Faming Zhao

Bio: Faming Zhao is an academic researcher. The author has contributed to research in topics: Medicine & Cancer. The author has an hindex of 1, co-authored 2 publications receiving 1073 citations.

Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China.

Abstract: Studies have reminded that cardiovascular metabolic comorbidities made patients more susceptible to suffer 2019 novel corona virus (2019-nCoV) disease (COVID-19), and exacerbated the infection. The aim of this analysis is to determine the association of cardiovascular metabolic diseases with the development of COVID-19. A meta-analysis of eligible studies that summarized the prevalence of cardiovascular metabolic diseases in COVID-19 and compared the incidences of the comorbidities in ICU/severe and non-ICU/severe patients was performed. Embase and PubMed were searched for relevant studies. A total of six studies with 1527 patients were included in this analysis. The proportions of hypertension, cardia-cerebrovascular disease and diabetes in patients with COVID-19 were 17.1%, 16.4% and 9.7%, respectively. The incidences of hypertension, cardia-cerebrovascular diseases and diabetes were about twofolds, threefolds and twofolds, respectively, higher in ICU/severe cases than in their non-ICU/severe counterparts. At least 8.0% patients with COVID-19 suffered the acute cardiac injury. The incidence of acute cardiac injury was about 13 folds higher in ICU/severe patients compared with the non-ICU/severe patients. Patients with previous cardiovascular metabolic diseases may face a greater risk of developing into the severe condition and the comorbidities can also greatly affect the prognosis of the COVID-19. On the other hand, COVID-19 can, in turn, aggravate the damage to the heart.

Inhibiting the IRE1α Axis of the Unfolded Protein Response Enhances the Antitumor Effect of AZD1775 in TP53 Mutant Ovarian Cancer

Abstract: Targeting the G2/M checkpoint mediator WEE1 has been explored as a novel treatment strategy in ovarian cancer, but mechanisms underlying its efficacy and resistance remains to be understood. Here, it is demonstrated that the WEE1 inhibitor AZD1775 induces endoplasmic reticulum stress and activates the protein kinase RNA‐like ER kinase (PERK) and inositol‐required enzyme 1α (IRE1α) branches of the unfolded protein response (UPR) in TP53 mutant (mtTP53) ovarian cancer models. This is facilitated through NF‐κB mediated senescence‐associated secretory phenotype. Upon AZD1775 treatment, activated PERK promotes apoptotic signaling via C/EBP‐homologous protein (CHOP), while IRE1α‐induced splicing of XBP1 (XBP1s) maintains cell survival by repressing apoptosis. This leads to an encouraging synergistic antitumor effect of combining AZD1775 and an IRE1α inhibitor MKC8866 in multiple cell lines and preclinical models of ovarian cancers. Taken together, the data reveal an important dual role of the UPR signaling network in mtTP53 ovarian cancer models in response to AZD1775 and suggest that inhibition of the IRE1α‐XBP1s pathway may enhance the efficacy of AZD1775 in the clinics.

Comparison of cardiovascular metabolic characteristics and impact on COVID-19 and MERS.

