Fulfilling the Promise of Breathomics: Considerations for the Discovery and Validation of Exhaled Volatile Biomarkers.

The exhaled breath represents an ideal matrix for non-invasive biomarker discovery, and exhaled metabolomics have the potential to be clinically useful in the era of precision medicine. In this concise translational review we will specifically address volatile organic compounds in the breath, with a view towards fulfilling the promise of these as actionable biomarkers, in particular for lung diseases. We review the literature paying attention to seminal work linked to key milestones in breath research; discuss potential applications for breath biomarkers across disease areas and healthcare systems, including the perspectives of industry; and outline critical aspects of study design that will need to be considered for any pivotal research going forward, if breath analysis is to provide robust validated biomarkers that meet the requirements for future clinical implementation.

Whole blood transcriptome in long-COVID patients reveals association with lung function and immune response.

BACKGROUND: Months after infection with severe acute respiratory syndrome coronavirus 2, at least 10% of patients still experience complaints. Long-COVID (coronavirus disease 2019) is a heterogeneous disease, and clustering efforts revealed multiple phenotypes on a clinical level. However, the molecular pathways underlying long-COVID phenotypes are still poorly understood. OBJECTIVES: We sought to cluster patients according to their blood transcriptomes and uncover the pathways underlying their disease. METHODS: Blood was collected from 77 patients with long-COVID from the Precision Medicine for more Oxygen (P4O2) COVID-19 study. Unsupervised hierarchical clustering was performed on the whole blood transcriptome. These clusters were analyzed for differences in clinical features, pulmonary function tests, and gene ontology term enrichment. RESULTS: Clustering revealed 2 distinct clusters on a transcriptome level. Compared with cluster 2 (n = 65), patients in cluster 1 (n = 12) showed a higher rate of preexisting cardiovascular disease (58% vs 22%), higher prevalence of gastrointestinal symptoms (58% vs 29%), shorter hospital duration during severe acute respiratory syndrome coronavirus 2 infection (median, 3 vs 8 days), lower FEV1/forced vital capacity (72% vs 81%), and lower diffusion capacity of the lung for carbon monoxide (68% vs 85% predicted). Gene ontology term enrichment analysis revealed upregulation of genes involved in the antiviral innate immune response in cluster 1, whereas genes involved with the adaptive immune response were upregulated in cluster 2. CONCLUSIONS: This study provides a start in uncovering the pathophysiological mechanisms underlying long-COVID. Further research is required to unravel why the immune response is different in these clusters, and to identify potential therapeutic targets to create an optimized treatment or monitoring strategy for the individual long-COVID patient.

Association between butyrate-producing gut bacteria and the risk of infectious disease hospitalisation: results from two observational, population-based microbiome studies.

