Inflammation-related Biomarkers Research Articles

The current state of inflammation-related research in prostate cancer: a bibliometric analysis and systematic review

BackgroundProstate cancer (PCa) is the second most prevalent malignancy among men globally. The diagnosis, treatment, and prognosis of prostate cancer frequently fall short of expectations. In recent years, the connection between inflammation and prostate cancer has attracted considerable attention. However, there is a lack of bibliometric studies analyzing the research on inflammation within the domain of prostate cancer.Research methodsWe utilized the Web of Science Core Collection (WOSCC) as our data source to extract articles and reviews related to inflammation in prostate cancer, published up until April 12, 2024. The collected data underwent meticulous manual screening, followed by bibliometric analysis and visualization using the Biblioshiny package in R.ResultsThis study encompasses an analysis of 2,786 papers focusing on inflammation-related research within the realm of prostate cancer. Recent years have seen a significant proliferation of publications in this area, with the United States and China being the foremost contributors. The most prolific author in this domain is Demarzoam, with Johns Hopkins University standing out as the most influential institution. The leading journal in disseminating these studies is PROSTATE. Keyword co-occurrence analysis reveals that ‘inflammation-related biomarkers’, ‘inflammation index’, and ‘tumor immune microenvironment’ represent the current research hotspots and frontiers.ConclusionThe findings of this bibliometric study serve to illuminate the current landscape of inflammation-related research in the field of prostate cancer, while further augmenting the discourse on inflammation-mediated cancer therapeutics. Of particular note is the potential of these discoveries to facilitate a more nuanced understanding among researchers regarding the interplay between inflammation and prostate cancer.

Mitigative Effects of Topical Norfloxacin on an Imiquimod-Induced Murine Model of Psoriasis.

Psoriasis is a chronic, inflammatory dermatosis characterized by thickened, reddened, and scaly skin lesions. Norfloxacin is a fluoroquinolone antibiotic with enhanced antioxidant, anti-inflammatory, and immunomodulatory bioactivities. The aim of this study was to figure out the possible impact of topical norfloxacin on an imiquimod-induced model of psoriasis in mice. Thirty albino-type mice were split into five distinct groups of six animals each. The control group included healthy mice that had not received any treatment. The induction group was given the vehicle 2 h after the topical imiquimod, once daily for 8 days. Two hours after receiving topical imiquimod, the treatment groups including calcipotriol, norfloxacin 2.5%, and norfloxacin 5% were given topical ointments containing calcipotriol 0.005%, norfloxacin 2.5%, and norfloxacin 5%, for 8 days. Topical norfloxacin ointment significantly reduced the severity of imiquimod-exacerbated psoriatic lesions including erythema, shiny-white scaling, and acanthosis and fixed histological abnormalities. Furthermore, imiquimod-subjected mice treated with a higher concentration of norfloxacin ointment exhibited dramatically lower skin levels of inflammation-related biomarkers like IFN-γ, TNF-α, IL-6, IL-17A, IL-23, and TGF-β but higher levels of IL-10. They also demonstrated a notable decrease in angiogenesis parameters such as VEGF and IL-8, a substantial reduction in oxidative indicators like MDA and MPO, and a considerable rise in antioxidant enzymes like SOD and CAT. This study offers novel evidence that norfloxacin may assist in controlling inflammatory dermatoses like psoriasis by minimizing the severity of psoriatic plaques, correcting histological alterations, and diminishing the production of inflammatory, oxidative, and angiogenetic parameters.

The Relationship of Adherence to the Mediterranean Diet with Disease Activity and Quality of Life in Crohn's Disease Patients.

Background and Objectives: Emerging evidence is placing the Mediterranean diet (MD) in the spotlight as a potential dietary model that could benefit inflammatory bowel disease (IBD) patients in terms of prevention and progress of the disease. The main aim of the present study is to shed some light on the relationship between the adherence to the MD and the degree of disease activity, as well as the quality of life in patients with Crohn's disease (CD). Materials and Methods: An administered questionnaire was used to assess and record a number of parameters, including recent medical and weight history, anthropometric characteristics, disease activity (in remission or active disease), and quality of life of both male and female CD patients. Moreover, the level of compliance of the participants to the Mediterranean diet model was evaluated and its relationship with disease activity and quality of life was investigated. Results: Adherence to the MD was significantly higher in patients with inactive disease than in those with active disease (p = 0.019). According to the correlation analysis conducted, adherence to the MD was negatively correlated with disease activity (p = 0.039) and positively correlated with quality of life (QoL) (p = 0.046) of the participants. Intake of fruits, vegetables, and dairy products was significantly higher in remission patients (p = 0.046, p = 0.001, p = 0.041, respectively). Conclusions: We conclude, according to the findings of the study, that adherence to the MD is associated with disease activity and QoL in patients with CD. Future research should focus on MD intervention studies on IBD patients in order to assess its effect on modulating disease activity/course and related inflammatory biomarkers.

