Biological heterogeneity in host inflammatory responses to severe pneumonia predicts clinical outcomes and may influence the effectiveness of immunomodulatory therapy. The upstream drivers of this heterogeneity remain poorly defined. We hypothesized that microbial translocation from the lungs to the bloodstream, detectable via multi-compartment metagenomic analysis, contributes to divergent host responses in pneumonia. In this nested case–control study of mechanically ventilated patients with severe pneumonia, we collected paired plasma and endotracheal aspirate samples at baseline. Plasma samples underwent microbial cell-free DNA (mcfDNA) sequencing, and endotracheal aspirates were analyzed by Nanopore metagenomic sequencing. Host-response biomarkers were measured in both plasma and endotracheal aspirate samples. Microbial translocation of pulmonary origin was defined by the genus-level concordance of detectable taxa between matched endotracheal aspirate and plasma samples. Among 98 patients (76 pneumonia, 22 controls), plasma mcfDNA was markedly higher in microbiologically confirmed pneumonia compared with culture-negative pneumonia (median 4015 vs. 210 molecules/μL, p = 0.0006). Pulmonary microbial translocation was identified in 31 (41

OBJECTIVES:Soluble ST2 (sST2), a decoy receptor for the alarmin interleukin-33 (IL-33), has been implicated in adverse clinical outcomes in acute respiratory failure (ARF). We evaluated sST2 distribution across diverse cohorts of patients with different etiologies of ARF, compared plasma and lower respiratory tract (LRT) concentrations, and examined associations with individual organ dysfunction, biological subphenotypes, and outcomes. DESIGN:Observational study. SETTING:Multicenter cohorts of ARF patients. PATIENTS:A total of 1432 ARF patients, including 863 non-COVID and 569 COVID-19 cases, from five cohorts. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:sST2 levels were measured in plasma and LRT specimens (when available) and analyzed for associations with ARF etiology, severity, organ dysfunction, systemic host response, subphenotypes, and 30-day mortality. Plasma sST2 levels were higher in non-COVID ARF patients compared with COVID-19 patients ( p < 0.05) and were markedly elevated compared with LRT levels (> 19-fold), with weak intercompartmental correlation. Elevated plasma sST2 levels were associated with extrapulmonary organ dysfunction and a hyperinflammatory ARF subphenotype but not with respiratory indices, including hypoxemia. Plasma sST2 independently predicted 30-day mortality in pooled cohort data, adjusted for age, sex, and illness severity. In longitudinal measurements, nonsurvivors had persistently elevated plasma sST2 levels in the first 2 weeks of critical illness compared with survivors. CONCLUSIONS:Plasma sST2 levels independently predict outcomes in ARF and are strongly associated with extrapulmonary organ dysfunction. The weak correlation between plasma and LRT sST2 levels suggests a predominantly systemic source. These findings highlight the potential of the IL-33/ST2 axis as a therapeutic target and warrant further investigation into its role in multiple organ dysfunction in ARF.

Background: Pulmonary complications in people living with HIV (PWH) have shifted away from infectious disease and towards chronic disease. HIV is an independent risk factor for chronic obstructive pulmonary disease (COPD), with PWH developing COPD younger and declining faster in pulmonary function. As an accelerated decline is associated with greater mortality, there is a need to identify individuals at high risk of longitudinal decline. Setting: 59 adults with HIV enrolled from the Pittsburgh Lung HIV study cohort. Methods: Targeted metabolite profiling was performed on baseline bronchoalveolar lavage fluid (BALF, n=35) and serum samples (n=54) using liquid chromatography-high resolution mass spectrometry. Longitudinal pulmonary function tests (median 3 measurements over 2.95 years with a follow-up interval of 1.34 years) were used to determine rates of decline. Predictive modeling and feature selection algorithms identified baseline clinical and metabolomic factors associated with longitudinal decline across forced expiratory volume, forced vital capacity, and diffusing capacity of the lung. Results: Predictive models found the BALF metabolome to successfully predict outcomes more consistently than serum. Key BALF metabolites such as elevated carnitine and reduced pyruvate predicted greater risk of longitudinal decline. Low serum citrate levels were a robust predictor of decline across multiple tests. Probabilistic graphical models supported direct relationships between these metabolites and lung function decline. Conclusion: Baseline metabolomic profiling, especially using BALF, can help identify PWH at risk for accelerated lung function decline. Key metabolic pathways related to glucose oxidation, fatty acid metabolism, and amino acid metabolism underlie observed lung function changes.

