The Immunogenetic Architecture of Autoimmune Disease

The development of most autoimmune diseases includes a strong heritable component. This genetic contribution to disease ranges from simple Mendelian inheritance of causative alleles to the complex interactions of multiple weak loci influencing risk. The genetic variants responsible for disease are being discovered through a range of strategies from linkage studies to genome-wide association studies. Despite the rapid advances in genetic analysis, substantial components of the heritable risk remain unexplained, either owing to the contribution of an as-yet unidentified, “hidden,” component of risk, or through the underappreciated effects of known risk loci. Surprisingly, despite the variation in genetic control, a great deal of conservation appears in the biological processes influenced by risk alleles, with several key immunological pathways being modified in autoimmune diseases covering a broad spectrum of clinical manifestations. The primary translational potential of this knowledge is in the rational design of new therapeutics to exploit the role of these key pathways in influencing disease. With significant further advances in understanding the genetic risk factors and their biological mechanisms, the possibility of genetically tailored (or “personalized”) therapy may be realized.Autoimmune diseases affect a significant proportion of the population, with >4% of the European population suffering from one or more of these disorders (Vyse and Todd 1996; Cooper et al. 2009; Eaton et al. 2010). Although all autoimmune diseases share similarities in the basic immunological mechanisms, in other aspects, such as clinical manifestation and age of onset, individual diseases vary widely. A few rare autoimmune diseases with Mendelian inheritance patterns within families occur including APS-1 (autoimmune polyendocrine syndrome type 1), IPEX (immunodysregulation, polyendocrinopathy, and enteropathy X-linked) syndrome, and ALPS (autoimmune lymphoproliferative syndrome). Most autoimmune diseases are, however, multifactorial in nature, with susceptibility controlled by multiple genetic and environmental factors.The genetic component of more common autoimmune diseases can be calculated in several different manners, including the sibling recurrence risk (λ_s) and the twin concordance rate. The sibling recurrence risk is the ratio of the lifetime risk in siblings of patients to the lifetime population risk, whereas the twin concordance rate measures the proportion of the siblings of affected twins that are also affected. Most common autoimmune diseases, such as multiple sclerosis (MS), type 1 diabetes (T1D), rheumatoid arthritis (RA), and inflammatory bowel disease (IBD) are characterized by a sibling recurrence risk between 6 and 20 (Vyse and Todd 1996), and concordance rates of 25%–50% in monozygotic twins and 2%–12% in dizygotic twins (Cooper et al. 1999). A substantial proportion of relatives may also have subclinical evidence of autoimmunity without developing clinically overt disease. For example, 19% of healthy siblings of MS patients show antibody production in the cerebrospinal fluid, compared to 4% of unrelated healthy controls (Haghighi et al. 2000), whereas 4% of healthy first-degree relatives display lesions that are indistinguishable from those seen in patients and are not seen in unrelated healthy controls (De Stefano et al. 2006). Furthermore, comorbidity with the development of several autoimmune diseases in the same patient and clustering of several autoimmune diseases within families above what is expected by chance appear common (Cooper et al. 2009; Zhernakova et al. 2009). Together these data show a strong genetic component to autoimmune disease development.     

性别与自身免疫性疾病

自身免疫性疾病在人群中感染率5-10％,具有明显的性别差异,女性患者显著高于男性,具体机制仍未研究清楚。研究发现。除了机体自身的遗传易感体质外,雌激素,微嵌合体和性染色体都与自身免疫性疾病发病有关。     

Para-Clinical and Immunological Evaluation in Buerger's Disease as a Suspected Autoimmune Disease: Case Series