Sex Differences in Inflammation-Related Biomarkers Detected with OCT in Patients with Diabetic Macular Edema

PurposeTo investigate sex-based differences in inflammation-related biomarkers on Spectral-Domain Optical Coherence Tomography (SD-OCT). DesignCross-sectional study. ParticipantsPatients with diabetic macular edema (DME) between February 1, 2019, and March 31, 2023, without intravitreal anti–vascular endothelial growth factor (anti-VEGF) injection within the prior six months. MethodsWe reviewed each patient’s medical record for age, biological sex, race and ethnicity, most recent glycated hemoglobin level (HbA1c), visual acuity (VA), and central macular thickness (CMT). OCT biomarkers that have been found in literature to be associated with inflammation, including disorganization of retinal inner layers (DRIL), retinal hyperreflective foci (HRF), hyperreflective choroidal foci (HCF), subfoveal neuroretinal detachment (SND), and perturbation in retinal nerve fiber layer (RNFL) thickness, ganglion cell layer (GCL) thickness, and inner nuclear layer (INL) thickness were evaluated by graders masked to the clinical characteristics of the patients. We performed multivariable regression analyses with the OCT biomarkers as the outcome variables and sex, age, HbA1c, and CMT as independent variables. Main Outcome MeasuresOCT inflammation-related biomarkers as listed above ResultsFemale patients were on average two years older than male patients (P = 0.041). There were no significant differences in race and ethnicity, HbA1c, VA, or CMT between male and female patients. After controlling for age, HbA1c, and CMT, we found male sex to be associated with more HRF (incidence rate ratio [IRR] = 1.19, 95% confidence interval [CI] = 1.10 – 1.29), more HCF (odds ratio = 2.01, 95% CI = 1.12 – 3.64), and thicker INL (7 μm thicker in males, 95% CI = 2 – 12). Sex was not a significant predictor for either DRIL or SND in the multivariable regression models. Patients with higher HbA1c were more likely to have more HRF (IRR = 1.02 per 1 point increase, 95% CI = 1.00 – 1.04) after controlling for other factors. ConclusionsMale sex was correlated with more inflammation-related biomarkers on OCT including more HRF, more HCF, and thicker INL, after accounting for age, glycemic control, and amount of DME. Further studies are needed to evaluate the potential implications of these sex-based differences for individualized treatment.

Identification and analysis of inflammation-related biomarkers in tetralogy of Fallot.

Studies have revealed that inflammatory response is relevant to the tetralogy of Fallot (TOF). However, there are no studies to systematically explore the role of the inflammation-related genes (IRGs) in TOF. Therefore, based on bioinformatics, we explored the biomarkers related to inflammation in TOF, laying a theoretical foundation for its in-depth study. TOF-related datasets (GSE36761 and GSE35776) were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between TOF and control groups were identified in GSE36761. And DEGs between TOF and control groups were intersected with IRGs to obtain differentially expressed IRGs (DE-IRGs). Afterwards, the least absolute shrinkage and selection operator (LASSO) and random forest (RF) were utilized to identify the biomarkers. Next, immune analysis was carried out. The transcription factor (TF)-mRNA, lncRNA-miRNA-mRNA, and miRNA-single nucleotide polymorphism (SNP)-mRNA networks were created. Finally, the potential drugs targeting the biomarkers were predicted. There were 971 DEGs between TOF and control groups, and 29 DE-IRGs were gained through the intersection between DEGs and IRGs. Next, a total of five biomarkers (MARCO, CXCL6, F3, SLC7A2, and SLC7A1) were acquired via two machine learning algorithms. Infiltrating abundance of 18 immune cells was significantly different between TOF and control groups, such as activated B cells, neutrophil, CD56dim natural killer cells, etc. The TF-mRNA network contained 4 mRNAs, 31 TFs, and 33 edges, for instance, ELF1-CXCL6, CBX8-SLC7A2, ZNF423-SLC7A1, ZNF71-F3. The lncRNA-miRNA-mRNA network was created, containing 4 mRNAs, 4 miRNAs, and 228 lncRNAs. Afterwards, nine SNPs locations were identified in the miRNA-SNP-mRNA network. A total of 21 drugs were predicted, such as ornithine, lysine, arginine, etc. Our findings detected five inflammation-related biomarkers (MARCO, CXCL6, F3, SLC7A2, and SLC7A1) for TOF, providing a scientific reference for further studies of TOF.

Blood-based inflammatory protein biomarker panel for the prediction of relapse and severity in patients with neuromyelitis optica spectrum disorder: A prospective cohort study.

