Clinical biomarker profiles reveals gender differences and mortality factors in sepsis.

Background: Sepsis is a major contributor to global morbidity and mortality, affecting millions each year. Notwithstanding the decline in sepsis incidence and mortality over decades, gender disparities in sepsis outcomes persist, with research suggesting higher mortality rates in males. Methods: This retrospective study aims to delineate gender-specific clinical biomarker profiles impacting sepsis progression and mortality by examining sepsis cases and related clinical data from the past three years. Propensity score matching was used to select age-matched healthy controls for comparison. Results: Among 265 sepsis patients, a significantly higher proportion were male (60.8%, P<0.001). While mortality did not significantly differ by gender, deceased patients were significantly older (mean 69 vs 43 years, P=0.003), more likely to have hypertension (54% vs 25%, P=0.019), and had higher SOFA scores (mean ~10 vs 4, P<0.01) compared to survivors. Principal Component Analysis (PCA) showed clear separation between sepsis patients and healthy controls. 48 serum biomarkers were significantly altered in sepsis, with Triiodothyronine, Apolipoprotein A, and Serum cystatin C having the highest diagnostic value by ROC analysis. Gender-stratified comparisons identified male-specific (e.g. AFP, HDLC) and female-specific (e.g. Rheumatoid factor, Interleukin-6) diagnostic biomarkers. Deceased patients significantly differed from survivors, with 22 differentially expressed markers; Antithrombin, Prealbumin, HDL cholesterol, Urea nitrogen and Hydroxybutyrate had the highest diagnostic efficiency for mortality. Conclusion: These findings enhance our understanding of gender disparities in sepsis and may guide future therapeutic strategies. Further research is warranted to validate these biomarker profiles and investigate the molecular mechanisms underlying these gender differences in sepsis outcomes.

Peripheral blood indicators and COVID-19: an observational and bidirectional Mendelian randomization study.

Blood is critical for health, supporting key functions like immunity and oxygen transport. While studies have found links between common blood clinical indicators and COVID-19, they cannot provide causal inference due to residual confounding and reverse causality. To identify indicators affecting COVID-19, we analyzed clinical data (n = 2,293, aged 18-65 years) from Guangzhou Medical University's first affiliated hospital (2022-present), identifying 34 significant indicators differentiating COVID-19 patients from healthy controls. Utilizing bidirectional Mendelian randomization analyses, integrating data from over 2.46 million participants from various large-scale studies, we established causal links for six blood indicators with COVID-19 risk, five of which is consistent with our observational findings. Specifically, elevated Troponin I and Platelet Distribution Width levels are linked with increased COVID-19 susceptibility, whereas higher Hematocrit, Hemoglobin, and Neutrophil counts confer a protective effect. Reverse MR analysis confirmed four blood biomarkers influenced by COVID-19, aligning with our observational data for three of them. Notably, COVID-19 exhibited a positive causal relationship with Troponin I (Tnl) and Serum Amyloid Protein A, while a negative association was observed with Plateletcrit. These findings may help identify high-risk individuals and provide further direction on the management of COVID-19.

Gastroesophageal reflux disease with 6 neurodegenerative and psychiatric disorders: Genetic correlations, causality, and potential molecular mechanisms.

The comorbidities between gastroesophageal reflux disease (GERD) and various neurodegenerative and psychiatric disorders have been widely reported. However, the genetic correlations, causal relationships, and underlying mechanisms linking GERD to these disorders remain largely unknown. Here, we conducted a bidirectional Mendelian randomization (MR) analysis to determine the causality between GERD and 6 neurodegenerative and psychiatric disorders. Sensitivity analyses and multivariable MR were performed to test the robustness of our findings. Linkage disequilibrium score regression was used to assess the genetic correlation between these diseases as affected by heredity. Multiple bioinformatics tools combining two machine learning algorithms were applied to further investigate the potential mechanisms underlying these diseases. We found that genetically predicted GERD significantly increased the risk of Alzheimer's disease, major depressive disorder, and anxiety disorders. There might be a bidirectional relationship between GERD and insomnia. GERD has varying degrees of genetic correlations with AD, ALS, anxiety disorders, insomnia, and depressive disorder. Bioinformatics analyses revealed the hub shared genes and the common pathways between GERD and 6 neurodegenerative and psychiatric disorders. Our findings demonstrated the complex nature of the genetic architecture across these diseases and clarified their causality, highlighting that treatments for the cure or remission of GERD may serve as potential strategies for preventing and managing neurodegenerative and psychiatric disorders.

