Bayesian semiparametric analysis for two-phase studies of gene-environment interaction

The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected subsample. It is natural to apply such a strategy for collecting genetic data in a subsample enriched for exposure to environmental factors for gene-environment interaction (G x E) analysis. In this paper, we consider two-phase studies of G x E interaction where phase I data are available on exposure, covariates and disease status. Stratified sampling is done to prioritize individuals for genotyping at phase II conditional on disease and exposure. We consider a Bayesian analysis based on the joint retrospective likelihood of phases I and II data. We address several important statistical issues: (i) we consider a model with multiple genes, environmental factors and their pairwise interactions. We employ a Bayesian variable selection algorithm to reduce the dimensionality of this potentially high-dimensional model; (ii) we use the assumption of gene-gene and gene-environment independence to trade off between bias and efficiency for estimating the interaction parameters through use of hierarchical priors reflecting this assumption; (iii) we posit a flexible model for the joint distribution of the phase I categorical variables using the nonparametric Bayes construction of Dunson and Xing [J. Amer. Statist. Assoc. 104 (2009) 1042-1051].Comment: Published in at http://dx.doi.org/10.1214/12-AOAS599 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

PNEUMOCONIOSIS IN A SPOONBILL - A CASE REPORT

Pneumoconiosis has been identified in an adult dead spoonbill (Platalea leucorodia) from a Zoo in Kolkata, West Bengal, India. An environmental automobile pollutants present around that ambient may be the cause of pneumoconiosis

Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis

With increasing frequency, epidemiologic studies are addressing hypotheses regarding gene-environment interaction. In many well-studied candidate genes and for standard dietary and behavioral epidemiologic exposures, there is often substantial  prior  information available that may be used to analyze current data as well as for designing a new study. In this article, first, we propose a proper full Bayesian approach for analyzing studies of gene–environment interaction. The Bayesian approach provides a natural way to incorporate uncertainties around the assumption of gene–environment independence, often used in such an analysis. We then consider Bayesian sample size determination criteria for both estimation and hypothesis testing regarding the multiplicative gene–environment interaction parameter. We illustrate our proposed methods using data from a large ongoing case–control study of colorectal cancer investigating the interaction of N-acetyl transferase type 2 (NAT2) with smoking and red meat consumption. We use the existing data to elicit a design prior and show how to use this information in allocating cases and controls in planning a future study that investigates the same interaction parameters. The Bayesian design and analysis strategies are compared with their corresponding frequentist counterparts.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78584/1/j.1541-0420.2009.01357.x.pd

Microsatellite diversity among the primitive tribes of India

The present study was undertaken to determine the extent of diversity at 12 microsatellite short tandem repeat (STR) loci in seven primitive tribal populations of India with diverse linguistic and geographic backgrounds. DNA samples of 160 unrelated individuals were analyzed for 12 STR loci by multiplex polymerase chain reaction (PCR). Gene diversity analysis suggested that the average heterozygosity was uniformly high (> 0.7) in these groups and varied from 0.705 to 0.794. The Hardy-Weinberg equilibrium analysis revealed that these populations were in genetic equilibrium at almost all the loci. The overall G ST value was high (G ST = 0.051; range between 0.026 and 0.098 among the loci), reflecting the degree of differentiation/heterogeneity of seven populations studied for these loci. The cluster analysis and multidimensional scaling of genetic distances reveal two broad clusters of populations, besides Moolu Kurumba maintaining their distinct genetic identity vis-\ue0-vis other populations. The genetic affinity for the three tribes of the Indo-European family could be explained based on geography and Language but not for the four Dravidian tribes as reflected by the NJT and MDS plots. For the overall data, the insignificant MANTEL correlations between genetic, linguistic and geographic distances suggest that the genetic variation among these tribes is not patterned along geographic and/or linguistic lines