To date, most existing models for predicting neuromyelitis optica spectrum disorder (NMOSD) are based primarily on clinical characteristics. Blood-based NMOSD severity and prognostic predictive immune- and inflammation-related biomarkers are needed. We aimed to investigate the associations between plasma inflammatory biomarkers and relapse and attack severity in NMOSD. This two-step, single-center prospective cohort study included discovery and validation cohorts. We quantified 92 plasma inflammatory proteins by using Olink's proximity extension assay and identified differentially expressed proteins in the relapse group (relapse within 1 year of follow-up) and severe attack group. To define a new molecular prognostic model, we calculated the risk score of each patient based on the key protein signatures and validated the results in the validation cohort. The relapse prediction model, including FGF-23, DNER, GDNF, and SLAMF1, predicted the 1-year relapse risk. The severe attack prediction model, including PD-L1 and MCP-2, predicted the severe clinical attack risk. Both the relapse and severe attack prediction models demonstrated good discriminative ability and high accuracy in the validation cohort. Our discovered biomarker signature and prediction models may complement current clinical risk stratification approaches. These inflammatory biomarkers could contribute to the discovery of therapeutic interventions and prevent NMOSD progression.

Preoperative examination of inflammatory biomarkers in relation to the prognosis of postoperative complications after heart transplantation

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Semmelweis University Heart transplantation (HTX) is the definitive therapy for end-stage heart failure. Although complications have drastically decreased with modern immunosuppressive therapy, surgical and anesthetic techniques, significant complications such as graft failure, acute rejection or infection must still be expected. The purpose of the study is to examine cytokine pathways linked to inflammation from direct preoperative serum samples, which can serve as prognostic factors in relation to septic events and mortality in the early postoperative period. The study was conducted using the blood samples of 102 patients who underwent HTX. Blood samples were taken from the patients immediately before HTX. The amounts of a total of 32 cytokines and related proteins were determined using LEGENDplex assays. After that, we correlated the biomarker amounts determined in the serum samples with the end points we indicated. In patients undergoing HTX who developed septic events during postoperative intensive care, the preoperative MMP2 serum concentration was significantly higher compared to other patients undergoing HTX (n=23, p=0.04). Independent predictors of mortality in the intensive care unit (n=5) were preoperative MRP8/14 (AUC=0.8), NGAL (AUC=0.75), IGFBP-4 (AUC=0.73), cystatin C (AUC=0.7) and the MMP2 (AUC=0.74) serum concentrations. Patients transplanted from left ventricular mechanical circulatory support (LVAD) (n=11) were examined as a separate group, where early postoperative mortality was significantly higher (n=4, p=0.02), the independent predictor of which was the concentration of IGFBP-4 (p=0.04 , AUC=0.73). Based on our results, it can be said that the differences in the preoperative concentration of certain inflammatory biomarkers that can be measured in the serum show correlations with the postoperative septic events and mortality of patients undergoing HTX.

Acupuncture improves neurological function and anti-inflammatory effect in patients with acute ischemic stroke: A double-blinded randomized controlled trial

Background and purposeAcupuncture exerts an anti-inflammatory effect and is recommended by the World Health Organization as a complementary therapy for stroke. This study investigated the improvement in neurological function outcome in acute-stage intervention of acute ischemic stroke (AIS), and the anti-inflammatory effect of early acupuncture. MethodsFifty patients with AIS were randomly assigned to either a control group (CG, 25 patients, received sham acupuncture) or treatment group (TG, 25 patients, received acupuncture treatment). Acupuncture intervention was administered twice a week for a total of 8 sessions over 4 consecutive weeks. The primary outcome was the changes in the National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), and Barthel Index (BI) scores. The secondary outcome was the changes in serum inflammation-related biomarker levels.(ANAIS trial) ResultsA total of 35 patients (18 patients in the CG and 17 patients in the TG) completed the trial. The reduction in NIHSS scores was greater in the TG than in the CG between V2 (second assessment administered after acupuncture intervention) and V1 (first assessment administered before acupuncture intervention; 4.33 ± 1.91 vs. 2.68 ± 1.42, p = 0.005) and between V3 (third assessment administered 28 days after last acupuncture intervention) and V1 (6.00 ± 2.53 vs. 3.83 ± 2.31, p = 0.012). The increase in BI scores was greater in the TG than in the CG between V2 and V1 (28.89 ± 15.39 vs. 14.21 ± 19.38, p = 0.016) and between V3 and V1 (39.41 ± 20.98 vs. 25.00 ± 18.47, p = 0.038). Among participants with high inflammation, the increase in serum IL-12p70 level between V2 and V1 was greater in the TG than in the CG (0.20 ± 0.19 vs. −0.14 ± 0.30, pg/mL p = 0.006). ConclusionsAcupuncture improved the neurological function of patients with AIS, and the relationship between acupuncture improving neurological function and anti-inflammatory effect needs further study. In addition, studies with larger sample sizes and longer follow-ups as well as multicenter clinical trials are expected in the future.

