Structured latent growth curves for twin data

Research Review: A guide to computing and implementing polygenic scores in developmental research

The increasing availability of genotype data in longitudinal population- and family-based samples provides opportunities for using polygenic scores (PGS) to study developmental questions in child and adolescent psychology and psychiatry. Here, we aim to provide a comprehensive overview of how PGS can be generated and implemented in developmental psycho(patho)logy, with a focus on longitudinal designs. As such, the paper is organized into three parts: First, we provide a formal definition of polygenic scores and related concepts, focusing on assumptions and limitations. Second, we give a general overview of the methods used to compute polygenic scores, ranging from the classic approach to more advanced methods. We include recommendations and reference resources available to researchers aiming to conduct PGS analyses. Finally, we focus on the practical applications of PGS in the analysis of longitudinal data. We describe how PGS have been used to research developmental outcomes, and how they can be applied to longitudinal data to address developmental questions.

Genetic Influences on Longitudinal Trajectories of Cortical Thickness and Surface Area during the First 2 Years of Life

Genetic influences on cortical thickness (CT) and surface area (SA) are known to vary across the life span. Little is known about the extent to which genetic factors influence CT and SA in infancy and toddlerhood. We performed the first longitudinal assessment of genetic influences on variation in CT and SA in 501 twins who were aged 0-2 years. We observed substantial additive genetic influences on both average CT (0.48 in neonates, 0.37 in 1-year-olds, and 0.44 in 2-year-olds) and total SA (0.59 in neonates, 0.74 in 1-year-olds, and 0.73 in 2-year-olds). In addition, we found strong heritability of the change in average CT (0.49) from neonates to 1-year-olds, but not from 1- to 2-year-olds. Moreover, we found strong genetic correlations for average CT (rG = 0.92) between 1- and 2-year-olds and strong genetic correlations for total SA across all timepoints (rG = 0.96 between neonates and 1-year-olds, rG = 1 between 1- and 2-year-olds). In addition, we found CT and SA are strongly genetic correlated at birth, but weaken over time. Overall, results suggest a dynamic genetic relationship between CT and SA during first 2 years of life and provide novel insights into how genetic influences shape the cortical structure during early brain development.

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).

How nonshared environmental factors come to correlate with heredity

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.

The Dynamic Associations Between Cortical Thickness and General Intelligence are Genetically Mediated

The neural substrates of intelligence represent a fundamental but largely uncharted topic in human developmental neuroscience. Prior neuroimaging studies have identified modest but highly dynamic associations between intelligence and cortical thickness (CT) in childhood and adolescence. In a separate thread of research, quantitative genetic studies have repeatedly demonstrated that most measures of intelligence are highly heritable, as are many brain regions associated with intelligence. In the current study, we integrate these 2 streams of prior work by examining the genetic contributions to CT-intelligence relationships using a genetically informative longitudinal sample of 813 typically developing youth, imaged with high-resolution MRI and assessed with Wechsler Intelligence Scales (IQ). In addition to replicating the phenotypic association between multimodal association cortex and language centers with IQ, we find that CT-IQ covariance is nearly entirely genetically mediated. Moreover, shared genetic factors drive the rapidly evolving landscape of CT-IQ relationships in the developing brain.

Longitudinal Twin Study of Subjective Health: Differences in Genetic and Environmental Components of Variance Across Age and Sex

OBJECTIVE

The current analysis examines sex differences in longitudinal changes in genetic and environmental influences on three measures of subjective health (SH).

METHOD

Sample includes 7,372 twins (mean intake age = 73.22) with up to 8 waves of measurement (mean = 3.1). Three SH items were included: general self-rated health (SRH), health compared to age peers (COMP), and impact of health on activities (ACT) which previous research shows capture different frames of reference.

RESULTS

Latent growth curve modeling indicated significant differences across gender and frame of reference in trajectories of change with age and in genetic and environmental contributions to change. Men have higher mean scores on all three SH measures, indicating better SH, but there were no sex differences in pattern of change with age. Accelerating declines with age were found for SRH and ACT, whereas COMP improved with age. Results indicated more genetic variance for women than men, but declining genetic variance for both after age 70. Increasing shared environmental variance with increasing age was also found for both sexes.

