Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation.

Acute graft-versus-host disease (aGvHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HSCT). We performed RNA analysis of 1408 candidate genes in bone marrow samples obtained from 167 patients undergoing HSCT. RNA expression data were used in a machine learning algorithm to predict the presence or absence of aGvHD using either random forest or extreme gradient boosting algorithms. Patients were randomly divided into training (2/3 of patients) and validation (1/3 of patients) sets. Using post-HSCT RNA data, the machine learning algorithm selected 92 genes for predicting aGvHD that appear to play a role in PI3/AKT, MAPK, and FOXO signaling, as well as microRNA. The algorithm selected 20 genes for predicting survival included genes involved in MAPK and chemokine signaling. Using pre-HSCT RNA data, the machine learning algorithm selected 400 genes and 700 genes predicting aGvHD and overall survival, but candidate signaling pathways could not be specified in this analysis. These data show that NGS analyses of RNA expression using machine learning algorithms may be useful biomarkers of aGvHD and overall survival for patients undergoing HSCT, allowing for the identification of major signaling pathways associated with HSCT outcomes and helping to dissect the complex steps involved in the development of aGvHD. The analysis of pre-HSCT bone marrow samples may lead to pre-HSCT interventions including choice of remission induction regimens and modifications in patient health before HSCT.

Systems immunology of transcriptional responses to viral infection identifies conserved antiviral pathways across macaques and humans.

Viral pandemics and epidemics pose a significant global threat. While macaque models of viral disease are routinely used, it remains unclear how conserved antiviral responses are between macaques and humans. Therefore, we conducted a cross-species analysis of transcriptomic data from over 6,088 blood samples from macaques and humans infected with one of 31 viruses. Our findings demonstrate that irrespective of primate or viral species, there are conserved antiviral responses that are consistent across infection phase (acute, chronic, or latent) and viral genome type (DNA or RNA viruses). Leveraging longitudinal data from experimental challenges, we identify virus-specific response kinetics such as host responses to Coronaviridae and Orthomyxoviridae infections peaking 1-3 days earlier than responses to Filoviridae and Arenaviridae viral infections. Our results underscore macaque studies as a powerful tool for understanding viral pathogenesis and immune responses that translate to humans, with implications for viral therapeutic development and pandemic preparedness.

Immune Checkpoint Inhibitors in "Special" NSCLC Populations: A Viable Approach?

Over the last decade, the therapeutic scenario for advanced non-small-cell lung cancer (NSCLC) has undergone a major paradigm shift. Immune checkpoint inhibitors (ICIs) have shown a meaningful clinical and survival improvement in different settings of the disease. However, the real benefit of this therapeutic approach remains controversial in selected NSCLC subsets, such as those of the elderly with active brain metastases or oncogene-addicted mutations. This is mainly due to the exclusion or underrepresentation of these patient subpopulations in most pivotal phase III studies; this precludes the generalization of ICI efficacy in this context. Moreover, no predictive biomarkers of ICI response exist that can help with patient selection for this therapeutic approach. Here, we critically summarize the current state of ICI efficacy in the most common "special" NSCLC subpopulations.

Ancestry-based differences in the immune phenotype are associated with lupus activity.

Systemic lupus erythematosus (SLE) affects 1 in 537 Black women, which is >2-fold more than White women. Black patients develop the disease at a younger age, have more severe symptoms, and have a greater chance of early mortality. We used a multiomics approach to uncover ancestry-associated immune alterations in patients with SLE and healthy controls that may contribute biologically to disease disparities. Cell composition, signaling, epigenetics, and proteomics were evaluated by mass cytometry; droplet-based single-cell transcriptomics and proteomics; and bead-based multiplex soluble mediator levels in plasma. We observed altered whole blood frequencies and enhanced activity in CD8+ T cells, B cells, monocytes, and DCs in Black patients with more active disease. Epigenetic modifications in CD8+ T cells (H3K27ac) could distinguish disease activity level in Black patients and differentiate Black from White patient samples. TLR3/4/7/8/9-related gene expression was elevated in immune cells from Black patients with SLE, and TLR7/8/9 and IFN-α phospho-signaling and cytokine responses were heightened even in immune cells from healthy Black control patients compared with White individuals. TLR stimulation of healthy immune cells recapitulated the ancestry-associated SLE immunophenotypes. This multiomic resource defines ancestry-associated immune phenotypes that differ between Black and White patients with SLE, which may influence the course and severity of SLE and other diseases.

Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors.

Current use of liquid biopsy is based on cell-free DNA (cfDNA) and the evaluation of mutations or methylation pattern. However, expressed RNA can capture mutations, changes in expression levels due to methylation, and provide information on cell of origin, growth, and proliferation status. We developed an approach to isolate cell-free total nucleic acid (cfDNA) and used targeted next generation sequencing to sequence cell-free RNA (cfRNA) and cfDNA as new approach in liquid biopsy. We demonstrate that cfRNA is overall more sensitive than cfDNA in detecting mutations. We show that cfRNA is reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. cfRNA levels of various solid tumor biomarkers were significantly higher (P < 0.0001) in samples from solid tumors as compared with normal control. Similarly, cfRNA lymphoid markers and cfRNA myeloid markers were all higher in lymphoid and myeloid neoplasms, respectively as compared with control (P < 0.0001). Using machine learning we demonstrate cfRNA was highly predictive of diagnosis (AUC >0.98) of solid tumors, B-cell lymphoid neoplasms, T-cell lymphoid neoplasms, and myeloid neoplasms. In evaluating the host immune system, cfRNA CD4:CD8B and CD3D:CD19 ratios in normal controls were as expected (median: 5.92 and 6.87, respectively) and were significantly lower in solid tumors (P < 0.0002). This data suggests that liquid biopsy combining analysis of cfRNA with cfDNA is practical and may provide helpful information in predicting genomic abnormalities, diagnosis of neoplasms and evaluating both the tumor biology and the host response.

Malaria-driven expansion of adaptive-like functional CD56-negative NK cells correlates with clinical immunity to malaria.

Natural killer (NK) cells likely play an important role in immunity to malaria, but the effect of repeated malaria on NK cell responses remains unclear. Here, we comprehensively profiled the NK cell response in a cohort of 264 Ugandan children. Repeated malaria exposure was associated with expansion of an atypical, CD56neg population of NK cells that differed transcriptionally, epigenetically, and phenotypically from CD56dim NK cells, including decreased expression of PLZF and the Fc receptor γ-chain, increased histone methylation, and increased protein expression of LAG-3, KIR, and LILRB1. CD56neg NK cells were highly functional and displayed greater antibody-dependent cellular cytotoxicity than CD56dim NK cells. Higher frequencies of CD56neg NK cells were associated with protection against symptomatic malaria and high parasite densities. After marked reductions in malaria transmission, frequencies of these cells rapidly declined, suggesting that continuous exposure to Plasmodium falciparum is required to maintain this modified, adaptive-like NK cell subset.

Inferring direction of associations between histone modifications using a neural processes-based framework.

Current technologies do not allow predicting interactions between histone post-translational modifications (HPTMs) at a system-level. We describe a computational framework, imputation-followed-by-inference, to predict directed association between two HPTMs using EpiTOF, a mass cytometry-based platform that allows profiling multiple HPTMs at a single-cell resolution. Using EpiTOF profiles of >55,000,000 peripheral mononuclear blood cells from 158 healthy human subjects, we show that neural processes (NP) have significantly higher accuracy than linear regression and k-nearest neighbors models to impute the abundance of an HPTM. Next, we infer the direction of association to show we recapitulate known HPTM associations and identify several previously unidentified ones in healthy individuals. Using this framework in an influenza vaccine cohort, we identify changes in associations between 6 pairs of HPTMs 30 days following vaccination, of which several have been shown to be involved in innate memory. These results demonstrate the utility of our framework in identifying directed interactions between HPTMs.

Characterising the autoantibody repertoire in systemic sclerosis following myeloablative haematopoietic stem cell transplantation.

