Building causal knowledge in behavior genetics without racial/ethnic diversity will result in weak causal knowledge.

Behavior genetics often emphasizes methods over the underlying quality of the psychological information to which the methods are applied. A core aspect of this quality is the demographic diversity of the samples. Building causal genetic models based only on European-ancestry samples compromises their generalizability. Behavior genetics researchers must spend additional time and resources diversifying their samples before emphasizing causation.

Multilevel Twin Models: Geographical Region as a Third Level Variable.

The classical twin model can be reparametrized as an equivalent multilevel model. The multilevel parameterization has underexplored advantages, such as the possibility to include higher-level clustering variables in which lower levels are nested. When this higher-level clustering is not modeled, its variance is captured by the common environmental variance component. In this paper we illustrate the application of a 3-level multilevel model to twin data by analyzing the regional clustering of 7-year-old children's height in the Netherlands. Our findings show that 1.8%, of the phenotypic variance in children's height is attributable to regional clustering, which is 7% of the variance explained by between-family or common environmental components. Since regional clustering may represent ancestry, we also investigate the effect of region after correcting for genetic principal components, in a subsample of participants with genome-wide SNP data. After correction, region no longer explained variation in height. Our results suggest that the phenotypic variance explained by region might represent ancestry effects on height.

Notes on Three Decades of Methodology Workshops.

Since 1987, a group of behavior geneticists have been teaching an annual methodology workshop on how to use state-of-the-art methods to analyze genetically informative data. In the early years, the focus was on analyzing twin and family data, using information of their known genetic relatedness to infer the role of genetic and environmental factors on phenotypic variation. With the rapid evolution of genotyping and sequencing technology and availability of measured genetic data, new methods to detect genetic variants associated with human traits were developed and became the focus of workshop teaching in alternate years. Over the years, many of the methodological advances in the field of statistical genetics have been direct outgrowths of the workshop, as evidence by the software and methodological publications authored by workshop faculty. We provide data and demographics of workshop attendees and evaluate the impact of the methodology workshops on scientific output in the field by evaluating the number of papers applying specific statistical genetic methodologies authored by individuals who have attended workshops.

Multilevel Modeling in Classical Twin and Modern Molecular Behavior Genetics.

For more than a decade, it has been known that many common behavior genetics models for a single phenotype can be estimated as multilevel models (e.g., van den Oord 2001; Guo and Wang 2002; McArdle and Prescott 2005; Rabe-Hesketh et al. 2007). This paper extends the current knowledge to (1) multiple phenotypes such that the method is completely general to the variance structure hypothesized, and (2) both higher and lower levels of nesting. The multi-phenotype method also allows extended relationships to be considered (see also, Bard et al. 2012; Hadfield and Nakagawa 2010). The extended relationship model can then be continuously expanded to merge with the case typically seen in the molecular genetics analyses of unrelated individuals (e.g., Yang et al. 2011). We use the multilevel form of behavior genetics models to fit a multivariate three level model that allows for (1) child level variation from unique environments and additive genetics, (2) family level variation from additive genetics and common environments, and (3) neighborhood level variation from broader geographic contexts. Finally, we provide R (R Development Core Team 2020) functions and code for multilevel specification of several common behavior genetics models using OpenMx (Neale et al. 2016).

The Boulder Workshop Question Box.

The International Statistical Genetics Workshop (commonly referred to as the "Boulder Workshop") has been held annually in Boulder, Colorado almost every year since 1990. A staple feature of each workshop has been the presence of a "question box" (either a physical box or an online virtual one) where workshop participants are given the opportunity of asking questions to the faculty. In this manuscript, we have compiled a list of ten "classic" questions that have appeared in one form or another across multiple workshops and our attempts at answering them.

Causal Reasoning About Human Behavior Genetics: Synthesis and Future Directions.

When explaining the causes of human behavior, genes are often given a special status. They are thought to relate to an intrinsic human 'essence', and essentialist biases have been shown to skew the way in which causation is assessed. Causal reasoning in general is subject to other pre-existing biases, including beliefs about normativity and morality. In this synthesis we show how factors which influence causal reasoning can be mapped to a framework of genetic essentialism, which reveals both the shared and unique factors underpinning biases in causal reasoning and genetic essentialism. This comparison identifies overlooked areas of research which could provide fruitful investigation, such as whether normative assessments of behaviors influence the way that genetic causes are ascribed or endorsed. We also outline the importance of distinguishing reasoning processes regarding genetic causal influences on one's self versus others, as different cognitive processes and biases are likely to be at play.

