Monocyte distribution width (MDW) performance as an early sepsis indicator in the emergency department: comparison with CRP and procalcitonin in a multicenter international European prospective study.

BACKGROUND: Early sepsis diagnosis has emerged as one of the main challenges in the emergency room. Measurement of sepsis biomarkers is largely used in current practice to improve the diagnosis accuracy. Monocyte distribution width (MDW) is a recent new sepsis biomarker, available as part of the complete blood count with differential. The objective was to evaluate the performance of MDW for the detection of sepsis in the emergency department (ED) and to compare to procalcitonin (PCT) and C-reactive protein (CRP). METHODS: Subjects whose initial evaluation included a complete blood count were enrolled consecutively in 2 EDs in France and Spain and categorized per Sepsis-2 and Sepsis-3 criteria. The performance of MDW for sepsis detection was compared to that of procalcitonin (PCT) and C-reactive protein (CRP). RESULTS: A total of 1,517 patients were analyzed: 837 men and 680 women, mean age 61 ± 19 years, 260 (17.1%) categorized as Sepsis-2 and 144 patients (9.5%) as Sepsis-3. The AUCs [95% confidence interval] for the diagnosis of Sepsis-2 were 0.81 [0.78-0.84] and 0.86 [0.84-0.88] for MDW and MDW combined with WBC, respectively. For Sepsis-3, MDW performance was 0.82 [0.79-0.85]. The performance of MDW combined with WBC for Sepsis-2 in a subgroup of patients with low sepsis pretest probability was 0.90 [0.84-0.95]. The AUC for sepsis detection using MDW combined with WBC was similar to CRP alone (0.85 [0.83-0.87]) and exceeded that of PCT. Combining the biomarkers did not improve the AUC. Compared to normal MDW, abnormal MDW increased the odds of Sepsis-2 by factor of 5.5 [4.2-7.1, 95% CI] and Sepsis-3 by 7.6 [5.1-11.3, 95% CI]. CONCLUSIONS: MDW in combination with WBC has the diagnostic accuracy to detect sepsis, particularly when assessed in patients with lower pretest sepsis probability. We suggest the use of MDW as a systematic screening test, used together with qSOFA score to improve the accuracy of sepsis diagnosis in the emergency department. Trial Registration ClinicalTrials.gov (NCT03588325).

Changes in the behaviour of monocyte subsets in acute post-traumatic sepsis patients.

Trauma remains a major public health problem worldwide, marked as the fourth leading cause of death among all diseases. Trauma patients who survived at initial stages in the Emergency Department (ED), have significantly higher chances of mortality due to sepsis associated complications in the ICU at the later stage. There is paucity of literature regarding the role of circulating monocytes subsets and development of sepsis complications following trauma haemorrhagic shock (THS). The study was conducted to investigate the circulating level of monocyte subsets (Classical, Inflammatory, and Patrolling) and its functions in patients with acute post-traumatic sepsis. A total 72, THS patients and 30 age matched healthy controls were recruited. Blood samples were collected at different time points on days 1, 7, and 14 to measure the serum levels of cytokines by Cytometric bead assay (CBA), for the immunophenotyping of monocytes subsets, and also for the cell sorting of monocytes subsets for the functional studies. The circulating levels of monocytes subsets were found to be significantly differs among THS patients, who developed sepsis when compared with others who did not. The levels of patrolling monocytes were elevated in THS patients who developed sepsis and showed negative correlation with Sequential organ failure assessment (SOFA) score on days 7 and 14. Classical monocytes responded strongly to bacterial TLR-agonist (LPS) and produced anti-inflammatory cytokines, whereas patrolling monocytes responded with viral TLR agonist TLR-7/8 (R848) and produced inflammatory cytokines in post-traumatic sepsis patients. In conclusion, this study shows disparity in the behaviour of monocytes subsets in patients with acute post-traumatic sepsis.

