Eoin F. McKinney

A CD8+ T cell transcription signature predicts prognosis in autoimmune disease

Autoimmune diseases are common and debilitating, but their severe manifestations could be reduced if biomarkers were available to allow individual tailoring of potentially toxic immunosuppressive therapy. Gene expression–based biomarkers facilitating such tailoring of chemotherapy in cancer, but not autoimmunity, have been identified and translated into clinical practice. We show that transcriptional profiling of purified CD8+ T cells, which avoids the confounding influences of unseparated cells, identifies two distinct subject subgroups predicting long-term prognosis in two autoimmune diseases, antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), a chronic, severe disease characterized by inflammation of medium-sized and small blood vessels, and systemic lupus erythematosus (SLE), characterized by autoantibodies, immune complex deposition and diverse clinical manifestations ranging from glomerulonephritis to neurological dysfunction. We show that the subset of genes defining the poor prognostic group is enriched for genes involved in the interleukin-7 receptor (IL-7R) pathway and T cell receptor (TCR) signaling and those expressed by memory T cells. Furthermore, the poor prognostic group is associated with an expanded CD8+ T cell memory population. These subgroups, which are also found in the normal population and can be identified by measuring expression of only three genes, raise the prospect of individualized therapy and suggest new potential therapeutic targets in autoimmunity.

T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection

The clinical course of autoimmune and infectious disease varies greatly, even between individuals with the same condition. An understanding of the molecular basis for this heterogeneity could lead to significant improvements in both monitoring and treatment. During chronic infection the process of T-cell exhaustion inhibits the immune response, facilitating viral persistence. Here we show that a transcriptional signature reflecting CD8 T-cell exhaustion is associated with poor clearance of chronic viral infection, but conversely predicts better prognosis in multiple autoimmune diseases. The development of CD8 T-cell exhaustion during chronic infection is driven both by persistence of antigen and by a lack of accessory ‘help’ signals. In autoimmunity, we find that where evidence of CD4 T-cell co-stimulation is pronounced, that of CD8 T-cell exhaustion is reduced. We can reproduce the exhaustion signature by modifying the balance of persistent stimulation of T-cell antigen receptors and specific CD2-induced co-stimulation provided to human CD8 T cells in vitro, suggesting that each process plays a role in dictating outcome in autoimmune disease. The ‘non-exhausted’ T-cell state driven by CD2-induced co-stimulation is reduced by signals through the exhaustion-associated inhibitory receptor PD-1, suggesting that induction of exhaustion may be a therapeutic strategy in autoimmune and inflammatory disease. Using expression of optimal surrogate markers of co-stimulation/exhaustion signatures in independent data sets, we confirm an association with good clinical outcome or response to therapy in infection (hepatitis C virus) and vaccination (yellow fever, malaria, influenza), but poor outcome in autoimmune and inflammatory disease (type 1 diabetes, anti-neutrophil cytoplasmic antibody-associated vasculitis, systemic lupus erythematosus, idiopathic pulmonary fibrosis and dengue haemorrhagic fever). Thus, T-cell exhaustion plays a central role in determining outcome in autoimmune disease and targeted manipulation of this process could lead to new therapeutic opportunities.

Gene expression profiling of CD8+ T cells predicts prognosis in patients with Crohn disease and ulcerative colitis

Crohn disease (CD) and ulcerative colitis (UC) are increasingly common, chronic forms of inflammatory bowel disease. The behavior of these diseases varies unpredictably among patients. Identification of reliable prognostic biomarkers would enable treatment to be personalized so that patients destined to experience aggressive disease could receive appropriately potent therapies from diagnosis, while those who will experience more indolent disease are not exposed to the risks and side effects of unnecessary immunosuppression. Using transcriptional profiling of circulating T cells isolated from patients with CD and UC, we identified analogous CD8+ T cell transcriptional signatures that divided patients into 2 otherwise indistinguishable subgroups. In both UC and CD, patients in these subgroups subsequently experienced very different disease courses. A substantially higher incidence of frequently relapsing disease was experienced by those patients in the subgroup defined by elevated expression of genes involved in antigen-dependent T cell responses, including signaling initiated by both IL-7 and TCR ligation - pathways previously associated with prognosis in unrelated autoimmune diseases. No equivalent correlation was observed with CD4+ T cell gene expression. This suggests that the course of otherwise distinct autoimmune and inflammatory conditions may be influenced by common pathways and identifies what we believe to be the first biomarker that can predict prognosis in both UC and CD from diagnosis, a major step toward personalized therapy.

