Angshuman Sarkar

Heritability estimation of conventional cardiovascular disease risk factors in Asian Indian families: The Calcutta family study

The genetic causes of the components of cardiovascular disease (CVD) risk factors and their intercorrelation are indeed complex and only partly understood. Keeping this view in mind, the present work was undertaken to estimate the heritability of conventional CVD risk factors using family study method. A total of twenty-four nuclear families inhabiting in Calcutta and adjacent areas was chosen randomly. Up to first degree relatives including father, mother and other sibs of the proband were considered as participants in the study. Anthropometric measures namely height, weight, waist circumference as well as skinfold thickness at biceps, triceps, subscapular and suprailiac were obtained using standard techniques. Body mass index (BMI), percentage of body fat (PBF), fat mass (FM), waist-hip ratio (WHR), sum of four skinfolds (SF4 ), arm muscle circumference (AMC), arm muscle area (AMA), arm fat area (AFA), systolic (SBP) and diastolic blood pressure (DBP) were also considered. To estimate’heritability’ in the study, the mid parent-offspring model was used where’heritability’ (h2 ) was equivalent to regression co-efficient (b). The regression sum of square (RSS) and total sum of square (TSS) ratio was also calculated both for mid parent-offspring and single parent-offspring. This ratio was considered as a measure of’heritability’ in the study with consideration that RSS is the variation due to genetic factor and the TSS is due to genetic and other additive factor. It was observed that the estimated heritability for BMI ranges from 0.69 to 0.31 using mid-parent off spring model while the range using single parent-offspring model was from 0.40 to 0.16. The range of heritability for SBP in mid parent-offspring model was 0.16 to 0.44 and 0.05 to 0.54 for single parent-offspring model. To conclude, it seems reasonable to argue that in the study a moderate to high h2 was evident for body fat level, body composition and blood pressure measures which indicate a moderate to high aggregation of gene(s) in the family.

A Preliminary Study on Oxya fuscovittata (Marschall) as an Alternative Nutrient Supplement in the Diets of Poecillia sphenops (Valenciennes)

Growth of the ornamental fish industry is being hindered by the scarcity of low cost feed; hence alternative protein supplements should be explored. In this context the present study aims to evaluate whether the grasshopper Oxya fuscovittata could be used as a supplement for fish meal in the diets of Poecillia sphenops, which is one of the most common ornamental fishes worldwide. The present work is divided into three phases: In the first phase proximate composition of the grasshopper is obtained and five diets are prepared where fish meal is gradually replaced by Oxya meal and named as control, D1, D2, D3 and D4. All the diets are formulated on iso-nitrogenous basis where the protein percentage is fixed at 400 g/kg. The second phase deals with feeding trial and in the third phase all the data of the feeding trial are subjected to a linear model. The feeding trial shows that the control, D1 and D2 fed fishes have almost similar results. The linear model proves that the variation in the indices are mainly due to replacement of fish meal by Oxya meal, not due to the variations of rice husk and mustard oil cake that are also used to formulate the diets of the present study. From the results two Oxya supplemented diets, i.e. D1 and D2 are proved to be almost equivalent to the control diet. Hence it is concluded that Oxya meal is able to replace 25% to 50% of fish meal from the diets of P. sphenops.

A Method of Finding Predictor Genes for a Particular Disease Using a Clustering Algorithm

Clustering Algorithms are nowadays really important tools in microarray data analysis. The different clustering algorithm generally used in biological science does not take into consideration the underlying probability distribution of the data. In this sense, they are heuristic in nature. In this work we proposed a clustering algorithm based on EM Algorithm. It gives 28% less misclassification than the K-means algorithm (which is mostly use in Bio science). We have also shown on a real data set that this algorithm can be efficiently used for detecting the genes which are responsible for a particular disease.

Analysis of bivariate binary data with possible chances of wrong ascertainment

In familial data, ascertainment correction is often necessary to decipher genetic bases of complex human diseases. This is because families usually are not drawn at random or are not selected according to well-defined rules. While there has been much progress in identifying genes associated with a certain phenotype, little attention has been paid so far for familial studies on exploring common genetic influences on different phenotypes of interest. In this study, we develop a powerful bivariate analytical approach that can be used for a complex situation with paired binary traits. In addition, our model has been framed to accommodate the possibility of imperfect diagnosis as traits may be wrongly observed. Thus, the primary focus is to see whether a particular gene jointly influences both phenotypes. We examine the plausibility of this theory in a sample of families ascertained on the basis of at least one affected individual. We propose a bivariate binary mixed model that provides a novel and flexible way to account for wrong ascertainment in families collected with multiple cases. A hierarchical Bayesian analysis using Markov Chain Monte Carlo (MCMC) method has been carried out to investigate the effect of covariates on the disease status. Results based on simulated data indicate that estimates of the parameters are biased when classification errors and/or ascertainment are ignored.

Designs for Searching two Two-Factor and One Three-Factor Interaction Effect Under the Tree Structure

Abtsrcat Search designs form an indispensable tool under model uncertainty. However, the progress in this area has been limited due to com- plexities of checking the necessary rank condition for search designs. Designs for searching two two-factor and one three-factor interaction effects under a tree structure in the presence of the general mean and all the main effects are provided here. These designs are obtained under the assumption that four-factor and higher order interaction effects are all absent. Probability of correct searching obtained through simulations is also discussed.

Effects of Mercury on Development of Oxya fuscovittata (Marschall) (Orthoptera: Acrididae)

Abstract Grasshoppers are ecologically significant because many animals consume them as a major protein source and thus any change in their population dynamics may have detrimental effects on an ecosystem. This study evaluates effects of mercury (Hg2+) on the developmental periods of different instars of a common short-horned grasshopper, Oxya fuscovittata (Marschall). Newly hatched nymphs were fed foods treated with three sublethal concentrations of HgCl2 i.e., dose 1 (d1): 20 mg HgCl2/ kg dry weight in oats, dose 2 (d2): 40 mg HgCl2/ kg dry weight in oats, and dose 3 (d3): 80 mg HgCl2/ kg dry weight in oats, until they reached the adult stage. The experiment was conducted for two consecutive generations (F1 and F2), tested in the same way for the same variables, in order to observe if there is any additional adversity in the latter generation. As HgCl2 concentrations in food increased, the Total Rearing Time (TRT) for each instar significantly increased, whereas survival, adult body weight and adult life span significantly decreased. The results for the F2 generation almost always showed more severe effects than those of the F1 generation.