DISCUSSION

As aging triggers a re-evaluation of the meaning of "good health," physical aspects of health may become less important and shared cultural conceptions of health may become more relevant. This change in conceptions of good health may reflect both aging and the change in composition of the elderly population as a result of selective survival.

The Genetic Contributions to Maturational Coupling in the Human Cerebrum: A Longitudinal Pediatric Twin Imaging Study

Although prior studies have demonstrated that genetic factors play the dominant role in the patterning of the pediatric brain, it remains unclear how these patterns change over time. Using 1748 longitudinal anatomic MRI scans from 792 healthy twins and siblings, we quantified how genetically mediated inter-regional associations change over time via multivariate longitudinal structural equation modeling. These analyses found that genetic correlations for both lobar volumes and cortical thickness are dynamic, with relatively static effects on surface area. While genetic correlations for lobar volumes decrease over childhood and adolescence, in general they increase for cortical thickness in the second decade of life. Quantification of how genetic factors influence maturational coupling improves our understanding of typical neurodevelopment and informs future molecular genetic analyses.

Etiology of Stability and Growth of Internalizing and Externalizing Behavior Problems Across Childhood and Adolescence

Internalizing and externalizing behaviors are heritable, and show genetic stability during childhood and adolescence. Less work has explored how genes influence individual differences in developmental trajectories. We estimated ACE biometrical latent growth curve models for the Teacher Report Form (TRF) and parent Child Behavior Checklist (CBCL) internalizing and externalizing scales from ages 7 to 16 years in 408 twin pairs from the Colorado Longitudinal Twin Study. We found that Intercept factors were highly heritable for both internalizing and externalizing behaviors (a2 = .61-.92), with small and nonsignificant environmental influences for teacher-rated data but significant nonshared environmental influences for parent-rated data. There was some evidence of heritability of decline in internalizing behavior (Slopes for teacher and parent ratings), but the Slope genetic variance was almost entirely shared with that for the Intercept when different than zero. These results suggest that genetic effects on these developmental trajectories operate primarily on initial levels and stability, with no significant unique genetic influences for change. Finally, cross-rater analyses of the growth factor scores revealed moderate to large genetic and environmental associations between growth factors derived from parents' and teachers' ratings, particularly the Intercepts.

The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design

The ABCD twin study will elucidate the genetic and environmental contributions to a wide range of mental and physical health outcomes in children, including substance use, brain and behavioral development, and their interrelationship. Comparisons within and between monozygotic and dizygotic twin pairs, further powered by multiple assessments, provide information about genetic and environmental contributions to developmental associations, and enable stronger tests of causal hypotheses, than do comparisons involving unrelated children. Thus a sub-study of 800 pairs of same-sex twins was embedded within the overall Adolescent Brain and Cognitive Development (ABCD) design. The ABCD Twin Hub comprises four leading centers for twin research in Minnesota, Colorado, Virginia, and Missouri. Each site is enrolling 200 twin pairs, as well as singletons. The twins are recruited from registries of all twin births in each State during 2006-2008. Singletons at each site are recruited following the same school-based procedures as the rest of the ABCD study. This paper describes the background and rationale for the ABCD twin study, the ascertainment of twin pairs and implementation strategy at each site, and the details of the proposed analytic strategies to quantify genetic and environmental influences and test hypotheses critical to the aims of the ABCD study.

Sum Scores in Twin Growth Curve Models: Practicality Versus Bias

To study behavioral or psychiatric phenotypes, multiple indices of the behavior or disorder are often collected that are thought to best reflect the phenotype. Combining these items into a single score (e.g. a sum score) is a simple and practical approach for modeling such data, but this simplicity can come at a cost in longitudinal studies, where the relevance of individual items often changes as a function of age. Such changes violate the assumptions of longitudinal measurement invariance (MI), and this violation has the potential to obfuscate the interpretation of the results of latent growth models fit to sum scores. The objectives of this study are (1) to investigate the extent to which violations of longitudinal MI lead to bias in parameter estimates of the average growth curve trajectory, and (2) whether absence of MI affects estimates of the heritability of these growth curve parameters. To this end, we analytically derive the bias in the estimated means and variances of the latent growth factors fit to sum scores when the assumption of longitudinal MI is violated. This bias is further quantified via Monte Carlo simulation, and is illustrated in an empirical analysis of aggression in children aged 3-12 years. These analyses show that measurement non-invariance across age can indeed bias growth curve mean and variance estimates, and our quantification of this bias permits researchers to weigh the costs of using a simple sum score in longitudinal studies. Simulation results indicate that the genetic variance decomposition of growth factors is, however, not biased due to measurement non-invariance across age, provided the phenotype is measurement invariant across birth-order and zygosity in twins.