Background:Autoimmunity causes the loss of normal immune homeostasis and involves the presence of autoantibodies and inflammation. Thromboangiitis obliterans or Buerger''s disease (BD) refers to a type of vascular obstructive syndrome, with tobacco exposure accounting for disease formation and progression. However, the current understanding of autoimmunity is unclear in the context of BD, and the scientific findings are not enough to support autoimmune mechanisms. This study was aimed at investigating autoimmunity factors in patients with BD.Methods:Clinical and experimental examinations were performed on 80 patients with BD. The diagnostic work-up for autoimmunity was composed of IgM rheumatoid factor (RF), anti-nuclear antibodies (ANA), The erythrocyte sedimentation rate (ESR), anti-cyclic citrullinated peptide (CCP) antibodies, Antiphospholipid antibodies (APA), Anti-cardiolipin antibodies (ACLA), anti-double-stranded DNA (ds-DNA), and extractable nuclear antigen (ENA) profile. Immunomarkers were detected using the quantitative enzyme-linked immunosorbent assay (ELISA).Results:Raynaud''s phenomenon (84.93%), cold sensitivity (76.25%), and claudication (73.75%) were the most common symptoms in the BD patients. Also, 64.29% represented with high ANA levels and positive RF, while 42.11% were found with increased ANA and ESR levels. The ANA/RF positive BD patients had ESR> 15 mm/hr and a high prevalence of cold sensitivity, claudication, and Raynaud''s phenomenon (p> 0.05).Conclusion:There is a possibility of a non-specific autoimmune disposition among BD patients. RF and ANA could be considered for predicting disease progression.Key Words: Antibodies, Autoimmunity, Buerger''s Disease, Immune System     

The Yeast Protein Database (YPD): a curated proteome database for Saccharomyces cerevisiae.

The Yeast Protein Database (YPD) is a curated database for the proteome of Saccharomyces cerevisiae . It consists of approximately 6000 Yeast Protein Reports, one for each of the known or predicted yeast proteins. Each Yeast Protein Report is a one-page presentation of protein properties, annotation lines that summarize findings from the literature, and references. In the past year, the number of annotation lines has grown from 25 000 to approximately 35 000, and the number of articles curated has grown from approximately 3500 to >5000. Recently, new data types have been included in YPD: protein-protein interactions, genetic interactions, and regulators of gene expression. Finally, a new layer of information, the YPD Protein Minireviews, has recently been introduced. The Yeast Protein Database can be found on the Web at http://www.proteome.com/YPDhome. html     

The HLA Region and Autoimmune Disease: Associations and Mechanisms of Action

The HLA region encodes several molecules that play key roles in the immune system. Strong association between the HLA region and autoimmune disease (AID) has been established for over fifty years. Association of components of the HLA class II encoded HLA-DRB1-DQA1-DQB1 haplotype has been detected with several AIDs, including rheumatoid arthritis, type 1 diabetes and Graves’ disease. Molecules encoded by this region play a key role in exogenous antigen presentation to CD4+ Th cells, indicating the importance of this pathway in AID initiation and progression. Although other components of the HLA class I and III regions have also been investigated for association with AID, apart from the association of HLA-B*27 with ankylosing spondylitis, it has been difficult to determine additional susceptibility loci independent of the strong linkage disequilibrium (LD) with the HLA class II genes. Recent advances in the statistical analysis of LD and the recruitment of large AID datasets have allowed investigation of the HLA class I and III regions to be re-visited. Association of the HLA class I region, independent of known HLA class II effects, has now been detected for several AIDs, including strong association of HLA-B with type 1 diabetes and HLA-C with multiple sclerosis and Graves’ disease. These results provide further evidence of a possible role for bacterial or viral infection and CD8+ T cells in AID onset. The advances being made in determining the primary associations within the HLA region and AIDs will not only increase our understanding of the mechanisms behind disease pathogenesis but may also aid in the development of novel therapeutic targets in the future.Key Words: Genes, autoimmunity & HLA     

The Molecular Biology Database Collection: an updated compilation of biological database resources

The Molecular Biology Database Collection is an online resource listing key databases of value to the biological community. This Collection is intended to bring fellow scientists' attention to high-quality databases that are available throughout the world, rather than just be a lengthy listing of all available databases. As such, this up-to-date listing is intended to serve as the initial point from which to find specialized databases that may be of use in biological research. The databases included in this Collection provide new value to the underlying data by virtue of curation, new data connections or other innovative approaches. Short, searchable summaries of each of the databases included in the Collection are available through the Nucleic Acids Research Web site, at http://www. nar.oupjournals.org.     

