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ABSTRACT We previously demonstrated that the lungs of deceased COVID-19 patients were filled with a clear hydrogel consisting of hyaluronan (HA). In this translational study, we investigated the role of HA at all stages of COVID-19 disease to map the consequences of elevated HA on morbidity and identify the mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced HA production. A reduced alveolar surface area was observed in the lungs of deceased COVID-19 patients compared to healthy controls, as visualized by a 3D rendering of lung morphology using light-sheet fluorescence microscopy. We confirmed the presence of HA in lung biopsies and found large quantities of proinflammatory fragmented HA. The association of systemic HA in blood plasma and disease severity was assessed in patients with mild (WHO Clinical Progression Scale, WHO-CPS, 1–5) and severe COVID-19 (WHO-CPS, 6–9) during the acute and convalescent phases and related to lung function. We found that systemic levels of HA were high during acute COVID-19 disease, remained elevated during convalescence, and were associated with a reduced diffusion capacity. In vitro 3D-lung models, differentiated from primary human bronchial epithelial cells, were used to study the effects of SARS-CoV-2 infection on HA metabolism, and transcriptomic analyses revealed a dysregulation of HA synthases and hyaluronidases, both contributing to increased HA in apical secretions. Furthermore, corticosteroid treatment reduced the inflammation and downregulated HA synthases. Our findings demonstrate that HA plays a role in COVID-19 morbidity and that sustained elevated HA concentrations may contribute to long-term respiratory impairment.IMPORTANCEThis study provides insights into the role of hyaluronan (HA) in the severity and long-term impact of COVID-19 on lung function. Through extensive morphological examination of lung tissues and a multicenter study, we identified that HA levels are significantly elevated in COVID-19 patients, correlating with a reduced lung diffusion capacity during convalescence. Using a 3D-lung model, we further uncovered how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 infection causes a dysregulated HA metabolism, leading to increased HA production. Our findings provide valuable insights into the pathogenesis of SARS-CoV-2 and suggest that targeting HA metabolism could offer new therapeutic avenues for managing COVID-19, particularly to prevent long-term lung impairment. Additionally, HA holds potential as a biomarker for predicting disease severity, which could guide personalized treatment strategies.

Objectives: To investigate the effectiveness of intravenous immunoglobulin (IVIG) as treatment for COVID-19 in immunocompromised patients. Methods: This retrospective study investigated outcomes for immunocompromised, vaccine non-responsive, patients that between September 2022 and April 2023 received IVIG as treatment for COVID-19 in the region of Västerbotten, Sweden. We analyzed clinical data, viral load, and anti-SARS-CoV-2 IgG binding and neutralization levels of patient serum samples and IVIG production batches. Primary and secondary outcomes were clinical cure and viral clearance, respectively. Results: Sixteen patients were analyzed. After a median COVID-19 duration of 4 weeks, a median 60 g IVIG infusion increased SARS-CoV-2 binding and neutralizing antibody levels, with broad in vitro activity against tested variants. The treatment resulted in abrogation of viremia in all patients and general improvement in 15 survivors that all met the primary endpoint. Thirteen patients met the secondary endpoint at follow-up after a median of four months. Two subjects with persistent SARS-CoV-2 carriage relapsed but were successfully retreated with IVIG. Conclusions: Antibodies in IVIG efficiently neutralized several SARS-CoV-2 variants. Treatment with IVIG was associated with clinical cure and viral clearance in immunocompromised patients. Our data suggests that IVIG could be a novel treatment alternative for COVID-19 for this patient category.

Abstract Background Olfactory dysfunction together with neurological and cognitive symptoms are common after COVID‐19. We aimed to study whether performance on olfactory and neuropsychological tests following infection predict post‐COVID condition (PCC), persisting symptoms, and reduced health‐related quality of life. Methods Both hospitalized (N = 10) and non‐hospitalized individuals (N = 56) were enrolled in this prospective cohort study. Participants were evaluated 1–3 months after infection with an olfactory threshold test and neuropsychological tests, which was used as predictors of PCC. A questionnaire outlining persisting symptoms and the validated instrument EuroQol five‐dimension five‐level for health‐related quality of life assessment were used as outcome data 1 year after infection (N = 59). Principal component analysis was used to identify relevant predictors for PCC at 1 year. Results Objectively assessed olfactory dysfunction at 1–3 months post infection, but not subjective olfactory symptoms, predicted post‐COVID condition with reduced health‐related quality of life (PCC+) at 1 year. The PCC+ group scored more often below the cut off for mild cognitive impairment on the Montreal Cognitive Assessment (61.5% vs. 21.7%) and higher on the Multidimensional Fatigue Inventory‐20, compared to the group without PCC+. Conclusion Our results indicate that objectively assessed, olfactory dysfunction is a predictor for PCC+. These findings underscore the importance of objective olfactory testing. We propose that olfactory screening in the early post‐acute phase of COVID‐19 infection might identify individuals that are at higher risk of developing long‐term health sequalae.

