Genetic analyses of DSM-IV nicotine withdrawal in adult twins

Background. We examined whether there are genetic influences on nicotine withdrawal. and whether there are genetic factors specific to nicotine withdrawal, after controlling for factors responsible for risk of progression beyond experimentation with cigarettes and for quantity smoked (average number of cigarettes per day at peak lifetime use). Method. Epidemiologic and genetic analyses were conducted using telephone diagnostic interview data from Young adult Australian twins reporting any cigarette use (3026 women. 2553 men: mean age 30 years). Results. Genetic analysis of the eight symptoms of DSM-IV nicotine withdrawal suggests heritability is intermediate for most symptoms (26-43%). and Similar in men and women. The exceptions were depressed mood upon withdrawal. which had stronger additive genetic influences in men (53%) compared to worrien (29%). and decreased heart rate. which had low heritability (9%). Although prevalence rates were substantlally lower for DSM-IV nicotine withdrawal syndrome (15-9%), which requires impairment. than for the DSM-IV nicotine dependence withdrawal criterion (43.6%), heritability was similar for both measures: as high as 47%. Genetic modeling of smoking more than 1 or 2 cigarettes lifetime ('progression'). qualtity smoked and nicotine withdrawal found significant genetic overlap across all three components of nicotine use/dependence (genetic correlations = 0.53-0.76). Controlling for factors associated with risk of cigarette smoking beyond experimentation and quantity smoked, evidence for genetic influences specific to nicotine withdrawal (up to 23% of total variance) remained. Conclusions. Our results suggest that at least some individuals become 'hooked' or progress in the smoking habit, in part, because of it vulnerability to nicotine withdrawal.

Genetic and environmental influences on extreme personality dispositions in adolescent female twins

Background: The objective was to determine whether the pattern of environmental and genetic influences on deviant personality scores differs from that observed for the normative range of personality, comparing results in adolescent and adult female twins. Methods: A sample of 2,796 female adolescent twins ascertained from birth records provided Junior Eysenck Personality Questionnaire data. The average age of the sample was 17.0 years ( S. D. 2.3). Genetic analyses of continuous and extreme personality scores were conducted. Results were compared for 3,178 adult female twins. Results: Genetic analysis of continuous traits in adolescent female twins were similar to findings in adult female twins, with genetic influences accounting for between 37% and 44% of the variance in Extraversion (Ex), Neuroticism (N), and Social Non-Conformity (SNC), with significant evidence of shared environmental influences (19%) found only for SNC in the adult female twins. Analyses of extreme personality characteristics, defined categorically, in the adolescent data and replicated in the adult female data, yielded estimates for high N and high SNC that deviated substantially (p < .05) from those obtained in the continuous trait analyses, and provided suggestive evidence that shared family environment may play a more important role in determining personality deviance than has been previously found when personality is viewed continuously. However, multiple-threshold models that assumed the same genetic and environmental determinants of both normative range variation and extreme scores gave acceptable fits for each personality dimension. Conclusions: The hypothesis of differences in genetic or environmental factors responsible for N and SNC among female twins with scores in the extreme versus normative ranges was partially supported, but not for Ex.

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.

Genetic and Cultural Transmission of Smoking Initiation: An Extended Twin Kinship Model

Background Considerable evidence from twin and adoption studies indicates that genetic and shared environmental factors play a significant role in the initiation of smoking behavior. Although twin and adoption designs are powerful to detect genetic and environmental influences, they do not provide information on the processes of assortative mating and parent–offspring transmission and their contribution to the variability explained by genetic and/or environmental factors. Methods We examined the role of genetic and environmental factors for smoking initiation using an extended kinship design. This design allows the simultaneous testing of additive and non-additive genetic, shared and individual-specific environmental factors, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission. A dichotomous lifetime smoking measure was obtained from twins and relatives in the Virginia 30,000 sample. Results Results demonstrate that both genetic and environmental factors play a significant role in the liability to smoking initiation. Major influences on individual differences appeared to be additive genetic and unique environmental effects, with smaller contributions from assortative mating, shared sibling environment, twin environment, cultural transmission and resulting genotype–environment covariance. The finding of negative cultural transmission without dominance led us to investigate more closely two possible mechanisms for the lower parent–offspring correlations compared to the sibling and DZ twin correlations in subsets of the data: (i) age × gene interaction, and (ii) social homogamy. Neither mechanism provided a significantly better explanation of the data, although age regression was significant. Conclusions This study showed significant heritability, partly due to assortment, and significant effects of primarily non-parental shared environment on smoking initiation.

