Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort.

BACKGROUND: Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster. METHODS: Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3. RESULTS: Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3. CONCLUSIONS: During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

Bacterial Adaptive Memory in Methicillin-Resistant Staphylococcus aureus from Endotracheal Tubes.

OBJECTIVES: To evaluate the expression dynamics of biofilm genes in methicillin-resistant Staphylococcus aureus (MRSA) retrieved from endotracheal tubes (ETT) and to determine how gene regulation is attenuated in vitro where host-environmental factors are no longer present. METHODS: Biofilm was grown (24 h) in tryptic broth soy plus 0.25% glucose for a clinical MRSA isolate in planktonic state and after sessile growth named ETT-MRSA (S2, S3, S4, S5, S6, S7). Gene expression of five biofilm-related genes (icaC, clfB, ebps, fnbB, and RNA III) was assessed consecutively from day 1 to day 4 after ETT growth through real-time PCR. 16S rRNA was used as a control. RESULTS: The MRSA isolates retrieved from ETT were capable of producing biofilms dependent on ica. The gene expression dynamics of ETT-MRSA changed progressively compared to planktonic MRSA gene expression under both ambient air (p < 0.001) and ambient air with 5% CO2 (p < 0.001). Dynamic assessment of icaC expression in both atmospheric conditions showed progressive downregulation in vitro compared to in vivo ETT biofilms. The expression patterns of clfB and ebps genes were similar to icaC. In contrast, the expression of the RNA III gene showed progressive upregulation from day 1 to day 4 (p < 0.001). CONCLUSIONS: MRSA loses its biofilm gene expression in vitro, by adaptive features across multiple generations, as evidenced by the progressive downregulation of icaC and upregulation of RNA III. These findings underscore the significance of host-environment dependence in regulating bacterial biofilm genes, highlighting its importance in diagnostics. Bacterial strains lose their host-specific characteristics as they are cultured in vitro.

The efficacy of telavancin in comparison with linezolid on endotracheal tube biofilm in pigs with methicillin-resistant Staphylococcus aureus pneumonia.

BACKGROUND: The effect of systemic treatment of ventilator-associated pneumonia (VAP) with telavancin, a semisynthetic lipoglycopeptide with good penetration in vitro biofilms, has not been tested in vivo during mechanical ventilation. This study examined the efficacy of telavancin compared with linezolid against endotracheal tube (ETT) biofilms in a porcine model of methicillin-resistant Staphylococcus aureus (MRSA) VAP. METHODS: VAP was induced in 18 pigs by instilling 107 colony-forming units (CFU/mL) of an MRSA strain susceptible to telavancin and linezolid into each pulmonary lobe. Randomization into three groups was done at pneumonia diagnosis: control (IV glucose 0.5% solution q24); linezolid (10 mg/kg q12) and telavancin groups (22.5 mg/kg q24). After 72 h of MV, data regarding bronchoalveolar lavage (BAL), tracheal aspirate (TA), ETT MRSA biofilm load and thickness measured by scanning electron microscopy were obtained. RESULTS: All 18 pigs completed the study. MRSA was isolated in 100% of ETTs from the control and linezolid groups and in 67% from the telavancin group. Telavancin treatment presented a lower MRSA load compared to the control and linezolid treatments (telavancin median [interquartile range (IQR)] = 1.94 [0.00-5.45], linezolid 3.99 [3.22-4.68] and control 4.93 [4.41-5.15], P = 0.236). Telavancin treatment also resulted in the lowest biofilm thickness according to the SEM (4.04 [2.09-6.00], P < 0.001). We found a positive correlation between ETT and BAL load (rho = 0.511, P = 0.045). CONCLUSIONS: In our VAP model, systemic telavancin treatment reduced ETT MRSA occurrence, load, and biofilm thickness. Our findings may have a bearing on ICU patients' clinical outcomes.

Brewpitopes: a pipeline to refine B-cell epitope predictions during public health emergencies.

