Associations of HLA DR and DQ molecules with Lyme borreliosis in Latvian patients

Copyright: Copyright 2012 Elsevier B.V., All rights reserved.Background: Many autoimmune diseases are associated with variants of HLA genes such as those encoding the MHC complex. This correlation is not absolute, but may help in understanding of the molecular mechanism of disease. The purpose of this study was to determine HLA-DR,-DQ alleles in Latvian patients with Lyme borreliosis and control (healthy) persons. Case patients and control subjects were similar in age, gender and ethnic heritage and differed only as regards the presence of Borrelia burgdorferi infection. The study included 25 patients with clinical stage - erythema migrans and 30 control (healthy) persons. HLA genotyping was performed by PCR with sequence-specific primers. Results: The results show difference in HLA-DRB1 alleles distribution between patients and control subjects. The frequencies of HLA-DRB1 *04 (OR 11.24; p<0.007) and HLA-DRB1 *17 (03) (OR 8.05; p<0.033) were increased in the Lyme disease patients. And the frequency of allele DRB1*13 (OR 0.12; p<0.017) was lower in Borreliosis patients and higher in control group. But, significant differences in frequencies of HLA-DQ alleles we did not detect. Conclusions: HLA predisposition to Lyme borreliosis appears not to be limited to HLA molecules, but some HLA-DR alleles also have a significant influence, and, may have implications in our understanding of pathogenesis of this disease. In particular, HLA-DRB1*04 and DRB1 *17 (03) may contribute to the Lyme borreliosis development in Latvian population.publishersversionPeer reviewe

A composite immune signature parallels disease progression across T1D subjects

At diagnosis, most people with type 1 diabetes (T1D) produce measurable levels of endogenous insulin, but the rate at which insulin secretion declines is heterogeneous. To explain this heterogeneity, we sought to identify a composite signature predictive of insulin secretion, using a collaborative assay evaluation and analysis pipeline that incorporated multiple cellular and serum measures reflecting beta cell health and immune system activity. The ability to predict decline in insulin secretion would be useful for patient stratification for clinical trial enrollment or therapeutic selection. Analytes from 12 qualified assays were measured in shared samples from subjects newly diagnosed with T1D. We developed a computational tool to identify a composite panel associated with decline in insulin secretion over 2 years after diagnosis. The tool employs multiple filtering steps to reduce data dimensionality, incorporates error-estimation techniques including cross-validation and sensitivity analysis, and is flexible to assay type, clinical outcome and disease setting. Using this novel analytical tool, we identified a panel of immune markers that, in combination, are highly associated with loss of insulin secretion. The methods used here represent a novel process for identifying combined immune signatures that predict outcomes relevant for complex and heterogeneous diseases like T1D

Investigating the Role of T-Cell Avidity and Killing Efficacy in Relation to Type 1 Diabetes Prediction

During the progression of the clinical onset of Type 1 Diabetes (T1D), high-risk individuals exhibit multiple islet autoantibodies and high-avidity T cells which progressively destroy beta cells causing overt T1D. In particular, novel autoantibodies, such as those against IA-2 epitopes (aa1-577), had a predictive rate of 100% in a 10-year follow up (rapid progressors), unlike conventional autoantibodies that required 15 years of follow up for a 74% predictive rate (slow progressors). The discrepancy between these two groups is thought to be associated with T-cell avidity, including CD8 and/or CD4 T cells. For this purpose, we build a series of mathematical models incorporating first one clone then multiple clones of islet-specific and pathogenic CD8 and/or CD4 T cells, together with B lymphocytes, to investigate the interaction of T-cell avidity with autoantibodies in predicting disease onset. These models are instrumental in examining several experimental observations associated with T-cell avidity, including the phenomenon of avidity maturation (increased average T-cell avidity over time), based on intra- and cross-clonal competition between T cells in high-risk human subjects. The model shows that the level and persistence of autoantibodies depends not only on the avidity of T cells, but also on the killing efficacy of these cells. Quantification and modeling of autoreactive T-cell avidities can thus determine the level of risk associated with each type of autoantibodies and the timing of T1D disease onset in individuals that have been tested positive for these autoantibodies. Such studies may lead to early diagnosis of the disease in high-risk individuals and thus potentially serve as a means of staging patients for clinical trials of preventive or interventional therapies far before disease onset

Peptide-MHC Cellular Microarray with Innovative Data Analysis System for Simultaneously Detecting Multiple CD4 T-Cell Responses