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

New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. 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 with 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. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. 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 QTLs.

Fast algorithms for automatic mapping with space-limited covariance functions

In this paper we discuss a fast Bayesian extension to kriging algorithms which has been used successfully for fast, automatic mapping in emergency conditions in the Spatial Interpolation Comparison 2004 (SIC2004) exercise. The application of kriging to automatic mapping raises several issues such as robustness, scalability, speed and parameter estimation. Various ad-hoc solutions have been proposed and used extensively but they lack a sound theoretical basis. In this paper we show how observations can be projected onto a representative subset of the data, without losing significant information. This allows the complexity of the algorithm to grow as O(n m 2), where n is the total number of observations and m is the size of the subset of the observations retained for prediction. The main contribution of this paper is to further extend this projective method through the application of space-limited covariance functions, which can be used as an alternative to the commonly used covariance models. In many real world applications the correlation between observations essentially vanishes beyond a certain separation distance. Thus it makes sense to use a covariance model that encompasses this belief since this leads to sparse covariance matrices for which optimised sparse matrix techniques can be used. In the presence of extreme values we show that space-limited covariance functions offer an additional benefit, they maintain the smoothness locally but at the same time lead to a more robust, and compact, global model. We show the performance of this technique coupled with the sparse extension to the kriging algorithm on synthetic data and outline a number of computational benefits such an approach brings. To test the relevance to automatic mapping we apply the method to the data used in a recent comparison of interpolation techniques (SIC2004) to map the levels of background ambient gamma radiation. © Springer-Verlag 2007.

Statnote 31:analysis of covariance

Analysis of covariance (ANCOVA) is a useful method of ‘error control’, i.e., it can reduce the size of the error variance in an experimental or observational study. An initial measure obtained before the experiment, which is closely related to the final measurement, is used to adjust the final measurements, thus reducing the error variance. When this method is used to reduce the error term, the X variable must not itself be affected by the experimental treatments, because part of the treatment effect would then also be removed. Hence, the method can only be safely used when X is measured before an experiment. A further limitation of the analysis is that only the linear effect of Y on X is being removed and it is possible that Y could be a curvilinear function of X. A question often raised is whether ANCOVA should be used routinely in experiments rather than a randomized blocks or split-plot design, which may also reduce the error variance. The answer to this question depends on the relative precision of the difference methods with reference to each scenario. Considerable judgment is often required to select the best experimental design and statistical help should be sought at an early stage of an investigation.

Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

2000 Mathematics Subject Classification: 62H12, 62P99

Positive relationship between genetic- and species diversity on limestone outcrops in the Carpathian Mountains

We asked if the genetic diversity of Saponaria bellidifolia (a habitat specialist plant) and the species diversity of its habitat are driven by parallel landscape level processes in an island-like system of limestone outcrops in the Carpathian Mountains. We tested the relationship of these two diversity levels at local and regional geographic scales. Local genetic and species diversity showed parallel patterns influenced by the number of plant communities. Likewise, at regional level there was strong evidence for parallel equilibrial dynamics of genotypes and species. However, a superimposed matrix effect enhanced the regional species diversity only. Genetic diversity of habitat specialist organisms and species diversity of these limestone outcrop islands on mainland are modulated by parallel landscape-level processes at different geographic scales, and mechanisms may be identified at very high spatial resolutions.

Temporal Population Genetic Structure of Eastern Mosquitofish in a Dynamic Aquatic Landscape

We analyzed the effect of periodic drying in the Florida Everglades on spatiotemporal population genetic structure of eastern mosquitofish (Gambusia holbrooki). Severe periodic drying events force individuals from disparate sources to mix in dry season relatively deep-water refuges. In 1996 (a wet year) and 1999 (a dry year), we sampled mosquitofish at 20 dry-season refuges distributed in 3 water management regions and characterized genetic variation for 10 allozyme and 3 microsatellite loci. In 1996, most of the ecosystem did not dry, whereas in 1999, many of our sampling locations were isolated by expanses of dried marsh surface. In 1996, most spatial genetic variation was attributed to heterogeneity within regions. In 1999, spatial genetic variation within regions was not significant. In both years, a small but significant amount of variation (less than 1% of the total variation) was partitioned among regions. Variance was consistently greater than zero among long-hydroperiod sites within a region, but not among short-hydroperiod sites within a region, where hydroperiod was measured as time since last marsh surface dry-down forcing fishes into local refuges. In 1996, all sites were in Hardy–Weinberg equilibrium. In 1999, we observed fewer heterozygotes than expected for most loci and sites suggesting a Wahlund effect arising from fish leaving areas that dried and mixing in deep-water refuges.