Identification of human immune cell subtypes most responsive to IL-1ß-induced inflammatory signaling using mass cytometry.

IL-1ß is a key mediator of the cytokine storm linked to high morbidity and mortality from COVID-19, and IL-1ß blockade with anakinra and canakinumab during COVID-19 infection has entered clinical trials. Using mass cytometry of human peripheral blood mononuclear cells, we identified effector memory CD4+ T cells and CD4-CD8low/-CD161+ T cells, specifically those positive for the chemokine receptor CCR6, as the circulating immune subtypes with the greatest response to IL-1ß. This response manifested as increased phosphorylation and, thus, activation of the proinflammatory transcription factor NF-κB and was also seen in other subsets, including CD11c+ myeloid dendritic cells, classical monocytes, two subsets of natural killer cells (CD16-CD56brightCD161- and CD16-CD56dimCD161+), and lineage- (Lin-) cells expressing CD161 and CD25. IL-1ß also induced a rapid but less robust increase in the phosphorylation of the kinase p38 as compared to that of NF-κB in most of these immune cell subsets. Prolonged IL-1ß stimulation increased the phosphorylation of the transcription factor STAT3 and to a lesser extent that of STAT1 and STAT5 across various immune cell types. IL-1ß-induced production of IL-6 likely led to the activation of STAT1 and STAT3 at later time points. Interindividual heterogeneity and inhibition of STAT activation by anakinra raise the possibility that assays measuring NF-κB phosphorylation in response to IL-1ß in CCR6+ T cell subtypes could identify those patients at higher risk of cytokine storm and most likely to benefit from IL-1ß-neutralizing therapies.

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits.

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.

A low level of CD16pos monocytes in SARS-CoV-2 infected patients is a marker of severity.

OBJECTIVES: Severe forms of coronavirus disease 2019 (COVID-19) are characterized by an excessive production of inflammatory cytokines. Activated monocytes secrete high levels of cytokines. Human monocytes are divided into three major populations: conventional (CD14posCD16neg), non-classical (CD14dimCD16pos), and intermediate (CD14posCD16pos) monocytes. The aim of this study was to analyze whether the distribution of conventional (CD16neg) and CD16pos monocytes is different in patients with COVID-19 and whether the variations could be predictive of the outcome of the disease. METHODS: We performed a prospective study on 390 consecutive patients referred to the Emergency Unit, with a proven diagnosis of SARS-CoV 2 infection by RT-PCR. Using the CytoDiff™ reagent, an automated routine leukocyte differential, we quantified CD16neg and CD16pos monocytes. RESULTS: In the entire population, median CD16neg and CD16pos monocyte levels (0.398 and 0.054×109/L, respectively) were in the normal range [(0.3-0.7×109/L) and (0.015-0.065×109/L), respectively], but the 35 patients in the intensive care unit (ICU) had a significantly (p<0.001) lower CD16pos monocyte count (0.018 × 109/L) in comparison to the 70 patients who were discharged (0.064 × 109/L) or were hospitalized in conventional units (0.058 × 109/L). By ROC curve analysis, the ratio [absolute neutrophil count/CD16pos monocyte count] was highly discriminant to identify patients requiring ICU hospitalization: with a cut-off 193.1, the sensitivity and the specificity were 74.3 and 81.8%, respectively (area under the curve=0.817). CONCLUSIONS: Quantification of CD16pos monocytes and the ratio [absolute neutrophil count/CD16pos monocyte count] could constitute a marker of the severity of disease in COVID-19 patients.

Baseline monocyte and its classical subtype may predict efficacy of PD-1/PD-L1 inhibitor in cancers.