Genetic and environmental influences on the codevelopment among borderline personality disorder traits, major depression symptoms, and substance use disorder symptoms from adolescence to young adulthood

Although borderline personality disorder (BPD) traits decline from adolescence to adulthood, comorbid psychopathology such as symptoms of major depressive disorder (MDD), alcohol use disorder (AUD), and drug use disorders (DUDs) likely disrupt this normative decline. Using a longitudinal sample of female twins (N = 1,763), we examined if levels of BPD traits were correlated with changes in MDD, AUD, and DUD symptoms from ages 14 to 24. A parallel process biometric latent growth model examined the contributions of genetic and environmental factors to the relationships between developmental components of these phenotypes. Higher BPD trait levels predicted a greater rate of increase in AUD and DUD symptoms, and higher AUD and DUD symptoms predicted a slower rate of decline of BPD traits from ages 14 to 24. Common genetic influences accounted for the associations between BPD traits and each disorder, as well as the interrelationships of AUD and DUD symptoms. Both genetic and nonshared environmental influences accounted for the correlated levels between BPD traits and MDD symptoms, but solely environmental influences accounted for the correlated changes between the two over time. Results indicate that higher levels of BPD traits may contribute to an earlier onset and faster escalation of AUD and DUD symptoms, and substance use problems slow the normative decline in BPD traits. Overall, our data suggests that primarily genetic influences contribute to the comorbidity between BPD features and substance use disorder symptoms. We discuss our data in the context of two major theories of developmental psychopathology and comorbidity.

Developmentally dynamic genome: Evidence of genetic influences on increases and decreases in conduct problems from early childhood to adolescence

The development of conduct problems in childhood and adolescence is associated with adverse long-term outcomes, including psychiatric morbidity. Although genes constitute a proven factor of stability in conduct problems, less is known regarding their role in conduct problems' developmental course (i.e. systematic age changes, for instance linear increases or decreases).Mothers rated conduct problems from age 4 to 16 years in 10,038 twin pairs from the Twins Early Development Study. Individual differences in the baseline level (.78; 95% CI: .68-.88) and the developmental course of conduct problems (.73; 95% CI: .60-.86) were under high and largely independent additive genetic influences. Shared environment made a small contribution to the baseline level but not to the developmental course of conduct problems. These results show that genetic influences not only contribute to behavioural stability but also explain systematic change in conduct problems. Different sets of genes may be associated with the developmental course versus the baseline level of conduct problems. The structure of genetic and environmental influences on the development of conduct problems suggests that repeated preventive interventions at different developmental stages might be necessary to achieve a long-term impact.

Stem cell transplantation as a dynamical system: are clinical outcomes deterministic?

Outcomes in stem cell transplantation (SCT) are modeled using probability theory. However, the clinical course following SCT appears to demonstrate many characteristics of dynamical systems, especially when outcomes are considered in the context of immune reconstitution. Dynamical systems tend to evolve over time according to mathematically determined rules. Characteristically, the future states of the system are predicated on the states preceding them, and there is sensitivity to initial conditions. In SCT, the interaction between donor T cells and the recipient may be considered as such a system in which, graft source, conditioning, and early immunosuppression profoundly influence immune reconstitution over time. This eventually determines clinical outcomes, either the emergence of tolerance or the development of graft versus host disease. In this paper, parallels between SCT and dynamical systems are explored and a conceptual framework for developing mathematical models to understand disparate transplant outcomes is proposed.

Exploring causal pathways of child behavior and maternal mental health in families with a child with congenital heart disease: a longitudinal study

BACKGROUND

A congenital heart defect (CHD) can increase the risk of mental health problems in affected children and their parents. The extent to which risk factors for these problems are shared in families or are specific to the individual family member is unclear.

METHOD

Prospective data from the Norwegian Mother and Child Cohort Study (MoBa; n = 93,009) were linked with a nationwide CHD registry, and 408 children with CHD were identified. Mothers' reports on child internalizing problems and their own distress were assessed by questionnaires at child ages 6, 18 and 36 months. A structural model was applied to distinguish between familial (shared) factors and individual-specific factors for mental health problems.