BACKGROUND: Microbiota alterations are common in patients hospitalised for severe infections, and preclinical models have shown that anaerobic butyrate-producing gut bacteria protect against systemic infections. However, the relationship between microbiota disruptions and increased susceptibility to severe infections in humans remains unclear. We investigated the relationship between gut microbiota and the risk of future infection-related hospitalisation in two large population-based cohorts. METHODS: In this observational microbiome study, gut microbiota were characterised using 16S rRNA gene sequencing in independent population-based cohorts from the Netherlands (HELIUS study; derivation cohort) and Finland (FINRISK 2002 study; validation cohort). HELIUS was conducted in Amsterdam, Netherlands, and included adults (aged 18-70 years at inclusion) who were randomly sampled from the municipality register of Amsterdam. FINRISK 2002 was conducted in six regions in Finland and is a population survey that included a random sample of adults (aged 25-74 years). In both cohorts, participants completed questionnaires, underwent a physical examination, and provided a faecal sample at inclusion (Jan 3, 2013, to Nov 27, 2015, for HELIUS participants and Jan 21 to April 19, 2002, for FINRISK participants. For inclusion in our study, a faecal sample needed to be provided and successfully sequenced, and national registry data needed to be available. Primary predictor variables were microbiota composition, diversity, and relative abundance of butyrate-producing bacteria. Our primary outcome was hospitalisation or mortality due to any infectious disease during 5-7-year follow-up after faecal sample collection, based on national registry data. We examined associations between microbiota and infection risk using microbial ecology and Cox proportional hazards. FINDINGS: We profiled gut microbiota from 10 699 participants (4248 [39·7%] from the derivation cohort and 6451 [60·3%] from the validation cohort). 602 (5·6%) participants (152 [3·6%] from the derivation cohort; 450 [7·0%] from the validation cohort) were hospitalised or died due to infections during follow-up. Gut microbiota composition of these participants differed from those without hospitalisation for infections (derivation p=0·041; validation p=0·0002). Specifically, higher relative abundance of butyrate-producing bacteria was associated with a reduced risk of hospitalisation for infections (derivation cohort cause-specific hazard ratio 0·75 [95% CI 0·60-0·94] per 10% increase in butyrate producers, p=0·013; validation cohort 0·86 [0·77-0·96] per 10% increase, p=0·0077). These associations remained unchanged following adjustment for demographics, lifestyle, antibiotic exposure, and comorbidities. INTERPRETATION: Gut microbiota composition, specifically colonisation with butyrate-producing bacteria, was associated with protection against hospitalisation for infectious diseases in the general population across two independent European cohorts. Further studies should investigate whether modulation of the microbiome can reduce the risk of severe infections. FUNDING: Amsterdam UMC, Porticus, National Institutes of Health, Netherlands Organisation for Health Research and Development (ZonMw), and Leducq Foundation.

Hemoglobin and Its Relationship with Fatigue in Long-COVID Patients Three to Six Months after SARS-CoV-2 Infection.

Background: While some long-term effects of COVID-19 are respiratory in nature, a non-respiratory effect gaining attention has been a decline in hemoglobin, potentially mediated by inflammatory processes. In this study, we examined the correlations between hemoglobin levels and inflammatory biomarkers and evaluated the association between hemoglobin and fatigue in a cohort of Long-COVID patients. Methods: This prospective cohort study in the Netherlands evaluated 95 (mostly hospitalized) patients, aged 40-65 years, 3-6 months post SARS-CoV-2 infection, examining their venous hemoglobin concentration, anemia (hemoglobin < 7.5 mmol/L in women and <8.5 mmol/L in men), inflammatory blood biomarkers, average FSS (Fatigue Severity Score), demographics, and clinical features. Follow-up hemoglobin was compared against hemoglobin during acute infection. Spearman correlation was used for assessing the relationship between hemoglobin concentrations and inflammatory biomarkers, and the association between hemoglobin and fatigue was examined using logistic regression. Results: In total, 11 (16.4%) participants were suffering from anemia 3-6 months after SARS-CoV-2 infection. The mean hemoglobin value increased by 0.3 mmol/L 3-6 months after infection compared to the hemoglobin during the acute phase (p-value = 0.003). Whilst logistic regression showed that a 1 mmol/L greater increase in hemoglobin is related to a decrease in experiencing fatigue in Long-COVID patients (adjusted OR 0.38 [95%CI 0.13-1.09]), we observed no correlations between hemoglobin and any of the inflammatory biomarkers examined. Conclusion: Our results indicate that hemoglobin impairment might play a role in developing Long-COVID fatigue. Further investigation is necessary to identify the precise mechanism causing hemoglobin alteration in these patients.

Dried Blood Spot Method Development and Clinical Validation for the Analysis of Elexacaftor, Elexacaftor-M23, Tezacaftor, Tezacaftor-M1, Ivacaftor, Ivacaftor Carboxylate, and Hydroxymethyl Ivacaftor Using LC-MS/MS.

