Prior history of atopy or autoimmunity increases risk for alopecia areata

Background. The association between a prior history of atopy or other autoimmune diseases and risk of alopecia areata is not well established. ^ Objective. Purpose of this study was to use the National Alopecia Areata Registry database to further investigate the association between history of atopy or other autoimmune diseases and risk of alopecia areata. ^ Methods. A total of 2,613 self-registered sporadic cases (n = 2,055) and controls (n = 558) were included in the present analysis. ^ Results. Possessing a history of any atopy (OR = 2.00; 95% CI 1.50-2.54) or autoimmune disease (OR = 1.73; 95% CI 1.10-2.72) was associated with an increased risk of alopecia areata. There was no trend for possessing a history of more than one atopy or autoimmune disease and increasing risk of alopecia areata. ^ Limitations. Recall, reporting, and recruiting bias are potential sources of limitations in this analysis. ^ Conclusion. This analysis revealed that a prior history of atopy and autoimmune disease was associated with an increased risk of alopecia areata and that the results were consistent for both the severe subtype of alopecia areata (i.e., alopecia totalis and alopecia universalis) and the localized subtype (i.e., alopecia areata persistent).^

Anti-glomerular basement membrane glomerulonephritis: Characterization of an epitope, antibody response, and the potential role of IL-4Ralpha in disease progression

Anti-Glomerular Basement Membrane Glomerulonephritis (anti-GBM GM) is one of the earliest described autoimmune disorders. Patients present with proteinuria, anti-GBM antibodies, and renal failure. Studies have implicated a T Helper 1 (TH1) response in disease induction and a T Helper 2 (TH2) response for disease progression. A 13 amino acid long peptide sequence spanning residues 28 through 40 [pCol(28–40)] of the Collagen IV α3 non-collagen domain (Col IV α3 NCD) is immunogenic and induces anti-GBM GN. In order to fully understand disease initiation, this peptide was further characterized. Peptides were created containing one amino acid substitution for the entire length of pCol(28–40) and induction of anti-GBM GN was monitored. When residues 31, 33, or 34 contained the substitution, anti-GBM GN was unable to be induced. Thus, residues 31, 33, and 34 of pCol(28–40) are required for induction of anti-GBM. Glomerular injury is observed as early as 14 days post anti-GBM GN induction. However, the presence of anti-GBM antibodies is not observed until 20 days post immunization. An enlarged lymph node adjacent to the diseased kidney exhibits B cell activation after renal injury and produces antibodies toward GBM. Thus, anti-GBM antibodies are a consequence of the initial renal injury. Differences between disease susceptible and disease resistant rat strains exist in the expression of IL-4Rα, a major player in the TH2 response. IL-4Rα signaling is regulated by soluble IL-4Rα (sIL-4Rα). Low expression levels of sIL-4Rα result in the stabilization of IL-4 binding, while elevated expression sequesters IL-4. Quantitative PCR experiments noted low siL-4Rα expression levels in disease susceptible rats. Induction of an immune response toward sIL-4Rα in this strain was responsible for delayed disease progression in 15 out of the 17 experimental animals. Antibody transfer and in vivo biological activity experiments confirmed that delayed disease development was due to anti-sIL-4Rα antibodies. Together these experiments indicate that a T-cell epitope is required for activation of a TH1 autoimmune response and anti-GBM antibodies are a consequence of renal injury. More importantly, a role for IL-4Rα signaling is implicated in the progression of anti-GBM GN. ^

Disease risk factors and humoral antibody response to periodontal-associated pathogens: A model to evaluate periodontal disease in older adults

