Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

The epidemiology and genetics of smoking initiation and persistence: Crosscultural comparisons of twin study results

We examined whether there are crosscultural differences in the magnitude of genetic and environmental contributions to risk of becoming a regular smoker and of persistence in smoking in men and women. Standard methods of epidemiologic and genetic analysis were applied to questionnaire data on history of cigarette use obtained from large samples of male and female like-sex twins from three different countries: Australia (N = 2284 pairs), Sweden (N = 8651 pairs), and Finland (N = 10,948 pairs). Samples were subdivided into three age groups (AG), 18-25 years, 26-35 years, and 36-46 years of age. The magnitude of genetic influence for lifetime smoking was found to be consistent across country and AG for women (46%) and men (57%), and estimates of the contribution from environmental influences shared by twin and co-twin could be equated across all countries by AG for the women (from youngest to oldest AG: 45%, 35%, and 26%), but not for men, with separate estimates obtained for the Scandinavian (33%, 29%, and 19%) and the Australian men (26%, 9%, and 11 %). There was no evidence for an important role for shared environmental influences on persistent smoking, and the genetic contribution was found to be consistent in magnitude in men and women, and the same across country and AG (52%). There are strong genetic influences on smoking behavior, and that risk of becoming a smoker (but not persistence in smoking) may be modified by experiences shared by twins that differ by AG and, at least for men, cultural background.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

RNA regulation: a new genetics?

Do non-coding RNAs that are derived from the introns and exons of protein-coding and non-protein-coding genes represent a fundamental advance in the genetic operating system of higher organisms? Recent evidence from comparative genomics and molecular genetics indicates that this might be the case. If so, there will be profound consequences for our understanding of the genetics of these organisms, and in particular how the trajectories of differentiation and development and the differences among individuals and species are genomically programmed. But how might this hypothesis be tested?

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.

Gene-flow between populations of cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) is highly variable between years

Both large and small scale migrations of Helicoverpa armigera Hübner in Australia were investigated using AMOVA analysis and genetic assignment tests. Five microsatellite loci were screened across 3142 individuals from 16 localities in eight major cotton and grain growing regions within Australia, over a 38-month period (November 1999 to January 2003). From November 1999 to March 2001 relatively low levels of migration were characterized between growing regions. Substantially higher than average gene-flow rates and limited differentiation between cropping regions characterized the period from April 2001 to March 2002. A reduced migration rate in the year from April 2002 to March 2003 resulted in significant genetic structuring between cropping regions. This differentiation was established within two or three generations. Genetic drift alone is unlikely to drive genetic differentiation over such a small number of generations, unless it is accompanied by extreme bottlenecks and/or selection. Helicoverpa armigera in Australia demonstrated isolation by distance, so immigration into cropping regions is more likely to come from nearby regions than from afar. This effect was most pronounced in years with limited migration. However, there is evidence of long distance dispersal events in periods of high migration (April 2001-March 2002). The implications of highly variable migration patterns for resistance management are considered.

The molecular genetics of breast cancer: The contribution of comparative genomic hybridization

Comparative genomic hybridization (CGH) has been the technique of choice over the last 10 years for mapping DNA copy number changes in human tumors. Here we review the literature to demonstrate how CGH has contributed to the comprehension of molecular aspects of breast tumorigenesis. At least two distinct molecular pathways of breast cancer have been characterized that show a strong correlation with histological grade. It seems that grade I invasive ductal carcinomas (IDCs) arise from well-differentiated ductal carcinoma in situ (DCIS), whereas grade III IDCs come from poorly differentiated DCIS. In addition, dedifferentiation from a low- to a high-grade breast cancer has proven an unlikely phenomenon. CGH has been instrumental in dissecting distinct molecular pathways toward breast malignancy and in establishing a direct relationship between genotype and clinical pathological features. (C) 2005 Elsevier GrnbH. All rights reserved.

Statistical modeling and projections of lung cancer mortality in 4 industrialized countries

