Cluster analysis unveils a severe persistent respiratory impairment phenotype 3-months after severe COVID-19.

BACKGROUND: The mid-term respiratory sequelae in survivors of severe COVID-19 appear highly heterogeneous. In addition, factors associated with respiratory sequelae are not known. In this monocentric prospective study, we performed a multidisciplinary assessment for respiratory and muscular impairment and psychological distress 3 months after severe COVID-19. We analysed factors associated with severe persistent respiratory impairment, amongst demographic, COVID-19 severity, and 3-month assessment. METHODS: Patients with severe SARS-CoV-2 pneumonia requiring ≥ 4L/min were included for a systematic 3-month visit, including respiratory assessment (symptoms, lung function, CT scan), muscular evaluation (body composition, physical function and activity, disability), psychopathological evaluation (anxiety, depression, post-traumatic stress disorder-PTSD) and quality of life. A cluster analysis was performed to identify subgroups of patients based on objective functional measurements: DLCO, total lung capacity and 6-min walking distance (6MWD). RESULTS: Sixty-two patients were analysed, 39% had dyspnea on exercise (mMRC ≥ 2), 72% had DLCO < 80%, 90% had CT-scan abnormalities; 40% had sarcopenia/pre-sarcopenia and 31% had symptoms of PTSD. Cluster analysis identified a group of patients (n = 18, 30.5%) with a severe persistent (SP) respiratory impairment (DLCO 48 ± 12%, 6MWD 299 ± 141 m). This SP cluster was characterized by older age, severe respiratory symptoms, but also sarcopenia/pre-sarcopenia, symptoms of PTSD and markedly impaired quality of life. It was not associated with initial COVID-19 severity or management. CONCLUSIONS AND CLINICAL IMPLICATION: We identified a phenotype of patients with severe persistent respiratory and muscular impairment and psychological distress 3 months after severe COVID-19. Our results highlight the need for multidisciplinary assessment and management after severe SARS-CoV-2 pneumonia. Trial registration The study was registered on ClinicalTrials.gov (May 6, 2020): NCT04376840.

Nicotinic receptors as SARS-CoV-2 spike co-receptors?

Nicotinic acetylcholine receptors (nAChRs) play an important role in homeostasis and respiratory diseases. Controversies regarding the association between COVID-19 hospitalizations and smoking suggest that nAChRs may contribute to SARS-CoV-2 respiratory syndrome. We recently detailed the expression and localization of all nAChR subunits in the human lung. Since virus association with nAChRs has been shown in the past, we hypothesize that nAChR subunits act as SARS-CoV-2 Spike co-receptors. Based on sequence alignment analysis, we report domains of high molecular similarities in nAChRs with the binding domain of hACE2 for SARS-CoV-2 Spike protein. This hypothesis supported by in silico pilot data provides a rational for the modelling and the in vitro experimental validation of the interaction between SARS-CoV-2 and the nAChRs.

Nicotinic Receptor Subunits Atlas in the Adult Human Lung.

Nicotinic acetylcholine receptors (nAChRs) are pentameric ligand-gated ion channels responsible for rapid neural and neuromuscular signal transmission. Although it is well documented that 16 subunits are encoded by the human genome, their presence in airway epithelial cells (AECs) remains poorly understood, and contribution to pathology is mainly discussed in the context of cancer. We analysed nAChR subunit expression in the human lungs of smokers and non-smokers using transcriptomic data for whole-lung tissues, isolated large AECs, and isolated small AECs. We identified differential expressions of nAChRs in terms of detection and repartition in the three modalities. Smoking-associated alterations were also unveiled. Then, we identified an nAChR transcriptomic print at the single-cell level. Finally, we reported the localizations of detectable nAChRs in bronchi and large bronchioles. Thus, we compiled the first complete atlas of pulmonary nAChR subunits to open new avenues to further unravel the involvement of these receptors in lung homeostasis and respiratory diseases.

A novel ACE2 isoform is expressed in human respiratory epithelia and is upregulated in response to interferons and RNA respiratory virus infection.

Angiotensin-converting enzyme 2 (ACE2) is the main entry point in airway epithelial cells for SARS-CoV-2. ACE2 binding to the SARS-CoV-2 protein spike triggers viral fusion with the cell plasma membrane, resulting in viral RNA genome delivery into the host. Despite ACE2's critical role in SARS-CoV-2 infection, full understanding of ACE2 expression, including in response to viral infection, remains unclear. ACE2 was thought to encode five transcripts and one protein of 805 amino acids. In the present study, we identify a novel short isoform of ACE2 expressed in the airway epithelium, the main site of SARS-CoV-2 infection. Short ACE2 is substantially upregulated in response to interferon stimulation and rhinovirus infection, but not SARS-CoV-2 infection. This short isoform lacks SARS-CoV-2 spike high-affinity binding sites and, altogether, our data are consistent with a model where short ACE2 is unlikely to directly contribute to host susceptibility to SARS-CoV-2 infection.

COVID-19: A qualitative chest CT model to identify severe form of the disease.

PURPOSE: The purpose of this study was to identify clinical and chest computed tomography (CT) features associated with a severe form of coronavirus disease 2019 (COVID-19) and to propose a quick and easy to use model to identify patients at risk of a severe form. MATERIALS AND METHODS: A total of 158 patients with biologically confirmed COVID-19 who underwent a chest CT after the onset of the symptoms were included. There were 84 men and 74 women with a mean age of 68±14 (SD) years (range: 24-96years). There were 100 non-severe and 58 severe cases. Their clinical data were recorded and the first chest CT examination was reviewed using a computerized standardized report. Univariate and multivariate analyses were performed in order to identify the risk factors associated with disease severity. Two models were built: one was based only on qualitative CT features and the other one included a semi-quantitative total CT score to replace the variable representing the extent of the disease. Areas under the ROC curves (AUC) of the two models were compared with DeLong's method. RESULTS: Central involvement of lung parenchyma (P<0.001), area of consolidation (P<0.008), air bronchogram sign (P<0.001), bronchiectasis (P<0.001), traction bronchiectasis (P<0.011), pleural effusion (P<0.026), large involvement of either one of the upper lobes or of the middle lobe (P<0.001) and total CT score≥15 (P<0.001) were more often observed in the severe group than in the non-severe group. No significant differences were found between the qualitative model (large involvement of either upper lobes or middle lobe [odd ratio (OR)=2.473], central involvement [OR=2.760], pleural effusion [OR=2.699]) and the semi-quantitative model (total CT score≥15 [OR=3.342], central involvement [OR=2.344], pleural effusion [OR=2.754]) with AUC of 0.722 (95% CI: 0.638-0.806) vs. 0.739 (95% CI: 0.656-0.823), respectively (P=0.209). CONCLUSION: We have developed a new qualitative chest CT-based multivariate model that provides independent risk factors associated with severe form of COVID-19.