BACKGROUND: The highly effective Cystic Fibrosis Transmembrane conductance Regulator (CFTR) modulator, elexacaftor-tezacaftor-ivacaftor, is now widely being used by people with cystic fibrosis. However, few independent studies have detailed the pharmacokinetics (PK) of CFTR modulators. Blood collection by venipuncture is the gold standard for PK measurements, but it is invasive. The aim of this study was to develop and clinically validate a quantification method for elexacaftor, tezacaftor, ivacaftor, and their main metabolites in dried blood spots (DBSs) using liquid chromatography with tandem mass spectrometry. METHODS: Linearity, accuracy, precision, stability, hematocrit (Hct), spot-to-spot carryover, spot volume, and extraction efficiency were validated in DBS for all analytes. The clinical validation of elexacaftor-tezacaftor-ivacaftor in patients was performed by comparing 21 DBS samples with matched plasma samples. RESULTS: The preset requirements for linearity, within-run and between-run accuracy, precision, Hct, spot volume, and extraction efficiency were met. Puncher carryover was observed and resolved by punching 3 blanks after each sample. The samples remained stable and showed no notable degradation across the tested temperatures and time intervals. Corrected DBS values with the Passing-Bablok regression equation showed good agreement in Bland-Altman plots, and acceptance values were within 20% of the mean for a minimum of 67% of the repeats, according to the EMA guidelines. CONCLUSIONS: A quantification method for the analysis of elexacaftor, tezacaftor, ivacaftor, and their main metabolites was developed and clinically validated in DBS. This method could be valuable in both clinical care and research to address unanswered PK questions regarding CFTR modulators.

Volatile Organic Compounds in Cellular Headspace after Hyperbaric Oxygen Exposure: An In Vitro Pilot Study.

Volatile organic compounds (VOCs) might be associated with pulmonary oxygen toxicity (POT). This pilot study aims to identify VOCs linked to oxidative stress employing an in vitro model of alveolar basal epithelial cells exposed to hyperbaric and hyperoxic conditions. In addition, the feasibility of this in vitro model for POT biomarker research was evaluated. The hyperbaric exposure protocol, similar to the U.S. Navy Treatment Table 6, was conducted on human alveolar basal epithelial cells, and the headspace VOCs were analyzed using gas chromatography-mass spectrometry. Three compounds (nonane [p = 0.005], octanal [p = 0.009], and decane [p = 0.018]), of which nonane and decane were also identified in a previous in vivo study with similar hyperbaric exposure, varied significantly between the intervention group which was exposed to 100% oxygen and the control group which was exposed to compressed air. VOC signal intensities were lower in the intervention group, but cellular stress markers (IL8 and LDH) confirmed increased stress and injury in the intervention group. Despite the observed reductions in compound expression, the model holds promise for POT biomarker exploration, emphasizing the need for further investigation into the complex relationship between VOCs and oxidative stress.

Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study.

RATIONALE: Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. OBJECTIVES: To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. METHODS: This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. MEASUREMENTS AND MAIN RESULTS: Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. CONCLUSIONS: Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

Long COVID exhibits clinically distinct phenotypes at 3-6 months post-SARS-CoV-2 infection: results from the P4O2 consortium.

BACKGROUND: Four months after SARS-CoV-2 infection, 22%-50% of COVID-19 patients still experience complaints. Long COVID is a heterogeneous disease and finding subtypes could aid in optimising and developing treatment for the individual patient. METHODS: Data were collected from 95 patients in the P4O2 COVID-19 cohort at 3-6 months after infection. Unsupervised hierarchical clustering was performed on patient characteristics, characteristics from acute SARS-CoV-2 infection, long COVID symptom data, lung function and questionnaires describing the impact and severity of long COVID. To assess robustness, partitioning around medoids was used as alternative clustering. RESULTS: Three distinct clusters of patients with long COVID were revealed. Cluster 1 (44%) represented predominantly female patients (93%) with pre-existing asthma and suffered from a median of four symptom categories, including fatigue and respiratory and neurological symptoms. They showed a milder SARS-CoV-2 infection. Cluster 2 (38%) consisted of predominantly male patients (83%) with cardiovascular disease (CVD) and suffered from a median of three symptom categories, most commonly respiratory and neurological symptoms. This cluster also showed a significantly lower forced expiratory volume within 1 s and diffusion capacity of the lung for carbon monoxide. Cluster 3 (18%) was predominantly male (88%) with pre-existing CVD and diabetes. This cluster showed the mildest long COVID, and suffered from symptoms in a median of one symptom category. CONCLUSIONS: Long COVID patients can be clustered into three distinct phenotypes based on their clinical presentation and easily obtainable information. These clusters show distinction in patient characteristics, lung function, long COVID severity and acute SARS-CoV-2 infection severity. This clustering can help in selecting the most beneficial monitoring and/or treatment strategies for patients suffering from long COVID. Follow-up research is needed to reveal the underlying molecular mechanisms implicated in the different phenotypes and determine the efficacy of treatment.