OBJECTIVES: Results from the SCOT (Scleroderma: Cyclophosphamide Or Transplantation) clinical trial demonstrated significant benefits of haematopoietic stem cell transplant (HSCT) versus cyclophosphamide (CTX) in patients with systemic sclerosis. The objective of this study was to test the hypothesis that transplantation stabilises the autoantibody repertoire in patients with favourable clinical outcomes. METHODS: We used a bead-based array containing 221 protein antigens to profile serum IgG autoantibodies in participants of the SCOT trial. RESULTS: Comparison of autoantibody profiles at month 26 (n=23 HSCT; n=22 CTX) revealed antibodies against two viral antigens and six self-proteins (SSB/La, CX3CL1, glycyl-tRNA synthetase (EJ), parietal cell antigen, bactericidal permeability-increasing protein and epidermal growth factor receptor (EGFR)) that were significantly different between treatment groups. Linear mixed model analysis identified temporal increases in antibody levels for hepatitis B surface antigen, CCL3 and EGFR in HSCT-treated patients. Eight of 32 HSCT-treated participants and one of 31 CTX-treated participants had temporally varying serum antibody profiles for one or more of 14 antigens. Baseline autoantibody levels against 20 unique antigens, including 9 secreted proteins (interleukins, IL-18, IL-22, IL-23 and IL-27), interferon-α2A, stem cell factor, transforming growth factor-ß, macrophage colony-stimulating factor and macrophage migration inhibitory factor were significantly higher in patients who survived event-free to month 54. CONCLUSIONS: Our results suggest that HSCT favourably alters the autoantibody repertoire, which remains virtually unchanged in CTX-treated patients. Although antibodies recognising secreted proteins are generally thought to be pathogenic, our results suggest a subset could potentially modulate HSCT in scleroderma.

Mass-Cytometry-Based Quantification of Global Histone Post-Translational Modifications at Single-Cell Resolution Across Peripheral Immune Cells in IBD.

BACKGROUND AND AIMS: Current understanding of histone post-translational modifications [histone modifications] across immune cell types in patients with inflammatory bowel disease [IBD] during remission and flare is limited. The present study aimed to quantify histone modifications at a single-cell resolution in IBD patients during remission and flare and how they differ compared to healthy controls. METHODS: We performed a case-control study of 94 subjects [83 IBD patients and 11 healthy controls]. IBD patients had either ulcerative colitis [n = 38] or Crohn's disease [n = 45] in clinical remission or flare. We used epigenetic profiling by time-of-flight [EpiTOF] to investigate changes in histone modifications within peripheral blood mononuclear cells from IBD patients. RESULTS: We discovered substantial heterogeneity in histone modifications across multiple immune cell types in IBD patients. They had a higher proportion of less differentiated CD34+ haematopoietic progenitors, and a subset of CD56bright natural killer [NK] cells and γδ T cells characterized by distinct histone modifications associated with gene transcription. The subset of CD56bright NK cells had increases in several histone acetylations. An epigenetically defined subset of NK cells was associated with higher levels of C-reactive protein in peripheral blood. CD34+ monocytes from IBD patients had significantly decreased cleaved H3T22, suggesting they were epigenetically primed for macrophage differentiation. CONCLUSION: We describe the first systems-level quantification of histone modifications across immune cells from IBD patients at a single-cell resolution, revealing the increased epigenetic heterogeneity that is not possible with traditional ChIP-seq profiling. Our data open new directions in investigating the association between histone modifications and IBD pathology using other epigenomic tools.

Differential Diagnosis of Hematologic and Solid Tumors Using Targeted Transcriptome and Artificial Intelligence.

