Prognostic value of circulating levels of stem cell growth factor beta (SCGF beta) in patients with Chagas’ disease and idiopathic dilated cardiomyopathy

Genetic Evidence for the Causal Association of Circulating Cytokines and Growth Factors With Coronary Artery Disease

BACKGROUND

Observational studies have suggested the potential role of inflammatory factors in the risk of coronary artery disease (CAD). We aimed to perform 2-sample Mendelian randomization (MR) analyses to assess the causal association between circulating cytokines/growth factors and CAD.

METHODS AND RESULTS

The instrumental variables for 28 circulating cytokines and growth factors were identified from a genome-wide association study of 8293 European participants. Summary-level data on CAD were derived from a large genome-wide association study (71 602 cases and 260 875 controls). We used the inverse-variance-weighted and Wald ratio methods as our main MR methods. The weighted median, simple median, maximum likelihood, MR pleiotropy residual sum and outlier, and MR-Egger methods were performed as sensitivity analyses. Genetic colocalization analyses were conducted to validate the robustness of our MR findings. We found that genetically predicted circulating levels of macrophage migration inhibitory factor were associated with an increased risk of CAD at the Bonferroni-adjusted level of significance (P<1.79×10-3). The odds ratio was 1.20 (95% CI, 1.08-1.33; P=6.83×10-4) per 1-SD increase in macrophage migration inhibitory factor. Colocalization analyses supported our MR findings. Additionally, we found suggestive evidence between the genetic effects of stem cell growth factor-β and the risk of CAD (odds ratio, 0.95 [95% CI, 0.91-0.98]; P=0.007).

CONCLUSIONS

Our findings suggested a risk-increasing effect of macrophage migration inhibitory factor level on the development of CAD. The roles of these inflammatory factors for CAD warrant further investigation.

The Expression of Cytokine Profiles and Related Receptors in Idiopathic Inflammatory Myopathies

Background: Cytokines play a vital role in the pathogenesis of idiopathic inflammatory myopathies (IIMs). Here, we investigated the expression of serum cytokine profiles in untreated IIMs and their correlations with clinical indicators, and further studied the expression of related cytokines receptors in IIMs. Methods: The Human 48-Plex Luminex assay for cytokines was performed in the serum of IIMs, including 93 untreated and 18 follow-up (39 samples) patients, and 32 healthy controls (HC). Mann-Whitney U test with bonferroni adjusted was used to identify the differentially expressed cytokines among groups. Celltalker software was used to identify the receptors of differentially expressed cytokines. The expression of receptors was further validated by published GEO datasets (muscle, blood and skin), RT-qPCR, western blot and flow cytometry. Results: The serum levels of Eotaxin, IL7, IL18, IP10, MCP1, MCSF, MIG and SCGFβ were elevated in the 93 untreated patients. Except for IL7, all other cytokines were decreased after treatment and their levels were positively correlated with clinical indices such as LDH, ESR, CRP, ALT, IgA, AST and IgG while negatively correlated with albumin and MMT8. According to the serum myositis-specific antibodies (MSAs), patients were classified into three groups: anti-ARS (Jo-1, OJ, EJ, PL7, PL12), anti-MDA5 positive, and anti-TIF1γ positive. Compared with HC, the levels of IP10 and MIG were increased in three groups. Moreover, IL18 and MSCF were increased in anti-ARS patients, and CTACK, Eotaxin, IL1Rα, IL7, IL18, MCP1, MCP3, MCSF and SCGFβ were elevated in anti-MDA5 patients. Twenty receptors of the 8 differentially expressed cytokines were matched by celltalker software, among them, IL18R1 and CCR1 were up-regulated in blood, muscle and skin of IIMs from the analysis of GEO published datasets. RT-qPCR and western blot further validated IL18R1 was upregulated in the muscle tissues of dermatomyositis. The number of IL18R1⁺CD4⁺ cells was increased while IL18R1⁺CD8⁺ cells was decreased in peripheral blood of anti-MDA5 patients. Conclusion: This study showed that cytokine profiles were significantly changed in IIMs, and different MSA groups had unique cytokine expression patterns. The levels of some cytokine were correlated with clinical indices. The IL18 receptor IL18R1 might play important roles in IIMs.

