Within- and between-subject biological variation estimates for the enumeration of lymphocyte deep immunophenotyping and monocyte subsets.

OBJECTIVES: This study aimed to deliver biological variation (BV) estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping (memory T/B cells, regulatory T cells, etc.) and classical, intermediate, and nonclassical monocyte subsets based on the full spectrum flow cytometry (FS-FCM) and a Biological Variation Data Critical Appraisal Checklist (BIVAC) design. METHODS: Samples were collected biweekly from 60 healthy Chinese adults over 10 consecutive two-week periods. Each sample was measured in duplicate within a single run for lymphocyte deep immunophenotyping and monocyte subset determination using FS-FCM, including the percentage (%) and absolute count (cells/µL). After trend adjustment, a Bayesian model was applied to deliver the within-subject BV (CVI) and between-subject BV (CVG) estimates with 95 % credibility intervals. RESULTS: Enumeration (% and cells/µL) for 25 types of lymphocyte deep immunophenotyping and three types of monocyte subset percentages showed considerable variability in terms of CVI and CVG. CVI ranged from 4.23 to 47.47 %. Additionally, CVG ranged between 10.32 and 101.30 %, except for CD4+ effector memory T cells re-expressing CD45RA. No significant differences were found between males and females for CVI and CVG estimates. Nevertheless, the CVGs of PD-1+ T cells (%) may be higher in females than males. Based on the desired analytical performance specification, the maximum allowable imprecision immune parameter was the CD8+PD-1+ T cell (cells/µL), with 23.7 %. CONCLUSIONS: This is the first study delivering BV estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping, along with classical, intermediate, and nonclassical monocyte subsets, using FS-FCM and adhering to the BIVAC design.

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.

Identification of an atypical monocyte and committed progenitor involved in fibrosis.

Monocytes and macrophages comprise a variety of subsets with diverse functions. It is thought that these cells play a crucial role in homeostasis of peripheral organs, key immunological processes and development of various diseases. Among these diseases, fibrosis is a life-threatening disease of unknown aetiology. Its pathogenesis is poorly understood, and there are few effective therapies. The development of fibrosis is associated with activation of monocytes and macrophages. However, the specific subtypes of monocytes and macrophages that are involved in fibrosis have not yet been identified. Here we show that Ceacam1+Msr1+Ly6C-F4/80-Mac1+ monocytes, which we term segregated-nucleus-containing atypical monocytes (SatM), share granulocyte characteristics, are regulated by CCAAT/enhancer binding protein ß (C/EBPß), and are critical for fibrosis. Cebpb deficiency results in a complete lack of SatM. Furthermore, the development of bleomycin-induced fibrosis, but not inflammation, was prevented in chimaeric mice with Cebpb-/- haematopoietic cells. Adoptive transfer of SatM into Cebpb-/- mice resulted in fibrosis. Notably, SatM are derived from Ly6C-FcεRI+ granulocyte/macrophage progenitors, and a newly identified SatM progenitor downstream of Ly6C-FcεRI+ granulocyte/macrophage progenitors, but not from macrophage/dendritic-cell progenitors. Our results show that SatM are critical for fibrosis and that C/EBPß licenses differentiation of SatM from their committed progenitor.

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.

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.

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).

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.

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.

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.

Infrequent HIV Infection of Circulating Monocytes during Antiretroviral Therapy.

