Brendan P. Zietsch

Genetic and environmental influences on cannabis use initiation and problematic use: A meta-analysis of twin studies

BACKGROUND Because cannabis use is associated with social, physical and psychological problems, it is important to know what causes some individuals to initiate cannabis use and a subset of those to become problematic users. Previous twin studies found evidence for both genetic and environmental influences on vulnerability, but due to considerable variation in the results it is difficult to draw clear conclusions regarding the relative magnitude of these influences. METHODS A systematic literature search identified 28 twin studies on cannabis use initiation and 24 studies on problematic cannabis use. The proportion of total variance accounted for by genes (A), shared environment (C) and unshared environment (E) in (i) initiation of cannabis use and (ii) problematic cannabis use was calculated by averaging corresponding A, C and E estimates across studies from independent cohorts and weighting by sample size. RESULTS For cannabis use initiation, A, C and E estimates were 48%, 25% and 27% in males and 40%, 39% and 21% in females. For problematic cannabis use A, C and E estimates were 51%, 20% and 29% for males and 59%, 15% and 26% for females. Confidence intervals of these estimates are considerably narrower than those in the source studies. CONCLUSIONS Our results indicate that vulnerability to both cannabis use initiation and problematic use was influenced significantly by A, C and E. There was a trend for a greater C and lesser A component for cannabis use initiation compared to problematic use for females.

MAINTENANCE OF GENETIC VARIATION IN HUMAN PERSONALITY: TESTING EVOLUTIONARY MODELS BY ESTIMATING HERITABILITY DUE TO COMMON CAUSAL VARIANTS AND INVESTIGATING THE EFFECT OF DISTANT INBREEDING

Personality traits are basic dimensions of behavioral variation, and twin, family, and adoption studies show that around 30% of the between‐individual variation is due to genetic variation. There is rapidly growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome‐wide single nucleotide polymorphism (SNP) data from > 8000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation–selection balance.

Common and specific genetic influences on EEG power bands delta, theta, alpha, and beta

It is difficult to study the genetic basis of psychological function/dysfunction due to its etiological complexity. Instead, we studied a biological marker, EEG power, which is associated with various psychological phenotypes and is closer to gene function. Previous studies have consistently demonstrated high heritability of EEG band power, but less is known about how common or specific genes influence each power band. For 519 adolescent twin pairs, spectral powers were calculated for delta, theta, alpha, and beta bands at bilateral occipital and frontal sites. All four bands were entered into a multivariate genetic model, with occipital and frontal sites modelled separately. Variance was decomposed into additive (A) and dominant (D) genetic factors, and common (C) and unique (E) environmental factors. Band heritabilities were higher at occipital (0.75-0.86) than frontal sites (0.46-0.80). Both common and specific genetic factors influenced the bands, with common genetic and specific genetic factors having more influence in the occipital and frontal regions, respectively. Non-additive genetic effects on beta power and a common environment effect on delta, theta, and alpha powers were observed in the frontal region.

Variation in human mate choice: Simultaneously investigating heritability, parental influence, sexual imprinting, and assortative mating

Human mate choice is central to individuals’ lives and to the evolution of the species, but the basis of variation in mate choice is not well understood. Here we looked at a large community-based sample of twins and their partners and parents ( individuals) to test for genetic and family environmental influences on mate choice, while controlling for and not controlling for the effects of assortative mating. Key traits were analyzed, including height, body mass index, age, education, income, personality, social attitudes, and religiosity. This revealed near-zero genetic influences on male and female mate choice over all traits and no significant genetic influences on mate choice for any specific trait. A significant family environmental influence was found for the age and income of females’ mate choices, possibly reflecting parental influence over mating decisions. We also tested for evidence of sexual imprinting, where individuals acquire mate-choice criteria during development by using their opposite-sex parent as the template of a desirable mate; there was no such effect for any trait. The main discernible pattern of mate choice was assortative mating; we found that partner similarity was due to initial choice rather than convergence and also at least in part to phenotypic matching.

Do shared etiological factors contribute to the relationship between sexual orientation and depression

BACKGROUND Gays, lesbians and bisexuals (i.e. non-heterosexuals) have been found to be at much greater risk for many psychiatric symptoms and disorders, including depression. This may be due in part to prejudice and discrimination experienced by non-heterosexuals, but studies controlling for minority stress, or performed in very socially liberal countries, suggest that other mechanisms must also play a role. Here we test the viability of common cause (shared genetic or environmental etiology) explanations of elevated depression rates in non-heterosexuals. METHOD A community-based sample of adult twins (n=9884 individuals) completed surveys investigating the genetics of psychiatric disorder, and were also asked about their sexual orientation. Large subsets of the sample were asked about adverse childhood experiences such as sexual abuse, physical abuse and risky family environment, and also about number of older brothers, paternal and maternal age, and number of close friends. Data were analyzed using the classical twin design. RESULTS Non-heterosexual males and females had higher rates of lifetime depression than their heterosexual counterparts. Genetic factors accounted for 31% and 44% of variation in sexual orientation and depression respectively. Bivariate analysis revealed that genetic factors accounted for a majority (60%) of the correlation between sexual orientation and depression. In addition, childhood sexual abuse and risky family environment were significant predictors of both sexual orientation and depression, further contributing to their correlation. CONCLUSIONS Non-heterosexual men and women had elevated rates of lifetime depression, partly due to shared etiological factors, although causality cannot be definitively resolved.