Post-genomic behavioral genetics: From revolution to routine.

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www. RESEARCH: va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

Publication Trends Over 55 Years of Behavioral Genetic Research.

We document the growth in published papers on behavioral genetics for 5-year intervals from 1960 through 2014. We used 1861 papers published in Behavior Genetics to train our search strategy which, when applied to Ovid PsychINFO, selected more than 45,000 publications. Five trends stand out: (1) the number of behavioral genetic publications has grown enormously; nearly 20,000 papers were published in 2010-2014. (2) The number of human quantitative genetic (QG) publications (e.g., twin and adoption studies) has steadily increased with more than 3000 papers published in 2010-2014. (3) The number of human molecular genetic (MG) publications increased substantially from about 2000 in 2000-2004 to 5000 in 2005-2009 to 9000 in 2010-2014. (4) Nonhuman publications yielded similar trends. (5) Although there has been exponential growth in MG publications, both human and nonhuman QG publications continue to grow. A searchable resource of this corpus of behavioral genetic papers is freely available online at http://www.teds.ac.uk/public_datasets.html and will be updated annually.

Genetics and neuropsychology: A merger whose time has come.

Genetics and neuropsychology have historically been 2 rather distant and unrelated fields. With the very rapid advances that have been taking place in genetics, research and treatment of disorders of cognition in the 21st century are likely to be increasingly informed by individual differences in genetics and epigenetics. Although neuropsychologists are not expected to become geneticists, it is our view that increased training in genetics should become more central to training in neuropsychology. This relationship should not be unidirectional. Here we note ways in which an understanding of genetics and epigenetics can inform neuropsychology. On the other hand, given the complexity of cognitive phenotypes, neuropsychology can also play a valuable role in informing and refining genetic studies. Greater integration of the 2 should advance both fields.

Genetic Prediction.

The fundamental reason that the genetics of behavior has remained so controversial for so long is that the layer of theory between data and their interpretation is thicker and more opaque than in more established areas of science. The finding that variations in tiny snippets of DNA have small but detectable relations to variation in behavior surprises no one, at least no one who was paying attention to the twin studies. How such snippets of DNA are related to differences in behavior-known as the gene-to-behavior pathway-is the great theoretical problem of modern behavioral genetics. Given that intentional human breeding is a horrific prospect, what kind of technology might we want (or fear) out of human behavioral genetics? One possibility is a technology that could predict important behavioral characteristics of humans based on their genomes alone. A moment's thought suggests significant benefits and risks that might be associated with such a possibility, but for the moment, just consider how convincing it would be if on the day of a baby's birth we could make meaningful predictions about whether he or she would become a concert pianist or an alcoholic. This article will consider where we are right now as regards that possibility, using human height and intelligence as the primary examples.

What Does Behavioral Genetics Offer for Improving Educaton?

For much of its history, behavioral genetics, or research into the influence genetics has on human behavior, has been associated with a pessimistic view of educational reforms' potential to make much difference in improving educational outcomes or reducing inequality. Recently, however, some behavioral geneticists have begun to speak in more optimistic terms about the promise of genetically informed education to improve learning for all children, especially those who are socially or economically disadvantaged. This shift in emphasis should be welcome news for everyone interested in promoting educational improvement who worried that behavioral genetics offered support for the status quo. However, I think it amounts to little more than a shift in tone. Behavioral genetics, I will argue, does not advance educational reform: its proposed solutions are rooted in the limits, not the strength, of behavioral genetics knowledge; repeat the ideas of earlier U.S. educational reform efforts; and rely on a naive optimism about the power of choice and personalization.

Behavior genetics: past, present, future.

The disciplines of developmental psychopathology and behavior genetics are concerned with many of the same questions about the etiology and course of normal and abnormal behavior and about the factors that promote typical development despite the presence of risk. The goal of this paper is to summarize how research in behavior genetics has shed light on questions that are central to developmental psychopathology. We briefly review the origins of behavior genetics, summarize the findings that have been gleaned from several decades of quantitative and molecular genetics research, and describe future directions for research that will delineate gene function as well as pathways from genes to brain to behavior. The importance of environmental contributions, at both genetic and epigenetic levels, will be discussed. We conclude that behavior genetics has made significant contributions to developmental psychopathology by documenting the interplay among risk and protective factors at multiple levels of the organism, by clarifying the causal status of risk exposures, and by identifying factors that account for change and stability in psychopathology. As the tools to identify gene function become increasingly sophisticated, and as behavioral geneticists become increasingly interdisciplinary in their scope, the field is poised to make ever greater contributions to our understanding of typical and atypical development.

