Constructing and validating a predictive nomogram for osteoporosis risk among Chinese single-center male population using the systemic immune-inflammation index.

Osteoporosis (OP) is a bone metabolism disease that is associated with inflammatory pathological mechanism. Nonetheless, rare studies have investigated the diagnostic effectiveness of immune-inflammation index in the male population. Therefore, it is interesting to achieve early diagnosis of OP in male population based on the inflammatory makers from blood routine examination. We developed a prediction model based on a training dataset of 826 Chinese male patients through a retrospective study, and the data was collected from January 2022 to May 2023. All participants underwent the dual-energy X-ray absorptiometry (DXEA) and blood routine examination. Inflammatory markers such as systemic immune-inflammation index (SII) and platelet-to-lymphocyte ratio (PLR) was calculated and recorded. We utilized the least absolute shrinkage and selection operator (LASSO) regression model to optimize feature selection. Multivariable logistic regression analysis was applied to construct a predicting model incorporating the feature selected in the LASSO model. This predictive model was displayed as a nomogram. Receiver operating characteristic (ROC) curve, C-index, calibration curve, and clinical decision curve analysis (DCA) to evaluate model performance. Internal validation was test by the bootstrapping method. This study was approved by the Ethic Committee of the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine (Ethic No. JY2023012) and conducted in accordance with the relevant guidelines and regulations. The predictive factors included in the prediction model were age, BMI, cardiovascular diseases, cerebrovascular diseases, neuropathy, thyroid diseases, fracture history, SII, PLR, C-reactive protein (CRP). The model displayed well discrimination with a C-index of 0.822 (95% confidence interval: 0.798-0.846) and good calibration. Internal validation showed a high C-index value of 0.805. Decision curve analysis (DCA) showed that when the threshold probability was between 3 and 76%, the nomogram had a good clinical value. This nomogram can effectively predict the incidence of OP in male population based on SII and PLR, which would help clinicians rapidly and conveniently diagnose OP with men in the future.

Biomarkers of inflammation and coagulation after minimally invasive mitral valve surgery: a prospective comparison to conventional surgery.

OBJECTIVES: Minimally invasive cardiac surgery techniques are increasingly used but have longer cardiopulmonary bypass time, which may increase inflammatory response and negatively affect coagulation. Our aim was to compare biomarkers of inflammation and coagulation as well as transfusion rates after minimally invasive mitral valve repair and mitral valve surgery using conventional sternotomy. DESIGN: A prospective non-randomized study was performed enrolling 71 patients undergoing mitral valve surgery (35 right mini-thoracotomy and 36 conventional sternotomy procedures). Blood samples were collected pre- and postoperatively to assess inflammatory response. Thromboelastometry (ROTEM) was performed to assess coagulation, and transfusion rates were monitored. RESULTS: The minimally invasive group had longer cardiopulmonary bypass times compared to the sternotomy group: 127 min ([115-146] vs 79 min [65-112], p < 0.001) and were cooled to a lower temperature during cardiopulmonary bypass, 34 °C vs 36 °C (p = 0.04). IL-6 was lower in the minimally invasive group compared to the conventional sternotomy group when measured at the end of the surgical procedure, (38 [23-69] vs 61[41-139], p = 0.008), but no differences were found at postoperative day 1 or postoperative day 3. The transfusion rate was lower in the minimally invasive group (14%) compared to full sternotomy (35%, p = 0.04) and the chest tube output was reduced, (395 ml [190-705] vs 570 ml [400-1040], p = 0.04). CONCLUSIONS: Our data showed that despite the longer use of extra corporal circulation during surgery, minimally invasive mitral valve repair is associated with reduced inflammatory response, lower rates of transfusion, and reduced chest tube output.

MRI of shoulder girdle in polymyalgia rheumatica: inflammatory findings and their diagnostic value.

