Distinct effects of asthma and COPD comorbidity on disease expression and outcome in patients with COVID-19.

BACKGROUND: The impacts of chronic airway diseases on coronavirus disease 2019 (COVID-19) are far from understood. OBJECTIVE: To explore the influence of asthma and chronic obstructive pulmonary disease (COPD) comorbidity on disease expression and outcomes, and the potential underlying mechanisms in COVID-19 patients. METHODS: A total of 961 hospitalized COVID-19 patients with a definite clinical outcome (death or discharge) were retrospectively enrolled. Demographic and clinical information were extracted from the medical records. Lung tissue sections from patients suffering from lung cancer were used for immunohistochemistry study of angiotensin-converting enzyme II (ACE2) expression. BEAS-2B cell line was stimulated with various cytokines. RESULTS: In this cohort, 21 subjects (2.2%) had COPD and 22 (2.3%) had asthma. After adjusting for confounding factors, COPD patients had higher risk of developing severe illness (OR: 23.433; 95% CI 1.525-360.135; P < .01) and acute respiratory distress syndrome (OR: 19.762; 95% CI 1.461-267.369; P = .025) than asthmatics. COPD patients, particularly those with severe COVID-19, had lower counts of CD4+ T and CD8+ T cells and B cells and higher levels of TNF-α, IL-2 receptor, IL-10, IL-8, and IL-6 than asthmatics. COPD patients had increased, whereas asthmatics had decreased ACE2 protein expression in lower airways, compared with that in control subjects without asthma and COPD. IL-4 and IL-13 downregulated, but TNF-α, IL-12, and IL-17A upregulated ACE2 expression in BEAS-2B cells. CONCLUSION: Patients with asthma and COPD likely have different risk of severe COVID-19, which may be associated with different ACE2 expression.

Antibody dynamics to SARS-CoV-2 in asymptomatic COVID-19 infections.

BACKGROUND: The missing asymptomatic COVID-19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. MEASURE: Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty-three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS-CoV-2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. RESULTS: A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS-CoV-2. Different from strong and persistent N-specific antibodies, S1-specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. CONCLUSION: Our findings might have important implications for the definition of asymptomatic COVID-19 infections, diagnosis, serological survey, public health, and immunization strategies.

[Effect of Guben Zenggu Decoction on Expressions of Serum BALP and CaM, CaMKâ ¡ mRNA in NEI Network of Ovariectomized Rats].

OBJECTIVE: To observe the effect of Guben Zenggu Decoction on the expressions of calmodulin (CaM) and calcium/calmodulin-dependent protein kinase Ⅱ (CaMK Ⅱ) mRNA in the hypothalamus, pituitary, spleen, adrenal gland and femur in ovariectomized rats. To explore the mechanism of Guben Zenggu Decoction regulating and controlling osteoporosis through neuro-endocrine-immune (NEI) network. METHODS: The osteoporosis model was established by ovariectomy and randomly divided into model control group, Estradiol valerate group, Guben Zenggu Decoction high, medium and low concentration group. Selected the same age rats as the blank control group, after intervention, 10 rats were randomly selected at the time of 4th, 8th, 12th and 16th weeks from each group, After the success of the model and the successful intervention of Guben Zenggu Decoction for 4, 8, 12 and 16 weeks, the blood were taken from the heart, the serum bone alkaline phosphatase (BALP) levels was measured by the enzyme-linked immunosorbent assay (ELISA), and the thalamus, pituitary, spleen, adrenal, femoral tissue of rats were collected to detected the expressions of CaM and CaMKⅡ mRNA by using real-time fluorescence quantitative polymerase chain reaction (RT-PCR). RESULTS: At different time points (4 weeks, 8 weeks, 12 weeks, 16 weeks), the expressions of serum BALP and CaM and CaMKⅡ mRNA in NEI network in model group were significantly different from those in blank control group ( P<0.05). Compared with the model control group, serum BALP concentration and CaM mRNA expression in hypothalamus and pituitary tissue were significantly increased in estradiol valerate and Guben Zenggu Decoction groups ( P<0.05). However, the expression of CaM mRNA in adrenal gland, spleen and femur and the expression of CaMKⅡ mRNA in hypothalamus, pituitary, adrenal gland, spleen and femur were significantly decreased ( P<0.05); compared with estradiol valerate group, the effect of Guben Zenggu Decoction on the expressions of CaM mRNA and CaMKⅡ mRNA in femoral and adrenal tissues was significantly different ( P<0.05). CONCLUSION: Guben Zenggu Decoction can increase the serum concentration of BALP, regulate the expression of CaM mRNA and CaMKⅡ mRNA in hypothalamus, pituitary, adrenal gland, spleen and femur, thus play a role in prevention and treatment of osteoporosis by regulating NEI network.

