Marc Jacobsen

A point mutation in PTPRC is associated with the development of multiple sclerosis

Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system. It is widely accepted that a dysregulated immune response against brain resident antigens is central to its yet unknown pathogenesis. Although there is evidence that the development of MS has a genetic component, specific genetic factors are largely unknown. Here we investigated the role of a point mutation in the gene (PTPRC) encoding protein-tyrosine phosphatase, receptor-type C (also known as CD45) in the heterozygous state in the development of MS. The nucleotide transition in exon 4 of the gene locus interferes with mRNA splicing and results in altered expression of CD45 isoforms on immune cells. In three of four independent case-control studies, we demonstrated an association of the mutation with MS. We found the PTPRC mutation to be linked to and associated with the disease in three MS nuclear families. In one additional family, we found the same variant CD45 phenotype, with an as-yet-unknown origin, among the members affected with MS. Our findings suggest an association of the mutation in PTPRC with the development of MS in some families.

Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis.

Infection with Mycobacterium tuberculosis is controlled by an efficacious immune response in about 90% of infected individuals who do not develop disease. Although essential mediators of protection, e.g., interferon-γ, have been identified, these factors are insufficient to predict the outcome of M. tuberculosis infection. As a first step to determine additional biomarkers, we compared gene expression profiles of peripheral blood mononuclear cells from tuberculosis patients and M. tuberculosis-infected healthy donors by microarray analysis. Differentially expressed candidate genes were predominantly derived from monocytes and comprised molecules involved in the antimicrobial defense, inflammation, chemotaxis, and intracellular trafficking. We verified differential expression for alpha-defensin 1, alpha-defensin 4, lactoferrin, Fcγ receptor 1A (cluster of differentiation 64 [CD64]), bactericidal permeability-increasing protein, and formyl peptide receptor 1 by quantitative polymerase chain reaction analysis. Moreover, we identified increased protein expression of CD64 on monocytes from tuberculosis patients. Candidate biomarkers were then assessed for optimal study group discrimination. Using a linear discriminant analysis, a minimal group of genes comprising lactoferrin, CD64, and the Ras-associated GTPase 33A was sufficient for classification of (1) tuberculosis patients, (2) M. tuberculosis-infected healthy donors, and (3) noninfected healthy donors.

Identification of T-Cell Antigens Specific for Latent Mycobacterium Tuberculosis Infection

Background T-cell responses against dormancy-, resuscitation-, and reactivation-associated antigens of Mycobacterium tuberculosis are candidate biomarkers of latent infection in humans. Methodology/Principal Findings We established an assay based on two rounds of in vitro restimulation and intracellular cytokine analysis that detects T-cell responses to antigens expressed during latent M. tuberculosis infection. Comparison between active pulmonary tuberculosis (TB) patients and healthy latently M. tuberculosis-infected donors (LTBI) revealed significantly higher T-cell responses against 7 of 35 tested M. tuberculosis latency-associated antigens in LTBI. Notably, T cells specific for Rv3407 were exclusively detected in LTBI but not in TB patients. The T-cell IFNγ response against Rv3407 in individual donors was the most influential factor in discrimination analysis that classified TB patients and LTBI with 83% accuracy using cross-validation. Rv3407 peptide pool stimulations revealed distinct candidate epitopes in four LTBI. Conclusions Our findings further support the hypothesis that the latency-associated antigens can be exploited as biomarkers for LTBI.

Identification of biomarkers for tuberculosis disease using a novel dual-color RT-MLPA assay

Owing to our lack of understanding of the factors that constitute protective immunity during natural infection with Mycobacterium tuberculosis (Mtb), there is an urgent need to identify host biomarkers that predict long-term outcome of infection in the absence of therapy. Moreover, the identification of host biomarkers that predict (in)adequate response to tuberculosis (TB) treatment would similarly be a major step forward. To identify/monitor multi-component host biomarker signatures at the transcriptomic level in large human cohort studies, we have developed and validated a dual-color reverse-transcriptase multiplex ligation-dependent probe amplification (dcRT–MLPA) method, permitting rapid and accurate expression profiling of as many as 60–80 transcripts in a single reaction. dcRT–MLPA is sensitive, highly reproducible, high-throughput, has an extensive dynamic range and is as quantitative as QPCR. We have used dcRT–MLPA to characterize the human immune response to Mtb in several cohort studies in two genetically and geographically diverse populations. A biomarker signature was identified that is strongly associated with active TB disease, and was profoundly distinct from that associated with treated TB disease, latent infection or uninfected controls, demonstrating the discriminating power of our biomarker signature. Identified biomarkers included apoptosis-related genes and T-cell/B-cell markers, suggesting important contributions of adaptive immunity to TB pathogenesis.

