Comparing HLA Shared Epitopes in French Caucasian Patients with Scleroderma

Although many studies have analyzed HLA allele frequencies in several ethnic groups in patients with scleroderma (SSc), none has been done in French Caucasian patients and none has evaluated which one of the common amino acid sequences, 67FLEDR71, shared by HLA-DRB susceptibility alleles, or 71TRAELDT77, shared by HLA-DQB1 susceptibility alleles in SSc, was the most important to develop the disease. HLA-DRB and DQB typing was performed for a total of 468 healthy controls and 282 patients with SSc allowing FLEDR and TRAELDT analyses. Results were stratified according to patient’s clinical subtypes and autoantibody status. Moreover, standardized HLA-DRß1 and DRß5 reverse transcriptase Taqman PCR assays were developed to quantify ß1 and ß5 mRNA in 20 subjects with HLA-DRB1*15 and/or DRB1*11 haplotypes. FLEDR motif is highly associated with diffuse SSc (χ2 = 28.4, p<10−6) and with anti-topoisomerase antibody (ATA) production (χ2 = 43.9, p<10−9) whereas TRAELDT association is weaker in both subgroups (χ2 = 7.2, p = 0.027 and χ2 = 14.6, p = 0.0007 respectively). Moreover, FLEDR motif- association among patients with diffuse SSc remains significant only in ATA subgroup. The risk to develop ATA positive SSc is higher with double dose FLEDR than single dose with respectively, adjusted standardised residuals of 5.1 and 2.6. The increase in FLEDR motif is mostly due to the higher frequency of HLA-DRB1*11 and DRB1*15 haplotypes. Furthermore, FLEDR is always carried by the most abundantly expressed ß chain: ß1 in HLA DRB1*11 haplotypes and ß5 in HLA-DRB1*15 haplotypes

Contribution of TLR7 and TLR9 signaling to the susceptibility of MyD88-deficient mice to myocarditis.

International audienceToll-like receptors (TLRs) are evolutionary conserved molecules that recognize various microbial components and host-derived agonists from damaged cells and play a central role in innate and adaptive immunity. It has been reported that MyD88, the adaptor molecule downstream of all TLRs, except TLR3, is essential for initiation of experimental autoimmune myocarditis (EAM). To determine the role of the intracellular TLRs in EAM, TLR3(-/-), TLR7(-/-), and TLR9(-/-) mice were immunized with cardiac alpha-myosin heavy chain peptide (MyHC-alpha) in Complete Freund's Adjuvant (CFA) and their EAM scores and associated immunological responses were compared to wild-type (WT) and MyD88(-/-) mice. MyD88(-/-) mice were completely resistant to EAM and had a profound defect in all the parameters we tested. Myocardial cellular infiltration and in vitro proliferation of MyHC-alpha-restimulated splenocytes were markedly reduced in TLR7(-/-) mice, while TLR3(-/-) and TLR9(-/-) mice showed similar inflammatory cell infiltration in the heart-like WT mice. Thus, the resistance of MyD88(-/-) mice to EAM can be attributed to a certain degree to TLR7 signaling. Moreover, upon murine cytomegalovirus-induced myocarditis, we found that the severity of myocardial inflammation was higher in TLR9(-/-) and MyD88(-/-) mice compared with WT, TLR3(-/-), or TLR7(-/-) mice and paralleled the ability of the mice to fight the viral infection

Microbiota present in cystic fibrosis lungs as revealed by whole genome sequencing.

Determination of the precise composition and variation of microbiota in cystic fibrosis lungs is crucial since chronic inflammation due to microorganisms leads to lung damage and ultimately, death. However, this constitutes a major technical challenge. Culturing of microorganisms does not provide a complete representation of a microbiota, even when using culturomics (high-throughput culture). So far, only PCR-based metagenomics have been investigated. However, these methods are biased towards certain microbial groups, and suffer from uncertain quantification of the different microbial domains. We have explored whole genome sequencing (WGS) using the Illumina high-throughput technology applied directly to DNA extracted from sputa obtained from two cystic fibrosis patients. To detect all microorganism groups, we used four procedures for DNA extraction, each with a different lysis protocol. We avoided biases due to whole DNA amplification thanks to the high efficiency of current Illumina technology. Phylogenomic classification of the reads by three different methods produced similar results. Our results suggest that WGS provides, in a single analysis, a better qualitative and quantitative assessment of microbiota compositions than cultures and PCRs. WGS identified a high quantity of Haemophilus spp. (patient 1) or Staphylococcus spp. plus Streptococcus spp. (patient 2) together with low amounts of anaerobic (Veillonella, Prevotella, Fusobacterium) and aerobic bacteria (Gemella, Moraxella, Granulicatella). WGS suggested that fungal members represented very low proportions of the microbiota, which were detected by cultures and PCRs because of their selectivity. The future increase of reads' sizes and decrease in cost should ensure the usefulness of WGS for the characterisation of microbiota