RESULTS

CHD was a substantial risk factor for problems in children and their mothers at all time points. CHD contributed on average 31% and 39% to the variance in children's and mothers' problems respectively. Both shared familial and individual-specific factors unique to CHD families contributed to risk for mental health problems. Whereas individual-specific risk factors contributed to the stability of problems in mothers, the effect of these factors lasted only a short time in children. Mutual influences over time were found between the mother's and the child's mental health at 18 and 36 months.

CONCLUSIONS

The burden of CHD in a child is shared between family members but is also specific to the individual. This study points to a need for both an individual and a family-based approach to provide psychological support to children with CHD and their parents.

A longitudinal twin study of physical aggression during early childhood: evidence for a developmentally dynamic genome

BACKGROUND

Physical aggression (PA) tends to have its onset in infancy and to increase rapidly in frequency. Very little is known about the genetic and environmental etiology of PA development during early childhood. We investigated the temporal pattern of genetic and environmental etiology of PA during this crucial developmental period.

METHOD

Participants were 667 twin pairs, including 254 monozygotic and 413 dizygotic pairs, from the ongoing longitudinal Quebec Newborn Twin Study. Maternal reports of PA were obtained from three waves of data at 20, 32 and 50 months. These reports were analysed using a biometric Cholesky decomposition and linear latent growth curve model.

RESULTS

The best-fitting Cholesky model revealed developmentally dynamic effects, mostly genetic attenuation and innovation. The contribution of genetic factors at 20 months substantially decreased over time, while new genetic effects appeared later on. The linear latent growth curve model revealed a significant moderate increase in PA from 20 to 50 months. Two separate sets of uncorrelated genetic factors accounted for the variation in initial level and growth rate. Non-shared and shared environments had no effect on the stability, initial status and growth rate in PA.

CONCLUSIONS

Genetic factors underlie PA frequency and stability during early childhood; they are also responsible for initial status and growth rate in PA. The contribution of shared environment is modest, and perhaps limited, as it appears only at 50 months. Future research should investigate the complex nature of these dynamic genetic factors through genetic-environment correlation (r GE) and interaction (G×E) analyses.

The dynamic role of genetics on cortical patterning during childhood and adolescence

Longitudinal imaging and quantitative genetic studies have both provided important insights into the nature of human brain development. In the present study we combine these modalities to obtain dynamic anatomical maps of the genetic contributions to cortical thickness through childhood and adolescence. A total of 1,748 anatomic MRI scans from 792 healthy twins and siblings were studied with up to eight time points per subject. Using genetically informative latent growth curve modeling of 81,924 measures of cortical thickness, changes in the genetic contributions to cortical development could be visualized across the age range at high resolution. There was highly statistically significant (P < 0.0001) genetic variance throughout the majority of the cerebral cortex, with the regions of highest heritability including the most evolutionarily novel regions of the brain. Dynamic modeling of changes in heritability over time demonstrated that the heritability of cortical thickness increases gradually throughout late childhood and adolescence, with sequential emergence of three large regions of high heritability in the temporal poles, the inferior parietal lobes, and the superior and dorsolateral frontal cortices.

Genetic amplification and the individualization of the parent-child relationship across adolescence

BACKGROUND

Many psychological traits become increasingly influenced by genetic factors throughout development, including several that might intuitively be seen as purely environmental characteristics. One such trait is the parent-child relationship, which is associated with a variety of socially significant outcomes, including mental health and criminal behavior. Genetic factors have been shown to partially underlie some of these associations, but the changing role of genetic influence over time remains poorly understood.

METHOD

Over 1000 participants in a longitudinal twin study were assessed at three points across adolescence with a self-report measure regarding the levels of warmth and conflict in their relationships with their parents. These reports were analyzed with a biometric growth curve model to identify changes in genetic and environmental influences over time.

RESULTS

Genetic influence on the child-reported relationship with parent increased throughout adolescence, while the relationship's quality deteriorated. The increase in genetic influence resulted primarily from a positive association between genetic factors responsible for the initial relationship and those involved in change in the relationship over time. By contrast, environmental factors relating to change were negatively related to those involved in the initial relationship.