Influence of the gut and airway microbiome on asthma development and disease.

There are ample data to suggest that early-life dysbiosis of both the gut and/or airway microbiome can predispose a child to develop along a trajectory toward asthma. Although individual studies show clear associations between dysbiosis and asthma development, it is less clear what (collection of) bacterial species is mechanistically responsible for the observed effects. This is partly due to issues related to the asthma diagnosis and the broad spectrum of anatomical sites, sample techniques, and analysis protocols that are used in different studies. Moreover, there is limited attention for potential differences in the genetics of individuals that would affect the outcome of the interaction between the environment and that individual. Despite these challenges, the first bacterial components were identified that are able to affect the transcriptional state of human cells, ergo the immune system. Such molecules could in the future be the basis for intervention studies that are now (necessarily) restricted to a limited number of bacterial species. For this transition, it might be prudent to develop an ex vivo human model of a local mucosal immune system to better and safer explore the impact of such molecules. With this approach, we might move beyond association toward understanding of causality.

Pulmonary function 3-6 months after acute COVID-19: A systematic review and multicentre cohort study.

Aims: To describe pulmonary function 3-6 months following acute COVID-19, to evaluate potential predictors of decreased pulmonary function and to review literature for the effect of COVID-19 on pulmonary function. Materials and methods: A systematic review and cohort study were conducted. Within the P4O2 COVID-19 cohort, 95 patients aged 40-65 years were recruited from outpatient post-COVID-19 clinics in five Dutch hospitals between May 2021-September 2022. At 3-6 months post COVID-19, medical records data and biological samples were collected and questionnaires were administered. In addition, pulmonary function tests (PFTs), including spirometry and transfer factor, were performed. To identify factors associated with PFTs, linear regression analyses were conducted, adjusted for covariates. Results: In PFTs (n = 90), mean ± SD % of predicted was 89.7 ± 18.2 for forced vital capacity (FVC) and 79.8 ± 20.0 for transfer factor for carbon monoxide (DLCO). FVC was

Exhaled breath analyses for bronchial thermoplasty in severe asthma patients.

BACKGROUND: Bronchial thermoplasty (BT) is a bronchoscopic treatment for severe asthma. Although multiple trials have demonstrated clinical improvement after BT, optimal patient selection remains a challenge and the mechanism of action is incompletely understood. The aim of this study was to examine whether exhaled breath analysis can contribute to discriminate between BT-responders and non-responders at baseline and to explore pathophysiological insights of BT. METHODS: Exhaled breath was collected from patients at baseline and six months post-BT. Patients were defined as responders or non-responders based on a half point increase in asthma quality of life questionnaire scores. Gas chromatography-mass spectrometry was used for volatile organic compounds (VOCs) detection and analyses. Analytical workflow consisted of: 1) detection of VOCs that differentiate between responders and non-responders and those that differ between baseline and six months post-BT, 2) identification of VOCs of interest and 3) explore correlations between clinical biomarkers and VOCs. RESULTS: Data was available from 14 patients. Nonanal, 2-ethylhexanol and 3-thujol showed a significant difference in intensity between responders and non-responders at baseline (p = 0.04, p = 0.01 and p = 0.03, respectively). After BT, no difference was found in the compound intensity of these VOCs. A negative correlation was observed between nonanal and IgE and BALF eosinophils (r = -0.68, p < 0.01 and r = -0.61, p = 0.02 respectively) and 3-thujol with BALF neutrophils (r = -0.54, p = 0.04). CONCLUSIONS: This explorative study identified discriminative VOCs in exhaled breath between BT responders and non-responders at baseline. Additionally, correlations were found between VOC's and inflammatory BALF cells. Once validated, these findings encourage research in breath analysis as a non-invasive easy to apply technique for identifying airway inflammatory profiles and eligibility for BT or immunotherapies in severe asthma.