Diagnosis and classification of tumors is increasingly dependent on biomarkers. RNA expression profiling using next-generation sequencing provides reliable and reproducible information on the biology of cancer. This study investigated targeted transcriptome and artificial intelligence for differential diagnosis of hematologic and solid tumors. RNA samples from hematologic neoplasms (N = 2606), solid tumors (N = 2038), normal bone marrow (N = 782), and lymph node control (N = 24) were sequenced using next-generation sequencing using a targeted 1408-gene panel. Twenty subtypes of hematologic neoplasms and 24 subtypes of solid tumors were identified. Machine learning was used for diagnosis between two classes. Geometric mean naïve Bayesian classifier was used for differential diagnosis across 45 diagnostic entities with assigned rankings. Machine learning showed high accuracy in distinguishing between two diagnoses, with area under the curve varying between 1 and 0.841. Geometric mean naïve Bayesian algorithm was trained using 3045 samples and tested on 1415 samples, and showed correct first-choice diagnosis in 100%, 88%, 85%, 82%, 88%, 72%, and 72% of acute lymphoblastic leukemia, acute myeloid leukemia, diffuse large B-cell lymphoma, colorectal cancer, lung cancer, chronic lymphocytic leukemia, and follicular lymphoma cases, respectively. The data indicate that targeted transcriptome combined with artificial intelligence are highly useful for diagnosis and classification of various cancers. Mutation profiles and clinical information can improve these algorithms and minimize errors in diagnoses.

Effect of Lockdowns on Hospital Staff in a COVID Center: A Retrospective Observational Study.

At the onset of the SARS-CoV-2 pandemic, individual and social measures were strengthened through restrictive non-pharmaceutical interventions, labelled with the term "lockdown". In Italy, there were two lockdowns (9 March 2020−3 May 2020 and 3 November 2020−27 March 2021). As part of preventive measures, healthcare workers and the administrative staff population of Policlinico A. Gemelli underwent nasopharyngeal swab tests from 1 March 2020 to 9 February 2022, a long time interval that includes the two aforementioned lockdowns. The population included 8958 people from 1 March 2020 to 31 December 2020; 8981 people from 1 January 2021 to 31 December 2021; and 8981 people from 1 January 2022 to 9 February 2022. We then analysed pseudo-anonymized data, using a retrospective observational approach to evaluate the impact of the lockdown on the incidence of SARS-CoV-2 infections within the population. Given the 14 day contagious period, the swab positivity rate (SPR) among the staff decreased significantly at the end of the first lockdown, every day prior to 18 May 2020, by 0.093 (p < 0.0001, CI = (−0.138−−0.047)). After the fourteenth day post the end of the first lockdown (18 May 2020), the SPR increased daily at a rate of 0.024 (p < 0.0001, 95% CI = (0.013−0.034)). In addition, the SPR appeared to increase significantly every day prior to 17 November 2020 by 0.024 (p < 0.0001, CI = (0.013−0.034)). After the fourteenth day post the start of the second lockdown (17 November 2020), the SPR decreased daily at a rate of 0.039 (p < 0.0001, 95% CI = (−0.050−−0.027)). These data demonstrate that, in our Institution, the lockdowns helped to both protect healthcare workers and maintain adequate standards of care for COVID and non-COVID patients for the duration of the state of emergency in Italy.

Monitoring Somatic Genetic Alterations in Circulating Cell-Free DNA/RNA of Patients with "Oncogene-Addicted" Advanced Lung Adenocarcinoma: A Real-World Clinical Study.

Liquid biopsy has advantages over tissue biopsy, but also some technical limitations that hinder its wide use in clinical applications. In this study, we aimed to evaluate the usefulness of liquid biopsy for the clinical management of patients with advanced-stage oncogene-addicted non-small-cell lung adenocarcinomas. The investigation was conducted on a series of cases-641 plasma samples from 57 patients-collected in a prospective consecutive manner, which allowed us to assess the benefits and limitations of the approach in a real-world clinical context. Thirteen samples were collected at diagnosis, and the additional samples during the periodic follow-up visits. At diagnosis, we detected mutations in ctDNA in 10 of the 13 cases (77%). During follow-up, 36 patients progressed. In this subset of patients, molecular analyses of plasma DNA/RNA at progression revealed the appearance of mutations in 29 patients (80.6%). Mutations in ctDNA/RNA were typically detected an average of 80 days earlier than disease progression assessed by RECIST or clinical evaluations. Among the cases positive for mutations, we observed 13 de novo mutations, responsible for the development of resistance to therapy. This study allowed us to highlight the advantages and disadvantages of liquid biopsy, which led to suggesting algorithms for the use of liquid biopsy analyses at diagnosis and during monitoring of therapy response.

