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We recently reported an association of offspring educational attainment with polygenic risk scores (PRS) computed on parent’s non-transmitted alleles for educational attainment using the second GWAS meta-analysis article on educational attainment published by the Social Science Genetic Association Consortium. Here we test the replication of these findings using a more powerful PRS from the third GWAS meta-analysis article by the Consortium. Each of the key findings of our previous paper is replicated using this improved PRS (N = 2335 adolescent twins and their genotyped parents). The association of children’s attainment with their own PRS increased substantially with the standardized effect size, moving from β = 0.134, 95% CI = 0.079, 0.188 for EA2, to β = 0.223, 95% CI = 0.169, 0.278, p < .001, for EA3. Parent’s PRS again predicted the socioeconomic status (SES) they provided to their offspring and increased from β = 0.201, 95% CI = 0.147, 0.256 to β = 0.286, 95% CI = 0.239, 0.333. Importantly, the PRS for alleles not transmitted to their offspring — therefore acting via the parenting environment — was increased in effect size from β = 0.058, 95% CI = 0.003, 0.114 to β = 0.067, 95% CI = 0.012, 0.122, p = .016. As previously found, this non-transmitted genetic effect was fully accounted for by parental SES. The findings reinforce the conclusion that genetic effects of parenting are substantial, explain approximately one-third the magnitude of an individual’s own genetic inheritance and are mediated by parental socioeconomic competence.
Large multigenerational cohort studies offer powerful ways to study the hereditary effects on various health outcomes. However, accounting for complex kinship relations in big data structures can be methodologically challenging. The traditional kinship model is computationally infeasible when considering thousands of individuals. In this article, we propose a computationally efficient alternative that employs fractional relatedness of family members through a series of founding members. The primary goal of this study is to investigate whether the effect of determinants on health outcome variables differs with and without accounting for family structure. We compare a fixed-effects model without familial effects with several variance components models that account for heritability and shared environment structure. Our secondary goal is to apply the fractional relatedness model in a realistic setting. Lifelines is a three-generation cohort study investigating the biological, behavioral, and environmental determinants of healthy aging. We analyzed a sample of 89,353 participants from 32,452 reconstructed families. Our primary conclusion is that the effect of determinants on health outcome variables does not differ with and without accounting for family structure. However, accounting for family structure through fractional relatedness allows for estimating heritability in a computationally efficient way, showing some interesting differences between physical and mental quality of life heritability. We have shown through simulations that the proposed fractional relatedness model performs better than the standard kinship model, not only in terms of computational time and convenience of fitting using standard functions in R, but also in terms of bias of heritability estimates and coverage.
Determining (1) the direction of causation and (2) the size of causal effects between two constructs is a central challenge of the scientific study of humans. In the early 1990s, researchers in behavioral genetics invented what was termed the direction of causation (DoC) model to address exactly these two concerns. The model claims that for any two traits whose mode of inheritance is sufficiently different, the direction of causation can be ascertained using a sufficiently large genetically informative sample. Using a series of simulation studies, we demonstrate a major challenge to the DoC model, namely that it is extremely sensitive to even tiny amounts of non-shared confounding. Even under ideal conditions for the DoC model (a large sample, N = 10,000), a large causal relationship (e.g., a causal correlation of .50) with very different modes of inheritance between the two traits (e.g., a pure AE model for one trait and a pure CE model for another trait) and a modest degree (correlation of .10) of non-shared confounding between the two traits results in the choice of the wrong causal models and estimating the wrong causal effects.
Structural equation modeling (SEM) is an important research tool, both for path-based model specification (common in the social sciences) and also for matrix-based models (in heavy use in behavior genetics). We developed umx to give more immediate access, relatively concise syntax and helpful defaults for users in these two broad disciplines. umx supports development, modification and comparison of models, as well as both graphical and tabular outputs. The second major focus of umx, behavior genetic models, is supported via functions implementing standard multigroup twin models. These functions support raw and covariance data, including joint ordinal data, and give solutions for ACE models, including support for covariates, common- and independent-pathway models, and gene × environment interaction models. A tutorial site and question forum are also available.
