Genetic and Environmental Factors Influencing BMI Development from Adolescence to Young Adulthood

BMI increases progressively from adolescence to young adulthood. The aims of the present study were firstly, to investigate the extent to which genetic and environmental influences account for differences in BMI trajectories during this period, and secondly to examine whether boys and girls show divergences in these influences, as their BMI normally start differing across adolescence. The study sample consisted of 4,915 monozygotic and like- and unlike-sex dizygotic twins, born between 1975 and 1979. Data on BMI was gathered when twins were on average 16.1, 17.1, 18.6 and 24.4 years old. Genetic and environmental influences on the BMI trajectories were modeled using a latent growth curve approach. The results showed that the heritability of BMI decreased slightly after the adolescence period, from ≈80 to 70%. BMI transition from adolescence to young adulthood was best described by a quadratic trajectory that was highly accounted (61.7–86.5%) for by additive genetic influences. Genetic influences on BMI level showed a low correlation with those on the trend in BMI with age indicating that different sets of genes underlie the change of BMI during this period. Importantly, the analyses also evidenced that different genetic and environmental influences may underlie boys and girls evolution. In conclusion, our results suggested specific genetic influences accounting for the BMI rate-of-change from adolescence to young adulthood. This indicates that the specific genes behind BMI level may not be the same as the genes affecting BMI change which should be taken into account in further efforts to identify these genes.     

Depressive Symptoms and Alcohol Use are Genetically and Environmentally Correlated Across Adolescence

Depressive symptoms and alcohol use are frequently positively associated during adolescence. This study aimed to assess the heritability of each phenotype across adolescence; to assess potential shared liabilities; to examine changes in the nature of shared liabilities across adolescence; and to investigate potential causal relationships between depressive symptoms and alcohol use. We studied a longitudinally assessed sample of adolescent Finnish twins (N = 1,282) to test hypotheses about genetic and environmental influences on these phenotypes within and across ages, using data from assessments at ages 12, 14, and 17.5 years. The heritability of depressive symptoms is consistent across adolescence (~40–50%), with contributions from common and unique environmental factors. The heritability of alcohol use varies across time (a² = .25–.44), and age 14 alcohol use is heavily influenced by shared environmental factors. Genetic attenuation and innovation were observed across waves. Modest to moderate genetic (r_A = .26–.59) and environmental (r_C = .30–.63) correlations between phenotypes exist at all ages, but decrease over time. Tests for causal relationships between traits differed across ages and sexes. Intrapair MZ difference tests provided evidence for reciprocal causation in girls at ages 14 and 17.5. Formal causal models suggested significant causal relationships between the variables in both boys and girls. The association between depressive symptoms and alcohol use during adolescence is likely due to a combination of shared genetic and environmental influences and causal influences. These influences are also temporally dynamic, complicating efforts to understand factors contributing to the relationship between these outcomes.     

Stable Genetic Effects on Symptoms of Alcohol Abuse and Dependence from Adolescence into Early Adulthood

Relatively little is known about how genetic influences on alcohol abuse and dependence (AAD) change with age. We examined the change in influence of genetic and environmental factors which explain symptoms of AAD from adolescence into early adulthood. Symptoms of AAD were assessed using the four AAD screening questions of the CAGE inventory. Data were obtained up to six times by self-report questionnaires for 8,398 twins from the Netherlands Twin Register aged between 15 and 32 years. Longitudinal genetic simplex modeling was performed with Mx. Results showed that shared environmental influences were present for age 15–17 (57%) and age 18–20 (18%). Unique environmental influences gained importance over time, contributing 15% of the variance at age 15–17 and 48% at age 30–32. At younger ages, unique environmental influences were largely age-specific, while at later ages, age-specific influences became less important. Genetic influences on AAD symptoms over age could be accounted for by one factor, with the relative influence of this factor differing across ages. Genetic influences increased from 28% at age 15–17 to 58% at age 21–23 and remained high in magnitude thereafter. These results are in line with a developmentally stable hypothesis that predicts that a single set of genetic risk factors acts on symptoms of AAD from adolescence into young adulthood.     

Heritability and Longitudinal Stability of Schizotypal Traits During Adolescence

The study investigated the genetic and environmental etiology of schizotypal personality traits in a non-selected sample of adolescent twins, measured on two occasions between the ages of 11 and 16 years old. The 22-item Schizotypal Personality Questionnaire- Child version (SPQ-C) was found to be factorially similar to the adult version of this instrument, with three underlying factors (Cognitive-Perceptual, Interpersonal-Affective, and Disorganization). Each factor was heritable at age 11–13 years (h ² = 42–53%) and 14–16 years old (h ² = 38–57%). Additive genetic and unique environmental influences for these three dimensions of schizotypal personality acted in part through a single common latent factor, with additional genetic effects specific to both Interpersonal-Affective and Disorganization subscales at each occasion. The longitudinal correlation between the latent schizotypy factor was r = 0.58, and genetic influences explained most of the stability in this latent factor over time (81%). These longitudinal data demonstrate significant genetic variance in schizotypal traits, with moderate stability between early to middle adolescence. In addition to common influences between the two assessments, there were new genetic and non-shared environmental effects that played a role at the later assessment, indicating significant change in schizotypal traits and their etiologies throughout adolescence.     