The impact of mgrA on progression of Staphylococcus aureus sepsis.

Sepsis induced by Staphylococcus aureus has worse outcome with the appearance of methicillin-resistant Staphylococcus aureus (MRSA) because of multi-resistance to a large group of antibiotics, which may lead to death from septic shock. Pathogenesis of S. aureus infections are involved in the production of a wide variety of virulence factors. MgrA, a noval global regulator, is a member of the MarR (multiple antibiotic resistance regulator)/SarA (staphylococcal accessory regulator A) family proteins, which plays a key role in regulating the expression of major virulence factors in S. aureus. In the present study, by using a murine model of sepsis, we investigated the role of mgrA in onset and progression of S. aureus induced sepsis. We found that mice inoculated with wild-type strain Newman had significantly higher mortality (p = 0.029), more weight lost, more bacterial load in blood, spleen and kidney, more intense inflammation response, and worse histopathology than mice inoculated with mgrA knockout strain. Our results has provided evidence that mgrA is a global regulator in S. aureus, and play an important role in S. aureus sepsis, could increase mortality and accelerate the onset and development of sepsis.

T cell receptor ß repertoires in patients with COVID-19 reveal disease severity signatures.

Background: The immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are crucial in maintaining a delicate balance between protective effects and harmful pathological reactions that drive the progression of coronavirus disease 2019 (COVID-19). T cells play a significant role in adaptive antiviral immune responses, making it valuable to investigate the heterogeneity and diversity of SARS-CoV-2-specific T cell responses in COVID-19 patients with varying disease severity. Methods: In this study, we employed high-throughput T cell receptor (TCR) ß repertoire sequencing to analyze TCR profiles in the peripheral blood of 192 patients with COVID-19, including those with moderate, severe, or critical symptoms, and compared them with 81 healthy controls. We specifically focused on SARS-CoV-2-associated TCR clonotypes. Results: We observed a decrease in the diversity of TCR clonotypes in COVID-19 patients compared to healthy controls. However, the overall abundance of dominant clones increased with disease severity. Additionally, we identified significant differences in the genomic rearrangement of variable (V), joining (J), and VJ pairings between the patient groups. Furthermore, the SARS-CoV-2-associated TCRs we identified enabled accurate differentiation between COVID-19 patients and healthy controls (AUC > 0.98) and distinguished those with moderate symptoms from those with more severe forms of the disease (AUC > 0.8). These findings suggest that TCR repertoires can serve as informative biomarkers for monitoring COVID-19 progression. Conclusions: Our study provides valuable insights into TCR repertoire signatures that can be utilized to assess host immunity to COVID-19. These findings have important implications for the use of TCR ß repertoires in monitoring disease development and indicating disease severity.

Anti-SARS-CoV-2 IgG responses are powerful predicting signatures for the outcome of COVID-19 patients.

Introduction: The COVID-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for early predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies evolved with disease progression and severity in COIVD-19 patients. Objectives: We assumed that antibodies may serve as biomarkers for predicting the clinical outcome of hospitalized COVID-19 patients on admission. Methods: By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgG responses against 20 proteins of SARS-CoV-2 in 1034 hospitalized COVID-19 patients on admission and followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality. Results: Nonsurvivors (n = 955) induced higher levels of IgG responses against most of non-structural proteins than survivors (n = 79) on admission. In particular, the magnitude of IgG antibodies against 8 non-structural proteins (NSP1, NSP4, NSP7, NSP8, NSP9, NSP10, RdRp, and NSP14) and 2 accessory proteins (ORF3b and ORF9b) possessed significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory biomarkers for disease severity (all with p trend < 0.05). Additionally, IgG responses to all of these 10 non-structural/accessory proteins were also associated with the severity of disease, and differential kinetics and serum positive rate of these IgG responses were confirmed in COVID-19 patients of varying severities within 20 days after symptoms onset. The area under curves (AUCs) for these IgG responses, determined by computational cross-validations, were between 0.62 and 0.71. Conclusions: Our findings might have important implications for improving clinical management of COVID-19 patients.

