Endocrine, metabolic & immune disorders drug targets最新文献

Introduction: Anemia has been linked to an increased risk of coronary heart disease (CHD), yet the underlying causal relationship remains unclear. This study aimed to investigate the bidirectional associations between anemia and CHD using a multi-method approach.

Methods: Data were obtained from the European FinnGen biobank and the Gene Expression Omnibus (GEO) database. Mendelian Randomization (MR) analysis was performed with instrumental variables (IVs). The study assessed causal robustness using MR methods and sensitivity analysis, followed by differential expression analysis and weighted gene co-expression network analysis (WGCNA) to screen for core genes. Further, machine learning algorithms, such as least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine (SVM) algorithms, were applied to screen for key diagnostic genes. Additionally, the CIBERSORT algorithm was used to analyze immune cell infiltration, and validation was conducted using an in vitro oxidized low-density lipoprotein (ox-LDL)-induced endothelial cell model and western blot experiments.

Results: MR analysis revealed a positive causal link among vitamin B12 deficiency anemia, hemolytic anemia, and coronary heart disease, while cardiovascular events appeared to have a negative association with hemolytic anemia. Integrated bioinformatics analysis identified six core genes involved in immune response, inflammation, and lipid metabolism. To improve the accuracy of key gene screening and avoid bias from a single method, this study combined multiple machine learning algorithms for comprehensive analysis, ultimately identifying IFIH1 and APBB2 as potentially valuable diagnostic biomarkers, and revealing affected macrophages, mast cells, and T cells infiltration. In vitro experiments confirmed altered expression of IFIH1 and APBB2 upon ox-LDL treatment, supporting their role in CHD pathogenesis.

Conclusion: This study, through the integration of MR, transcriptomics, and machine learning methods, has for the first time revealed the causal role of vitamin B12 deficiency anemia and hemolytic anemia in the occurrence of CHD, and identified IFIH1 and APBB2 as potential biomarkers. This research study has provided a new theoretical basis and research direction for understanding the molecular link between anemia and CHD and for improving clinical early warning systems.

Introduction: Sepsis is a Systemic Inflammatory Response (SIR) caused by invading pathogens. We aimed to characterize infiltrating cells in sepsis and provide novel insight for the treatment of sepsis.

Materials and methods: Whole-blood scRNA-seq samples from four septic patients and five healthy subjects were collected from the Gene Expression Omnibus (GEO) database (GSE175453). The Seurat R package was used for quality control and cell clustering by scRNA- seq analysis. Gene set enrichment analysis (GSEA) was performed using the clusterProfiler R package for pathway enrichment analysis. Then, the SCENIC analysis was used to identify key transcriptional regulons, and the CellChat R package was used for cell communication analysis.

Results: We mainly obtained 9 cell clusters, including myeloid cells, T cells, dendritic cells, NK T cells, B cells, plasma B cells, megakaryocytes, mast cells and erythrocytes. Notably, myeloid cells, erythrocytes and mast cells had a higher proportion in sepsis patients. Activated IL-17 and p53 pathways supported anti-infection response in myeloid cells, and JUNB and SPI1 mediated multiple inflammatory pathways, including TNF signaling and neutrophil activation. We also identified that the cell interaction mode of myeloid cells, such as MPZL1-MPZL1 and FASL-FAS, may serve as a potential target for an anti-inflammatory response in sepsis treatment.

Discussions: The scRNA-seq analysis revealed pro-inflammatory pathways (IL-17, p53) and key regulators (JUNB, SPI1) in septic myeloid cells. Receptor genes (MPZL1 and FAS) mediated cell communication, offering potential biomarkers and targets for sepsis therapy.

Conclusion: We characterized the pro-inflammatory immune response pathways, transcriptional regulon and cell interaction modes of myeloid cells in the development of sepsis.