Whereas human immunodeficiency virus (HIV) persists in tissue macrophages during antiretroviral therapy (ART), the role of circulating monocytes as HIV reservoirs remains controversial. Three magnetic bead selection methods and flow cytometry cell sorting were compared for their capacity to yield pure CD14+ monocyte populations. Cell sorting by flow cytometry provided the purest population of monocytes (median CD4+ T-cell contamination, 0.06%), and the levels of CD4+ T-cell contamination were positively correlated with the levels of integrated HIV DNA in the monocyte populations. Using cell sorting by flow cytometry, we assessed longitudinally the infection of monocytes and other cell subsets in a cohort of 29 Thai HIV-infected individuals. Low levels of HIV DNA were detected in a minority of monocyte fractions obtained before and after 1 year of ART (27% and 33%, respectively), whereas HIV DNA was readily detected in CD4+ T cells from all samples. Additional samples (2 to 5 years of ART) were obtained from 5 individuals in whom monocyte infection was previously detected. Whereas CD4+ T cells were infected at high levels at all time points, monocyte infection was inconsistent and absent in at least one longitudinal sample from 4/5 individuals. Our results indicate that infection of monocytes is infrequent and highlight the importance of using flow cytometry cell sorting to minimize contamination by CD4+ T cells.IMPORTANCE The role of circulating monocytes as persistent HIV reservoirs during ART is still controversial. Several studies have reported persistent infection of monocytes in virally suppressed individuals; however, others failed to detect HIV in this subset. These discrepancies are likely explained by the diversity of the methods used to isolate monocytes and to detect HIV infection. In this study, we show that only flow cytometry cell sorting yields a highly pure population of monocytes largely devoid of CD4 contaminants. Using this approach in a longitudinal cohort of HIV-infected individuals before and during ART, we demonstrate that HIV is rarely found in monocytes from untreated and treated HIV-infected individuals. This study highlights the importance of using methods that yield highly pure populations of cells as flow cytometry cell sorting to minimize and control for CD4+ T-cell contamination.

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.

Monocyte subsets responsible for immunoglobulin G-dependent effector functions in vivo.

Immunoglobulin G (IgG) antibodies confer protection against pathogenic microorganisms, serve as therapeutics in tumor therapy, and are involved in destruction of healthy tissues during autoimmune diseases. Understanding the molecular pathways and effector cell types involved in antibody-mediated effector functions is a prerequisite to modulate these activities. In this study we used two independent model systems to identify innate immune effector cells required for IgG activity in vivo. We first defined the precise repertoire of receptors for the IgG Fc fragment (FcγR) on innate immune effector cells in the blood and on tissue-resident macrophage populations. Despite expression of relevant activating FcγRs on various phagocyte populations, our data indicate that the majority of these cell types are dispensable for IgG activity in vivo. In contrast, IgG-dependent effector functions were selectively impaired in animals lacking the CX(3)CR1(hi)Ly6C(lo)CD11c(int) monocyte subset, which expressed the full set of FcγRs required for IgG activity.

Single-Cell RNA-Seq Reveals the Transcriptional Landscape and Heterogeneity of Aortic Macrophages in Murine Atherosclerosis.

RATIONALE: It is assumed that atherosclerotic arteries contain several macrophage subsets endowed with specific functions. The precise identity of these subsets is poorly characterized as they have been defined by the expression of a restricted number of markers. OBJECTIVE: We have applied single-cell RNA sequencing as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis. METHOD AND RESULTS: We performed single-cell RNA sequencing of total aortic CD45+ cells extracted from the nondiseased (chow fed) and atherosclerotic (11 weeks of high-fat diet) aorta of low-density lipoprotein receptor-deficient (Ldlr-/-) mice. Unsupervised clustering singled out 13 distinct aortic cell clusters. Among the myeloid cell populations, resident-like macrophages with a gene expression profile similar to aortic resident macrophages were found in healthy and diseased aortas, whereas monocytes, monocyte-derived dendritic cells, and 2 populations of macrophages were almost exclusively detectable in atherosclerotic aortas, comprising inflammatory macrophages showing enrichment in Il1b and previously undescribed TREM2hi (triggered receptor expressed on myeloid cells 2) macrophages showing enrichment in Trem2. Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these 3 macrophage subsets and monocyte-derived dendritic cells and uncovered putative functions of each cell type. Notably, TREM2hi macrophages seemed to be endowed with specialized functions in lipid metabolism and catabolism and presented a gene expression signature reminiscent of osteoclasts, suggesting a role in lesion calcification. TREM2 expression was moreover detected in human lesional macrophages. Importantly, these macrophage populations were present also in advanced atherosclerosis and in Apoe-/- aortas, indicating relevance of our findings in different stages of atherosclerosis and mouse models. CONCLUSIONS: These data unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and monocyte-derived dendritic cells in atherosclerotic and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions. Our findings will open up novel opportunities to explore distinct myeloid cell populations and their functions in atherosclerosis.

