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.

Copulas in QTL mapping

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.

Genetic time-series analysis identifies a major QTL for in vivo alcohol metabolism not predicted by in vitro studies of structural protein polymorphism at the ADH1B or ADH1C loci

After ingestion of a standardized dose of ethanol, alcohol concentrations were assessed, over 3.5 hours from blood (six readings) and breath (10 readings) in a sample of 412 MZ and DZ twins who took part in an Alcohol Challenge Twin Study (ACTS). Nearly all participants were subsequently genotyped on two polymorphic SNPs in the ADH1B and ADH1C loci known to affect in vitro ADH activity. In the DZ pairs, 14 microsatellite markers covering a 20.5 cM region on chromosome 4 that includes the ADH gene family were assessed, Variation in the timed series of autocorrelated blood and breath alcohol readings was studied using a bivariate simplex design. The contribution of a quantitative trait locus (QTL) or QTL's linked to the ADH region was estimated via a mixture of likelihoods weighted by identity-by-descent probabilities. The effects of allelic substitution at the ADH1B and ADH1C loci were estimated in the means part of the model simultaneously with the effects sex and age. There was a major contribution to variance in alcohol metabolism due to a QTL which accounted for about 64% of the additive genetic covariation common to both blood and breath alcohol readings at the first time point. No effects of the ADH1B*47His or ADH1C*349Ile alleles on in vivo metabolism were observed, although these have been shown to have major effects in vitro. This implies that there is a major determinant of variation for in vivo alcohol metabolism in the ADH region that is not accounted for by these polymorphisms. Earlier analyses of these data suggested that alcohol metabolism is related to drinking behavior and imply that this QTL may be protective against alcohol dependence.

A reassessment of genetic limits to evolutionary change

An absence of genetic variance in traits under selection is perhaps the oldest explanation for a limit to evolutionary change, but has also been the most easily dismissed. We review a range of theoretical and empirical results covering single traits to more complex multivariate systems, and show that an absence of genetic variance may be more common than is currently appreciated. From a single-trait perspective, we highlight that it is becoming clear that some trait types do not display significant levels of genetic variation, and we raise the possibility that species with restricted ranges may differ qualitatively from more widespread species in levels of genetic variance in ecologically important traits. A common misconception in many life-history studies is that a lack of genetic variance in single traits, and genetic constraints as a consequence of bivariate genetic correlations, are different causes of selection limits. We detail how interpretations of bivariate patterns are unlikely to demonstrate genetic limits to selection in many cases. We advocate a multivariate definition of genetic constraints that emphasizes the presence (or otherwise) of genetic variance in the multivariate direction of selection. For multitrait systems, recent results using longer term studies of organisms, in which more is understood concerning what traits may be under selection, have indicated that selection may exhaust genetic variance, resulting in a limit to the selection response.

Access to parental leave in Australia: evidence from Negotiating the Life Course

Although unpaid parental leave has been available to most Australian employees for more than a decade, and public sector legislation and company policies provide at least some employees with an entitlement to paid parental leave, there is as yet little information available on accessibility, take-up rates or the extent to which current leave provisions meet the needs of parents. In this paper, data from the Negotiating the Life Course survey are used to examine the first of these issues: accessibility. Variations in perceptions of access to paid and unpaid parental leave are examined in bivariate and multivariate analyses, which emphasise marked divisions in the Australian labour market between permanent and casual status. The data also suggest that access to unpaid parental leave is more variable than might be expected from a reading of formal legislative provisions, and raise questions over the accessibility of paid parental leave to those who need it most-employees with young children.