Background: Metabolic dysfunction-related fatty liver disease (MAFLD) has emerged as the predominant chronic liver disorder among children and adolescents. Like in adults, pediatric MAFLD encompasses a disease spectrum progressing from isolated steatosis to inflammatory changes, fibrotic development, and ultimately, cirrhosis. Despite increasing recognition of MAFLD as a major pediatric health issue, current literature lacks a systematic quantitative evaluation of research trends, leading to knowledge gaps in this field. To address this limitation, a comprehensive bibliometric analysis was performed to assess global research output on pediatric MAFLD by focusing specifically on the 2014-2023 period. This analysis avoids the confounding effects of the heterogeneity of earlier data while achieving sufficient temporal resolution to reveal emerging trends that might be obscured in long-term studies. This study synthesizes existing evidence, enhances understanding of this disciplinary field, and informs future research directions in pediatric MAFLD.

Methods: Articles concerning children with MAFLD published from 2014--2023 were identified from the Science Citation Index-Expanded of the Web of Science Core Collection. CiteSpace software, VOSviewer, and the Online Analysis Platform of Literature Metrology were used to analyze the current publication trends and hotspots.

Results: The analysis identified 1,609 English-language articles on pediatric MAFLD published from 2014 to 2023. The United States emerged as the most active participant in international collaborations. The University of California San Diego (UCSD) demonstrated the highest research output among the analyzed institutions. Additionally, UCSD exhibited the most extensive collaborative network, engaging in frequent and substantive research partnerships with a diverse range of academic and scientific organizations. Valerio Nobili was found to be the most prolific author, with 67 articles. Keyword burst analysis revealed that cardiovascular risk factors were the most intense research hotspot.

Conclusion: Current research on pediatric MAFLD warrants greater attention, particularly regarding cardiovascular risk factors. This study provides valuable references for researchers, offering insights to guide future research directions and potential collaborations.

Introduction: Previous studies suggest a link between Basal Metabolic Rate (BMR) and obstetrical disorders; however, causality remains unclear. We investigated the causal effects of BMR on 14 obstetric disorders and evaluated the potential mediating effects of blood metabolites in these relationships.

Methods: Using Genome-Wide Association Study (GWAS) summary data, we conducted both univariate and multivariable Mendelian Randomization (MVMR) analyses. The primary causal inference was based on Inverse Variance Weighted (IVW), MR-Egger, weighted median, and sensitivity analyses (Cochran's Q, MR-PRESSO). Mediation analysis was employed to quantify the proportion of effects operating through metabolite-regulated pathways.

Results: BMR was inversely associated with hyperemesis gravidarum (OR=0.73, 95%CI: 0.59-0.90, P=0.008), Intrahepatic Cholestasis of Pregnancy (ICP) (OR=0.67, 95%CI: 0.56-0.80, P<0.001), poor fetal growth (OR=0.80, 95%CI:0.71-0.90, P=0.001), and preterm delivery (OR=0.78, 95%CI:0.70-0.87, P<0.001). MVMR identified elevated BMR and mannose levels as protective against ICP, with BMR showing a positive correlation with mannose. Mediation analysis revealed that BMR reduced ICP risk partly through increased mannose (OR = 1.38, 95% CI: 1.19-1.59, P = 2.03 × 10^-5), accounting for 29.93% of the effect.

Discussion: Elevated BMR significantly reduced risks of intrahepatic cholestasis (HR=0.67), fetal distress (HR=0.80), and preterm birth (HR=0.78), mediated partly by mannose levels. Mendelian randomization established causality, linking metabolic adaptation to improved pregnancy outcomes. However, these findings, based on European genetic data, limit generalizability, and unmeasured confounders may persist despite MR methods.

Conclusion: Higher BMR may lower risks of hyperemesis gravidarum, ICP, poor fetal growth, and preterm delivery. Mannose mediates the protective effect of BMR on ICP, highlighting potential metabolic pathways for intervention.

Background: Obesity, a rapidly escalating global health concern, is associated with comorbidities and chronic inflammation. However, the link between obesity and thyroid autoimmunity remains unclear.

Objective: This case-control study, conducted at a tertiary care center, aimed to elucidate the relationship between obesity and the degree of obesity, thyroid autoimmunity, and TFTs in euthyroid individuals with a BMI >30 kg/m2 and explore variations based on the degree of obesity.