CONCLUSIONS

The increasing genetic influence seems to be due to early genetic influences having greater freedom of expression over time whereas environmental circumstances were decreasingly important to variance in the parent-child relationship. We infer that the parent-child relationship may become increasingly influenced by the particular characteristics of the child (many of which are genetically influenced), gradually displacing the effects of parental or societal ideas of child rearing.

Advances in Behavioral Genetics Modeling Using Mplus: Applications of Factor Mixture Modeling to Twin Data

This article discusses new latent variable techniques developed by the authors. As an illustration, a new factor mixture model is applied to the monozygotic–dizygotic twin analysis of binary items measuring alcohol-use disorder. In this model, heritability is simultaneously studied with respect to latent class membership and within-class severity dimensions. Different latent classes of individuals are allowed to have different heritability for the severity dimensions. The factor mixture approach appears to have great potential for the genetic analyses of heterogeneous populations. Generalizations for longitudinal data are also outlined.

Advanced methods in twin studies

While twin studies have been used to estimate the heritability of different traits and disorders since the beginning of the twentieth century, statistical developments over the past 20 years and more extensive and systematic data collection have greatly expanded the scope of twin studies. This chapter reviews selected possibilities of twin study designs to address specific hypotheses regarding the role of both genetic and environmental factors in the development of traits and diseases. In addition to modelling latent genetic influences, current models permit inclusion of information on specific genetic variants, measured environmental factors and their interactive effects. Examples from studies of anthropometric traits are used to illustrate such approaches.

A biometric latent curve analysis of memory decline in older men of the NAS-NRC twin registry

Previous research has shown cognitive abilities to have different biometric patterns of age-changes. We examined the variation in episodic memory (word recall task) for over 6,000 twin pairs who were initially aged 59-75, and were subsequently re-assessed up to three more times over 12 years. In cross-sectional analyses, variation in the number of words recalled independent of age was explained largely by non-shared influences (65-72%), with clear additive genetic influences (12-32%), and marginal shared family influences (1-18%). The longitudinal phenotypic analysis of the word recall task showed systematic linear declines over age, but several nonlinear models with more dramatic changes at later ages, improved the overall fit. A two-part spline model for the longitudinal twin data with an optimal turning point at age 74 led to: (a) a separation of non-shared environmental influences and transient measurement error (~50%); (b) strong additive genetic components of this latent curve (~44% at age 60) with increases (over 50%) up to age 74, but with no additional genetic variation after age 74; (c) the smaller influences of shared family environment (~15% at age 74) were constant over all ages; (d) non-shared effects play an important role over most of the life-span but diminish after age 74.

Stability, change, and heritability of borderline personality disorder traits from adolescence to adulthood: a longitudinal twin study

Although personality disorders are best understood in the context of lifetime development, there is a paucity of work examining their longitudinal trajectory. An understanding of the expected course and the genetic and environmental contributions to these disorders is necessary for a detailed understanding of risk processes that lead to their manifestation. The current study examined the longitudinal course and heritability of borderline personality disorder (BPD) over a period of 10 years starting in adolescence (age 14) and ending in adulthood (age 24). In doing so, we built on existing research by using a large community sample of adolescent female twins, a sensitive dimensional measure of BPD traits, an extended follow-up period, and a longitudinal twin design that allowed us to investigate the heritability of BPD traits at four discrete ages spanning midadolescence to early adulthood. Results indicated that mean-level BPD traits significantly decline from adolescence to adulthood, but rank order stability remained high. BPD traits were moderately heritable at all ages, with a slight trend for increased heritability from age 14 to age 24. A genetically informed latent growth curve model indicated that both the stability and change of BPD traits are highly influenced by genetic factors and modestly by nonshared environmental factors. Our results indicate that as is the case for other personality dimensions, trait BPD declines as individuals mature from adolescence to adulthood, and that this process is influenced in part by the same genetic factors that influence BPD trait stability.

Genetic influences on growth traits of BMI: a longitudinal study of adult twins

OBJECTIVE

To investigate the interplay between genetic factors influencing baseline level and changes in BMI in adulthood.

METHODS AND PROCEDURES

A longitudinal twin study of the cohort of Finnish twins (N = 10,556 twin individuals) aged 20-46 years at baseline was conducted and followed up 15 years. Data on weight and height were obtained from mailed surveys in 1975, 1981, and 1990.

