Project description:With the burgeoning immunological data in the scientific literature, scientists must increasingly rely on Internet resources to inform and enhance their work. Here we provide a brief overview of the adaptive immune response and summaries of immunoinformatics resources, emphasizing those with Web interfaces. These resources include searchable databases of epitopes and immune-related molecules, and analysis tools for T cell and B cell epitope prediction, vaccine design, and protein structure comparisons. There is an agreeable synergy between the growing collections in immune-related databases and the growing sophistication of analysis software; the databases provide the foundation for developing predictive computational tools, which in turn enable more rapid identification of immune responses to populate the databases. Collectively, these resources contribute to improved understanding of immune responses and escape, and evolution of pathogens under immune pressure. The public health implications are vast, including designing vaccines, understanding autoimmune diseases, and defining the correlates of immune protection.
Project description:Genome-wide association studies (GWASs) have been used to great effect to identify genetic susceptibility loci for complex disease. A series of GWAS and meta-analyses have informed the discovery of over 100 loci for rheumatoid arthritis (RA). In common with findings in other autoimmune diseases the lead signals for the majority of these loci do not map to known gene sequences. In order to realise the benefit of investment in GWAS studies it is vital we determine how disease associated alleles function to influence disease processes. This is leading to rapid development in our knowledge as to the function of non-coding regions of the genome. Here we consider possible functional mechanisms for intergenic RA-associated variants which lie within lncRNA sequences.
Project description:To provide an overview of the genetics of type 2 diabetes in the context of recent progress in the understanding of the genetic architecture of the disease and its applicability to the pathogenesis of the disease as well as efforts to individualize therapy in type 2 diabetes. Efforts are underway to understand how these loci alter measurable physiologic processes in nondiabetic humans. However, it is important to understand the potential pitfalls in such studies and the limitations underlying measurement of insulin secretion and action using qualitative methodologies.The availability of large population-based cohorts and the ease with which large numbers of common genetic variants can be genotyped has enabled the discovery of multiple loci and pathways associated with type 2 diabetes. Recent efforts examining quantitative traits such as fasting glucose concentrations have led to the discovery of other genes likely to be important in the development of diabetes.The past 4 years have witnessed a significant increase in our understanding of genetic predisposition to type 2 diabetes. Hopefully more progress will be made in applying this knowledge to the pathophysiology of type 2 diabetes in the coming years.
Project description:Type 1 diabetes (T1D) results from immune-mediated loss of pancreatic beta cells leading to insulin deficiency. It is the most common form of diabetes in children, and its incidence is on the rise. This article reviews the current knowledge on the genetics of T1D. In particular, we discuss the influence of HLA and non-HLA genes on T1D risk and disease progression through the preclinical stages of the disease, and the development of genetic scores that can be applied to disease prediction. Racial/ethnic differences, challenges and future directions in the genetics of T1D are also discussed.
Project description:BackgroundType 1 diabetes, a multifactorial disease with a strong genetic component, is caused by the autoimmune destruction of pancreatic β cells. The major susceptibility locus maps to the HLA class II genes at 6p21, although more than 40 non-HLA susceptibility gene markers have been confirmed.ContentAlthough HLA class II alleles account for up to 30%-50% of genetic type 1 diabetes risk, multiple non-MHC loci contribute to disease risk with smaller effects. These include the insulin, PTPN22, CTLA4, IL2RA, IFIH1, and other recently discovered loci. Genomewide association studies performed with high-density single-nucleotide-polymorphism genotyping platforms have provided evidence for a number of novel loci, although fine mapping and characterization of these new regions remain to be performed. Children born with the high-risk genotype HLADR3/4-DQ8 comprise almost 50% of children who develop antiislet autoimmunity by the age of 5 years. Genetic risk for type 1 diabetes can be further stratified by selection of children with susceptible genotypes at other diabetes genes, by selection of children with a multiple family history of diabetes, and/or by selection of relatives that are HLA identical to the proband.SummaryChildren with the HLA-risk genotypes DR3/4-DQ8 or DR4/DR4 who have a family history of type 1 diabetes have more than a 1 in 5 risk for developing islet autoantibodies during childhood, and children with the same HLA-risk genotype but no family history have approximately a 1 in 20 risk. Determining extreme genetic risk is a prerequisite for the implementation of primary prevention trials, which are now underway for relatives of individuals with type 1 diabetes.