Abstract: Over the past decade, Middle East Respiratory Syndrome (MERS) coronavirus has emerged in the human population and accounted for a large number of deaths worldwide. In early December 2019, a series of pneumonia cases caused by SARS-CoV-2 emerged in Wuhan, Hubei, China, with the name of coronavirus disease 2019 (COVID-19). Both MERS-CoV and SARS-CoV-2 belong to the Coronavirus genus in the Coronaviridae family. MERS-CoV spread across Africa and East Asia from 2012 and had caused 1600 infections and 574 deaths by 2016, while SARS-CoV-2 has induced 81,099 infections with 3218 deaths in China and 91,216 infections with 3421 deaths outside of China as of 16 March 2020. Both SARSCoV-2 and MERS-CoV target the respiratory tract and share many similar clinical symptoms. Common symptoms include fever, fatigue and dry cough, followed always by anorexia, myalgia, dyspnoea and so on. Lymphopaenia and prolonged prothrombin time are also most common characteristics. Metabolic comorbidities were defined as the presence of one or more of the following conditions known to be associated with obesity: diabetes, hypertension, hypercholesterolaemia or cardiovascular disease. A systematic analysis of 637 MERS-CoV cases showed that diabetes and hypertension are prevalent in about 50% of the patients and cardiac diseases are present in 30% of the cases. With spread of SARS-CoV-2, more and more individuals exhibit comorbidities such as hypertension, diabetes and cardio-cerebrovascular disease. In Chen’s study of 99 cases, 40% of patients had cardiocerebrovascular disease, and in Huang’s study of 41 cases, 20% of patients had diabetes. These cardiovascular metabolic comorbidities might render them more susceptible to poor prognosis. The mechanisms by which coronavirus influences the cardiovascular system include: direct damage to cardiomyocytes by the virus, hypoxaemia and higher-level oxygen support, high concentration of inflammatory factors, repeated floods of catecholamines due to anxiety and the side effects of medication. In addition, studies found that patients with higher N-terminal pro-brain natriuretic peptide level and d-dimer greater than 1 lg/ml had more risk of death. COVID-19 can activate also coagulation cascade, leading to severe hypercoagulability and poor prognosis. Comparing the epidemiological characteristics of MERS and COVID-19 will be helpful for us to understand the characteristics of the novel coronavirus and to carry out targeted treatment. Prevalence of comorbidities including hypertension, diabetes and cardiovascular and cerebrovascular diseases in COVID-19 and MERS (Supplementary Material Tables 1 and 2 and Figure 1 online) together with clinical outcomes (intensive care unit (ICU) admission, death and cardiac injury) were

Effect of evolocumab on the progression of intraplaque neovascularization of the carotid based on contrast-enhanced ultrasonography (EPIC study): A prospective single-arm, open-label study

Abstract: Background and Purpose: The aim of this study was to explore the effect of half a year of evolocumab plus moderate-intensity statin treatment on carotid intraplaque neovascularization (IPN) and blood lipid levels. Methods: A total of 31 patients with 33 carotid plaques who received evolocumab plus statin treatment were included. Blood lipid levels, B-mode ultrasound and contrast-enhanced ultrasonography (CEUS) at baseline and after half a year of evolocumab plus statin therapy were collected. The area under the curve (AUC) reflected the total amount of acoustic developer entering the plaque or lumen within the 180 s measurement period. The enhanced intensity reflected the peak blood flow intensity during the monitoring period, and the contrast agent area reflected the area of vessels in the plaques. Results: Except for high-density lipoprotein cholesterol (HDL-c), all other lipid indices decreased. Compared with baseline, low-density lipoprotein cholesterol (LDL-c) decreased by approximately 57% (p < 0.001); total cholesterol (TC) decreased by approximately 34% (p < 0.001); small dense low-density lipoprotein (sd-LDL) decreased by approximately 52% (p < 0.001); and HDL-c increased by approximately 20% (p < 0.001). B-mode ultrasonography showed that the length and thickness of the plaque and the hypoechoic area ratio were reduced (p < 0.05). The plaque area, calcified area ratio, and lumen cross-sectional area changed little (p > 0.05). CEUS revealed that the area under the curve of plaque/lumen [AUC (P/L)] decreased from 0.27 ± 0.13 to 0.19 ± 0.11 (p < 0.001). The enhanced intensity ratio of plaque/lumen [intensity ratio (P/L)] decreased from 0.37 ± 0.16 to 0.31 ± 0.14 (p = 0.009). The contrast agent area in plaque/area of plaque decreased from 19.20 ± 13.23 to 12.66 ± 9.59 (p = 0.003). The neovascularization score decreased from 2.64 ± 0.54 to 2.06 ± 0.86 (p < 0.001). Subgroup analysis based on statin duration (<6 months and ≥6 months) showed that there was no significant difference in the AUC (P/L) or intensity ratio (P/L) at baseline or after half a year of evolocumab treatment. Conclusion: This study found that evolocumab combined with moderate-intensity statins significantly improved the blood lipid profile and reduced carotid IPN. Clinical Trial Registration: https://www.clinicaltrials.gov; identifier: NCT04423406.