Periodontal diseases (PD) are infectious, inflammatory, and tissue destructive events which affect the periodontal ligament that surround and support the teeth. Periodontal diseases are the major cause of tooth loss after age 35, with gingivitis and periodontitis affecting 75% of the adult population. A select group of bacterial organisms are associated with periodontal pathogenesis. There is a direct association between oral hygiene and prevention of PD. The importance of genetic differences and host immune response capabilities in determining host, susceptibility or resistance to PD has not been established. This study examined the risk factors and serum (humoral) immune response to periodontal diseased-associated pathogens in a 55 to 80+ year old South Texas study sample with PD. This study sample was described by: age, sex, ethnicity, the socioeconomic factors marital status, income and occupation, IgG, IgA, IgM immunoglobulin status, and the autoimmune response markers rheumatoid factor (RF) and antinuclear antibody (ANA). These variables were used to determine the risk factors associated with development of PD. Serum IgG, IgA, IgM antibodies to bacterial antigens provided evidence for disease exposure.^ A causal model for PD was constructed from associations for risk factors (ethnicity, marital status, income, and occupation) with dental exam and periodontitis. The multiple correlation between PD and ethnicity, income and dental exam was significant. Hispanics of low income were least likely to have had a dental exam in the last year and most likely to have PD. The etiologic agents for PD, as evidenced by elevated humoral antibody responses, were the Gram negative microorganisms Bacteroides gingivalis, serotypes FDC381 and SUNYaBA7A1-28, and Wolinella recta. Recommendation for a PD prevention and control program are provided. ^

Pathway analysis of genome-wide association study data in primary biliary cirrhosisa

Genome-wide association studies (GWAS) have successfully identified several genetic loci associated with inherited predisposition to primary biliary cirrhosis (PBC), the most common autoimmune disease of the liver. Pathway-based tests constitute a novel paradigm for GWAS analysis. By evaluating genetic variation across a biological pathway (gene set), these tests have the potential to determine the collective impact of variants with subtle effects that are individually too weak to be detected in traditional single variant GWAS analysis. To identify biological pathways associated with the risk of development of PBC, GWAS of PBC from Italy (449 cases and 940 controls) and Canada (530 cases and 398 controls) were independently analyzed. The linear combination test (LCT), a recently developed pathway-level statistical method was used for this analysis. For additional validation, pathways that were replicated at the P <0.05 level of significance in both GWAS on LCT analysis were also tested for association with PBC in each dataset using two complementary GWAS pathway approaches. The complementary approaches included a modification of the gene set enrichment analysis algorithm (i-GSEA4GWAS) and Fisher's exact test for pathway enrichment ratios. Twenty-five pathways were associated with PBC risk on LCT analysis in the Italian dataset at P<0.05, of which eight had an FDR<0.25. The top pathway in the Italian dataset was the TNF/stress related signaling pathway (p=7.38×10 -4, FDR=0.18). Twenty-six pathways were associated with PBC at the P<0.05 level using the LCT in the Canadian dataset with the regulation and function of ChREBP in liver pathway (p=5.68×10-4, FDR=0.285) emerging as the most significant pathway. Two pathways, phosphatidylinositol signaling system (Italian: p=0.016, FDR=0.436; Canadian: p=0.034, FDR=0.693) and hedgehog signaling (Italian: p=0.044, FDR=0.636; Canadian: p=0.041, FDR=0.693), were replicated at LCT P<0.05 in both datasets. Statistically significant association of both pathways with PBC genetic susceptibility was confirmed in the Italian dataset on i-GSEA4GWAS. Results for the phosphatidylinositol signaling system were also significant in both datasets on applying Fisher's exact test for pathway enrichment ratios. This study identified a combination of known and novel pathway-level associations with PBC risk. If functionally validated, the findings may yield fresh insights into the etiology of this complex autoimmune disease with possible preventive and therapeutic application.^

