Patient phenotypes and their relation to TNFα signaling and immune cell composition in critical illness and autoimmune disease (preprint)

RationaleTNF inhibitors have shown promise in reducing mortality in hospitalized COVID-19 patients; one hypothesis explaining the limited clinical efficacy is patient heterogeneity in the TNF pathway. MethodsWe evaluated the effect of TNF inhibitors in a mouse model of LPS-induced acute lung injury. Using machine learning we attempted predictive enrichment of TNF signaling in patients with either ARDS or sepsis. We examined biological factors that drive heterogeneity in host responses to critical infection and their relation to clinical outcomes. ResultsIn mice, LPS induced TNF-dependent neutrophilia, alveolar permeability and endothelial injury. In humans, TNF pathway activation was significantly increased in peripheral blood of patients with critical illnesses and associated with the presence of mature neutrophils across critical illnesses and several autoimmune conditions. Machine learning using a gene signature separated patients into 5 phenotypes; one was a hyper-inflammatory, interferon-associated phenotype enriched for increased TNF pathway activation and conserved across critical illnesses and autoimmune diseases. Cell subset profiles segregated severely ill patients into neutrophil-subset-dependent groups that were enriched for disease severity, demonstrating the importance of neutrophils in the immune response in critical illness. ConclusionsTNF signaling and mature neutrophils are associated with a hyper-inflammatory phenotype of patients, shared across critical illness and autoimmune disease. This phenotyping provides a personalized medicine hypothesis to test anti-TNF therapy in severe respiratory illness. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/564631v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1e25724org.highwire.dtl.DTLVardef@c708bcorg.highwire.dtl.DTLVardef@10e7531org.highwire.dtl.DTLVardef@3014b8_HPS_FORMAT_FIGEXP M_FIG C_FIG

Development and validation of predictive models for mortality and length of hospitalisation in adults with community-onset bacteraemia under the COVID-19 pandemic: Application of early data dynamics (preprint)

Background Bacteraemia is associated with increased morbidity and mortality and contributes substantially to healthcare costs. The development of a scoring system to predict the short-term mortality and the length of hospitalisation (LOS) in patients with bacteraemia is essential to improve quality of care and reduce variance in hospital bed occupancy.Methods This multicentre study of patients hospitalised with community-onset bacteraemia retrospectively enrolled derivation and validation cohorts in the pre-COVID-19 and COVID-19 eras. This study developed five models to compare the performances of various scoring algorithms. Model I incorporated all variables available on day 0, Model II incorporated all variables available on day 3, and Models III, IV, and V incorporated the variables that changed from day 0 to day 3. This study adopted the statistical and machine learning (ML) methods to determine the crucial determinants of 30-day mortality and LOS in patients with community-onset bacteraemia, respectively.Results A total of 3,639 (81.4%) and 834 (18.6%) patients were included in the derivation and validation cohorts, respectively. Model IV best predicted 30-day mortality in both cohorts; it achieved the best performance (i.e., the largest area under the receiver operating characteristic [ROC] curve) according to the results of the logistic regression and most ML methods. The most frequently identified variables incorporated into Model IV were deteriorated consciousness from day 0 to day 3 and deteriorated respiration from day 0 to day 3. The generalised linear models and the majorities of ML methods also identified Model V as having the best performance (i.e., the lowest mean square error) in predicting LOS. The most frequently identified variables incorporated into Model V were deteriorated consciousness from day 0 to day 3, a body temperature ≤ 36.0°C or ≥ 39.0°C on day 3, and a diagnosis of complicated bacteraemia.Conclusions For hospitalised adults with community-onset bacteraemia, clinical variables that dynamically changed from day 0 to day 3 were crucial in predicting both the short-term mortality and their LOS.

The impact of alcoholic drinks and dietary factors on epigenetic markers associated with triglyceride levels (preprint)

Background: Although current evidence shows that environmental and lifestyle factors are associated with DNA methylation patterns, mechanisms underlying the relationship between diet and other exposures and epigenetic profiles remain to be fully described. To clarify the unique connections between dietary intake and lifestyle factors on disease risk, we conducted epigenetic mapping of diet and lifestyle habits for plasma triglyceride concentrations (TG) by investigating links between lifestyle, including diet, and methylation marks with TG. Methods: We first conducted an epigenome-wide association study (EWAS) for TG in the Framingham Heart Study Offspring population (n=2,178). We then examined the relationships between dietary and lifestyle-related variables, collected over 13 years, and differential DNA methylation sites (DMSs) associated with the last TG measures (exam 8). Second, we conducted a mediation analysis to evaluate causal relationships between diet-related variables and TG. Results: The EWAS revealed 28 TG-associated DMSs at 19 regions (e.g., ABCG1, CPT1A, DHCR24, GARS, NCORS, PFKFB3, PHGDH, PPP2R2B, RNF145, SARS, SLC1A5, SLC43A1, SLC7A11 SREBF1, TXNIP, ZFHX3). After accounting for multiple testing, we identified 427 significant associations (representative of 102 unique associations) between these DMSs and one or more dietary and lifestyle-related variables. The most significant and consistent associations between 11 TG-associated DMSs and diet were alcohol and carbohydrate intake (% total energy), with P-values ranging from 2.89E-04 to 8.37E-70. Mediation analyses demonstrated that alcohol and carbohydrate intake independently affect TG via DMSs as mediators. For seven of the 19 identified DMS regions, higher alcohol intake was associated with lower methylation and higher TG. In contrast, increased carbohydrate intake was associated with higher DNA methylation at two epigenetic loci (CPT1A and SLC7A11) and lower TG. Conclusions: Our findings imply that TG-associated DMSs reflect dietary intakes that could affect cardiometabolic disease risk via epigenetic changes, specifically through their impact on DNA methylation.

