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Obesity and diabetes gene discovery approaches
journal contribution
posted on 2003-07-01, 00:00 authored by Ken WalderKen Walder, D Segal, Jeremy Jowett, J Blangero, Gregory CollierNew treatments are currently required for the common metabolic diseases obesity and type 2 diabetes. The identification of physiological and biochemical factors that underlie the metabolic disturbances observed in obesity and type 2 diabetes is a key step in developing better therapeutic outcomes. The discovery of new genes and pathways involved in the pathogenesis of these diseases is critical to this process, however identification of genes that contribute to the risk of developing these diseases represents a significant challenge as obesity and type 2 diabetes are complex diseases with many genetic and environmental causes. A number of diverse approaches have been used to discover and validate potential new targets for obesity and diabetes. To date, DNA-based approaches using candidate gene and genome-wide linkage analysis have had limited success in identifying genomic regions or genes involved in the development of these diseases. Recent advances in the ability to evaluate linkage analysis data from large family pedigrees using variance components based linkage analysis show great promise in robustly identifying genomic regions associated with the development of obesity and diabetes. RNA-based technologies such as cDNA microarrays have identified many genes differentially expressed in tissues of healthy and diseased subjects. Using a combined approach, we are endeavouring to focus attention on differentially expressed genes located in chromosomal regions previously linked with obesity and / or diabetes. Using this strategy, we have identified Beacon as a potential new target for obesity and diabetes.
History
Journal
Current pharmaceutical designVolume
9Issue
17Pagination
1357 - 1372Publisher
Bentham Science Publishers LtdLocation
Schiphol, NetherlandsISSN
1381-6128eISSN
1873-4286Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2003, Bentham Science PublishersUsage metrics
Categories
Keywords
diabetesgene expressionlinkagemicroarraysobesityquantitative trait locigeneticsScience & TechnologyLife Sciences & BiomedicinePharmacology & PharmacyGENOME-WIDE SEARCHQUANTITATIVE-TRAIT LOCIBODY-MASS INDEXSINGLE-NUCLEOTIDE POLYMORPHISMSMULTIPOINT LINKAGE ANALYSISMAJOR SUSCEPTIBILITY LOCUSPOSITIONAL CANDIDATE GENECOMMON DISEASE GENESPIMA-INDIANSINSULIN-RESISTANCE