Endocrine, metabolic & immune disorders drug targets最新文献

Introduction: This study aimed to investigate the correlation between Prognostic Nutritional Index (PNI) and diabetic retinopathy (DR) in patients with diabetes.

Methods: In this cross-sectional NHANES study, 3,318 diabetic patients aged ≥40 years were analyzed. PNI was calculated as: serum albumin (g/L) + 5 × lymphocyte count (109/L). Statistical analyses incorporated complex sampling survey design methods. Associations between DR and PNI were assessed using univariate and multivariate logistic regression models, with restricted cubic splines detecting potential non-linearity. Subgroup analyses examined population-specific effects.

Results: Among the participants, 679 (18%) had DR. Patients with DR exhibited significantly lower PNI (50.46 ± 5.35) than those without DR (52.26 ± 6.07, P < 0.001). After adjusting for covariates- including age, sex, race, education, BMI, smoking status, hypertension, coronary heart disease, anemia, and blood glucose management-PNI remained inversely associated with DR risk (OR = 0.96, 95% CI: 0.94-0.98, P < 0.01). Restricted cubic spline analysis confirmed a non-linear relationship between PNI and DR (P = 0.01). Subgroup analyses showed significant inverse associations in patients aged 40-59 (OR = 0.93, 95% CI: 0.88-0.98, P = 0.01) and 60-79 (OR = 0.93, 95% CI: 0.89-0.96, P < 0.01), in overweight (OR = 0.94, 95% CI: 0.90-0.98, P < 0.01) and obese individuals (OR = 0.93, 95% CI: 0.89-0.96, P < 0.01), and in those using no medication (OR = 0.95, 95% CI: 0.90-0.99, P = 0.02) or oral hypoglycemic agents (OR = 0.96, 95% CI: 0.92-1.00, P = 0.04). The inverse association was not significant in patients with anemia or coronary heart disease (all quartiles P > 0.05).

Discussion: This study demonstrates a significant non-linear inverse association between PNI and DR risk, particularly among adults aged 40-79 years and overweight/obese individuals, while the relationship was attenuated in those with anemia or coronary heart disease. As a composite nutritional- inflammatory marker, PNI may reflect overall health status in diabetic patients.

Conclusion: PNI shows potential as a simple biomarker for DR risk stratification. Prospective validation is needed before clinical application.

Background: Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, contributing substantially to global morbidity and mortality. Although adiposity-related adipokines such as leptin have been associated with AF, the causal direction and independence from confounding factors remain uncertain.

Methods: We applied a bidirectional two-sample Mendelian randomization (MR) framework to assess the causal relationship between genetically predicted circulating leptin levels and AF risk. Genetic instruments for leptin were obtained from BMI-adjusted genome-wide association studies (GWAS), and AF summary statistics were sourced from large-scale meta-analyses. Causal estimates were derived using inverse variance-weighted (IVW), weighted median, and MR-robust adjusted profile score (MR-RAPS) methods. Reverse MR and sensitivity analyses were conducted to evaluate directionality and robustness.

Results: Genetically predicted elevated leptin levels were significantly associated with increased AF risk (IVW OR = 1.18, 95% CI: 1.05-1.32, p = 0.005), supported by weighted median (OR = 1.24, 95% CI: 1.07-1.43, p = 0.004) and MR-RAPS (OR = 1.18, 95% CI: 1.05-1.33, p = 0.007) analyses. Reverse MR showed no evidence of a causal effect of AF on leptin levels. Sensitivity analyses confirmed the consistency and robustness of the findings.

Conclusion: This study provides genetic evidence supporting a unidirectional causal effect of elevated leptin levels on AF risk, independent of adiposity. While these findings highlight leptin as a potential biomarker for AF susceptibility, further mechanistic and translational research is warranted to explore its role in atrial remodeling and therapeutic targeting.

Background: Regulatory T cells (Tregs) exhibit compromised immunosuppressive functions in psoriasis, yet understanding of their dysregulated perturbations remains limited.

Methods: scRNA-seq data from the skin of patients with psoriasis and healthy controls were analyzed to identify emigrating cells and their populations and functional states. Pseudotime as well as cell-cell communication analyses were employed to explore the origins and interactions of psoriasis- related Tregs. hdWGCNA, LASSO, and XGBoost were applied to identify critical Treg-associated gene signatures (TRGS). Various machine learning algorithms were used to develop a diagnostic model for psoriasis.

