Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.

Plasma steroid concentrations reflect acute disease severity and normalise during recovery in people hospitalised with COVID-19.

OBJECTIVE: Endocrine systems are disrupted in acute illness, and symptoms reported following coronavirus disease 2019 (COVID-19) are similar to those found with clinical hormone deficiencies. We hypothesised that people with severe acute COVID-19 and with post-COVID symptoms have glucocorticoid and sex hormone deficiencies. DESIGN/PATIENTS: Samples were obtained for analysis from two UK multicentre cohorts during hospitalisation with COVID-19 (International Severe Acute Respiratory Infection Consortium/World Health Organisation [WHO] Clinical Characterization Protocol for Severe Emerging Infections in the UK study), and at follow-up 5 months after hospitalisation (Post-hospitalisation COVID-19 study). MEASUREMENTS: Plasma steroids were quantified by liquid chromatography-mass spectrometry. Steroid concentrations were compared against disease severity (WHO ordinal scale) and validated symptom scores. Data are presented as geometric mean (SD). RESULTS: In the acute cohort (n = 239, 66.5% male), plasma cortisol concentration increased with disease severity (cortisol 753.3 [1.6] vs. 429.2 [1.7] nmol/L in fatal vs. least severe, p < .001). In males, testosterone concentrations decreased with severity (testosterone 1.2 [2.2] vs. 6.9 [1.9] nmol/L in fatal vs. least severe, p < .001). In the follow-up cohort (n = 198, 62.1% male, 68.9% ongoing symptoms, 165 [121-192] days postdischarge), plasma cortisol concentrations (275.6 [1.5] nmol/L) did not differ with in-hospital severity, perception of recovery, or patient-reported symptoms. Male testosterone concentrations (12.6 [1.5] nmol/L) were not related to in-hospital severity, perception of recovery or symptom scores. CONCLUSIONS: Circulating glucocorticoids in patients hospitalised with COVID-19 reflect acute illness, with a marked rise in cortisol and fall in male testosterone. These findings are not observed 5 months from discharge. The lack of association between hormone concentrations and common post-COVID symptoms suggests steroid insufficiency does not play a causal role in this condition.

Accelarated immune ageing is associated with COVID-19 disease severity.

BACKGROUND: The striking increase in COVID-19 severity in older adults provides a clear example of immunesenescence, the age-related remodelling of the immune system. To better characterise the association between convalescent immunesenescence and acute disease severity, we determined the immune phenotype of COVID-19 survivors and non-infected controls. RESULTS: We performed detailed immune phenotyping of peripheral blood mononuclear cells isolated from 103 COVID-19 survivors 3-5 months post recovery who were classified as having had severe (n = 56; age 53.12 ± 11.30 years), moderate (n = 32; age 52.28 ± 11.43 years) or mild (n = 15; age 49.67 ± 7.30 years) disease and compared with age and sex-matched healthy adults (n = 59; age 50.49 ± 10.68 years). We assessed a broad range of immune cell phenotypes to generate a composite score, IMM-AGE, to determine the degree of immune senescence. We found increased immunesenescence features in severe COVID-19 survivors compared to controls including: a reduced frequency and number of naïve CD4 and CD8 T cells (p < 0.0001); increased frequency of EMRA CD4 (p < 0.003) and CD8 T cells (p < 0.001); a higher frequency (p < 0.0001) and absolute numbers (p < 0.001) of CD28-ve CD57+ve senescent CD4 and CD8 T cells; higher frequency (p < 0.003) and absolute numbers (p < 0.02) of PD-1 expressing exhausted CD8 T cells; a two-fold increase in Th17 polarisation (p < 0.0001); higher frequency of memory B cells (p < 0.001) and increased frequency (p < 0.0001) and numbers (p < 0.001) of CD57+ve senescent NK cells. As a result, the IMM-AGE score was significantly higher in severe COVID-19 survivors than in controls (p < 0.001). Few differences were seen for those with moderate disease and none for mild disease. Regression analysis revealed the only pre-existing variable influencing the IMM-AGE score was South Asian ethnicity ([Formula: see text] = 0.174, p = 0.043), with a major influence being disease severity ([Formula: see text] = 0.188, p = 0.01). CONCLUSIONS: Our analyses reveal a state of enhanced immune ageing in survivors of severe COVID-19 and suggest this could be related to SARS-Cov-2 infection. Our data support the rationale for trials of anti-immune ageing interventions for improving clinical outcomes in these patients with severe disease.