Newborn Screening for Sickle Cell Disease: Indian Experience

Sickle cell disease (SCD) is a major public health problem in India with the highest prevalence amongst the tribal and some non-tribal ethnic groups. The clinical manifestations are extremely variable ranging from a severe to mild or asymptomatic condition. Early diagnosis and providing care is critical in SCD because of the possibility of lethal complications in early infancy in pre-symptomatic children. Since 2010, neonatal screening programs for SCD have been initiated in a few states of India. A total of 18,003 babies have been screened by automated HPLC using either cord blood samples or heel prick dried blood spots and 2944 and 300 babies were diagnosed as sickle cell carriers and SCD respectively. A follow up of the SCD babies showed considerable variation in the clinical presentation in different population groups, the disease being more severe among non-tribal babies. Around 30% of babies developed serious complications within the first 2 to 2.6 years of life. These pilot studies have demonstrated the feasibility of undertaking newborn screening programs for SCD even in rural areas. A longer follow up of these babies is required and it is important to establish a national newborn screening program for SCD in all of the states where the frequency of the sickle cell gene is very high followed by the development of comprehensive care centers along with counselling and treatment facilities. This comprehensive data will ultimately help us to understand the natural history of SCD in India and also help the Government to formulate strategies for the management and prevention of sickle cell disease in India

Molecular Heterogeneity of Hb H Disease in India

Alpha thalassemia is an autosomal recessive disorder caused by large deletions and/or point mutations in the α- globin genes. Hemoglobin H (Hb H) disease is most frequently due to deletion of three of the four α globin genes associated with variable clinical severity depending on the genotype. There are few reports on Hb H disease in Indians where genotyping has been done and we have reviewed the molecular and clinical heterogeneity of these cases. An electronic search for relevant articles was conducted using two journal databases, i.e., PubMed and Science Direct using the key words “Hb H Disease”, “Hemoglobin H”, “α-thalassemia”, “mutations”, “molecular heterogeneity”, “case reports” and “India”. This review was performed based on preferred reporting items for the systematic review and meta-analysis protocols (PRISMA-P) guidelines. The molecular spectrum of Hb H disease in Indians includes the most common [-α3.7, -α4.2, --SA, Poly A (AATAAA→AATA--), Hb Sallanches], rare [--SEA, --MED, IVS 1nt 1 (G→A), Hb Koya Dora, Hb Sun Prairie], very rare [Hb Iberia, Hb Seal Rock, Hb Zürich-Albisrieden] and novel [Codon 76 (+T) and --Kol] α-globin gene mutations inherited largely as compound heterozygotes with considerable clinical variability. The molecular diagnosis of Hb H disease is important for genetic counseling and management

Molecular Heterogeneity of Hb H Disease in India

Alpha thalassemia is an autosomal recessive disorder caused by large deletions and/or point mutations in the α- globin genes. Hemoglobin H (Hb H) disease is most frequently due to deletion of three of the four α globin genes associated with variable clinical severity depending on the genotype. There are few reports on Hb H disease in Indians where genotyping has been done and we have reviewed the molecular and clinical heterogeneity of these cases. An electronic search for relevant articles was conducted using two journal databases, i.e., PubMed and Science Direct using the key words “Hb H Disease”, “Hemoglobin H”, “α-thalassemia”, “mutations”, “molecular heterogeneity”, “case reports” and “India”. This review was performed based on preferred reporting items for the systematic review and meta-analysis protocols (PRISMA-P) guidelines. The molecular spectrum of Hb H disease in Indians includes the most common [-α3.7, -α4.2, --SA, Poly A (AATAAA→AATA--), Hb Sallanches], rare [--SEA, --MED, IVS 1nt 1 (G→A), Hb Koya Dora, Hb Sun Prairie], very rare [Hb Iberia, Hb Seal Rock, Hb Zürich-Albisrieden] and novel [Codon 76 (+T) and --Kol] α-globin gene mutations inherited largely as compound heterozygotes with considerable clinical variability. The molecular diagnosis of Hb H disease is important for genetic counseling and management