Multiplex proteomics identifies inflammation-related plasma biomarkers for aging and cardio-metabolic disorders

Abstract Background Cardio-metabolic disorders (CMDs) are common in aging people and are pivotal risk factors for cardiovascular diseases (CVDs). Inflammation is involved in the pathogenesis of CVDs and aging, but the underlying inflammatory molecular phenotypes in CMDs and aging are still unknown. Method We utilized multiple proteomics to detect 368 inflammatory proteins in the plasma of 30 subjects, including healthy young individuals, healthy elderly individuals, and elderly individuals with CMDs, by Proximity Extension Assay technology (PEA, O-link). Protein-protein interaction (PPI) network and functional modules were constructed to explore hub proteins in differentially expressed proteins (DEPs). The correlation between proteins and clinical traits of CMDs was analyzed and diagnostic value for CMDs of proteins was evaluated by ROC curve analysis. Result Our results revealed that there were 161 DEPs (adjusted p < 0.05) in normal aging and EGF was the most differentially expressed hub protein in normal aging. Twenty-eight DEPs were found in elderly individuals with CMDs and MMP1 was the most differentially expressed hub protein in CMDs. After the intersection of DEPs in aging and CMDs, there were 10 overlapping proteins: SHMT1, MVK, EGLN1, SLC39A5, NCF2, CXCL6, IRAK4, REG4, PTPN6, and PRDX5. These proteins were significantly correlated with the level of HDL-C, TG, or FPG in plasma. They were verified to have good diagnostic value for CMDs in aging with an AUC > 0.7. Among these, EGLN1, NCF2, REG4, and SLC39A2 were prominently increased both in normal aging and aging with CMDs. Conclusion Our results could reveal molecular markers for normal aging and CMDs, which need to be further expanded the sample size and to be further investigated to predict their significance for CVDs.

Addition of inflammation-related biomarkers to the CAIDE model for risk prediction of all-cause dementia, Alzheimer’s disease and vascular dementia in a prospective study

BackgroundIt is of interest whether inflammatory biomarkers can improve dementia prediction models, such as the widely used Cardiovascular Risk Factors, Aging and Dementia (CAIDE) model.MethodsThe Olink Target 96 Inflammation panel was assessed in a nested case-cohort design within a large, population-based German cohort study (n = 9940; age-range: 50–75 years). All study participants who developed dementia over 20 years of follow-up and had complete CAIDE variable data (n = 562, including 173 Alzheimer’s disease (AD) and 199 vascular dementia (VD) cases) as well as n = 1,356 controls were selected for measurements. 69 inflammation-related biomarkers were eligible for use. LASSO logistic regression and bootstrapping were utilized to select relevant biomarkers and determine areas under the curve (AUCs).ResultsThe CAIDE model 2 (including Apolipoprotein E (APOE) ε4 carrier status) predicted all-cause dementia, AD, and VD better than CAIDE model 1 (without APOE ε4) with AUCs of 0.725, 0.752 and 0.707, respectively. Although 20, 7, and 4 inflammation-related biomarkers were selected by LASSO regression to improve CAIDE model 2, the AUCs did not increase markedly. CAIDE models 1 and 2 generally performed better in mid-life (50–64 years) than in late-life (65–75 years) sub-samples of our cohort, but again, inflammation-related biomarkers did not improve their predictive abilities.ConclusionsDespite a lack of improvement in dementia risk prediction, the selected inflammation-related biomarkers were significantly associated with dementia outcomes and may serve as a starting point to further elucidate the pathogenesis of dementia.

INFLAMMATION's cognitive impact revealed by a novel "Line of Identity" approach.