BACKGROUND: Non-synovial inflammation as detected by MRI is characteristic in polymyalgia rheumatica (PMR) with potentially high diagnostic value. OBJECTIVE: The objective is to describe inflammatory MRI findings in the shoulder girdle of patients with PMR and discriminate from other causes of shoulder girdle pain. METHODS: Retrospective study of 496 contrast-enhanced MRI scans of the shoulder girdle from 122 PMR patients and 374 non-PMR cases. Two radiologists blinded to clinical and demographic information evaluated inflammation at six non-synovial plus three synovial sites for the presence or absence of inflammation. The prevalence of synovial and non-synovial inflammation, both alone and together with clinical information, was tested for its ability to differentiate PMR from non-PMR. RESULTS: A high prevalence of non-synovial inflammation was identified as striking imaging finding in PMR, in average 3.4±1.7, mean (M)±SD, out of the six predefined sites were inflamed compared with 1.1±1.4 (M±SD) in non-PMR group, p<0.001, with excellent discriminatory effect between PMR patients and non-PMR cases. The prevalence of synovitis also differed significantly between PMR patients and non-PMR cases, 2.5±0.8 (M±SD) vs 1.9±1.1 (M±SD) out of three predefined synovial sites, but with an inferior discriminatory effect. The detection of inflammation at three out of six predefined non-synovial sites differentiated PMR patients from controls with a sensitivity/specificity of 73.8%/85.8% and overall better performance than detection of synovitis alone (sensitivity/specificity of 86.1%/36.1%, respectively). CONCLUSION: Contrast-enhanced MRI of the shoulder girdle is a reliable imaging tool with significant diagnostic value in the assessment of patients suffering from PMR and differentiation to other conditions for shoulder girdle pain.

Joint association of TyG index and high sensitivity C-reactive protein with cardiovascular disease: a national cohort study.

BACKGROUND: Both the triglyceride-glucose (TyG) index, as a surrogate marker of insulin resistance, and systemic inflammation are predictors of cardiovascular diseases; however, little is known about the coexposures and relative contributions of TyG index and inflammation to cardiovascular diseases. Using the nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), we conducted longitudinal analyses to evaluate the joint and mutual associations of the TyG index and high-sensitivity C-reactive protein (hsCRP) with cardiovascular events in middle-aged and older Chinese population. METHODS: This study comprised 8 658 participants aged at least 45 years from the CHARLS 2011 who are free of cardiovascular diseases at baseline. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Cardiovascular events were defined as the presence of physician-diagnosed heart disease and/or stroke followed until 2018.We performed adjusted Cox proportional hazards regression and mediation analyses. RESULTS: The mean age of the participants was 58.6 ± 9.0 years, and 3988 (46.1%) were females. During a maximum follow-up of 7.0 years, 2606 (30.1%) people developed cardiovascular diseases, including 2012 (23.2%) cases of heart diseases and 848 (9.8%) cases of stroke. Compared with people with a lower TyG index (< 8.6 [median level]) and hsCRP < 1 mg/L, those concurrently with a higher TyG and hsCRP had the highest risk of overall cardiovascular disease (adjusted hazard ratio [aHR], 1.300; 95% CI 1.155-1.462), coronary heart disease (aHR, 1.294; 95% CI 1.130-1.481) and stroke (aHR, 1.333; 95% CI 1.093-1.628), which were predominant among those aged 70 years or below. High hsCRP significantly mediated 13.4% of the association between the TyG index and cardiovascular disease, while TyG simultaneously mediated 7.9% of the association between hsCRP and cardiovascular risk. CONCLUSIONS: The findings highlight the coexposure effects and mutual mediation between the TyG index and hsCRP on cardiovascular diseases. Joint assessments of the TyG index and hsCRP should be underlined for the residual risk stratification and primary prevention of cardiovascular diseases, especially for middle-aged adults.

[How to Perform Autoantibody Testing for Autoimmune and Inflammatory Diseases of Peripheral Nerves and Muscles].

Measurement of autoantibodies is essential for the management of several peripheral nerve and muscle diseases. The clinical significance of autoantibody testing differs for each antibody. In addition, clinicians must understand several issues including the accuracy of the test, isotype and subclass distribution, and its relationship to disease activity. Moreover, many autoantibody tests are not covered by health insurance. With limited medical resources, clinicians are required to be up-to-date with the latest information to utilize test results in daily practice without misunderstanding.