Decoding acute myocarditis in patients with COVID-19: Early detection through machine learning and hematological indices.

During the persistent COVID-19 pandemic, the swift progression of acute myocarditis has emerged as a profound concern due to its augmented mortality, underscoring the urgency of prompt diagnosis. This study analyzed blood samples from 5,230 COVID-19 individuals, identifying key blood and myocardial markers that illuminate the relationship between COVID-19 severity and myocarditis. A predictive model, applying Bayesian and random forest methodologies, was constructed for myocarditis' early identification, unveiling a balanced gender distribution in myocarditis cases contrary to a male predominance in COVID-19 occurrences. Particularly, older men exhibited heightened vulnerability to severe COVID-19 strains. The analysis revealed myocarditis was notably prevalent in younger demographics, and two subvariants COVID-19 progression paths were identified, characterized by symptom intensity and specific blood indicators. The enhanced myocardial marker model displayed remarkable diagnostic accuracy, advocating its valuable application in future myocarditis detection and treatment strategies amidst the COVID-19 crisis.

Association between Atopic Dermatitis and Colorectal Cancer: TET2 as a Shared Gene Signature and Prognostic Biomarker.

Background: Recent studies have linked atopic dermatitis (AD) to colorectal cancer (CRC) risk. Their causality and potential molecular mechanisms remain unclear. Methods: We performed Mendelian randomization (MR) analysis to evaluate the causality between AD and CRC. Summary statistic data-based Mendelian randomization (SMR) analysis was used to identify CRC-related causal genes. Transcriptome analyses and immunohistochemical methods were applied to investigate the shared gene signature and potential mechanisms that contribute to the pathogenesis of both AD and CRC. A predictive analysis was performed to examine the shared gene signature associated with immunotherapy response in CRC. Results: MR analysis indicated a causal association between AD and a decreased risk of CRC. SMR analysis uncovered TET2 as a CRC-related causal gene, showing an inverse relationship with the risk of CRC. Transcriptome analyses identified TET2 as a shared gene signature between AD and CRC. Decreased TET2 expression is associated with impaired demethylation and worse prognosis in CRC patients. We observed ten pathways related to the inflammatory response and immune regulation that may be shared mechanisms underlying both AD and CRC. These findings were validated through single-cell analysis. TET2 shows promise as a powerful predictive biomarker for cancer prognosis and immunotherapy response in CRC. Conclusion: There is a causal association between AD and a decreased risk of CRC. AD may influence the occurrence of CRC by modulating immune and inflammatory responses. TET2 could serve as a potential biomarker for prognosis and may be considered a novel therapeutic target for methylation and immune-related interventions.

The genetic etiology of body fluids on chronic obstructive airways disease.

BACKGROUND: Numerous studies have documented significant alterations in the bodily fluids of Chronic Obstructive Pulmonary Disease (COPD) patients. However, existing literature lacks causal inference due to residual confounding and reverse causality. METHODS: Summary-level data for COPD were obtained from two national biobanks: the UK Biobank, comprising 1,605 cases and 461,328 controls, and FinnGen, with 6,915 cases and 186,723 controls. We also validated our findings using clinical data from 2,690 COPD patients and 3,357 healthy controls from the First Affiliated Hospital of Guangzhou Medical University. A total of 44 bodily fluid biomarkers were selected as candidate risk factors. Mendelian randomization (MR) and meta-analyses were used to evaluate the causal effects of these bodily fluids on COPD and lung function (FEV1/FVC). RESULTS: Mendelian randomization (MR) and meta-analyses, by integrating data from the UK Biobank and FinnGen cohort, found that 3 bodily fluids indicators (HDLC, EOS, and TP) were causally associated with the risk of COPD, two (EOS and TP) of which is consistent with our observational findings. Moreover, we noticed EOS and TP were causally associated with the risk of lung function (FEV1/FVC). CONCLUSIONS: The MR findings and clinical data highlight the independent and significant roles of EOS and TP in the development of COPD and lung function (FEV1/FVC), which might provide a deeper insight into COPD risk factors and supply potential preventative strategies.