The future of genomics for developmentalists.

The momentum of genomic science will carry it far into the future and into the heart of research on typical and atypical behavioral development. The purpose of this paper is to focus on a few implications and applications of these advances for understanding behavioral development. Quantitative genetics is genomic and will chart the course for molecular genomic research now that these two worlds of genetics are merging in the search for many genes of small effect. Although current attempts to identify specific genes have had limited success, known as the missing heritability problem, whole-genome sequencing will improve this situation by identifying all DNA sequence variations, including rare variants. Because the heritability of complex traits is caused by many DNA variants of small effect in the population, polygenic scores that are composites of hundreds or thousands of DNA variants will be used by developmentalists to predict children's genetic risk and resilience. The most far-reaching advance will be the widespread availability of whole-genome sequence for children, which means that developmentalists would no longer need to obtain DNA or to genotype children in order to use genomic information in research or in the clinic.

What psychiatric genetics has taught us about the nature of psychiatric illness and what is left to learn.

Psychiatric genetics has taught us a great deal about the nature of psychiatric disorders. Traditional family, twin and adoption studies have demonstrated the substantial role of genetic factors in their etiology, clarified the role of genetic factors in comorbidity, elucidated development pathways, and documented the importance of gene-environment correlation and interaction. We have also received some hard lessons when we were unable to detect replicable genes of large effect size and found that our much-valued candidate genes did not live up to their expected promise. With more mature molecular and statistical methods, we are entering now a different era. Statistical analyses of aggregate molecular signals are validating earlier heritability estimates. Replicated findings from genome-wide association studies are beginning to emerge, as are discoveries of large-effect size rare genomic variants. The number of such findings is likely to soon grow dramatically. The most pressing question facing the field is what biological picture these results will reveal. I articulate four possible scenarios that reflect (i) no, (ii) minimal, (iii) moderate and (iv) high biological coherence in the replicated molecular variant findings, which are soon likely to emerge. I discuss the factors that will likely influence these patterns, including the problems of etiological heterogeneity and multiple realizability. These findings could provide critical insights into the underlying biology of our psychiatric syndromes and potentially permit us to perceive, 'through a glass darkly,' the levels of the mind-brain system that are disordered.

Insatisfacción corporal en la adolescencia: Evolución en una década / Body dissatisfaction in adolescence. Changes in a decade

La presente investigación examina los cambios en la imagen corporal y en el índice de masa corporal ocurridos en un periodo de 11 años en una muestra de adolescentes españoles con edades comprendidas entre los 13 y 21 años. Los datos provienen de dos submuestras recogidas en el año 1997 (n = 3468) y en el año 2008 (n = 846). La imagen corporal fue operacionalizada por medio de la escala insatisfacción corporal perteneciente al inventario de trastornos de la conducta alimentaria (Garner, 1998, 2004). Los resultados pusieron de manifiesto que el índice de masa corporal es una covariable importante en el estudio de la insatisfacción corporal. Se observó una disminución no-significativa de los valores medios de insatisfacción corporal en la muestra de mujeres. Las puntuaciones de los varones no han cambiado durante los últimos 11 años (AU)

This study examines the changes in adolescents’ body image and body mass index over the last 11 years. Data came from two different subsamples collected in the years 1997 (n = 3468) and 2008 (n = 846). The body image was assessed by the Body Dissatisfaction scale belonging to Eating Disorder Inventory (Garner, 1998, 2004). The results showed that the Body Mass Index is an important covariable in the study of the body dissatisfaction. The body dissatisfaction mean values decreased in the female sample, although the observed reduction was not statistically significant. The male’s values didn’t change over the last 11 years (AU)

Genetics in Psychiatry - up-to-date review 2011.

Psychiatric genetics is a popular and much-discussed topic. Many candidate genes have been investigated in relation to psychiatric disorders and many connections have been found. The utilization of these investigations is currently at a theoretical level. Nevertheless, these findings of candidate genes will be important for further research and subsequent clinical use, for example in pharmacogenetics). Due to the rapidly growing number of empirical studies that provide profound analysis of different genes and their variants in different psychiatrical symptomatology, the field is highly divided, and providing a succinct overview is challenging. This article attempts to provide an up-to-date review of the most important and most discussed genes (mainly transporter and receptor genes) contributing to the etiology of psychiatric disorders.