Dementia is an "overdetermined" syndrome. Few individuals are demented by any single biomarker, while several may independently explain small fractions of dementia severity. It may be advantageous to identify individuals afflicted by a specific biomarker to guide individualized treatment. We aim to validate a psychometric classifier to identify persons adversely impacted by inflammation and replicate it in a second cohort. Secondary analyses of data collected by the Texas Alzheimer's Research and Care Consortium (TARCC) (N = 3497) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1737). Two large, well-characterized multi-center convenience samples. Volunteers with normal cognition (NC), Mild Cognitive Impairment (MCI) or clinical "Alzheimer's Disease (AD)". Participants were assigned to "Afflicted" or "Resilient" classes on the basis of a psychometric classifier derived by confirmatory factor analysis. The groups were contrasted on multiple assessments and biomarkers. The groups were also contrasted regarding 4-year prospective conversions to "AD" from non-demented baseline diagnoses (controls and MCI). The Afflicted groups were predicted to have adverse levels of inflammation-related blood-based biomarkers, greater dementia severity and greater risk of prospective conversion. In ADNI /plasma, 47.1% of subjects were assigned to the Afflicted class. 44.6% of TARCC's subjects were afflicted, 49.5% of non-Hispanic Whites (NHW) and 37.2% of Mexican Americans (MA). There was greater dementia severity in the Afflicted class [by ANOVA: ADNI /F(1) = 686.99, p <0.001; TARCC /F(1) = 1544.01, p <0.001]. "INFLAMMATION" factor composite scores were significantly higher (adverse) in Afflicted subjects [by ANOVA in ADNI /plasma F(1) = 1642.64, p <0.001 and in TARCC /serum F(1) = 3059.96, p <0.001]. Afflicted cases were more likely to convert to AD in the next four years [by Cox's F, ADNI /plasma: F (252, 268) = 3.74 p < 0.001; TARCC /serum: F (160, 134) = 3.03, p < 0.001 (in TARCC's entire sample), F (110, 90) = 4.92, p <0.001 in NHW, and F(50, 44) = 2.13, p = 0.006 in MA]. The proportions converting were similar among afflicted NHW in both cohorts /biofluids but MA exhibited a lower risk (7% in TARCC /serum at 48 months). Our inflammation-specific psychometric classifier selects individuals with pre-specified biomarker profiles and predicts conversion to "AD" across cohorts, biofluids, and ethnicities. This algorithm might be applied to any dementia-related biomarker making the psychometric estimation of individual biomarker effects feasible without biomarker assessment. Our approach also distinguishes individuals resilient to individual biomarker effects allowing for more accurate prediction and precision intervention.

The role of peripheral inflammation-related biomarkers in distinguishing Parkinson's disease

BackgroundPeripheral inflammation plays a significant role in Parkinson's disease (PD). Conflicting studies on whether inflammatory indicators in blood could serve as biomarkers to distinguish PD. ObjectiveInclude a wider range of biomarkers and control confounding factors to comprehensively evaluate the value of peripheral inflammation-related indicators. MethodsA total of 80 PD patients were recruited and 80 one-to-one matched healthy controls (HCs). The levels of B-cell, T-cell, and natural killer (NK)-cell in blood were measured using flow cytometry. The levels of neurodegeneration-related proteins in serum were detected and clinical blood test results were collected. Multivariable logistic regression analysis was conducted to explore the role of significant variables in PD. Receiver operating characteristic curve analysis was performed to assess the potential value of these variables. ResultsCompared to HCs, PD patients showed lower levels of lymphocyte, B-cell, T-cell, high-density lipoprotein cholesterol (HDL-C) and lymphocyte-to-monocyte ratio, while the levels of neutrophil, NK-cell, β-amyloid40, neurofilament light chain, neutrophil-to-lymphocyte ratio, and neutrophil-to-HDL-C ratio (NHR) were increased. A higher B-cell count was associated with a lower risk of PD, while higher levels of NK-cell and NHR were associated with a higher risk of PD. B-cell, NK-cell and NHR have potential value in distinguishing PD from non-PD. B-cell and NHR levels were significantly correlated with PD dyskinesia scores. ConclusionsB-cell, NK-cell, and NHR may potentially contribute to distinguishing PD patients from HCs. There could be a correlation between the number of B-cell, the level of NHR, and the severity of PD dyskinesia.

Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients.

Gastric cancer (GC) is a highly aggressive malignancy with a heterogeneous nature, which makes prognosis prediction and treatment determination difficult. Inflammation is now recognized as one of the hallmarks of cancer and plays an important role in the aetiology and continued growth of tumours. Inflammation also affects the prognosis of GC patients. Recent reports suggest that a number of inflammatory-related biomarkers are useful for predicting tumour prognosis. However, the importance of inflammatory-related biomarkers in predicting the prognosis of GC patients is still unclear. To investigate inflammatory-related biomarkers in predicting the prognosis of GC patients. In this study, the mRNA expression profiles and corresponding clinical information of GC patients were obtained from the Gene Expression Omnibus (GEO) database (GSE66229). An inflammatory-related gene prognostic signature model was constructed using the least absolute shrinkage and selection operator Cox regression model based on the GEO database. GC patients from the GSE26253 cohort were used for validation. Univariate and multivariate Cox analyses were used to determine the independent prognostic factors, and a prognostic nomogram was established. The calibration curve and the area under the curve based on receiver operating characteristic analysis were utilized to evaluate the predictive value of the nomogram. The decision curve analysis results were plotted to quantify and assess the clinical value of the nomogram. Gene set enrichment analysis was performed to explore the potential regulatory pathways involved. The relationship between tumour immune infiltration status and risk score was analysed via Tumour Immune Estimation Resource and CIBERSORT. Finally, we analysed the association between risk score and patient sensitivity to commonly used chemotherapy and targeted therapy agents. A prognostic model consisting of three inflammatory-related genes (MRPS17, GUF1, and PDK4) was constructed. Independent prognostic analysis revealed that the risk score was a separate prognostic factor in GC patients. According to the risk score, GC patients were stratified into high- and low-risk groups, and patients in the high-risk group had significantly worse prognoses according to age, sex, TNM stage and Lauren type. Consensus clustering identified three subtypes of inflammation that could predict GC prognosis more accurately than traditional grading and staging. Finally, the study revealed that patients in the low-risk group were more sensitive to certain drugs than were those in the high-risk group, indicating a link between inflammation-related genes and drug sensitivity. In conclusion, we established a novel three-gene prognostic signature that may be useful for predicting the prognosis and personalizing treatment decisions of GC patients.