The functional implication of ATF6α in castration‐resistant prostate cancer cells

Abstract: Stress in the endoplasmic reticulum (ER) may perturb proteostasis and activates the unfolded protein response (UPR). UPR activation is frequently observed in cancer cells and is believed to fuel cancer progression. Here, we report that one of the three UPR sensors, ATF6α, was associated with prostate cancer (PCa) development, while both genetic and pharmacological inhibition of ATF6α impaired the survival of castration‐resistance PCa (CRPC) cells. Transcriptomic analyses identified the molecular pathways deregulated upon ATF6α depletion, and also discovered considerable disparity in global gene expression between ATF6α knockdown and Ceapin‐A7 treatment. In addition, combined analyses of human CRPC bulk RNA‐seq and single‐cell RNA‐seq (scRNA‐seq) public datasets confirmed that CRPC tumors with higher ATF6α activity displayed higher androgen receptor (AR) activity, proliferative and neuroendocrine (NE) like phenotypes, as well as immunosuppressive features. Lastly, we identified a 14‐gene set as ATF6α NE gene signature with encouraging prognostic power. In conclusion, our results indicate that ATF6α is correlated with PCa progression and is functionally relevant to CRPC cell survival. Both specificity and efficacy of ATF6α inhibitors require further refinement and evaluation.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Abstract: Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. Design Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. Conclusion Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

Abstract: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Postmortem examination of COVID-19 patients reveals diffuse alveolar damage with severe capillary congestion and variegated findings in lungs and other organs suggesting vascular dysfunction.

Abstract: Aims Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly evolved into a sweeping pandemic. Its major manifestation is in the respiratory tract, and the general extent of organ involvement and the microscopic changes in the lungs remain insufficiently characterised. Autopsies are essential to elucidate COVID-19-associated organ alterations. Methods and results This article reports the autopsy findings of 21 COVID-19 patients hospitalised at the University Hospital Basel and at the Cantonal Hospital Baselland, Switzerland. An in-corpore technique was performed to ensure optimal staff safety. The primary cause of death was respiratory failure with exudative diffuse alveolar damage and massive capillary congestion, often accompanied by microthrombi despite anticoagulation. Ten cases showed superimposed bronchopneumonia. Further findings included pulmonary embolism (n = 4), alveolar haemorrhage (n = 3), and vasculitis (n = 1). Pathologies in other organ systems were predominantly attributable to shock; three patients showed signs of generalised and five of pulmonary thrombotic microangiopathy. Six patients were diagnosed with senile cardiac amyloidosis upon autopsy. Most patients suffered from one or more comorbidities (hypertension, obesity, cardiovascular diseases, and diabetes mellitus). Additionally, there was an overall predominance of males and individuals with blood group A (81% and 65%, respectively). All relevant histological slides are linked as open-source scans in supplementary files. Conclusions This study provides an overview of postmortem findings in COVID-19 cases, implying that hypertensive, elderly, obese, male individuals with severe cardiovascular comorbidities as well as those with blood group A may have a lower threshold of tolerance for COVID-19. This provides a pathophysiological explanation for higher mortality rates among these patients.

Comorbidity and its Impact on Patients with COVID-19.

Abstract: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in Wuhan, China, in December 2019. Since then, the virus has made its way across the globe to affect over 180 countries. SARS-CoV-2 has infected humans in all age groups, of all ethnicities, both males and females while spreading through communities at an alarming rate. Given the nature of this virus, there is much still to be learned; however, we know that the clinical manifestations range from a common cold to more severe diseases such as bronchitis, pneumonia, severe acute respiratory distress syndrome (ARDS), multi-organ failure, and even death. It is believed that COVID-19, in those with underlying health conditions or comorbidities, has an increasingly rapid and severe progression, often leading to death. This paper examined the comorbid conditions, the progression of the disease, and mortality rates in patients of all ages, infected with the ongoing COVID-19 disease. An electronic literature review search was performed, and applicable data was then collected from peer-reviewed articles published from January to April 20, 2020. From what is known at the moment, patients with COVID-19 disease who have comorbidities, such as hypertension or diabetes mellitus, are more likely to develop a more severe course and progression of the disease. Furthermore, older patients, especially those 65 years old and above who have comorbidities and are infected, have an increased admission rate into the intensive care unit (ICU) and mortality from the COVID-19 disease. Patients with comorbidities should take all necessary precautions to avoid getting infected with SARS CoV-2, as they usually have the worst prognosis.