Methods: Free thyroid hormones, TSH, thyroid peroxidase antibodies (anti-TPO), anti-thyroglobulin antibodies (Anti-Tg), and metabolic parameters (glucose, lipid profile, insulin resistance, hemoglobin A1c) were measured in 164 euthyroid patients with obesity and 73 lean subjects aged 18-65 years. Subjects with obesity were stratified into three groups based on body mass index (BMI): first-degree obesity (BMI 30-34.9 kg/m2), second-degree obesity (BMI 35-39.9 kg/m2), and third-degree obesity (BMI ≥ 40 kg/m2).

Results: The prevalence of thyroid antibody positivity was significantly higher in the obese group compared with the non-obese group, specifically for anti-TPO (45 (27.4%) vs. 7 (9.6%) and anti- Tg (35 (21.3%) vs. 5 (6.8%). Anti-Tg titers were elevated in the obese group (p=0.006), but anti- TPO levels were similar across the groups. Among the BMI-stratified groups, individuals with first and second-degree obesity exhibited higher anti-TPO positivity and anti-Tg titers compared with the control group. No significant differences were found in the third-degree obesity group. TSH and fT4 levels were higher in the obese group compared with the non-obese group (p=0.016 and p=0.045, respectively), whereas fT3 levels and the fT3/fT4 ratio remained consistent across the groups. Although no direct correlation was found between thyroid autoantibodies and metabolic parameters, individuals positive for anti-TPO and/or anti-Tg exhibited worse metabolic profiles compared with individuals who were antibody-negative.

Conclusion: There is an increase in thyroid autoimmunity among euthyroid individuals with obesity; however, this increase does not appear to be proportional to BMI. The effect of antibody presence on metabolic parameters in individuals with obesity is not yet fully understood.

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer, and myocardial infarction (MI) is an acute cardiovascular disease resulting from the disruption of coronary blood supply. Recent studies have suggested that these two diseases may share common molecular mechanisms.

Aims: The aim of this study was to discover common diagnostic genes for LUAD and MI and analyze their molecular functions and potential drug values by applying bioinformatics analysis.

Objective: The objective was to provide a theoretical basis for further research on the pathological mechanisms of LUAD and MI, contributing to the development of novel diagnostic and therapeutic strategies for the two diseases.

Methods: In this study, the datasets of LUAD and MI were obtained from TCGA and GEO databases, and differential expression analysis was performed to screen significantly differentially expressed genes (DEGs). Subsequently, disease-related genes were identified using WGCNA analysis, and the biological functions of these genes were explored by functional enrichment analysis. After screening key genes using the protein-protein interaction (PPI) network and the cytoHubba algorithm, biomarkers were determined by LASSO and SVM-RFE machine-learning methods. Finally, immune infiltration analysis and drug prediction were performed, and biomarker expression was verified by single-cell sequencing analysis.

Results: A total of 158 differentially upregulated genes were identified between LUAD and MI. WGCNA analysis screened 86 genes that were significantly associated with both diseases and were enriched in an inflammatory response and immune regulation-related pathways, such as the IL-17 signaling pathway. Ten significant genes were identified by the PPI network and cytoHubba and then reduced to 4 using LASSO and SVM-RFE. Noticeably, MMP9 was significantly overexpressed in both diseases. Immune infiltration analysis showed that MMP9 was significantly related to multiple immune cell infiltration. Drug prediction and molecular docking analysis predicted Ilomastat and Osthole as the potential target drugs. Single-cell sequencing analysis revealed that MMP9 was high-expressed in the macrophages in LUAD tissues.

Conclusion: This study identified MMP9 as a common diagnostic gene and potential therapeutic target for both LUAD and MI and revealed its role in inflammation and immune regulation through comprehensive bioinformatics analysis. These findings provided a theoretical basis for further research on the pathological mechanisms of LUAD and MI, contributing to the development of novel diagnostic and therapeutic strategies.

