The clinical and bioinformatics analysis for the role of antihypertension drugs on mortality among patients with hypertension hospitalized with COVID‐19

Zhao, Liyang; Li, Yusi; Yi, Wenjuan; Yan, Kuo; Yang, Chia-Han; Sridhar, R.; Li, Rui; Fan, Gang; Dai, Mengyuan; Liu, Miao; Shao, Ning‐Yi

doi:10.1002/jmv.27914

Cited by 8 publications

(6 citation statements)

References 19 publications

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“…47 Single-cell RNA-Seq datasets in COVID-19 patients suggested that LST1 may play a role in the effect of Angiotensin II receptor blocker on COVID-19-related mortality. 48 Therefore, LST1 not only contributes to predict the COVID-19 outcomes, but also may be a potential COVID-19 treatment target. AGER is also named RAGE, and its plasma protein level was identified to be significantly upregulated in ICU COVID-19 patients compared to controls.…”

Section: Discussionmentioning

confidence: 99%

Shared genetics and causal association between plasma levels of SARS‐CoV‐2 entry receptor ACE2 and Alzheimer's disease

Zhang,

Xu,

Wang

et al. 2024

CNS Neurosci Ther

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BackgroundAlzheimer's disease (AD) is the highest risk of COVID‐19 infection, hospitalization, and mortality. However, it remains largely unclear about the link between AD and COVID‐19 outcomes. ACE2 is an entry receptor for SARS‐CoV‐2. Circulating ACE2 is a novel biomarker of death and associated with COVID‐19 outcomes.MethodsHere, we explored the shared genetics and causal association between AD and plasma ACE2 levels using large‐scale genome‐wide association study, gene expression, expression quantitative trait loci, and high‐throughput plasma proteomic profiling datasets.ResultsWe found a significant causal effect of genetically increased circulating ACE2 on increased risk of AD. Cross‐trait association analysis identified 19 shared genetic variants, and three variants rs3104412, rs2395166, and rs3135344 at chromosome 6p21.32 were associated with COVID‐19 infection, hospitalization, and severity. We mapped 19 variants to 117 genes, which were significantly upregulated in lung, spleen, and small intestine, downregulated in brain tissues, and involved in immune system, immune disease, and infectious disease pathways. The plasma proteins corresponding to LST1, AGER, TNXB, and APOC1 were predominantly associated with COVID‐19 infection, ventilation, and death.ConclusionTogether, our findings suggest the shared genetics and causal association between AD and plasma ACE2 levels, which may partially explain the link between AD and COVID‐19.

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Section: Discussionmentioning

confidence: 99%

Shared genetics and causal association between plasma levels of SARS‐CoV‐2 entry receptor ACE2 and Alzheimer's disease

Zhang,

Xu,

Wang

et al. 2024

CNS Neurosci Ther

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“…New variants of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) are emerging. Although the new variants of SARS‐CoV‐2 are becoming less pathogenic, 1 they appear to be transmitted more rapidly and are still capable of causing widespread epidemics 2 . Influenza viruses can also cause epidemics occasionally 3 .…”

Section: Wild Typea Group (N = 161) Mono‐infection Group Co‐infection...mentioning

confidence: 99%

Effect of serum inflammatory factors in predicting co‐infection with influenza viruses and Omicron