Impact of ultra-low temperature storage on serum sIgE detection and allergic disease biobank feasibility.

Research has shown that the concentration and composition of biological samples may change after long-term ultra-low temperature storage. Consequently, this study examined the effect of ultra-low temperature storage on serum sIgE detection by comparing sIgE concentrations at various durations from the time of sample storage to subsequent testing. We selected 40 serum samples from the Guangzhou Medical University Affiliated First Hospital Biobank, which had been tested for house dust mites, dog hair, tobacco mold, cockroaches, and cow milk allergen sIgE. Samples were categorized by storage duration: 14 samples stored for 10 years, 12 for 5 years, and 14 for 3 years. They were also classified by sIgE positive levels: 15 samples at levels 1-2, 15 at levels 3-4, and 10 at levels 5-6. The allergen sIgE of these samples was retested using the same technology. Regardless of the type of allergen or the level of positivity, the majority of sIgE concentrations measured at the time of storage were higher than the current measurements, but the difference was not statistically significant. The correlation between the sIgE results at the time of storage and the current results was high for samples stored for 10 years (rs = 0.991, P < 0.001) and 5 years (rs = 0.964, P < 0.001). Serum allergen sIgE is stable when stored under ultra-low temperature conditions, making the construction of a biological sample bank for allergic diseases feasible. This will facilitate researchers in quickly obtaining samples, conducting technical research, and translating findings, thereby promoting the development of the field of allergy through integration of industry, academia, and research.

ERC-BiP Functional Protein Pathway for Assessing Endoplasmic Reticulum Stress Induced by SARS-CoV-2 Replication after Cell Invasion.

Background: SARS-CoV-2 induces apoptosis and amplifies the immune response by continuously stressing the endoplasmic reticulum (ER) after invading cells. This study aimed to establish a protein-metabolic pathway associated with ER dysfunction based on the invasion mechanism of SARS-CoV-2. Methods: This study included 17 healthy people and 46 COVID-19 patients, including 38 mild patients and 8 severe patients. Proteomics and metabolomics were measured in the patient plasma collected at admission and one week after admission. The patients were further divided into the aggravation and remission groups based on disease progression within one week of admission. Results: Cross-sectional comparison showed that endoplasmic reticulum molecular chaperone-binding immunoglobulin protein (ERC-BiP), angiotensinogen (AGT), ceramide acid (Cer), and C-reactive protein (CRP) levels were significantly increased in COVID-19 patients, while the sphingomyelin (SM) level was significantly decreased (P < 0.05). In addition, longitudinal comparative analysis found that the temporal fold changes of ERC-BiP, AGT, Cer, CRP, and SM were significantly different between the patients in the aggravation and remission groups (P < 0.05). ERC-BiP, AGT, and Cer levels were significantly increased in aggravation patients, while SM was significantly decreased (P < 0.05). Meanwhile, ERC-BiP was significantly correlated with AGT (r = 0.439; P < 0.001). Conclusions: ERC-BiP can be used as a core index to reflect the degree of ER stress in COVID-19 patients, which is of great value for evaluating the functional state of cells. A functional pathway for AGT/ERC-BiP/glycolysis can directly assess the activation of unfolded protein reactions. The ERC-BiP pathway is closer to the intracellular replication pathway of SARS-CoV-2 and may help in the development of predictive protocols for COVID-19 exacerbation.

Utilizing Protein-Peptide Hybrid Microarray for Time-Resolved Diagnosis and Prognosis of COVID-19.

The COVID-19 pandemic has highlighted the urgent need for accurate, rapid, and cost-effective diagnostic methods to identify and track the disease. Traditional diagnostic methods, such as PCR and serological assays, have limitations in terms of sensitivity, specificity, and timeliness. To investigate the potential of using protein-peptide hybrid microarray (PPHM) technology to track the dynamic changes of antibodies in the serum of COVID-19 patients and evaluate the prognosis of patients over time. A discovery cohort of 20 patients with COVID-19 was assembled, and PPHM technology was used to track the dynamic changes of antibodies in the serum of these patients. The results were analyzed to classify the patients into different disease severity groups, and to predict the disease progression and prognosis of the patients. PPHM technology was found to be highly effective in detecting the dynamic changes of antibodies in the serum of COVID-19 patients. Four polypeptide antibodies were found to be particularly useful for reflecting the actual status of the patient's recovery process and for accurately predicting the disease progression and prognosis of the patients. The findings of this study emphasize the multi-dimensional space of peptides to analyze the high-volume signals in the serum samples of COVID-19 patients and monitor the prognosis of patients over time. PPHM technology has the potential to be a powerful tool for tracking the dynamic changes of antibodies in the serum of COVID-19 patients and for improving the diagnosis and prognosis of the disease.