Long COVID presents a significant public health challenge, complicating diagnosis and treatment. In a prospective study of 349 individuals with long COVID (March 2021-December 2023), latent class analysis identified three symptom subphenotypes: high constitutional symptom burden (21%), predominant smell/taste disturbances (17%), and minimal persisting symptoms (62%). While viral persistence in saliva and stool was limited, 16S rRNA gene sequencing revealed microbiota associations with symptomatology. Alpha diversity was lower in individuals with high symptom burden, and specific taxa correlated with nausea and smell/taste disturbances. Distinct oral and gut microbiota patterns emerged across symptom clusters, with microbiota profiles also linked to patient-reported outcomes, including employment and overall health impact. These findings suggest that bacterial dysbiosis may contribute to long COVID symptom variability and highlight the microbiome's potential role in its pathophysiology. Understanding microbial influences on symptom persistence may inform microbiome-targeted therapeutic strategies and improve long COVID management.

Background: Diagnosing pulmonary complications (PCs) in hematologic malignancies remains challenging due to insensitive conventional microbiologic testing (CMT) and overlapping clinical manifestations of infectious and noninfectious pulmonary complications. For these reasons, empirical antimicrobials and immunosuppression (eg, corticosteroids) are used for prolonged periods. Research Question: How does metagenomic sequencing of the lower respiratory tract compare with conventional microbiologic testing among patients with hematologic malignancy? Study Design and Methods: Prospective proof-of-concept cohort study of 30 adult inpatients with hematologic malignancies and PCs who underwent bronchoscopy for suspected lower respiratory tract infection. Results: CMT identified a pathogen via culture- or polymerase chain reaction-based testing in 53% of patients. 16S sequencing demonstrated 66.7% positive and 42.9% negative concordance with CMT, while also identifying additional plausible respiratory pathogens in 59.3% of patients. Nanopore demonstrated 6.7% positive and 87.5% negative concordance with CMT and identified additional plausible respiratory pathogens in 42.3% of patients. Interpretation: Culture-independent sequencing approaches had modest agreement with CMT when considering bacterial PCs and showed poor detection of fungal pathogens. Sequencing frequently identified additional plausible respiratory pathogens, and further validation is needed to determine if such detection represents clinically missed infections or nonpathogenic colonization.

The human microbiome contributes to health and disease, but the oral microbiota is understudied relative to the gut microbiota. The salivary microbiota is easily accessible, underexplored, and may provide insight into response to infections. We sought to determine the composition, association with clinical features, and heterogeneity of the salivary microbiota in patients with acute lower respiratory tract infection (LRTI). We conducted a multicenter prospective cohort study of 147 adults with acute LRTI presenting to the emergency department of seven hospitals in three states (Pennsylvania, Michigan, and Ohio) between May 2017 and November 2018. Salivary samples were collected in the emergency department, at days 2-5 if hospitalized, and at day 30, as well as fecal samples if patients were willing. We compared salivary microbiota profiles from patients to those of healthy adult volunteers by sequencing and analyzing bacterial 16-rRNA. Compared to healthy volunteers, the salivary microbiota of patients with LRTI was highly distinct and strongly enriched with intestinal anaerobes such as Bacteroidaceae, Ruminococcaceae, and Lachnospiraceae (e.g., mean 10% relative abundance of Bacteroides vs < 1% in healthy volunteers). Within the LRTI population, COPD exacerbation was associated with altered salivary microbiota composition compared to other LRTI conditions. The largest determinant of microbiota variation within the LRTI population was geography (city in which the hospital was located).

Objective: The gut microbiome has been associated with visceral fat (VAT) in European and Asian populations; however, associations with VAT and with ectopic fats among African-ancestry individuals are not known. Our objective was to investigate cross-sectional associations of fecal microbiota diversity and composition with VAT and ectopic fat, as well as body mass index (BMI), among middle-aged and older African Caribbean men. Methods: We included in our analysis n = 193 men (mean age = 62.2 ± 7.6 years; mean BMI = 28.3 ± 4.9 kg/m2) from the Tobago Health Study. We assessed fecal microbiota using V4 16s rRNA gene sequencing. We evaluated multivariable-adjusted associations of microbiota features (alpha diversity, beta diversity, microbiota differential abundance) with BMI and with computed tomography-measured VAT and ectopic fats (pericardial and intermuscular fat; muscle and liver attenuation). Results: Lower alpha diversity was associated with higher VAT and BMI, and somewhat with higher pericardial and liver fat. VAT, BMI, and pericardial fat each explained similar levels of variance in beta diversity. Gram-negative Prevotellaceae and Negativicutes microbiota showed positive associations, while gram-positive Ruminococcaceae microbiota showed inverse associations, with ectopic fats. Conclusions: Fecal microbiota features associated with measures of general adiposity also extend to metabolically pernicious VAT and ectopic fat accumulation in older African-ancestry men.

