Maternal alcohol use disorder and offspring ADHD: disentangling genetic and environmental effects using a children-of-twins design

Background. Children of alcoholics are significantly more likely to experience high-risk environmental exposures, including prenatal substance exposure, and are more likely to exhibit externalizing problems [e.g. attention deficit hyperactivity disorder (ADHD)]. While there is evidence that genetic influences and prenatal nicotine and/or alcohol exposure play separate roles in determining risk of ADHD, little has been done on determining the joint roles that genetic risk associated with maternal alcohol use disorder (AUD) and prenatal risk factors play in determining risk of ADHD. Method. Using a children-of-twins design, diagnostic telephone interview data from high-risk families (female monozygotic and dizygotic twins concordant or discordant for AUD as parents) and control families targeted from a large Australian twin cohort were analyzed using logistic regression models. Results. Offspring of twins with a history of AUD, as well as offspring of non-AUD monozygotic twins whose co-twin had AUD, were significantly more likely to exhibit ADHD than offspring of controls. This pattern is consistent with a genetic explanation for the association between maternal AUD and increased offspring risk of ADHD. Adjustment for prenatal smoking, which remained significantly predictive, did not remove the significant genetic association between maternal AUD and offspring ADHD. Conclusions. While maternal smoking during pregnancy probably contributes to the association between maternal AUD and offspring ADHD risk, the evidence for a significant genetic correlation suggests: (i) pleiotropic genetic effects, with some genes that influence risk of AUD also influencing vulnerability to ADHD; or (ii) ADHD is a direct risk-factor for AUD.

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.

Interactive effects of MC1R and OCA2 on melanoma risk phenotypes

The relationships between MC1R gene variants and red hair, skin reflectance, degree of freckling and nevus count were investigated in 2331 adolescent twins, their sibs and parents in 645 twin families. Penetrance of each MC1R variant allele was consistent with an allelic model where effects were multiplicative for red hair but additive for skin reflectance. Of nine MC1R variant alleles assayed, four common alleles were strongly associated with red hair and fair skin (Asp84Glu, Arg151Cys, Arg160Trp and Asp294His), with a further three alleles having low penetrance (Val60Leu, Val92Met and Arg163Gln). These variants were separately combined for the purposes of this analysis and designated as strong 'R' (OR=63.3; 95% CI 31.9-139.6) and weak 'r ' (OR=5.1; 95% CI 2.5-11.3) red hair alleles. Red-haired individuals are predominantly seen in the R/R and R/r groups with 67.1 and 10.8%, respectively. To assess the interaction of the brown eye color gene OCA2 on the phenotypic effects of variant MC1R alleles we included eye color as a covariate, and also genotyped two OCA2 SNPs (Arg305Trp and Arg419Gln), which were confirmed as modifying eye color. MC1R genotype effects on constitutive skin color, freckling and mole count were modified by eye color, but not genotype for these two OCA2 SNPs. This is probably due to the association of these OCA2 SNPs with brown/green not blue eye color. Amongst individuals with a R/R genotype (but not R/r), those who also had brown eyes had a mole count twice that of those with blue eyes. This suggests that other OCA2 polymorphisms influence mole count and remain to be described.

Effects of tourism development on the local poor people - Case study in Taibai Region China

In China, protected areas are one of the main destinations attracting tourists and homeland for many poor people living in and around them. Based on a case study, the paper focuses on correlation between tourism and poverty alleviation by tracing the cash flows to the local poor. It also reviews the social and environmental effects of tourism on local area. The case study is conducted in a group of protected areas in Qinling Mountain Region in Shaanxi, a western province in China. Qinling Mountain is one of the most important distribution zones for Giant Panda and some other endangered wildlife such as Golden Takin and Golden Monkey. The tourism development in the region is happening. Research indicates that there is 29.33%, of tourist expenditure is going to local households, directly or indirectly. Tourist spends US$7.11 (13.67%) in food and beverage, and US$6.39 (12.23%) in accommodation service, which are the greatest contributors to local households in terms of tourism benefits. Local households can get US$8.15 from food/beverage and accommodation sectors, taking 56.64% of total income from tourism. Generally, tourism development benefits all stakeholders. However, poor people get less benefit. The paper analyses the barriers for the poor to be involved in tourism development, and discusses the government roles, major issues in implementation of Sustainable Tourism-Eliminating Poverty (ST-EP) model. [ABSTRACT FROM AUTHOR]