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1 H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters. PURPOSE: Develop a generalizable CNN for lung segmentation in 1 H-MRI, robust to pathology, acquisition protocol, vendor, and center. STUDY TYPE: Retrospective. POPULATION: A total of 809 1 H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6-85); 42% females) and 31 healthy participants (median age (range): 34 (23-76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1 H-MRI. ASSESSMENT: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance. STATISTICAL TESTS: Kruskal-Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland-Altman analyses assessed agreement with manually derived lung volumes. A P value of <0.05 was considered statistically significant. RESULTS: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880-0.987), Average HD of 1.63 mm (0.65-5.45) and XOR of 0.079 (0.025-0.240) on the testing set and a DSC of 0.973 (0.866-0.987), Average HD of 1.11 mm (0.47-8.13) and XOR of 0.054 (0.026-0.255) on external validation data. DATA CONCLUSION: The 3D CNN generated accurate 1 H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Joint patient and clinician priority setting to identify 10 key research questions regarding the long-term sequelae of COVID-19.

Given the large numbers of people infected and high rates of ongoing morbidity, research is clearly required to address the needs of adult survivors of COVID-19 living with ongoing symptoms (long COVID). To help direct resource and research efforts, we completed a research prioritisation process incorporating views from adults with ongoing symptoms of COVID-19, carers, clinicians and clinical researchers. The final top 10 research questions were agreed at an independently mediated workshop and included: identifying underlying mechanisms of long COVID, establishing diagnostic tools, understanding trajectory of recovery and evaluating the role of interventions both during the acute and persistent phases of the illness.

Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a multicentre study.

BACKGROUND: The number of individuals recovering from severe COVID-19 is increasing rapidly. However, little is known about physical behaviours that make up the 24-h cycle within these individuals. This study aimed to describe physical behaviours following hospital admission for COVID-19 at eight months post-discharge including associations with acute illness severity and ongoing symptoms. METHODS: One thousand seventy-seven patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and individuals with type 2 diabetes were comparators. RESULTS: Valid accelerometer data from 253 women and 462 men were included. Women engaged in a mean ± SD of 14.9 ± 14.7 min/day of moderate-to-vigorous physical activity (MVPA), with 12.1 ± 1.7 h/day spent inactive and 7.2 ± 1.1 h/day asleep. The values for men were 21.0 ± 22.3 and 12.6 ± 1.7 h /day and 6.9 ± 1.1 h/day, respectively. Over 60% of women and men did not have any days containing a 30-min bout of MVPA. Variability in sleep timing was approximately 2 h in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer total sleep time, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes. CONCLUSIONS: Those recovering from a hospital admission for COVID-19 have low levels of physical activity and disrupted patterns of sleep several months after discharge. Our comparative cohorts indicate that the long-term impact of COVID-19 on physical behaviours is significant.

Phenotypic and functional translation of IL33 genetics in asthma.