Peptide:MHC cellular microarrays have been proposed to simultaneously characterize multiple Ag-specific populations of T cells. The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation. T cell cultures. A novel statistical methodology was also developed to facilitate batch processing of raw array-like data into standardized endpoint scores, which linearly correlated with total Ag-specific T cell inputs. Applying these methods to analyze Influenza A viral antigen-specific T cell responses, we not only revealed the most prominent viral epitopes, but also demonstrated the heterogeneity of anti-viral cellular responses in healthy individuals. Applying these methods to examine the insulin producing beta-cell autoantigen specific T cell responses, we observed little difference between autoimmune diabetic patients and healthy individuals, suggesting a more subtle association between diabetes status and peripheral autoreactive T cells.The data analysis system is reliable for T cell specificity and functional testing. Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings

Extended LTA, TNF, LST1 and HLA Gene Haplotypes and Their Association with Rubella Vaccine-Induced Immunity

Recent studies have suggested the importance of HLA genes in determining immune responses following rubella vaccine. The telomeric class III region of the HLA complex harbors several genes, including lymphotoxin alpha (LTA), tumor necrosis factor (TNF) and leukocyte specific transcript -1 (LST1) genes, located between the class I B and class II DRB1 loci. Apart from HLA, little is known about the effect of this extended genetic region on HLA haplotypic backgrounds as applied to immune responses.We examined the association between immune responses and extended class I-class II-class III haplotypes among 714 healthy children after two doses of rubella vaccination. These extended haplotypes were then compared to the HLA-only haplotypes. The most significant association was observed between haplotypes extending across the HLA class I region, ten-SNP haplotypes, and the HLA class II region (i.e. A-C-B-LTA-TNF-LST1-DRB1-DQA1-DQB1-DPA1-DPB1) and rubella-specific antibodies (global p-value of 0.03). Associations were found between both extended A*02-C*03-B*15-AAAACGGGGC-DRB1*04-DQA1*03-DQB1*03-DPA1*01-DPB1*04 (p = 0.002) and HLA-only A*02-C*03-B*15-DRB1*04-DQA1*03-DQB1*03-DPA1*01-DPB1*04 haplotypes (p = 0.009) and higher levels of rubella antibodies. The class II HLA-only haplotype DRB1*13-DQA1*01-DQB1*06-DPA1*01-DPB1*04 (p = 0.04) lacking LTA-TNF-LST1 SNPs was associated with lower rubella antibody responses. Similarly, the class I-class II HLA-only A*01-C*07-B*08-DRB1*03-DQA1*05-DQB1*02-DPA1*01-DPB1*04 haplotype was associated with increased TNF-alpha secretion levels (p = 0.009). In contrast, the extended AAAACGGGGC-DRB1*01-DQA1*01-DQB1*05-DPA1*01-DPB1*04 (p = 0.01) haplotype was found to trend with decreased rubella-specific IL-6 secretion levels.These data suggest the importance of examining both HLA genes and genes in the class III region as part of the extended haplotypes useful in understanding genomic drivers regulating immune responses to rubella vaccine

TRAIL Death Receptor-4, Decoy Receptor-1 and Decoy Receptor-2 Expression on CD8+ T Cells Correlate with the Disease Severity in Patients with Rheumatoid Arthritis

BACKGROUND: Rheumatoid Arthritis (RA) is a chronic autoimmune inflammatory disorder. Although the pathogenesis of disease is unclear, it is well known that T cells play a major role in both development and perpetuation of RA through activating macrophages and B cells. Since the lack of TNF-Related Apoptosis Inducing Ligand (TRAIL) expression resulted in defective thymocyte apoptosis leading to an autoimmune disease, we explored evidence for alterations in TRAIL/TRAIL receptor expression on peripheral T lymphocytes in the molecular mechanism of RA development. METHODS: The expression of TRAIL/TRAIL receptors on T cells in 20 RA patients and 12 control individuals were analyzed using flow cytometry. The correlation of TRAIL and its receptor expression profile was compared with clinical RA parameters (RA activity scored as per DAS28) using Spearman Rho Analysis. RESULTS: While no change was detected in the ratio of CD4+ to CD8+ T cells between controls and RA patient groups, upregulation of TRAIL and its receptors (both death and decoy) was detected on both CD4+ and CD8+ T cells in RA patients compared to control individuals. Death Receptor-4 (DR4) and the decoy receptors DcR1 and DcR2 on CD8+ T cells, but not on CD4+ T cells, were positively correlated with patients' DAS scores. CONCLUSIONS: Our data suggest that TRAIL/TRAIL receptor expression profiles on T cells might be important in revelation of RA pathogenesis

