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Deep-immunophenotyping of the circulatory T cell compartment using mass cytometry and unsupervised clustering analysis, identifies phenotypic and functional differences in patients with atopic dermatitis (AD) and psoriasis, highlighting the stronger systemic component associated with AD.

Manual gating has been traditionally applied to cytometry data sets to identify cells based on protein expression. The advent of mass cytometry allows for a higher number of proteins to be simultaneously measured on cells, therefore providing a means to define cell clusters in a high dimensional expression space. This enhancement, whilst opening unprecedented opportunities for single cell-level analyses, makes the incremental replacement of manual gating with automated clustering a compelling need. To this aim many methods have been implemented and their successful applications demonstrated in different settings. However, the reproducibility of automatically generated clusters is proving challenging and an analytical framework to distinguish spurious clusters from more stable entities, and presumably more biologically relevant ones, is still missing. One way to estimate cell clusters' stability is the evaluation of their consistent re-occurrence within- and between-algorithms, a metric that is commonly used to evaluate results from gene expression. Herein we report the usage and importance of cluster stability evaluations, when applied to results generated from three popular clustering algorithms - SPADE, FLOCK and PhenoGraph - run on four different data sets. These algorithms were shown to generate clusters with various degrees of statistical stability, many of them being unstable. By comparing the results of automated clustering with manually gated populations, we illustrate how information on cluster stability can assist towards a more rigorous and informed interpretation of clustering results. We also explore the relationships between statistical stability and other properties such as clusters' compactness and isolation, demonstrating that whilst cluster stability is linked to other properties it cannot be reliably predicted by any of them. Our study proposes the introduction of cluster stability as a necessary checkpoint for cluster interpretation and contributes to the construction of a more systematic and standardized analytical framework for the assessment of cytometry clustering results. © 2016 International Society for Advancement of Cytometry.

In type 1 diabetes, cytotoxic CD8+ T cells with specificity for β cell autoantigens are found in the pancreatic islets, where they are implicated in the destruction of insulin-secreting β cells. In contrast, the disease relevance of β cell-reactive CD8+ T cells that are detectable in the circulation, and their relationship to β cell function, are not known. Here, we tracked multiple, circulating β cell-reactive CD8+ T cell subsets and measured β cell function longitudinally for 2 years, starting immediately after diagnosis of type 1 diabetes. We found that change in β cell-specific effector memory CD8+ T cells expressing CD57 was positively correlated with C-peptide change in subjects below 12 years of age. Autoreactive CD57+ effector memory CD8+ T cells bore the signature of enhanced effector function (higher expression of granzyme B, killer-specific protein of 37 kDa, and CD16, and reduced expression of CD28) compared with their CD57-counterparts, and network association modeling indicated that the dynamics of β cell-reactive CD57+ effector memory CD8+ T cell subsets were strongly linked. Thus, coordinated changes in circulating β cell-specific CD8+ T cells within the CD57+ effector memory subset calibrate to functional insulin reserve in type 1 diabetes, providing a tool for immune monitoring and a mechanism-based target for immunotherapy.

In this paper, the candidate gene discriminating gliomas identification via a supervised iteration of bipartitive k-mean is presented. Gliomas are supervisedly discriminated by identifying, via iterative bipartitive division according to principal directions initializing k-means, salient genes able to cluster representative patients, thus also giving an insight about degrees of epigenetic similarity among different kinds of gliomas.

Background Expression quantitative trait loci (eQTL) databases represent a valuable resource to link disease-associated SNPs to specific candidate genes whose gene expression is significantly modulated by the SNP under investigation. We previously identified signal inhibitory receptor on leukocytes-1 (SIRL-1) as a powerful regulator of human innate immune cell function. While it is constitutively high expressed on neutrophils, on monocytes the SIRL-1 surface expression varies strongly between individuals. The underlying mechanism of regulation, its genetic control as well as potential clinical implications had not been explored yet. Methods Whole blood eQTL data of a Chinese cohort was used to identify SNPs regulating the expression of VSTM1, the gene encoding SIRL-1. The genotype effect was validated by flow cytometry (cell surface expression), correlated with electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP) and bisulfite sequencing (C-methylation) and its functional impact studied the inhibition of reactive oxygen species (ROS). Results We found a significant association of a single CpG-SNP, rs612529T/C, located in the promoter of VSTM1. Through flow cytometry analysis we confirmed that primarily in the monocytes the protein level of SIRL-1 is strongly associated with genotype of this SNP. In monocytes, the T allele of this SNP facilitates binding of the transcription factors YY1 and PU.1, of which the latter has been recently shown to act as docking site for modifiers of DNA methylation. In line with this notion rs612529T associates with a complete demethylation of the VSTM1 promoter correlating with the allele-specific upregulation of SIRL-1 expression. In monocytes, this upregulation strongly impacts the IgA-induced production of ROS by these cells. Through targeted association analysis we found a significant Meta P value of 1.14 × 10–6 for rs612529 for association to atopic dermatitis (AD). Conclusion Low expression of SIRL-1 on monocytes is associated with an increased risk for the manifestation of an inflammatory skin disease. It thus underlines the role of both the cell subset and this inhibitory immune receptor in maintaining immune homeostasis in the skin. Notably, the genetic regulation is achieved by a single CpG-SNP, which controls the overall methylation state of the promoter gene segment. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0404-6) contains supplementary material, which is available to authorized users.