BACKGROUND: Asthma is a complex disease with multiple phenotypes that may differ in disease pathobiology and treatment response. IL33 single nucleotide polymorphisms (SNPs) have been reproducibly associated with asthma. IL33 levels are elevated in sputum and bronchial biopsies of patients with asthma. The functional consequences of IL33 asthma SNPs remain unknown. OBJECTIVE: This study sought to determine whether IL33 SNPs associate with asthma-related phenotypes and with IL33 expression in lung or bronchial epithelium. This study investigated the effect of increased IL33 expression on human bronchial epithelial cell (HBEC) function. METHODS: Association between IL33 SNPs (Chr9: 5,815,786-6,657,983) and asthma phenotypes (Lifelines/DAG [Dutch Asthma GWAS]/GASP [Genetics of Asthma Severity & Phenotypes] cohorts) and between SNPs and expression (lung tissue, bronchial brushes, HBECs) was done using regression modeling. Lentiviral overexpression was used to study IL33 effects on HBECs. RESULTS: We found that 161 SNPs spanning the IL33 region associated with 1 or more asthma phenotypes after correction for multiple testing. We report a main independent signal tagged by rs992969 associating with blood eosinophil levels, asthma, and eosinophilic asthma. A second, independent signal tagged by rs4008366 presented modest association with eosinophilic asthma. Neither signal associated with FEV1, FEV1/forced vital capacity, atopy, and age of asthma onset. The 2 IL33 signals are expression quantitative loci in bronchial brushes and cultured HBECs, but not in lung tissue. IL33 overexpression in vitro resulted in reduced viability and reactive oxygen species-capturing of HBECs, without influencing epithelial cell count, metabolic activity, or barrier function. CONCLUSIONS: We identify IL33 as an epithelial susceptibility gene for eosinophilia and asthma, provide mechanistic insight, and implicate targeting of the IL33 pathway specifically in eosinophilic asthma.

LabPipe: an extensible bioinformatics toolkit to manage experimental data and metadata.

BACKGROUND: Data handling in clinical bioinformatics is often inadequate. No freely available tools provide straightforward approaches for consistent, flexible metadata collection and linkage of related experimental data generated locally by vendor software. RESULTS: To address this problem, we created LabPipe, a flexible toolkit which is driven through a local client that runs alongside vendor software and connects to a light-weight server. The toolkit allows re-usable configurations to be defined for experiment metadata and local data collection, and handles metadata entry and linkage of data. LabPipe was piloted in a multi-site clinical breathomics study. CONCLUSIONS: LabPipe provided a consistent, controlled approach for handling metadata and experimental data collection, collation and linkage in the exemplar study and was flexible enough to deal effectively with different data handling challenges.

Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software.

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for processing GC×GC data are challenging and often require multiple tools or software to process a single dataset. We describe a new approach, which uses an existing underutilized interface within commercial software to integrate free and open-source/external scripts and tools, tailoring the workflow to the needs of the individual researcher within a single software environment. To demonstrate the concept, the interface was successfully used to complete a first-pass alignment on a large-scale GC×GC metabolomics dataset. The analysis was performed by interfacing bespoke and published external algorithms within a commercial software environment to automatically correct the variation in retention times captured by a routine reference standard. Variation in 1tR and 2tR was reduced on average from 8 and 16% CV prealignment to less than 1 and 2% post alignment, respectively. The interface enables automation and creation of new functions and increases the interconnectivity between chemometric tools, providing a window for integrating data-processing software with larger informatics-based data management platforms.

Lung Computational Models and the Role of the Small Airways in Asthma.

Rationale: Asthma is characterized by disease within the small airways. Several studies have suggested that forced oscillation technique-derived resistance at 5 Hz (R5) - resistance at 20 Hz (R20) is a measure of small airway disease; however, there has been limited validation of this measurement to date.Objectives: To validate the use of forced oscillation R5 - R20 as a measure of small airway narrowing in asthma, and to investigate the role that small airway narrowing plays in asthma.Methods: Patient-based complete conducting airway models were generated from computed tomography scans to simulate the impact of different degrees of airway narrowing at different levels of the airway tree on forced oscillation R5 - R20 (n = 31). The computational models were coupled with regression models in an asthmatic cohort (n = 177) to simulate the impact of small airway narrowing on asthma control and quality of life. The computational models were used to predict the impact on small airway narrowing of type-2 targeting biologics using pooled data from two similarly design randomized, placebo-controlled biologic trials (n = 137).Measurements and Main Results: Simulations demonstrated that narrowing of the small airways had a greater impact on R5 - R20 than narrowing of the larger airways and was associated (above a threshold of approximately 40% narrowing) with marked deterioration in both asthma control and asthma quality of life, above the minimal clinical important difference. The observed treatment effect on R5 - R20 in the pooled trials equated to a predicted small airway narrowing reversal of approximately 40%.Conclusions: We have demonstrated, using computational modeling, that forced oscillation R5 - R20 is a direct measure of anatomical narrowing in the small airways and that small airway narrowing has a marked impact on both asthma control and quality of life and may be modified by biologics.