Correlations of Gene Expression with Blood Lead Levels in Children with Autism Compared to Typically Developing Controls

The objective of this study was to examine the correlation between gene expression and lead (Pb) levels in blood in children with autism (AU, n = 37) compared to typically developing controls (TD, n = 15). We postulated that, though lead levels did not differ between the groups, AU children might metabolize lead differently compared to TD children. RNA was isolated from blood and processed on Affymetrix microarrays. Separate analyses of covariance (ANCOVA) corrected for age and gender were performed for TD, AU, and all subjects (AU + TD). To reduce false positives, only genes that overlapped these three ANCOVAs were considered. Thus, 48 probe sets correlated with lead levels in both AU and TD subjects and were significantly different between the groups (p(Diagnosis × log2 Pb) < 0.05). These genes were related mainly to immune and inflammatory processes, including MHC Class II family members and CD74. A large number (n = 791) of probe sets correlated (P ≤ 0.05) with lead levels in TD but not in AU subjects; and many probe sets (n = 162) correlated (P ≤ 0.05) with lead levels in AU but not in TD subjects. Only 30 probe sets correlated (P ≤ 0.05) with lead levels in a similar manner in the AU and TD groups. These data show that AU and TD children display different associations between transcript levels and low levels of lead. We postulate that this may relate to the underlying genetic differences between the two groups, though other explanations cannot be excluded

Identification and HLA-Tetramer-Validation of Human CD4(+) and CD8(+) T Cell Responses against HCMV Proteins IE1 and IE2

Human cytomegalovirus (HCMV) is an important human pathogen. It is a leading cause of congenital infection and a leading infectious threat to recipients of solid organ transplants as well as of allogeneic hematopoietic cell transplants. Moreover, it has recently been suggested that HCMV may promote tumor development. Both CD4+ and CD8+ T cell responses are important for long-term control of the virus, and adoptive transfer of HCMV-specific T cells has led to protection from reactivation and HCMV disease. Identification of HCMV-specific T cell epitopes has primarily focused on CD8+ T cell responses against the pp65 phosphoprotein. In this study, we have focused on CD4+ and CD8+ T cell responses against the immediate early 1 and 2 proteins (IE1 and IE2). Using overlapping peptides spanning the entire IE1 and IE2 sequences, peripheral blood mononuclear cells from 16 healthy, HLA-typed, donors were screened by ex vivo IFN-γ ELISpot and in vitro intracellular cytokine secretion assays. The specificities of CD4+ and CD8+ T cell responses were identified and validated by HLA class II and I tetramers, respectively. Eighty-one CD4+ and 44 CD8+ T cell responses were identified representing at least seven different CD4 epitopes and 14 CD8 epitopes restricted by seven and 11 different HLA class II and I molecules, respectively, in total covering 91 and 98% of the Caucasian population, respectively. Presented in the context of several different HLA class II molecules, two epitope areas in IE1 and IE2 were recognized in about half of the analyzed donors. These data may be used to design a versatile anti-HCMV vaccine and/or immunotherapy strategy

A quantitative analysis of complexity of human pathogen-specific CD4 T cell responses in healthy M. tuberculosis infected South Africans

Author Summary: Human pathogen-specific immune responses are tremendously complex and the techniques to study them ever expanding. There is an urgent need for a quantitative analysis and better understanding of pathogen-specific immune responses. Mycobacterium tuberculosis (Mtb) is one of the leading causes of mortality due to an infectious agent worldwide. Here, we were able to quantify the Mtb-specific response in healthy individuals with Mtb infection from South Africa. The response is highly diverse and 66 epitopes are required to capture 80% of the total reactivity. Our study also show that the majority of the identified epitopes are restricted by multiple HLA alleles. Thus, technical advances are required to capture and characterize the complete pathogen-specific response. This study demonstrates further that the approach combining identified epitopes into "megapools" allows capturing a large fraction of the total reactivity. This suggests that this technique is generally applicable to the characterization of immunity to other complex pathogens. Together, our data provide for the first time a quantitative analysis of the complex pathogen-specific T cell response and provide a new understanding of human infections in a natural infection setting