Effects of rock properties on specific cutting energy in linear cutting of sandstones by picks

Specific cutting energy (SE) has been widely used to assess the rock cuttability for mechanical excavation purposes. Some prediction models were developed for SE through correlating rock properties with SE values. However, some of the textural and compositional rock parameters i.e. texture coefficient and feldspar, mafic, and felsic mineral contents were not considered. The present study is to investigate the effects of previously ignored rock parameters along with engineering rock properties on SE. Mineralogical and petrographic analyses, rock mechanics, and linear rock cutting tests were performed on sandstone samples taken from sites around Ankara, Turkey. Relationships between SE and rock properties were evaluated using bivariate correlation and linear regression analyses. The tests and subsequent analyses revealed that the texture coefficient and feldspar content of sandstones affected rock cuttability, evidenced by significant correlations between these parameters and SE at a 90% confidence level. Felsic and mafic mineral contents of sandstones did not exhibit any statistically significant correlation against SE. Cementation coefficient, effective porosity, and pore volume had good correlations against SE. Poisson's ratio, Brazilian tensile strength, Shore scleroscope hardness, Schmidt hammer hardness, dry density, and point load strength index showed very strong linear correlations against SE at confidence levels of 95% and above, all of which were also found suitable to be used in predicting SE individually, depending on the results of regression analysis, ANOVA, Student's t-tests, and R2 values. Poisson's ratio exhibited the highest correlation with SE and seemed to be the most reliable SE prediction tool in sandstones.

Conditional risk, return and contagion in the banking sector in Asia

This paper investigates risk and return in the banking sector in three Asian markets of Taiwan, China and Hong Kong. The study focuses on the risk-return relation in a conditional factor GARCH-M framework that controls for time-series effects. The factor approach is adopted to incorporate intra-industry contagion and an analysis of spillovers between large banks and small banks. Finally, the study provides evidence on these relations before and after the Asian financial crisis of 1997. The results are generally consistent across the markets and with expectations.

Variance components analyses of multiple asthma traits in a large sample of Australian families ascertained through a twin proband

Background: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. Objective: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. Methods: A total of 3073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. Results: Overall 2716 participants completed an asthma questionnaire and 2087 were clinically tested, including 1289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV1) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV1 and atopy (0.05), airway obstruction and IgE (0.07) and FEV1 and D. pter (0.11). Conclusion: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.

Assortative Mating for Cigarette Smoking and for Alcohol Consumption in Female Australian Twins and their Spouses

Background Non-random mating affects population variation for substance use and dependence. Developmentally, mate selection leading to positive spousal correlations for genetic similarity may result in increased risk for substance use and misuse in offspring. Mate selection varies by cohort and thus, assortative mating in one generation may produce marked changes in rates of substance use in the next. We aim to clarify the mechanisms contributing to spousal similarity for cigarette smoking and alcohol consumption. Methods Using data from female twins and their male spouses, we fit univariate and bivariate twin models to examine the contribution of primary assortative mating and reciprocal marital interaction to spousal resemblance for regular cigarette smoking and nicotine dependence, and for regular alcohol use and alcohol dependence. Results We found that assortative mating significantly influenced regular smoking, regular alcohol use, nicotine dependence and alcohol dependence. The bivariate models for cigarette smoking and alcohol consumption also highlighted the importance of primary assortative mating on all stages of cigarette smoking and alcohol consumption, with additional evidence for assortative mating across the two stages of alcohol consumption. Conclusions Women who regularly used, and subsequently were dependent on cigarettes or alcohol were more likely to marry men with similar behaviors. After mate selection had occurred, one partner's cigarette or alcohol involvement did not significantly modify the other partner's involvement with these psychoactive substances.