Fatigue and symptom-based clusters in post COVID-19 patients: a multicentre, prospective, observational cohort study.

BACKGROUND: In the Netherlands, the prevalence of post COVID-19 condition is estimated at 12.7% at 90-150 days after SARS-CoV-2 infection. This study aimed to determine the occurrence of fatigue and other symptoms, to assess how many patients meet the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) criteria, to identify symptom-based clusters within the P4O2 COVID-19 cohort and to compare these clusters with clusters in a ME/CFS cohort. METHODS: In this multicentre, prospective, observational cohort in the Netherlands, 95 post COVID-19 patients aged 40-65 years were included. Data collection at 3-6 months after infection included demographics, medical history, questionnaires, and a medical examination. Follow-up assessments occurred 9-12 months later, where the same data were collected. Fatigue was determined with the Fatigue Severity Scale (FSS), a score of ≥ 4 means moderate to high fatigue. The frequency and severity of other symptoms and the percentage of patients that meet the ME/CFS criteria were assessed using the DePaul Symptom Questionnaire-2 (DSQ-2). A self-organizing map was used to visualize the clustering of patients based on severity and frequency of 79 symptoms. In a previous study, 337 Dutch ME/CFS patients were clustered based on their symptom scores. The symptom scores of post COVID-19 patients were applied to these clusters to examine whether the same or different clusters were found. RESULTS: According to the FSS, fatigue was reported by 75.9% of the patients at 3-6 months after infection and by 57.1% of the patients 9-12 months later. Post-exertional malaise, sleep disturbances, pain, and neurocognitive symptoms were also frequently reported, according to the DSQ-2. Over half of the patients (52.7%) met the Fukuda criteria for ME/CFS, while fewer patients met other ME/CFS definitions. Clustering revealed specific symptom patterns and showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort, where 2 clusters had > 10 patients. CONCLUSIONS: This study shows persistent fatigue and diverse symptomatology in post COVID-19 patients, up to 12-18 months after SARS-CoV-2 infection. Clustering showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort.

Reframing sepsis immunobiology for translation: towards informative subtyping and targeted immunomodulatory therapies.

Sepsis is a common and deadly condition. Within the current model of sepsis immunobiology, the framing of dysregulated host immune responses into proinflammatory and immunosuppressive responses for the testing of novel treatments has not resulted in successful immunomodulatory therapies. Thus, the recent focus has been to parse observable heterogeneity into subtypes of sepsis to enable personalised immunomodulation. In this Personal View, we highlight that many fundamental immunological concepts such as resistance, disease tolerance, resilience, resolution, and repair are not incorporated into the current sepsis immunobiology model. The focus for addressing heterogeneity in sepsis should be broadened beyond subtyping to encompass the identification of deterministic molecular networks or dominant mechanisms. We explicitly reframe the dysregulated host immune responses in sepsis as altered homoeostasis with pathological disruption of immune-driven resistance, disease tolerance, resilience, and resolution mechanisms. Our proposal highlights opportunities to identify novel treatment targets and could enable successful immunomodulation in the future.

International Care programs for Pediatric Post-COVID Condition (Long COVID) and the way forward.

