Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0011849 (diabetes)
 277,896 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Two clinically most widely used agglutination tests, Thymune and Serodia distributed by Wellcome and Fjirebio/Ames, respectively, to determine thyroid autoantibodies were compared. The Serodia tests seemed to be considerably more sensitive than the corresponding Thymune tests; first, Serodia tests resulted in several new positive samples and second, 16% and 30% of positive thyroglobulin and thyroid microsomal antibodies by Serodia resulted in at least 16 times higher titres, respectively. Over 300 healthy blood donor sera were used to determine the occurrence of thyroid autoantibodies in normal population. Titre limits of 400 and 6400 in anti-thyroglobulin and anti-microsomal antibodies were adapted for clinical use, respectively, even though the results suggested that the lower titre limits could be applied for males and subjects younger than 40 years. These defined titre limits were applied to examine randomly selected clinical patient material gathered during 1 year. The main patient groups identified included patients with chronic thyroiditis, thyroid malignancy, diabetes. Graves' disease and rheumatoid diseases as well as patients with vaguely defined clinical conditions. Without the aid of antithyroglobulin antibodies only one patient with chronic thyroiditis would have been missed if thyroid microsomal antibodies were used alone. Thus, in general clinical practise thyroid microsomal antibodies can be used as a sole diagnostic test for autoimmune thyroid diseases.
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PMID:Performance of two agglutination techniques in the detection of thyroid antibodies and assessment of their clinical significance. 208 27

An account is given of the development of tests for the bio-assay of insulin and the progress made, at the Wellcome Foundation Limited, during the last 30 years in reducing the number of animals used in the testing of insulin for the treatment of Diabetes Mellitus. The progressive evolution of methods shows how the number of mice used per sample has already been reduced five-fold and an ongoing development of in vitro methods, particularly high-performance liquid chromatography (HPLC), has enabled Wellcome to recommend to the regulatory authorities alternative procedures to replace animal testing.
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PMID:Bio-assays for the analysis of insulin. 248 20

Adis CommentsPramlintide [AC 0137, AC 137, tripro-amylin, Symlin] is a synthetic human amylin analogue with proline substitutions at positions 25, 28 and 29, which limits the self-aggregation seen with native amylin. Pramlintide improves glycaemic control, and appears to reduce postprandial blood glucose peaks and flatten the glucose peaks and troughs observed in diabetic patients. The reduction of hypoglycaemia would be an immediate advantage, and the reduction of hyperglycaemia could potentially prevent diabetic complications. Development - US: Amylin has submitted an NDA in the US for pramlintide acetate (Symlin trade mark ) as an adjunctive therapy for the treatment of type 1 and type 2 diabetes mellitus. However, the FDA's Endocrinologic and Metabolic Drugs Advisory Committee at their meeting on 26 July 2001, voted not to recommend approval of pramlintide for type 1 and type 2 diabetes. Although eight out of nine Committee members were convinced of the potential of pramlintide therapy, the Committee expressed concerns regarding safety issues and requested additional data addressing these concerns. Finally, on 12 October 2001, Amylin received an 'approvable letter' for Symlin- for the treatment of diabetes. In April 2002, Amylin commenced a trial in 250 patients with type 1 diabetes to evaluate the safety issues regarding cases of severe hypoglycaemia with pramlintide in combination with insulin reported in this group of patients. The trial will investigate dose titration in the initial first month of the treatment period combined with insulin adjustment for the optimisation of glucose control. Patients are then treated for 6 months at a steady-state dose of pramlintide or placebo, accompanied by the additional insulin adjustments. Amylin has completed patient enrolment in September 2002. Final approval is subject to satisfactory results from this safety and dose titration study and the four small pharmacology studies already completed or underway. Amylin plans to file an amendment to the pramlintide's NDA in the Q1 of 2003. Development - non-USA: A wholly owned subsidiary of Amylin Pharmaceuticals, Amylin Europe, filed a regulatory submission with the European Agency for Evaluation of Medicinal Products (EMEA) and Switzerland for pramlintide for the treatment of both type 1 and type 2 diabetes under the centralised procedure. Amylin completed pivotal phase III clinical trials with pramlintide acetate (Symlin trade mark ) for the treatment of type 1 and type 2 diabetes mellitus in North America and Europe. However, in October 2002, Amylin announced that following consultation with the Committee for Proprietary Medicinal Products (CPMP) of the EMEA, it has found that additional information is necessary to proceed with review of the MAA for pramlintide for diabetes. Since, the centralised procedure does not allow the adding of new information to the application that is already under review, Amylin has decided to withdraw the MAA for pramlintide. The company will continue discussions with the EMEA to clarify the information required for a resubmission of the application. The submission for pramlintide in Switzerland is currently under review. In a separate phase II programme, Amylin is investigating the use of pramlintide in type 2 diabetes mellitus patients who are not achieving satisfactory results with oral hypoglycaemic agents but who have not progressed to using insulin. Collaborations: Pramlintide was under joint development with Amylin Pharmaceuticals and Johnson and Johnson, as an injectable partner hormone for insulin for the treatment of both type 1 and type 2 diabetes mellitus. The terms of the agreement between Amylin and Johnson and Johnson were that Amylin had primary responsibility for development and regulatory submissions, while Johnson and Johnson had primary responsibility for marketing; development costs and eventual profits were to be shared equally. Later, Johnson and Johnson decided to terminate the collaboration to commercialise pramlintide. An earlier development collaboration betweion between Amylin and Glaxo Wellcome was also discontinued. However, Amylin is in new ongoing discussions with collaborative partners for pramlintide in Europe and Japan. Amylin has signed an agreement with CP Pharmaceuticals in the UK to manufacture pramlintide.
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PMID:Pramlintide: (AC 137, AC 0137, Symlin, Tripro-Amylin). 1253 23