The genetic associations of COVID-19 on genitourinary symptoms.

Background: Recently emerged reports indicated that patients with coronavirus disease 2019 (COVID-19) might experience novo genitourinary symptoms after discharge. Nevertheless, the causal associations and underlying mechanisms remain largely unclear. Methods: Genome-wide association study (GWAS) statistics for COVID-19 and 28 genitourinary symptoms with consistent definitions were collected from the COVID-19 Host Genetic Initiative, FinnGen, and UK Biobanks. Mendelian randomization (MR) analyses were applied to explore the causal effects of COVID-19 on genitourinary symptoms by selecting single-nucleotide polymorphisms as instrumental variables. Meta-analyses were conducted to evaluate the combined causal effect. Molecular pathways connecting COVID-19 and its associated disorders were evaluated by weighted gene co-expression network analysis (WGCNA) and enrichment analyses to extract insights into the potential mechanisms underlying the connection. Results: The MR and meta-analyses indicated that COVID-19 was causally associated with increased risk for calculus of the lower urinary tract (LUTC, OR: 1.2984 per doubling in odds of COVID-19, 95% CI: 1.0752-1.5680, p = 0.007) and sexual dysfunction (SD, OR: 1.0931, 95% CI: 1.0292-1.1610, p = 0.004). Intriguingly, COVID-19 might exert a slight causal protective effect on the progression of urinary tract infections (UTIs) and bladder cancer (BLCA). These results were robust to sensitivity analyses. Bioinformatic analyses indicated that the inflammatory-immune response module may mediate the links between COVID-19 and its associated disorders at the molecular level. Conclusions: In response to post-COVID-19 symptoms, we recommend that COVID-19 patients should strengthen the prevention of LUTC and the monitoring of sexual function. Meanwhile, the positive effects of COVID-19 on UTIs and BLCA should attach equal importance.

SARS-CoV-2 neutralising antibody therapies: Recent advances and future challenges.

The COVID-19 pandemic represents an unparalleled global public health crisis. Despite concerted research endeavours, the repertoire of effective treatment options remains limited. However, neutralising-antibody-based therapies hold promise across an array of practices, encompassing the prophylaxis and management of acute infectious diseases. Presently, numerous investigations into COVID-19-neutralising antibodies are underway around the world, with some studies reaching clinical application stages. The advent of COVID-19-neutralising antibodies signifies the dawn of an innovative and promising strategy for treatment against SARS-CoV-2 variants. Comprehensively, our objective is to amalgamate contemporary understanding concerning antibodies targeting various regions, including receptor-binding domain (RBD), non-RBD, host cell targets, and cross-neutralising antibodies. Furthermore, we critically examine the prevailing scientific literature supporting neutralising antibody-based interventions, and also delve into the functional evaluation of antibodies, with a particular focus on in vitro (vivo) assays. Lastly, we identify and consider several pertinent challenges inherent to the realm of COVID-19-neutralising antibody-based treatments, offering insights into potential future directions for research and development.

Component-Resolved Analyses for Diagnosis of Food Allergies in Infants and Young Children in Southern China.