Creating machine learning models that interpretably link systemic inflammatory index, sex steroid hormones, and dietary antioxidants to identify gout using the SHAP (SHapley Additive exPlanations) method.

Background: The relationship between systemic inflammatory index (SII), sex steroid hormones, dietary antioxidants (DA), and gout has not been determined. We aim to develop a reliable and interpretable machine learning (ML) model that links SII, sex steroid hormones, and DA to gout identification. Methods: The dataset we used to study the relationship between SII, sex steroid hormones, DA, and gout was from the National Health and Nutrition Examination Survey (NHANES). Six ML models were developed to identify gout by SII, sex steroid hormones, and DA. The seven performance discriminative features of each model were summarized, and the eXtreme Gradient Boosting (XGBoost) model with the best overall performance was selected to identify gout. We used the SHapley Additive exPlanation (SHAP) method to explain the XGBoost model and its decision-making process. Results: An initial survey of 20,146 participants resulted in 8,550 being included in the study. Selecting the best performing XGBoost model associated with SII, sex steroid hormones, and DA to identify gout (male: AUC: 0.795, 95% CI: 0.746- 0.843, accuracy: 98.7%; female: AUC: 0.822, 95% CI: 0.754- 0.883, accuracy: 99.2%). In the male group, The SHAP values showed that the lower feature values of lutein + zeaxanthin (LZ), vitamin C (VitC), lycopene, zinc, total testosterone (TT), vitamin E (VitE), and vitamin A (VitA), the greater the positive effect on the model output. In the female group, SHAP values showed that lower feature values of E2, zinc, lycopene, LZ, TT, and selenium had a greater positive effect on model output. Conclusion: The interpretable XGBoost model demonstrated accuracy, efficiency, and robustness in identifying associations between SII, sex steroid hormones, DA, and gout in participants. Decreased TT in males and decreased E2 in females may be associated with gout, and increased DA intake and decreased SII may reduce the potential risk of gout.

[Chinese expert consensus on the diagnosis and management of severe asthma (2024 edition)].

Severe asthma is the main cause of disability and death in patients with asthma, with a high risk of future disease, but also caused serious social and economic burden. The pathophysiological mechanisms such as obvious heterogeneity of airway inflammation, severe airway remodeling, influence of genetic factors, decreased glucocorticoid responsiveness, and many factors affecting asthma control make the treatment of severe asthma particularly difficult. In recent years, with the deepening of the understanding of the pathogenesis of asthma, especially the development of biologics targeting type 2 inflammation, a new approach has been opened up for the treatment of patients with severe asthma. How to correctly diagnose and evaluate severe asthma patients and how to choose treatment are still the perplexity and challenge in clinical practice. This expert consensus is based on the "Chinese Expert Consensus on the Diagnosis and Management of Severe Asthma" published in 2017 and combined with the latest research progress at home and abroad, and is updated on the definition, pathogenesis, diagnosis and evaluation, and treatment of severe asthma, especially the treatment recommendation for type 2 inflammatory biologics, so as to provide reference for the individualized diagnosis and treatment of severe asthma.

Evaluation of the inflammatory parameters as potential biomarkers of systemic inflammation extent and the disease severity in psoriasis patients.

The disease severity of psoriasis is mainly assessed subjectively via  psoriasis area and severity index (PASI) and body surface area (BSA), while an optimal measure of cutaneous response, may overlook systemic inflammation in psoriasis patients. The neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), monocyte to high density lipoprotein ratio (MHR), and systemic immune-inflammation index (SII) exhibit notable associations with the inflammation severity in multiple diseases. The aim of this retrospective study was to explore the associations between inflammatory parameters and the skin lesions' severity of psoriasis. After analysis, we found that patients with psoriasis had higher NLR, MLR, PLR, MHR, and SII levels compared to the control group. At baseline, the parameters of NLR (r = 0.124, P = 0.003), MLR (r = 0.153, P < 0.001), MHR (r = 0.217, P < 0.001) and SII (r = 0.141, P = 0.001) had a positive correlation with PASI in psoriasis patients. At the same time, we analyzed the patients who received different systemic therapy. We observed a significant decrease in NLR, PLR, MLR, and SII in psoriasis patients after treatment. Notably, TNF-α inhibitors and IL-17A inhibitors subgroups showed a more significant reduction than IL-23/IL-12/23 inhibitors and MTX medication. Additionally, we found the change of NLR (r = 0.194, P < 0.001), PLR (r = 0.104, P = 0.014), MLR (r = 0.191, P < 0.001), MHR (r = 0.106, P = 0.012), and SII (r = 0.228, P < 0.001) had a positive correlation with the change of PASI in psoriasis patients. In conclusion, this study suggests that NLR, MLR, and SII may serve as useful biomarkers for assessing systemic inflammation extent and disease severity in psoriasis patients.