Characterization of anti -sulfatide autoantibodies in demyelinating diseases

Multiple sclerosis (MS) is the most common autoimmune disease of the central nerve system and Guillain Barré Syndrome (GBS) is an inflammatory neuropathy involving the peripheral nerves. Anti-myelin immunoglobins may play a role in the demyelination processes of the both diseases. Sulfatide is an abundant glycolipid on myelin and is a candidate target antigen for disease related autoantibodies. The objective of this study was to characterize anti-sulfatide antibodies and compare antibodies from GBS and MS patients with fetal antibodies. Our hypothesis is that some B cells producing disease-associated autoantibodies are derived from or related to B cells of the fetal repertoire. Here we report that reactivity of plasma IgM against sulfatide was elevated in twelve MS patients compared with twelve normal subjects. This result implies that anti-sulfatide antibodies are disease-related. A total of sixteen human B lymphocyte clones producing anti-sulfatide autoantibodies were isolated from MS patients, GBS patients and a human fetus. Seven of the clones were from three MS patients, four of the clones were from three GBS patients and five were from the spleen of a twenty-week human fetus. Sequences have been obtained for the heavy and light chain variable regions (VDJ and VJ regions) of all of the anti-sulfatide immunoglobulins. Seven of the sixteen antibodies used VH3 for the variable region gene of the heavy chain consistent with the rate of VH3 usage in randomly selected B cells. Somatic mutations were significantly more frequent in the patient antibodies than in the fetus and somatic mutations in CDR's (Complementarity Determining Region) were significantly more frequent than in framework regions. No significant difference was found between patients and fetus in length of VH CDRIII. However, it is reported that antibodies from randomly selected normal adult B cells have longer CDRIII lengths than those of the fetus (Sanz I, 1991 Journal of Immunology Sep 1;147(5):1720-9). Our results are consistent with derivation of the precursors of B cells producing these autoantibodies from B cells related to those of the fetal repertoire. These findings are consistent with a model in which quiescent B cells from clones produced early in development undergo proliferation in dysregulated disease states, accumulating somatic mutations and increasing in reactivity toward self-antigens. ^ Epitope mapping and molecular modeling were done to elucidate the relationships between antibody structure and binding characteristics. The autoantibodies were tested for binding activity to three different antigens: sulfatide, galactoceramide and ceramide. Molecular modeling suggests that antibodies with positive charge surrounded by or adjacent to hydrophobic groups in the binding pocket bind to the head of sulfatide via the sulfate group through electrostatic interactions. However, the antibodies with hydrophobic groups separated from positive charges appear to bind to the hydrophobic tail of sulfatide. This observation was supported by a study of the effect of NaCl concentration on antigen binding. The result suggested that electrostatic interactions played a major role in sulfate group binding and that hydrophobic interactions were of greater importance for binding to the ceramide group. Our three-dimensional structure data indicated that epitope specificity of these antibodies is more predictable at the level of tertiary than primary structure and suggested positive selection based on structure occurred in the. formation of those autoantibodies. ^

Papel de la interleuquina 23 en la diferenciación hacia Th17

The incidence of inflammatory and autoimmune diseases has increased among developed countries in the past 30 years, creating a demand for the development of effective and economic therapies for these diseases. Interleukin 23 (IL-23) is a pro-inflammatory cytokine whose increased production has been shown to play a key role in the establishment and maintenance of inflammatory and autoimmune diseases in different murine models such as inflammatory bowel disease, psoriasis and experimental autoimmune encephalomyelitis. More importantly, increased levels of IL-23 have been found in biopsies from patients with Crohn’s disease and ulcerative colitis, and psoriasis. The pathological consequences of excessive IL-23 signalling have been linked to its ability to promote the production of interleukin 17 (IL-17), particularly in the subpopulation of CD4 T cells Th17. However, the precise molecular mechanisms by which IL-23 sustains the Th17 response and induces pathogenic effector functions in these cells remain largely unknown. The global objective of the experiments carried out in this work was to determine the effect of IL-23 on the proliferation, survival and IL-17 and interferon gamma (IFN-ɣ) production in Th17 cells. These experiments have shown that IL-23 does not promote proliferation or survival of in vitro generated Th17 cells, and that there is no difference in the production of IL -17 in the absence or presence of IL -23. The IL-23 receptor, like other cytokine receptors, lacks intrinsic enzymatic activity. Instead, IL-23 receptor associates with members of the Janus tyrosine kinase family (Jaks). Cytokine binding to a Jak-associated receptor triggers the activation of the Signal Transducers and Activators of Transcription (STAT) family of transcription factors. Previous work indicated that the IL-23 receptor complex is associated with the tyrosine kinases Jak2 and Tyk2 that promote STAT3 phosphorylation. Subsequent studies showed that IL23 activation of STAT3 induces the expression of the transcription factor RORγt, which is crucial for IL-17 production. This work has explored the IL-23 signalling cascade, determining the optimal conditions for STAT3 activation and demonstrating the activation of other transcription factors such as STAT4, STAT5 and STAT1 that contribute to IL-23-mediated signalling pathways.

