Mast Cells in Inflammation and Disease: Recent Progress and Ongoing Concerns.

Mast cells have existed long before the development of adaptive immunity, although they have been given different names. Thus, in the marine urochordate Styela plicata, they have been designated as test cells. However, based on their morphological characteristics (including prominent cytoplasmic granules) and mediator content (including heparin, histamine, and neutral proteases), test cells are thought to represent members of the lineage known in vertebrates as mast cells. So this lineage presumably had important functions that preceded the development of antibodies, including IgE. Yet mast cells are best known, in humans, as key sources of mediators responsible for acute allergic reactions, notably including anaphylaxis, a severe and potentially fatal IgE-dependent immediate hypersensitivity reaction to apparently harmless antigens, including many found in foods and medicines. In this review, we briefly describe the origins of tissue mast cells and outline evidence that these cells can have beneficial as well as detrimental functions, both innately and as participants in adaptive immune responses. We also discuss aspects of mast cell heterogeneity and comment on how the plasticity of this lineage may provide insight into its roles in health and disease. Finally, we consider some currently open questions that are yet unresolved.

Autophagy and Inflammation.

The cellular degradative pathway of autophagy has a fundamental role in immunity. Here, we review the function of autophagy and autophagy proteins in inflammation. We discuss how the autophagy machinery controls the burden of infectious agents while simultaneously limiting inflammatory pathologies, which often involves processes that are distinct from conventional autophagy. Among the newly emerging processes we describe are LC3-associated phagocytosis and targeting by autophagy proteins, both of which require many of the same proteins that mediate conventional autophagy. We also discuss how autophagy contributes to differentiation of myeloid and lymphoid cell types, coordinates multicellular immunity, and facilitates memory responses. Together, these functions establish an intimate link between autophagy, mucosal immunity, and chronic inflammatory diseases. Finally, we offer our perspective on current challenges and barriers to translation.

Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics.

Transcriptomics, the high-throughput characterization of RNAs, has been instrumental in defining pathogenic signatures in human autoimmunity and autoinflammation. It enabled the identification of new therapeutic targets in IFN-, IL-1- and IL-17-mediated diseases. Applied to immunomonitoring, transcriptomics is starting to unravel diagnostic and prognostic signatures that stratify patients, track molecular changes associated with disease activity, define personalized treatment strategies, and generally inform clinical practice. Herein, we review the use of transcriptomics to define mechanistic, diagnostic, and predictive signatures in human autoimmunity and autoinflammation. We discuss some of the analytical approaches applied to extract biological knowledge from high-dimensional data sets. Finally, we touch upon emerging applications of transcriptomics to study eQTLs, B and T cell repertoire diversity, and isoform usage.

Neuroinflammation after surgery: from mechanisms to therapeutic targets.

Injury is a key driver of inflammation, a critical yet necessary response involving several mediators that is aimed at restoring tissue homeostasis. Inflammation in the central nervous system can be triggered by a variety of stimuli, some intrinsic to the brain and others arising from peripheral signals. Fine-tuned regulation of this response is crucial in a system that is vulnerable due to, for example, aging and ongoing neurodegeneration. In this context, seemingly harmless interventions like a common surgery to repair a broken limb can overwhelm the immune system and become the driver of further complications such as delirium and other perioperative neurocognitive disorders. Here, we discuss potential mechanisms by which the immune system affects the central nervous system after surgical trauma. Together, these neuroimmune interactions are becoming hallmarks of and potential therapeutic targets for multiple neurologic conditions, including those affecting the perioperative space.

Sub-1.4 cm3 capsule for detecting labile inflammatory biomarkers in situ.

Transient molecules in the gastrointestinal tract such as nitric oxide and hydrogen sulfide are key signals and mediators of inflammation. Owing to their highly reactive nature and extremely short lifetime in the body, these molecules are difficult to detect. Here we develop a miniaturized device that integrates genetically engineered probiotic biosensors with a custom-designed photodetector and readout chip to track these molecules in the gastrointestinal tract. Leveraging the molecular specificity of living sensors1, we genetically encoded bacteria to respond to inflammation-associated molecules by producing luminescence. Low-power electronic readout circuits2 integrated into the device convert the light emitted by the encapsulated bacteria to a wireless signal. We demonstrate in vivo biosensor monitoring in the gastrointestinal tract of small and large animal models and the integration of all components into a sub-1.4 cm3 form factor that is compatible with ingestion and capable of supporting wireless communication. With this device, diseases such as inflammatory bowel disease could be diagnosed earlier than is currently possible, and disease progression could be more accurately tracked. The wireless detection of short-lived, disease-associated molecules with our device could also support timely communication between patients and caregivers, as well as remote personalized care.