A type I interferon transcriptional signature precedes autoimmunity in children genetically at risk for type 1 diabetes.

Diagnosis of the autoimmune disease type 1 diabetes (T1D) is preceded by the appearance of circulating autoantibodies to pancreatic islets. However, almost nothing is known about events leading to this islet autoimmunity. Previous epidemiological and genetic data have associated viral infections and antiviral type I interferon (IFN) immune response genes with T1D. Here, we first used DNA microarray analysis to identify IFN-β–inducible genes in vitro and then used this set of genes to define an IFN-inducible transcriptional signature in peripheral blood mononuclear cells from a group of active systemic lupus erythematosus patients (n = 25). Using this predefined set of 225 IFN signature genes, we investigated the expression of the signature in cohorts of healthy controls (n = 87), patients with T1D (n = 64), and a large longitudinal birth cohort of children genetically predisposed to T1D (n = 109; 454 microarrayed samples). Expression of the IFN signature was increased in genetically predisposed children before the development of autoantibodies (P = 0.0012) but not in patients with established T1D. Upregulation of IFN-inducible genes was transient, temporally associated with a recent history of upper respiratory tract infections (P = 0.0064), and marked by increased expression of SIGLEC-1 (CD169), a lectin-like receptor expressed on CD14+ monocytes. DNA variation in IFN-inducible genes altered T1D risk (P = 0.007), as exemplified by IFIH1, one of the genes in our IFN signature for which increased expression is a known risk factor for disease. These findings identify transient increased expression of type I IFN genes in preclinical diabetes as a risk factor for autoimmunity in children with a genetic predisposition to T1D.

High Prevalence of Autoantibodies to hLAMP-2 in Anti–Neutrophil Cytoplasmic Antibody–Associated Vasculitis

The involvement of autoantibodies to human lysosome-associated membrane protein-2 (hLAMP-2) in anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is controversial because of the absence of confirmatory data subsequent to the initial reports of their high prevalence in this disease. We characterized three assays for anti-hLAMP-2 antibodies: ELISA and Western blotting assays using unglycosylated recombinant hLAMP-2 expressed in Escherichia coli, and an indirect immunofluorescence assay using stably transfected ldlD cells that expressed glycosylated full-length hLAMP-2 on the plasma membrane. The assays detected autoantibodies to hLAMP-2 in human sera reproducibly and with comparable sensitivity and the assays gave the same results in 80.5% of the test panel of 40 selected positive and negative sera. In untreated patients at presentation, the frequencies of autoantibodies to LAMP-2 were 89%, 91%, and 80%, respectively, among three groups of patients with ANCA-associated vasculitis from Vienna, Austria (n=19); Groningen, the Netherlands (n=50) and Cambridge, United Kingdom (n=53). Prevalence of LAMP-2 autoantibodies was similar in both those with myeloperoxidase-ANCA and proteinase 3-ANCA. Furthermore, we detected LAMP-2 autoantibodies in two ANCA-negative patients. LAMP-2 autoantibodies rapidly became undetectable after the initiation of immunosuppressive treatment and frequently became detectable again during clinical relapse. We conclude that when robust assays are used, circulating autoantibodies to hLAMP-2 can be detected in most European patients with ANCA-associated vasculitis. Large-scale prospective studies are now needed to determine whether they are pathogenic or merely an epiphenomenon.

Novel expression signatures identified by transcriptional analysis of separated leucocyte subsets in systemic lupus erythematosus and vasculitis

Objective To optimise a strategy for identifying gene expression signatures differentiating systemic lupus erythematosus (SLE) and antineutrophil cytoplasmic antibody-associated vasculitis that provide insight into disease pathogenesis and identify biomarkers. Methods 44 vasculitis patients, 13 SLE patients and 25 age and sex-matched controls were enrolled. CD4 and CD8 T cells, B cells, monocytes and neutrophils were isolated from each patient and, together with unseparated peripheral blood mononuclear cells (PBMC), were hybridised to spotted oligonucleotide microarrays. Results Using expression data obtained from purified cells a substantial number of differentially expressed genes were identified that were not detectable in the analysis of PBMC. Analysis of purified T cells identified a SLE-associated, CD4 T-cell signature consistent with type 1 interferon signalling driving the generation and survival of tissue homing T cells and thereby contributing to disease pathogenesis. Moreover, hierarchical clustering using expression data from purified monocytes provided significantly improved discrimination between the patient groups than that obtained using PBMC data, presumably because the differentially expressed genes reflect genuine differences in processes underlying disease pathogenesis. Conclusion Analysis of leucocyte subsets enabled the identification of gene signatures of both pathogenic relevance and with better disease discrimination than those identified in PBMC. This approach thus provides substantial advantages in the search for diagnostic and prognostic biomarkers in autoimmune disease.