TLR8 deficiency leads to autoimmunity in mice

TLRs play an essential role in the induction of immune responses by detecting conserved molecular products of microorganisms. However, the function of TLR8 is largely unknown. In the current study, we investigated the role of TLR8 signaling in immunity in mice. We found that Tlr8–/– DCs overexpressed TLR7, were hyperresponsive to various TLR7 ligands, and showed stronger and faster NF-κB activation upon stimulation with the TLR7 ligand R848. Tlr8–/– mice showed splenomegaly, defective development of marginal zone (MZ) and B1 B cells, and increased serum levels of IgM and IgG2a. Furthermore, Tlr8–/– mice exhibited increased serum levels of autoantibodies against small nuclear ribonucleoproteins, ribonucleoprotein, and dsDNA and developed glomerulonephritis, whereas neither Tlr7–/– nor Tlr8–/–Tlr7–/– mice showed any of the phenotypes observed in Tlr8–/– mice. These data provide evidence for a pivotal role for mouse TLR8 in the regulation of mouse TLR7 expression and prevention of spontaneous autoimmunity

Prevalence of FLEDR and TRAELDT in patients with SSc divided by clinical subtypes.

a<p>adjusted standardized residual >1.96 indicates that the number of cases in that cell is significantly larger than would be expected if the null hypothesis were true (represented in bold), with a significance level of.05. An adjusted residual < −2.0 indicates that the number of cases in that cell is significantly smaller than would be expected if the null hypothesis were true (represented in italic).</p>b<p>when comparing different subgroups for FLEDR association: DcSSc/LcSSc/healthy controls: χ² = 29.1, p<10⁻⁵; LcSSc/healthy controls: not significant; DcSSc/healthy controls: χ² = 28.4, p<10⁻⁶.</p>c<p>when comparing different subgroups for TRAELDT association: DcSSc/LcSSc/healthy controls: χ² = 10.2, p = 0.029; LcSSc/healthy controls: not significant; DcSSc/healthy controls: χ² = 7.2, p = 0.027.</p

Prevalence of FLEDR and TRAELDT in patients with SSc divided by antibody status.

a<p>adjusted standardized residual >1.96 indicates that the number of cases in that cell is significantly larger than would be expected if the null hypothesis were true (represented in bold), with a significance level of.05. An adjusted residual < −2.0 indicates that the number of cases in that cell is significantly smaller than would be expected if the null hypothesis were true (represented in italic).</p>b<p>when comparing different subgroups for FLEDR association: Ab neg/ACA pos/ATA pos/healthy controls: χ² = 48.5, p<10⁻⁸; Ab neg/healthy controls: not significant; ACA pos/healthy controls: χ² = 0.17, p = 0.9; ATA pos: χ² = 43.9, p<10⁻⁹.</p>c<p>when comparing different subgroups for TRAELDT association: Ab neg/ACA pos/ATA pos/healthy controls: χ² = 27.6, p = 0.00013; Ab neg/healthy controls: not significant; ACA pos: χ² = 7.9, p = 0.02; ATA pos/healthy controls: χ² = 14.6, p = 0.0007.</p

Transient B-Cell Depletion with Anti-CD20 in Combination with Proinsulin DNA Vaccine or Oral Insulin: Immunologic Effects and Efficacy in NOD Mice

<div><p>A recent type 1 diabetes (T1D) clinical trial of rituximab (a B cell-depleting anti-CD20 antibody) achieved some therapeutic benefit in preserving C-peptide for a period of approximately nine months in patients with recently diagnosed diabetes. Our previous data in the NOD mouse demonstrated that co-administration of antigen (insulin) with anti-CD3 antibody (a T cell-directed immunomodulator) offers better protection than either entity alone, indicating that novel combination therapies that include a T1D-related autoantigen are possible. To accelerate the identification and development of novel combination therapies that can be advanced into the clinic, we have evaluated the combination of a mouse anti-CD20 antibody with either oral insulin or a proinsulin-expressing DNA vaccine. Anti-CD20 alone, given once or on 4 consecutive days, produced transient B cell depletion but did not prevent or reverse T1D in the NOD mouse. Oral insulin alone (twice weekly for 6 weeks) was also ineffective, while proinsulin DNA (weekly for up to 12 weeks) showed a trend toward modest efficacy. Combination of anti-CD20 with oral insulin was ineffective in reversing diabetes in NOD mice whose glycemia was controlled with SC insulin pellets; these experiments were performed in three independent labs. Combination of anti-CD20 with proinsulin DNA was also ineffective in diabetes reversal, but did show modest efficacy in diabetes prevention (p = 0.04). In the prevention studies, anti-CD20 plus proinsulin resulted in modest increases in Tregs in pancreatic lymph nodes and elevated levels of proinsulin-specific CD4+ T-cells that produced IL-4. Thus, combination therapy with anti-CD20 and either oral insulin or proinsulin does not protect hyperglycemic NOD mice, but the combination with proinsulin offers limited efficacy in T1D prevention, potentially by augmentation of proinsulin-specific IL-4 production.</p> </div

Shared amino acid sequences of the most common DRß chains.

<p>Shared amino acid sequences of the most common DRß chains.</p