Mycobacterium tuberculosis-specific CD4+, IFNγ+, and TNFα+ multifunctional memory T cells coexpress GM-CSF

Multifunctional T cells expressing several cytokines in parallel are thought to play a crucial role in protection against different infections. To characterize T cell cytokine patterns associated with disease and protection in Mycobacterium tuberculosis infection we determined the expression of IFNgamma, IL-2, TNFalpha, and GM-CSF in T cell subpopulations from children with tuberculosis (TB) and healthy latently M. tuberculosis-infected children (LTBI) after short-term in vitro restimulation. We identified CD4(+) effector memory T cells (T(EM)) as the major source of all measured cytokines after antigen-specific restimulation. T(EM) from children with TB expressed higher proportions of IFNgamma, TNFalpha, and IL-2 after Mtb restimulation while no differences were detected for GM-CSF between both study groups. GM-CSF secretion strongly depended on antigen-specific stimulation. Analyses of multiple cytokine patterns revealed that the majority of GM-CSF-positive M. tuberculosis-specific memory T cells coexpressed IFNgamma and TNFalpha therefore showing a characteristic feature of multifunctional T cells. We conclude that children with active TB possess higher proportions of IFNgamma-, TNFalpha-, and/or IL-2-positive T(EM) than children with LTBI while GM-CSF coexpression reveals a novel subpopulation within CD4(+) memory T cells not increased in children with active TB.

Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

BackgroundFor heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.ResultsExperimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach.Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.ConclusionsThe deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.

Novel strategies to identify biomarkers in tuberculosis

Abstract The more we learn about the immune response against tuberculosis (TB) and particularly about the features which distinguish protective immunity, disease susceptibility and pathology, the better we can define biomarkers which correlate with these different stages of infection. The most widely used biomarker in TB, which without a doubt is an important component of protective immunity, is IFNγ secreted by antigen-specific CD4 T-cells. However, the complexity of the immune response against TB makes it more than likely that additional biomarkers are required for a reliable correlate of protection. As a corollary, we assume that a set of biomarkers will be required, termed a biosignature.

Clonal Expansion of CD8+ Effector T Cells in Childhood Tuberculosis

The role of CD8+ T cells in human tuberculosis (TB) remains elusive. We analyzed the T cell repertoire and phenotype in 1) children with active TB (≤4 years), 2) healthy latently Mycobacterium tuberculosis-infected children, and 3) noninfected age-matched (tuberculin skin test-negative) controls. Ex vivo phenotyping of T cell subpopulations by flow cytometry revealed a significant increase in the proportion of CD8+CD45RO−CD62L−CD28−CD27− effector T cells (TEF) in the peripheral blood of children with active TB (22.1 vs 9.5% in latently M. tuberculosis-infected children, vs 8.5% in tuberculin skin test-negative controls). Analyses of TCR variable β-chains revealed markedly skewed repertoires in CD8+ TEF and effector memory T cells. Expansions were restricted to single TCR variable β-chains in individual donors indicating clonal growth. CDR3 spectratyping and DNA sequencing verified clonal expansion as the cause for CD8+ effector T cell enrichment in individual TB patients. The most prominent enrichment of highly similar TEF clones (>70% of CD8+ TEF) was found in two children with active severe TB. Therefore, clonal expansion of CD8+ TEF occurs in childhood TB with potential impact on course and severity of disease.

Rapid identification of local T cell expansion in inflammatory organ diseases by flow cytometric T cell receptor Vβ analysis

Oligoclonal expansion of antigen-specific T cells occurs frequently during inflammatory diseases. These cells may persist for a long time at high frequency in the body and be enriched in the affected tissues. As a screening test for expanded cell T cell populations at sites of inflammation, we developed an optimized methodology for flow-cytometry-based quantification of T cell receptor Vbeta (TCRBV) expression. We first validated the specificity of a TCRBV-specific monoclonal antibody set by direct comparison with PCR-based analysis of mono- and polyclonal T cell samples. This monoclonal antibody (mAb) panel recognized approximately two thirds of the T cell receptor alpha/beta repertoire in a group of 64 healthy donors and allowed defining TCR usage in the CD4+ and CD8+ subsets. The reliable detection of expanded Vbeta gene families in T cell populations was confirmed in experiments on superantigen-stimulated T cells. Through differential TCR analysis on T cell subpopulations in cerebrospinal fluid and blood in patients with acute encephalitis, we were able to identify locally expanded CD8+ T cells. The power of this approach affords not only high-throughput comparative TCR analysis for immunological studies in vitro, but also rapid ex vivo identification of cell populations enriched in organ compartments during inflammatory diseases.

Secondary lymphoid organs are dispensable for the development of T‐cell‐mediated immunity during tuberculosis

Tuberculosis causes 2 million deaths per year, yet in most cases the immune response successfully contains the infection and prevents disease outbreak. Induced lymphoid structures associated with pulmonary granuloma are observed during tuberculosis in both humans and mice and could orchestrate host defense. To investigate whether granuloma perform lymphoid functions, mice lacking secondary lymphoid organs (SLO) were infected with Mycobacterium tuberculosis (MTB). As in WT mice, granuloma developed, exponential growth of MTB was controlled, and antigen‐specific T‐cell responses including memory T cells were generated in the absence of SLO. Moreover, adoptively transferred T cells were primed locally in lungs in a granuloma‐dependent manner. T‐cell activation was delayed in the absence of SLO, but resulted in a normal development program including protective subsets and functional recall responses that protected mice against secondary MTB infection. Our data demonstrate that protective immune responses can be generated independently of SLO during MTB infection and implicate local pulmonary T‐cell priming as a mechanism contributing to host defense.