Extracción de conocimientos de la diabetes tipo 1 utilizando la metodología de "Data Mining"

La diabetes mellitus es un trastorno en la metabolización de los carbohidratos, caracterizado por la nula o insuficiente segregación de insulina (hormona producida por el páncreas), como resultado del mal funcionamiento de la parte endocrina del páncreas, o de una creciente resistencia del organismo a esta hormona. Esto implica, que tras el proceso digestivo, los alimentos que ingerimos se transforman en otros compuestos químicos más pequeños mediante los tejidos exocrinos. La ausencia o poca efectividad de esta hormona polipéptida, no permite metabolizar los carbohidratos ingeridos provocando dos consecuencias: Aumento de la concentración de glucosa en sangre, ya que las células no pueden metabolizarla; consumo de ácidos grasos mediante el hígado, liberando cuerpos cetónicos para aportar la energía a las células. Esta situación expone al enfermo crónico, a una concentración de glucosa en sangre muy elevada, denominado hiperglucemia, la cual puede producir a medio o largo múltiples problemas médicos: oftalmológicos, renales, cardiovasculares, cerebrovasculares, neurológicos… La diabetes representa un gran problema de salud pública y es la enfermedad más común en los países desarrollados por varios factores como la obesidad, la vida sedentaria, que facilitan la aparición de esta enfermedad. Mediante el presente proyecto trabajaremos con los datos de experimentación clínica de pacientes con diabetes de tipo 1, enfermedad autoinmune en la que son destruidas las células beta del páncreas (productoras de insulina) resultando necesaria la administración de insulina exógena. Dicho esto, el paciente con diabetes tipo 1 deberá seguir un tratamiento con insulina administrada por la vía subcutánea, adaptado a sus necesidades metabólicas y a sus hábitos de vida. Para abordar esta situación de regulación del control metabólico del enfermo, mediante una terapia de insulina, no serviremos del proyecto “Páncreas Endocrino Artificial” (PEA), el cual consta de una bomba de infusión de insulina, un sensor continuo de glucosa, y un algoritmo de control en lazo cerrado. El objetivo principal del PEA es aportar al paciente precisión, eficacia y seguridad en cuanto a la normalización del control glucémico y reducción del riesgo de hipoglucemias. El PEA se instala mediante vía subcutánea, por lo que, el retardo introducido por la acción de la insulina, el retardo de la medida de glucosa, así como los errores introducidos por los sensores continuos de glucosa cuando, se descalibran dificultando el empleo de un algoritmo de control. Llegados a este punto debemos modelar la glucosa del paciente mediante sistemas predictivos. Un modelo, es todo aquel elemento que nos permita predecir el comportamiento de un sistema mediante la introducción de variables de entrada. De este modo lo que conseguimos, es una predicción de los estados futuros en los que se puede encontrar la glucosa del paciente, sirviéndonos de variables de entrada de insulina, ingesta y glucosa ya conocidas, por ser las sucedidas con anterioridad en el tiempo. Cuando empleamos el predictor de glucosa, utilizando parámetros obtenidos en tiempo real, el controlador es capaz de indicar el nivel futuro de la glucosa para la toma de decisones del controlador CL. Los predictores que se están empleando actualmente en el PEA no están funcionando correctamente por la cantidad de información y variables que debe de manejar. Data Mining, también referenciado como Descubrimiento del Conocimiento en Bases de Datos (Knowledge Discovery in Databases o KDD), ha sido definida como el proceso de extracción no trivial de información implícita, previamente desconocida y potencialmente útil. Todo ello, sirviéndonos las siguientes fases del proceso de extracción del conocimiento: selección de datos, pre-procesado, transformación, minería de datos, interpretación de los resultados, evaluación y obtención del conocimiento. Con todo este proceso buscamos generar un único modelo insulina glucosa que se ajuste de forma individual a cada paciente y sea capaz, al mismo tiempo, de predecir los estados futuros glucosa con cálculos en tiempo real, a través de unos parámetros introducidos. Este trabajo busca extraer la información contenida en una base de datos de pacientes diabéticos tipo 1 obtenidos a partir de la experimentación clínica. Para ello emplearemos técnicas de Data Mining. Para la consecución del objetivo implícito a este proyecto hemos procedido a implementar una interfaz gráfica que nos guía a través del proceso del KDD (con información gráfica y estadística) de cada punto del proceso. En lo que respecta a la parte de la minería de datos, nos hemos servido de la denominada herramienta de WEKA, en la que a través de Java controlamos todas sus funciones, para implementarlas por medio del programa creado. Otorgando finalmente, una mayor potencialidad al proyecto con la posibilidad de implementar el servicio de los dispositivos Android por la potencial capacidad de portar el código. Mediante estos dispositivos y lo expuesto en el proyecto se podrían implementar o incluso crear