Isolation and molecular characterization of circulating extracellular vesicles from blood of chronic Chagas disease patients

Extracellular vesicles (EVs) are lipid bilayer envelopes that encase several types of molecules. Their contents mostly reflect their cell origin and possible targets at other locations in the organism and can be modified in pathological conditions to interfere with intercellular communication, thus promoting disease establishment and development. These characteristics, in addition to their presence in virtually all body fluids, make such vesicles ideal for biomarker discovery in human diseases. Here we describe the effect of different anticoagulants and the combination of two purification methods for isolation and characterization of circulating extracellular vesicles from blood of chronic Chagas disease (CCD) patients. We illustrated this procedure by studying a population of patients with Chagas disease at the indeterminate chronic stage, in which the Trypanosoma cruzi is very scarce in circulation. EVs were harvested from blood collected without or with different anticoagulants. Protein and nanoparticle tracking analysis was used to measure EVs size and concentration. The EVs were purified by ultracentrifugation, followed by size exclusion chromatography and characterized by chemiluminescent ELISA and Dot Blot using antibodies that recognized parasite-derived EVs, such as hyperimmune sera, polyclonal and monoclonal antibodies against trans-sialidase and mucins. In parallel, antibodies against classical human EV markers CD9, CD63, CD81 and CD82, were also analyzed. The results showed that anticoagulants did not interfere with the analyzed parameters and circulating EVs from CCD patients contain T. cruzi antigens and classical human exosomal markers. Overall, our protocol is adequate for the isolation of the total circulating extracellular vesicles and can serve as an important basis for further studies on biomarker discovery in Chagas' disease. This article is protected by copyright. All rights reserved.

Targeted proteomics of right heart adaptation to pulmonary arterial hypertension

No prior proteomic screening study has centred on the right ventricle (RV) in pulmonary arterial hypertension (PAH). This study investigates the circulating proteomic profile associated with right heart maladaptive phenotype (RHMP) in PAH.Plasma proteomic profiling was performed using multiplex immunoassay in 121 (discovery cohort) and 76 (validation cohort) PAH patients. The association between proteomic markers and RHMP, defined by the Mayo right heart score (combining RV strain, New York Heart Association (NYHA) class and N-terminal pro-brain natriuretic peptide (NT-proBNP)) and Stanford score (RV end-systolic remodelling index, NYHA class and NT-proBNP), was assessed by partial least squares regression. Biomarker expression was measured in RV samples from PAH patients and controls, and pulmonary artery banding (PAB) mice.High levels of hepatocyte growth factor (HGF), stem cell growth factor-β, nerve growth factor and stromal derived factor-1 were associated with worse Mayo and Stanford scores independently from pulmonary resistance or pressure in both cohorts (the validation cohort had more severe disease features: lower cardiac index and higher NT-proBNP). In both cohorts, HGF added value to the REVEAL score in the prediction of death, transplant or hospitalisation at 3 years. RV expression levels of HGF and its receptor c-Met were higher in end-stage PAH patients than controls, and in PAB mice than shams.High plasma HGF levels are associated with RHMP and predictive of 3-year clinical worsening. Both HGF and c-Met RV expression levels are increased in PAH. Assessing plasma HGF levels might identify patients at risk of heart failure who warrant closer follow-up and intensified therapy.