Project description:Admixture mapping is based on the hypothesis that differences in disease rates between populations are due in part to frequency differences in disease-causing genetic variants. In admixed populations, these genetic variants occur more often on chromosome segments inherited from the ancestral population with the higher disease variant frequency. A genome scan for disease association requires only enough markers to identify the ancestral chromosome segments; for recently admixed populations, such as African Americans, 1,500-2,500 ancestry-informative markers (AIMs) are sufficient. The method was proposed over 50 years ago, but the AIM panels and statistical methods required have only recently become available. Since the first admixture scan in 2005, the genetic bases for a range of diseases/traits have been identified by admixture mapping. Here, we provide a historical perspective, review AIM panels and software packages, and discuss recent successes and unexpected insights into human diseases that exhibit disparate rates across human populations.
Project description:The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.
Project description:Since fulminant type 1 diabetes was reported as a distinct subtype of type 1 diabetes in 2000, the Committee on Type 1 diabetes, Japan Diabetes Society has continuously recruited patients and conducted genomic research to elucidate the genetic basis of fulminant type 1 diabetes. The contribution of the human leukocyte antigen complex (HLA) to genetic susceptibility to fulminant type 1 diabetes was compared with that of other subtypes in 2009. The alleles and haplotypes associated with fulminant type 1 diabetes were found to be different from acute-onset and slowly progressive type 1 diabetes. DRB1*15:01-DQB1*06:02, a protective haplotype against acute-onset type 1 diabetes, does not provide protection against fulminant type 1 diabetes and DRB1*08:02-DQB1*03:02, a susceptible haplotype to acute-onset type 1 diabetes, does not confer susceptibility to fulminant type 1 diabetes. Recently, the first genome-wide association study (GWAS) of fulminant type 1 diabetes was performed in Japanese individuals. A strong association was observed with multiple single nucleotide polymorphisms (SNPs) in the HLA region, and the strongest association was observed with rs9268853 in the class II DR region. In addition, 11 SNPs outside the HLA region showed some evidence of association with the disease. In particular, rs11170445 in CSAD/lnc-ITGB7-1 on chromosome 12q13.13 showed an association at a genome-wide significance level. Fine mapping revealed that rs3782151 in CSAD/lnc-ITGB7-1 showed the lowest P value. CSAD/lnc-ITGB7-1 was found to be strongly associated with susceptibility to fulminant, but not classical, autoimmune type 1 diabetes, implicating this locus in the distinct phenotype of fulminant type 1 diabetes.
Project description:The global epidemic of type 2 diabetes mellitus (T2D) is one of the most challenging problems of the 21(st) century leading cause of and the fifth death worldwide. Substantial evidence suggests that T2D is a multifactorial disease with a strong genetic component. Recent genome-wide association studies (GWAS) have successfully identified and replicated nearly 75 susceptibility loci associated with T2D and related metabolic traits, mostly in Europeans, and some in African, and South Asian populations. The GWAS serve as a starting point for future genetic and functional studies since the mechanisms of action by which these associated loci influence disease is still unclear and it is difficult to predict potential implication of these findings in clinical settings. Despite extensive replication, no study has unequivocally demonstrated their clinical role in the disease management beyond progression to T2D from impaired glucose tolerance. However, these studies are revealing new molecular pathways underlying diabetes etiology, gene-environment interactions, epigenetic modifications, and gene function. This review highlights evolving progress made in the rapidly moving field of T2D genetics that is starting to unravel the pathophysiology of a complex phenotype and has potential to show clinical relevance in the near future.
Project description:Concurrent with the development of recombinant factor replacement products, the characterization of the F9 and F8 genes over 3 decades ago allowed for the development of recombinant factor products and made the hemophilias a target disease for gene transfer. The progress of hemophilia gene therapy has been announced in 3 American Society of Hematology scientific plenary sessions, including the first "cure" in a large animal model of hemophilia B in 1998, first in human sustained vector-derived factor IX activity in 2011, and our clinical trial results reporting sustained vector-derived factor IX activity well into the mild or normal range in 2016. This progression to clinically meaningful success combined with numerous ongoing recombinant adeno-associated virus (rAAV)-mediated hemophilia gene transfer clinical trials suggest that the goal of gene therapy to alter the paradigm of hemophilia care may soon be realized. Although several novel therapeutics have recently emerged for hemophilia, gene therapy is unique in its potential for a one-time disease-altering, or even curative, treatment. This review will focus on the prior progress and current clinical trial investigation of rAAV-mediated gene transfer for hemophilia A and B.