Experimental evidence that women's mate preferences are directly influenced by cues of pathogen prevalence and resource scarcity

When choosing a mate, women are thought to face a trade-off between genetic and parental quality. Recent research suggests that this trade-off is influenced by environmental factors such as pathogen prevalence and resource scarcity, which affect the relative value of genetic and parental quality to offspring fitness. To further investigate these findings, the current study primed 60 women with pathogen prevalence, resource scarcity or an irrelevant threat, before administering a forced trade-off task that assessed mate preferences for traits thought to be indicative of genetic or parental quality. Women primed with pathogen prevalence revealed greater preferences for traits indicative of genetic quality at the expense of traits indicative of parental quality. The reverse was found for women primed with resource scarcity. These findings suggest that environmental factors may directly influence womens mate preferences owing to evolved plasticity, such that mate preferences are flexible in response to environmental factors.

Perfect genetic correlation between number of offspring and grandoffspring in an industrialized human population

Significance Reproductive success (offspring quantity) is widely used as a measure of fitness (genetic contribution to future generations). Accurate predictions of the direction and magnitude of evolutionary change using this measure depend on the untested assumption that the genes influencing number of offspring are the same as those influencing number of grandoffspring. Using a population sample of identical and nonidentical Swedish twins and their descendants, we show that the genetic influences on number of offspring and grandoffspring are identical, supporting the use of reproductive success as a measure of fitness in comparable human populations. Reproductive success is widely used as a measure of fitness. However, offspring quantity may not reflect the genetic contribution to subsequent generations if there is nonrandom variation in offspring quality. Offspring quality is likely to be an important component of human fitness, and tradeoffs between offspring quantity and quality have been reported. As such, studies using offspring quantity as a proxy for fitness may yield erroneous projections of evolutionary change, for example if there is little or no genetic variance in number of grandoffspring or if its genetic variance is to some extent independent of the genetic variance in number of offspring. To address this, we performed a quantitative genetic analysis on the reproductive history of 16,268 Swedish twins born between 1915 and 1929 and their offspring. There was significant sex limitation in the sources of familial variation, but the magnitudes of the genetic and environmental effects were the same in males and females. We found significant genetic variation in number of offspring and grandoffspring (heritability = 24% and 16%, respectively), and genetic variation in the two variables completely overlapped—i.e., there was a perfect genetic correlation between number of offspring and grandoffspring. Shared environment played a smaller but significant role in number of offspring and grandoffspring; again, there was a perfect shared environmental correlation between the two variables. These findings support the use of lifetime reproductive success as a proxy for fitness in populations like the one used here, but we caution against generalizing this conclusion to other kinds of human societies.

Estimating heritability from twin studies.

This chapter describes how the heritability of a trait can be estimated using data collected from pairs of twins. The principles of the classical twin design are described, followed by the assumptions and possible extensions of the design. In the second part of this chapter, two example scripts are presented and described, explaining the basic steps for estimating heritability using the statistical program OpenMx. OpenMx and the scripts used for this chapter can be downloaded so that readers can adapt and use the scripts for their own purposes.

Fractal Analysis: Pitfalls and Revelations in Neuroscience

Fractal analysis has become a popular method in all branches of scientific investigation including ecology, physics and medicine. The method is often used to determine effects such as impact of cattle grazing, the distribution of stars within a galaxy or whether tissue is pathological. However several aspects of fractal analysis are not often considered when interpreting results communicated in the literature. These include the concept that no presentation of any pattern on a computer, even for an ideal fractal, is truly fractal. Pre-processing that is also required, such as scanning of images and resizing play a role in the variation of the final fractal dimension. In addition D is also a function of the fractal analysis method used and how the final fractal dimension is determined. To obtain a better overview of the effects of the steps involved in fractal analysis and the utility of this method, this chapter describes, using biological material from neuroscience, a non fractal based method, Sholl analysis and continues by discussing various processing options and the results obtained using fractal analysis. The effect of different fractal analysis methods, different computer applications of the same method, scale and resolution as well as regression analysis, which is for most methods the final step in determining D are discussed. This provides a platform for a better understanding of fractal analysis in research fields other than physics and mathematics and a more meaningful interpretation of results.

Genetic Basis of a Cognitive Complexity Metric

Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ), reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787). Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG), followed by meta-analysis (N>6500) at the single marker level. Twin modelling showed RC is highly heritable (67%), has considerable genetic overlap with IQ (59%), and is a major component of genetic covariation between reasoning and working memory (72%). At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB), and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.