Functional CT imaging for identification of the spatial determinants of small-airways disease in adults with asthma.

BACKGROUND: Asthma is a disease characterized by ventilation heterogeneity (VH). A number of studies have demonstrated that VH markers derived by using impulse oscillometry (IOS) or multiple-breath washout (MBW) are associated with key asthmatic patient-related outcome measures and airways hyperresponsiveness. However, the topographical mechanisms of VH in the lung remain poorly understood. OBJECTIVES: We hypothesized that specific regionalization of topographical small-airway disease would best account for IOS- and MBW-measured indices in patients. METHODS: We evaluated the results of paired expiratory/inspiratory computed tomography in a cohort of asthmatic (n = 41) and healthy (n = 11) volunteers to understand the determinants of clinical VH indices commonly reported by using IOS and MBW. Parametric response mapping (PRM) was used to calculate the functional small-airways disease marker PRMfSAD and Hounsfield unit (HU)-based density changes from total lung capacity to functional residual capacity (ΔHU); gradients of ΔHU in gravitationally perpendicular (parallel) inferior-superior (anterior-posterior) axes were quantified. RESULTS: The ΔHU gradient in the inferior-superior axis provided the highest level of discrimination of both acinar VH (measured by using phase 3 slope analysis of multiple-breath washout data) and resistance at 5 Hz minus resistance at 20 Hz measured by using impulse oscillometry (R5-R20) values. Patients with a high inferior-superior ΔHU gradient demonstrated evidence of reduced specific ventilation in the lower lobes of the lungs and high levels of PRMfSAD. A computational small-airway tree model confirmed that constriction of gravitationally dependent, lower-zone, small-airway branches would promote the largest increases in R5-R20 values. Ventilation gradients correlated with asthma control and quality of life but not with exacerbation frequency. CONCLUSIONS: Lower lobe-predominant small-airways disease is a major driver of clinically measured VH in adults with asthma.

In vitro, in silico and in vivo study challenges the impact of bronchial thermoplasty on acute airway smooth muscle mass loss.

Bronchial thermoplasty is a treatment for asthma. It is currently unclear whether its histopathological impact is sufficiently explained by the proportion of airway wall that is exposed to temperatures necessary to affect cell survival.Airway smooth muscle and bronchial epithelial cells were exposed to media (37-70°C) for 10 s to mimic thermoplasty. In silico we developed a mathematical model of airway heat distribution post-thermoplasty. In vivo we determined airway smooth muscle mass and epithelial integrity pre- and post-thermoplasty in 14 patients with severe asthma.In vitro airway smooth muscle and epithelial cell number decreased significantly following the addition of media heated to ≥65°C. In silico simulations showed a heterogeneous heat distribution that was amplified in larger airways, with <10% of the airway wall heated to >60°C in airways with an inner radius of ∼4 mm. In vivo at 6 weeks post-thermoplasty, there was an improvement in asthma control (measured via Asthma Control Questionnaire-6; mean difference 0.7, 95% CI 0.1-1.3; p=0.03), airway smooth muscle mass decreased (absolute median reduction 5%, interquartile range (IQR) 0-10; p=0.03) and epithelial integrity increased (14%, IQR 6-29; p=0.007). Neither of the latter two outcomes was related to improved asthma control.Integrated in vitro and in silico modelling suggest that the reduction in airway smooth muscle post-thermoplasty cannot be fully explained by acute heating, and nor did this reduction confer a greater improvement in asthma control.