Direct activation of endothelial cells by SARS-CoV-2 nucleocapsid protein is blocked by Simvastatin (preprint)

ABSTRACT Emerging evidence suggests that endothelial activation plays a central role in the pathogenesis of acute respiratory distress syndrome (ARDS) and multi-organ failure in patients with COVID-19. However, the molecular mechanisms underlying endothelial activation in COVID-19 patients remain unclear. In this study, the SARS-CoV-2 viral proteins that potently activate human endothelial cells were screened to elucidate the molecular mechanisms involved with endothelial activation. It was found that nucleocapsid protein (NP) of SARS-CoV-2 significantly activated human endothelial cells through TLR2/NF-κB and MAPK signaling pathways. Moreover, by screening a natural microbial compound library containing 154 natural compounds, simvastatin was identified as a potent inhibitor of NP-induced endothelial activation. Remarkablely, though the protein sequences of N proteins from coronaviruses are highly conserved, only NP from SARS-CoV-2 induced endothelial activation. The NPs from other coronaviruses such as SARS-CoV, MERS-CoV, HUB1-CoV and influenza virus H1N1 did not affect endothelial activation. These findings are well consistent with the results from clinical investigations showing broad endotheliitis and organ injury in severe COVID-19 patients. In conclusion, the study provides insights on SARS-CoV-2-induced vasculopathy and coagulopathy, and suggests that simvastatin, an FDA-approved lipid-lowering drug, may benefit to prevent the pathogenesis and improve the outcome of COVID-19 patients.

Strategies for Supplying Face Masks to the Population of Taiwan During the COVID-19 Pandemic. (preprint)

Background The use of face masks has become ubiquitous in Taiwan during the early COVID-19 pandemic. A name-based rationing system was established to enable the population of Taiwan to purchase face masks. This study is to assess the extent and fairness of face mask supply to the public in Taiwan.Methods The weekly face marks supplies were collected from name-based rationing system administrative statistics included national health insurance card and e-Mask selling record. National registered population statistics by age, gender, and district were collected from department of statistics ministry of the interior. The number of COVID-19 non-imported cases of Taiwan was collected from Taiwan centers of disease control.Results A total of 146,831,844 person times purchase records from February 6, 2020, to July 19, 2020, the weekly average face mask supply is 0.5 mask (per person) at the start of name-based rationing system, and gradually expanded to the maximum 5.1 masks (per person). Comparing the highest weekly total face mask supply (from Apr 9, 2020, to Apr 15, 2020) in aged 0–9 -, 10–19 -, 20–29 -, 30–39 -, 40–49 -, 50–69 -, 60–69 -,70–79 -, 80–89 -, 90–99, and > 100 years to the register population showed similar distribution between mask supplied people and total population (all standardized difference < 0.1).Conclusions The masks supply strategies has gradually escalated the number of face masks for the public, it not only has dominant decreased the barrier of acquiring face mask, but a fair supply for total population use of Taiwan.

Strategies for Supplying Face Masks to the Population of Taiwan During the COVID-19 Pandemic (preprint)

Background: The use of face masks has become ubiquitous in Taiwan during the COVID-19 pandemic. A name-based rationing system was established to enable the population of Taiwan to purchase affordable medical face masks on-site and on the electronic platform (eMask). This study is to assess the extent and fairness of face mask supply to the public during the COVID-19 pandemic in Taiwan.Methods: This was a retrospective longitudinal study. The weekly face mask supply statistics were collected from name-based rationing system administration and included the National Health Insurance Card and eMask selling records. National registered population statistics by age, gender, and district were collected from the Ministry of the Interior Department of Statistics.Findings: Purchase records showed that the weekly average face mask supply was 0·5 mask per person at the beginning of the name-based rationing system and gradually increased to a maximum of 5·1 masks per person. Comparing monthly total face mask supply in aged 0-9,10-19, 20-59, and aged ≥60 years to the register population in Taiwan, exception first month implementation, the other period showed a similar distribution of mask supply to that to the total population. Comparing the highest weekly face mask supply among 0–9, 10–19, 20–29, 30–39, 40–49, 50–69, 60–69, 70–79, 80–89, 90–99, and ≥100 years age groups showed a similar distribution of mask supply to the total population.Interpretation: This study showed that mask supply ensured fair distribution throughout the population of Taiwan.Funding Statement: None.Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: Using de-identified data, this study was exempt from informed consent.