The Relationship between Retinol-Binding Protein 4 and Markers of Inflammation and Thrombogenesis in Children with Kawasaki Disease

Prediction model for developing neuropsychiatric systemic lupus erythematosus in lupus patients

OBJECTIVE

This study aimed to construct a predictive model for assessing the risk of development of neuropsychiatric systemic lupus erythematosus (NPSLE) among patients with SLE based on clinical, laboratory, and meteorological data.

METHODS

A total of 2232 SLE patients were included and were randomly assigned into training and validation sets. Variables such as clinical and laboratory data and local meteorological data were screened by univariate and least absolute shrinkage and selection operator (LASSO) logistic regression modelling. After 10-fold cross-validation, the predictive model was built by multivariate logistic regression, and a nomogram was constructed to visualize the risk of NPSLE. The efficacy and accuracy of the model were assessed by receiver operating characteristic (ROC) curve and calibration curve analysis. Net clinical benefit was assessed by decision curve analysis.

RESULTS

Variables that were included in the predictive model were anti-dsDNA, anti-SSA, lymphocyte count, hematocrit, erythrocyte sedimentation rate, pre-albumin, retinol binding protein, creatine kinase isoenzyme MB, Nterminal brain natriuretic peptide precursor, creatinine, indirect bilirubin, fibrinogen, hypersensitive C-reactive protein, CO, and mild contamination. The nomogram showed a broad prediction spectrum; the area under the curve (AUC) was 0.895 (0.858-0.931) for the training set and 0.849 (0.783-0.916) for the validation set.

CONCLUSION

The model exhibits good predictive performance and will confer clinical benefit in NPSLE risk calculation. Key Points • Clinical, laboratory, and meteorological data were incorporated into a predictive model for neuropsychiatric systemic lupus erythematosus (NPSLE) in SLE patients. • Anti-dsDNA, anti-SSA, LYM, HCT, ESR, hsCRP, IBIL, PA, RBP, CO, Fib, NT-proBNP, Crea, CO, and mild contamination are predictors of the development of NPSLE and may have potential for research. • The nomogram has good predictive performance and clinical value and can be used to guide clinical diagnosis and treatment.

A novel multiplex biomarker panel for profiling human acute and chronic kidney disease

Acute and chronic kidney disease continues to confer significant morbidity and mortality in the clinical setting. Despite high prevalence of these conditions, few validated biomarkers exist to predict kidney dysfunction. In this study, we utilized a novel kidney multiplex panel to measure 21 proteins in plasma and urine to characterize the spectrum of biomarker profiles in kidney disease. Blood and urine samples were obtained from age-/sex-matched healthy control subjects (HC), critically-ill COVID-19 patients with acute kidney injury (AKI), and patients with chronic or end-stage kidney disease (CKD/ESKD). Biomarkers were measured with a kidney multiplex panel, and results analyzed with conventional statistics and machine learning. Correlations were examined between biomarkers and patient clinical and laboratory variables. Median AKI subject age was 65.5 (IQR 58.5-73.0) and median CKD/ESKD age was 65.0 (IQR 50.0-71.5). Of the CKD/ESKD patients, 76.1% were on hemodialysis, 14.3% of patients had kidney transplant, and 9.5% had CKD without kidney replacement therapy. In plasma, 19 proteins were significantly different in titer between the HC versus AKI versus CKD/ESKD groups, while NAG and RBP4 were unchanged. TIMP-1 (PPV 1.0, NPV 1.0), best distinguished AKI from HC, and TFF3 (PPV 0.99, NPV 0.89) best distinguished CKD/ESKD from HC. In urine, 18 proteins were significantly different between groups except Calbindin, Osteopontin and TIMP-1. Osteoactivin (PPV 0.95, NPV 0.95) best distinguished AKI from HC, and β2-microglobulin (PPV 0.96, NPV 0.78) best distinguished CKD/ESKD from HC. A variety of correlations were noted between patient variables and either plasma or urine biomarkers. Using a novel kidney multiplex biomarker panel, together with conventional statistics and machine learning, we identified unique biomarker profiles in the plasma and urine of patients with AKI and CKD/ESKD. We demonstrated correlations between biomarker profiles and patient clinical variables. Our exploratory study provides biomarker data for future hypothesis driven research on kidney disease.

