Gene-Environment Interaction Effects on Behavioral Variation and Risk of Complex Disorders: The Example of Alcoholism and Other Psychiatric Disorders

There have been few replicated examples of genotype x environment interaction effects on behavioral variation or risk of psychiatric disorder. We review some of the factors that have made detection of genotype x environment interaction effects difficult, and show how genotype x shared environment interaction (GxSE) effects are commonly confounded with genetic parameters in data from twin pairs reared together. Historic data on twin pairs reared apart can in principle be used to estimate such GxSE effects, but have rarely been used for this purpose. We illustrate this using previously published data from the Swedish Adoption Twin Study of Aging (SATSA), which suggest that GxSE effects could account for as much as 25% of the total variance in risk of becoming a regular smoker. Since few separated twin pairs will be available for study in the future, we also consider methods for modifying variance components linkage analysis to allow for environmental interactions with linked loci.

Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

Multi-environment trials (METs) used to evaluate breeding lines vary in the number of years that they sample. We used a cropping systems model to simulate the target population of environments (TPE) for 6 locations over 108 years for 54 'near-isolines' of sorghum in north-eastern Australia. For a single reference genotype, each of 547 trials was clustered into 1 of 3 'drought environment types' (DETs) based on a seasonal water stress index. Within sequential METs of 2 years duration, the frequencies of these drought patterns often differed substantially from those derived for the entire TPE. This was reflected in variation in the mean yield of the reference genotype. For the TPE and for 2-year METs, restricted maximum likelihood methods were used to estimate components of genotypic and genotype by environment variance. These also varied substantially, although not in direct correlation with frequency of occurrence of different DETs over a 2-year period. Combined analysis over different numbers of seasons demonstrated the expected improvement in the correlation between MET estimates of genotype performance and the overall genotype averages as the number of seasons in the MET was increased.

Social Interaction Effects on Fertility: Intentions and Behaviors

The existing literature shows that social interactions in individuals' networks affect their reproductive attitudes and behaviors through three mechanisms: social influence, social learning, and social support. In this paper, we discuss to what extent the Theory of Planned Behavior (TPB), an individual based theorization of intentions and behavior used to model fertility, takes these social mechanisms into account. We argue that the TPB already integrates social influence and that it could easily accommodate the two other social network mechanisms. By doing so, the theory would be enriched in two respects. First, it will explain more completely how macro level changes eventually ends in micro level changes in behavioral intentions. Indeed, mechanisms of social influence may explain why changes in representations of parenthood and ideal family size can be slower than changes in socio-economic conditions and institutions. Social learning mechanisms should also be considered, since they are crucial to distinguish who adopts new behavioral beliefs and practices, when change at the macro level finally sinks in. Secondly, relationships are a capital of services that can complement institutional offering (informal child care) as well as a capital of knowledge which help individuals navigate in a complex institutional reality, providing a crucial element to explain heterogeneity in the successful realization of fertility intentions across individuals. We develop specific hypotheses concerning the effect of social interactions on fertility intentions and their realization to conclude with a critical review of the existing surveys suitable to test them and their limits.

Simultaneous estimation of indirect and interaction effects using structural equation models

Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting formeasurement error. From the various specifications, Jöreskog and Yang's(1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Ecological Footprint Inequality across countries: the role of environment intensity, income and interaction effects

Recently, White (2007) analysed the international inequalities in Ecological Footprints per capita (EF hereafter) based on a two-factor decomposition of an index from the Atkinson family (Atkinson (1970)). Specifically, this paper evaluated the separate role of environment intensity (EF/GDP) and average income as explanatory factors for these global inequalities. However, in addition to other comments on their appeal, this decomposition suffers from the serious limitation of the omission of the role exerted by probable factorial correlation (York et al. (2005)). This paper proposes, by way of an alternative, a decomposition of a conceptually similar index like Theil’s (Theil, 1967) which, in effect, permits clear decomposition in terms of the role of both factors plus an inter-factor correlation, in line with Duro and Padilla (2006). This decomposition might, in turn, be extended to group inequality components (Shorrocks, 1980), an analysis that cannot be conducted in the case of the Atkinson indices. The proposed methodology is implemented empirically with the aim of analysing the international inequalities in EF per capita for the 1980-2007 period and, amongst other results, we find that, indeed, the interactive component explains, to a significant extent, the apparent pattern of stability observed in overall international inequalities.