The BioImage Database Project: organizing multidimensional biological images in an object-relational database

The BioImage Database Project collects and structures multidimensional data sets recorded by various microscopic techniques relevant to modern life sciences. It provides, as precisely as possible, the circumstances in which the sample was prepared and the data were recorded. It grants access to the actual data and maintains links between related data sets. In order to promote the interdisciplinary approach of modern science, it offers a large set of key words, which covers essentially all aspects of microscopy. Nonspecialists can, therefore, access and retrieve significant information recorded and submitted by specialists in other areas. A key issue of the undertaking is to exploit the available technology and to provide a well-defined yet flexible structure for dealing with data. Its pivotal element is, therefore, a modern object relational database that structures the metadata and ameliorates the provision of a complete service. The BioImage database can be accessed through the Internet.     

Olfactory Receptor Database: a database of the largest eukaryotic gene family.

The Olfactory Receptor Database (ORDB) is a WWW-accessible database that stores data on Olfactory Receptor-like molecules (ORs) and has been open to the public since June 1996. It contains a public and a private area. The public area includes published DNA and protein sequence data for ORs, links to OR models and data on their expression, chromosomal localization and source organism, as well as (i) links to bibliography through PubMed and (ii) interactive WWW-based tools, such as BLAST homology searching. The private area functions as a service to laboratories that are actively cloning receptors. Source laboratories enter the sequences of the receptor clones they have characterized to the private database and can search for identical or near identical OR sequences in both public and private databases. If another laboratory has cloned and deposited an identical or closely matching sequence there are means for communication between the laboratories to help avoid duplication of work. ORDB is available via the WWW at http://crepe.med.yale.edu/ORDB/HTML     

GXD: a gene expression database for the laboratory mouse. The Gene Expression Database Group.

The Gene Expression Database (GXD) is a community resource that stores and integrates expression information for the laboratory mouse, with a particular emphasis on mouse development, and makes these data freely available in formats appropriate for comprehensive analysis. GXD is implemented as a relational database and integrated with the Mouse Genome Database (MGD) to enable global analysis of genotype, expression and phenotype information. Interconnections with sequence databases and with databases from other species further extend GXD's utility for the analysis of gene expression data. GXD is available through the Mouse Genome Informatics Web Site at http://www.informatics.jax.org/     

Desmosomal Cadherins and Signaling: Lessons from Autoimmune Disease

Abstract

Autoantibodies from patients suffering from the autoimmune blistering skin disease pemphigus can be applied as tools to study desmosomal adhesion. These autoantibodies targeting the desmosomal cadherins desmoglein (Dsg) 1 and Dsg3 cause disruption of desmosomes and loss of intercellular cohesion. Although pemphigus autoantibodies were initially proposed to sterically hinder desmosomes, many groups have shown that they activate signaling pathways which cause disruption of desmosomes and loss of intercellular cohesion by uncoupling the desmosomal plaque from the intermediate filament cytoskeleton and/or by interfering with desmosome turnover. These studies demonstrate that desmogleins serve as receptor molecules to transmit outside-in signaling and demonstrate that desmosomal cadherins have functions in addition to their adhesive properties. Two central molecules regulating cytoskeletal anchorage and desmosome turnover are p38MAPK and PKC. As cytoskeletal uncoupling in turn enhances Dsg3 depletion from desmosomes, both mechanisms reinforce one another in a vicious cycle that compromise the integrity and number of desmosomes.     

Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network

MOTIVATION: There is a general scientific need to be able to identify and evaluate what any given set of 'objects' (e.g. genes, phenotypes, chemicals, diseases) has in common. Whether it is to classify, expand upon or identify commonalities and functional groupings, informational needs can be diverse and the best source to identify relationships among a potentially heterogeneous set of objects is the scientific literature. RESULTS: We first establish a network of related objects by their co-occurrence within MEDLINE records. A set of objects within this network can then be queried to identify shared relationships, and a method is presented to score their statistical relevance by comparing observed frequencies with what would be expected in a random network model. Using Gene Ontology (GO) categories, we demonstrate that this method enables a quantitative ranking of the 'cohesiveness' of a set of objects and, importantly, allows other objects related to this set to be identified and evaluated for their 'cohesion' to it. Supplemental information: A list of ranked genes related to each GO category analyzed can be found at http://innovation.swmed.edu/IRIDESCENT/GO_relationships.htm     

