Epidemiology, Symptomatology, and Risk Factors for Long COVID Symptoms: Population-Based, Multicenter Study.

BACKGROUND: Long COVID induces a substantial global burden of disease. The pathogenesis, complications, and epidemiological and clinical characteristics of patients with COVID-19 in the acute phase have been evaluated, while few studies have characterized the epidemiology, symptomatology, and risk factors of long COVID symptoms. Its characteristics among patients with COVID-19 in the general population remain unaddressed. OBJECTIVE: We examined the prevalence of long COVID symptoms, its symptom patterns, and its risk factors in 4 major Chinese cities in order to fill the knowledge gap. METHODS: We performed a population-based, multicenter survey using a representative sampling strategy via the Qualtrics platform in Beijing, Shanghai, Guangzhou, and Hong Kong in June 2022. We included 2712 community-dwelling patients with COVID-19 and measured the prevalence of long COVID symptoms defined by the World Health Organization (WHO), and their risk factors. The primary outcomes were the symptoms of long COVID, with various levels of impact. A descriptive analysis of the prevalence and distribution of long COVID symptoms according to disease severity was conducted. A sensitivity analysis of increasing the number of long COVID symptoms was also conducted. Univariate and multivariate regression analyses were performed to examine the risk factors of severe long COVID symptoms, including age, gender, marital status, current occupation, educational level, living status, smoking habits, monthly household income, self-perceived health status, the presence of chronic diseases, the use of chronic medication, COVID-19 vaccination status, and the severity of COVID-19. RESULTS: The response rate was 63.6% (n=2712). The prevalence of long COVID, moderate or severe long COVID, and severe long COVID was 90.4% (n=2452), 62.4% (n=1692), and 31.0% (n=841), respectively. Fatigue (n=914, 33.7%), cough (n=865, 31.9%), sore throat (n=841, 31.0%), difficulty in concentrating (n=828, 30.5%), feeling of anxiety (n=817, 30.2%), myalgia (n=811, 29.9%), and arthralgia (n=811, 29.9%) were the most common severe long COVID symptoms. From multivariate regression analysis, female gender (adjusted odds ratio [aOR]=1.49, 95% CI 1.13-1.95); engagement in transportation, logistics, or the discipline workforce (aOR=2.52, 95% CI 1.58-4.03); living with domestic workers (aOR=2.37, 95% CI 1.39-4.03); smoking (aOR=1.55, 95% CI 1.17-2.05); poor or very poor self-perceived health status (aOR=15.4, 95% CI 7.88-30.00); ≥3 chronic diseases (aOR=2.71, 95% CI 1.54-4.79); chronic medication use (aOR=4.38, 95% CI 1.66-11.53); and critical severity of COVID-19 (aOR=1.52, 95% CI 1.07-2.15) were associated with severe long COVID. Prior vaccination with ≥2 doses of COVID-19 vaccines was a protective factor (aOR=0.35-0.22, 95% CI 0.08-0.90). CONCLUSIONS: We examined the prevalence of long COVID symptoms in 4 Chinese cities according to the severity of COVID-19. We also evaluated the pattern of long COVID symptoms and their risk factors. These findings may inform early identification of patients with COVID-19 at risk of long COVID and planning of rehabilitative services.

Multi-kingdom gut microbiota analyses define COVID-19 severity and post-acute COVID-19 syndrome.

Our knowledge of the role of the gut microbiome in acute coronavirus disease 2019 (COVID-19) and post-acute COVID-19 is rapidly increasing, whereas little is known regarding the contribution of multi-kingdom microbiota and host-microbial interactions to COVID-19 severity and consequences. Herein, we perform an integrated analysis using 296 fecal metagenomes, 79 fecal metabolomics, viral load in 1378 respiratory tract samples, and clinical features of 133 COVID-19 patients prospectively followed for up to 6 months. Metagenomic-based clustering identifies two robust ecological clusters (hereafter referred to as Clusters 1 and 2), of which Cluster 1 is significantly associated with severe COVID-19 and the development of post-acute COVID-19 syndrome. Significant differences between clusters could be explained by both multi-kingdom ecological drivers (bacteria, fungi, and viruses) and host factors with a good predictive value and an area under the curve (AUC) of 0.98. A model combining host and microbial factors could predict the duration of respiratory viral shedding with 82.1% accuracy (error ± 3 days). These results highlight the potential utility of host phenotype and multi-kingdom microbiota profiling as a prognostic tool for patients with COVID-19.