BACKGROUND: Programmed death 1 (PD-1)/ programmed death-ligand 1 (PD-L1) inhibitor is one of the most popular immune therapies. Biomarkers for predicting response are highly needed, but no biomarkers are widely used till now. PATIENTS AND METHODS: From February 2018 to April 2019, pan-cancer patients treated with PD-1 or PD-L1 inhibitor as a single agent in our center were included. The benefit group included patients with partial response, complete response and stable disease, while the patients with progressive disease were classified into the nonbenefit group, according to the RECIST 1.1 criteria. Baseline peripheral blood was sampled to determine absolute monocyte count (AMC) and/or classical monocyte frequency (CMF) of peripheral blood mononuclear cells. Then, the association of the above-mentioned two biomarkers with response or progression-free survival (PFS) was evaluated. RESULTS: In total, 107 patients enrolled in the present study. The nonbenefit group had significantly larger number of AMC than benefit group (P<0.001), and patients with higher AMC had decreased PFS time (P=0.001). Of 39 patients tested for CMF, the nonbenefit group had significantly higher CMF than benefit group (P=0.002), and patients with higher CMF had significantly decreased PFS time (P=0.002). The sensitivity of AMC and CMF was 87.9% and 85.7%, respectively, and the specificity was 44.9% and 61.1%, respectively. Multivariate analysis showed high baseline CMF and AMC were both significantly associated with decreased PFS time. CONCLUSION: Baseline CMF and baseline AMC can be potential pan-cancer biomarkers to predict efficacy of PD-1/PD-L1 inhibitors, especially in the PD-L1 subgroup.

Progress and challenge for computational quantification of tissue immune cells.

Tissue immune cells have long been recognized as important regulators for the maintenance of balance in the body system. Quantification of the abundance of different immune cells will provide enhanced understanding of the correlation between immune cells and normal or abnormal situations. Currently, computational methods to predict tissue immune cell compositions from bulk transcriptomes have been largely developed. Therefore, summarizing the advantages and disadvantages is appropriate. In addition, an examination of the challenges and possible solutions for these computational models will assist the development of this field. The common hypothesis of these models is that the expression of signature genes for immune cell types might represent the proportion of immune cells that contribute to the tissue transcriptome. In general, we grouped all reported tools into three groups, including reference-free, reference-based scoring and reference-based deconvolution methods. In this review, a summary of all the currently reported computational immune cell quantification tools and their applications, limitations, and perspectives are presented. Furthermore, some critical problems are found that have limited the performance and application of these models, including inadequate immune cell type, the collinearity problem, the impact of the tissue environment on the immune cell expression level, and the deficiency of standard datasets for model validation. To address these issues, tissue specific training datasets that include all known immune cells, a hierarchical computational framework, and benchmark datasets including both tissue expression profiles and the abundances of all the immune cells are proposed to further promote the development of this field.

Monocyte subsets to differentiate chronic myelomonocytic leukemia from reactive monocytosis.

BACKGROUND: Chronic myelomonocytic leukemia (CMML) is characterized by persistent monocytosis and dysplastic features of blood cells. No specific genetic abnormalities are present in CMML, and reactive monocytosis should be excluded. An increase in classical monocytes (MO1) has been suggested as a screening tool for CMML. METHODS: We evaluated monocyte subsets in the peripheral blood of patients with CMML (n = 16), patients with reactive monocytosis (n = 19), and normal controls (n = 15) with flow cytometry using antibodies against CD14, CD16, CD56, CD24, CD45, and CD2. The cutoff of MO1 ≥94% was validated, and the optimal cutoff was analyzed with receiver operating curve analysis. RESULTS: The sensitivity of monocyte subset testing for screening for CMML was 0.938 (0.717-0.997), and the specificity was 0.882 (0.734 - 0.953) using the cutoff of MO1 ≥94%. Serial samples from patients who responded to hypomethylating therapy showed an MO1 < 94%. However, few patients with reactive monocytosis, including patients with nonhematologic malignancies and acute myeloid leukemia, showed an increase in the MO1 ≥ 94%. Monocyte subset results were correlated with the response to hypomethylating therapy in follow-up samples. CONCLUSION: Monocyte subset analysis is useful in screening for and monitoring CMML. Harmonization of the protocols for monocyte subset analysis is required.