Systems Medicine in Chronic Inflammatory Diseases.

Chronic inflammatory diseases represent an increasing medical burden, yet neither tools to predict the individual disease course nor causal cures are at hand. We discuss opportunities for systems medicine to derive precise, individualized disease models and outline the European consortium SYSCID as part of the roadmap to clinical practice.

Fluorescent Probes for Disease Diagnosis.

The identification and detection of disease-related biomarkers is essential for early clinical diagnosis, evaluating disease progression, and for the development of therapeutics. Possessing the advantages of high sensitivity and selectivity, fluorescent probes have become effective tools for monitoring disease-related active molecules at the cellular level and in vivo. In this review, we describe current fluorescent probes designed for the detection and quantification of key bioactive molecules associated with common diseases, such as organ damage, inflammation, cancers, cardiovascular diseases, and brain disorders. We emphasize the strategies behind the design of fluorescent probes capable of disease biomarker detection and diagnosis and cover some aspects of combined diagnostic/therapeutic strategies based on regulating disease-related molecules. This review concludes with a discussion of the challenges and outlook for fluorescent probes, highlighting future avenues of research that should enable these probes to achieve accurate detection and identification of disease-related biomarkers for biomedical research and clinical applications.

Microbes as Biosensors.

The ability to detect disease early and deliver precision therapy would be transformative for the treatment of human illnesses. To achieve these goals, biosensors that can pinpoint when and where diseases emerge are needed. Rapid advances in synthetic biology are enabling us to exploit the information-processing abilities of living cells to diagnose disease and then treat it in a controlled fashion. For example, living sensors could be designed to precisely sense disease biomarkers, such as by-products of inflammation, and to respond by delivering targeted therapeutics in situ. Here, we provide an overview of ongoing efforts in microbial biosensor design, highlight translational opportunities, and discuss challenges for enabling sense-and-respond precision medicines.

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.

The Value of Systemic Immune-Inflammation Index and T Cell Subsets in the Severity and Prognosis of Sepsis.

Systemic immune-inflammation index (SII) and T cell subsets show involvement in mortality risk in septic patients, and we explored their predictive value in sepsis. Subjects were categorized into the Sepsis (SP)/Septic Shock (SSP)/Septic Shock (SPS) groups. T cell subsets [T-helper (Th)1, Th2, regulatory T cells (Treg), Th17]/platelets (PLT)/neutrophils (NEU)/lymphocytes (LYM)/C-reactive protein (CRP)/procalcitonin (PCT)/interleukin (IL)-4/IL-10/fibrinogen (FIB) were measured by an automatic blood biochemical analyzer/flow cytometry/Countess II FL automatic blood cell analyzer, with SII calculated. The correlations between SII/T cell subsets with Acute Physiology and Chronic Health Evaluation (APACH) II/Sequential Organ Failure Assessment (SOFA) scores and the predictive value of SII/Th1/Th2 for septic diagnosis/prognosis were analyzed using Spearman/ROC curve/Kaplan-Meier. The three groups varied in PLT/NEU/LYM/CRP/PCT/IL-4/IL-10/FIB levels and APACH II/SOFA scores. Compared with the SP group, the other two groups showed elevated APACH II/SOFA scores and SII/Th1/Th2/Th17/Treg levels. SII/Th1/Th2 levels significantly positively correlated with APACH II/SOFA scores. SII/Th1/Th2 levels had high predictive value for septic diagnosis/prognosis, with their combination exhibiting higher predictive value. Septic patients with high SII/Th1/Th2 levels exhibited lower survival rates. Altogether, SII, Th1, and Th2 had good predictive value for the diagnosis and prognosis of patients with varying severity of sepsis, with their high levels increasing mortality in septic patients.

Airway hyperresponsiveness correlates with airway TSLP in asthma independent of eosinophilic inflammation.