The application of B-cell epitope identification to develop therapeutic antibodies and vaccine candidates is well established. However, the validation of epitopes is time-consuming and resource-intensive. To alleviate this, in recent years, multiple computational predictors have been developed in the immunoinformatics community. Brewpitopes is a pipeline that curates bioinformatic B-cell epitope predictions obtained by integrating different state-of-the-art tools. We used additional computational predictors to account for subcellular location, glycosylation status, and surface accessibility of the predicted epitopes. The implementation of these sets of rational filters optimizes in vivo antibody recognition properties of the candidate epitopes. To validate Brewpitopes, we performed a proteome-wide analysis of SARS-CoV-2 with a particular focus on S protein and its variants of concern. In the S protein, we obtained a fivefold enrichment in terms of predicted neutralization versus the epitopes identified by individual tools. We analyzed epitope landscape changes caused by mutations in the S protein of new viral variants that were linked to observed immune escape evidence in specific strains. In addition, we identified a set of epitopes with neutralizing potential in four SARS-CoV-2 proteins (R1AB, R1A, AP3A, and ORF9C). These epitopes and antigenic proteins are conserved targets for viral neutralization studies. In summary, Brewpitopes is a powerful pipeline that refines B-cell epitope bioinformatic predictions during public health emergencies in a high-throughput capacity to facilitate the optimization of experimental validation of therapeutic antibodies and candidate vaccines.

Procalcitonin and C-reactive protein to rule out early bacterial coinfection in COVID-19 critically ill patients.

PURPOSE: Although the prevalence of community-acquired respiratory bacterial coinfection upon hospital admission in patients with coronavirus disease 2019 (COVID-19) has been reported to be < 5%, almost three-quarters of patients received antibiotics. We aim to investigate whether procalcitonin (PCT) or C-reactive protein (CRP) upon admission could be helpful biomarkers to identify bacterial coinfection among patients with COVID-19 pneumonia. METHODS: We carried out a multicentre, observational cohort study including consecutive COVID-19 patients admitted to 55 Spanish intensive care units (ICUs). The primary outcome was to explore whether PCT or CRP serum levels upon hospital admission could predict bacterial coinfection among patients with COVID-19 pneumonia. The secondary outcome was the evaluation of their association with mortality. We also conducted subgroups analyses in higher risk profile populations. RESULTS: Between 5 February 2020 and 21 December 2021, 4076 patients were included, 133 (3%) of whom presented bacterial coinfection. PCT and CRP had low area under curve (AUC) scores at the receiver operating characteristic (ROC) curve analysis [0.57 (95% confidence interval (CI) 0.51-0.61) and 0.6 (95% CI, 0.55-0.64), respectively], but high negative predictive values (NPV) [97.5% (95% CI 96.5-98.5) and 98.2% (95% CI 97.5-98.9) for PCT and CRP, respectively]. CRP alone was associated with bacterial coinfection (OR 2, 95% CI 1.25-3.19; p = 0.004). The overall 15, 30 and 90 days mortality had a higher trend in the bacterial coinfection group, but without significant difference. PCT ≥ 0.12 ng/mL was associated with higher 90 days mortality. CONCLUSION: Our study suggests that measurements of PCT and CRP, alone and at a single time point, are not useful for ruling in or out bacterial coinfection in viral pneumonia by COVID-19.

A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study.

BACKGROUND: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. METHODS: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. RESULTS: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. CONCLUSIONS: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.

A long-lasting porcine model of ARDS caused by pneumonia and ventilator-induced lung injury.

