). In patients classified by both microbiological testing and PCT levels, a 13-transcript signature showed excellent accuracy for discriminating bacterial from viral CAP (AUC 1.00, 95% CI 1.00-1.00), while a 7-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.93, 95% CI 0.87-0.98). CONCLUSION: Our findings support host transcriptional signatures in peripheral blood samples as a potential tool for guiding clinical decision-making and antibiotic stewardship in CAP.

Delays in diagnosis and treatment of pulmonary tuberculosis (TB) can lead to more severe disease and increased transmission. Contact investigation among household contacts (HHCs) of TB patients is crucial to ensure optimal outcomes. In the context of a prospective cohort study in Palamaner, Southern India, this study attempted to assess the potential of 27 different soluble immune markers to accurately assign HHCs for appropriate treatment. A multiplex bead assay was applied on QuantiFERON (QFT)-nil supernatants collected from 89 HHCs grouped by longitudinal QFT status; M. tuberculosis (Mtb) infected (QFT positive at baseline and follow-up, n = 30), recent QFT converters (QFT-negative at baseline, n = 27) and converted to QFT-positivity within 6 months of exposure (at follow-up, n = 24) and QFT consistent negatives (n = 32). The 29 TB index cases represented Active TB. Active TB cases and HHCs with Mtb infection produced significantly different levels of both pro-inflammatory (IFNγ, IL17, IL8, IP10, MIP-1α, MIP1β, and VEGF) and anti-inflammatory (IL9 and IL1RA) cytokines. We identified a 4-protein signature (bFGF, IFNγ, IL9, and IP10) that correctly classified HHCs with Mtb infection vs. Active TB with a specificity of 92.6%, suggesting that this 4-protein signature has the potential to assign HHCs for either full-length TB treatment or preventive TB treatment. We further identified a 4-protein signature (bFGF, GCSF, IFNγ, and IL1RA) that differentiated HHCs with Mtb infection from QFT consistent negatives with a specificity of 62.5%, but not satisfactory to safely assign HHCs to no preventive TB treatment. QFT conversion, reflecting new Mtb infection, induced an elevated median concentration in nearly two-thirds (19/27) of the analyzed soluble markers compared to the levels measured at baseline. Validation in other studies is warranted in order to establish the potential of the immune biosignatures for optimized TB case detection and assignment to therapeutic and preventive treatment of Mtb infected individuals.

Host-directed-therapy strategies are warranted to fight tuberculosis. Here we assess the safety and immunogenicity of adjunctive vaccination with the H56:IC31 candidate and cyclooxygenase-2-inhibitor treatment (etoricoxib) in pulmonary and extra-pulmonary tuberculosis patients in a randomized open-label phase I/II clinical trial (TBCOX2, NCT02503839). A total of 222 patients were screened, 51 enrolled and randomized; 13 in the etoricoxib-group, 14 in the H56:IC31-group, 12 in the etoricoxib+H56:IC31-group and 12 controls. Three Serious Adverse Events were reported in the etoricoxib-groups; two urticarial rash and one possible disease progression, no Serious Adverse Events were vaccine related. H56:IC31 induces robust expansion of antigen-specific T-cells analyzed by fluorospot and flow cytometry, and higher proportion of seroconversions. Etoricoxib reduced H56:IC31-induced T-cell responses. Here, we show the first clinical data that H56:IC31 vaccination is safe and immunogenic in tuberculosis patients, supporting further studies of H56:IC31 as a host-directed-therapy strategy. Although etoricoxib appears safe, our data do not support therapy with adjunctive cyclooxygenase-2-inhibitors.