BACKGROUND: Thymic stromal lymphopoietin (TSLP) is released from the airway epithelium in response to various environmental triggers, inducing a type-2 inflammatory response, and is associated with airway inflammation, airway hyperresponsiveness (AHR), and exacerbations. TSLP may also induce AHR via a direct effect on airway smooth muscle and mast cells, independently of type-2 inflammation, although association between airway TSLP and AHR across asthma phenotypes has been described sparsely. OBJECTIVES: This study sought to investigate the association between AHR and levels of TSLP in serum, sputum, and bronchoalveolar lavage in patients with asthma with and without type-2 inflammation. METHODS: A novel ultrasensitive assay was used to measure levels of TSLP in patients with asthma (serum, n = 182; sputum, n = 81; bronchoalveolar lavage, n = 85) and healthy controls (serum, n = 47). The distribution and association among airway and systemic TSLP, measures of AHR, type-2 inflammation, and severity of disease were assessed. RESULTS: TSLP in sputum was associated with AHR independently of levels of eosinophils and fractional exhaled nitric oxide (ρ = 0.49, P = .005). Serum TSLP was higher in both eosinophil-high and eosinophil-low asthma compared to healthy controls: geometric mean: 1600 fg/mL (95% CI: 1468-1744 fg/mL) and 1294 fg/mL (95% CI: 1167-1435 fg/mL) versus 846 fg/mL (95% CI: 661-1082 fg/mL), but did not correlate with the level of AHR. Increasing age, male sex, and eosinophils in blood were associated with higher levels of TSLP in serum, whereas lung function, inhaled corticosteroid dose, and symptom score were not. CONCLUSIONS: The association between TSLP in sputum and AHR to mannitol irrespective of markers of type-2 inflammation further supports a role of TSLP in AHR that is partially independent of eosinophilic inflammation.

Electrochemical Lateral Flow Immunoassay with Built-In Electrodes for Ultrasensitive and Wireless Detection of Inflammatory Biomarkers.

Paper-based lateral flow immunoassays (LFIAs) are cost-effective, portable, and simple methods for detection of diverse analytes, which however only provide qualitative or semiquantitative results and lack sufficient sensitivity. A combination of LFIA and electrochemical detection, namely, electrochemical lateral flow immunoassay (eLFIA), enables quantitative detection of analytes with high sensitivity, but the integration of external electrodes makes the system relatively expensive and unstable. Herein, the working, counter, and reference electrodes were prepared directly on the nitrocellulose membrane using screen printing, which remarkably simplified the structure of eLFIA and decreased the cost. Moreover, a horseradish peroxidase (HRP)-based electrochemical signal amplification strategy was used for further increasing the analytical sensitivity. HRP captured on the working electrode can catalyze the oxidation of tetramethylbenzidine (TMB) to form the TMB-TMBox precipitate on the electrode surface, which as an electrochemically active product can output an amplified current for quantification. We demonstrated that the eLFIA could detect low-abundant inflammatory biomarkers in human plasma samples with limits of detection of 0.17 and 0.54 pg mL-1 for interleukin-6 and C-reactive protein, respectively. Finally, a fully portable system was fabricated by integrating eLFIA with a flexible and wireless electrochemical workstation, realizing the point-of-care detection of interleukin-6.

The role of body mass index on the association between the energy-adjusted dietary inflammatory index and hyperuricemia: a mediation analysis based on NHANES (2007-2016).

BACKGROUND: The Energy-Adjusted Dietary Inflammatory Index (E-DII) is related to both body mass index (BMI) and hyperuricemia. However, the association among BMI, hyperuricemia and DII is yet to be fully elucidated. The purpose of this study is to explore the role of BMI in the relationship between E-DII and hyperuricemia in the American population. METHODS: A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2007 to 2016, with a sample size of 10,571 participants. The study used a weighted logistic regression model and a generalized additive model (GAM) to explore the associations among BMI, hyperuricemia and E-DII. Furthermore, mediation analysis was utilized to illustrate the mediating relationships among these variables. RESULTS: The results of the study indicated that a higher E-DII was related to an increased risk of hyperuricemia. The association between E-DII and hyperuricemia was partially mediated by BMI. CONCLUSIONS: E-DII is associated with hyperuricemia. BMI mediates the relationship between E-DII and hyperuricemia among Americans, which provides crucial information for the prevention of hyperuricemia.