BACKGROUND: Pediatric Post-COVID-Condition (PPCC) clinics treat children despite limited scientific substantiation. By exploring real-life management of children diagnosed with PPCC, the International Post-COVID-Condition in Children Collaboration (IP4C) aimed to provide guidance for future PPCC care. METHODS: We performed a cross-sectional international, multicenter study on used PPCC definitions; the organization of PPCC care programs and patients characteristics. We compared aggregated data from PPCC cohorts and identified priorities to improve PPCC care. RESULTS: Ten PPCC care programs and six COVID-19 follow-up research cohorts participated. Aggregated data from 584 PPCC patients was analyzed. The most common symptoms included fatigue (71%), headache (55%), concentration difficulties (53%), and brain fog (48%). Severe limitations in daily life were reported in 31% of patients. Most PPCC care programs organized in-person visits with multidisciplinary teams. Diagnostic testing for respiratory and cardiac morbidity was most frequently performed and seldom abnormal. Treatment was often limited to physical therapy and psychological support. CONCLUSIONS: We found substantial heterogeneity in both the diagnostics and management of PPCC, possibly explained by scarce scientific evidence and lack of standardized care. We present a list of components which future guidelines should address, and outline priorities concerning PPCC care pathways, research and international collaboration. IMPACT: Pediatric Post-COVID Condition (PPCC) Care programs have been initiated in many countries. Children with PPCC in different countries are affected by similar symptoms, limiting many to participate in daily life. There is substantial heterogeneity in diagnostic testing. Access to specific diagnostic tests is required to identify some long-term COVID-19 sequelae. Treatments provided were limited to physical therapy and psychological support. This study emphasizes the need for evidence-based diagnostics and treatment of PPCC. The International Post-COVID Collaboration for Children (IP4C) provides guidance for guideline development and introduces a framework of priorities for PPCC care and research, to improve PPCC outcomes.

A BEAT-PCD consensus statement: a core outcome set for pulmonary disease interventions in primary ciliary dyskinesia.

Background: Consistent use of reliable and clinically appropriate outcome measures is a priority for clinical trials, with clear definitions to allow comparability. We aimed to develop a core outcome set (COS) for pulmonary disease interventions in primary ciliary dyskinesia (PCD). Methods: A multidisciplinary international PCD expert panel was set up. A list of outcomes was created based on published literature. Using a modified three-round e-Delphi technique, the panel was asked to decide on relevant end-points related to pulmonary disease interventions and how they should be reported. First, inclusion of an outcome in the COS was determined. Second, the minimum information that should be reported per outcome. The third round finalised statements. Consensus was defined as ≥80% agreement among experts. Results: During the first round, experts reached consensus on four out of 24 outcomes to be included in the COS. Five additional outcomes were discussed in subsequent rounds for their use in different subsettings. Consensus on standardised methods of reporting for the COS was reached. Spirometry, health-related quality-of-life scores, microbiology and exacerbations were included in the final COS. Conclusion: This expert consensus resulted in a COS for clinical trials on pulmonary health among people with PCD.

The effects of the COVID-19 pandemic on PICU admissions for severe asthma exacerbations: A single-center experience.

BACKGROUND: The incidence of severe asthma exacerbations (SAE) requiring a pediatric intensive care unit (PICU) admission during the coronavirus disease 2019 (COVID-19) pandemic (and its association with public restrictions) is largely unknown. We examined the trend of SAE requiring PICU admission before, during, and after COVID-19 restrictions in Amsterdam, the Netherlands, and its relationship with features such as environmental triggers and changes in COVID-19 restriction measures. METHODS: In this single-center, retrospective cohort study, all PICU admissions of children aged ≥2 years for severe asthma at the Amsterdam UMC between 2018 and 2022 were included. The concentrations of ambient fine particulate matter (PM2.5 ) and pollen were obtained from official monitoring stations. RESULTS: Between January 2018 and December 2022, 228 children were admitted to the PICU of the Amsterdam UMC for SAE. While we observed a decrease in admissions during periods of more stringent restriction, there was an increase in the PICU admission rate for SAE in some periods following the lifting of restrictions. In particular, following the COVID-19 restrictions in 2021, we observed a peak incidence of admissions from August to November, which was higher than any other peak during the indicated years. No association with air pollution or pollen was observed. CONCLUSION: We hypothesize that an increase in clinically diagnosed viral infections after lockdown periods was the reason for the altered incidence of SAE at the PICU in late 2021, rather than air pollution and pollen concentrations.