Short-Term Perturbations and Tourism Effects: The case of SARS in China

In China, protected areas are one of the main destinations attracting tourists and homeland for many poor people living in and around them. Based on a case study, the paper focuses on correlation between tourism and poverty alleviation by tracing the cash flows to the local poor. It also reviews the social and environmental effects of tourism on local area. The case study is conducted in a group of protected areas in Qinling Mountain Region in Shaanxi, a western province in China. Qinling Mountain is one of the most important distribution zones for Giant Panda and some other endangered wildlife such as Golden Takin and Golden Monkey. The tourism development in the region is happening. Research indicates that there is 29.33%, of tourist expenditure is going to local households, directly or indirectly. Tourist spends US$7.11 (13.67%) in food and beverage, and US$6.39 (12.23%) in accommodation service, which are the greatest contributors to local households in terms of tourism benefits. Local households can get US$8.15 from food/beverage and accommodation sectors, taking 56.64% of total income from tourism. Generally, tourism development benefits all stakeholders. However, poor people get less benefit. The paper analyses the barriers for the poor to be involved in tourism development, and discusses the government roles, major issues in implementation of Sustainable Tourism-Eliminating Poverty (ST-EP) model.

A genetic two-factor model of the covariation among a subset of Multidimensional Aptitude Battery and Wechsler Adult Intelligence Scale - Revised subtests

The phenotypic and genetic factor structure of performance on five Multidimensional Aptitude Battery (MAB) subtests and one Wechsler Adult Intelligence Scale-Revised (WAIS-R) subtest was explored in 390 adolescent twin pairs (184 monozygotic [MZ]; 206 dizygotic (DZ)). The temporal stability of these measures was derived from a subsample of 49 twin pairs, with test-retest correlations ranging from .67 to .85. A phenotypic factor model, in which performance and verbal factors were correlated, provided a good fit to the data. Genetic modeling was based on the phenotypic factor structure, but also took into account the additive genetic (A), common environmental (C), and unique environmental (E) parameters derived from a fully saturated ACE model. The best fitting model was characterized by a genetic correlated two-factor structure with specific effects, a general common environmental factor, and overlapping unique environmental effects. Results are compared to multivariate genetic models reported in children and adults, with the most notable difference being the growing importance of common genes influencing diverse abilities in adolescence. (C) 2003 Elsevier Inc. All rights reserved.

The genetics of alcohol intake and of alcohol dependence

Background: Because alcohol has multiple dose-dependent consequences, it is important to understand the causes of individual variation in the amount of alcohol used. The aims of this study were to assess the long-term repeatability and genetic or environmental causes of variation in alcohol intake and to estimate the degree of overlap with causes of susceptibility to alcohol dependence. Methods: Data were used from three studies conducted between 1980 and 1995 on volunteer adult male and female Australian twin subjects. In each study, alcohol intake was reported both as quantity X frequency and as past-week data. Repeatability was calculated as correlations between occasions and between measures, and the effects of genes and environment were estimated by multivariate model fitting to the twin pair repeated measures of alcohol use. Relationships between mean alcohol use and the lifetime history of DSM-III-R alcohol dependence were tested by bivariate model fitting. Results: Repeatability of the alcohol intake measures was between 0.54 and 0.85, with the highest repeatability between measures within study and the lowest repeatability between the first and last studies. Reported alcohol consumption was mainly affected by genetic factors affecting all times of study and by nonshared environmental factors (including measurement error) unique to each time of study. Genes that affect alcohol intake do affect alcohol dependence, but genetic effects unique to dependence are also significant; environmental effects are largely unique to either intake and dependence. Conclusions: Nearly all the repeatable component of variation in alcohol intake is due to genetic effects. Genes affecting intake also affect dependence risk, but there are other genes that affect dependence alone. Studies aiming to identify genes that affect alcohol use disorders need to test loci and candidate genes against both phenotypes.

Exploring the Etiology of the Association Between Birthweight and IQ in an Adolescent Twin Sample

The negative effects of very low birthweight on intellectual development have been well documented, and more recently this effect has been shown to generalise to birthweights within the normal range. In this study we investigate the etiology of this relationship by using a classical twin design to disentangle the contributions of genes and environment. A previous Dutch study (Boomsma et al., 2001) examining these effects indicated that genes were important in mediating the association of birthweight to full IQ measured at ages 7 and 10, but not at ages 5 and 12. Here the association between birthweight and IQ at age 16 is considered (N = 523 twin pairs). Using variance components modeling we found that the genetic variance in birthweight (4%) completely overlapped with that in verbal IQ but not performance or full IQ. Results further showed the importance of shared environmental effects on birthweight (similar to 60%) but not on IQ (with genes explaining up to 72% of IQ variance). Models incorporating a direction of causation parameter between birthweight and IQ provided adequate fit to the data in either causal direction for performance and full IQ, but the model with verbal 10 causing birthweight was preferred to one in which birthweight influenced verbal IQ. As the measurement of birthweight precedes the measurement of twins' IQ at age 16, the influence of verbal IQ might be better considered as a proxy for parents' 10 or education, and it is possible that brighter mothers provide better prenatal environments for their children.

