GENETIC SUSCEPTIBILITY TO TYPE II DIABETES AND OBESITY: THE ROLE OF UCP2, UCP3 AND CAPN10 GENES

PhDThe global prevalence of type 2 diabetes (T2DM) and obesity is increasing, with obesity the most important predisposing factor contributing to the development of T2DM. Epidemiological and genetic evidence supports a major genetic component in both multifactorial and heterogeneous disorders. The identification of disease susceptibility genes in humans could greatly assist in the elucidation of underlying pathophysiological mechanisms and allow the development of more effective preventative and therapeutic strategies for these conditions. Three candidate genes, uncoupling proteins 2 and 3 (UCP2; UCP3) and calpain 10 (CAPN10), are proposed and the rationale for their selection discussed. Gene variants were identified in UCP2 and UCP3. These variants were tested for association with T2DM, obesity and intermediate quantitative traits in a South Indian population and family collection, and also a cohort of British obese case/control subjects. No variant was associated with T2DM. However, investigations revealed positive associations with a UCP2 3'UTR 45bp Ins/Del and a novel UCP3 promoter variant (-55C/T) with variation in body mass (BMI) and fat distribution (WHR) respectively. The results support the view that uncoupling proteins may influence weight gain and hence progression to obesity/T2DM. A significant correlation with plasma leptin levels and the UCP2 Ins/Del variant might indicate one potential mechanism whereby weight could be modulated by uncoupling proteins. A linkage study in affected sibling pairs of North European descent, was negative for the putative T2DM susceptibility gene region, NIDDMI. In contrast, haplotypes of four sequence variants of a T2DM susceptibility gene (CAPN10) identified in this region positively associated with T2DM in a South Indian population. In conclusion, these investigations provide evidence that the three genes studied may contribute to susceptibility for development of T2DM or obesity. However, the findings are in agreement with the most likely genetic model for non-Mendelian complex diseases, that many genes are involved in determining susceptibility to disease with no single gene capable of determining the overall disease phenotype

Generalization of Risch's Algorithm to Special Functions.

Symbolic integration deals with the evaluation of integrals in closed form. We present an overview of Risch’s algorithm including recent developments. The algorithms discussed are suited for both indefinite and definite integration. They can also be used to compute linear relations among integrals and to find identities for special functions given by parameter integrals. The aim of this presentation is twofold: to introduce the reader to some basic ideas of differential algebra in the context of integration and to raise awareness in the physics community of computer algebra algorithms for indefinite and definite integration