nuevas aplicaciones novedosas y muy útiles para este campo. Como conclusión del proyecto, y tras un exhaustivo análisis de los resultados obtenidos, podemos apreciar como logramos obtener el modelo insulina-glucosa de cada paciente. ABSTRACT. The diabetes mellitus is a metabolic disorder, characterized by the low or none insulin production (a hormone produced by the pancreas), as a result of the malfunctioning of the endocrine pancreas part or by an increasing resistance of the organism to this hormone. This implies that, after the digestive process, the food we consume is transformed into smaller chemical compounds, through the exocrine tissues. The absence or limited effectiveness of this polypeptide hormone, does not allow to metabolize the ingested carbohydrates provoking two consequences: Increase of the glucose concentration in blood, as the cells are unable to metabolize it; fatty acid intake through the liver, releasing ketone bodies to provide energy to the cells. This situation exposes the chronic patient to high blood glucose levels, named hyperglycemia, which may cause in the medium or long term multiple medical problems: ophthalmological, renal, cardiovascular, cerebrum-vascular, neurological … The diabetes represents a great public health problem and is the most common disease in the developed countries, by several factors such as the obesity or sedentary life, which facilitate the appearance of this disease. Through this project we will work with clinical experimentation data of patients with diabetes of type 1, autoimmune disease in which beta cells of the pancreas (producers of insulin) are destroyed resulting necessary the exogenous insulin administration. That said, the patient with diabetes type 1 will have to follow a treatment with insulin, administered by the subcutaneous route, adapted to his metabolic needs and to his life habits. To deal with this situation of metabolic control regulation of the patient, through an insulin therapy, we shall be using the “Endocrine Artificial Pancreas " (PEA), which consists of a bomb of insulin infusion, a constant glucose sensor, and a control algorithm in closed bow. The principal aim of the PEA is providing the patient precision, efficiency and safety regarding the normalization of the glycemic control and hypoglycemia risk reduction". The PEA establishes through subcutaneous route, consequently, the delay introduced by the insulin action, the delay of the glucose measure, as well as the mistakes introduced by the constant glucose sensors when, decalibrate, impede the employment of an algorithm of control. At this stage we must shape the patient glucose levels through predictive systems. A model is all that element or set of elements which will allow us to predict the behavior of a system by introducing input variables. Thus what we obtain, is a prediction of the future stages in which it is possible to find the patient glucose level, being served of input insulin, ingestion and glucose variables already known, for being the ones happened previously in the time. When we use the glucose predictor, using obtained real time parameters, the controller is capable of indicating the future level of the glucose for the decision capture CL controller. The predictors that are being used nowadays in the PEA are not working correctly for the amount of information and variables that it need to handle. Data Mining, also indexed as Knowledge Discovery in Databases or KDD, has been defined as the not trivial extraction process of implicit information, previously unknown and potentially useful. All this, using the following phases of the knowledge extraction process: selection of information, pre- processing, transformation, data mining, results interpretation, evaluation and knowledge acquisition. With all this process we seek to generate the unique insulin glucose model that adjusts individually and in a personalized way for each patient form and being capable, at the same time, of predicting the future conditions with real time calculations, across few input parameters. This project of end of grade seeks to extract the information contained in a database of type 1 diabetics patients, obtained from clinical experimentation. For it, we will use technologies of Data Mining. For the attainment of the aim implicit to this project we have proceeded to implement a graphical interface that will guide us across the process of the KDD (with graphical and statistical information) of every point of the process. Regarding the data mining part, we have been served by a tool called WEKA's tool called, in which across Java, we control all of its functions to implement them by means of the created program. Finally granting a higher potential to the project with the possibility of implementing the service for Android devices, porting the code. Through these devices and what has been exposed in the project they might help or even create new and very useful applications for this field. As a conclusion of the project, and after an exhaustive analysis of the obtained results, we can show how we achieve to obtain the insulin–glucose model for each patient.