5-Hydroxymethylcytosine Signatures in Circulating Cell-Free DNA as Early Warning Biomarkers for COVID-19 Progression and Myocardial Injury.

Background: The symptoms of coronavirus disease 2019 (COVID-19) range from moderate to critical conditions, leading to death in some patients, and the early warning indicators of the COVID-19 progression and the occurrence of its serious complications such as myocardial injury are limited. Methods: We carried out a multi-center, prospective cohort study in three hospitals in Wuhan. Genome-wide 5-hydroxymethylcytosine (5hmC) profiles in plasma cell-free DNA (cfDNA) was used to identify risk factors for COVID-19 pneumonia and develop a machine learning model using samples from 53 healthy volunteers, 66 patients with moderate COVID-19, 99 patients with severe COVID-19, and 38 patients with critical COVID-19. Results: Our warning model demonstrated that an area under the curve (AUC) for 5hmC warning moderate patients developed into severe status was 0.81 (95% CI 0.77-0.85) and for severe patients developed into critical status was 0.92 (95% CI 0.89-0.96). We further built a warning model on patients with and without myocardial injury with the AUC of 0.89 (95% CI 0.84-0.95). Conclusion: This is the first study showing the utility of 5hmC as an accurate early warning marker for disease progression and myocardial injury in patients with COVID-19. Our results show that phosphodiesterase 4D and ten-eleven translocation 2 may be important markers in the progression of COVID-19 disease.

Application of ImmunoScore Model for the Differentiation between Active Tuberculosis and Latent Tuberculosis Infection as Well as Monitoring Anti-tuberculosis Therapy.

Tuberculosis (TB) is a leading global public health problem. To achieve the end TB strategy, non-invasive markers for diagnosis and treatment monitoring of TB disease are urgently needed, especially in high-endemic countries such as China. Interferon-gamma release assays (IGRAs) and tuberculin skin test (TST), frequently used immunological methods for TB detection, are intrinsically unable to discriminate active tuberculosis (ATB) from latent tuberculosis infection (LTBI). Thus, the specificity of these methods in the diagnosis of ATB is dependent upon the local prevalence of LTBI. The pathogen-detecting methods such as acid-fast staining and culture, all have limitations in clinical application. ImmunoScore (IS) is a new promising prognostic tool which was commonly used in tumor. However, the importance of host immunity has also been demonstrated in TB pathogenesis, which implies the possibility of using IS model for ATB diagnosis and therapy monitoring. In the present study, we focused on the performance of IS model in the differentiation between ATB and LTBI and in treatment monitoring of TB disease. We have totally screened five immunological markers (four non-specific markers and one TB-specific marker) and successfully established IS model by using Lasso logistic regression analysis. As expected, the IS model can effectively distinguish ATB from LTBI (with a sensitivity of 95.7% and a specificity of 92.1%) and also has potential value in the treatment monitoring of TB disease.

Differences in the arbuscular mycorrhizal fungi-improved rice resistance to low temperature at two N levels: aspects of N and C metabolism on the plant side.

We performed an experiment to determine how N and C metabolism is involved in the low-temperature tolerance of mycorrhizal rice (Oryza sativa) at different N levels and examined the possible signaling molecules involved in the stress response of mycorrhizal rice. Pot cultures were performed, and mycorrhizal rice growth was evaluated based on treatments at two temperatures (15 °C and 25 °C) and two N levels (20 mg pot(-1) and 50 mg pot(-1)). The arbuscular mycorrhizal fungi (AMF) colonization of rice resulted in different responses of the plants to low and high N levels. The mycorrhizal rice with the low N supplementation had more positive feedback from the symbiotic AMF, as indicated by accelerated N and C metabolism of rice possibly involving jasmonic acid (JA) and the up-regulation of enzyme activities for N and C metabolism. Furthermore, the response of the mycorrhizal rice plants to low temperature was associated with P uptake and nitric oxide (NO).