Results: Psoriatic lesions displayed a significant upregulation of C4-clustered genes, such as KRT14, DDIT4, and KRT1, in the granular and spinous layers of keratinocytes, which are associated with metabolic reprogramming under localized hypoxia. Psoriasis-associated Tregs exhibited increased glycolytic activity, impairing their functionality and highlighting the IL-17-HIF-1α axis. Pseudotime analysis revealed that Treg differentiation stalls at an intermediate stage, characterized by elevated expression of LTB, IL7R, and CCL5. Tregs were found to engage in IL16-CD4 autocrine signaling, potentially enhancing their proliferation and aggregation in psoriatic lesions. Five key Treg-related genes (TRGs)-CRIP1, FBXW11, CD47, ECH1, and H3F3A-were identified, and their expression was validated in a psoriasis-mimetic cellular model. The TRGS score exhibited a significant positive correlation with patients' PASI score (r = 0.43, p < 0.001). Finally, a diagnostic model was constructed based on their differential expression patterns.

Discussion: This study integrated single-cell transcriptomics and machine learning approaches to reveal the heterogeneity of Tregs and their key gene signatures in psoriasis, validated the expression of these genes through in vitro experiments, and ultimately constructed a high-accuracy diagnostic model based on TRGs.

Conclusion: This study provides a comprehensive analysis of the cellular heterogeneity of the epidermal immune microenvironment in psoriasis through single-cell transcriptomics, offering valuable insights into metabolic reprogramming, developmental pathways, cell-cell interactions, and the functional properties of Tregs in psoriasis. Additionally, a high-accuracy diagnostic model for psoriasis was developed using machine learning techniques. These findings offer a single-cell molecular perspective on immune microenvironment regulation in psoriasis and contribute to the identification of diagnostic biomarkers as well as the refinement of clinical diagnostic strategies.

Introduction: Observational studies suggest a link between hypertension, blood pressure- related hormones, and frailty. However, the causal nature of the association between these hormones and frailty remains unclear. This study employs Mendelian randomization (MR) to investigate the causal relationships between frailty and genetically influenced blood pressure-related hormones.

Methods: Genetic variants were selected as instrumental variables (IVs) from genome-wide association studies (GWAS) using strict significance thresholds. To evaluate causal relationships, a twosample MR analysis was performed. The primary method for estimating causal effects was the inverse variance weighted (IVW) approach, supplemented by the weighted median, weighted mode, and MR-Egger methods. Sensitivity analyses, including Cochran's Q tests, MR-Egger, MR-PRESSO, and leave-one-out assessments, were conducted to identify potential heterogeneity and pleiotropy.

Results: No causal associations between frailty index and genetically determined levels of well- recognized hormones regulating blood pressure, such as ACE (IVW: OR: 0.9934, 95%CI: 0.9847-1.0022, P=0.1425) and ACE2 (IVW: OR: 1.004, 95%CI: 0.9858-1.0226, P=0.6679), were found.

Discussion: The absence of a detectable causal effect suggests that previously observed associations in observational studies may be influenced by confounding factors. These findings challenge the hypothesis that these hormones are primary drivers of frailty from a genetic standpoint, highlighting the complexity of frailty's etiology, which may be more strongly influenced by non-genetic or environmental factors. Study limitations include the potential for weak instrument bias in smaller GWAS datasets.

Conclusion: Our findings do not support a causal relationship between genetically determined levels of six major blood pressure-related hormones and the frailty index in European populations.

Introduction: Periodontal disease is a condition that damages the supporting tissues, potentially resulting in tooth extraction, while type 2 diabetes is a condition that involves insulin resistance, leading to hyperglycaemia and systemic inflammation.

Methods: A broad literature search was conducted in PubMed, Scopus, Web of Science, Google Scholar, and ProQuest. Search terms included combinations of keywords related to periodontal disease, type 2 diabetes, bone metabolism, genetics/epigenetics, inflammation, and oxidative stress, refined using Boolean operators. Titles and abstracts were screened, and eligible full-text articles were reviewed for relevant data.

Results: This review found that periodontal disease, a major cause of tooth loss in adults, is strongly influenced by the bidirectional relationship with type 2 diabetes. Hyperglycaemia in poorly controlled diabetes exacerbates periodontal inflammation by enhancing the formation of advanced glycation end-products, triggering pro-inflammatory pathways such as the activation of Nuclear Factor kappa-light-chain-enhancer of activated B cells and cytokine release (e.g., Tumour Necrosis Factor-α, Interleukin [IL]-6, IL-18). Concurrent dysbiosis of the oral microbiome disrupts immunoregulation, while an imbalance in the receptor activator of nuclear factor kappa-B ligand (RANKL) and osteoprotegerin (OPG) system promotes osteoclastogenesis, collectively leading to accelerated tissue destruction, impaired healing, and an increased risk of complications.