Rapid GPR183-mediated recruitment of eosinophils to the lung after Mycobacterium tuberculosis infection.

Influx of eosinophils into the lungs is typically associated with type II responses during allergy and fungal and parasitic infections. However, we previously reported that eosinophils accumulate in lung lesions during type I inflammatory responses to Mycobacterium tuberculosis (Mtb) in humans, macaques, and mice, in which they support host resistance. Here we show eosinophils migrate into the lungs of macaques and mice as early as one week after Mtb exposure. In mice this influx is CCR3 independent and instead requires cell-intrinsic expression of the oxysterol receptor GPR183, which is highly expressed on human and macaque eosinophils. Murine eosinophils interact directly with bacilli-laden alveolar macrophages, which upregulate the oxysterol-synthesizing enzyme Ch25h, and eosinophil recruitment is impaired in Ch25h-deficient mice. Our findings show that eosinophils are among the earliest cells from circulation to sense and respond to Mtb infection of alveolar macrophages and reveal a role for GPR183 in the migration of eosinophils into lung tissue.

An 8-gene machine learning model improves clinical prediction of severe dengue progression.

BACKGROUND: Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed. METHODS: We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD. RESULTS: We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression. CONCLUSIONS: The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

Sustained Hematopoietic Engraftment Potential after Prolonged Storage of Cryopreserved Hematopoietic Stem Cells Used in Salvage Autologous Stem Cell Transplantation.

Salvage autologous hematopoietic stem cell transplantation (HSCT) is an effective treatment for patients with relapsed multiple myeloma (MM). Peripheral blood stem cells (PBSCs), a source of hematopoietic stem cells (HSCs), are collected before the first transplantation, and adequate quantities of PBSCs can be collected and stored potentially for years to support at least 2 transplantations for eligible patients. To ensure the safety of salvage HSCT in the treatment of patients in subsequent relapse, PBSCs must retain the potential to engraft even after several years of cryopreservation. Although PBSC viability has been studied extensively using in vitro techniques, few publications describe the most rigorous functional potency measure, of patients receiving a myeloablative conditioning regimen. This study describes a large single-institution experience evaluating the engraftment kinetics of PBSCs used in salvage transplantation after multiple years of storage compared with first transplantation for the same patients in the treatment of MM. A retrospective chart review of patients with MM undergoing HSCT between 2000 and 2021 identified 89 patients who received salvage autologous PBSCs stored for >1 year after first HSCT. PBSCs were cryopreserved and stored in vapor-phase liquid nitrogen refrigerators at ≤-150°C. All patients received a PBSC product from the same collection cycle for both transplantations. Differences in CD34+ cell doses and days to engraftment between the first and salvage transplantations were tested using the paired 2-tailed t-test and Wilcoxon signed-rank test. Univariate and multivariable linear regressions were used to determine the association between storage time and days to engraftment, adjusting for CD34+ cell dose and conditioning regimen in the multivariable model. The median duration of storage between the day of initial collection and salvage transplant was 5.4 years (range, 1.0 to 19.7 years). Engraftment kinetics demonstrated a sustained neutrophil engraftment (absolute neutrophil count >0.5 × 109 cells/L) at a median of 11 days after both the first and salvage transplantations (range, 8 to 15 days and 8 to 19 days, respectively; P < .05). The median time to sustained platelet engraftment (>20 × 109 cells/L without transfusion support) was 13.5 days after the first HSCT and 14 days after salvage HSCT (range, 9 to 27 days and 10 to 56 days, respectively; P = .616). After adjusting for CD34+ cell doses and conditioning regimens, there was no association between the duration of cryopreservation and days to neutrophil engraftment (r = 0.178, P = .130) or platelet engraftment (r = 0.244, P = .100). Engraftment kinetics of the salvage HSCT are comparable to those of the first HSCT even when products are stored in vapor-phase nitrogen refrigerators for a median of 5.4 years. There is no association between the duration of storage and time to engraftment when controlling for CD34+ cell dose and conditioning regimen. Prolonged storage of cryopreserved HSC products is a safe practice for MM patients undergoing salvage autologous HSCT.