Critical illness can significantly alter the composition and function of the human microbiome, but few studies have examined these changes over time. Here, we conduct a comprehensive analysis of the oral, lung, and gut microbiota in 479 mechanically ventilated patients (223 females, 256 males) with acute respiratory failure. We use advanced DNA sequencing technologies, including Illumina amplicon sequencing (utilizing 16S and ITS rRNA genes for bacteria and fungi, respectively, in all sample types) and Nanopore metagenomics for lung microbiota. Our results reveal a progressive dysbiosis in all three body compartments, characterized by a reduction in microbial diversity, a decrease in beneficial anaerobes, and an increase in pathogens. We find that clinical factors, such as chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, are associated with specific patterns of dysbiosis. Interestingly, unsupervised clustering of lung microbiota diversity and composition by 16S independently predicted survival and performed better than traditional clinical and host-response predictors. These observations are validated in two separate cohorts of COVID-19 patients, highlighting the potential of lung microbiota as valuable prognostic biomarkers in critical care. Understanding these microbiome changes during critical illness points to new opportunities for microbiota-targeted precision medicine interventions. Here, the authors profile the oral, lung, and gut microbiota of 479 patients with acute respiratory failure, revealing that reduced diversity and increased pathogen presence can predict survival outcomes, highlighting the potential for microbiota-based approaches in critical care.

Objective To characterise subphenotypes of self-reported symptoms and outcomes (SRSOs) in postacute sequelae of COVID-19 (PASC).Design Prospective, observational cohort study of subjects with PASC.Setting Academic tertiary centre from five clinical referral sources.Participants Adults with COVID-19 ≥20 days before enrolment and presence of any new self-reported symptoms following COVID-19.Exposures We collected data on clinical variables and SRSOs via structured telephone interviews and performed standardised assessments with validated clinical numerical scales to capture psychological symptoms, neurocognitive functioning and cardiopulmonary function. We collected saliva and stool samples for quantification of SARS-CoV-2 RNA via quantitative PCR.Outcomes measures Description of PASC SRSOs burden and duration, derivation of distinct PASC subphenotypes via latent class analysis (LCA) and relationship with viral load.Results We analysed baseline data for 214 individuals with a study visit at a median of 197.5 days after COVID-19 diagnosis. Participants reported ever having a median of 9/16 symptoms (IQR 6–11) after acute COVID-19, with muscle-aches, dyspnoea and headache being the most common. Fatigue, cognitive impairment and dyspnoea were experienced for a longer time. Participants had a lower burden of active symptoms (median 3 (1–6)) than those ever experienced (p<0.001). Unsupervised LCA of symptoms revealed three clinically active PASC subphenotypes: a high burden constitutional symptoms (21.9%), a persistent loss/change of smell and taste (20.6%) and a minimal residual symptoms subphenotype (57.5%). Subphenotype assignments were strongly associated with self-assessments of global health, recovery and PASC impact on employment (p<0.001) as well as referral source for enrolment. Viral persistence (5.6% saliva and 1% stool samples positive) did not explain SRSOs or subphenotypes.Conclusions We identified three distinct PASC subphenotypes. We highlight that although most symptoms progressively resolve, specific PASC subpopulations are impacted by either high burden of constitutional symptoms or persistent olfactory/gustatory dysfunction, requiring prospective identification and targeted preventive or therapeutic interventions.

