Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation.

BACKGROUND: Long COVID impacts ∼10% of people diagnosed with COVID-19, yet the pathophysiology driving ongoing symptoms is poorly understood. We hypothesised that 129Xe magnetic resonance imaging (MRI) could identify unique pulmonary phenotypic subgroups of long COVID, therefore we evaluated ventilation and gas exchange measurements with cluster analysis to generate imaging-based phenotypes. METHODS: COVID-negative controls and participants who previously tested positive for COVID-19 underwent 129XeMRI ∼14-months post-acute infection across three centres. Long COVID was defined as persistent dyspnea, chest tightness, cough, fatigue, nausea and/or loss of taste/smell at MRI; participants reporting no symptoms were considered fully-recovered. 129XeMRI ventilation defect percent (VDP) and membrane (Mem)/Gas, red blood cell (RBC)/Mem and RBC/Gas ratios were used in k-means clustering for long COVID, and measurements were compared using ANOVA with post-hoc Bonferroni correction. RESULTS: We evaluated 135 participants across three centres: 28 COVID-negative (40±16yrs), 34 fully-recovered (42±14yrs) and 73 long COVID (49±13yrs). RBC/Mem (p=0.03) and FEV1 (p=0.04) were different between long- and COVID-negative; FEV1 and all other pulmonary function tests (PFTs) were within normal ranges. Four unique long COVID clusters were identified compared with recovered and COVID-negative. Cluster1 was the youngest with normal MRI and mild gas-trapping; Cluster2 was the oldest, characterised by reduced RBC/Mem but normal PFTs; Cluster3 had mildly increased Mem/Gas with normal PFTs; and Cluster4 had markedly increased Mem/Gas with concomitant reduction in RBC/Mem and restrictive PFT pattern. CONCLUSION: We identified four 129XeMRI long COVID phenotypes with distinct characteristics. 129XeMRI can dissect pathophysiologic heterogeneity of long COVID to enable personalised patient care.

Single-cell RNA sequencing of bronchoscopy specimens: development of a rapid minimal handling protocol.

Single-cell RNA sequencing (scRNA-seq) is an important tool for understanding disease pathophysiology, including airway diseases. Currently, the majority of scRNA-seq studies in airway diseases have used invasive methods (airway biopsy, surgical resection), which carry inherent risks and thus present a major limitation to scRNA-seq investigation of airway pathobiology. Bronchial brushing, where the airway mucosa is sampled using a cytological brush, is a viable, less invasive method of obtaining airway cells for scRNA-seq. Here we describe the development of a rapid and minimal handling protocol for preparing single-cell suspensions from bronchial brush specimens for scRNA-seq. Our optimized protocol maximizes cell recovery and cell quality and facilitates large-scale profiling of the airway transcriptome at single-cell resolution.

Post-COVID-19 dyspnoea and pulmonary imaging: a systematic review and meta-analysis.

BACKGROUND: A proportion of coronavirus disease 2019 (COVID-19) survivors experience persistent dyspnoea without measurable impairments in lung function. We performed a systematic review and meta-analysis to determine relationships between dyspnoea and imaging abnormalities over time in post-COVID-19 patients. METHODS: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we analysed studies published prior to 15 September 2022 and indexed by Google Scholar, PubMed and LitCOVID which assessed chest imaging in adults ≥3 months after COVID-19. Demographic, chest imaging, spirometric and post-COVID-19 symptom data were extracted. The relationships between imaging abnormalities and dyspnoea, sex and age were determined using a random effects model and meta-regression. RESULTS: 47 studies were included in the meta-analysis (n=3557). The most prevalent computed tomography (CT) imaging abnormality was ground-glass opacities (GGOs) (44.9% (95% CI 37.0-52.9%) at any follow-up time-point). Occurrence of reticulations significantly decreased between early and late follow-up (p=0.01). The prevalence of imaging abnormalities was related to the proportion of patients with dyspnoea (p=0.012). The proportion of females was negatively correlated with the presence of reticulations (p=0.001), bronchiectasis (p=0.001) and consolidations (p=0.025). Age was positively correlated with imaging abnormalities across all modalities (p=0.002) and imaging abnormalities present only on CT (p=0.001) (GGOs (p=0.004) and reticulations (p=0.001)). Spirometric values improved during follow-up but remained within the normal range at all time-points. CONCLUSIONS: Imaging abnormalities were common 3 months after COVID-19 and their occurrence was significantly related to the presence of dyspnoea. This suggests that CT imaging is a sensitive tool for detecting pulmonary abnormalities in patients with dyspnoea, even in the presence of normal spirometric measurements.

COPD and the risk of poor outcomes in COVID-19: A systematic review and meta-analysis.

BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) are highly susceptible from respiratory exacerbations from viral respiratory tract infections. However, it is unclear whether they are at increased risk of COVID-19 pneumonia or COVID-19-related mortality. We aimed to determine whether COPD is a risk factor for adverse COVID-19 outcomes including hospitalization, severe COVID-19, or death. METHODS: Following the PRISMA guidelines, we performed a systematic review of COVID-19 clinical studies published between November 1st, 2019 and January 28th, 2021 (PROSPERO ID: CRD42020191491). We included studies that quantified the number of COPD patients, and reported at least one of the following outcomes stratified by COPD status: hospitalization; severe COVID-19; ICU admission; mechanical ventilation; acute respiratory distress syndrome; or mortality. We meta-analyzed the results of individual studies to determine the odds ratio (OR) of these outcomes in patients with COPD compared to those without COPD. FINDINGS: Fifty-nine studies met the inclusion criteria, and underwent data extraction. Most studies were retrospective cohort studies/case series of hospitalized patients. Only four studies examined the effects of COPD on COVID-19 outcomes as their primary endpoint. In aggregate, COPD was associated with increased odds of hospitalization (OR 4.23, 95% confidence interval [CI] 3.65-4.90), ICU admission (OR 1.35, 95% CI 1.02-1.78), and mortality (OR 2.47, 95% CI 2.18-2.79). INTERPRETATION: Having a clinical diagnosis of COPD significantly increases the odds of poor clinical outcomes in patients with COVID-19. COPD patients should thus be considered a high-risk group, and targeted for preventative measures and aggressive treatment for COVID-19 including vaccination.