Changes in genetic and environmental influences on trait anxiety from middle adolescence to early adulthood

Background

Middle adolescence to early adulthood is an important developmental period for the emergence of anxiety. Genetically-influenced stable traits are thought to underlie internalizing psychopathology throughout development, but no studies have examined changes in genetic and environmental influences on trait anxiety during this period.

Method

A longitudinal twin study design was used to study same-sex twin pairs (485 monozygotic pairs, 271 dizygotic pairs) at three ages, 14, 18, and 21 years, to examine developmental shifts in genetic and environmental effects on trait anxiety.

Results

The heritability of trait anxiety increased with age, particularly between ages 14 and 18, no significant new genetic influences emerged after age 14, and the genetic influences were highly correlated across the three ages, supporting developmentally stable genetic risk factors. The environmental effects shared by members of a family decreased in influence across adolescence, while the influence of environmental effects unique to each individual twin remained relatively stable over the course of development and were largely age-specific.

Limitations

The twin study design does not inform about specific genes and environmental risk factors.

Conclusions

Genetic influences increased in importance from middle to late adolescence but common genetic factors influenced trait anxiety across the three ages. Shared environmental influences decreased in importance and demonstrated negligible influence by late adolescence/early adulthood. Nonshared environmental effects were almost entirely age-specific. These findings support the importance of developmentally-sensitive interventions that target shared environmental factors prior to middle adolescence and shifting non-shared environmental risks at each age.     

Internalizing Behavior in Adolescent Girls Affects Parental Emotional Overinvolvement: A Cross-lagged Twin Study

The aim of this study was to examine the direction and the etiology of the association between different parenting styles (parental emotional overinvolvement [EOI] and parental criticism) and internalizing behavior from adolescence to early adulthood. A longitudinal genetically informative cross-lagged design was applied to a population-based sample of Swedish twins contacted at age 16–17 (n = 2369) and at age 19–20 (n = 1705). Sex-limitation modelling revealed different effects for boys and girls. For girls, genetic influences on internalizing problems at age 16–17 independently explained 2.7% of the heritability in parental EOI at age 19–20. These results suggest that emotionally overinvolved and self-sacrificing parental behavior stems in part from daughters (but not sons) genetic predisposition for internalizing behavior. These findings highlight the importance of genetically influenced child-driven effects underlying the parenting-internalizing association, and clarify that the role of such effects may differ depending on sex, type of parenting and developmental period.     

Stability and Change of Genetic and Environmental Effects on the Common Liability to Alcohol, Tobacco, and Cannabis DSM-IV Dependence Symptoms

This study investigated the stability of genetic and environmental effects on the common liability to alcohol, tobacco, and cannabis dependence across adolescence and young adulthood. DSM-IV symptom counts from 2,361 adolescents were obtained using a structured diagnostic interview. Several sex-limited longitudinal common pathway models were used to examine gender differences in the magnitude of additive genetic (A), shared environment, and non-shared environmental effects over time. Model fitting indicated limited gender differences. Among older adolescents (i.e., age >14), the heritability of the latent trait was estimated at 0.43 (0.05, 0.94) during the first wave and 0.63 (0.21, 0.83) during the second wave of assessment. A common genetic factor could account for genetic influences at both assessments, as well as the majority of the stability of SAV over time [rA = 1.00 (0.55, 1.00)]. These results suggest that early genetic factors continue to play a key role at later developmental stages.     

Sex differences in the genetic and environmental influences on the development of antisocial behavior

The present study uses a population-based sample of 6.806 adult twins from same-sex and opposite-sex twin pairs to examine sex differences in the underlying genetic and environmental architecture of the development of antisocial behavior (AB). Retrospective reports of AB during three different developmental periods were obtained: prior to age 15 years (childhood), age 15-17 years (adolescent), and age 18 years and older (adult). Structural equation modeling analyses revealed that there was no evidence for sex-specific genetic or sex-specific shared family environmental influences on the development of AB; that is, the types of genetic and environmental influence were similar for males and females. For both sexes, a model that allowed for genetic influences on adolescent and adult AB that were not shared with childhood AB fit better than a model with a single genetic factor. In contrast, shared environmental influences on adolescent and adult AB overlapped entirely with shared environmental influences on childhood AB. Genetic factors played a larger role in variation in childhood AB among females, whereas shared environmental factors played a larger role among males. However, heritability of AB increased from childhood to adolescence and adulthood for both sexes, and the magnitude of genetic and environmental influences on adolescent and adult AB was approximately equal across sex. We speculate that sex differences in timing of puberty may account for the earlier presence of genetic effects among females.     