Neutrophil to Lymphocyte Ratio as a Biomarker for Predicting the Coronary Artery Abnormality in Kawasaki Disease: A Meta-Analysis

We conducted a systematic review and meta-analysis on the relationship between the neutrophil to lymphocyte ratio (NLR) and coronary artery abnormalities (CAA) in patients with Kawasaki disease (KD), according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements. We searched PubMed, Scopus, Web of Science, Embase, TRIP, Google Scholar, and ProQuest up to the 8th of August 2022. This was done to retrieve eligible studies. No date or language limitations were considered in this study. Methodology quality assessment was conducted according to the Newcastle–Ottawa scale (NOS). Standard mean difference (SMD) and its 95% confidence interval (CI) were used to depict the pooled continuous variables. Finally, 17 articles with 6334 KD patients, of whom 1328 developed CAA, were enrolled in this meta-analysis. NLR level was significantly higher in KD patients with CAA compared to those without CAA (SMD =0.81; 95% CI =0.05–1.57, P = 0.03). In addition, NLR level was significantly higher in patients with coronary artery aneurysms than those without coronary artery aneurysms (SMD =2.29; 95% CI =0.18–4.41, P = 0.03). However, no significant association between NLR and coronary artery dilation was observed in this meta-analysis (SMD =0.56; 95% CI = -0.86–1.99). There was no publication bias for the pooled SMD of NLR for coronary artery abnormality in KD (Egger's test P = 0.82; Begg's test P = 0.32). The NLR may be useful in monitoring CAA development in these patients and may further imply a mechanistic role in potential inflammation that mediates this process.

Thromboinflammatory Processes at the Nexus of Metabolic Dysfunction and Prostate Cancer: The Emerging Role of Periprostatic Adipose Tissue

Simple Summary

As overweight and obesity increase among the population worldwide, a parallel increase in the number of individuals diagnosed with prostate cancer was observed. There appears to be a relationship between both diseases where the increase in the mass of fat tissue can lead to inflammation. Such a state of inflammation could produce many factors that increase the aggressiveness of prostate cancer, especially if this inflammation occurred in the fat stores adjacent to the prostate. Another important observation that links obesity, fat tissue inflammation, and prostate cancer is the increased production of blood clotting factors. In this article, we attempt to explain the role of these latter factors in the effect of increased body weight on the progression of prostate cancer and propose new ways of treatment that act by affecting how these clotting factors work.

Abstract

The increased global prevalence of metabolic disorders including obesity, insulin resistance, metabolic syndrome and diabetes is mirrored by an increased incidence of prostate cancer (PCa). Ample evidence suggests that these metabolic disorders, being characterized by adipose tissue (AT) expansion and inflammation, not only present as risk factors for the development of PCa, but also drive its increased aggressiveness, enhanced progression, and metastasis. Despite the emerging molecular mechanisms linking AT dysfunction to the various hallmarks of PCa, thromboinflammatory processes implicated in the crosstalk between these diseases have not been thoroughly investigated. This is of particular importance as both diseases present states of hypercoagulability. Accumulating evidence implicates tissue factor, thrombin, and active factor X as well as other players of the coagulation cascade in the pathophysiological processes driving cancer development and progression. In this regard, it becomes pivotal to elucidate the thromboinflammatory processes occurring in the periprostatic adipose tissue (PPAT), a fundamental microenvironmental niche of the prostate. Here, we highlight key findings linking thromboinflammation and the pleiotropic effects of coagulation factors and their inhibitors in metabolic diseases, PCa, and their crosstalk. We also propose several novel therapeutic targets and therapeutic interventions possibly modulating the interaction between these pathological states.

All trans retinoic acid alleviates coronary stenosis by regulating smooth muscle cell function in a mouse model of Kawasaki disease

Coronary artery (CA) stenosis is a detrimental and often life-threatening sequela in Kawasaki disease (KD) patients with coronary artery aneurysm (CAA). Therapeutic strategies for these patients have not yet been established. All-trans-retinoic acid (atRA) is a modulator of smooth muscle cell functions. The purpose of this study was to investigate the effect of atRA on CA stenosis in a mouse model of KD. Lactobacillus casei cell wall extract (LCWE) was intraperitoneally injected into 5-week-old male C57BL/6 J mice to induce CA stenosis. Two weeks later, the mice were orally administered atRA (30 mg/kg) 5 days per week for 14 weeks (LCWE + atRA group, n = 7). Mice in the untreated group (LCWE group, n = 6) received corn oil alone. Control mice were injected with phosphate-buffered saline (PBS, n = 5). Treatment with atRA significantly suppressed CA inflammation (19.3 ± 2.8 vs 4.4 ± 2.8, p < 0.0001) and reduced the incidence of CA stenosis (100% vs 18.5%, p < 0.05). In addition, atRA suppressed the migration of human coronary artery smooth muscle cells (HCASMCs) induced by platelet-derived growth factor subunit B homodimer (PDGF-BB). In conclusion, atRA dramatically alleviated CA stenosis by suppressing SMC migration. Therefore, it is expected to have clinical applications preventing CA stenosis in KD patients with CAA.