Next-Generation Sequencing and Proteomics of Cerebrospinal Fluid From COVID-19 Patients With Neurological Manifestations.

The SARS-CoV-2 and its variants are still hitting the world. Ever since the outbreak, neurological involvements as headache, ageusia, and anosmia in COVID-19 patients have been emphasized and reported. But the pathogenesis of these new-onset neurological manifestations in COVID-19 patients is still obscure and controversial. As difficulty always lay in the diagnosis of neurological infection, current reports to validate the presence of SARS-CoV-2 in cerebrospinal fluid (CSF) almost relied on the basic methods and warranted improvement. Here we reported a case series of 8 patients with prominent new-onset neurological manifestations, who were screened out from a patch of 304 COVID-19 confirmed patients. Next-generation sequencing (NGS) and proteomics were conducted in the simultaneously obtained CSF and serum samples of the selected patients, with three non-COVID-19 patients with matched demographic features used as the controls for proteomic analysis. SARS-CoV-2 RNA was detected in the CSF of four COVID-19 patients and was suspicious in the rest four remaining patients by NGS, but was negative in all serum samples. Proteomic analysis revealed that 185 and 59 proteins were differentially expressed in CSF and serum samples, respectively, and that only 20 proteins were shared, indicating that the proteomic changes in CSF were highly specific. Further proteomic annotation highlighted the involvement of complement system, PI3K-Akt signaling pathway, enhanced cellular interaction, and macrophages in the CSF proteomic alterations. This study, equipped with NGS and proteomics, reported a high detection rate of SARS-CoV-2 in the CSF of COVID-19 patients and the proteomic alteration of CSF, which would provide insights into understanding the pathological mechanism of SARS-CoV-2 CNS infection.

Inpatient use of metformin and acarbose is associated with reduced mortality of COVID-19 patients with type 2 diabetes mellitus.

AIMS: Type 2 diabetes mellitus (T2DM) is a strong risk factor for complications of coronavirus disease 2019 (COVID-19). The effect of T2DM medications on COVID-19 outcomes remains unclear. In a retrospective analysis of a cohort of 131 patients with T2DM hospitalized for COVID-19 in Wuhan, we have previously found that metformin use prior to hospitalization is associated with reduced mortality. The current study aims to investigate the effects of inpatient use of T2DM medications, including metformin, acarbose, insulin and sulfonylureas, on the mortality of COVID-19 patients with T2DM during hospitalization. METHODS: We continue to carry out a retrospective analysis of a cohort of 131 patients with T2DM hospitalized for COVID-19 and treated with different combinations of diabetes medications. RESULTS: We found that patients using metformin (p = .02) and acarbose (p = .04), alone or both together (p = .03), after admission were significantly more likely to survive than those who did not use either metformin or acarbose. 37 patients continued to take metformin after admission and 35 (94.6%) survived. Among the 57 patients who used acarbose after admission, 52 survived (91.2%). A total of 20 patients used both metformin and acarbose, while 57 used neither. Of the 20 dual-use patients, 19 (95.0%) survived. CONCLUSION: Our analyses suggest that inpatient use of metformin and acarbose together or alone during hospitalization should be studied in randomized trials.

Metformin Use in Diabetes Prior to Hospitalization: Effects on Mortality in Covid-19.

OBJECTIVE: Although type 2 diabetes mellitus (T2DM) has been reported as a risk factor for coronavirus disease 2019 (COVID-19), the effect of pharmacologic agents used to treat T2DM, such as metformin, on COVID-19 outcomes remains unclear. Metformin increases the expression of angiotensin converting enzyme 2, a known receptor for severe acute respiratory syndrome coronavirus 2. Data from people with T2DM hospitalized for COVID-19 were used to test the hypothesis that metformin use is associated with improved survival in this population. METHODS: Retrospective analyses were performed on de-identified clinical data from a major hospital in Wuhan, China, that included patients with T2DM hospitalized for COVID-19 during the recent epidemic. One hundred and thirty-one patients diagnosed with COVID-19 and T2DM were used in this study. The primary outcome was mortality. Demographic, clinical characteristics, laboratory data, diabetes medications, and respiratory therapy data were also included in the analysis. RESULTS: Of these 131 patients, 37 used metformin with or without other antidiabetes medications. Among the 37 metformin-taking patients, 35 (94.6%) survived and 2 (5.4%) did not survive. The mortality rates in the metformin-taking group versus the non-metformin group were 5.4% (2/37) versus 22.3% (21/94). Using multivariate analysis, metformin was found to be an independent predictor of survival in this cohort (P = .02). CONCLUSION: This study reveals a significant association between metformin use and survival in people with T2DM diagnosed with COVID-19. These clinical data are consistent with potential benefits of the use of metformin for COVID-19 patients with T2DM.

Worldwide inverse correlation between Bacille Calmette-Guérin (BCG) immunization and COVID-19 mortality.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has spread to all countries in the world, and different countries have been impacted differently. The study aims to understand what factors contribute to different COVID-19 impacts at the country level. METHODS: Multivariate statistical analyses were used to evaluate COVID-19 deaths and cases relative to nine other demographic and socioeconomic factors in all countries and regions of the world using data as of August 1, 2020. The factors analyzed in the study include a country's total COVID-19 deaths and cases per million population, per capita gross domestic product (GDP), population density, virus tests per million population, median age, government response stringency index, hospital beds availability per thousand population, extreme poverty rate, Bacille Calmette-Guérin (BCG) vaccination rate, and diphtheria-tetanus-pertussis (DTP3) immunization rate. RESULTS: The study reveals that COVID-19 deaths per million population in a country most significantly correlates, inversely, with the country's BCG vaccination rate (r = - 0.50, p = 5.3e-5), and also significantly correlates a country's per capita GDP (r = 0.39, p = 7.4e-3) and median age (r = 0.30, p = 0.042), while COVID-19 cases per million population significantly correlate with per capita GDP and tests per thousand population. To control for possible confounding effects of age, the correlation was assessed in countries propensity score matched for age. The inverse correlation between BCG vaccination rates and COVID-19 case (r = - 0.30, p = 0.02) and death (r = - 0.42, p = 0.0007) remained significant among the top 61 countries with the highest median age. CONCLUSION: This study contributes to a growing body of evidence supporting the notion that BCG vaccination may be protective against COVID-19 mortality.

Worldwide inverse correlation between Bacille Calmette-Guérin immunization and COVID-19 morbidity and mortality.

The COVID-19 pandemic has spread to all countries in the world after more than six months since it was first reported in late 2019, and different countries have been impacted differently. Correlation analysis between COVID-19 death numbers and different demographic and socioeconomic factors for all world countries (n=210) as of June 1, 2020, reveals that COVID-19 deaths per million population in a country significantly correlates with the country's median age (r=0.48, p=4.8e-4) and per capita gross domestic product (GDP) (r=0.55, p=4.14e-5), and inversely correlates with the country's Bacille Calmette-Guérin (BCG) vaccination rate (r=-0.63, p=9.9e-7). COVID-19 death is found not significantly associated, however, with a country's policy stringency index, population density, extreme poverty rate, hospital beds availability per thousand people, and diphtheria-tetanus-pertussis (DTP3) immunization. Old age is likely a confounding factor for the correlation between COVID-19 and per capita GDP (r=0.66, p=2.3e-7). To control for possible confounding effects of age, countries with similar median age were grouped and analyzed. The inverse correlation between BCG vaccination rates and COVID-19 case (r=-0.338, p=0.0082) and death (r=-0.411, p=0.0011) remained significant among the top 61 countries with highest median age. The current study suggests that BCG might be protective against SARS-CoV-2 infection.