SuPAR, biomarkers of inflammation, and severe outcomes in patients hospitalized for COVID-19: The International Study of Inflammation in COVID-19.

Severe coronavirus disease 2019 (COVID-19) is a hyperinflammatory syndrome. The biomarkers of inflammation best suited to triage patients with COVID-19 are unknown. We conducted a prospective multicenter observational study of adult patients hospitalized specifically for COVID-19 from February 1, 2020 to October 19, 2022. Biomarkers measured included soluble urokinase plasminogen activator receptor (suPAR), C-reactive protein, interleukin-6, procalcitonin, ferritin, and D-dimer. In-hospital outcomes examined include death and the need for mechanical ventilation. Patients admitted in the United States (US, n = 1962) were used to compute area under the curves (AUCs) and identify biomarker cutoffs. The combined European cohorts (n = 1137) were used to validate the biomarker cutoffs. In the US cohort, 356 patients met the composite outcome of death (n = 197) or need for mechanical ventilation (n = 290). SuPAR was the most important predictor of the composite outcome and had the highest AUC (0.712) followed by CRP (0.642), ferritin (0.619), IL-6 (0.614), D-dimer (0.606), and lastly procalcitonin (0.596). Inclusion of other biomarkers did not improve discrimination. A suPAR cutoff of 4.0 ng/mL demonstrated a sensitivity of 95.4% (95% CI: 92.4%-98.0%) and negative predictive value (NPV) of 92.5% (95% CI: 87.5%-96.9%) for the composite outcome. Patients with suPAR < 4.0 ng/mL comprised 10.6% of the cohort and had a 0.8% probability of the composite outcome. Applying this cutoff to the validation cohort yielded a sensitivity of 93.8% (90.4%-96.7%) and NPV of 95.5% (93.1%-97.8%) for the composite outcome. Among commonly measured biomarkers, suPAR offered stronger discriminatory ability and may be useful in triaging low-risk patients with COVID-19.

Myocardial injury and inflammation following pulsed-field ablation and very high-power short-duration ablation for atrial fibrillation.

INTRODUCTION: Pulmonary vein isolation (PVI) using radiofrequency ablation (RFA) is an established treatment strategy for atrial fibrillation (AF). To improve PVI efficacy and safety, high-power short-duration (HPSD) ablation and pulsed-field ablation (PFA) were recently introduced into clinical practice. This study aimed to determine the extent of myocardial injury and systemic inflammation following PFA, HPSD, and standard RFA using established biomarkers. METHODS: We included 179 patients with paroxysmal AF receiving first-time PVI with different ablation technologies: standard RFA (30-40 W/20-30 s, n = 52), power-controlled HPSD (70 W/5-7 s, n = 60), temperature-controlled HPSD (90 W/4 s, n = 32), and PFA (biphasic, bipolar waveform, n = 35). High-sensitivity cardiac troponin T (hs-cTnT), creatine kinase (CK), CK MB isoform (CK-MB), and white blood cell (WBC) count were determined before and after ablation. RESULTS: Baseline characteristics were well-balanced between groups (age 63.1 ± 10.3 years, 61.5% male). Postablation hs-cTnT release was significantly higher with PFA (1469.3 ± 495.0 ng/L), HPSD-70W (1322.3 ± 510.6 ng/L), and HPSD-90W (1441.2 ± 409.9 ng/L) than with standard RFA (1045.9 ± 369.7 ng/L; p < .001). CK and CK-MB release was increased with PFA by 3.4-fold and 5.8-fold, respectively, as compared to standard RFA (p < .001). PFA was associated with the lowest elevation in WBC (Δ1.5 ± 1.5 × 109 /L), as compared to standard RFA (Δ3.8 ± 2.5 × 109 /L, p < .001), HPSD-70W (Δ2.7 ± 1.7 × 109 /L, p = .037), and HPSD-90W (Δ3.6 ± 2.5 × 109 /L, p < .001). CONCLUSION: Among the four investigated ablation technologies, PFA was associated with the highest myocardial injury and the lowest inflammatory reaction.

Prognostic implications of systemic immune-inflammation index in myocardial infarction patients with and without diabetes: insights from the NOAFCAMI-SH registry.