Wheat allergy in celiac children

Gluten is the main structural protein complex of wheat with equivalent toxic proteins found in other cereals (rye, barley, and oats) which are responsible for different immunologic responses with different clinical expressions of disease. The spectrum of gluten-related disorders has been classified according to pathogenic, clinical, and epidemiological differences in three main forms: (i) wheat allergy (WA), an IgE-mediated disease; (ii) autoimmune disease, including celiac disease (CD), dermatitis herpetiformis, and gluten ataxia; and (iii) possibly immune-mediated, gluten sensitivity [1]. WA is an immunologic Th2 response with typical manifestations which can vary from dermatological, respiratory, and/or intestinal to anaphylactic reactions. In contrast, CD is an autoimmune disorder, a gliadin-specific T-cell response which is enhanced by the action of intestinal tissue transglutaminase (tTG), with a wide clinical spectrum including symptomatic cases with either intestinal (e.g., chronic diarrhea, weight loss) or extraintestinal features (e.g., anemia, osteoporosis, neurologic disturbances) and silent forms that are occasionally discovered as a result of serological screening [1]. We studied wheat allergy in two children with early diagnosis of CD, who developed immediate allergic symptoms after eating small amounts of wheat flour.

Ontogeny of T cell tolerance to peripherally expressed antigens

Transgenic expression of the influenza virus hemagglutinin (HA) in the pancreatic islet β cells of InsHA mice leads to peripheral tolerance of HA-specific T cells. To examine the onset of tolerance, InsHA mice were immunized with influenza virus A/PR/8 at different ages, and the presence of nontolerant T cells was determined by the induction of autoimmune diabetes. The data revealed a neonatal period wherein T cells were not tolerant and influenza virus infection led to HA-specific β cell destruction and autoimmune diabetes. The ability to induce autoimmunity gradually waned, such that adult mice were profoundly tolerant to viral HA and were protected from diabetes. Because cross-presentation of islet antigens by professional antigen-presenting cells had been reported to induce peripheral tolerance, the temporal relationship between tolerance induction and activation of HA-specific T cells in the lymph nodes draining the pancreas was examined. In tolerant adult mice, but not in 1-week-old neonates, activation and proliferation of HA-specific CD8+ T cells occurred in the pancreatic lymph nodes. Thus, lack of tolerance in the perinatal period correlated with lack of activation of antigen-specific CD8+ T cells. This work provides evidence for the developmental regulation of peripheral tolerance induction.