The purpose of this work was to model lung cancer mortality as a function of past exposure to tobacco and to forecast age-sex-specific lung cancer mortality rates. A 3-factor age-period-cohort (APC) model, in which the period variable is replaced by the product of average tar content and adult tobacco consumption per capita, was estimated for the US, UK, Canada and Australia by the maximum likelihood method. Age- and sex-specific tobacco consumption was estimated from historical data on smoking prevalence and total tobacco consumption. Lung cancer mortality was derived from vital registration records. Future tobacco consumption, tar content and the cohort parameter were projected by autoregressive moving average (ARIMA) estimation. The optimal exposure variable was found to be the product of average tar content and adult cigarette consumption per capita, lagged for 2530 years for both males and females in all 4 countries. The coefficient of the product of average tar content and tobacco consumption per capita differs by age and sex. In all models, there was a statistically significant difference in the coefficient of the period variable by sex. In all countries, male age-standardized lung cancer mortality rates peaked in the 1980s and declined thereafter. Female mortality rates are projected to peak in the first decade of this century. The multiplicative models of age, tobacco exposure and cohort fit the observed data between 1950 and 1999 reasonably well, and time-series models yield plausible past trends of relevant variables. Despite a significant reduction in tobacco consumption and average tar content of cigarettes sold over the past few decades, the effect on lung cancer mortality is affected by the time lag between exposure and established disease. As a result, the burden of lung cancer among females is only just reaching, or soon will reach, its peak but has been declining for I to 2 decades in men. Future sex differences in lung cancer mortality are likely to be greater in North America than Australia and the UK due to differences in exposure patterns between the sexes. (c) 2005 Wiley-Liss, Inc.

Will nicotine genetics and a nicotine vaccine prevent cigarette smoking and smoking-related diseases?

This paper briefly explains why it would be unwise to use genetic and neurobiological knowledge to prevent cigarette smoking and tobacco-related disease. However implausible these uses may seem to those who are well informed about the genetics of tobacco use or tobacco-control policy, it is the preventive uses of genetic information and nicotine vaccines that most excite the interest of the media and the public. The major challenges that these approaches face need to be widely understood if we are to prevent these superfi cially attractive but controversial uses from undermining effective control policies and the development of better methods of helping smokers to quit.

The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, intersample variation in the proportion of linked families ( a) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage. findings obtained using allele- sharing LOD scores ( LODexp) - which assume homogeneity - and heterogeneity LOD scores ( HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LODexp and two different heterogeneity statistics. One of these ( HLOD- P) estimates the heterogeneity parameter a only in aggregate data, while the second ( HLOD- S) determines a separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LODexp. Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD- S, but not HLOD- P. Using HLOD- S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.

Estimating variable returns to scale production frontiers with alternative stochastic assumptions

Two stochastic production frontier models are formulated within the generalized production function framework popularized by Zellner and Revankar (Rev. Econ. Stud. 36 (1969) 241) and Zellner and Ryu (J. Appl. Econometrics 13 (1998) 101). This framework is convenient for parsimonious modeling of a production function with returns to scale specified as a function of output. Two alternatives for introducing the stochastic inefficiency term and the stochastic error are considered. In the first the errors are added to an equation of the form h(log y, theta) = log f (x, beta) where y denotes output, x is a vector of inputs and (theta, beta) are parameters. In the second the equation h(log y,theta) = log f(x, beta) is solved for log y to yield a solution of the form log y = g[theta, log f(x, beta)] and the errors are added to this equation. The latter alternative is novel, but it is needed to preserve the usual definition of firm efficiency. The two alternative stochastic assumptions are considered in conjunction with two returns to scale functions, making a total of four models that are considered. A Bayesian framework for estimating all four models is described. The techniques are applied to USDA state-level data on agricultural output and four inputs. Posterior distributions for all parameters, for firm efficiencies and for the efficiency rankings of firms are obtained. The sensitivity of the results to the returns to scale specification and to the stochastic specification is examined. (c) 2004 Elsevier B.V. All rights reserved.

The implications of simultaneous smoking initiation for inferences about the genetics of smoking behavior from twin data

We examined early social influences across stages of smoking within the context of a twin study using an environmental exposure specific to smoking: whether twins started smoking at the same time (simultaneous smoking initiation: SSI). We expected that SSI would be a good index of shared social influences on smoking initiation. Rates of SSI were indeed significantly higher in MZ twins and in twins who shared peers and classes, as well as in male twins. With the exception of regular smoking in females, we found no significant difference in estimates of genetic and environmental parameters between SSI and non-SSI pairs for any of the smoking measures that we examined (DSM-IV and Fagerstrom HSI measures of nicotine dependence; DSM-IV nicotine withdrawal; heavy smoking; and in males, regular smoking). For regular smoking in females, allowing for additional shared environmental influences associated with SSI only modestly reduced our estimates of additive genetic variance (56% vs. 68%). These results indicate the important social influences that may occur for smoking initiation do not appear to seriously bias estimates of genetic effects on later stages of smoking.

A golden age of human pigmentation genetics

The zebrafish golden mutation is characterized by the production of small and irregular-shaped melanin granules, resulting in a lightening of the pigmented lateral stripes of the animal. The recent positional cloning and localization of the golden gene, combined with genotype-phenotype correlations of alleles of its human orthologue (SLC24A5) in African-American and African-Caribbean populations, provide insights into the genetic and molecular basis of human skin colour. SLC24A5 promotes melanin deposition through maturation of the melanosome, highlighting the importance of ion-exchange in the function of this organelle.