Comparative single-cell analysis reveals IFN-γ as a driver of respiratory sequelae post COVID-19 (preprint)

Post-acute sequelae of SARS-CoV-2 infection (PASC) represents an urgent public health challenge, with its impact resonating in over 60 million individuals globally. While a growing body of evidence suggests that dysregulated immune reactions may be linked with PASC symptoms, most investigations have primarily centered around blood studies, with few focusing on samples derived from post-COVID affected tissues. Further, clinical studies alone often provide correlative insights rather than causal relationships. Thus, it is essential to compare clinical samples with relevant animal models and conduct functional experiments to truly understand the etiology of PASC. In this study, we have made comprehensive comparisons between bronchoalveolar lavage fluid (BAL) single-cell RNA sequencing (scRNAseq) data derived from clinical PASC samples and relevant PASC mouse models. This revealed a strong pro-fibrotic monocyte-derived macrophage response in respiratory PASC (R-PASC) in both humans and mice, and abnormal interactions between pulmonary macrophages and respiratory resident T cells. IFN-g emerged as a key node mediating the immune anomalies in R-PASC. Strikingly, neutralizing IFN-g post the resolution of acute infection reduced lung inflammation, tissue fibrosis, and improved pulmonary gas-exchange function in two mouse models of R-PASC. Our study underscores the importance of performing comparative analysis to understand the root cause of PASC for developing effective therapies.

Proximal immune-epithelial progenitor interactions drive chronic tissue sequelae post COVID-19 (preprint)

The long-term health effects of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are quickly evolving into a major public health concern, but the underlying cellular and molecular etiology remain poorly defined. There is growing evidence that PASC is linked to abnormal immune responses and/or poor organ recovery post-infection. However, the exact processes linking non-resolving inflammation, impaired tissue repair, and PASC are still unclear. In this report, we utilized a cohort of respiratory PASC patients with viral infection-mediated pulmonary fibrosis and a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. Using a combination of imaging and spatial transcriptomics, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell-macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, and the development of fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-{gamma} and TNF stimulated lung macrophages to chronically release IL-1{beta}, resulting in the abnormal accumulation of dysplastic epithelial progenitors in fibrotic areas. Notably, therapeutic neutralization of IFN-{gamma} and TNF, or IL-1{beta} after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC and identify potential therapeutic targets to dampen chronic pulmonary sequelae post respiratory viral infections including SARS-CoV-2.

Evaluation on College Students' Anxiety and Social Media Usage during Shanghai Closure

As COVID-19 mutates, the highly infectious omicron mutants (BA. 5.2., BF. 7) tension shrouded China. Given the internet information explosion and youth social media addiction, observing the mental impact on college students during the 2022 Shanghai closure is worthwhile. A pilot survey study was conducted to explore the anxiety levels of college students during the closure. The sample size was limited to 101 second-year college students. In addition to demographics, the survey involved the Self-Rating Anxiety Scale, self-perceived COVID-19 anxiety, frequency of COVID-19 information reception, number of social media accounts, and number of electronic devices. Though 68.4% of students equipped with two electronic devices (N = 95) exceeded the students with only one electronic device, a Chi-square test showed that students with only one electronic device had the highest anxiety index (mean = 50). Further, the Kruskal-Wallis test indicated that the number of electronic devices affected the students' anxiety level (p = 0.027) while social media membership did not (p = 0.565). As a result, it was suggested that social media usage and pandemic information inputs among college students were significant concerns that required special attention from the government, schools, teachers, and families.

Individualism Versus Collectivism and the Early-Stage Transmission of COVID-19.

We propose a perspective based on the individualism versus collectivism (IC) cultural distinction to understand the diverging early-stage transmission outcomes of COVID-19 between countries. Since individualism values personal freedom, people in such cultures would be less likely to make the collective action of staying at home and less likely to support compulsory measures. As a reaction to the public will, governments of individualistic societies would be more hesitant to take compulsory measures, leading to the delay of necessary responses. With processed COVID-19 data that can provide a fair comparison, we find that COVID-19 spread much faster in more individualistic societies than in more collectivistic societies. We further use pronoun drop and absolute latitude as the instruments for IC to address reverse causality and omitted variable bias. The results are robust to different measures. We propose to consider the role of IC not only for understanding the current pandemic but also for thinking about future trends in the world.

Immuno-inflammatory Characters in Low Severity COVID-19 Patients with Digestive Symptoms (preprint)

Background: Coronavirus disease 2019 (COVID-19) is an emerged infection raised widely concerns for pneumonia and respiratory manifestations. It is noteworthy that digestive symptoms are frequently observed in COVID-19 patients. We sought to describe the immune-inflammatory characteristics of COVID-19 patients with digestive symptoms and mild disease severity.Methods: We designated enrolled mild patients into three subtypes depending on the patients with or without digestive symptoms, including Digestive only (digestive symptoms only), Respiratory only (respiratory symptoms only) and Digestive+ Respiratory (Both digestive and respiratory symptoms). Patient discharge was based on negative results of rRT-PCR testing for SARS-CoV-2 from at least two sequential respiratory tract specimens collected ≥24 hours apart. The multiorgan function, immune-inflammatory characteristics were analyzed among three groups.Results: Mild liver damage and the activation of immuno-inflammatory system are the most abnormalities in mild patients but no significant differences were found (p＞0.05). Compared with the Respiratory only group, patients with digestive symptoms were more likely to have slightly higher and later peak values of inflammatory cytokines during the subsequent course of disease(P＜0.05). Additionally, we also found that there was a significant correlation between IL-2 and TNF level in the Digestive only cases (P＜0.05). Conclusions: Mild patients only/accompanied with digestive symptoms are a special subtype of COVID-19. Patients in this group were more likely to have slightly higher and later peak values of inflammatory cytokines during the subsequent course of disease. The prevention and clinical management of this type should be taken into consideration.  

Dynamic Estimation of Epidemiological Parameters of COVID-19 Outbreak and Effects of Interventions on Its Spread (preprint)

A key challenge for estimating the epidemiological parameters of the COVID-19 out-break in Wuhan is the discrepancy between the officially reported number of infections and the true number of infections. A common approach to tackling the challenge is to use the number of infections exported from Wuhan to infer the true number in the city. This approach can only provide a static estimate of the epidemiological parameters before Wuhan lockdown on January 23, 2020, because there are almost no exported cases thereafter. Here, we propose a method to dynamically estimate the epidemiological parameters of the COVID-19 outbreak in Wuhan by recovering true numbers of infections from day-to-day official numbers. Using the method, we provide a comprehensive retrospection on how the disease had progressed in Wuhan from January 19 to March 5, 2020. Particularly, we estimate that the outbreak sizes by January 23 and March 5 were 11,239 [95% CI 4,794-22,372] and 124,506 [95% CI 69,526-265,113], respectively. The effective reproduction number attained its maximum on January 24 (3.42 [95% CI 3.34-3.50]) and became less than 1 from February 7 (0.76 [95% CI 0.65-0.92]). We also estimate the effects of two major government interventions on the spread of COVID-19 in Wuhan. In particular, transportation suspension and large scale hospitalization respectively prevented 33,719 and 90,072 people from getting infected in the nine-day time period right after its implementation.