T cell vaccination induces T cell receptor Vβ-specific Qa-1-restricted regulatory CD8+ T cells

Vaccination of mice with activated autoantigen-reactive CD4+ T cells (T cell vaccination, TCV) has been shown to induce protection from the subsequent induction of a variety of experimental autoimmune diseases, including experimental allergic encephalomyelitis (EAE). Although the mechanisms involved in TCV-mediated protection are not completely known, there is some evidence that TCV induces CD8+ regulatory T cells that are specific for pathogenic CD4+ T cells. Previously, we demonstrated that, after superantigen administration in vivo, CD8+ T cells emerge that preferentially lyse and regulate activated autologous CD4+ T cells in a T cell receptor (TCR) Vβ-specific manner. This TCR Vβ-specific regulation is not observed in β2-microglobulin-deficient mice and is inhibited, in vitro, by antibody to Qa-1. We now show that similar Vβ8-specific Qa-1-restricted CD8+ T cells are also induced by TCV with activated CD4+ Vβ8+ T cells. These CD8+ T cells specifically lyse murine or human transfectants coexpressing Qa-1 and murine TCR Vβ8. Further, CD8+ T cell hybridoma clones generated from B10.PL mice vaccinated with a myelin basic protein-specific CD4+Vβ8+ T cell clone specifically recognize other CD4+ T cells and T cell tumors that express Vβ8 and the syngeneic Qa-1a but not the allogeneic Qa-1b molecule. Thus, Vβ-specific Qa-1-restricted CD8+ T cells are induced by activated CD4+ T cells. We suggest that these CD8+ T cells may function to specifically regulate activated CD4+ T cells during immune responses.

Rpp2, an essential protein subunit of nuclear RNase P, is required for processing of precursor tRNAs and 35S precursor rRNA in Saccharomyces cerevisiae

RPP2, an essential gene that encodes a 15.8-kDa protein subunit of nuclear RNase P, has been identified in the genome of Saccharomyces cerevisiae. Rpp2 was detected by sequence similarity with a human protein, Rpp20, which copurifies with human RNase P. Epitope-tagged Rpp2 can be found in association with both RNase P and RNase mitochondrial RNA processing in immunoprecipitates from crude extracts of cells. Depletion of Rpp2 protein in vivo causes accumulation of precursor tRNAs with unprocessed introns and 5′ and 3′ termini, and leads to defects in the processing of the 35S precursor rRNA. Rpp2-depleted cells are defective in processing of the 5.8S rRNA. Rpp2 immunoprecipitates cleave both yeast precursor tRNAs and precursor rRNAs accurately at the expected sites and contain the Rpp1 protein orthologue of the human scleroderma autoimmune antigen, Rpp30. These results demonstrate that Rpp2 is a protein subunit of nuclear RNase P that is functionally conserved in eukaryotes from yeast to humans.

Transfer of human serum IgG to nonobese diabetic Igμnull mice reveals a role for autoantibodies in the loss of secretory function of exocrine tissues in Sjögren’s syndrome

The NOD (nonobese diabetic) mouse has been studied as an animal model for autoimmune insulin-dependent diabetes and Sjögren’s syndrome. NOD.Igμnull mice, which lack functional B lymphocytes, develop progressive histopathologic lesions of the submandibular and lachrymal glands similar to NOD mice, but in the absence of autoimmune insulitis and diabetes. Despite the focal appearance of T cells in salivary and lachrymal tissues, NOD.Igμnull mice fail to lose secretory function as determined by stimulation of the muscarinic/cholinergic receptor by the agonist pilocarpine, suggesting a role for B cell autoantibodies in mediating exocrine dryness. Infusion of purified serum IgG or F(ab′)2 fragments from parental NOD mice or human primary Sjögren’s syndrome patients, but not serum IgG from healthy controls, alters stimulated saliva production, an observation consistent with antibody binding to neural receptors. Furthermore, human patient IgG fractions competitively inhibited the binding of the muscarinic receptor agonist, [3H]quinuclidinyl benzilate, to salivary gland membranes. This autoantibody activity is lost after preadsorption with intact salivary cells. These findings indicate that autoantibodies play an important part in the functional impairment of secretory processes seen in connection with the autoimmune exocrinopathy of Sjögren’s syndrome.