Autoimmune Thyroid Disease: A Risk Factor for Thyroid Cancer

ObjectiveTo examine the relationship between clinical markers of autoimmune thyroid disease and the risk of thyroid cancer in patients with thyroid nodules.MethodsA retrospective cohort analysis was performed in a single clinical practice. In 2, 500 consecutive patients, fine-needle aspiration biopsy (FNAB) was performed on all 3, 658 ultrasonography-positive thyroid nodules that were ≥ 1.0 cm in diameter or ≥ 0.5 cm in diameter with ultrasound features suspicious for thyroid cancer. Serum concentrations of thyroglobulin antibodies (TgAb), thyroid peroxidase antibodies, and thyroid-stimulating hormone were measured before FNAB. Diagnosis of thyroid cancer was based on pathologic analysis of thyroidectomy tissue. Associations of thyroid cancer with the independent variables were determined by multivariate logistic regression analysis and reported as the adjusted odds ratio (OR) with the 95% confidence interval (CI).ResultsThere were 202 patients with malignant thyroid nodules, 51 patients with microscopic unsuspected thyroid cancer distal to the nodule under investigation (found at thyroidectomy), and 2, 247 patients with benign thyroid nodules. To evaluate the association of clinical markers for autoimmune thyroid disease with thyroid cancer, we included all 253 patients with thyroid cancer in the malignant cohort. Thyroid cancer was associated with elevated levels of TgAb (OR = 1.57; CI = 1.11 to 2.23) and age < 55 years (OR = 2.01; CI = 1.45 to 2.78), and a strong trend was demonstrated for association with male sex (OR = 1.45; CI = 0.99 to 2.12). Thyroid cancer was not associated with elevated levels of thyroid peroxidase antibodies.ConclusionIn patients who have thyroid nodules with indications for FNAB, elevated levels of TgAb are associated with thyroid cancer. (Endocr Pract. 2011;17: 201-209)     

检测抗核抗体谱对自身免疫性疾病的临床应用

目的:分析自身免疫性疾病患者抗核抗体谱检测结果,探讨抗核抗体谱检测在自身免疫性疾病诊断中的应用。方法:分别采用间接免疫荧光法和免疫印迹法检测130例自身免疫性疾病患者和20例健康人的ANA和抗核抗体谱。结果:ANA在各种自身免疫性疾病中均有一定的阳性检出率,ANA在SLE中的检出率最高,阳性率为89.6%,其次为ITP、MCTD和SS。抗核抗体谱中的各种自身抗体在不同的自身免疫性疾病中有不同的敏感性和特异性。结论:采用间接免疫荧光法对ANA的检测对自身免疫性疾病有重要的筛查意义,抗核抗体谱检测对自身免疫性疾病的诊断有重要意义。     

The Database of European Forest Insect and Disease Disturbances: DEFID2

Insect and disease outbreaks in forests are biotic disturbances that can profoundly alter ecosystem dynamics. In many parts of the world, these disturbance regimes are intensifying as the climate changes and shifts the distribution of species and biomes. As a result, key forest ecosystem services, such as carbon sequestration, regulation of water flows, wood production, protection of soils, and the conservation of biodiversity, could be increasingly compromised. Despite the relevance of these detrimental effects, there are currently no spatially detailed databases that record insect and disease disturbances on forests at the pan-European scale. Here, we present the new Database of European Forest Insect and Disease Disturbances (DEFID2). It comprises over 650,000 harmonized georeferenced records, mapped as polygons or points, of insects and disease disturbances that occurred between 1963 and 2021 in European forests. The records currently span eight different countries and were acquired through diverse methods (e.g., ground surveys, remote sensing techniques). The records in DEFID2 are described by a set of qualitative attributes, including severity and patterns of damage symptoms, agents, host tree species, climate-driven trigger factors, silvicultural practices, and eventual sanitary interventions. They are further complemented with a satellite-based quantitative characterization of the affected forest areas based on Landsat Normalized Burn Ratio time series, and damage metrics derived from them using the LandTrendr spectral–temporal segmentation algorithm (including onset, duration, magnitude, and rate of the disturbance), and possible interactions with windthrow and wildfire events. The DEFID2 database is a novel resource for many large-scale applications dealing with biotic disturbances. It offers a unique contribution to design networks of experiments, improve our understanding of ecological processes underlying biotic forest disturbances, monitor their dynamics, and enhance their representation in land-climate models. Further data sharing is encouraged to extend and improve the DEFID2 database continuously. The database is freely available at https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/FOREST/DISTURBANCES/DEFID2/ .