Ecological Footprint Inequality across countries: the role of environment intensity, income and interaction effects

Recently, White (2007) analysed the international inequalities in Ecological Footprints per capita (EF hereafter) based on a two-factor decomposition of an index from the Atkinson family (Atkinson (1970)). Specifically, this paper evaluated the separate role of environment intensity (EF/GDP) and average income as explanatory factors for these global inequalities. However, in addition to other comments on their appeal, this decomposition suffers from the serious limitation of the omission of the role exerted by probable factorial correlation (York et al. (2005)). This paper proposes, by way of an alternative, a decomposition of a conceptually similar index like Theil’s (Theil, 1967) which, in effect, permits clear decomposition in terms of the role of both factors plus an inter-factor correlation, in line with Duro and Padilla (2006). This decomposition might, in turn, be extended to group inequality components (Shorrocks, 1980), an analysis that cannot be conducted in the case of the Atkinson indices. The proposed methodology is implemented empirically with the aim of analysing the international inequalities in EF per capita for the 1980-2007 period and, amongst other results, we find that, indeed, the interactive component explains, to a significant extent, the apparent pattern of stability observed in overall international inequalities. Key words: ecological footprint; international environmental distribution; inequality decomposition

The concentration of foreigners in French schools: interaction effects in place?

This paper explores the existence of negative peer-group pressures derived from the concentration of foreigners in French lower secondary schools. Using different dependent variables (number of years spent in lower secondary education, grades in 4th ‘and 3rd year and track election in upper secondary schooling) the analyses indicate that the much disputed existence of significant and negative effects of the concentration of foreign students in schools depends on the method used for the estimation. If we assume that the concentration of foreigners is a random and exogenous process, then the multivariate analyses confirm negative interactions. If, on the contrary, we question the assumption that this contextual information is not end the result of prior sorting mechanisms of individuals across social spaces, the concentration of foreigners has no statistical impact on attainment.

Gene by environment interaction: effects of a single-gene and social-environment on reproductive phenotypes of fire ant queens

1. The gene Pgm-3 (or a closely linked gene) influences the phenotype and reproductive success of queens in multiple-queen (polygynous) colonies but not single-queen (monogynous) colonies of the Fire Ant Solenopsis invicta. 2. We investigated the mechanisms of differential phenotypic expression of Pgm-3 in these alternate social forms. Mature winged queens with the homozygous genotype Pgm-3(a/a) averaged 26% heavier than queens with the genotypes Pgm-3(a/b) and Pgm 3(b/b) in the polygynous form. Heterozygotes were slightly heavier (2%) than Pgm-3(b/b) queens in this form, demonstrating that the allele Pgm-3(a) is not completely recessive in its effects on weight. 3. There was no significant difference in weight among queens of the three Pgm-3 genotypes in the monogynous form, with the mean weight of monogynous queens slightly greater than that of polygynous Pgm-3(a/a) queens. Differences in weight between queens of the two social forms and among queens of the three genotypes in the polygynous form are not evident at the pupal stage and thus appear to develop during sexual maturation of the adults. This suggests that some component of the social environment of polygynous colonies inhibits weight gains during queen maturation and that Pgm-(3a/a) queens are relatively less sensitive to this factor. 4. To test whether the high cumulative queen pheromone level characteristic of polygynous colonies is the factor responsible for the differential queen maturation, we compared phenotypes of winged queens reared in split colonies in which pheromone levels were manipulated by adjusting queen number. Queens produced in colony fragments made monogynous were heavier than those produced in polygynous fragments, a finding consistent with the hypothesis that pheromone level affects the reproductive development of queens. However, genotype-specific differences in weights of queens were similar between the two treatments, suggesting that pheromone level was not the key factor of the social environment responsible for the gene-environment interaction. 5. To test whether limited food availability to winged queens associated with the high brood/worker ratios in polygynous colonies is the factor responsible for this interaction, similar split-colony experiments were performed. Elevated brood/worker ratios decreased the weight of winged queens but there was no evidence that this treatment intensified differential weight gains among queens with different Pgm-3 genotypes. Manipulation of the amount of food provided to colonies had no effect on queen weight. 6. The combined data indicate that cumulative pheromone level and brood/worker ratio are two of the factors responsible for the differences in reproductive phenotypes between monogynous and polygynous winged queens but that these factors are not directly responsible for inducing the phenotypic effects of Pgm-3 in polygynous colonies.

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Simultaneous estimation of indirect and interaction effects using structural equation models

Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting for measurement error. From the various specifications, Jöreskog and Yang's (1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

Genetic group x ambient temperature interaction effects on physiological responses and growth performance of rabbits

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Exchange interaction effects in the ESR spectra of Eu2+ in LaB6

The electron spin resonance (ESR) spectra of Eu2+ (4f(7), S = 7/2) in LaB6 single crystal show a single Dysonian resonance for the localized Eu2+ magnetic moments. It is shown that the Eu2+ ions are covalent exchange coupled to the (B) 2p-like host conduction electrons. (c) 2007 Elsevier B.V. All rights reserved.