Associations in asthma between quantitative computed tomography and bronchial biopsy-derived airway remodelling.

Airway remodelling in asthma remains poorly understood. This study aimed to determine the association of airway remodelling measured on bronchial biopsies with 1) lung function impairment and 2) thoracic quantitative computed tomography (QCT)-derived morphometry and densitometry measures of proximal airway remodelling and air trapping.Subjects were recruited from a single centre. Bronchial biopsy remodelling features that were the strongest predictors of lung function impairment and QCT-derived proximal airway morphometry and air trapping markers were determined by stepwise multiple regression. The best predictor of air trapping was validated in an independent replication group.Airway smooth muscle % was the only predictor of post-bronchodilator forced expiratory volume in 1 s (FEV1) % pred, while both airway smooth muscle % and vascularity were predictors of FEV1/forced vital capacity. Epithelial thickness and airway smooth muscle % were predictors of mean segmental bronchial luminal area (R2=0.12; p=0.02 and R2=0.12; p=0.015), whereas epithelial thickness was the only predictor of wall area % (R2=0.13; p=0.018). Vascularity was the only significant predictor of air trapping (R2=0.24; p=0.001), which was validated in the replication group (R2=0.19; p=0.031).In asthma, airway smooth muscle content and vascularity were both associated with airflow obstruction. QCT-derived proximal airway morphometry was most strongly associated with epithelial thickness and airway smooth muscle content, whereas air trapping was related to vascularity.

Quantitative computed tomography-derived clusters: redefining airway remodeling in asthmatic patients.

BACKGROUND: Asthma heterogeneity is multidimensional and requires additional tools to unravel its complexity. Computed tomography (CT)-assessed proximal airway remodeling and air trapping in asthmatic patients might provide new insights into underlying disease mechanisms. OBJECTIVES: The aim of this study was to explore novel, quantitative, CT-determined asthma phenotypes. METHODS: Sixty-five asthmatic patients and 30 healthy subjects underwent detailed clinical, physiologic characterization and quantitative CT analysis. Factor and cluster analysis techniques were used to determine 3 novel, quantitative, CT-based asthma phenotypes. RESULTS: Patients with severe and mild-to-moderate asthma demonstrated smaller mean right upper lobe apical segmental bronchus (RB1) lumen volume (LV) in comparison with healthy control subjects (272.3 mm(3) [SD, 112.6 mm(3)], 259.0 mm(3) [SD, 53.3 mm(3)], 366.4 mm(3) [SD, 195.3 mm(3)], respectively; P = .007) but no difference in RB1 wall volume (WV). Air trapping measured based on mean lung density expiratory/inspiratory ratio was greater in patients with severe and mild-to-moderate asthma compared with that seen in healthy control subjects (0.861 [SD, 0.05)], 0.866 [SD, 0.07], and 0.830 [SD, 0.06], respectively; P = .04). The fractal dimension of the segmented airway tree was less in asthmatic patients compared with that seen in control subjects (P = .007). Three novel, quantitative, CT-based asthma clusters were identified, all of which demonstrated air trapping. Cluster 1 demonstrates increased RB1 WV and RB1 LV but decreased RB1 percentage WV. On the contrary, cluster 3 subjects have the smallest RB1 WV and LV values but the highest RB1 percentage WV values. There is a lack of proximal airway remodeling in cluster 2 subjects. CONCLUSIONS: Quantitative CT analysis provides a new perspective in asthma phenotyping, which might prove useful in patient selection for novel therapies.

Lung clearance index in adults with non-cystic fibrosis bronchiectasis.