Introduction Recently published studies support the beneficial effects of consuming fibre-rich legumes, such as cooked dry beans, to improve metabolic health and reduce cancer risk. In participants with overweight/obesity and a history of colorectal polyps, the Fibre-rich Foods to Treat Obesity and Prevent Colon Cancer randomised clinical trial will test whether a high-fibre diet featuring legumes will simultaneously facilitate weight reduction and suppress colonic mucosal biomarkers of colorectal cancer (CRC).Methods/design This study is designed to characterise changes in (1) body weight; (2) biomarkers of insulin resistance and systemic inflammation; (3) compositional and functional profiles of the faecal microbiome and metabolome; (4) mucosal biomarkers of CRC risk and (5) gut transit. Approximately 60 overweight or obese adults with a history of noncancerous adenomatous polyps within the previous 3 years will be recruited and randomised to one of two weight-loss diets. Following a 1-week run-in, participants in the intervention arm will receive preportioned high-fibre legume-rich entrées for two meals/day in months 1–3 and one meal/day in months 4–6. In the control arm, entrées will replace legumes with lean protein sources (eg, chicken). Both groups will receive in-person and written guidance to include nutritionally balanced sides with energy intake to lose 1–2 pounds per week.Ethics and dissemination The National Institutes of Health fund this ongoing 5-year study through a National Cancer Institute grant (5R01CA245063) awarded to Emory University with a subaward to the University of Pittsburgh. The study protocol was approved by the Emory Institutional Review Board (IRB approval number: 00000563).Trial registration number NCT04780477.

E-cigarette/vaping-associated lung injury (EVALI) is strongly associated with vitamin E acetate and often occurs with concomitant tetrahydrocannabinol (THC) use. To uncover pathways associated with EVALI, we examined cytokines, transcriptomic signatures, and lipidomic profiles in bronchoalveolar lavage fluid (BALF) from THC-EVALI patients. At a single center, we prospectively enrolled mechanically ventilated patients with EVALI from THC-containing products (N = 4) and patients with non-vaping acute lung injury and airway controls (N = 5). BALF samples were analyzed by Luminex multiplex assay, RNA sequencing, and mass spectrometry. After treating BEAS-2B lung epithelial cells with vaping and non-vaping BALF, LDH release was quantified. THC-EVALI BALF had significant increases in IFN gamma, CCL2, CXCL5, and MMP2 relative to non-vaping patients. RNA sequencing showed enrichment for biological oxidation, glucuronidation, and fatty acid metabolism pathways. Oleic acid and arachidonic acid metabolites were increased in THC-EVALI, as were oxidized phosphatidylethanolamines (PE) such as PE(38:4). THC-EVALI BALF induced more LDH release compared to BALF from non-vaping patients. Thus, THC-EVALI is characterized by altered phospholipid composition, accumulation of lipid oxidation products, and increased pro-inflammatory mediators that may contribute to epithelial cell death. These findings serve as a framework to study novel oxidized phospholipids implicated in the pathogenesis of EVALI.

Secondary infection (SI) diagnosis in severe COVID-19 remains challenging. We correlated metagenomic sequencing of plasma microbial cell-free DNA (mcfDNA-Seq) with clinical SI assessment, immune response, and outcomes. We classified 42 COVID-19 inpatients as microbiologically confirmed-SI (Micro-SI, n = 8), clinically diagnosed-SI (Clinical-SI, n = 13, i.e., empiric antimicrobials), or no-clinical-suspicion-for-SI (No-Suspected-SI, n = 21). McfDNA-Seq was successful in 73% of samples. McfDNA detection was higher in Micro-SI (94%) compared to Clinical-SI (57%, p = 0.03), and unexpectedly high in No-Suspected-SI (83%), similar to Micro-SI. We detected culture-concordant mcfDNA species in 81% of Micro-SI samples. McfDNA correlated with LRT 16S rRNA bacterial burden (r = 0.74, p = 0.02), and biomarkers (white blood cell count, IL-6, IL-8, SPD, all p < 0.05). McfDNA levels were predictive of worse 90-day survival (hazard ratio 1.30 [1.02-1.64] for each log(10) mcfDNA, p = 0.03). High mcfDNA levels in COVID-19 patients without clinical SI suspicion may suggest SI under-diagnosis. McfDNA-Seq offers a non-invasive diagnostic tool for pathogen identification, with prognostic value on clinical outcomes.