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.

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.

Mon2 predicts poor outcome in ST-elevation myocardial infarction.

AIMS: There are limited data on the role of human monocyte subsets in ST-elevation myocardial infarction (STEMI). The study aimed to establish the relationship between monocyte subsets, their phagocytic and nuclear factor κB (NFκB) activity and outcomes in STEMI. METHODS: Monocyte subsets and their phagocytic activity and intracellular levels of inhibitory κB kinase ß (IKKß, marker of NFκB activity) were measured by flow cytometry in 245 patients with STEMI, median follow-up of 46 months. RESULTS: Mon2 (CD14++CD16+CCR2+) counts were independently predictive of major adverse cardiovascular events (MACE) [4th quartile HR 3.42 (95% CI 1.43-8.16), P = 0.006 and 3rd quartile HR 2.88 (95% CI 1.19-7.00), P = 0.02 vs. 1st quartile]. Mon2 subset was the only subset associated with higher occurrence of heart failure (4th quartile vs. 1st quartile, sevenfold, P = 0.001 on univariate analysis; fivefold, P = 0.04 on multivariable analysis). On receiver operating characteristic, analysis including of Mon2 improved prognostic value of troponin T and creatine kinase for MACE and heart failure (HF). Higher intracellular Mon2 IKKß levels were associated with 10-fold lower occurrence of HF on multivariable analysis (4th vs. 1st quartiles, P = 0.03). Abnormal Mon1 and Mon2 phagocytic capacities were related to HF development, but the association was dependent on the infarct size and other prognosticators. High Mon2 levels were associated with lower ejection fraction after STEMI onset (P = 0.001) and at 6-month follow-up (P < 0.001). CONCLUSIONS: Abnormal Mon2 characteristics have a unique association with poor outcome in patients with STEMI. The relation of Mon2 with occurrence of HF is strongly and independently related to their functional status, which may have potential therapeutic implications.

Human Monocyte Subsets Are Transcriptionally and Functionally Altered in Aging in Response to Pattern Recognition Receptor Agonists.

Age-related alterations in immunity have been linked to increased incidence of infections and decreased responses to vaccines in the aging population. Human peripheral blood monocytes are known to promote Ag presentation and antiviral activities; however, the impact of aging on monocyte functions remains an open question. We present an in-depth global analysis examining the impact of aging on classical (CD14+CD16-), intermediate (CD14+CD16+), and nonclassical (CD14dimCD16+) monocytes. Monocytes sorted from nonfrail healthy adults (21-40 y) and old (≥65 y) individuals were analyzed after stimulation with TLR4, TLR7/8, and retinoic acid-inducible gene I agonists. Our data showed that under nonstimulated conditions, monocyte subsets did not reveal significant age-related alternations; however, agonist stimulated-monocytes from adults and old subjects did show differences at the transcriptional and functional levels. These alternations in many immune-related transcripts and biological processes resulted in reduced production of IFN-α, IFN-γ, IL-1ß, CCL20, and CCL8, and higher expression of CX3CR1 in monocytes from old subjects. Our findings represent a comprehensive analysis of the influence of human aging on pattern recognition receptors signaling and monocyte functions, and have implications for strategies to enhance the immune response in the context of infection and immunization.

Monocyte Conversion During Inflammation and Injury.