Conclusion: This review clarifies the molecular mechanisms of the triad axis of oral microbiota- inflammatory factors-bone metabolism markers in the bidirectional association between periodontal disease and type 2 diabetes. Understanding the underlying mechanisms of this bidirectional relationship can provide valuable information for researchers to identify potential targets for effective management strategies for periodontal disease in patients with type 2 diabetes.

Background: Ulcerative colitis (UC) is a complex disease associated with immune dysregulation. Classic prescriptions (CP) of traditional Chinese medicine have a strong theoretical foundation and a long history of clinical use in treating UC. This study aims to uncover the intrinsic patterns and characteristics of these CPs.

Methods: Data mining of CP literature for UC from VIP, CNKI, WanFang, and PubMed (2013-2023), which focused on herb usage frequency, properties, flavors, meridian tropisms, core herb pairs, and UC categories. Finally, the top ten CPs were further analyzed for clinical application.

Results: A total of 62 prescriptions from 383 articles were analyzed, and the most frequently used prescriptions were Sishen pill, Huangqin decoction, and Shaoyao decoction. The greatest frequency herbs were Glycyrrhizae Radix et Rhizoma, Coptidis Rhizoma, Paeoniae Radix Alba, and Atractylodis Macrocephalae Rhizoma. Herbs were pungent, bitter, and sweet in flavor with properties mainly being warm, cold, and neutral and targeting the liver, spleen, stomach, and heart meridians. Core herb pairs included Bupleuri-Poria, Atractylodis-Saposhnikoviae, Zingiberis-Jujubae, Phellodendri Chinensis Cortex -Coptidis Rhizoma, Pinelliae Rhizoma-Ginseng Radix et Rhizoma. Through cluster analysis, the herbs were categorized into four distinct clusters. Furthermore, the CP primarily exerted therapeutic effects by alleviating inflammation, restoring mucosal barriers, and maintaining immune balance.

Conclusion: Data mining identified Sishen Pill, Huangqin Decoction, and Shaoyao Decoction as the top three CPs for UC. The main mechanism of treating UC is by reducing inflammation, maintaining immune balance, and repairing the mucosal barrier.

Introduction: Obesity is one of the most common health problems today and is known to cause insulin resistance due to diabetes mellitus (DM). Many treatment methods are still being tested. This study aimed to examine in detail the beneficial effects of exercise (EXE) and L-carnitine (LC) on insulin resistance associated with type 2 DM (DM-2).

Methods: Twenty-four obese male Wistar Albino rats with DM-2 were divided into four groups: DCG, LCG, SEG, and SE+LCG. A 12-week SE and LC administration protocol was applied in the study. Blood serum glucose levels were measured using a blood glucose meter, and insulin levels were determined by an ELISA test. The obtained OD values were used to calculate insulin resistance using the HOMA-IR method. Paired Samples T Test and One-Way ANOVA were used in statistical analyses.

Results: Except for the DCG group, all rats showed significant improvements in body weight, blood glucose levels, and insulin resistance levels. However, no statistically significant differences were found in HOMA-IR values within or between the groups.

Discussion: In disorders observed in juvenile obese rats with Type 2 Diabetes, the combined use of LC and Sbe more effective in enhancing fat burning and facilitating weight loss compared to LC and SE programs applied separately.

Conclusion: LC and SE are effective in reducing obesity, Type 2 Diabetes, and associated insulin resistance levels. Further studies are needed in this field to evaluate the effects of different exercise modalities, treatment types, and durations.

Introduction: This study aimed to explore the current status, hotspots, and trends in research on polyunsaturated fatty acids (PUFAs) and cardiovascular inflammation.

Methods: Literature related to cardiovascular inflammation and PUFAs from the Web of Science Core Collection between January 1, 2009, and July 1, 2024, was retrieved using specific search terms, and the data were visualized and analyzed using CiteSpace (version 6.3.R3) and VOSviewer (version 1.6.20).