Dr Winkelmann is the Head of the Cooperation Unit for Pharmacogenomics and Applied Genomics in Heidelberg, which was founded in 2001 by the Department of Internal Medicine VI and the Coordination Centre for Clinical Trials at the University of Heidelberg. His main interests are sophisticated phenotyping procedures for patient characterization and the conduct of multicenter clinical trials according to international standards with state-of-the-art data management. He currently applies new genomic tools in order to achieve progress in personalized medicine using collaborating networks of general practitioners for patient enrollment. The focus of his research group is on the common complex genetic cardiovascular and metabolic diseases ranging from coronary artery disease, dyslipidemia and hypertension, to metabolic syndrome and diabetes mellitus. In collaboration with partners from biotech, the genomic techniques used in clinical studies include haplotyping of candidate genes, gene expression profiling of peripheral leucocytes and proteomics in order to identify new biomarkers of effect in therapeutic studies or pathway/target gene identification in disease-specific family studies using microarray-based linkage approaches. An innovative web-based remote data entry system with an integrated pedigree drawing tool is used in the family studies. Dr Winkelmann is also involved as the clinical database coordinator for a European Framework VI research initiative of leading European centers in cardiovascular genetics for identification of risk genes for atherothrombosis in coronary artery disease by transcriptome and proteome analysis and high throughput exon resequencing at the Wellcome Trust Sanger Institute, Cambridge, UK.
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PMID:Pharmacogenomics, genetic testing and ethnic variability: tackling the ethical questions. 1294 62

The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes.
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PMID:Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. 1746 49

There has been a recent spate of genome-wide association studies reporting new associations between sequence variations on the human genome and common diseases such as diabetes. These associations can lead to a better understanding of the etiology of the disease, help with diagnosis, predict drug response and identify potential new targets for therapy. Many of the recent findings were reported at the Nature Genetics/Wellcome Trust conference on the Genomics of Common Diseases, held July 7-10, 2007, at the Wellcome Trust Conference Centre, Cambridge, United Kingdom, and have recently been published. This meeting summary focuses on some of the recently described associations between genomic variation and common diseases.
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PMID:Genomics of common diseases. 1799 71

