Endocrine, metabolic & immune disorders drug targets最新文献

The preclinical efficacy of tumor immunotherapy is often evaluated using mouse models. However, due to species differences, conventional normal or nude mouse models cannot fully replicate the human immune response, resulting in many mouse-based research findings being inconsistent with the outcomes of clinical trials. Recently, the development of Severe Combined Immunodeficient (SCID) mice has paved the way for the reconstitution of a human CD45⁺ immune cell population exceeding 25% within the host, greatly assisting researchers in addressing these challenges. By engrafting human CD34⁺ hematopoietic cells, peripheral blood mononuclear cells, organoids, or fetal tissues into SCID mice-including various non-obese diabetic Prkdc^-/-IL2rg^-/- mice (commonly referred to as NSG, NCG, or NXG) and NSG mice expressing human cytokines- these models not only confer human immune functionality for the investigation of human innate immunity and specific viral infections but also facilitate the development and survival of human cancer cell-derived or patient-derived xenografts for immuno-oncology research. Despite the presence of graft-versus-host disease and a short experimental duration, this approach facilitates the investigation of tumor growth mechanisms within a human tumor immune microenvironment. It also enables the evaluation of the efficacy of human-specific immunotherapies, including CART and CAR-NK therapies, immune checkpoint inhibitors, and combination therapies, along with their underlying mechanisms. This article summarizes the latest research advancements and existing challenges related to SCID mouse models and humanized immune system mouse models, as well as their applications and obstacles in immuno-oncology research.

Introduction: Diabetes mellitus can be complicated by a variety of ocular diseases, among which the postoperative complications of diabetic cataract (DC) are significantly higher than those of non-DC patients. Therefore, finding drugs with natural active ingredients is an urgent challenge in the prevention and treatment of DC. Discovering the potential molecular mechanism of celosiae semen (CS) for the treatment of DC and providing new ideas and programs for the treatment and prevention of DC.

Methods: In this study, network pharmacology, molecular docking, and molecular dynamics simulations were utilized to predict the binding and functional enrichment of the main active ingredients of CS with DC-related targets, and to explore the potential pathways and mechanisms of CS for the treatment of DC.

Results: Through database searching and screening, a total of 45 potential targets of CS for the treatment of DC were identified, functionally enriched, and a protein-protein interaction network was constructed, and the key target, SRC, was finally found. The results of molecular docking and molecular dynamics simulation showed that the main active ingredient of CS, stigmasterol, could bind stably to the key target SRC protein.

Discussion: This study not only elucidates the phyto-pharmacological basis of CS in DC management but also provides a framework for developing natural product-derived targeted therapies against diabetic ocular complications. The integration of modern genomics and computational chemistry to deconstruct the therapeutic effects of traditional Chinese herbal medicines has great clinical significance in expanding the scope of traditional Chinese medicines for the treatment of DC and promoting precision targeting. However, this requires verification through basic experiments.

Conclusion: These computational findings suggest that CS may exert its anti-cataract effects through the multi-target modulation of diabetic metabolic pathways and SRC-mediated signaling cascades.

To meet the increased nutrient requirements associated with rapid cellular proliferation, tumor cells undergo metabolic reprogramming, characterized by a substantial increase in the production of energy and precursor molecules necessary for biosynthetic processes. Similarly, T cells experience metabolic reprogramming to support their proliferation and immunological functions, leading to metabolic competition with tumor cells within the tumor microenvironment (TME). This metabolic competition adversely affects T cell activation, proliferation, and immune function, primarily due to the limited availability of glucose, lipids, and amino acids. Furthermore, cytokines and immune checkpoints significantly impact T cell-mediated immunoreactivity. Modulating the metabolism of tumor cells and T cell-mediated immune evasion within the TME is of paramount importance. Notably, the metabolism of small-molecule target agents has garnered considerable attention in the context of the TME. This study aimed to examine the influence of various microenvironmental factors on T cell metabolism and explore corresponding innovative therapeutic approaches, thereby offering a comprehensive array of potential clinical strategies for cancer prevention and treatment.