RESULTS

Latent growth models revealed a substantial genetic influence on BMI level at baseline in males and females (heritability (h(2)) 80% (95% confidence interval 0.79-0.80) for males and h(2) = 82% (0.81, 0.84) for females) and a moderate-to-high influence on rate of change in BMI (h(2) = 58% (0.50, 0.69) for males and h(2) = 64% (0.58, 0.69) for females). Only very weak evidence for genetic pleiotropy was observed; the genetic correlation between baseline and rate of change in BMI was very modest (-0.070 (-0.13, -0.068) for males and 0.04 (0.00, 0.08) for females.

DISCUSSION

Our population-based results provide a basis for identifying genetic variants for change in BMI, in particular weight gain. Furthermore, they demonstrate for the first time that such genetic variants for change in BMI are likely to be different from those affecting level of BMI.

Modeling genetic and environmental factors to increase heritability and ease the identification of candidate genes for birth weight: a twin study

Heritability estimates of birth weight have been inconsistent. Possible explanations are heritability changes during gestational age or the influence of covariates (e.g. chorionicity). The aim of this study was to model birth weights of twins across gestational age and to quantify the genetic and environmental components. We intended to reduce the common environmental variance to increase heritability and thereby the chance of identifying candidate genes influencing the genetic variance of birth weight. Perinatal data were obtained from 4232 live-born twin pairs from the East Flanders Prospective Twin Survey, Belgium. Heritability of birth weights across gestational ages was estimated using a non-linear multivariate Gaussian regression with covariates in the means model and in covariance structure. Maternal, twin-specific, and placental factors were considered as covariates. Heritability of birth weight decreased during gestation from 25 to 42 weeks. However, adjusting for covariates increased the heritability over this time period, with the highest heritability for first-born twins of multipara with separate placentas, who were staying alive (from 52% at 25 weeks to 30% at 42 weeks). Twin-specific factors revealed latent genetic components, whereas placental factors explained common and unique environmental factors. The number of placentas and site of the insertion of the umbilical cord masked the effect of chorionicity. Modeling genetic and environmental factors leads to a better estimate of their role in growth during gestation. For birth weight, mainly environmental factors were explained, resulting in an increase of the heritability and thereby the chance of finding genes influencing birth weight in linkage and association studies.

Social activity and healthy aging: a study of aging Danish twins

Although social and intellectual engagement have been consistently associated with late-life functioning, rather than true causation, these associations may reflect the experiential choices of high functioning individuals (i.e., selection effects). We investigated the association of social activity with late-life physical functioning, cognitive functioning, and depression symptomatology using data from 1112 pairs of like-sex twins who participated in the Longitudinal Study of Aging Danish Twins. Consistent with previous research, we found that social activity was significantly correlated with overall level of physical functioning, cognitive functioning, and depression symptomatology. We also found that social activity was significantly and moderately heritable (estimate of .36), raising the possibility that its association with late-life functioning might reflect selection processes. Further, social activity did not predict change in functioning and in monozygotic twin pairs discordant on level of social activity, the more socially active twin was not less susceptible to age decreases in physical and cognitive functioning and increases in depression symptomatology than the less socially active twin. These results are interpreted in the context of the additional finding that nonshared environmental factors, although apparently not social activity, are the predominant determinant of changes in late-life functioning.

Size and morbidity in Malawian twins

OBJECTIVE

Twins in developing countries may be disadvantaged due to their small size at birth, compromised nutrition and high infection risk. Although twinning is common in Africa, there are few longitudinal studies of growth and morbidity in this high-risk group. The aim of the present paper was to describe growth and morbidity of Malawian twins compared to singletons.

METHODS

Morbidity episodes were recorded at 4 weekly intervals and at extra visits made to health centres for illness. Weight, length, head and arm circumference were recorded at birth and weight, length and MUAC at 4 weekly intervals to 52 weeks of age.

RESULTS

Twins showed reduced fetal growth compared to singletons, with increasing fall-off in percentiles from 33 weeks gestation. Infant growth percentiles for twins were below those for singletons at all ages, but showed no fall-off from singleton percentile values. There were no differences in morbidity incidence during infancy between twins and singletons.

CONCLUSION

Malawian twins showed no catch-up growth during infancy, their smaller size was not associated with higher morbidity incidence compared to singletons.