Monocytes are circulating leukocytes important in both innate and adaptive immunity, primarily functioning in immune defense, inflammation, and tissue remodeling. There are 2 subsets of monocytes in mice (3 subsets in humans) that are mobilized from the bone marrow and recruited to sites of inflammation, where they carry out their respective functions in promoting inflammation or facilitating tissue repair. Our understanding of the fate of these monocyte subsets at the site of inflammation is constantly evolving. This brief review highlights the plasticity of monocyte subsets and their conversion during inflammation and injury.

Human Blood Monocyte Subsets: A New Gating Strategy Defined Using Cell Surface Markers Identified by Mass Cytometry.

OBJECTIVE: Human monocyte subsets are defined as classical (CD14++CD16-), intermediate (CD14++CD16+), and nonclassical (CD14+CD16+). Alterations in monocyte subset frequencies are associated with clinical outcomes, including cardiovascular disease, in which circulating intermediate monocytes independently predict cardiovascular events. However, delineating mechanisms of monocyte function is hampered by inconsistent results among studies. APPROACH AND RESULTS: We use cytometry by time-of-flight mass cytometry to profile human monocytes using a panel of 36 cell surface markers. Using the dimensionality reduction approach visual interactive stochastic neighbor embedding (viSNE), we define monocytes by incorporating all cell surface markers simultaneously. Using viSNE, we find that although classical monocytes are defined with high purity using CD14 and CD16, intermediate and nonclassical monocytes defined using CD14 and CD16 alone are frequently contaminated, with average intermediate and nonclassical monocyte purity of ≈86.0% and 87.2%, respectively. To improve the monocyte purity, we devised a new gating scheme that takes advantage of the shared coexpression of cell surface markers on each subset. In addition to CD14 and CD16, CCR2, CD36, HLA-DR, and CD11c are the most informative markers that discriminate among the 3 monocyte populations. Using these additional markers as filters, our revised gating scheme increases the purity of both intermediate and nonclassical monocyte subsets to 98.8% and 99.1%, respectively. We demonstrate the use of this new gating scheme using conventional flow cytometry of peripheral blood mononuclear cells from subjects with cardiovascular disease. CONCLUSIONS: Using cytometry by time-of-flight mass cytometry, we have identified a small panel of surface markers that can significantly improve monocyte subset identification and purity in flow cytometry. Such a revised gating scheme will be useful for clinical studies of monocyte function in human cardiovascular disease.

Frequency of circulating CD14++ CD16+ intermediate monocytes as potential biomarker for the diagnosis of oral squamous cell carcinoma.

BACKGROUND: Monocytes, which subdivided into three functional subsets (classical, intermediate, and nonclassical), play important roles in the progression of cancer. The subset composition is altered in several pathologic conditions including cancers. However, the composition and function of circulating monocyte subsets in patients with oral squamous cell carcinoma (OSCC) are still obscure. METHODS: The frequencies of monocyte subsets in peripheral blood of patients with OSCC and healthy donors are determined by flow cytometry, and their diagnostic values for OSCC were evaluated. The associations between levels of monocyte subsets and clinicopathological features of patients with OSCC were analyzed using cross-tabulation with the chi-square test. RESULTS: We demonstrated that the frequency of CD14++ CD16+ intermediate monocytes was remarkably increased (P < 0.0001) in OSCC patients compared with healthy controls (7.33% ± 2.56% of total monocytes, n = 68 versus 4.78% ± 1.50% of total monocytes, n = 57). A trend of decrease in CD14++ CD16- classical subset was observed between these two groups (P = 0.0508), whereas no significant difference was detected in CD14+ CD16++ nonclassical subset (P > 0.05). The receiver operating characteristic (ROC) curve analysis indicated that the frequency of intermediate monocytes (AUC = 0.810, P < 0.0001) could be a potential diagnostic biomarker to discriminate patients with OSCC from healthy subjects. Moreover, this parameter was significantly correlated to the worst pattern of invasion (WPOI, P < 0.05) of OSCC tissues. CONCLUSIONS: Detection of monocyte subsets in peripheral blood sheds a light on utilizing the frequency of intermediate monocytes as a potential diagnostic biomarker for OSCC.