Meteorological observations and eddy covariance raw data from polygonal tundra in the Lena River Delta, Siberia

We present the first ecosystem-scale methane flux data from a northern Siberian tundra ecosystem covering the entire snow-free period from spring thaw until initial freeze-back. Eddy covariance measurements of methane emission were carried out from the beginning of June until the end of September in the southern central part of the Lena River Delta (72°22' N, 126°30' E). The study site is located in the zone of continuous permafrost and is characterized by Arctic continental climate with very low precipitation and a mean annual temperature of -14.7°C. We found relatively low fluxes of on average 18.7 mg/m**2/d, which we consider to be because of (1) extremely cold permafrost, (2) substrate limitation of the methanogenic archaea, and (3) a relatively high surface coverage of noninundated, moderately moist areas. Near-surface turbulence as measured by the eddy covariance system in 4 m above the ground surface was identified as the most important control on ecosystem-scale methane emission and explained about 60% of the variance in emissions, while soil temperature explained only 8%. In addition, atmospheric pressure was found to significantly improve an exponential model based on turbulence and soil temperature. Ebullition from waterlogged areas triggered by decreasing atmospheric pressure and near-surface turbulence is thought to be an important pathway that warrants more attention in future studies. The close coupling of methane fluxes and atmospheric parameters demonstrated here raises questions regarding the reliability of enclosure-based measurements, which inherently exclude these parameters.

Fisheries stocks from an ecological perspective: Disentangling ecological connectivity from genetic interchange

The concept of a stock of fish as a management unit has been around for well over a hundred years, and this has formed the basis for fisheries science. Methods for delimiting stocks have advanced considerably over recent years, including genetic, telemetric, tagging, geochemical and phenotypic information. In parallel with these developments, concepts in population ecology such as meta-population dynamics and connectivity have advanced. The pragmatic view of stocks has always accepted some mixing during spawning, feeding and/or larval drift. Here we consider the mismatch between ecological connectivity of a matrix of populations typically focussed on demographic measurements, and genetic connectivity of populations that focus on genetic exchange detected using modern molecular approaches. We suggest that from an ecological-connectivity perspective populations can be delimited as management units if there is limited exchange during recruitment or via migration in most years. From a genetic-connectivity perspective such limited exchange can maintain panmixia. We use case-studies of species endangered by overexploitation and/or habitat degradation to show how current methods of stock delimitation can help in managing populations and in conservation.

Fisheries stocks from an ecological perspective: Disentangling ecological connectivity from genetic interchange

The concept of a stock of fish as a management unit has been around for well over a hundred years, and this has formed the basis for fisheries science. Methods for delimiting stocks have advanced considerably over recent years, including genetic, telemetric, tagging, geochemical and phenotypic information. In parallel with these developments, concepts in population ecology such as meta-population dynamics and connectivity have advanced. The pragmatic view of stocks has always accepted some mixing during spawning, feeding and/or larval drift. Here we consider the mismatch between ecological connectivity of a matrix of populations typically focussed on demographic measurements, and genetic connectivity of populations that focus on genetic exchange detected using modern molecular approaches. We suggest that from an ecological-connectivity perspective populations can be delimited as management units if there is limited exchange during recruitment or via migration in most years. From a genetic-connectivity perspective such limited exchange can maintain panmixia. We use case-studies of species endangered by overexploitation and/or habitat degradation to show how current methods of stock delimitation can help in managing populations and in conservation.

Epigenetics within the matrix:a neo-regulator of fibrotic disease

Fibrosis of any tissue is characterized by excessive extracellular matrix accumulation that ultimately destroys tissue architecture and eventually abolishes normal organ function. Although much research has focused on the mechanisms underlying disease pathogenesis, there are still no effective antifibrotic therapies that can reverse, stop or delay the formation of scar tissue in most fibrotic organs. As fibrosis can be described as an aberrant wound healing response, a recent hypothesis suggests that the cells involved in this process gain an altered heritable phenotype that promotes excessive fibrotic tissue accumulation. This article will review the most recent observations in a newly emerging field that links epigenetic modifications to the pathogenesis of fibrosis. Specifically, the roles of DNA methylation and histone modifications in fibrotic disease will be discussed.