INTRODUCTION: Chicken eggs and cow's milk are two of the most common foods that cause allergic reactions in infants and young children, and there is a lack of precise diagnostic methods to identify the allergic state of these patients. The recently developed food allergen component-resolved diagnosis (CRD) may be a more accurate diagnosis method for food allergies. METHODS: One hundred children sensitized to egg white and milk crude extracts and diagnosed with or suspected allergic disease were included. The specific immunoglobulin E (sIgE) (s) of animal food allergen crude extracts (egg yolk, milk, shrimp, crab, cod, beef) and the main components of egg white and milk were tested. The sensitization characteristics, cross-reactivity, and clinical relevance were analyzed. RESULTS: The results of egg white-sensitized patients showed that ovalbumin (Gal d 2) had the highest positive rate of 100%. Compared with other pairwise combinations of egg allergens, the combination of egg white and Gal d 2 had higher diagnostic accuracy, with an AUC of 0.876 (95% CI: 0.801-0.951), a sensitivity of 88.9%, and a specificity of 75.9%. The positive rates of beta-lactoglobulin (Bos d 5) and alpha-lactoglobulin (Bos d 4) in the milk-sensitized children were comparable, 92% and 91%, respectively. The combination of crude milk extract and Bos d 4 had the highest diagnostic accuracy, with an AUC of 0.969 (95% CI: 0.938-0.999), a sensitivity of 100%, and a specificity of 82.7%. CONCLUSION: Among these subjects, our study found the main allergenic component of egg white was Gal d 2, and the main allergenic components of milk were Bos d 4 and Bos d 5. CRD may help identify egg/milk allergies and non-allergies.

Evaluating SARS-CoV-2 antibody reactivity to natural exposure and inactivated vaccination with peptide microarrays.

Objective: Vaccination is effective tool for preventing and controlling SARS-CoV-2 infections, and inactivated vaccines are the most widely used type of vaccine. In order to identify antibody-binding peptide epitopes that can distinguish between individuals who have been vaccinated and those who have been infected, this study aimed to compare the immune responses of vaccinated and infected individuals. Methods: SARS-CoV-2 peptide microarrays were used to assess the differences between 44 volunteers inoculated with the inactivated virus vaccine BBIBP-CorV and 61 patients who were infected with SARS-CoV-2. Clustered heatmaps were used to identify differences between the two groups in antibody responses to peptides such as M1, N24, S15, S64, S82, S104, and S115. Receiver operating characteristic curve analysis was used to determine whether a combined diagnosis with S15, S64, and S104 could effectively distinguish infected patients from vaccinated individuals. Results: Our findings showed that the specific antibody responses against S15, S64, and S104 peptides were stronger in vaccinators than in infected persons, while responses to M1, N24, S82, and S115 were weaker in asymptomatic patients than in symptomatic patients. Additionally, two peptides (N24 and S115) were found to correlate with the levels of neutralizing antibodies. Conclusion: Our results suggest that antibody profiles specific to SARS-CoV-2 can be used to distinguish between vaccinated individuals and those who are infected. The combined diagnosis with S15, S64, and S104 was found to be more effective in distinguishing infected patients from those who have been vaccinated than the diagnosis using individual peptides. Moreover, the specific antibody responses against the N24 and S115 peptides were found to be consistent with the changing trend of neutralizing antibodies.

Novel nutritional indicator as predictors among subtypes of lung cancer in diagnosis.

Introduction: Lung cancer is a serious global health concern, and its subtypes are closely linked to lifestyle and dietary habits. Recent research has suggested that malnutrition, over-nutrition, electrolytes, and granulocytes have an effect on the development of cancer. This study investigated the impact of combining patient nutritional indicators, electrolytes, and granulocytes as comprehensive predictors for lung cancer treatment outcomes, and applied a machine learning algorithm to predict lung cancer. Methods: 6,336 blood samples were collected from lung cancer patients classified as lung squamous cell carcinoma (LUSC), lung adenocarcinoma (LUAD), and small cell lung cancer (SCLC). 2,191 healthy individuals were used as controls to compare the differences in nutritional indicators, electrolytes and granulocytes among different subtypes of lung cancer, respectively. Results: Our results demonstrated significant differences between men and women in healthy people and NSCLC, but no significant difference between men and women in SCLC patients. The relationship between indicators is basically that the range of indicators for cancer patients is wider, including healthy population indicators. In the process of predicting lung cancer through nutritional indicators by machine learning, the AUC of the random forest model was as high as 93.5%, with a sensitivity of 75.9% and specificity of 96.5%. Discussion: This study supports the feasibility and accuracy of nutritional indicators in predicting lung cancer through the random forest model. The successful implementation of this novel prediction method could guide clinicians in providing both effective diagnostics and treatment of lung cancers.

Clinical Application of Antibody Immunity Against SARS-CoV-2: Comprehensive Review on Immunoassay and Immunotherapy.