Prognostic value of inflammation-related biomarkers in patients with gastroenteropancreatic neuroendocrine neoplasms: A systematic review and meta-analysis.

Hematological indicators of chronic systemic inflammation are significant biomarkers for gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). We performed a systematic review and meta-analysis to assess the impact of certain factors on the overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of patients with GEP-NENs. These factors include the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), and C-reactive protein (CRP) levels. After searching the Medline, Embase, and Cochrane Library databases from January 1, 2000 to October 20, 2022 and the American Society of Clinical Oncology conference proceedings from January 1, 2017, hazard ratios (HRs) and 95% confidence intervals (CIs) were extracted. Subgroup analyses were conducted to identify the origins of heterogeneity and examine the impact of factor grouping. The effects of the cut-off values and sample size were assessed by meta-regression. The results revealed that higher NLRs, PLRs, and CRP levels were associated with shorter OS (HR = 2.09, 95% CI = 1.55-2.8; HR = 1.79, 95% CI = 1.40-2.28; and HR = 2.88, 95% CI = 2.09-3.95, respectively; all p < 0.001). Higher NLRs and lower LMRs were associated with shorter DFS (HR = 3.34, 95% CI = 2.11-5.29 and HR = 2.71, 95% CI = 2.27-3.24, respectively; both p < 0.001). Higher PLRs and CRP levels were correlated with shorter PFS (HR = 3.48, 95% CI = 1.34-9.03, p = 0.01 and HR = 3.14, 95% CI = 1.63-6.08, p = 0.001). As demonstrated in the research, hematological indicators of systemic inflammation are promising biomarkers for GEP-NEN assessment.

Serum and salivary inflammatory biomarkers in juvenile idiopathic arthritis—an explorative cross-sectional study

BackgroundBiomarkers may be useful in monitoring disease activity in juvenile idiopathic arthritis (JIA). With new treatment options and treatment goals in JIA, there is an urgent need for more sensitive and responsive biomarkers.ObjectiveWe aimed to investigate the patterns of 92 inflammation-related biomarkers in serum and saliva in a group of Norwegian children and adolescents with JIA and controls and in active and inactive JIA. In addition, we explored whether treatment with tumor necrosis factor inhibitors (TNFi) affected the biomarker levels.MethodsThis explorative, cross-sectional study comprised a subset of children and adolescents with non-systemic JIA and matched controls from the Norwegian juvenile idiopathic arthritis study (NorJIA Study). The JIA group included individuals with clinically active or inactive JIA. Serum and unstimulated saliva were analyzed using a multiplex assay of 92 inflammation-related biomarkers. Welch’s t-test and Mann–Whitney U-test were used to analyze the differences in biomarker levels between JIA and controls and between active and inactive disease.ResultsWe included 42 participants with JIA and 30 controls, predominantly females, with a median age of 14 years. Of the 92 biomarkers, 87 were detected in serum, 73 in saliva, and 71 in both biofluids. A pronounced difference between serum and salivary biomarker patterns was found. Most biomarkers had higher levels in serum and lower levels in saliva in JIA versus controls, and in active versus inactive disease. In serum, TNF and S100A12 levels were notably higher in JIA and active disease. The TNF increase was less pronounced when excluding TNFi-treated individuals. In saliva, several biomarkers from the chemokine family were distinctly lower in the JIA group, and levels were even lower in active disease.ConclusionIn this explorative study, the serum and salivary biomarker patterns differed markedly, suggesting that saliva may not be a suitable substitute for serum when assessing systemic inflammation in JIA. Increased TNF levels in serum may not be a reliable biomarker for inflammatory activity in TNFi-treated children and adolescents with JIA. The lower levels of chemokines in saliva in JIA compared to controls and in active compared to inactive disease, warrant further investigation.