Idiopathic aplastic anemia (AA) is an immune-mediated and serious form of bone marrow failure. Akin to other autoimmune diseases, we have previously shown that in AA regulatory T-cells (Tregs) are reduced in number and function. The aim of this study was to further characterize Treg subpopulations in AA and investigate the potential correlation between specific Treg subsets and response to immunosuppressive therapy (IST) as well as their in-vitro expandability for potential clinical use. Using mass cytometry (CyTOF) and an unbiased multidimensional analytical approach, we identified two specific human Treg subpopulations (Treg A and Treg B) with distinct phenotypes, gene-expression, expandability and function. Treg subpopulation B, predominates in IST responder patients, has a memory/activated phenotype (with higher expression of CD95, CCR4 and CD45RO within FOXP3hi, CD127lo Tregs), expresses the IL- 2/STAT5 pathway and cell-cycle commitment genes. Furthermore, in-vitro expanded Tregs become functional and with the characteristics of Treg subpopulation B. Collectively, this study identifies human Treg subpopulations that can be used as predictive biomarkers for response to IST in AA and potentially other autoimmune diseases. We also show that Tregs from AA patients are IL-2 sensitive and expandable in-vitro, suggesting novel therapeutic approaches such as low dose IL-2 therapy and/or expanded autologous Tregs and meriting further exploration.

Manual gating has been traditionally applied to cytometry data sets to identify cells based on protein expression. The advent of mass cytometry allows for a higher number of proteins to be simultaneously measured on cells, therefore providing a means to define cell clusters in a high dimensional expression space. This enhancement, whilst opening unprecedented opportunities for single cell-level analyses, makes the incremental replacement of manual gating with automated clustering a compelling need. To this aim many methods have been implemented and their successful applications demonstrated in different settings. However, the reproducibility of automatically generated clusters is proving challenging and an analytical framework to distinguish spurious clusters from more stable entities, and presumably more biologically relevant ones, is still missing. One way to estimate cell clusters' stability is the evaluation of their consistent re-occurrence within- and between-algorithms, a metric that is commonly used to evaluate results from gene expression. Herein we report the usage and importance of cluster stability evaluations, when applied to results generated from three popular clustering algorithms - SPADE, FLOCK and PhenoGraph - run on four different data sets. These algorithms were shown to generate clusters with various degrees of statistical stability, many of them being unstable. By comparing the results of automated clustering with manually gated populations, we illustrate how information on cluster stability can assist towards a more rigorous and informed interpretation of clustering results. We also explore the relationships between statistical stability and other properties such as clusters' compactness and isolation, demonstrating that whilst cluster stability is linked to other properties it cannot be reliably predicted by any of them. Our study proposes the introduction of cluster stability as a necessary checkpoint for cluster interpretation and contributes to the construction of a more systematic and standardized analytical framework for the assessment of cytometry clustering results. © 2016 International Society for Advancement of Cytometry.

Neutrophils are an abundant immune cell type involved in both antimicrobial defence and autoimmunity. The regulation of their gene expression, however, is still largely unknown. Here we report an eQTL study on isolated neutrophils from 114 healthy individuals of Chinese ethnicity, identifying 21,210 eQTLs on 832 unique genes. Unsupervised clustering analysis of these eQTLs confirms their role in inflammatory responses and immunological diseases but also indicates strong involvement in dermatological pathologies. One of the strongest eQTL identified (rs2058660) is also the tagSNP of a linkage block reported to affect leprosy and Crohn's disease in opposite directions. In a functional study, we can link the C allele with low expression of the β-chain of IL18-receptor (IL18RAP). In neutrophils, this results in a reduced responsiveness to IL-18, detected both on the RNA and protein level. Thus, the polymorphic regulation of human neutrophils can impact beneficial as well as pathological inflammatory responses., Neutrophils are abundant immune cells important for antimicrobial defence and in autoimmunity. Here, by mapping expression quantitative trait loci (eQTL) in neutrophils of Chinese ethnicity from Singapore, Andiappan et al. provide a resource for understanding immune-related trait associated genetic variants.