Integrated bulk and single-cell RNA-sequencing identified disease-relevant monocytes and a gene network module underlying systemic sclerosis.

OBJECTIVE: Immunological disturbances have been reported in systemic sclerosis (SSc). This study assessed the transcriptome disturbances in immune cell subsets in SSc and characterized a disease-related gene network module and immune cell cluster at single cell resolution. METHODS: Twenty-one Japanese SSc patients were enrolled and compared with 13 age- and sex-matched healthy controls (HC). Nineteen peripheral blood immune cell subsets were sorted by flow cytometry and bulk RNA-seq analysis was performed for each. Differential expression and pathway analyses were conducted. Iterative weighted gene correlation network analysis (iWGCNA) of each subset revealed clustered co-expressed gene network modules. Random forest analysis prioritized a disease-related gene module. Single cell RNA-seq analysis of 878 monocytes was integrated with bulk RNA-seq analysis and with a public database for single cell RNA-seq analysis of SSc patients. RESULTS: Inflammatory pathway genes were differentially expressed in widespread immune cell subsets of SSc. An inflammatory gene module from CD16+ monocytes, which included KLF10, PLAUR, JUNB and JUND, showed the greatest discrimination between SSc and HC. One of the clusters of SSc monocytes identified by single-cell RNA-seq analysis characteristically expressed these inflammatory co-expressed genes and was similar to lung infiltrating FCN1hi monocytes expressing IL1B. CONCLUSIONS: Our integrated analysis of bulk and single cell RNA-seq analysis identified an inflammatory gene module and a cluster of monocytes that are relevant to SSc pathophysiology. They could serve as candidate novel therapeutic targets in SSc.

Increased Frequencies of Myeloid-Derived Suppressor Cells Precede Immunodiscordance in HIV-Infected Subjects.

Background: We have previously observed increased levels of inflammatory biomarkers and Th17 as well as Treg cells, but not other T-cell specific alterations, preceding immunodiscordance of successfully-treated HIV-infected subjects. Our hypothesis is that this could be related with potential alterations in myeloid-derived suppressor cells (MDSCs) and/or monocyte subsets. Methods: We determined the frequencies of MDSCs and monocyte subsets and the expression of several functional markers (CCR2, ß7-integrin, IDO, PDL1, CD11b) in HIV-infected subjects before treatment. We additionally analyzed follow-up samples after 24 months of suppressive cART in a subgroup of subjects. Bivariate regressions were performed, and correlations with soluble proinflammatory and bacterial translocation biomarkers, as well as with Th17/Treg ratio and anti-CMV titers were explored. Results: Increased frequencies of MDSCs, but normal distribution of monocyte subsets, preceded immunodiscordance. The expression of several functional markers, such as CCR2, CD16, CD11b and PDL1, on MDSCs and monocyte subsets was altered in this scenario. MDSC and monocyte-related functional markers were associated with soluble biomarkers and T-cell parameters. Several of these cellular alterations were not restored after 24 months of suppressive cART. Conclusion: An early immunosuppressive environment, characterized by the expansion of MDSCs and Tregs, precedes immunodiscordance and is related with a highly inflammatory status.

Type 2 diabetes mellitus metabolic control correlates with the phenotype of human monocytes and monocyte-derived macrophages.