Introduction: Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease and seriously threatens children's health. Fortunellin exerts a protective role in several human diseases, but its function in NAFLD is unclear. This research tried to uncover Fortunellin's function and mechanism in young NAFLD rats.

Methods: A young rat model of NAFLD was established by administering a high-fat diet (HFD). Also, Fortunellin was delivered via intragastric administration. The effects of Fortunellin on NAFLD were assessed through hematoxylin-eosin staining, analysis of serum levels of ALT, AST, TCH, TG, LDL-C, and HDL-C, Oil Red O staining, Western blot, ELISA, and quantitative real-time PCR (qRT-PCR). Additionally, the Fortunellin mechanism in NAFLD was estimated with Western blot, immunofluorescence, Oil Red O staining, and ELISA assays.

Results: Functionally, Fortunellin (5 or 10 mg/kg) reduced liver injury in young NAFLD rats, which was mainly associated with the gradual decrease of a liver index, the increased liver tissue score, and the gradually decreased serum levels of ALT and AST. Also, Fortunellin restrained NFALD rat dyslipidemia by lessening TCH, TG, LDL-C serum levels, and increasing HDL-C levels. Furthermore, Fortunellin repressed liver lipid metabolism and immune disorders in young NAFLD rats. Mechanically, Fortunellin enhanced the AMPK activation in young NAFLD rats. Additionally, Fortunellin relieved lipid deposition and immune disorders in young NAFLD rats, while compound C (CC, an AMPK inhibitor) abolished these impacts.

Discussion: This study confirmed that Fortunellin alleviated liver injury in young rats with NAFLD, and this might be achieved by activating the AMPK axis. The completion of this study provided a promising drug for the NAFLD treatment.

Conclusion: In summary, Fortunellin alleviated lipid deposition and immune disorders in young rats with NAFLD through the activation of AMPK.

Introduction: Celiac Disease (CeD) is a serious, lifelong autoimmune condition. There remains a significant unmet medical need for effective pharmacological treatments for CeD.

Methods: We utilized summary statistics for 2,888 druggable genes from the eQTLGen Consortium and the FinnGen Consortium for CeD. In our Mendelian Randomization (MR) analysis, we identified genes associated with CeD that had a false discovery rate (FDR) < 0.05 using the Inverse Variance Weighted (IVW) method. To enhance the reliability of the results, we validated them through colocalization analysis and Summary-data-based Mendelian Randomization (SMR) analyses.

Results: Through our analysis, we identified 18 druggable genes with a causal relationship to CeD under an FDR < 0.05. Subsequent colocalization and SMR analyses highlighted the PRKCD gene as a potential therapeutic target for CeD (IVW method: Odds Ratio 1.319, 95% Confidence Interval 1.182-1.471, P = 6.85E-07, FDR = 0.002). Additionally, these results have passed horizontal pleiotropy tests, heterogeneity analysis, and leave-one-out sensitivity analysis.

Discussion: The identification of PRKCD as a therapeutic target represents a significant advancement in addressing the unmet medical need for CeD treatment. However, the hypothesis that PRKCD contributes to CeD pathogenesis by regulating tight junction proteins and altering intestinal barrier function requires further experimental validation in future studies.

Conclusion: Our study is the first to identify the PRKCD gene as a potential therapeutic target for treating CeD, providing new insights into the treatment of CeD and guiding the development of corresponding therapeutic drugs.

Introduction: Childhood acute lymphoblastic leukemia (cALL), the most common pediatric hematologic malignancy, arises primarily from B-cell origin and is strongly associated with immune dysfunction. This article integrated single-cell and bulk transcriptomic data to identify key B-cell subsets and cALL-related molecules as biomarkers.

Methods: Single-cell RNA sequencing (scRNA-seq) Data from 2 pre-B high hyperdiploid (HHD) ALL patients and 3 healthy pediatric bone marrow samples (GSE132509) were utilized for cell clustering using the Seurat package. Functional enrichment, pseudo-time trajectory, and cell-cell communication analyses were performed using clusterProfiler, Monocle2, and CellChat R packages, respectively. Bulk RNA-seq data of 511 cALL samples in the TARGET-ALL-P2 cohort were used to construct a prognostic model via Cox and LASSO regression. Immune infiltration differences between different risk groups were analyzed using ESTIMATE, MCP-counter, and CIBERSORT algorithms.