BACKGROUND: Animal models of acute respiratory distress syndrome (ARDS) do not completely resemble human ARDS, struggling translational research. We aimed to characterize a porcine model of ARDS induced by pneumonia-the most common risk factor in humans-and analyze the additional effect of ventilator-induced lung injury (VILI). METHODS: Bronchoscopy-guided instillation of a multidrug-resistant Pseudomonas aeruginosa strain was performed in ten healthy pigs. In six animals (pneumonia-with-VILI group), pulmonary damage was further increased by VILI applied 3 h before instillation and until ARDS was diagnosed by PaO2/FiO2 < 150 mmHg. Four animals (pneumonia-without-VILI group) were protectively ventilated 3 h before inoculum and thereafter. Gas exchange, respiratory mechanics, hemodynamics, microbiological studies and inflammatory markers were analyzed during the 96-h experiment. During necropsy, lobar samples were also analyzed. RESULTS: All animals from pneumonia-with-VILI group reached Berlin criteria for ARDS diagnosis until the end of experiment. The mean duration under ARDS diagnosis was 46.8 ± 7.7 h; the lowest PaO2/FiO2 was 83 ± 5.45 mmHg. The group of pigs that were not subjected to VILI did not meet ARDS criteria, even when presenting with bilateral pneumonia. Animals developing ARDS presented hemodynamic instability as well as severe hypercapnia despite high-minute ventilation. Unlike the pneumonia-without-VILI group, the ARDS animals presented lower static compliance (p = 0.011) and increased pulmonary permeability (p = 0.013). The highest burden of P. aeruginosa was found at pneumonia diagnosis in all animals, as well as a high inflammatory response shown by a release of interleukin (IL)-6 and IL-8. At histological examination, only animals comprising the pneumonia-with-VILI group presented signs consistent with diffuse alveolar damage. CONCLUSIONS: In conclusion, we established an accurate pulmonary sepsis-induced ARDS model.

The value of biofilm testing to guide antimicrobial stewardship in chronic respiratory diseases.

Introduction: Biofilm production is an important yet currently overlooked aspect of diagnostic microbiology that has implications for antimicrobial stewardship. In this study, we aimed to validate and identify additional applications of the BioFilm Ring Test® (BRT) for Pseudomonas aeruginosa (PA) isolates from patients with bronchiectasis (BE). Materials and methods: Sputa were collected from BE patients who had at least one PA positive culture in the previous year. We processed the sputa to isolate both mucoid and non-mucoid PA, and determined their susceptibility pattern, mucA gene status, and presence of ciprofloxacin mutations in QRDR genes. The Biofilm production index (BPI) was obtained at 5 and 24 hours. Biofilms were imaged using Gram staining. Results: We collected 69 PA isolates, including 33 mucoid and 36 non-mucoid. A BPI value below 14.75 at 5 hours predicted the mucoid PA phenotype with 64% sensitivity and 72% specificity. Conclusion: Overall, our findings suggest that the fitness-cost associated with the mucoid phenotype or ciprofloxacin resistance is shown through a time-dependent BPI profile. The BRT has the potential to reveal biofilm features with clinical implications.

Interferon gamma-1b for the prevention of hospital-acquired pneumonia in critically ill patients: a phase 2, placebo-controlled randomized clinical trial.

PURPOSE: We aimed to determine whether interferon gamma-1b prevents hospital-acquired pneumonia in mechanically ventilated patients. METHODS: In a multicenter, placebo-controlled, randomized trial conducted in 11 European hospitals, we randomly assigned critically ill adults, with one or more acute organ failures, under mechanical ventilation to receive interferon gamma-1b (100 µg every 48 h from day 1 to 9) or placebo (following the same regimen). The primary outcome was a composite of hospital-acquired pneumonia or all-cause mortality on day 28. The planned sample size was 200 with interim safety analyses after enrolling 50 and 100 patients. RESULTS: The study was discontinued after the second safety analysis for potential harm with interferon gamma-1b, and the follow-up was completed in June 2022. Among 109 randomized patients (median age, 57 (41-66) years; 37 (33.9%) women; all included in France), 108 (99%) completed the trial. Twenty-eight days after inclusion, 26 of 55 participants (47.3%) in the interferon-gamma group and 16 of 53 (30.2%) in the placebo group had hospital-acquired pneumonia or died (adjusted hazard ratio (HR) 1.76, 95% confidence interval (CI) 0.94-3.29; P = 0.08). Serious adverse events were reported in 24 of 55 participants (43.6%) in the interferon-gamma group and 17 of 54 (31.5%) in the placebo group (P = 0.19). In an exploratory analysis, we found that hospital-acquired pneumonia developed in a subgroup of patients with decreased CCL17 response to interferon-gamma treatment. CONCLUSIONS: Among mechanically ventilated patients with acute organ failure, treatment with interferon gamma-1b compared with placebo did not significantly reduce the incidence of hospital-acquired pneumonia or death on day 28. Furthermore, the trial was discontinued early due to safety concerns about interferon gamma-1b treatment.