AIMS: Monocytes and macrophages express cell-surface markers indicative of their inflammatory and activation status. In this study, we investigated whether these markers are affected or correlated in non-obese T2D subjects, or glycemic/metabolic control variables. METHODS: Clinical data was recorded, and peripheral blood drawn from T2D patients (n = 28) and control subjects (n = 27). Isolated monocytes were evaluated by flow cytometry for the expression of CD14, CD16, and the phenotypic markers for the different states of activation spectrum, such as pro-inflammatory (M1) (HLA-DR, CD86), anti-inflammatory/pro-resolving (M2) (CD163, CD206, MERTK, PD-L1) and metabolically-activated (MMe) (CD36, ABCA-1). From a subset of individuals, monocytes-derived macrophages (MDM) were obtained and evaluated for phenotypic markers. A correlation analysis was performed between the clinical variables and the marker expression. RESULTS: The frequency of CD14++CD16- monocytes was lower in T2D patients and it correlates negatively with poor control in glycemic and metabolic variables. T2D monocytes expressed lower levels of HLA-DR, CD86, PD-L1, and CD163, which correlated negatively with poor metabolic control. In MDM from T2D patients, HLA-DR, CD86 and CD163 expression was lower and it inversely correlated with deficient glycemic or metabolic control parameters. CONCLUSION: The glycemic/metabolic control associated with T2D influences monocyte and MDM phenotypes toward an immune-suppressive phenotype.

COVID-19 severity associates with pulmonary redistribution of CD1c+ DCs and inflammatory transitional and nonclassical monocytes.

SARS-CoV-2 is responsible for the development of coronavirus disease 2019 (COVID-19) in infected individuals, who can either exhibit mild symptoms or progress toward a life-threatening acute respiratory distress syndrome (ARDS). Exacerbated inflammation and dysregulated immune responses involving T and myeloid cells occur in COVID-19 patients with severe clinical progression. However, the differential contribution of specific subsets of dendritic cells and monocytes to ARDS is still poorly understood. In addition, the role of CD8+ T cells present in the lung of COVID-19 patients and relevant for viral control has not been characterized. Here, we have studied the frequencies and activation profiles of dendritic cells and monocytes present in the blood and lung of COVID-19 patients with different clinical severity in comparison with healthy individuals. Furthermore, these subpopulations and their association with antiviral effector CD8+ T cell subsets were also characterized in lung infiltrates from critical COVID-19 patients. Our results indicate that inflammatory transitional and nonclassical monocytes and CD1c+ conventional dendritic cells preferentially migrate from blood to lungs in patients with severe COVID-19. Thus, this study increases the knowledge of specific myeloid subsets involved in the pathogenesis of COVID-19 disease and could be useful for the design of therapeutic strategies for fighting SARS-CoV-2 infection.

Monocyte subsets in bone marrow grafts may contribute to a low incidence of acute graft-vs-host disease for young donors.

Young donors are associated with a lower cumulative incidence of acute graft-vs-host disease (aGVHD) after allogenic haematopoietic stem cell transplantation (allo-HSCT) than old donors. Although grafts are harvested from healthy donors, it is unclear whether donor age is associated with aGVHD occurrence owing to its effect on cell compositions in grafts. Moreover, the differences in monocyte subsets in grafts between young and old donors and the association between monocyte subsets in bone marrow (BM) grafts and aGVHD remain to be elucidated. In the current study, non-classical monocytes and the CD4+ /CD8+ T cell ratio were remarkably decreased in BM grafts in donors <30 years old. Multivariate analysis further revealed that the level of non-classical monocytes in BM grafts (≥0.31 × 106 /kg) was an independent risk factor for the occurrence of II-IV aGVHD. In summary, our data indicate that non-classical monocytes in BM grafts may help identify patients at high risk for aGVHD after allo-HSCT. Although further validation is required, our results suggest that the low level of non-classical monocytes and a low ratio of CD4+ /CD8+ T cell in BM grafts may be correlated with the lower incidence of aGVHD in young donors.

Human Monocyte Subset Distinctions and Function: Insights From Gene Expression Analysis.