Results and discussion: PUFAs and cardiovascular inflammation publications have been found to grow over the past 15 years. The United States leads in this field, with Nutrients being the leading journal. Harvard University and the University of California system are the most influential institutions. Most publications are in immunology and medical journals, while citations are primarily in biology and nutrition journals. International collaboration is strong, with Mozaffarian and Calder making significant contributions. Bhatt et al. and Bosch et al. have the most citations and the highest centrality, respectively. Research trends focus on the relationship between PUFAs and inflammatory markers, the anti-inflammatory mechanisms of PUFAs, and their association with diseases. Omega-3 and omega-6 PUFAs show divergent impacts on inflammation and cardiovascular diseases (CVD) risk, with gut microbiota mediating bidirectional regulation. Emerging research directions in PUFAs' anti-inflammatory mechanisms encompass gut microbiota, oxidative stress, and pro-resolving mechanisms, with gut microbiota as the current focus.

Conclusion: This bibliometric analysis has highlighted sustained growth and global collaboration in PUFAs-cardiovascular inflammation research. Key emerging mechanisms have been found to focus on the gut-microbiota-PUFAs axis, oxidative stress, and pro-resolving pathways, pointing towards future translational opportunities.

Introduction: The human gastrointestinal tract is home to a vast array of microorganisms, and the imbalance of these microorganisms is closely linked to various diseases. The composition of gut microbiota in individuals is influenced by many factors, among which gender differences are often overlooked and lack targeted treatment plans in clinical practice. Based on this, we conducted this study aimed at exploring the pathogenesis of gastrointestinal inflammation and the importance of gender specificity, providing new ideas and targets for the diagnosis and treatment of gastrointestinal inflammation stratified by gender.

Methods: We collected fecal samples from 89 patients with gastrointestinal inflammation (40 males and 49 females) for DNA extraction, DNA library construction, sequencing, and clinical data analysis.

Results: In laboratory indicators, male patients had significantly lower mean LDH levels than females (P < 0.05), whereas median GGT, HB, M, and E values were significantly higher (P < 0.05). Additionally, significant differences in microbial α diversity at the species level were observed between the two groups (all P < 0.05). In the prediction analysis of microbial population function, the mean values of heterologous biodegradation and metabolism, signal transduction, cell activity, metabolism of other amino acids, and bacterial infectious disease pathways in the female patient group were higher than those in the male patient group (all P<0.05), and the mean values of nucleotide metabolism, replication and repair, and transcription and translation were lower than those in the male patient group (all P<0.05).

Discussion: Gender differences affect gastrointestinal inflammation progression, with male and female patients showing distinct gut microbiota and laboratory indicators. Males have lower LDH but higher GGT, HB, M, and E, linked to hormonal effects. The gut microbiome composition differs by gender, with males having a higher prevalence of Prevotella and altered metabolic pathways. Females show higher activity in xenobiotic degradation and infection-related functions. Diet, exercise, and clinical interventions, such as FMT, can modulate the microbiota, but gender-specific responses exist.

Conclusion: Analysis revealed significant sex-based differences in gastrointestinal disease patients, including variations in laboratory indicators (LDH, GGT, HB, M, E), gut microbiome composition and diversity, and predicted microbial functional profiles. This provides insights for precise medical treatment of gastrointestinal inflammation stratified by gender.

Introduction: This study aimed to assess the relationship between fibrinogen-like protein 1 (FGL1) and adverse pregnancy outcomes (APOs) as well as metabolic disorders during pregnancy.

Methods: The pregnant women from 24 to 28 weeks of gestation were divided into different groups according to the number of metabolic abnormalities in a 2:1:1 ratio. A total of 120 cases were in the normal metabolic group, 120 cases were in the one metabolic disorder group, and 60 cases were in the two or more metabolic disorder groups. Blood collection and other sample collections were performed at 24-28 weeks of gestation.

Results: Serum FGL1 levels increased gradually across the normal metabolism group, one metabolic disorder group, and the two or more metabolic disorders group (H=9.410, p=0.009). Serum FGL1 level was extensively higher in the gestational diabetes mellitus (GDM) group compared to the normal glucose tolerance group (P<0.001). Compared with 190 women without APOs, serum FGL1 was higher in 59 women who developed adverse outcomes (P<0.05). Receiver operating characteristic (ROC) curve analysis showed that the combination of FGL1 with traditional indicators had higher predictive performance for APOs, with the area under the AUC of 0.718, than that of traditional indicators alone (AUC=0.700).

Discussion: High serum FGL1 may be a potential biomarker to monitor the severity of metabolic abnormality to enhance the predictive capability of traditional biomarkers for APOs.

Conclusion: Serum FGL1 in mid-pregnancy was closely related to metabolic disorders, GDM, and APOs.