Introduction SARS-CoV-2 infection causes acute COVID-19 and may result in post-COVID syndrome (PCS). We aimed to investigate how clinicians diagnose PCS and identify associated clinical and demographic characteristics.Methods We analysed multiregistry data of all SARS-CoV-2 test-positive individuals in Sweden (n=1 057 174) between 1 February 2020 and 25 May 2021. We described clinical characteristics that prompt PCS diagnosis in outpatient and inpatient settings. In total, there were 6389 individuals with a hospital inpatient or outpatient diagnosis for PCS. To understand symptomatology, we examined individuals diagnosed with PCS at least 3 months after COVID-19 onset (n=6389) and assessed factors associated with PCS diagnosis.Results Mechanical ventilation correlated with PCS (OR 114.7, 95% CI 105.1 to 125.3) compared with no outpatient/inpatient contact during initial COVID-19. Dyspnoea (13.4%), malaise/fatigue (8%) and abnormal pulmonary diagnostic imaging findings (4.3%) were the most common features linked to PCS. We compared clinical features of PCS with matched controls (COVID-19 negative, n=23 795) and COVID-19 severity-matched patients (COVID-19 positive, n=25 556). Hypertension associated with PCS cohort (26.61%) than in COVID-19-negative (OR 17.16, 95% CI 15.23 to 19.3) and COVID-19-positive (OR 9.25, 95% CI 8.41 to 10.16) controls, although most individuals received this diagnosis before COVID-19. Dyspnoea was the second most common feature in the PCS cohort (17.2%), and new to the majority compared with COVID-19-negative (OR 54.16, 95% CI 42.86 to 68.45) and COVID-19-positive (OR 18.7, 95% CI 16.21 to 21.57) controls.Conclusions Our findings highlight factors Swedish physicians associate with PCS.

ABSTRACT Pathogenic bacteria encounter various stressors while residing in the host. They respond through intricate mechanisms of gene expression regulation, ensuring their survival and adaptation. Understanding how bacteria adapt to different stress conditions through regulatory processes of specific genes requires exploring complex transcriptional responses using gene co-expression networks. We employed a large transcriptome data set comprising 32 diverse human bacterial pathogens exposed to the same 11 host-mimicking stress conditions. Using the weighted gene co-expression network analysis algorithm, we generated bacterial gene co-expression networks. By associating modular eigengene expression with specific stress conditions, we identified gene co-expression modules and stress-specific stimulons, including genes with unique expression patterns under specific stress conditions. Suggesting a new potential role of the frm operon in responding to bile stress in enteropathogenic bacteria demonstrates the effectiveness of our approach. We also revealed the regulation of streptolysin S genes, involved in the production, processing, and export of streptolysin S, a toxin responsible for the β-hemolytic phenotype of group A Streptococcus. In a comparative analysis of stress responses in three Escherichia coli strains from the core transcriptome, we revealed shared and unique expression patterns across the strains, offering insights into convergent and divergent stress responses. To help researchers perform similar analyses, we created the user-friendly web application Co-PATHOgenex. This tool aids in deepening our understanding of bacterial adaptation to stress conditions and in deciphering complex transcriptional responses of bacterial pathogens. IMPORTANCE Unveiling gene co-expression networks in bacterial pathogens has the potential for gaining insights into their adaptive strategies within the host environment. Here, we developed Co-PATHOgenex, an interactive and user-friendly web application that enables users to construct networks from gene co-expressions using custom-defined thresholds (https://avicanlab.shinyapps.io/copathogenex/). The incorporated search functions and visualizations within the tool simplify the usage and facilitate the interpretation of the analysis output. Co-PATHOgenex also includes stress stimulons for various bacterial species, which can help identify gene products not previously associated with a particular stress condition.