Zhang,

Wang,

Luo

et al. 2024

Immunity Inflam & Disease

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ObjectivesTo identify the key differences in laboratory indicators between mono‐infection and co‐infection by influenza viruses and Omicron to facilitate timely adjustments in patient treatment strategies.MethodsPrealbumin and C‐reactive protein (CRP) levels were analyzed in 161 COVID‐19 cases infected by SARS‐CoV‐2 (wild type), 299 cases infected by Omicron, 95 cases infected by influenza virus A/B (Flu A/B) and 133 co‐infection cases infected with Flu A/B and Omicron. The receiver operating characteristic (ROC) curve and logistic regression equation were used to analyze the clinical predictive capacity of prealbumin and CRP in coinfected patients.ResultsThe co‐infected and wild‐type infected patients had significantly different CRP and prealbumin levels compared to mono‐infected patients with Omicron or Flu A/B (p < .001). The ROC curve results indicated that prealbumin was more efficient than CRP in identifying co‐infection from Omicron (AUC: 0.867 vs. 0.724) or Flu A/B (AUC: 0.797 vs. 0.730), and joint prediction significantly improved the diagnostic ability to discriminate co‐infection from mono‐infection (AUC: 0.934 and 0.887).ConclusionThe findings suggest that prealbumin is a valuable indicator that can warn of co‐infection and guide timely treatment decisions. Joint prediction may offer an even more effective diagnostic tool for discriminating co‐infection from mono‐infection.

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“…Unduly harsh policy may cause inconvenience and huge financial burden. China has the highest proportion of older adults among the countries worldwide, and a large part of this population with underlying health conditions are more vulnerable to COVID-19 [13][14][15][16] .…”

Section: (Which Was Not Certified By Peer Review) Preprintmentioning

confidence: 99%

Is it possible to flatten-the-curve after the initial outbreak of Covid-19? A data-driven modeling analysis for Omicron pandemic in China

SUN

Shao

et al. 2022

Preprint

Self Cite

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In the current coronavirus disease 2019 (COVID-19) pandemic, the Omicron variant of severe acute respiratory syndrome coronavirus 2 has become the predominant strain circulating worldwide. In China, enormous controversies exist regarding the “dynamic zero tolerance” (DZT) and “totally no inventions” (TNI) strategies for preventing the spread of the Omicron variant. Currently, China is gradually relaxing the COVID-19 measures from DZT level. In such situations, the “flatten-the-curve” (FTC) strategy, which decreases and maintains the low rate of infection to avoid overwhelming the healthcare system by adopting relaxed nonpharmaceutical interventions (NPIs) after the initial outbreak, has been perceived as most appropriate and effective method to prevent the spread of the Omicron variant. Hence, we established a data-driven model of Omicron transmission based on the pandemic data of Macau, Hong Kong, and Singapore in 2022 to deduce the overall prevention effect throughout China. In the current immunity level without any NPI applied, more than 12.7 billion (including asymptomatic individuals) were infected with the Omicron variant within 90 days, but the daily new infections sharply declined; moreover, Omicron outbreak would result to 1.49 million deaths within 180 days. The application of FTC could decrease the deaths by 36.91% within 360 days. Age-stratified analyses showed that the NPI application among individuals aged >60 years would also result in 0.81 million deaths within 360 days, and the application of FTC strategy through treatment with anti-COVID drugs can reduce the number of deaths to 0.40 million. In a model of completed vaccination, the application of TNI strategy would also result in 0.56 million deaths and slightly decrease the infection numbers. The strict implementation of FTC policy combined with completed vaccination and drug use, which only resulted in 0.19 million deaths in an age-stratified model, will help end the pandemic within about 240 days. The pandemic would be terminated within a shorter period of time without resulting in a high fatality rate; therefore, the FTC policy could be strictly implemented through enhancement of immunity and drug use.

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The clinical and bioinformatics analysis for the role of antihypertension drugs on mortality among patients with hypertension hospitalized with COVID‐19

Cited by 8 publications

References 19 publications

Shared genetics and causal association between plasma levels of SARS‐CoV‐2 entry receptor ACE2 and Alzheimer's disease

Shared genetics and causal association between plasma levels of SARS‐CoV‐2 entry receptor ACE2 and Alzheimer's disease

Effect of serum inflammatory factors in predicting co‐infection with influenza viruses and Omicron

Is it possible to flatten-the-curve after the initial outbreak of Covid-19? A data-driven modeling analysis for Omicron pandemic in China

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