Transcript Analysis Reveals a Specific HOX Signature Associated with Positional Identity of Human Endothelial Cells

The endothelial cell has a remarkable ability for sub-specialisation, adapted to the needs of a variety of vascular beds. The role of developmental programming versus the tissue contextual environment for this specialization is not well understood. Here we describe a hierarchy of expression of HOX genes associated with endothelial cell origin and location. In initial microarray studies, differential gene expression was examined in two endothelial cell lines: blood derived outgrowth endothelial cells (BOECs) and pulmonary artery endothelial cells. This suggested shared and differential patterns of HOX gene expression between the two endothelial lines. For example, this included a cluster on chromosome 2 of HOXD1, HOXD3, HOXD4, HOXD8 and HOXD9 that was expressed at a higher level in BOECs. Quantative PCR confirmed the higher expression of these HOXs in BOECs, a pattern that was shared by a variety of microvascular endothelial cell lines. Subsequently, we analysed publically available microarrays from a variety of adult cell and tissue types using the whole “HOX transcriptome” of all 39 HOX genes. Using hierarchical clustering analysis the HOX transcriptome was able to discriminate endothelial cells from 61 diverse human cell lines of various origins. In a separate publically available microarray dataset of 53 human endothelial cell lines, the HOX transcriptome additionally organized endothelial cells related to their organ or tissue of origin. Human tissue staining for HOXD8 and HOXD9 confirmed endothelial expression and also supported increased microvascular expression of these HOXs. Together these observations suggest a significant involvement of HOX genes in endothelial cell positional identity.

The immunopathology of ANCA-associated vasculitis.

The small-vessel vasculitides are a group of disorders characterised by variable patterns of small blood vessel inflammation producing a markedly heterogeneous clinical phenotype. While any vessel in any organ may be involved, distinct but often overlapping sets of clinical features have allowed the description of three subtypes associated with the presence of circulating anti-neutrophil cytoplasmic antibodies (ANCA), namely granulomatosis with polyangiitis (GPA, formerly known as Wegener’s Granulomatosis), microscopic polyangiitis (MPA) and eosinophilic granulomatosis with polyangiitis (eGPA, formerly known as Churg-Strauss syndrome). Together, these conditions are called the ANCA-associated vasculitidies (AAV). Both formal nomenclature and classification criteria for the syndromes have changed repeatedly since their description over 100 years ago and may conceivably do so again following recent reports showing distinct genetic associations of patients with detectable ANCA of distinct specificities. ANCA are not only useful in classifying the syndromes but substantial evidence implicates them in driving disease pathogenesis although the mechanism by which they develop and tolerance is broken remains controversial. Advances in our understanding of the pathogenesis of the syndromes have been accompanied by some progress in treatment, although much remains to be done to improve the chronic morbidity associated with the immunosuppression required for disease control.

Lipid Anti-Lipid Antibody Responses Correlate with Disease Activity in Systemic Lupus Erythematosus

Systemic Lupus Erythematosus (SLE) is a chronic autoimmune disorder characterized by broad clinical manifestations including cardiovascular and renal complications with periodic disease flares and significant morbidity and mortality. One of the main contributing factors to the pathology of SLE is the accumulation and impaired clearance of immune complexes of which the principle components are host auto-antigens and antibodies. The contribution of host lipids to the formation of these autoimmune complexes remains poorly defined. The aim of the present study was to identify and analyze candidate lipid autoantigens and their corresponding anti–lipid antibody responses in a well-defined SLE patient cohort using a combination of immunological and biophysical techniques. Disease monitoring in the SLE cohort was undertaken with serial British Isles Lupus Assessment Group (BILAG) scoring. Correlations between specific lipid/anti-lipid responses were investigated as disease activity developed from active flares to quiescent during a follow up period. We report a significant negative correlation between anti-lipid antibodies for 24S-hydroxycholesterol, cardiolipin and phosphatidylserine with SLE disease activity. Taken together, these data suggest that lipid autoantigens represent a new family of biomarkers that can be employed to monitor disease activity plus the efficacy of therapeutic intervention in SLE.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation

BackgroundAlthough numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study.ResultsUsing a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this “gold-standard” comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues.ConclusionsMicroarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.