The Role of Hepcidin, sTfR, and sTfR/Log Ferritin Index for the Differential Diagnosis of Iron Deficiency Anemia and Anemia of Chronic Disease

Background: In chronic diseases characterized by persistent inflammation, anemia of chronic disease (ACD) and iron deficiency anemia (IDA) are commonly encountered forms of anemia and can often co-occur. In such situations, the conventional iron status tests used for differential diagnosis are influenced by inflammation, reducing their diagnostic accuracy. The primary objective of this study was to assess the significance of hepcidin as a crucial diagnostic marker for ACD and to investigate the correlation between hepcidin and inflammation-related indicators. Furthermore, a significant secondary aim of this research was to ascertain the diagnostic role of novel biochemical markers, specifically soluble transferrin receptor (sTfR) and the derived sTfR/log ferritin index (sTfR-F index). Methods and Results: This study was conducted at the Laboratory Service of the University Hospital Center "Mother Teresa" and included a cohort of 187 subjects, comprising 156 patients (83 females and 73 males) who were admitted to and received treatment at the Rheumatology and Cardiology Departments of the "Mother Teresa" University Hospital Center in Tirana. Additionally, 31 individuals without anemia and inflammatory conditions were included as a control group. All subjects incorporated into the study were classified into five distinct groups based on a comprehensive analysis of their complete blood profiles, iron status, and inflammation-related biomarkers: IDA, ACD, ACD+IDA, RA/CHF patients without anemia, and the control group without anemia. The comparison between groups showed that the mean values of pro-hepcidin, TNFα, IL6, Hs-PCR, and ferritin are significantly decreased in IDA vs. ACD, while sTFR and sTfR-F index are significantly increased. In comparing ACD vs. ACD+IDA groups, ferritin increased significantly in the ACD group, while sTFR and sTfR-F index decreased significantly in ACD, compared to the ACD+IDA group. The ROC curves analysis of the biochemical parameters selected for the comparison of ACD vs IDA showed that the pro-hepcidin test is a perfect test for the differential diagnosis of ACD vs. IDA. The suggested cut-off value for pro-hepcidin was ≥153 ng/ml, yielding a sensitivity of 100% and a specificity of 100% for the diagnosis of ACD. As regards sTFR, the suggested cut-off value for the diagnosis of IDA vs. ACD was≥ 4.9 µg/ml resulting in 84% sensitivity and 100% specificity. The sTfR-F index was also very useful for the diagnosis of IDA vs. ACD: for a cut-off value of ≥2.06, the sensitivity was 90% and the specificity was 96%. sTfR resulted in a good test for the diagnosis of ACD+IDA vs. ACD: the cut-off value was ≥ 3.7µ/ml, the sensitivity was 92.3% and the specificity was 93.2%. Similarly, the parameter sTfR-F index resulted in a very good test for the diagnosis of ACD+IDA vs. ACD: for the suggested cut-off value of ≥2.3, the sensitivity was 92.3% and the specificity was 100%. Conclusion: As a result of the study, it was found that the pro-hepcidin test was a highly accurate test for distinguishing between ACD and IDA. Meanwhile, sTfR and the sTfR-F index proved to be excellent indicators for the differential diagnosis of IDA in chronic inflammatory conditions.

Identification of inflammation-related biomarkers in keloids.

The relationship between inflammation-related genes (IRGs) and keloid disease (KD) is currently unclear. The aim of this study was to identify a new set of inflammation-related biomarkers in KD. GSE145725 and GSE7890 datasets were used in this study. A list of 3026 IRGs was obtained from the Molecular Signatures Database. Differentially expressed inflammation-related genes (DEGs) were obtained by taking the intersection of DEGs between KD and control samples and the list of IRGs. Candidate genes were selected using least absolute shrinkage and selection operator (LASSO) regression analysis. Candidate genes with consistent expression differences between KD and control in both GSE145725 and GSE7890 datasets were screened as biomarkers. An alignment diagram was constructed and validated, and in silico immune infiltration analysis and drug prediction were performed. Finally, RT-qPCR was performed on KD samples to analyze the expression of the identified biomarkers. A total of 889 DEGs were identified from the GSE145725 dataset, 169 of which were IRGs. Three candidate genes (TRIM32, LPAR1 and FOXF1) were identified by the LASSO regression analysis, and expression validation analysis suggested that FOXF1 and LPAR1 were down-regulated in KD samples and TRIM32 was up-regulated. All three candidate genes had consistent changes in expression in both the GSE145725 and GSE7890 datasets. An alignment diagram was constructed to predict KD. Effector memory CD4 T cells, T follicular helper cell, Myeloid derived suppressor cell, activated dendritic cell, Immature dendritic cell and Monocyte were differentially expressed between the KD and control group. Sixty-seven compounds that may act on FOXF1, 108 compounds that may act on LPAR1 and 56 compounds that may act on TRIM32 were predicted. Finally, RT-qPCR showed that the expression of LPAR1 was significantly lower in KD samples compared to normal samples whereas TRIM32 was significantly higher, while there was no difference in the expression of FOXF1. This study provides a new perspective to study the relationship between IRGs and KD.