Determining the most accurate 16S rRNA hypervariable region for taxonomic identification from respiratory samples.

16S rRNA gene profiling, which contains nine hypervariable regions (V1-V9), is the gold standard for identifying taxonomic units by high-throughput sequencing. Microbiome studies combine two or more region sequences (usually V3-V4) to increase the resolving power for identifying bacterial taxa. We compare the resolving powers of V1-V2, V3-V4, V5-V7, and V7-V9 to improve microbiome analyses in sputum samples from patients with chronic respiratory diseases. DNA were isolated from 33 human sputum samples, and libraries were created using a QIASeq screening panel intended for Illumina platforms (16S/ITS; Qiagen Hilden, Germany). The analysis included a mock community as a microbial standard control (ZymoBIOMICS). We used the Deblur algorithm to identify bacterial amplicon sequence variants (ASVs) at the genus level. Alpha diversity was significantly higher for V1-V2, V3-V4, and V5-V7 compared with V7-V9, and significant compositional dissimilarities in the V1-V2 and V7-V9 analyses versus the V3-V4 and V5-V7 analyses. A cladogram confirmed these compositional differences, with the latter two being very similar in composition. The combined hypervariable regions showed significant differences when discriminating between the relative abundances of bacterial genera. The area under the curve revealed that V1-V2 had the highest resolving power for accurately identifying respiratory bacterial taxa from sputum samples. Our study confirms that 16S rRNA hypervariable regions provide significant differences for taxonomic identification in sputum. Comparing the taxa of microbial community standard control with the taxa samples, V1-V2 combination exhibits the most sensitivity and specificity. Thus, while third generation full-length 16S rRNA sequencing platforms become more available, the V1-V2 hypervariable regions can be used for taxonomic identification in sputum.

Inhaled amikacin for pneumonia treatment and dissemination prevention: an experimental model of severe monolateral Pseudomonas aeruginosa pneumonia.

BACKGROUND: Pseudomonas aeruginosa pneumonia is commonly treated with systemic antibiotics to ensure adequate treatment of multidrug resistant (MDR) bacteria. However, intravenous (IV) antibiotics often achieve suboptimal pulmonary concentrations. We therefore aimed to evaluate the effect of inhaled amikacin (AMK) plus IV meropenem (MEM) on bactericidal efficacy in a swine model of monolateral MDR P. aeruginosa pneumonia. METHODS: We ventilated 18 pigs with monolateral MDR P. aeruginosa pneumonia for up to 102 h. At 24 h after the bacterial challenge, the animals were randomized to receive 72 h of treatment with either inhaled saline (control), IV MEM only, or IV-MEM plus inhaled AMK (MEM + AMK). We dosed IV MEM at 25 mg/kg every 8 h and inhaled AMK at 400 mg every 12 h. The primary outcomes were the P. aeruginosa burden and histopathological injury in lung tissue. Secondary outcomes included the P. aeruginosa burden in tracheal secretions and bronchoalveolar lavage fluid, the development of antibiotic resistance, the antibiotic distribution, and the levels of inflammatory markers. RESULTS: The median (25-75th percentile) P. aeruginosa lung burden for animals in the control, MEM only, and MEM + AMK groups was 2.91 (1.75-5.69), 0.72 (0.12-3.35), and 0.90 (0-4.55) log10 CFU/g (p = 0.009). Inhaled therapy had no effect on preventing dissemination compared to systemic monotherapy, but it did have significantly higher bactericidal efficacy in tracheal secretions only. Remarkably, the minimum inhibitory concentration of MEM increased to > 32 mg/L after 72-h exposure to monotherapy in 83% of animals, while the addition of AMK prevented this increase (p = 0.037). Adjunctive therapy also slightly affected interleukin-1ß downregulation. Despite finding high AMK concentrations in pulmonary samples, we found no paired differences in the epithelial lining fluid concentration between infected and non-infected lungs. Finally, a non-significant trend was observed for higher amikacin penetration in low-affected lung areas. CONCLUSIONS: In a swine model of monolateral MDR P. aeruginosa pneumonia, resistant to the inhaled AMK and susceptible to the IV antibiotic, the use of AMK as an adjuvant treatment offered no benefits for either the colonization of pulmonary tissue or the prevention of pathogen dissemination. However, inhaled AMK improved bacterial eradication in the proximal airways and hindered antibiotic resistance.