Results: The scRNA-seq analysis identified five cell subpopulations, with B cells demonstrating significant enrichment in cALL samples. Notably, the C2 subset was associated with cell proliferation. Ligand-receptor analysis revealed key interactions involving B cell C2. Four marker genes (CENPF, IGLL1, ANP32E, and PSMA2) were identified to build a risk model. Low-risk patients showed better survival, while high-risk patients had higher ESTIMATE scores.

Discussion: This study examined the key role of B cells in cALL, constructed a risk model with strong prognostic predictive ability applying multi-omics analysis, and primarily explored its potential mechanism in immune regulation.

Conclusion: This study revealed the critical role of B cells in cALL, and the prognostic model showed a high prediction accuracy, providing a potential target for individualized treatment of cALL.

Introduction: Some cases report that beta-blockers may induce or exacerbate psoriasis. However, pharmacoepidemiology studies have yielded conflicting results. This study aims to investigate whether there is a potential association between beta-blockers and psoriasis.

Methods: An observational study was conducted on the U.S. population from the National Health and Nutrition Examination Survey (NHANES) database using propensity score matching and multivariable logistic regression models. Subsequently, a disproportionality analysis was performed based on the FDA Adverse Event Reporting System (FAERS) database, and a two-sample Mendelian randomization (MR) study was conducted to assess the association between beta-blockers and the risk of developing psoriasis.

Results: Based on the NHANES database, logistic regression analysis, adjusted for relevant confounders, showed no significant association between beta-blocker use and the risk of psoriasis (OR: 1.49, 95% CI: 0.76-2.92, p = 0.250). FAERS analysis identified 300 psoriasis-related reports for beta-blockers, but no robust safety signals were detected (ROR: 0.34, 95% CI: 0.30-0.38), even after false-negative analysis. The meta-analysis of MR results demonstrated a statistically significant association between beta-blocker use and reduced risk of psoriasis (OR: 0.9985, 95% CI: 0.9978-0.9991, p < 0.001).

Discussion: The observed epidemiological association likely stems from confounding by cardiovascular indications for beta-blockers, rather than a direct causal effect. Neuroimmune pathways (sympathetic activity, β1/β2 receptor effects on immune cells/keratinocytes) present biologically plausible but complex and potentially opposing mechanisms, requiring further investigation.

Conclusions: We found that beta-blockers did not significantly elevate the risk of psoriasis. In clinical practice, labeling beta-blockers as drug-induced psoriasis may be inappropriate.

Hyperprolactinemia is characterized by unusually high levels of prolactin, a hormone primarily known for regulating reproductive functions. However, studies have shown that prolactin has also a significant impact on various neurotransmitter systems in the brain. This review examined the intricate relationship between hyperprolactinemia and neurotransmission, with a particular emphasis on the dopaminergic and serotonergic systems. Prolactin affects these systems in ways that can notably influence mood, behavior, and cognitive functions. One significant consequence of elevated prolactin is the disruption of dopaminergic signaling. Prolactin inhibits the release of dopamine and modifies the sensitivity of dopamine receptors, which may lead to the onset of neuropsychiatric disorders like depression, psychosis, and other mood-related issues. Moreover, high prolactin levels have been found to impact the serotonergic system, further worsening symptoms of depression, anxiety, and other mood disturbances. The review also evaluated the interactions between prolactin and other neurotransmitter systems, such as the GABAergic and glutamatergic systems, providing insights into the potential mechanisms through which hyperprolactinemia affects neuropsychiatric health. Additionally, the review discussed the complex relationship between prolactin and sex hormones, which not only affects reproductive health but also plays a role in regulating sexual behavior and mood. The clinical significance of hyperprolactinemia is considerable, as it is associated with various neuropsychiatric conditions. Current treatment options, including dopamine agonists, are explored as strategies to address the neurotransmitter imbalances linked to this condition. Furthermore, the review highlighted potential avenues for future research, including innovative therapeutic approaches that target neurotransmitter systems to tackle disorders related to hyperprolactinemia more effectively.