To achieve the ambitious targets for tuberculosis (TB) prevention, care, and control stated by the End TB Strategy, new health care strategies, diagnostic tools are warranted. Host-derived biosignatures are explored for their TB diagnostic potential in accordance with the WHO target product profiles (TPPs) for point-of-care (POC) testing. We aimed to identify sputum-independent TB diagnostic signatures in newly diagnosed adult pulmonary-TB (PTB) patients recruited in the context of a prospective household contact cohort study conducted in Andhra Pradesh, India. Whole-blood mRNA samples from 158 subjects (PTB, n = 109; age-matched household controls, n = 49) were examined by dual-color Reverse-Transcriptase Multiplex Ligation-dependent Probe-Amplification (dcRT-MLPA) for the expression of 198 pre-defined genes and a Mesoscale discovery assay for the concentration of 18 cytokines/chemokines in TB-antigen stimulated QuantiFERON supernatants. To identify signatures, we applied a two-step approach; in the first step, univariate filtering was used to identify and shortlist potentially predictive biomarkers; this step may be seen as removing redundant biomarkers. In the second step, a logistic regression approach was used such that group membership (PTB vs. household controls) became the binary response in a Lasso regression model. We identified an 11-gene signature that distinguished PTB from household controls with AUCs of ≥0.98 (95% CIs: 0.94–1.00), and a 4-protein signature (IFNγ, GMCSF, IL7 and IL15) that differentiated PTB from household controls with AUCs of ≥0.87 (95% CIs: 0.75–1.00), in our discovery cohort. Subsequently, we evaluated the performance of the 11-gene signature in two external validation data sets viz, an independent cohort at the Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK (GSE107994 data set), and the Catalysis treatment response cohort (GSE89403 data set) from South Africa. The 11-gene signature validated and distinguished PTB from healthy and asymptomatic M. tuberculosis infected household controls in the GSE107994 data set, with an AUC of 0.95 (95% CI: 0.91–0.98) and 0.94 (95% CI: 0.89–0.98). More interestingly in the GSE89403 data set, the 11-gene signature distinguished PTB from household controls and patients with other lung diseases with an AUC of 0.93 (95% CI: 0.87–0.99) and 0.73 (95% CI: 0.56–0.89). These criteria meet the WHO TTP benchmarks for a non–sputum-based triage test for TB diagnosis. We suggest that further validation is required before clinical implementation of the 11-gene signature we have identified markers will be possible.

Background. Prognostic markers for disease severity and identification of therapeutic targets in COVID-19 are urgently needed. We have studied innate and adaptive immunity on protein and transcriptomic level in COVID-19 patients with different disease severity at admission and longitudinally during hospitalization. Methods. Peripheral blood mononuclear cells (PBMCs) were collected at three time points from 31 patients included in the Norwegian SARS-CoV-2 cohort study and analysed by flow cytometry and RNA sequencing. Patients were grouped as either mild/moderate (n = 14), severe (n = 11) or critical (n = 6) disease in accordance with WHO guidelines and compared with patients with SARS-CoV-2-negative bacterial sepsis (n = 5) and healthy controls (n = 10). Results. COVID-19 severity was characterized by decreased interleukin 7 receptor alpha chain (CD127) expression in naive CD4 and CD8 T cells. Activation (CD25 and HLA-DR) and exhaustion (PD-1) markers on T cells were increased compared with controls, but comparable between COVID-19 severity groups. Non-classical monocytes and monocytic HLA-DR expression decreased whereas monocytic PD-L1 and CD142 expression increased with COVID-19 severity. RNA sequencing exhibited increased plasma B-cell activity in critical COVID-19 and yet predominantly reduced transcripts related to immune response pathways compared with milder disease. Conclusion. Critical COVID-19 seems to be characterized by an immune profile of activated and exhausted T cells and monocytes. This immune phenotype may influence the capacity to mount an efficient T-cell immune response. Plasma B-cell activity and calprotectin were higher in critical COVID-19 while most transcripts related to immune functions were reduced, in particular affecting B cells. The potential of these cells as therapeutic targets in COVID-19 should be further explored.

Background: Several host inflammatory markers have been proposed as biomarkers for diagnosis and treatment response in Tuberculosis (TB), but few studies compare their utility in different demographic, ethnic, and TB endemic settings. Methods: Fifty-four host biomarkers were evaluated in plasma samples obtained from presumed TB cases recruited at the Oslo University Hospital in Norway, and a health center in Cape Town, South Africa. Based on clinical and laboratory assessments, participants were classified as having TB or other respiratory diseases (ORD). The concentrations of biomarkers were analyzed using the Luminex multiplex platform. Results: Out of 185 study participants from both study sites, 107 (58%) had TB, and 78 (42%) ORD. Multiple host markers showed diagnostic potential in both the Norwegian and South African cohorts, with I-309 as the most accurate single marker irrespective of geographical setting. Although study site-specific biosignatures had high accuracy for TB, a site-independent 5-marker biosignature (G-CSF, C3b/iC3b, procalcitonin, IP-10, PDGF-BB) was identified diagnosing TB with a sensitivity of 72.7% (95% CI, 49.8–82.3) and specificity of 90.5% (95% CI, 69.6–98.8) irrespective of geographical site. Conclusion: A 5-marker host plasma biosignature has diagnostic potential for TB disease irrespective of TB setting and should be further explored in larger cohorts.