Antibiotics and probiotics impact gut antimicrobial resistance gene reservoir in COVID-19 patients.

Dysbiosis of gut microbiota is well-described in patients with coronavirus 2019 (COVID-19), but the dynamics of antimicrobial resistance genes (ARGs) reservoir, known as resistome, is less known. Here, we performed longitudinal fecal metagenomic profiling of 142 patients with COVID-19, characterized the dynamics of resistome from diagnosis to 6 months after viral clearance, and reported the impact of antibiotics or probiotics on the ARGs reservoir. Antibiotic-naive patients with COVID-19 showed increased abundance and types, and higher prevalence of ARGs compared with non-COVID-19 controls at baseline. Expansion in resistome was mainly driven by tetracycline, vancomycin, and multidrug-resistant genes and persisted for at least 6 months after clearance of SARS-CoV-2. Patients with expanded resistome exhibited increased prevalence of Klebsiella sp. and post-acute COVID-19 syndrome. Antibiotic treatment resulted in further increased abundance of ARGs whilst oral probiotics (synbiotic formula, SIM01) significantly reduced the ARGs reservoir in the gut microbiota of COVID-19 patients during the acute infection and recovery phase. Collectively, these findings shed new insights on the dynamic of ARGs reservoir in COVID-19 patients and the potential role of microbiota-directed therapies in reducing the burden of accumulated ARGs.

SARS-CoV-2 non-structural protein 6 triggers NLRP3-dependent pyroptosis by targeting ATP6AP1.

A recent mutation analysis suggested that Non-Structural Protein 6 (NSP6) of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a key determinant of the viral pathogenicity. Here, by transcriptome analysis, we demonstrated that the inflammasome-related NOD-like receptor signaling was activated in SARS-CoV-2-infected lung epithelial cells and Coronavirus Disease 2019 (COVID-19) patients' lung tissues. The induction of inflammasomes/pyroptosis in patients with severe COVID-19 was confirmed by serological markers. Overexpression of NSP6 triggered NLRP3/ASC-dependent caspase-1 activation, interleukin-1ß/18 maturation, and pyroptosis of lung epithelial cells. Upstream, NSP6 impaired lysosome acidification to inhibit autophagic flux, whose restoration by 1α,25-dihydroxyvitamin D3, metformin or polydatin abrogated NSP6-induced pyroptosis. NSP6 directly interacted with ATP6AP1, a vacuolar ATPase proton pump component, and inhibited its cleavage-mediated activation. L37F NSP6 variant, which was associated with asymptomatic COVID-19, exhibited reduced binding to ATP6AP1 and weakened ability to impair lysosome acidification to induce pyroptosis. Consistently, infection of cultured lung epithelial cells with live SARS-CoV-2 resulted in autophagic flux stagnation, inflammasome activation, and pyroptosis. Overall, this work supports that NSP6 of SARS-CoV-2 could induce inflammatory cell death in lung epithelial cells, through which pharmacological rectification of autophagic flux might be therapeutically exploited.

Lysosome activation in peripheral blood mononuclear cells and prognostic significance of circulating LC3B in COVID-19.

Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide, causing significant mortality. There is a mechanistic relationship between intracellular coronavirus replication and deregulated autophagosome-lysosome system. We performed transcriptome analysis of peripheral blood mononuclear cells (PBMCs) from COVID-19 patients and identified the aberrant upregulation of genes in the lysosome pathway. We further determined the capability of two circulating markers, namely microtubule-associated proteins 1A/1B light chain 3B (LC3B) and (p62/SQSTM1) p62, both of which depend on lysosome for degradation, in predicting the emergence of moderate-to-severe disease in COVID-19 patients requiring hospitalization for supplemental oxygen therapy. Logistic regression analyses showed that LC3B was associated with moderate-to-severe COVID-19, independent of age, sex and clinical risk score. A decrease in LC3B concentration <5.5 ng/ml increased the risk of oxygen and ventilatory requirement (adjusted odds ratio: 4.6; 95% CI: 1.1-22.0; P = 0.04). Serum concentrations of p62 in the moderate-to-severe group were significantly lower in patients aged 50 or below. In conclusion, lysosome function is deregulated in PBMCs isolated from COVID-19 patients, and the related biomarker LC3B may serve as a novel tool for stratifying patients with moderate-to-severe COVID-19 from those with asymptomatic or mild disease. COVID-19 patients with a decrease in LC3B concentration <5.5 ng/ml will require early hospital admission for supplemental oxygen therapy and other respiratory support.