Introduction: Jiangtang Decoction (JTD) demonstrates notable efficacy in managing Type 2 Diabetes Mellitus (T2DM) and Non-Alcoholic Fatty Liver Disease (NAFLD). This study aimed to elucidate JTD's causal targets and therapeutic mechanisms by integrating network pharmacology, Summary-data Mendelian Randomization (SMR), and molecular docking, complemented by in vitro validation.

Materials and methods: JTD's targets were cross-matched with genes associated with T2DM or NAFLD. SMR and co-localization analyses, utilizing eQTL and pQTL data, identified causal signals for each disease and their shared counterparts. GO/KEGG enrichment analyses were performed on these shared signals. Molecular docking assessed binding interactions. In vitro experiments, including ELISA (Enzyme-linked immunosorbent assay) and lipid staining, evaluated JTD's hypoglycemic/hypolipidemic effects, while PCR/immunofluorescence validated key molecular predictions in High-Glucose and High-Lipid (HGHL)-induced HepG2 cells.

Results: Initial network pharmacology identified 1107 JTD targets for T2DM and 1126 for NAFLD. SMR analyses revealed 78 eQTLs and 67 pQTLs for T2DM, and 40 eQTLs and 38 pQTLs for NAFLD. Eight shared causal genetic signals were identified: ADAMTS4, ALDH2, GLO1, CDH1, PDHB, PRKAB1, TCF4, and EP300. In vitro, JTD significantly attenuated hepatic gluconeogenesis and lipid deposition, downregulated IL-1β, and notably restored PRKAB1 expression in HepG2 cells treated with HGHL.

Discussion: Enrichment analysis revealed shared processes, including membrane microdomains, oxidoreductase activity, and responses to nutrient and oxygen levels. PRKAB1 exhibited a strong binding affinity with the JTD component Salsalate.

Conclusion: This study identified eight genes that are genetically predicted to be causal for the therapeutic effects of JTD on both T2DM and NAFLD, thereby establishing a genetic link between the conditions. These targets and associated pathways illuminate common underlying mechanisms, supporting JTD's potential for integrated treatment strategies and providing a basis for further investigation.

Introduction: Insulin Autoimmune Syndrome (IAS) is a rare yet clinically significant drug-induced adverse reaction, characterized by hypoglycemic episodes caused by insulin autoantibodies. While individual drug associations are documented in case reports, systematic pharmacovigilance analyses supporting drug-induced IAS are lacking in the literature. This study aims to identify drugs associated with IAS through pharmacovigilance analysis and explore potential molecular mechanisms.

Methods: We conducted a comprehensive analysis of IAS reports in the FDA Adverse Event Reporting System (FAERS) database (2004-2024) using multiple disproportionality analysis methods. Drug-gene interaction networks were constructed using DGIdb, GeneCards, and SwissTarget- Prediction databases, with subsequent protein-protein interaction analysis and pathway enrichment performed using STRING and DAVID databases.

Results: Analysis of 228 IAS reports revealed significant associations with 17 medications, 16 of which were not documented in the current IAS literature. Captopril showed the strongest association (ROR: 1777, 95% CI: 1051-3005), followed by thiamazole and clopidogrel. Network analysis identified enrichment in the PI3K-Akt signaling pathway, insulin resistance, and AMPK pathways, suggesting these pathways may play a role in the development of IAS.

Discussion: This study identified novel drug associations with IAS, highlighting the high risk of captopril in patients with the HLA-DRB1*0406 genotype, and the need for close monitoring of elderly patients on thiamazole or clopidogrel, particularly for hypoglycemia. Additionally, monitoring PI3K-Akt pathway disruption is crucial, as it may impair Treg function and promote the production of autoantibodies against insulin.

Conclusions: The study identified 17 medications associated with IAS and emphasized the potential role of the PI3K-Akt pathway, recommending avoidance of certain drugs and enhanced monitoring in high-risk patients.