Associations between spirometric impairments and microvascular complications in type 2 diabetes: a cross-sectional study.

OBJECTIVE: Evidence shows that the conventional cardiometabolic risk factors do not fully explain the burden of microvascular complications in type 2 diabetes (T2D). One potential factor is the impact of pulmonary dysfunction on systemic microvascular injury. We assessed the associations between spirometric impairments and systemic microvascular complications in T2D. DESIGN: Cross-sectional study. SETTING: National Diabetes Management and Research Centre in Ghana. PARTICIPANTS: The study included 464 Ghanaians aged ≥35 years with established diagnosis of T2D without primary myocardial disease or previous/current heart failure. Participants were excluded if they had primary lung disease including asthma or chronic obstructive pulmonary disease. PRIMARY AND SECONDARY OUTCOME MEASURES: The associations of spirometric measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC ratio) with microvascular complications (nephropathy (albumin-creatinine ratio ≥3 mg/g), neuropathy (vibration perception threshold ≥25 V and/or Diabetic Neuropathy Symptom score >1) and retinopathy (based on retinal photography)) were assessed using multivariable logistic regression models with adjustments for age, sex, diabetes duration, glycated haemoglobin concentration, suboptimal blood pressure control, smoking pack years and body mass index. RESULTS: In age and sex-adjusted models, lower Z-score FEV1 was associated with higher odds of nephropathy (OR 1.55, 95% CI 1.19-2.02, p=0.001) and neuropathy (1.27 (1.01-1.65), 0.038) but not retinopathy (1.22 (0.87-1.70), 0.246). Similar observations were made for the associations of lower Z-score FVC with nephropathy (1.54 (1.19-2.01), 0.001), neuropathy (1.25 (1.01-1.54), 0.037) and retinopathy (1.19 (0.85-1.68), 0.318). In the fully adjusted model, the associations remained significant for only lower Z-score FEV1 with nephropathy (1.43 (1.09-1.87), 0.011) and neuropathy (1.34 (1.04-1.73), 0.024) and for lower Z-score FVC with nephropathy (1.45 (1.11-1.91), 0.007) and neuropathy (1.32 (1.03-1.69), 0.029). Lower Z-score FEV1/FVC ratio was not significantly associated with microvascular complications in age and sex and fully adjusted models. CONCLUSION: Our study shows positive but varying strengths of associations between pulmonary dysfunction and microvascular complications in different circulations. Future studies could explore the mechanisms linking pulmonary dysfunction to microvascular complications in T2D.

Exhaled volatile organic compounds associated with risk factors for obstructive pulmonary diseases: a systematic review.

Background: Asthma and COPD are among the most common respiratory diseases. To improve the early detection of exacerbations and the clinical course of asthma and COPD new biomarkers are needed. The development of noninvasive metabolomics of exhaled air into a point-of-care tool is an appealing option. However, risk factors for obstructive pulmonary diseases can potentially introduce confounding markers due to altered volatile organic compound (VOC) patterns being linked to these risk factors instead of the disease. We conducted a systematic review and presented a comprehensive list of VOCs associated with these risk factors. Methods: A PRISMA-oriented systematic search was conducted across PubMed, Embase and Cochrane Libraries between 2000 and 2022. Full-length studies evaluating VOCs in exhaled breath were included. A narrative synthesis of the data was conducted, and the Newcastle-Ottawa Scale was used to assess the quality of included studies. Results: The search yielded 2209 records and, based on the inclusion/exclusion criteria, 24 articles were included in the qualitative synthesis. In total, 232 individual VOCs associated with risk factors for obstructive pulmonary diseases were found; 58 compounds were reported more than once and 12 were reported as potential markers of asthma and/or COPD in other studies. Critical appraisal found that the identified studies were methodologically heterogeneous and had a variable risk of bias. Conclusion: We identified a series of exhaled VOCs associated with risk factors for asthma and/or COPD. Identification of these VOCs is necessary for the further development of exhaled metabolites-based point-of-care tests in these obstructive pulmonary diseases.