Introduction: Endothelial cell (EC) dysfunction is increasingly recognized as a precipitating event in Pulmonary hypertension (PH), a progressive, severe disease characterized by high blood pressure in the pulmonary circulation and excessive pulmonary vascular remodeling and inflammation. Microbiome-derived metabolites are altered in PH but their role in this disease remains poorly understood. Butyrate, a microbiome-derived short-chain fatty acid (SCFA) with biological activity, has been associated with benefit in cardiovascular diseases such as atherosclerosis. We aimed to test whether and how butyrate plays a protective role in PH. Results: PH-related inflammatory cytokine IL1β (10 ng/ml) increased expression of mesenchymal markers fibronectin, N-cadherin and transgelin (SM22) in human pulmonary arterial EC (HPAEC), consistent with induction of endothelial-to-mesenchymal transdifferentiation (EndMT). Butyrate (given as sodium butyrate, NaB; 2mM) attenuated this IL1β -induced upregulation (p<0.01, p<0.001, p<0.001 for each gene, respectively). Likewise, butyrate inhibited IL1β-induced upregulation of b-catenin (p<0.001), an important mediator of EndoMT. We previously showed that butyrate reversed IL1 β-induced downregulation of the PDZ protein EBP50, which we showed as a critical modulator of EndMT. In vivo, butyrate (NaB, 150mM) reversed PH phenotypes in wildtype mice (WT) following hypoxia exposure. In contrast, this reversal was attenuated in EBP50 heterozygous mice (Het, 50% EBP50 expression vs. WT) under hypoxia supplemented with butyrate. Similarly, butyrate reduced the number of circulating monocytes in hypoxia exposed WT but not Het mice. Conclusions: Collectively our results demonstrate that butyrate attenuates PH potentially via protecting against pulmonary vascular endothelial reprogramming and myeloid cell induction, through a mechanism that involves EBP50. These findings support the possible therapeutic benefits of butyrate in PH and shed mechanistic insight on the underlying cellular pathways propagating butyrate protection.

ABSTRACTRationaleDisruption of respiratory bacterial communities predicts poor clinical outcomes in critical illness; however, the role of respiratory fungal communities (mycobiome) is poorly understood.ObjectivesWe investigated whether mycobiota variation in the respiratory tract is associated with host-response and clinical outcomes in critically ill patients.MethodsTo characterize the upper and lower respiratory tract mycobiota, we performed rRNA gene sequencing (internal transcribed spacer) of oral swabs and endotracheal aspirates (ETA) from 316 mechanically-ventilated patients. We examined associations of mycobiome profiles (diversity and composition) with clinical variables, host-response biomarkers, and outcomes.Measurements and Main ResultsETA samples with >50% relative abundance forC. albicans(51%) were associated with elevated plasma IL-8 and pentraxin-3 (p=0.05), longer time-to-liberation from mechanical ventilation (p=0.04) and worse 30-day survival (adjusted hazards ratio (adjHR): 1.96 [1.04-3.81], p=0.05). Using unsupervised clustering, we derived two clusters in ETA samples, with Cluster 2 (39%) showing lower alpha diversity (p<0.001) and higher abundance ofC. albicans(p<0.001). Cluster 2 was significantly associated with the prognostically adverse hyperinflammatory subphenotype (odds ratio 2.07 [1.03-4.18], p=0.04) and predicted worse survival (adjHR: 1.81 [1.03-3.19], p=0.03).C. albicansabundance in oral swabs was also associated with the hyper-inflammatory subphenotype and mortality.ConclusionsVariation in respiratory mycobiota was significantly associated with systemic inflammation and clinical outcomes.C. albicansabundance emerged as a negative predictor in both the upper and lower respiratory tract. The lung mycobiome may play an important role in the biological and clinical heterogeneity among critically ill patients and represent a potential therapeutic target for lung injury in critical illness.

Critical illness can disrupt the composition and function of the microbiome, yet comprehensive longitudinal studies are lacking. We conducted a longitudinal analysis of oral, lung, and gut microbiota in a large cohort of 479 mechanically ventilated patients with acute respiratory failure. Progressive dysbiosis emerged in all three body compartments, characterized by reduced alpha diversity, depletion of obligate anaerobe bacteria, and pathogen enrichment. Clinical variables, including chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, shaped dysbiosis. Notably, of the three body compartments, unsupervised clusters of lung microbiota diversity and composition independently predicted survival, transcending clinical predictors, organ dysfunction severity, and host-response sub-phenotypes. These independent associations of lung microbiota may serve as valuable biomarkers for prognostication and treatment decisions in critically ill patients. Insights into the dynamics of the microbiome during critical illness highlight the potential for microbiota-targeted interventions in precision medicine.