Although it is well known that parental depression is transmitted within families across generations, the etiology of this transmission remains unclear. Our goal was to develop a novel study design capable of explicitly examining the etiologic sources of intergenerational transmission. We specifically leveraged naturally-occurring variations in genetic relatedness between parents and their adolescent children in the 720 families participating in the Nonshared Environment in Adolescent Development (NEAD) study, 58.5% of which included a rearing stepparent (nearly always a stepfather). Results pointed squarely to the environmental transmission of psychopathology between fathers and children. Paternal depression was associated with adolescent depression and adolescent behavior problems (i.e., antisocial behavior, headstrong behavior, and attention problems) regardless of whether or not fathers and their children were genetically related. Moreover, these associations persisted to a subset of “blended” families in which the father was biologically related to one participating child but not to the other, and appeared to be mediated via father–child conflict. Such findings are not only fully consistent with the environmental transmission of psychopathology across generations, but also add to extant evidence that parent–child conflict is a robust and at least partially environmental predictor of adolescent psychopathology.

Conventional longitudinal behavioral genetic models estimate the relative contribution of genetic and environmental factors to stability and change of traits and behaviors. Longitudinal models rarely explain the processes that generate observed differences between genetically and socially related individuals. We propose that exchanges between individuals and their environments (i.e., phenotype–environment effects) can explain the emergence of observed differences over time. Phenotype–environment models, however, would require violation of the independence assumption of standard behavioral genetic models; that is, uncorrelated genetic and environmental factors. We review how specification of phenotype–environment effects contributes to understanding observed changes in genetic variability over time and longitudinal correlations among nonshared environmental factors. We then provide an example using 30 days of positive and negative affect scores from an all-female sample of twins. Results demonstrate that the phenotype–environment effects explain how heritability estimates fluctuate as well as how nonshared environmental factors persist over time. We discuss possible mechanisms underlying change in gene–environment correlation over time, the advantages and challenges of including gene–environment correlation in longitudinal twin models, and recommendations for future research.

Despite increased focus on ascertaining the status of elasmobranch fish, the stock units for many species are uncertain. Data from mark-recapture tagging studies undertaken from 1959–2017 were analysed for 13 batoid species. Data were most comprehensive for skates (Rajidae), with 22,374 released and 3342 (14.9%) returned. Most data related to thornback ray Raja clavata, blonde ray R. brachyura and spotted ray R. montagui. Tags were generally returned from areas less than 50 km from their release, and usually from the ICES Division in which they were released. However, straight-line distances travelled of up to 910 km (R. brachyura) and 772 km (R. clavata) were recorded, highlighting that individual skates are capable of longer-distance movements. The maximum time at liberty was 16.6 years (R. clavata). Whilst mark-recapture data indicated that the current stock units used by ICES are broadly appropriate, southward movements of several skate species tagged off Northern Ireland (Division 6.a) to the Irish Sea (Division 7.a) were observed. In contrast, skates tagged in the Irish Sea and Bristol Channel (Division 7.f) generally remained in that area, with only occasional recaptures from Division 6.a.

The primary aim of the Michigan State University Twin Registry (MSUTR) is to examine developmental differences in genetic, environmental, neural, epigenetic, and neurobiological influences on psychopathology and resilience, particularly during childhood and adolescence. The MSUTR has two broad components: a large-scale, population-based registry of child, adolescent, and adult twins and their families (current N ~30,000) and a series of more focused and in-depth studies drawn from the registry (projected N ~7200). Participants in the population-based registry complete a family health and demographic questionnaire via mail. Families can then be recruited for one or more of the intensive, in-person studies from the population-based registry, using any one of several recruitment strategies (e.g., population-based, based on their answers to the registry questionnaire). These latter studies target a variety of biological, genetic, and environmental phenotypes, including multi-informant measures of psychiatric and behavioral phenotypes, functional and structural neuroimaging, comprehensive measures of the twin family environment (e.g., census and neighborhood informant reports of twin neighborhood characteristics, videotaped interactions of child twin families), buccal swab and salivary DNA samples, and/or assays of adolescent and adult steroid hormone levels. This article provides an overview of the MSUTR and describes current and future research directions.

The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural–geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.

