Uncoupling Protein 2 and 3 Gene Polymorphisms and Their Association with Type 2 Diabetes in Asian Indians

Background: This study examined the association of -866G/A, Ala55Val, 45bpI/D, and -55C/T polymorphisms at the uncoupling protein (UCP) 3-2 loci with type 2 diabetes in Asian Indians. Methods: A case-control study was performed among 1,406 unrelated subjects (487 with type 2 diabetes and 919 normal glucose-tolerant NGT]), chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in Southern India. The polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism and direct sequencing. Haplotype frequencies were estimated using an expectation-maximization algorithm. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. Results: The genotype (P = 0.00006) and the allele (P = 0.00007) frequencies of Ala55Val of the UCP2 gene showed a significant protective effect against the development of type 2 diabetes. The odds ratios (adjusted for age, sex, and body mass index) for diabetes for individuals carrying Ala/Val was 0.72, and that for individuals carrying Val/Val was 0.37. Homeostasis insulin resistance model assessment and 2-h plasma glucose were significantly lower among Val-allele carriers compared to the Ala/Ala genotype within the NGT group. The genotype (P = 0.02) and the allele (P = 0.002) frequencies of -55C/T of the UCP3 gene showed a significant protective effect against the development of diabetes. The odds ratio for diabetes for individuals carrying CT was 0.79, and that for individuals carrying TT was 0.61. The haplotype analyses further confirmed the association of Ala55Val with diabetes, where the haplotypes carrying the Ala allele were significantly higher in the cases compared to controls. Conclusions: Ala55Val and -55C/T polymorphisms at the UCP3-2 loci are associated with a significantly reduced risk of developing type 2 diabetes in Asian Indians.

Study of wrist pulse signals using time domain spatial features

Blood travels throughout the body and thus its flow is modulated by changes in body condition. As a consequence, the wrist pulse signal contains important information about the status of the human body. In this work we have employed signal processing techniques to extract important information from these signals. Radial artery pulse pressure signals are acquired at wrist position noninvasively for several subjects for two cases of interest, viz. before and after exercise, and before and after lunch. Further analysis is performed by fitting a bi-modal Gaussian model to the data and extracting spatial features from the fit. The spatial features show statistically significant (p < 0.001) changes between the groups for both the cases, which indicates that they are effective in distinguishing the changes taking place due to exercise or food intake. Recursive cluster elimination based support vector machine classifier is used to classify between the groups. A high classification accuracy of 99.71% is achieved for the exercise case and 99.94% is achieved for the lunch case. This paper demonstrates the utility of certain spatial features in studying wrist pulse signals obtained under various experimental conditions. The ability of the spatial features in distinguishing changing body conditions can be potentially used for various healthcare applications. (C) 2015 Elsevier Ltd. All rights reserved.

A novel gene THSD7A is associated with obesity

Body mass index (BMI) is a non-invasive measurement of obesity. It is commonly used for assessing adiposity and obesity-related risk prediction. Genetic differences between ethnic groups are important factors, which contribute to the variation in phenotypic effects. India inhabited by the first out-of-Africa human population and the contemporary Indian populations are admixture of two ancestral populations; ancestral north Indians (ANI) and ancestral south Indians (ASI). Although ANI are related to Europeans, ASI are not related to any group outside Indian-subcontinent. Hence, we expect novel genetic loci associated with BMI. In association analysis, we found eight genic SNPs in extreme of distribution (P <= 3.75 x 10(-5)), of which WWOX has already been reported to be associated with obesity-related traits hence excluded from further study. Interestingly, we observed rs1526538, an intronic SNP of THSD7A; a novel gene significantly associated with obesity (P = 2.88 x 10(-5), 8.922 x 10(-6) and 2.504 x 10(-9) in discovery, replication and combined stages, respectively). THSD7A is neural N-glycoprotein, which promotes angiogenesis and it is well known that angiogenesis modulates obesity, adipose metabolism and insulin sensitivity, hence our result find a correlation. This information can be used for drug target, early diagnosis of obesity and treatment.

DNA methylation analysis of phenotype specific stratified Indian population

Background: DNA methylation and its perturbations are an established attribute to a wide spectrum of phenotypic variations and disease conditions. Indian traditional system practices personalized medicine through indigenous concept of distinctly descriptive physiological, psychological and anatomical features known as prakriti. Here we attempted to establish DNA methylation differences in these three prakriti phenotypes. Methods: Following structured and objective measurement of 3416 subjects, whole blood DNA of 147 healthy male individuals belonging to defined prakriti (Vata, Pitta and Kapha) between the age group of 20-30years were subjected to methylated DNA immunoprecipitation (MeDIP) and microarray analysis. After data analysis, prakriti specific signatures were validated through bisulfite DNA sequencing. Results: Differentially methylated regions in CpG islands and shores were significantly enriched in promoters/UTRs and gene body regions. Phenotypes characterized by higher metabolism (Pitta prakriti) in individuals showed distinct promoter (34) and gene body methylation (204), followed by Vata prakriti which correlates to motion showed DNA methylation in 52 promoters and 139 CpG islands and finally individuals with structural attributes (Kapha prakriti) with 23 and 19 promoters and CpG islands respectively. Bisulfite DNA sequencing of prakriti specific multiple CpG sites in promoters and 5'-UTR such as; LHX1 (Vata prakriti), SOX11 (Pitta prakriti) and CDH22 (Kapha prakriti) were validated. Kapha prakriti specific CDH22 5'-UTR CpG methylation was also found to be associated with higher body mass index (BMI). Conclusion: Differential DNA methylation signatures in three distinct prakriti phenotypes demonstrate the epigenetic basis of Indian traditional human classification which may have relevance to personalized medicine.

Groups constrain the use of risky habitat by individuals: a new cost to sociality?

Predation risk can strongly constrain how individuals use time and space. Grouping is known to reduce an individual's time investment in costly antipredator behaviours. Whether grouping might similarly provide a spatial release from antipredator behaviour and allow individuals to use risky habitat more and, thus, improve their access to resources is poorly known. We used mosquito larvae, Aedes aegypti, to test the hypothesis that grouping facilitates the use of high-risk habitat. We provided two habitats, one darker, low-risk and one lighter, high-risk, and measured the relative time spent in the latter by solitary larvae versus larvae in small groups. We tested larvae reared under different resource levels, and thus presumed to vary in body condition, because condition is known to influence risk taking. We also varied the degree of contrast in habitat structure. We predicted that individuals in groups should use high-risk habitat more than solitary individuals allowing for influences of body condition and contrast in habitat structure. Grouping strongly influenced the time spent in the high-risk habitat, but, contrary to our expectation, individuals in groups spent less time in the high-risk habitat than solitary individuals. Furthermore, solitary individuals considerably increased the proportion of time spent in the high-risk habitat over time, whereas individuals in groups did not. Both solitary individuals and those in groups showed a small increase over time in their use of riskier locations within each habitat. The differences between solitary individuals and those in groups held across all resource and contrast conditions. Grouping may, thus, carry a poorly understood cost of constraining habitat use. This cost may arise because movement traits important for maintaining group cohesion (a result of strong selection on grouping) can act to exaggerate an individual preference for low-risk habitat. Further research is needed to examine the interplay between grouping, individual movement and habitat use traits in environments heterogeneous in risk and resources. (C) 2015 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.