Definition of MHC and T cell receptor contacts in the HLA-DR4restricted immunodominant epitope in type II collagen and characterization of collagen-induced arthritis in HLA-DR4 and human CD4 transgenic mice

Rheumatoid arthritis (RA) is an autoimmune disease associated with the HLA-DR4 and DR1 alleles. The target autoantigen(s) in RA is unknown, but type II collagen (CII) is a candidate, and the DR4- and DR1-restricted immunodominant T cell epitope in this protein corresponds to amino acids 261–273 (CII 261–273). We have defined MHC and T cell receptor contacts in CII 261–273 and provide strong evidence that this peptide corresponds to the peptide binding specificity previously found for RA-associated DR molecules. Moreover, we demonstrate that HLA-DR4 and human CD4 transgenic mice homozygous for the I-Abβ0 mutation are highly susceptible to collagen-induced arthritis and describe the clinical course and histopathological changes in the affected joints.

T1/ST2 is preferentially expressed on murine Th2 cells, independent of interleukin 4, interleukin 5, and interleukin 10, and important for Th2 effector function

T helper (Th) cells can be categorized according to their cytokine expression. The differential induction of Th cells expressing Th1 and/or Th2 cytokines is key to the regulation of both protective and pathological immune responses. Cytokines are expressed transiently and there is a lack of stably expressed surface molecules, significant for functionally different types of Th cells. Such molecules are of utmost importance for the analysis and selective functional modulation of Th subsets and will provide new therapeutic strategies for the treatment of allergic or autoimmune diseases. To this end, we have identified potential target genes preferentially expressed in Th2 cells, expressing interleukin (IL)-4, IL-5, and/or IL-10, but not interferon-γ. One such gene, T1/ST2, is expressed stably on both Th2 clones and Th2-polarized cells activated in vivo or in vitro. T1/ST2 expression is independent of induction by IL-4, IL-5, or IL-10. T1/ST2 plays a critical role in Th2 effector function. Administration of either a mAb against T1/ST2 or recombinant T1/ST2 fusion protein attenuates eosinophilic inflammation of the airways and suppresses IL-4 and IL-5 production in vivo following adoptive transfer of Th2 cells.

Gene therapy in allergic encephalomyelitis using myelin basic protein-specific T cells engineered to express latent transforming growth factor-β1

A myelin basic protein (MBP)-specific BALB/c T helper 1 (Th1) clone was transduced with cDNA for murine latent transforming growth factor-β1 (TGF-β1) by coculture with fibroblasts producing a genetically engineered retrovirus. When SJL x BALB/c F1 mice, immunized 12–15 days earlier with proteolipid protein in complete Freund’s adjuvant, were injected with 3 × 106 cells from MBP-activated untransduced cloned Th1 cells, the severity of experimental allergic encephalomyelitis (EAE) was slightly increased. In contrast, MBP-activated (but not resting) latent TGF-β1-transduced T cells significantly delayed and ameliorated EAE development. This protective effect was negated by simultaneously injected anti-TGF-β1. The transduced cells secreted 2–4 ng/ml of latent TGF-β1 into their culture medium, whereas control cells secreted barely detectable amounts. mRNA profiles for tumor necrosis factor, lymphotoxin, and interferon-γ were similar before and after transduction; interleukin-4 and -10 were absent. TGF-β1-transduced and antigen-activated BALB/c Th1 clones, specific for hemocyanin or ovalbumin, did not ameliorate EAE. Spinal cords from mice, taken 12 days after receiving TGF-β1-transduced, antigen-activated cells, contained detectable amounts of TGF-β1 cDNA. We conclude that latent TGF-β1-transduced, self-reactive T cell clones may be useful in the therapy of autoimmune diseases.