Associations of novel complete blood count-derived inflammatory markers with psoriasis: a systematic review and meta-analysis.

Psoriasis is an immune-mediated disorder which primarily affects skin and has systemic inflammatory involvement. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and monocyte-to-lymphocyte ratio (MLR) are novel complete blood count (CBC)-derived markers which can reflect systemic inflammation. This study aimed to systematically investigate the associations of NLR, PLR, SII, and MLR with psoriasis. This study was performed in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. A comprehensive search of Pubmed, Embase, Scopus, and Google Scholar was conducted for relevant studies. Observational studies evaluating the correlations of NLR, PLR, SII, or MLR with psoriasis were included. The primary outcomes were the associations of these inflammatory markers with the presence and severity of psoriasis. The random-effect model was applied for meta-analysis. 36 studies comprising 4794 psoriasis patients and 55,121 individuals in total were included in the meta-analysis. All inflammatory markers were significantly increased in psoriasis groups compared to healthy controls (NLR: MD = 0.59, 95% CI: 0.47-0.7; PLR: MD = 15.53, 95% CI: 8.48-22.58; SII: MD = 111.58, 95% CI: 61.49-161.68; MLR: MD = 0.034, 95% CI: 0.021-0.048; all p < 0.001). Between-group mean differences in NLR and PLR were positively correlated with the mean scores of Psoriasis Area Severity Index (NLR: p = 0.041; PLR: p = 0.021). NLR, PLR, SII, and MLR are associated with the presence of psoriasis. NLR and PLR serve as significant indicators of psoriasis severity. These novel CBC-derived markers constitute potential targets in the screening and monitoring of psoriasis.

Inflammatory biomarkers in cardiac syndrome X: a systematic review and meta-analysis.

INTRODUCTION: In the current systematic review and meta-analysis, we aim to analyze the existing literature to evaluate the role of inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP), tumor necrosis factor-a (TNF-a), and interleukin-6 (IL-6) among individuals with cardiac syndrome X (CSX) compared to healthy controls. METHODS: We used PubMed, Web of Science, Scopus, Science Direct, and Embase to systematically search relevant publications published before April 2, 2023. We performed the meta-analysis using Stata 11.2 software (Stata Corp, College Station, TX). So, we used standardized mean difference (SMD) with a 95% confidence interval (CI) to compare the biomarker level between patients and healthy controls. The I2 and Cochran's Q tests were adopted to determine the heterogeneity of the included studies. RESULTS: Overall, 29 articles with 3480 participants (1855 with CSX and 1625 healthy controls) were included in the analysis. There was a significantly higher level of NLR (SMD = 0.85, 95%CI = 0.55-1.15, I2 = 89.0 %), CRP (SMD = 0.69, 95%CI = 0.38 to 1.02, p < 0.0001), IL-6 (SMD = 5.70, 95%CI = 1.91 to 9.50, p = 0.003), TNF-a (SMD = 3.78, 95%CI = 0.63 to 6.92, p = 0.019), and PLR (SMD = 1.38, 95%CI = 0.50 to 2.28, p = 0.02) in the CSX group in comparison with healthy controls. CONCLUSION: The results of this study showed that CSX leads to a significant increase in inflammatory biomarkers, including NLR, CRP, IL-6, TNF-a, and PLR.

Plasma mtDNA as a possible contributor to and biomarker of inflammation in rheumatoid arthritis.