Measurement of multiple cytokines for discrimination and risk stratification in patients with Chagas' disease and idiopathic dilated cardiomyopathy

Chagas' disease (CD), caused by the hemoflagellate protozoan, Trypanosoma cruzi, is endemic in most countries of Latin America. Heart failure (HF) is often a late manifestation of chronic CD, and is associated with high morbidity and mortality. Inflammatory processes mediated by cytokines play a key role in the pathogenesis and progression of CD. Keeping in view the inflammatory nature of CD, this study investigated the possible role of 21 different inflammatory cytokines as biomarkers for prediction and prognosis of CD. The plasma concentration of these cytokines was measured in a group of patients with CD (n = 94), and then compared with those measured in patients with dilated cardiomyopathy (DCM) from idiopathic causes (n = 48), and with control subjects (n = 25). Monovariately, plasma levels of cytokines such as stem cell growth factor beta (SCGF beta), hepatocyte growth factor (HGF), monokine induced by interferon gamma (CXCL9), and macrophage inhibitory factor (MIF) were significantly increased in CD patients with advanced HF compared to control group. None of the cytokines could demonstrate any prognostic potency in CD patients, and only MIF and stromal derived factor-1 alpha (CXCL12) showed significance in predicting mortality and necessity for heart transplant in DCM patients. However, multivariate analysis prognosticated a large proportion of CD and DCM patients. In CD patients, HGF and Interleukin-12p40 (IL-12p40) together separated 81.9% of 3-year survivors from the deceased, while in DCM patients, CXCL12, stem cell factor (SCF), and CXCL9 together discriminated 77.1% of survivors from the deceased. The significant increase in plasma concentrations of cytokines such as HGF and CXCL9 in CD patients, and the ability of these cytokines to prognosticate a large proportion of CD and DCM patients multivariately, encourages further studies to clarify the diagnostic and prognostic potential of cytokines in such patients.

A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study

Background

Approximately 80% of those infected with COVID-19 are immune. They are asymptomatic unknown carriers who can still infect those with whom they come into contact. Understanding what makes them immune could inform public health policies as to who needs to be protected and why, and possibly lead to a novel treatment for those who cannot, or will not, be vaccinated once a vaccine is available.

Objective

The primary objectives of this study were to learn if machine learning could identify patterns in the pathogen-host immune relationship that differentiate or predict COVID-19 symptom immunity and, if so, which ones and at what levels. The secondary objective was to learn if machine learning could take such differentiators to build a model that could predict COVID-19 immunity with clinical accuracy. The tertiary purpose was to learn about the relevance of other immune factors.

Methods

This was a comparative effectiveness research study on 53 common immunological factors using machine learning on clinical data from 74 similarly grouped Chinese COVID-19-positive patients, 37 of whom were symptomatic and 37 asymptomatic. The setting was a single-center primary care hospital in the Wanzhou District of China. Immunological factors were measured in patients who were diagnosed as SARS-CoV-2 positive by reverse transcriptase-polymerase chain reaction (RT-PCR) in the 14 days before observations were recorded. The median age of the 37 asymptomatic patients was 41 years (range 8-75 years); 22 were female, 15 were male. For comparison, 37 RT-PCR test-positive patients were selected and matched to the asymptomatic group by age, comorbidities, and sex. Machine learning models were trained and compared to understand the pathogen-immune relationship and predict who was immune to COVID-19 and why, using the statistical programming language R.

Results

When stem cell growth factor-beta (SCGF-β) was included in the machine learning analysis, a decision tree and extreme gradient boosting algorithms classified and predicted COVID-19 symptom immunity with 100% accuracy. When SCGF-β was excluded, a random-forest algorithm classified and predicted asymptomatic and symptomatic cases of COVID-19 with 94.8% AUROC (area under the receiver operating characteristic) curve accuracy (95% CI 90.17%-100%). In total, 34 common immune factors have statistically significant associations with COVID-19 symptoms (all c<.05), and 19 immune factors appear to have no statistically significant association.

Conclusions

The primary outcome was that asymptomatic patients with COVID-19 could be identified by three distinct immunological factors and levels: SCGF-β (>127,637), interleukin-16 (IL-16) (>45), and macrophage colony-stimulating factor (M-CSF) (>57). The secondary study outcome was the suggestion that stem-cell therapy with SCGF-β may be a novel treatment for COVID-19. Individuals with an SCGF-β level >127,637, or an IL-16 level >45 and an M-CSF level >57, appear to be predictively immune to COVID-19 100% and 94.8% (AUROC) of the time, respectively. Testing levels of these three immunological factors may be a valuable tool at the point of care for managing and preventing outbreaks. Further, stem-cell therapy via SCGF-β and M-CSF appear to be promising novel therapeutics for patients with COVID-19.