A side order of stem cells: The SP phenotype

A defining property of murine hematopoietic stein cells (HSCs) is low fluorescence after staining with Hoechst 33342 and Rhodamine 123. These dyes have proven to be remarkably powerful tools in the purification and characterization of HSCs when used alone or in combination with antibodies directed against stem cell epitopes. Hoechst low cells are described as side population (SP) cells by virtue of their typical profiles in Hoechst red versus Hoechst blue bivariate fluorescent-activated cell sorting dot plots. Recently, excitement has been generated by the findings that putative stem cells from solid tissues may also possess this SP phenotype. SP cells have now been isolated from a wide variety of mammalian tissues based on this same dye efflux phenomenon, and in many cases this cell population has been shown to contain apparently multipotent stem cells. What is yet to be clearly addressed is whether cell fusion accounts for this perceived SP multipotency. Indeed, if low fluorescence after Hoechst staining is a phenotype shared by hematopoietic and organ-specific stem cells, do all resident tissue SP cells have bone marrow origins or might the SP phenotype be a property common to all stem cells? Subject to further analysis, the SP phenotype may prove invaluable for the initial isolation of resident tissue stem cells in the absence of definitive cell-surface markers and may have broad-ranging applications in stem cell biology, from the purification of novel stem cell populations to the development of autologous stem cell therapies.

A stochastic metapopulation model accounting for habitat dynamics

A stochastic metapopulation model accounting for habitat dynamics is presented. This is the stochastic SIS logistic model with the novel aspect that it incorporates varying carrying capacity. We present results of Kurtz and Barbour, that provide deterministic and diffusion approximations for a wide class of stochastic models, in a form that most easily allows their direct application to population models. These results are used to show that a suitably scaled version of the metapopulation model converges, uniformly in probability over finite time intervals, to a deterministic model previously studied in the ecological literature. Additionally, they allow us to establish a bivariate normal approximation to the quasi-stationary distribution of the process. This allows us to consider the effects of habitat dynamics on metapopulation modelling through a comparison with the stochastic SIS logistic model and provides an effective means for modelling metapopulations inhabiting dynamic landscapes.

Effects of rock properties on specific cutting energy in linear cutting of sandstones by picks

Specific cutting energy (SE) has been widely used to assess the rock cuttability for mechanical excavation purposes. Some prediction models were developed for SE through correlating rock properties with SE values. However, some of the textural and compositional rock parameters i.e. texture coefficient and feldspar, mafic, and felsic mineral contents were not considered. The present study is to investigate the effects of previously ignored rock parameters along with engineering rock properties on SE. Mineralogical and petrographic analyses, rock mechanics, and linear rock cutting tests were performed on sandstone samples taken from sites around Ankara, Turkey. Relationships between SE and rock properties were evaluated using bivariate correlation and linear regression analyses. The tests and subsequent analyses revealed that the texture coefficient and feldspar content of sandstones affected rock cuttability, evidenced by significant correlations between these parameters and SE at a 90% confidence level. Felsic and mafic mineral contents of sandstones did not exhibit any statistically significant correlation against SE. Cementation coefficient, effective porosity, and pore volume had good correlations against SE. Poisson's ratio, Brazilian tensile strength, Shore scleroscope hardness, Schmidt hammer hardness, dry density, and point load strength index showed very strong linear correlations against SE at confidence levels of 95% and above, all of which were also found suitable to be used in predicting SE individually, depending on the results of regression analysis, ANOVA, Student's t-tests, and R-2 values. Poisson's ratio exhibited the highest correlation with SE and seemed to be the most reliable SE prediction tool in sandstones.

Relationship between work performance and personality traits in Hong Kong organizational settings

Four hundred and thirty-seven employees from four Hong Kong organizations completed the Traditional Chinese versions of the Fifteen Factor Personality Questionnaire Plus (15FQ+) and the Cross-Cultural Personality Assessment Inventory (CPAI-2) (indigenous scales) and provided objective and memory-based recent performance appraisal scores. A number of significant bivariate correlations were found between personality and performance scores. Hierarchical multiple regression analyses revealed that a number of the scales from the 15FQ+ contributed to significantly predicting four of the performance competency dimensions, but that the CPAI-2 indigenous scales contributed no incremental validity in performance prediction over and above the 15FQ+. Results are discussed in the light of previous research and a call made for continued research to further develop and increase the reliability of the Chinese instruments used in the study and to enable generalization of the findings with confidence.

Bias, precision and heritability of self-reported and clinically measured height in Australian twins

Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.