There is a growing body of literature linking religious attendance to prosocial behavior (PB). The main purposes of the present study were to estimate genetic and environmental influences on the frequency of religious attendance (FRA) and to explore whether and how FRA moderates genetic and/or environmental influences on PB. As part of the Nigerian Twin and Sibling Study, 2860 (280 monozygotic male, 417 monozygotic female, 544 dizygotic male, 699 dizygotic female, and 920 opposite-sex dizygotic) twins (mean age = 14.2 years; SD = 1.7 years; age range = 12–18 years) completed a questionnaire regarding FRA and a PB scale. Similar to the findings from western twin samples, FRA showed substantial shared environmental influences of 74% (95% CI = 69%, 78%), with absence of genetic effects. The phenotypic correlation between FRA and PB was modest but positive and significant (r = .12; p < .01), suggesting that PB is higher among more frequent attenders than among less frequent attenders. The results of gene–environment (G × E) interaction model-fitting analysis revealed that FRA changed individual environmental experiences rather than genetic effects on PB such that while genetic variance was stable, non-shared environmental variance declined, leading the total phenotypic variance of PB to decrease with increasing levels of religious attendance.
This study uses novel approaches to examine genetic and environmental influences shared between childhood behavioral inhibition (BI) and symptoms of preadolescent anxiety disorders. Three hundred and fifty-two twin pairs aged 9–13 and their mothers completed questionnaires about BI and anxiety symptoms. Biometrical twin modeling, including a direction-of-causation design, investigated genetic and environmental risk factors shared between BI and social, generalized, panic and separation anxiety. Social anxiety shared the greatest proportion of genetic (20%) and environmental (16%) variance with BI with tentative evidence for causality. Etiological factors underlying BI explained little of the risk associated with the other anxiety domains. Findings further clarify etiologic pathways between BI and anxiety disorder domains in children.
Twinning is rare among humans, but there is much variability among populations. Several studies show that certain demographic and socioeconomic factors, such as maternal age, mother’s educational level and income, influence twinning rate. There is no background of analytical studies of twins in Uruguay. To the best of our knowledge, this is the first study that has focused on describing and analyzing Uruguayan twinning rates over a period of 17 years (1999–2015). The birth data were collected from the website of Uruguay’s Ministry of Public Health. Economic data were obtained from Uruguay’s Instituto Nacional de Estadísti’s website for the period 2001–2013, since these variables are defined specifically for that period of time. The statistical software R (The R Project for Statistical Computing) was used. The twinning rate varied from 8.51 to 13 in the studied period. Montevideo has the highest median and the smallest variability in comparison with the other departments. In Uruguay (1999–2015), the highest twinning rate (28.94%) was observed in women aged 45 and older. The analysis also showed a relationship between twin birth rates and the mother’s educational level. In three regions of the country (West, Center and East), twin births show a random pattern but in the other two (North and Metropolitan), there is an increasing trend in the number of twins over time. In conclusion, this study recognizes social, economic and demographic factors that influence in the rate of twin births in Uruguay.
It has been suggested that the risk of adverse perinatal outcomes in twin pregnancies is exacerbated by concomitant gestational diabetes mellitus (GDM). This study aimed to assess the risk incurred by twin pregnancy and by a diagnosis of GDM, separately, on the development of poor perinatal outcomes. A retrospective cohort study was conducted on all pregnant women at a tertiary center between 2016 and 2017. The impact of GDM and twin pregnancies on perinatal outcomes — birth weight above the 90th centile for gestational age, cesarean delivery, clinical neonatal hypoglycemia, and premature delivery (before 37 weeks’ gestation) — was assessed using univariate and multivariate analyses. Overall, 13,527 women were eligible for the study; 11,915 were uncomplicated singleton pregnancies; 1379 of these had GDM; 194 were twin pregnancies, and 39 of these had GDM. Univariate analyses showed that twin pregnancies were associated with a higher risk of all perinatal outcomes except macrosomia. In the multivariate analyses, twin pregnancy was a much higher predictor of cesarean delivery (OR 8.40, 95% CI [6.25, 11.49], p < .0001) and preterm birth (OR 58.82, 95% CI [31.25, 125], p < .0001) compared to GDM but GDM was a higher predictor of neonatal hypoglycemia (OR 4.87, 95% CI [3.74, 6.29], p < .0001). Twin pregnancy is more strongly associated with all adverse perinatal outcomes except macrosomia. GDM does not increase risk of adverse perinatal outcomes except for neonatal hypoglycemia.
Twin studies have shown that our sense of humor has an underlying genetic component, but less investigation of the origins of stand-up comedy has been undertaken. This article briefly reviews twin research findings on humor, then describes the working partnership and social affiliation of a pair of monozygotic male twins who perform together as stand-up comedians. The abilities, personalities and temperaments of these twins suggest future avenues for research in this interesting area. Next, findings from twin studies and case reports of twins with cleft lip and palate, dental caries, noninvasive prenatal testing and Capgras syndrome (with folie à deux) are summarized. In conclusion, recent news about athletic twins, transgendered twins, crib-sharing and career choice are presented.