Neutrophil extracellular trap production and CCL4L2 expression influence corticosteroid response in asthma.

The association between neutrophil extracellular traps (NETs) and response to inhaled corticosteroids (ICS) in asthma is unclear. To better understand this relationship, we analyzed the blood transcriptomes from children with controlled and uncontrolled asthma in the Taiwanese Consortium of Childhood Asthma Study using weighted gene coexpression network analysis and pathway enrichment methods. We identified 298 uncontrolled asthma-specific differentially expressed genes and one gene module associated with neutrophil-mediated immunity, highlighting a potential role for neutrophils in uncontrolled asthma. We also found that NET abundance was associated with nonresponse to ICS in patients. In a neutrophilic airway inflammation murine model, steroid treatment could not suppress neutrophilic inflammation and airway hyperreactivity. However, NET disruption with deoxyribonuclease I (DNase I) efficiently inhibited airway hyperreactivity and inflammation. Using neutrophil-specific transcriptomic profiles, we found that CCL4L2 was associated with ICS nonresponse in asthma, which was validated in human and murine lung tissue. CCL4L2 expression was also negatively correlated with pulmonary function change after ICS treatment. In summary, steroids fail to suppress neutrophilic airway inflammation, highlighting the potential need to use alternative therapies such as leukotriene receptor antagonists or DNase I that target the neutrophil-associated phenotype. Furthermore, these results highlight CCL4L2 as a potential therapeutic target for individuals with asthma refractory to ICS.

Haemophilus influenzae and Moraxella catarrhalis in sputum of severe asthma with inflammasome and neutrophil activation.

BACKGROUND: Because of altered airway microbiome in asthma, we analysed the bacterial species in sputum of patients with severe asthma. METHODS: Whole genome sequencing was performed on induced sputum from non-smoking (SAn) and current or ex-smoker (SAs/ex) severe asthma patients, mild/moderate asthma (MMA) and healthy controls (HC). Data were analysed by asthma severity, inflammatory status and transcriptome-associated clusters (TACs). RESULTS: α-diversity at the species level was lower in SAn and SAs/ex, with an increase in Haemophilus influenzae and Moraxella catarrhalis, and Haemophilus influenzae and Tropheryma whipplei, respectively, compared to HC. In neutrophilic asthma, there was greater abundance of Haemophilus influenzae and Moraxella catarrhalis and in eosinophilic asthma, Tropheryma whipplei was increased. There was a reduction in α-diversity in TAC1 and TAC2 that expressed high levels of Haemophilus influenzae and Tropheryma whipplei, and Haemophilus influenzae and Moraxella catarrhalis, respectively, compared to HC. Sputum neutrophils correlated positively with Moraxella catarrhalis and negatively with Prevotella, Neisseria and Veillonella species and Haemophilus parainfluenzae. Sputum eosinophils correlated positively with Tropheryma whipplei which correlated with pack-years of smoking. α- and ß-diversities were stable at one year. CONCLUSIONS: Haemophilus influenzae and Moraxella catarrhalis were more abundant in severe neutrophilic asthma and TAC2 linked to inflammasome and neutrophil activation, while Haemophilus influenzae and Tropheryma whipplei were highest in SAs/ex and in TAC1 associated with highest expression of IL-13 type 2 and ILC2 signatures with the abundance of Tropheryma whipplei correlating positively with sputum eosinophils. Whether these bacterial species drive the inflammatory response in asthma needs evaluation.