Monocytes are a highly plastic innate immune cell population that displays significant heterogeneity within the circulation. Distinct patterns of surface marker expression have become accepted as a basis for distinguishing three monocyte subsets in humans. These phenotypic subsets, termed classical, intermediate and nonclassical, have also been demonstrated to differ in regard to their functional properties and disease associations when studied in vitro and in vivo. Nonetheless, for the intermediate monocyte subset in particular, functional experiments have yielded conflicting results and some studies point to further levels of heterogeneity. Developments in genetic sequencing technology have provided opportunities to more comprehensively explore the phenotypic and functional differences among conventionally-recognized immune cell subtypes as well as the potential to identify novel subpopulations. In this review, we summarize the transcriptomic evidence in support of the existence of three separate monocyte subsets. We also critically evaluate the insights into subset functional distinctions that have been garnered from monocyte gene expression analysis and the potential utility of such studies to unravel subset-specific functional changes which arise in disease states.

Pattern of human monocyte subpopulations in health and disease.

Monocytes are important cells of the innate system. They are a heterogeneous type of cells consisting of phenotypically and functionally distinct subpopulations, which play a specific role in the control, development and escalation of the immunological processes. Based on the expression of superficial CD14 and CD16 in flow cytometry, they can be divided into three subsets: classical, intermediate and non-classical. Variation in the levels of human monocyte subsets in the blood can be observed in patients in numerous pathological states, such as infections, cardiovascular and inflammatory diseases, cancer and autoimmune diseases. The aim of this review is to summarize current knowledge of human monocyte subsets and their significance in homeostasis and in pathological conditions.

Analysis of the Expression of Regulator Genes in Kupffer Cells and Monocytes.

Differences in the gene expression profiles in resident macrophages (in particular, Kupffer cells) and monocytes were revealed. However, these differences in gene expression profiles do not allow considering resident liver macrophages as purely M2 macrophages and monocytes as purely M1 macrophages. At the same time, a significant number of the genes upregulated in Kupffer cells are associated with normal regulation of liver functions (Arg 1, Flt, iNOs, and Kng). In monocytes, the expression of genes Alox15, Alox12, Tlr2, Tlr4, Tlr7, and Tlr8 (typical functional genes of macrophages) was also upregulated in comparison with Kupffer cells.

CD14+ CD16+ monocytes are involved in daratumumab-mediated myeloma cells killing and in anti-CD47 therapeutic strategy.

A deep elucidation of the mechanisms of action of anti-CD38 monoclonal antibodies (mAbs), such as daratumumab (DARA), is required to identify patients with multiple myeloma (MM) who are more responsive to this treatment. In the present study, an autologous ex vivo approach was established, focussing on the role of the monocytes in the anti CD38-mediated killing of MM cells. In bone marrow (BM) samples from 29 patients with MM, we found that the ratio between monocytes (CD14+ ) and MM cells (CD138+ ) influences the response to DARA. Further, the exposure of the BM samples to DARA is followed by the formation of a CD138+ CD14+ double-positive (DP) population, that quantitatively correlates with the anti-MM cells killing. These effects were dependent on the presence of a CD14+ CD16+ monocyte subset and on high CD16 expression levels. Lastly, the addition of a mAb neutralising the CD47/signal-regulatory protein α (SIRPα) axis was able to increase the killing mediated by DARA. The effects were observed only in coincidence with high CD14+ :CD138+ ratio, with a significant presence of the DP population and were correlated with CD16 expression. In conclusion, the present study underlines the critical role of the CD16+ monocytes in DARA anti-MM killing effects and gives a rationale to test the combination of an anti-CD47 mAb with anti-CD38 mAbs.

Persistent Systemic Inflammation in Patients With Severe Burn Injury Is Accompanied by Influx of Immature Neutrophils and Shifts in T Cell Subsets and Cytokine Profiles.