OBJECTIVES: Neutrophil extracellular trap formation and cell-free DNA (cfDNA) contribute to the inflammation in rheumatoid arthritis (RA), but it is unknown if mitochondrial DNA (mtDNA) or nuclear DNA (nDNA) is more abundant in the circulation. It is unclear if DNA concentration measurements may assist in clinical decision-making. METHODS: This single-center prospective observational study collected plasma from consecutive RA patients and healthy blood donors. Platelets were removed, and mtDNA and nDNA copy numbers were quantified by polymerase chain reaction (PCR). RESULTS: One hundred six RA patients and 85 healthy controls (HC) were recruited. Circulating median mtDNA copy numbers were increased 19.4-fold in the plasma of patients with RA (median 1.1 x108 copies/mL) compared to HC (median 5.4 x106 copies/mL, p<0.0001). Receiver operating characteristics (ROC) curve analysis of mtDNA copy numbers identified RA patients with high sensitivity (92.5%) and specificity (89.4%) with an area under the curve (AUC) of 0.97, p <0.0001 and a positive likelihood ratio of 8.7. Demographic, serological (rheumatoid factor (RF) positivity, anti-citrullinated protein antibodies (ACPA) positivity) and treatment factors were not associated with DNA concentrations. mtDNA plasma concentrations, however, correlated significantly with disease activity score-28- erythrocyte sedimentation rate (DAS28-ESR) and increased numerically with increasing DAS28-ESR and clinical disease activity index (CDAI) activity. MtDNA copy numbers also discriminated RA in remission (DAS28 <2.6) from HC (p<0.0001). Also, a correlation was observed between mtDNA and the ESR (p = 0.006, R= 0.29). Similar analyses showed no significance for nDNA. CONCLUSION: In contrast to nDNA, mtDNA is significantly elevated in the plasma of RA patients compared with HC. Regardless of RA activity, the abundance of circulating mtDNA is a sensitive discriminator between RA patients and HC. Further validation of the diagnostic value of mtDNA testing is required.

Iron oxide nanoparticles for treatment and diagnosis of chronic inflammatory diseases: A systematic review.

Chronic inflammatory conditions are among the most prevalent diseases worldwide. Several debilitating diseases such as atherosclerosis, inflammatory bowel disease, rheumatoid arthritis, and Alzheimer's are linked to chronic inflammation. These conditions often develop into complex and fatal conditions, making early detection and treatment of chronic inflammation crucial. Current diagnostic methods show high variability and do not account for disease heterogeneity and disease-specific proinflammatory markers, often delaying the disease detection until later stages. Furthermore, existing treatment strategies, including high-dose anti-inflammatory and immunosuppressive drugs, have significant side effects and an increased risk of infections. In recent years, superparamagnetic iron oxide nanoparticles (SPIONs) have shown tremendous biomedical potential. SPIONs can function as imaging modalities for magnetic resonance imaging, and as therapeutic agents due to their magnetic hyperthermia capability. Furthermore, the surface functionalization of SPIONs allows the detection of specific disease biomarkers and targeted drug delivery. This systematic review explores the utility of SPIONs against chronic inflammatory disorders, focusing on their dual role as diagnostic and therapeutic agents. We extracted studies indexed in the Web of Science database from the last 10 years (2013-2023), and applied systematic inclusion criteria. This resulted in a final selection of 38 articles, which were analyzed for nanoparticle characteristics, targeted diseases, in vivo and in vitro models used, and the efficacy of the therapeutic or diagnostic modalities. The results revealed that ultrasmall SPIONs are excellent for imaging arterial and neuronal inflammation. Furthermore, novel therapies using SPIONs loaded with chemotherapeutic drugs show promise in the treatment of inflammatory diseases. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > In Vivo Nanodiagnostics and Imaging.

Association between dietary inflammation index and asthma COPD overlap.