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus., Author Summary Many variants in the genome, including variants associated with disease, affect the expression of genes. These so-called expression quantitative trait loci (eQTL) can be used to gain insight in the downstream consequences of disease. While it has been shown that many disease-associated variants alter gene expression in a cell-type dependent manner, eQTL datasets for specific cell types may not always be available and their sample size is often limited. We present a method that is able to detect cell type specific effects within eQTL datasets that have been generated from whole tissues (which may be composed of many cell types), in our case whole blood. By combining numerous whole blood datasets through meta-analysis, we show that we are able to detect eQTL effects that are specific for neutrophils and lymphocytes (two blood cell types). Additionally, we show that the variants associated with some diseases may preferentially alter the gene expression in one of these cell types. We conclude that our method is an alternative method to detect cell type specific eQTL effects, that may complement generating cell type specific eQTL datasets and that may be applied on other cell types and tissues as well.

Regulatory T cells (Tregs) are an essential component of the cellular immune response, occupying a key role in maintaining immunological tolerance and present an attractive therapeutic target in a range of immunopathologies. Comprehensive analysis of the human Treg compartment has been restricted due to technical limitations. The advent of mass cytometry enables simultaneous assessment of vastly increased phenotypic parameters at single-cell resolution. In this study, we used mass cytometry to examine the complexity of human Tregs using an extensive panel of surface markers associated with Treg function and phenotype. We applied unsupervised clustering analysis, revealing 22 distinct subpopulations of Tregs, representing previously identified and novel subpopulations. Our data represent the most in-depth phenotypic description of the human Treg compartment at single-cell resolution and show a hitherto unrecognized degree of phenotypic complexity among cells of the regulatory lineage.

Expression quantitative trait locus (eQTL) mapping on tissue, organ or whole organism data can detect associations that are generic across cell types. We describe a new method to focus upon specific cell types without first needing to sort cells. We applied the method to whole blood data from 5,683 samples and demonstrate that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils.

Background Extracellular ATP is a pro-inflammatory molecule released by damaged cells. Regulatory T cells (Treg) can suppress inflammation by hydrolysing this molecule via ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1), also termed as CD39. Multiple studies have reported differences in CD39+ Treg percentages in diseases such as multiple sclerosis, Hepatitis B and HIV-1. In addition, CD39 polymorphisms have been implicated in immune-phenotypes such as susceptibility to inflammatory bowel disease and AIDS progression. However none of the studies published so far has linked disease-associated variants with differences in CD39 Treg surface expression. This study aims at identifying variants affecting CD39 expression on Treg and at evaluating their association with allergic rhinitis, a disease characterized by a strong Treg involvement. Methods Cohorts consisting of individuals of different ethnicities were employed to identify any association of CD39 variants to surface expression. Significant variant(s) were tested for disease association in a published GWAS cohort by one-locus and two-locus genetic analyses based on logistic models. Further functional characterization was performed using existing microarray data and quantitative RT-PCR on sorted cells. Results Our study shows that rs7071836, a promoter SNP in the CD39 gene region, affects the cell surface expression on Treg cells but not on other CD39+ leukocyte subsets. Epistasis analysis revealed that, in conjunction with a SNP upstream of the FAM134B gene (rs257174), it increased the risk of allergic rhinitis (P = 1.98 × 10-6). As a promoter SNP, rs257174 controlled the expression of the gene in monocytes but, notably, not in Treg cells. Whole blood transcriptome data of three large cohorts indicated an inverse relation in the expression of the two proteins. While this observation was in line with the epistasis data, it also implied that a functional link must exist. Exposure of monocytes to extracellular ATP resulted in an up-regulation of FAM134B gene expression, suggesting that extracellular ATP released from damaged cells represents the connection for the biological interaction of CD39 on Treg cells with FAM134B on monocytes. Conclusions The interplay between promoter SNPs of CD39 and FAM134B results in an intercellular epistasis which influences the risk of a complex inflammatory disease.