Cytokine signatures differentiate systemic sclerosis patients at high versus low risk for pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) affects approximately 10% of patients with systemic sclerosis (SSc) and is a leading cause of death. We sought to identify serum cytokine signatures that risk stratify SSc patients for this potentially fatal complication. METHODS: Subjects at high risk for PAH and with incident PAH based on right heart catheterization (RHC) were enrolled in the multi-center prospective registry, Pulmonary Hypertension Assessment and Recognition of Outcomes in Scleroderma (PHAROS). Low-risk SSc patients were enrolled at Stanford and had normal pulmonary function test and echocardiogram parameters. Serum was available from 71 high-risk patients, 81 incident PAH patients, 10 low-risk patients, and 20 healthy controls (HC). Custom 14- and 65-plex arrays were used for cytokine analysis. Cytokine expression was compared between patient groups by principal component analysis and Tukey's test result. A multiple hypotheses corrected p value <0.05 was considered significant. RESULTS: Exploratory analysis using principal components showed unique clustering for each patient group. There was a significant difference in cytokine expression in at least one group comparison for every cytokine. Overall, there was very little difference in cytokine expression comparing high-risk and PAH patient groups; however, these groups had substantially different cytokine profiles compared to low-risk patients and HC. CONCLUSION: These data suggest that cytokine profiles can distinguish SSc patients who are at high-risk for or have PAH from SSc patients who may be at lower risk for PAH and HC. However, high-risk and PAH patients had very similar cytokine profiles, suggesting that these patients are on a disease continuum.

The immunoregulatory landscape of human tuberculosis granulomas.

Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-ß, regulatory T cells and IDO1+ PD-L1+ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.

A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections.

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.

Macrophage-derived IL-6 trans-signalling as a novel target in the pathogenesis of bronchopulmonary dysplasia.

RATIONALE: Premature infants exposed to oxygen are at risk for bronchopulmonary dysplasia (BPD), which is characterised by lung growth arrest. Inflammation is important, but the mechanisms remain elusive. Here, we investigated inflammatory pathways and therapeutic targets in severe clinical and experimental BPD. METHODS AND RESULTS: First, transcriptomic analysis with in silico cellular deconvolution identified a lung-intrinsic M1-like-driven cytokine pattern in newborn mice after hyperoxia. These findings were confirmed by gene expression of macrophage-regulating chemokines (Ccl2, Ccl7, Cxcl5) and markers (Il6, Il17A, Mmp12). Secondly, hyperoxia-activated interleukin 6 (IL-6)/signal transducer and activator of transcription 3 (STAT3) signalling was measured in vivo and related to loss of alveolar epithelial type II cells (ATII) as well as increased mesenchymal marker. Il6 null mice exhibited preserved ATII survival, reduced myofibroblasts and improved elastic fibre assembly, thus enabling lung growth and protecting lung function. Pharmacological inhibition of global IL-6 signalling and IL-6 trans-signalling promoted alveolarisation and ATII survival after hyperoxia. Third, hyperoxia triggered M1-like polarisation, possibly via Krüppel-like factor 4; hyperoxia-conditioned medium of macrophages and IL-6-impaired ATII proliferation. Finally, clinical data demonstrated elevated macrophage-related plasma cytokines as potential biomarkers that identify infants receiving oxygen at increased risk of developing BPD. Moreover, macrophage-derived IL6 and active STAT3 were related to loss of epithelial cells in BPD lungs. CONCLUSION: We present a novel IL-6-mediated mechanism by which hyperoxia activates macrophages in immature lungs, impairs ATII homeostasis and disrupts elastic fibre formation, thereby inhibiting lung growth. The data provide evidence that IL-6 trans-signalling could offer an innovative pharmacological target to enable lung growth in severe neonatal chronic lung disease.