Aims: There is a close relationship between obesity and hyperuricemia. Relative Fat Mass (RFM) is considered a new indicator for evaluating obesity. We aim to explore the relationship between RFM and the risk of hyperuricemia in adults.

Methods: This cross-sectional study included adult participants from the 2007-2018 National Health and Nutrition Examination Survey (NHANES). The RFM was calculated as: RFM =64 - (20 × height/waist circumference) + (12 × sex), where sex is defined as 0 for men and 1 for women. Hyperuricemia was confirmed by using serum uric acid (SUA) levels ≥ 7 mg/dL in men and ≥ 6 mg/dL in women. The relationship between RFM and the risk of hyperuricemia was thoroughly investigated.

Results: A total of 29369 participants were enrolled in this study. The RFM levels in the hyperuricemia group were higher than those in the non-hyperuricemia group (P < 0.01). Logistic and linear regression indicated that RFM levels were positively associated with the risk of hyperuricemia (OR=1.08, 95% CI: 1.05-1.11, P < 0.001) and SUA levels (β=0.04, 95% CI: 0.03-0.05, P < 0.001). The relationship remained consistent across subgroups. Smooth curve fitting showed a nonlinear relationship, with an inflection point at 34.22. Above this threshold, the link between RFM levels and hyperuricemia was found to be more remarkable.

Conclusion: Higher RFM is associated with an increased risk of hyperuricemia. RFM could act as a cost-efficient and straightforward measure for hyperuricemia risk assessment.

SGLT2 inhibitors are a family of drugs that were developed to treat diabetes mellitus. In randomized controlled trials, SGLT2 inhibitors seem to prevent kidney deterioration in patients with nephropathies, both diabetic and non-diabetic. However, in contrast to biochemical/physiological results (proteinuria and serum creatinine levels) that improve in all studies, the clinical results (all-cause mortality, cardiovascular death, need for dialysis, or renal transplant) do not consistently improve. In this article, the author would like to suggest that SGLT2 inhibitors do not, in fact, prevent the progression of renal diseases but rather alter laboratory results. This study will present a theory that gives an alternative explanation for the findings in the studies that would explain the above discrepancy between biochemical/physiological and clinical results. In general, the author claims that SGLT2 inhibitors change the kinetics of renal creatinine and microalbumin excretion but do not prevent parenchymal adverse changes in kidneys. This causes a dissociation between renal function markers (such as serum creatinine level and urinary protein) and the real kidney function. Thus, the clinical renal prognosis does not improve despite seemingly better laboratory results.

Background: Bladder cancer is one of the major health threats worldwide, and aberrant regulation of nitrogen metabolism is closely related to its development. Understanding the role of nitrogen metabolism-related genes in BC is pivotal for the development of new therapeutic strategies and prognostic assessment.

Aim and objectives: This study aimed to explore the prognostic factors associated with nitrogen metabolism in bladder cancer (BC) and to construct a prognostic model.

Methods: Differential expression gene analysis was performed to identify genes associated with nitrogen metabolism by analyzing mRNA expression data from BC patients. The prognostic relationship between these genes and BC patients was analyzed using univariate Cox regression. One hundred one combinatorial machine learning methods were applied for feature selection, and key prognostic genes were identified based on the method with the highest combined score. Immunocyte infiltration analysis was carried out to assess the tumor microenvironmental characteristics of patients in different risk groups.

Results: Twenty-five genes significantly associated with prognosis were identified from nitrogen metabolism-related genes. Twenty-three most prognostically predictive signature genes were screened under feature screening with multiple machine-learning models. Immune cell infiltration analysis showed that patients in the high-risk group had significantly different immune cell infiltration, suggesting that these genes may influence BC progression by regulating immune escape mechanisms. These results provide new biomarkers and potential therapeutic targets for precision treatment and prognostic assessment of BC.

Conclusion: The expression patterns of nitrogen metabolism-related genes identified can be used as effective biomarkers for bladder cancer prognosis, providing a scientific basis for personalized treatment. Future studies can further explore the specific biological functions and mechanisms of action of these genes to promote more effective clinical applications.