Inflammatory Mediator Profiles in Secretory Otitis Media in Relationship to Viable Bacterial Pathogens and Bacterial and Viral Nucleic Acids

Secretory otitis media (SOM) is characterized by persistence of fluid in the middle ear, often following an episode of acute otitis media. Our hypothesis is that failure to eliminate bacterial or viral pathogens may result in persistent low-grade inflammation. In this study, we analyzed inflammatory mediators in middle ear fluids from 67 children with SOM. This was combined with determinations of viable bacteria by culture along with detection of bacterial and viral genetic material by real-time polymerase chain reaction (PCR). The inflammatory mediators found at the highest concentrations (>30 ng/mL) were stem cell growth factor-β (median 110 ng/mL), CXCL1, IL-16, IL-8, migration inhibitory factor, CXCL10, and CXCL9. Among bacterial pathogens, Moraxella catarrhalis and Haemophilus influenzae dominated, regardless of detection methods, while rhinovirus dominated among viral pathogens. Middle ear fluid levels of interleukin (IL)-1α, IL-17, IL-1β, fibroblast growth factor basic, and tumor necrosis factor correlated strongly with presence of bacteria detected either by culture or PCR, while IL-1RA, IL-3, IL-6, IL-8, CCL3, CCL4, and granulocyte-colony stimulating factor correlated significantly with real-time PCR values. CXCL10, CXCL9, CCL2, and TRAIL correlated significantly with viral nucleic acid levels. To conclude, persistence of viral and bacterial pathogens may fuel persistent inflammation in SOM. Bacteria caused a broad inflammatory response, while viruses chiefly elicited the interferon-induced chemokines CXCL9 and CXCL10.

Molecular structure, expression, and functional role of Clec11a in skeletal biology and cancers

C-type lectin domain family 11 member A (Clec11a), also known as stem cell growth factor (SCGF), C-type lectin superfamily member 3 (CLECSF3), or osteolectin was initially identified as a growth factor for hematopoietic progenitor cells. The human Clec11a gene encodes a polypeptide of 323 amino acids with characteristics of a secreted glycoprotein encompassing two integrin-binding motifs, RGD (Arg-Gly-Asp) and LDT (Leu-Asp-Thr), a putative leucine zipper domain, and a functional C-type lectin domain. It regulates hematopoietic differentiation and homeostasis and exhibits a protective effect against severe malarial anemia and lipotoxicity. Furthermore, Clec11a promotes the differentiation of mesenchymal progenitors into mature osteoblasts in vitro and plays an important role in the maintenance of adult skeleton age-related bone loss and fracture repair. Receptor ligand binding results in activation of downstream signaling cascades including glycogen synthase kinase 3 (GSK3), β-catenin, and Wnt, resulting in the expression of osteoblast-related gene transcripts including Alp, Runx2, Lef1, and Axin2. In addition, Clec11a is also associated with the development of several cancers, including leukemia, multiple myeloma, and gastrointestinal tract tumors. To date, however, the mechanisms governing transcription regulation of the Clec11a gene are not known and remain to be uncovered. Understanding the function and mechanism of action of Clec11a will pave the way for the development of Clec11a as a novel therapeutic target for conditions such as cancer, anemia, and skeletal diseases.

Current and upcoming therapies to modulate skin scarring and fibrosis

Skin is the largest organ of the human body. Being the interface between the body and the outer environment, makes it susceptible to physical injury. To maintain life, nature has endowed skin with a fast healing response that invariably ends in the formation of scar at the wounded dermal area. In many cases, skin remodelling may be impaired, leading to local hypertrophic scars or keloids. One should also consider that the scarring process is part of the wound healing response, which always starts with inflammation. Thus, scarring can also be induced in the dermis, in the absence of an actual wound, during chronic inflammatory processes. Considering the significant portion of the population that is subject to abnormal scarring, this review critically discusses the state-of-the-art and upcoming therapies in skin scarring and fibrosis.