Available twin-family data on sex differences in antisocial behavior (ASB) simultaneously suggest that ASB is far more prevalent in males than in females, and that its etiology (i.e. the effects of genes, environments, hormones, culture) does not differ across sex. This duality presents a conundrum: How do we make sense of mean sex differences in ASB if not via differences in genes, environments, hormones, and/or cultures? The current selective review and critique explores possible contributions to these seemingly incompatible sets of findings. We asked whether the presence of sex differences in behavior could be smaller than is typically assumed, or confined to a specific set of behaviors. We also asked whether there might be undetected differences in etiology across sex in twin-family studies. We found little evidence that bias or measurement invariance across sex account for phenotypic sex differences in ASB, but we did identify some key limitations to current twin-family approaches. These included the questionable ability of qualitative sex difference analyses to detect gender norms and prenatal exposure to testosterone, and concerns regarding specific analytic components of quantitative sex difference analyses. We conclude that the male preponderance in ASB is likely to reflect a true sex difference in observed behavior. It was less clear, however, that the genetic and environmental contributions to ASB are indeed identical across sex, as argued by prior twin-family studies. It is our hope that this review will inspire the development of new, genetically-informed methods for studying sex differences in etiology.

Using recent substantive results on China and the West, we highlight some virtues to Mill's method of residues for comparative network research. The result is research that combines the emic-etic approaches discussed by Leung (2009) with the spirit of Whetten's (2009: 49) efforts to make ‘theory borrowing more context sensitive’. We draw on recent comparative research about the competitive advantage enjoyed by network brokers, trust facilitated by embedding a relationship in a closed network, the subset of Chinese relations that constitute guanxi, the idea of American and European guanxi, different business environments maintained by the same network mechanism, cocoon networks, small-world networks, the longer history apparent in Chinese networks, and job search via colleagues, friends, and family. We also illustrate the value of data graphs for the expository value of the method of residuals in comparative network analyses.

Although there is growing recognition that disadvantaged contexts attenuate genetic influences on youth misbehavior, it is not yet clear how this dampening occurs. The current study made use of a “geographic contagion” model to isolate specific contexts contributing to this effect, with a focus on nonaggressive rule-breaking behaviors (RB) in the families’ neighbors. Our sample included 847 families residing in or near modestly-to-severely disadvantaged neighborhoods who participated in the Michigan State University Twin Registry. Neighborhood sampling techniques were used to recruit neighbors residing within 5km of a given family (the mean number of neighbors assessed per family was 13.09; range, 1–47). Analyses revealed clear evidence of genotype–environment interactions by neighbor RB, such that sibling-level shared environmental influences on child RB increased with increasing neighbor self-reports of their own RB, whereas genetic influences decreased. Moreover, this moderation appeared to be driven by geographic proximity to neighbors. Sensitivity analyses further indicated that this effect was specifically accounted for by higher levels of neighbor joblessness, rather than elements of neighbor RB that would contribute to neighborhood blight or crime. Such findings provocatively suggest that future genotype–environment interactions studies should integrate the dynamic networks of social contagion theory.

We extend Burt, Burzynska, and Opper's cross-sectional network prediction of relative success among Chinese entrepreneurs by predicting which ventures are still active five years later. The cross-sectional analysis is corroborated in three ways (despite the vicissitudes of a national anti-corruption campaign): (1) Businesses run in 2012 by CEOs with a network rich in structural holes are more likely to be active five years later, in 2017. (2) Survival odds are improved if the large, open network around a CEO in 2012 was initially a supportive ‘cocoon’ closed network when the business was founded. (3) Both results are contingent on capturing the guanxi ties valuable early in the history of the business. The two network effects disappear when the network around a CEO is limited to his or her currently valued contacts. Beyond corroboration, we find that advantage is concentrated in ventures that began well and had become successful. Network advantage here does not compensate for weakness – it is a mechanism for cumulative advantage, amplifying the success of businesses already doing well.

Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.

We trace the social networks around Chinese entrepreneurs back to their firm's founding to learn about the role early events play in the later success of a business. We use name generator questions paired with career history questions to identify ‘event contacts’ missed by the usual focus on current business. We draw four conclusions from interviews with a large, stratified random sample of entrepreneurs: (1) Relations with event contacts stand out for guanxi qualities of high trust relatively independent of the surrounding network structure, and are critical to distinguishing more successful entrepreneurs from the less successful. (2) The substance of a significant event matters less than the fact that the entrepreneur deems it significant. (3) When family is turned to for support it is most likely at founding, but family is not the usual source of support at founding. Rather, entrepreneurs turn to people they have known for many years, typically people beyond the entrepreneur's family. (4) The transition from founding to first significant event stands out as distinctly consequential for later success. Entrepreneurs who turn for help on their first significant event to a person separate from, but especially close to, the founding contact are more successful in their business development. That early move is not visible in the later network around the entrepreneur.