Several genome-wide association studies (GWAS) have been published on various complex diseases. Although, new loci are found to be associated with these diseases, still only very little of the genetic risk for these diseases can be explained. As GWAS are still underpowered to find small main effects, and gene-gene interactions are likely to play a role, the data might currently not be analyzed to its full potential. In this study, we evaluated alternative methods to study GWAS data. Instead of focusing on the single nucleotide polymorphisms (SNPs) with the highest statistical significance, we took advantage of prior biological information and tried to detect overrepresented pathways in the GWAS data. We evaluated whether pathway classification analysis can help prioritize the biological pathways most likely to be involved in the disease etiology. In this study, we present the various benefits and limitations of pathway-classification tools in analyzing GWAS data. We show multiple differences in outcome between pathway tools analyzing the same dataset. Furthermore, analyzing randomly selected SNPs always results in significantly overrepresented pathways, large pathways have a higher chance of becoming statistically significant and the bioinformatics tools used in this study are biased toward detecting well-defined pathways. As an example, we analyzed data from two GWAS on type 2 diabetes (T2D): the Diabetes Genetics Initiative (DGI) and the Wellcome Trust Case Control Consortium (WTCCC). Occasionally the results from the DGI and the WTCCC GWAS showed concordance in overrepresented pathways, but discordance in the corresponding genes. Thus, incorporating gene networks and pathway classification tools into the analysis can point toward significantly overrepresented molecular pathways, which cannot be picked up using traditional single-locus analyses. However, the limitations discussed in this study, need to be addressed before these methods can be widely used.
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PMID:Using genome-wide pathway analysis to unravel the etiology of complex diseases. 1923 86

The current paradigm within genetic diagnostics is to test individuals only at loci known to affect risk of complex disease-yet the technology exists to genotype an individual at thousands of loci across the genome. We investigated whether information from genome-wide association studies could be harnessed to improve discrimination of complex disease affection status. We employed genome-wide data from the Wellcome Trust Case Control Consortium to test this hypothesis. Each disease cohort together with the same set of controls were split into two samples-a 'Training Set', where thousands of SNPs that might predispose to disease risk were identified and a 'Prediction Set', where the discriminatory ability of these SNPs was assessed. Genome-wide scores consisting of, for example, the total number of risk alleles an individual carries was calculated for each individual in the prediction set. Case-control status was regressed on this score and the area under the receiver operator characteristic curve (AUC) estimated. In most cases, a liberal inclusion of SNPs in the genome-wide score improved AUC compared with a more stringent selection of top SNPs, but did not perform as well as selection based upon established variants. The addition of genome-wide scores to known variant information produced only a limited increase in discriminative accuracy but was most effective for bipolar disorder, coronary heart disease and type II diabetes. We conclude that this small increase in discriminative accuracy is unlikely to be of diagnostic or predictive utility at the present time.
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PMID:Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk. 1955 58

The advent of genome-wide association (GWA) studies has revolutionized the detection of disease loci and provided abundant evidence for previously undetected disease loci that can be pooled together in meta-analysis studies or used to design follow-up studies. A total of 1715 SNPs from the Wellcome Trust Case Control Consortium GWA study of type I diabetes (T1D) were selected and a follow-up study was conducted in 1410 affected sib-pair families assembled by the Type I Diabetes Genetics Consortium. In addition to the support for previously identified loci (PTPN22/1p13; ERBB3/12q13; SH2B3/12q24; CLEC16A/16p13; UBASH3A/21q22), evidence supporting two new and distinct chromosome locations associated with T1D was observed: FHOD3/18q12 (rs2644261, P=5.9 x 10(-4)) and Xp22 (rs5979785, P=6.8 x 10(-3); http://www.T1DBase.org). There was independent support for both SNPs in a GWA meta-analysis of 7514 cases and 9045 controls (P values=5.0 x 10(-3) and 6.7 x 10(-6), respectively). The chromosome 18q12 region contains four genes, none of which are obvious functional candidate genes. In contrast, the Xp22 SNP is located 30 kb centromeric of the functional candidate genes TLR8 and TLR7 genes. Both TLR8 and TLR7 are functional candidate genes owing to their key roles as pathogen recognition receptors and, in the case of TLR7, overexpression has been associated directly with murine autoimmune disease.
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PMID:Follow-up of 1715 SNPs from the Wellcome Trust Case Control Consortium genome-wide association study in type I diabetes families. 1995 7

Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher-dimensional models). We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high-dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising single-nucleotide polymorphisms (SNPs) are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.
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PMID:Screen and clean: a tool for identifying interactions in genome-wide association studies. 2008 21


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