BACKGROUND: Lung clearance index (LCI) is a measure of abnormal ventilation distribution derived from the multiple breath inert gas washout (MBW) technique. We aimed to determine the clinical utility of LCI in non-CF bronchiectasis, and to assess two novel MBW parameters that distinguish between increases in LCI due to specific ventilation inequality (LCIvent) and increased respiratory dead space (LCIds). METHODS: Forty-three patients with non-CF bronchiectasis and 18 healthy control subjects underwent MBW using the sulphur hexafluoride wash-in technique, and data from 40 adults with CF were re-analysed. LCIvent and LCIds were calculated using a theoretical two-compartment lung model, and represent the proportional increase in LCI above its ideal value due to specific ventilation inequality and increased respiratory dead space, respectively. RESULTS: LCI was significantly raised in patients with non-CF bronchiectasis compared to healthy controls (9.99 versus 7.28, p < 0.01), and discriminated well between these two groups (area under receiver operating curve = 0.90, versus 0.83 for forced expiratory volume in one second [% predicted]). LCI, LCIvent and LCIds were repeatable (intraclass correlation coefficient > 0.75), and correlated significantly with measures of spirometric airflow obstruction. CONCLUSION: LCI is repeatable, discriminatory, and is associated with spirometric airflow obstruction in patients with non-CF bronchiectasis. LCIvent and LCIds are a practical and repeatable alternative to phase III slope analysis and may allow a further level of mechanistic information to be extracted from the MBW test in patients with severe ventilation heterogeneity.

Validation of a photoacoustic gas analyser for the measurement of functional residual capacity using multiple-breath inert gas washout.

BACKGROUND: The respiratory mass spectrometer is the current gold-standard technique for performing multiple-breath inert gas washout (MBW), but is expensive and lacks portability. A number of alternative techniques have recently been described. OBJECTIVES: We aimed to validate, using an in vitro lung model, an open-circuit MBW system that utilises a portable photoacoustic gas analyser, with sulphur hexafluoride (SF6) as the inert tracer gas. METHODS: An acrylic glass lung model was utilised to assess the accuracy of functional residual capacity (FRC) measurements derived from MBW. Measurements were performed in triplicate at 20 combinations of simulated FRC, tidal volume and respiratory rate. FRC measured using MBW (FRCmbw) was compared to FRC calculated from the known dimensions of the model (FRCcalc). MBW was also performed in 10 healthy subjects and 14 patients with asthma. RESULTS: The MBW system measured FRC with high precision. The mean bias of FRCmbw with respect to FRCcalc was -0.4% (95% limits of agreement of -4.6 and 3.9%). The mean coefficient of variation of triplicate FRC measurements was 4.0% in vivo and 1.0% in vitro. MBW slightly underestimated low lung volumes and overestimated high lung volumes, but this did not cause a significant error in lung clearance index except at lung volumes below 1,500 ml. CONCLUSIONS: The open-circuit MBW system utilising SF6 as the inert tracer gas and a photoacoustic gas analyser is both accurate and repeatable within the adult range of lung volumes. Further modifications would be required before its use in young children or infants.

Elevated sputum interleukin-5 and submucosal eosinophilia in obese individuals with severe asthma.

RATIONALE: The relationship between airway inflammation and obesity in severe asthma is poorly understood. OBJECTIVES: We sought to determine the relationship between sputum mediator profiles and the distribution of eosinophilic inflammation and obesity in people with severe asthma. METHODS: Clinical parameters and eight mediators in sputum were assessed in 131 subjects with severe asthma from a single center categorized into lean, overweight, and obese groups defined by their body mass index. In an independent group of people with severe asthma (n = 45) and healthy control subjects (n = 19) eosinophilic inflammation was enumerated in bronchial submucosa, blood, and sputum and related to their body mass index. MEASUREMENTS AND MAIN RESULTS: Sputum IL-5 geometric mean (95% confidence interval) (pg/ml) was elevated in the obese (1.8 [1.2-2.6]) compared with overweight (1.1 [0.8-1.3]; P = 0.025) and lean (0.9 [0.6-1.2]; P = 0.018) subjects with asthma and was correlated with body mass index (r = 0.29; P < 0.001). There was no relationship among body mass index, the sputum cell count, or other sputum mediators. In the bronchoscopy group the submucosal eosinophil number in the subjects with asthma was correlated with body mass index (Spearman rank correlation, rs = 0.38; P = 0.013) and the median (interquartile range) number of submucosal eosinophils was increased in obese (19.4 [11.8-31.2]) (cells per square millimeter) versus lean subjects (8.2 [5.4-14.6]) (P = 0.006). There was no significant association between sputum or peripheral blood eosinophil counts and body mass index. CONCLUSIONS: Sputum IL-5 and submucosal eosinophils, but not sputum eosinophils, are elevated in obese people with severe asthma. Whether specific antieosinophilic therapy is beneficial, or improved diet and lifestyle in obese asthma has antiinflammatory effects beyond weight reduction, requires further study.