BACKGROUND: It is well-known that systemic inflammation plays a crucial role in the pathogenesis and prognosis of acute myocardial infarction (AMI). The systemic immune-inflammation index (SII, platelet × neutrophil/lymphocyte ratio) is a novel index that is used for the characterization of the severity of systemic inflammation. Recent studies have identified the high SII level as an independent predictor of poor outcomes in patients with AMI. We aimed to investigate the prognostic implications of SII in AMI patients with and without diabetes mellitus (DM). METHODS: We included 2111 patients with AMI from February 2014 to March 2018. Multivariable Cox regression analyses were performed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause death and cardiovascular (CV) death. Multiple imputation was used for missing covariates. RESULTS: Of 2111 patients (mean age: 65.2 ± 12.2 years, 77.5% were males) analyzed, 789 (37.4%) had DM. Generalized additive model analyses showed that as the SII increased, the C-reactive protein and peak TnT elevated while the LVEF declined, and these associations were similar in patients with and without DM. During a median of 2.5 years of follow-up, 210 all-cause deaths and 154 CV deaths occurred. When treating the SII as a continuous variable, a higher log-transformed SII was significantly associated with increased all-cause mortality (HR: 1.57, 95%CI: 1.02-2.43) and CV mortality (HR: 1.85, 95%CI 1.12-3.05), and such an association was also significant in the diabetics (HRs and 95%CIs for all-cause death and CV death were 2.90 [1.40-6.01] and 3.28 [1.43-7.57], respectively) while not significant in the nondiabetics (Pinteraction for all-cause death and CV death were 0.019 and 0.049, respectively). Additionally, compared to patients with the lowest tertiles of SII, those with the highest tertiles of SII possessed significantly higher all-cause mortality (HR: 1.82, 95%CI 1.19-2.79) and CV mortality (HR: 1.82, 95%CI 1.19-2.79) after multivariable adjustment, and this relationship remained pronounced in the diabetics (HRs and 95%CIs for all-cause death and CV death were 2.00 [1.13-3.55] and 2.09 [1.10-3.98], respectively) but was not observed in the nondiabetics (HRs and 95%CIs for all-cause death and CV death were 1.21 [0.75-1.97] and 1.60 [0.89-2.90], respectively). Our restricted cubic splines analyses indicated a pronounced linear association between SII and mortality only in diabetics. CONCLUSIONS: In AMI patients with DM, high SII is an independent predictor of poor survival and may be helpful for patient's risk stratification.

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.

Is systemic inflammation a missing link between cardiometabolic index with mortality? Evidence from a large population-based study.

BACKGROUND: This study sought to elucidate the associations of cardiometabolic index (CMI), as a metabolism-related index, with all-cause and cardiovascular mortality among the older population. Utilizing data from the National Health and Nutrition Examination Survey (NHANES), we further explored the potential mediating effect of inflammation within these associations. METHODS: A cohort of 3029 participants aged over 65 years old, spanning six NHANES cycles from 2005 to 2016, was enrolled and assessed. The primary endpoints of the study included all-cause mortality and cardiovascular mortality utilizing data from National Center for Health Statistics (NCHS). Cox regression model and subgroup analysis were conducted to assess the associations of CMI with all-cause and cardiovascular mortality. The mediating effect of inflammation-related indicators including leukocyte, neutrophil, lymphocyte, systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR) were evaluated to investigate the potential mechanism of the associations between CMI and mortality through mediation package in R 4.2.2. RESULTS: The mean CMI among the enrolled participants was 0.74±0.66, with an average age of 73.28±5.50 years. After an average follow-up period of 89.20 months, there were 1,015 instances of all-cause deaths and 348 cardiovascular deaths documented. In the multivariable-adjusted model, CMI was positively related to all-cause mortality (Hazard Ratio (HR)=1.11, 95% CI=1.01-1.21). Mediation analysis indicated that leukocytes and neutrophils mediated 6.6% and 13.9% of the association of CMI with all-cause mortality. CONCLUSION: Elevated CMI is positively associated with all-cause mortality in the older adults. The association appeared to be partially mediated through inflammatory pathways, indicating that CMI may serve as a valuable indicator for poor prognosis among the older population.