There are few studies on the relationship between dietary habits and asthma-COPD overlap (ACO). In this study, we aimed to investigate the association between dietary inflammation index (DII) score and ACO. Data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2020. The DII score was first calculated and the demographic characteristics of the grouping based on the DII quartile were assessed. The weighted logistic regression model was used to study the relationship between DII and ACO. Subgroup analysis was used to further explore the differences in different subgroups. Restricted cubic spline (RCS) plot was used to show the general trend of DII score and disease risk, and threshold effect analysis was used to determine the inflection point. In a comparison of baseline characteristics, the highest ACO prevalence was found in the fourth quartile array of people in DII. An adjusted weighted logistic regression model showed that DII was positively correlated with the incidence of ACO. Subgroup analysis showed that the association was more pronounced in women, non-Hispanics, people with cardiovascular disease, and people without diabetes. The RCS graph shows that overall, the risk of ACO increases with the increase of DII score. Threshold effect analysis showed that the inflection point was 3.779, and the risk was more significant after the DII score was greater than the inflection point value (OR 2.001, 95% CI 1.334-3.001, P < 0.001). Higher DII scores were positively associated with ACO risk. These results further support diet as an intervention strategy for ACO prevention and treatment.

Predictive value of the systemic immune-inflammation index on one-year mortality in geriatric hip fractures.

BACKGROUND: Geriatric hip fractures are associated with a high incidence of mortality. This study examines the predictive value of the systemic immune-inflammation index (SII) on one-year mortality in elderly hip fracture patients. METHODS: A single-center retrospective study was conducted between February 2017 and October 2020. Three hundred and eleven surgically treated consecutive hip fracture patients were included in the study. Admission, postoperative first day, and postoperative fifth-day SII values were calculated. The receiver operating characteristic (ROC) curve was used to calculate the cut-off values, and patients were divided into high and low groups according to these cut-off values. After univariate Cox regression analysis, significant factors were included in the multivariate Cox proportional hazards model to adjust the effect of covariates and explore independent predictive factors associated with mortality. Further subgroup analysis was performed to evaluate the accuracy of the results for different clinical and biological characteristics. RESULTS: The mean age was 80.7 ± 8.0 years, and women made up the majority (67.8%) of the patients. The one-year mortality rate was 28.0%. After univariate and multivariate analyses, high postoperative fifth-day SII remained an independent predictor of one-year mortality (adjusted HR 2.16, 95% CI 1.38-3.38, p = 0.001). Older age, male gender, Charlson comorbidity index (CCI) ≥ 2, and hypoalbuminemia were found to be other independent predictors. The optimal cut-off value of the postoperative fifth-day SII was calculated at 1751.9 units (p < 0.001). CONCLUSION: The postoperative fifth-day SII is a simple and useful inflammatory biomarker for predicting one-year mortality in patients with hip fracture.

International Classification of Diseases Coding for Inflammatory Arthritides.

This quality improvement study investigates usage patterns of codes for inflammatory arthritides under International Statistical Classification of Diseases and Related Health Problems, Tenth Revision vs International Classification of Diseases, Ninth Revision.

[Le miR-224-5p régulé sert de biomarqueur pour l'insuffisance hépatique aiguë pédiatrique et régule l'inflammation en modulant ZBTB20]. / Upregulated miR-224-5p served as a biomarker for pediatric acute liver failure and regulate inflammation by modulating ZBTB20.

Pediatric acute liver failure (PALF) is a severe liver dysfunction with complex pathological mechanisms and rapid development. MiRNAs have been identified as promising biomarkers for human disease screening and monitoring. This study focused on evaluating the clinical significance of miR-224-5p in PALF and revealing its potential molecular mechanism in regulating liver cell injury. This study enrolled 103 children with PALF and 55 healthy children without liver diseases. Serum miR-224-5p levels were compared between the two groups, and their clinical significance was estimated by analyzing the correlation with clinicopathological features and outcomes of PALF children. In vitro, a normal liver cell was treated with lipopolysaccharide (LPS), and cell growth and inflammation were assessed by CCK8 and ELISA assay. Upregulated miR-224-5p in PALF showed significance in screening PALF children from healthy children with the sensitivity and specificity of 78.64% and 84.47%, respectively. Increasing serum miR-224-5p in PALF children was closely associated with increasing prothrombin time, alanine transaminase, international normalized ratio, total bilirubin, ammonia, and aspartic transaminase and decreasing albumin of PALF children. MiR-224-5p was also identified as a risk factor for adverse outcomes in children with PALF. In LPS-treated liver cells, miR-224-5p could negatively regulate ZBTB20, and silencing miR-224-5p could alleviate the inhibited cell growth and promoted inflammation by LPS, which was reversed by ZBTB20 knockdown. Increasing miR-224-5p distinguished PALF children, predict severe disease development and risk of adverse prognosis. miR-224-5p also reguled LPS-induced liver cell injury via negatively regulating ZBTB20.