Long COVID and cardiovascular disease: a prospective cohort study.

BACKGROUND: Pre-existing cardiovascular disease (CVD) or cardiovascular risk factors have been associated with an increased risk of complications following hospitalisation with COVID-19, but their impact on the rate of recovery following discharge is not known. OBJECTIVES: To determine whether the rate of patient-perceived recovery following hospitalisation with COVID-19 was affected by the presence of CVD or cardiovascular risk factors. METHODS: In a multicentre prospective cohort study, patients were recruited following discharge from the hospital with COVID-19 undertaking two comprehensive assessments at 5 months and 12 months. Patients were stratified by the presence of either CVD or cardiovascular risk factors prior to hospitalisation with COVID-19 and compared with controls with neither. Full recovery was determined by the response to a patient-perceived evaluation of full recovery from COVID-19 in the context of physical, physiological and cognitive determinants of health. RESULTS: From a total population of 2545 patients (38.8% women), 472 (18.5%) and 1355 (53.2%) had CVD or cardiovascular risk factors, respectively. Compared with controls (n=718), patients with CVD and cardiovascular risk factors were older and more likely to have had severe COVID-19. Full recovery was significantly lower at 12 months in patients with CVD (adjusted OR (aOR) 0.62, 95% CI 0.43 to 0.89) and cardiovascular risk factors (aOR 0.66, 95% CI 0.50 to 0.86). CONCLUSION: Patients with CVD or cardiovascular risk factors had a delayed recovery at 12 months following hospitalisation with COVID-19. Targeted interventions to reduce the impact of COVID-19 in patients with cardiovascular disease remain an unmet need. TRAIL REGISTRATION NUMBER: ISRCTN10980107.

Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury.

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury.

Sputum mediator profiling and relationship to airway wall geometry imaging in severe asthma.

BACKGROUND: Severe asthma is a heterogeneous disease and the relationship between airway inflammation and airway remodelling is poorly understood. We sought to define sputum mediator profiles in severe asthmatics categorised by CT-determined airway geometry and sputum differential cell counts. METHODS: In a single centre cross-sectional observational study we recruited 59 subjects with severe asthma that underwent sputum induction and thoracic CT. Quantitative CT analysis of the apical segment of the right upper lobe (RB1) was performed. Forty-one mediators in sputum samples were measured of which 21 mediators that were assessable in >50% of samples were included in the analyses. RESULTS: Independent of airway geometry, sputum MMP9 and IL-1ß were elevated in those groups with a high sputum neutrophil count while sputum ICAM was elevated in those subjects with a low sputum neutrophil count. In contrast, sputum CCL11, IL-1α and fibrinogen were different in groups stratified by both sputum neutrophil count and airway geometry. Sputum CCL11 concentration was elevated in subjects with a low sputum neutrophil count and high luminal and total RB1 area, whereas sputum IL1α was increased in subjects with a high sputum neutrophil count and low total RB1 area. Sputum fibrinogen was elevated in those subjects with RB1 luminal narrowing and in those subjects with neutrophilic inflammation without luminal narrowing. CONCLUSIONS: We have demonstrated that sputum mediator profiling reveals a number of associations with airway geometry. Whether these findings reflect important biological phenotypes that might inform stratified medicine approaches requires further investigation.