Adiponectin, Interleukin-18 (IL-18), and Visceral Adipose Tissue in Filipino Americans: Biomarkers and Risk of Type 2 Diabetes.

Filipino Americans (FAs) are at high risk for developing type 2 diabetes despite other Asian phenotypes. Evidence suggests that pro-inflammatory interleukin-18 (IL-18) and anti-inflammatory adiponectin biomarkers associated with visceral adipose tissue (VAT) may explain this risk. This study aimed to quantify the biomarkers in relation to standard ranges of VAT or typical circulating concentration ranges reported in the literature of IL-18 and adiponectin, examine relationships of these markers, and determine if they were different among those participants without diabetes, prediabetes, and diabetes. A cross-sectional study was used to enroll FAs without diabetes, prediabetes, or diabetes. VAT was measured using the InBody 570© Body Composition Analyzer. Blood samples were obtained to assess plasma concentrations of IL-18 and adiponectin using enzyme-linked immunosorbent assay. All analyses were conducted using a 5% type I error rate. Mean ±SD and percentages were used to describe the sample and data where appropriate. Pearson's correlations (R) were calculated to determine the relationships between VAT and IL-18 in each group. Analysis of variance was used to determine differences in VAT, IL-18, and adiponectin among groups. Further, nonparametric procedures examined the differences in adiponectin among those within groups. Seventy-five participants were enrolled. Biomarkers above the typical concentration range were observed for VAT, IL-18, and adiponectin. Adiponectin significantly differed among groups with lower values in the diabetes group vs. the nondiabetes group. The findings indicate that while inflammation-related biomarkers, such as adiponectin, correlate with VAT and may serve as indicators of increased risk of type 2 diabetes in FAs, correlation alone does not establish causality.

Validation of new immune and inflammation-related diagnostic biomarkers for RA.

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease, whose development is associated with immune cells and persistent inflammation. Exploring the biomarkers of RA holds immense significance in terms of the prevention, diagnosis, and treatment of RA. The differentially expressed genes (DEGs) in RA patients and the control group were screened by limma package. Through DEGs intersection overlapping 200 inflammatory response-related genes and 2498 immune-related genes, differentially expressed immune and inflammation-related genes (DE-IIRGs) were identified. Lasso regression analysis screened RA diagnostic biomarkers and constructed PPI networks. Finally, immune infiltration analysis and drug prediction were performed. A total of 20 DE-IIRGs were identified by overlapping DEGs with 2498 immune-related genes and 200 inflammatory response-related genes. These DE-IIRGs were primarily enriched in the cytokine-cytokine receptor interaction and other biological processes, and then five biomarker genes (TNFSF10, IL1R1, CXCL9, ACVR1B, and IL15) were identified. It was found that the expression levels of CXCL9, IL15, and TNFSF10 in the disease samples were significantly higher than those in the control group. These biomarker genes have more effective diagnostic potential. The RA samples exhibited significantly higher levels of cell infiltration compared to the control samples. hsa-miR-199a-5p's connections to the ACVR1B and CCR7 genes were identified by creating ceRNA networks from 20 screened DE-IIRGs. There was a connection between CCL5 and AEMA4D and hsa-miR-214-3p. We identified immune- and inflammation-related biomarkers in RA based on bioinformatics analysis and screened TNFSF10, IL1R1, CXCL9, ACVR1B, and IL15 as diagnostic markers for RA. Key Points • TNFSF10, IL1R1, CXCL9, ACVR1B, and IL15 may be new diagnostic biomarkers for RA. • These findings may provide a theoretical basis for early RA diagnosis.

Potential roles of IL-38, among other inflammation-related biomarkers, in predicting post-percutaneous coronary intervention cardiovascular events.

Percutaneous coronary intervention (PCI), as a relatively rapid and effective minimally invasive treatment for coronary heart disease (CHD), can effectively relieve coronary artery stenosis and restore myocardial perfusion. However, the occurrence of major adverse cardiovascular events (MACE) is a significant challenge for post PCI care. To better understand risk/benefit indicators and provide post PCI MACE prediction, 408 patients with CHD who had undergone PCI treatment from 2018 to 2021 in Tianjin Chest hospital were retrospectively studied for their clinical characteristics in relation with the MACE occurrence during a 12-month follow-up. In the study, 194 patients had MACE and 214 patients remained MACE-free. Using uni- and multivariate regression analyses, we have shown that smoking history, elevated serum C-reactive protein levels (hs-CRP), and high haemoglobin levels A1c (HbA1c) are all independent risk factors for MACE after PCI. Furthermore, we have discovered that the serum level of IL-38, one of the latest members identified in the IL-1 cytokine family, is another predictive factor and is reversely related to the occurrence of MACE. The serum level of IL-38 alone is capable of predicting non-MACE occurrence in subcategorized patients with abnormal levels of hs-CRP and/or HbA1c.