Sodium-glucose cotransporter 2 inhibitors, inflammation, and heart failure: a two-sample Mendelian randomization study.

BACKGROUND: Sodium-glucose cotransporter 2 (SGLT-2) inhibitors are increasingly recognized for their role in reducing the risk and improving the prognosis of heart failure (HF). However, the precise mechanisms involved remain to be fully delineated. Evidence points to their potential anti-inflammatory pathway in mitigating the risk of HF. METHODS: A two-sample, two-step Mendelian Randomization (MR) approach was employed to assess the correlation between SGLT-2 inhibition and HF, along with the mediating effects of inflammatory biomarkers in this relationship. MR is an analytical methodology that leverages single nucleotide polymorphisms as instrumental variables to infer potential causal inferences between exposures and outcomes within observational data frameworks. Genetic variants correlated with the expression of the SLC5A2 gene and glycated hemoglobin levels (HbA1c) were selected using datasets from the Genotype-Tissue Expression project and the eQTLGen consortium. The Genome-wide association study (GWAS) data for 92 inflammatory biomarkers were obtained from two datasets, which included 14,824 and 575,531 individuals of European ancestry, respectively. GWAS data for HF was derived from a meta-analysis that combined 26 cohorts, including 47,309 HF cases and 930,014 controls. Odds ratios (ORs) and 95% confidence interval (CI) for HF were calculated per 1 unit change of HbA1c. RESULTS: Genetically predicted SGLT-2 inhibition was associated with a reduced risk of HF (OR 0.42 [95% CI 0.30-0.59], P < 0.0001). Of the 92 inflammatory biomarkers studied, two inflammatory biomarkers (C-X-C motif chemokine ligand 10 [CXCL10] and leukemia inhibitory factor) were associated with both SGLT-2 inhibition and HF. Multivariable MR analysis revealed that CXCL10 was the primary inflammatory cytokine related to HF (MIP = 0.861, MACE = 0.224, FDR-adjusted P = 0.0844). The effect of SGLT-2 inhibition on HF was mediated by CXCL10 by 17.85% of the total effect (95% CI [3.03%-32.68%], P = 0.0183). CONCLUSIONS: This study provides genetic evidence supporting the anti-inflammatory effects of SGLT-2 inhibitors and their beneficial impact in reducing the risk of HF. CXCL10 emerged as a potential mediator, offering a novel intervention pathway for HF treatment.

Systemic immune-inflammation index as a novel predictor of major adverse cardiovascular events in patients undergoing percutaneous coronary intervention: a meta-analysis of cohort studies.

BACKGROUND: The Systemic Immune-Inflammation Index (SII), a novel marker of inflammation based on neutrophil, platelet, and lymphocyte counts, has demonstrated potential prognostic value in patients undergoing percutaneous coronary intervention (PCI). Our aim was to assess the correlation between the SII and major adverse cardiovascular events following percutaneous coronary intervention. METHODS: We searched PubMed, Web of Science, Embase, and The Cochrane Library from inception to November 20, 2023, for cohort studies investigating the association between SII and the occurrence of MACEs after PCI. Statistical analysis was performed using Revman 5.3, with risk ratios (RRs) and 95% confidence intervals (CIs) as relevant parameters. RESULTS: In our analysis, we incorporated a total of 8 studies involving 11,117 participants. Our findings revealed that a high SII is independently linked to a increased risk of MACEs in PCI patients (RR: 2.08,95%CI: 1.87-2.32, I2 = 42%, p < 0.00001). Additionally, we demonstrated the prognostic value of SII in all-cause mortality, heart failure, and non-fatal myocardial infarction. CONCLUSIONS: Elevated SII may serve as a potential predictor for subsequent occurrence of MACEs in patients undergoing PCI. TRIAL REGISTRATION: Our protocol was registered in PROSPERO (registration number: CRD42024499676).