Genetic Simplex Modeling of Eysenck's Dimensions of Personality in a Sample of Young Australian Twins

The relative stability and magnitude of genetic and environmental effects underlying major dimensions of adolescent personality across time were investigated. The Junior Eysenck Personality Questionnaire was administered to over 540 twin pairs at ages 12, 14 and 16 years. Their personality scores were analyzed using genetic simplex modeling which explicitly took into account the longitudinal nature of the data. With the exception of the dimension lie, multivariate model fitting results revealed that familial aggregation was entirely explained by additive genetic effects. Results from simplex model fitting suggest that large proportions of the additive genetic variance observed at ages 14 and 16 years could be explained by genetic effects present at the age of 12 years. There was also evidence for smaller but significant genetic innovations at 14 and 16 years of age for male and female neuroticism, at 14 years for male extraversion, at 14 and 16 years for female psychoticism, and at 14 years for male psychoticism.

Multivariate genetic analysis of cognitive abilities in an adolescent twin sample

The sources of covariation among cognitive measures of Inspection Time, Choice Reaction Time, Delayed Response Speed and Accuracy, and IQ were examined in a classical twin design that included 245 monozygotic (MZ) and 298 dizygotic (DZ) twin pairs. Results indicated that a factor model comprising additive genetic and unique environmental effects was the most parsimonious. In this model, a general genetic cognitive factor emerged with factor loadings ranging from 0.28 to 0.64. Three other genetic factors explained the remaining genetic covariation between various speed and Delayed Response measures with IQ. However, a large proportion of the genetic variation in verbal (54%) and performance (25%) IQ was unrelated to these lower order cognitive measures. The independent genetic IQ variation may reflect information processes not captured by the elementary cognitive tasks, Inspection Time and Choice Reaction Time, nor our working memory task, Delayed Response. Unique environmental effects were mostly nonoverlapping, and partly represented test measurement error.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Rice morphogenesis and plant architecture: Measurement, specification and the reconstruction of structural development by 3D architectural modelling

Background and Aims The morphogenesis and architecture of a rice plant, Oryza sativa, are critical factors in the yield equation, but they are not well studied because of the lack of appropriate tools for 3D measurement. The architecture of rice plants is characterized by a large number of tillers and leaves. The aims of this study were to specify rice plant architecture and to find appropriate functions to represent the 3D growth across all growth stages. Methods A japonica type rice, 'Namaga', was grown in pots under outdoor conditions. A 3D digitizer was used to measure the rice plant structure at intervals from the young seedling stage to maturity. The L-system formalism was applied to create '3D virtual rice' plants, incorporating models of phenological development and leaf emergence period as a function of temperature and photoperiod, which were used to determine the timing of tiller emergence. Key Results The relationships between the nodal positions and leaf lengths, leaf angles and tiller angles were analysed and used to determine growth functions for the models. The '3D virtual rice' reproduces the structural development of isolated plants and provides a good estimation of the fillering process, and of the accumulation of leaves. Conclusions The results indicated that the '3D virtual rice' has a possibility to demonstrate the differences in the structure and development between cultivars and under different environmental conditions. Future work, necessary to reflect both cultivar and environmental effects on the model performance, and to link with physiological models, is proposed in the discussion.

A multiple account framework for cost-benefit analysis

The paper presents a spreadsheet-based multiple account framework for cost-benefit analysis which incorporates all the usual concerns of cost-benefit analysts such as shadow-pricing to account for market failure. distribution of net benefits. sensitivity and risk analysis, cost of public funds, and environmental effects. The approach is generalizable to a wide range of projects and situations and offers a number of advantages to both analysts and decision-makers, including transparency, a check on internal consistency, and a detailed summary of project net benefits disaggregated by stakeholder group. Of particular importance is the ease with which this framework allows for a project to be evaluated from alternative decision-making perspectives and under alternative policy scenarios where the trade-offs among the project's stakeholders can readily be identified and quantified. (C) 2004 Elsevier Ltd. All rights reserved.

On measuring wealth: A case study on the state of Queensland

In order for policy makers to plan effectively for sustainable development, there is a need for measures of welfare that consider changes in the natural capital stock. Current measures based on conventional national accounting are flawed because they are based solely on flow measures and do not account for environmental effects. In this paper, we use an expanded measure of wealth to estimate the value of natural capital for Queensland. The state's stock of natural capital is valued at A$355.6 billion, of which non-timber forest resources account for 45.3%, ecosystem services 20.0%, and mineral resources 17.6%. This figure is a conservative estimate of the true value since some significant components such as the ecological and life-support functions of the environment are excluded. The estimates highlight the relative importance of different forms of natural capital and can be used to draw the attention of policymakers to the need to give adequate weight to the value of such services in decision-making processes. (c) 2005 Elsevier Ltd. All rights reserved.