Severe burn injury causes local and systemic immune responses that can persist up to months, and can lead to systemic inflammatory response syndrome, organ damage and long-term sequalae such as hypertrophic scarring. To prevent these pathological conditions, a better understanding of the underlying mechanisms is essential. In this longitudinal study, we analyzed the temporal peripheral blood immune profile of 20 burn wound patients admitted to the intensive care by flow cytometry and secretome profiling, and compared this to data from 20 healthy subjects. The patient cohort showed signs of systemic inflammation and persistently high levels of pro-inflammatory soluble mediators, such as IL-6, IL-8, MCP-1, MIP-1ß, and MIP-3α, were measured. Using both unsupervised and supervised flow cytometry techniques, we observed a continuous release of neutrophils and monocytes into the blood for at least 39 days. Increased numbers of immature neutrophils were present in peripheral blood in the first three weeks after injury (0.1-2.8 × 106/ml after burn vs. 5 × 103/ml in healthy controls). Total lymphocyte numbers did not increase, but numbers of effector T cells as well as regulatory T cells were increased from the second week onward. Within the CD4+ T cell population, elevated numbers of CCR4+CCR6- and CCR4+CCR6+ cells were found. Altogether, these data reveal that severe burn injury induced a persistent innate inflammatory response, including a release of immature neutrophils, and shifts in the T cell composition toward an overall more pro-inflammatory phenotype, thereby continuing systemic inflammation and increasing the risk of secondary complications.

Features of repeated muscle biopsies and phenotypes of monocytes in paired blood samples and clinical long-term response to treatment in patients with idiopathic inflammatory myopathy: a pilot study.

OBJECTIVES: In a pilot study we aimed to identify biomarkers in repeated muscle biopsies and paired blood samples, taken before and after conventional immunosuppressive therapy, in order to predict long-term therapeutic response in patients with idiopathic inflammatory myopathies (IIM). METHODS: Muscle biopsies were selected from 13 new onset patients, six responders and seven non-responders. Repeated muscle biopsies after a median of 11 months follow-up were available from 9 patients and paired peripheral blood mononuclear cells (PBMCs) from 5 patients. Treatment response after 3 years was defined by MMT-8 measuring muscle strength and the ACR/EULAR 2016 improvement criteria. Frozen biopsy sections were immunohistochemically stained for expression of CD3, CD66b, IL-15, CD68, CD163 and myosin heavy chain neonatal (MHCn). PBMCs were analysed by flow cytometry for monocyte phenotypes (CD14, CD16, CD68, CX3CR1, and CCR2). RESULTS: Before treatment there were no significant differences in any clinical or muscle biopsy variables or monocyte subsets between responders and non-responders. MMT-8 was significantly higher compared to baseline in the responders at 3-year follow-up. In responders the expression of CD68 in the repeated biopsies was significantly lower compared to non-responders (p<0.05). CONCLUSIONS: Baseline biopsy, monocyte profile or clinical data did not predict long-term treatment response, but in the repeated biopsy within 1 year of immunosuppressive treatment, the lower number of macrophages (CD68+) seemed to predict a more favourable long-term clinical response with regard to improved muscle strength.

Monocyte Subsets Are Differently Associated with Infarct Size, Left Ventricular Function, and the Formation of a Potentially Arrhythmogenic Scar in Patients with Acute Myocardial Infarction.

To investigate the role of classical (CLM, CD14++CD16-), intermediate (INTM, CD14++CD16+), and non-classical (Non-CLM, CD14+CD16++) monocytes in scar formation after ST-elevation myocardial infarction (STEMI), evaluated with cardiac magnetic resonance (CMR). One hundred two patients with a first STEMI had serial blood analyses after 1, 3, and 7 days. A CMR was performed at 7 days and 6 months, depicting scar core (CO), border zone (BZ), and the presence of BZ channels. CLM and INTM levels progressively decreased, correlated with the scar mass, CO, and BZ at 7 days and 6 months (p < 0.05), and inversely with left ventricular ejection fraction (LVEF, p < 0.01). Non-CLM levels gradually increased, correlated with BZ mass and the presence of BZ channels at 7 days and 6 months (p < 0.001).CLM and INTM are associated with infarct size and inversely with LVEF, whereas Non-CLM are associated with BZ mass and the presence of potentially arrhythmogenic substrate.