Exploration of Diagnostic Markers Associated with Inflammation in Chronic Kidney Disease Based on WGCNA and Machine Learning.

Chronic kidney disease (CKD) is a common disorder related to inflammatory pathways; its effective management remains limited. This study aimed to use bioinformatics analysis to find diagnostic markers that might be therapeutic targets for CKD. CKD microarray datasets were screened from the GEO database and the differentially expressed genes (DEGs) in CKD dataset GSE98603 were analyzed. Gene set variation analysis (GSVA) was used to explore the activity scores of the inflammatory pathways and samples. Algorithms such as weighted gene co-expression network analysis (WGCNA) and Lasso were used to screen CKD diagnostic markers related to inflammation. Then functional enrichment analysis of inflammation-related DEGs was performed. ROC curves were conducted to examine the diagnostic value of inflammation-related hub-genes. Lastly, quantitative real-time PCR further verified the prediction of bioinformatics. A total of 71 inflammation-related DEGs were obtained, of which 5 were hub genes. Enrichment analysis showed that these genes were significantly enriched in inflammation-related pathways (NF-κB, JAK-STAT, and MAPK signaling pathways). ROC curves showed that the 5 CKD diagnostic markers (TIGD7, ACTA2, ACTG2, MAP4K4, and HOXA11) also exhibited good diagnostic value. In addition, TIGD7, ACTA2, ACTG2, and HOXA11 expression was downregulated while MAP4K4 expression was upregulated in LPS-induced HK-2 cells. The present study identified TIGD7, ACTA2, ACTG2, MAP4K4, and HOXA11 as reliable CKD diagnostic markers, thereby providing a basis for further understanding of CKD in clinical treatments.

Correlation between blood inflammatory indices and carotid intima-media thickness in the middle-aged and elderly adults.

OBJECTIVES: This study aimed to investigate the correlations between carotid intima-media thickness (IMT) and systemic immune inflammation index (SII), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte (NLR) ratio. MATERIALS AND METHODS: This was a cross-sectional study enrolling a total of 582 middle-aged and elderly patients. The correlations between SII, PLR, and NLR with IMT were assessed using logistic regression models, which were subsequently incorporated into the underlying models with traditional risk factors and their predictive values for IMT. RESULTS: NLR exhibited a significant correlation with IMT in the simple regression analysis (ß = 0.01, 95 %CI= 0.00-0.02, p < 0.05). After controlling for potential confounding variables in the multivariate analysis, the association between NLR and both Maximum IMT [ß = 0.04, 95 %CI = 0.02-0.07, p = 0.0006] and Mean IMT [ß = 0.05, 95 %CI = 0.02-0.07, p = 0.0001] remained statistically significant. Additionally, PLR was found to be a significant independent predictor of Maximum IMT [ß = 0.04, 95 % CI =0.00-0.07, p = 0.0242] and Mean IMT [ß = 0.04, 95 % CI = 0.01-0.07, p = 0.0061]. Similarly, SII was identified as an independent predictor of Maximum IMT [ß = 1.87, 95 % CI =1.24, p = 0.0003]. The study found a significant positive correlation between Maximum IMT and the levels NLR, PLR, and SII. Specifically, in the Maximum IMT group, higher quartiles of NLR, PLR, and SII were associated with increased odds ratios (OR) for elevated IMT levels, with statistically significant results for NLR (Q4vsQ1: OR 3.87, 95 % CI 1.81-8.29), PLR (Q4vsQ1: OR 2.84, 95 % CI 1.36-5.95), and SII (Q4vsQ1: OR 2.64, 95 % CI 1.30-5.37). Finally, the inclusion of NLR, PLR, and NLR+PLR+SII in the initial model with traditional risk factors resulted in a marginal improvement in the predictive ability for Maximum IMT, as evidenced by the net reclassification index (p < 0.05). CONCLUSIONS: This study discovered a positive correlation between SII, PLR, NLR, and IMT, which are likely to emerge as new predictors for IMT thickening. These findings lay a theoretical reference for future predictive research and pathophysiological research on carotid intima-media thickening.