The current COVID-19 global pandemic poses immense challenges to global health, largely due to the difficulty to detect infection in the early stages of the disease, as well as the current lack of effective antiviral therapy. Research and understanding of the human immune system can provide important theoretical and technical support for the clinical diagnosis and treatment of COVID-19, the clinical implementations of which include immunoassays and immunotherapy, which play a crucial role in the fight against the pandemic. This review consolidates the current scientific evidence for immunoassay, which includes multiple methods of detecting antigen and antibody against SARS-CoV-2. We compared the characteristics, advantages and disadvantages, and clinical applications of these three detection techniques. In addition to detecting viral infections, knowledge on the body's immunity against the virus is desirable; thus, the immunotherapy-based neutralizing antibody (nAb) detection methods were discussed. We also gave a brief introduction to the new immunoassay technology such as biosensing. This was followed by an in-depth and extensive review on a variety of immunotherapy methods. It includes convalescent plasma therapy, neutralizing antibody-based treatments targeting different regions of SARS-CoV-2, immunotherapy targeted on the host cell including inhibiting the host cell receptor and cytokine storm, as well as cocktail antibodies, cross-neutralizing antibodies, and immunotherapy based on cross-reactivity between viral epitopes and autoepitopes and autoantibody. Despite the development of various immunological testing methods and antibody therapies, the current global situation of COVID-19 is still tense. We need more efficient detection methods and more reliable antibody therapies. The up-to-date knowledge on therapeutic strategies will likely help clinicians worldwide to protect patients from life-threatening viral infections.

Global burden of rabies in 204 countries and territories, from 1990 to 2019: results from the Global Burden of Disease Study 2019.

OBJECTIVES: Rabies is an acute lethal infectious disease caused by a lyssavirus infection. In 2018, the World Health Organization proposed a global strategic plan to end human rabies deaths by 2030. However, systematic studies on the global rabies disease burden and epidemiological trends are scarce. METHODS: We extracted the disease burden and epidemiological data of rabies worldwide in the preceding 30 years from the Global Burden of Disease Study 2019 and performed a comprehensive analysis. RESULTS: In 2019, the incident cases of rabies worldwide were 14,075.51 (95% uncertainty interval: 6124.33-21,618.11), and the number of deaths was 13,743.44 (95% uncertainty interval: 6019.13-17,938.53), both of which were lower than that in 1990. With the improvement of the sociodemographic index, the incident cases, the number of deaths, age-standardized incidence rate, age-standardized incidence death rate, and disability-adjusted life years of rabies all showed downward trends. Adolescents and adults aged <50 years represented the majority of rabies cases worldwide. CONCLUSION: The global disease burden of rabies has declined over the past 30 years. Furthermore, the disease burden of rabies was closely related to the sociodemographic index level.

Prevalence and Disability-Adjusted Life Year Rates of Asthma in China: Findings from the GBD Study 2019 of the G20.

BACKGROUND: The credible materials about the burden of asthma in China when compared to other countries in the group of twenty (G20) remain unavailable. OBJECTIVES AND DESIGN: Following the popular analysis strategy used in the Global Burden of Disease Study, the age-, sex-, country-specific prevalence, and disability-adjusted life years (DALYs) of asthma in China were analyzed. Meanwhile, the comparison in trends between China and other countries in the G20 was also evaluated. RESULTS: In 2019, asthma was the 8th leading cause of the DALYs' burden of 369 diseases in China. From 1990 to 2019, the age-standardized prevalence and DALY rates of asthma in China decreased by 14% and 51%, respectively; further, the decline rate of DALYs was much higher than the global average (-51%: -43%). It is worth noting that the overall population age-standardized DALYs rate of asthma in China was the lowest in the G20 during 2019 (102.81, 95% UI: (72.30,147.42)/100,000). Moreover, the age-standardized asthma prevalence rate peaks in both childhood (178.14, 95% UI: (90.50, 329.01)/100,000) and the elderly (541.80, 95% UI: (397.79, 679.92)/100,000). Moreover, throughout the study, subjects in the 5 to 9 years old interval were a constant focus of our attention. CONCLUSIONS: The disease burden of asthma has varied greatly by gender and age over the past 30 years. In contrast to the increasing burden in most other G20 countries, the age-standardized prevalence rate of asthma shows a significant decreasing trend in China, however, the age-standardized DALYs rate shows a fluctuating change, and has even shown a rebound trend in recent years.