Engineered live bacteria suppress Pseudomonas aeruginosa infection in mouse lung and dissolve endotracheal-tube biofilms.

Engineered live bacteria could provide a new modality for treating lung infections, a major cause of mortality worldwide. In the present study, we engineered a genome-reduced human lung bacterium, Mycoplasma pneumoniae, to treat ventilator-associated pneumonia, a disease with high hospital mortality when associated with Pseudomonas aeruginosa biofilms. After validating the biosafety of an attenuated M. pneumoniae chassis in mice, we introduced four transgenes into the chromosome by transposition to implement bactericidal and biofilm degradation activities. We show that this engineered strain has high efficacy against an acute P. aeruginosa lung infection in a mouse model. In addition, we demonstrated that the engineered strain could dissolve biofilms formed in endotracheal tubes of patients with ventilator-associated pneumonia and be combined with antibiotics targeting the peptidoglycan layer to increase efficacy against Gram-positive and Gram-negative bacteria. We expect our M. pneumoniae-engineered strain to be able to treat biofilm-associated infections in the respiratory tract.

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic: a matched analysis.

BACKGROUND: The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with coronavirus disease 2019 (COVID-19)-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior noninvasive respiratory support on outcomes. METHODS: This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICUs) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of ICU admission. Propensity score matching was used to achieve a balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different time-point (48 h from ICU admission) for early and delayed intubation. RESULTS: Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After propensity score matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%; p=0.01), ICU mortality (25.7% versus 36.1%; p=0.007) and 90-day mortality (30.9% versus 40.2%; p=0.02) compared with the early intubation group. Very similar findings were observed when we used a 48-h time-point for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth waves, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (HFNC) (n=294) who were intubated earlier. The subgroup of patients undergoing noninvasive ventilation (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. CONCLUSIONS: In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received HFNC.

Genome-wide transcriptional profiling of pulmonary functional sequelae in ARDS- secondary to SARS-CoV-2 infection.

BACKGROUND: Up to 80% of patients surviving acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 infection present persistent anomalies in pulmonary function after hospital discharge. There is a limited understanding of the mechanistic pathways linked to post-acute pulmonary sequelae. AIM: To identify the molecular underpinnings associated with severe lung diffusion involvement in survivors of SARS-CoV-2-induced ARDS. METHODS: Survivors attended to a complete pulmonary evaluation 3 months after hospital discharge. RNA sequencing (RNA-seq) was performed using Illumina technology in whole-blood samples from 50 patients with moderate to severe diffusion impairment (DLCO<60%) and age- and sex-matched individuals with mild-normal lung function (DLCO≥60%). A transcriptomic signature for optimal classification was constructed using random forest. Transcriptomic data were analyzed for biological pathway enrichment, cellular deconvolution, cell/tissue-specific gene expression and candidate drugs. RESULTS: RNA-seq identified 1357 differentially expressed transcripts. A model composed of 14 mRNAs allowed the optimal discrimination of survivors with severe diffusion impairment (AUC=0.979). Hallmarks of lung sequelae involved cell death signaling, cytoskeleton reorganization, cell growth and differentiation and the immune response. Resting natural killer (NK) cells were the most important immune cell subtype for the prediction of severe diffusion impairment. Components of the signature correlated with neutrophil, lymphocyte and monocyte counts. A variable expression profile of the transcripts was observed in lung cell subtypes and bodily tissues. One upregulated gene, TUBB4A, constitutes a target for FDA-approved drugs. CONCLUSIONS: This work defines the transcriptional programme associated with post-acute pulmonary sequelae and provides novel insights for targeted interventions and biomarker development.