Does adolescent depression predict obesity in black and white young adult women?

BACKGROUND: To examine whether adolescent depressive symptoms predict young adult body mass index (BMI) and obesity in black and white women. METHOD: Participants included 1554 black and white adolescent girls from the National Heart, Lung, and Blood Institute Growth and Health Study (NGHS) who completed the Center for Epidemiological Studies--Depression Scale (CES-D) at ages 16 and 18 years. RESULTS: Regression analyses showed that depressive symptoms at both ages 16 and 18 were associated with increased risk of obesity (BMI > or = 30) and elevated BMI in young adulthood (age 21) in both black and white girls. Black girls exhibited a significantly greater likelihood of obesity and higher BMI (i.e. a main effect of race), but the race x CES-D interaction was not significant in any analysis. CONCLUSIONS: Depressive symptoms in adolescence appear to be predictive of obesity and elevated BMI in early adulthood for both black and white girls, even when taking prior BMI into account, indicating that depressive symptoms confer risk for obesity above and beyond the known tracking of body weight. Obesity prevention studies might consider assessing depressive symptoms in adolescence in order to more fully capture important risk variables.     

Thought Problems from Adolescence to Adulthood: Measurement Invariance and Longitudinal Heritability

This study investigates the longitudinal heritability in Thought Problems (TP) as measured with ten items from the Adult Self Report (ASR). There were ~9,000 twins, ~2,000 siblings and ~3,000 additional family members who participated in the study and who are registered at the Netherlands Twin Register. First an exploratory factor analysis was conducted to examine the underlying factor structure of the TP-scale. Then the TP-scale was tested for measurement invariance (MI) across age and sex. Next, genetic and environmental influences were modeled on the longitudinal development of TP across three age groups (12–18, 19–27 and 28–59 year olds) based on the twin and sibling relationships in the data. An exploratory factor analysis yielded a one-factor solution, and MI analyses indicated that the same TP-construct is assessed across age and sex. Two additive genetic components influenced TP across age: the first influencing TP throughout all age groups, while the second arises during young adulthood and stays significant throughout adulthood. The additive genetic components explained 37% of the variation across all age groups. The remaining variance (63%) was explained by unique environmental influences. The longitudinal phenotypic correlation between these age groups was entirely explained by the additive genetic components. We conclude that the TP-scale measures a single underlying construct across sex and different ages. These symptoms are significantly influenced by additive genetic factors from adolescence to late adulthood.     

Genetic and Environmental Factors Affecting Self-Rated Health from Age 16–25: A Longitudinal Study of Finnish Twins

We analyzed genetic and environmental determinants of self-rated health and its change from adolescence to early adulthood. Questionnaires were mailed to Finnish twins born 1975–1979 at ages 16, 17, and, on average, 25 years of age (N = 2465 complete twin pairs). The data were analyzed using quantitative genetic methods for twin data by the Mx statistical package. Heritability of self-rated health was greatest at age 16 (63%, 95% confidence intervals (CI) 56–67%, men and women together) and declined steadily to age 25 (33%, 95% CI 25–41%). The residual variation was due to unshared environments. Health ratings at different ages were modestly correlated (r = 0.33–0.61). These correlations were mainly due to genetic factors, but unshared environment also contributed to them. An important challenge for further research is to identify environmental influences contributing to self-rated health independently of, or in interaction with, genetic factors. Edited by Peter McGuffin and John Hewitt     

Continuity of Genetic Risk for Aggressive Behavior Across the Life-Course

We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N?=?13,471) and Australia (N?=?5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12–70 years, Australia: 16–73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a ‘rolling weights’ model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41–70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.

     

Effects of strength training and detraining on regional muscle in young and older men and women

To examine the effects of 9 weeks of strength training (ST) and 31 weeks of detraining on regional muscle area in young and older men and women, three regions of the quadriceps muscle area (proximal, middle, and distal) were measured via MRI in 11 men ages 20–30, 11 men ages 65–75, 10 women ages 20–30, and 11 women ages 65–75. These effects were assessed by determining the difference between the control limb and the trained limb (T-UT) at all three time points. This design provided control for possible influences of biological, methodological, seasonal variations, as well as influences due to attention or genetic differences that commonly occur between experimental and control groups. There were no significant differences in any of the three regions at any of the three time points, when comparing subjects by age. However, men had significantly greater T-UT CSA at the after ST time point [6.9 (3.7) cm²] when compared with women [2.8 (3.7) cm², P < 0.05]. Baseline T-UT CSA was higher than after detraining T-UT CSA for young men in the proximal and middle regions [0.1 (3.6), 0.4 (3.6) cm² vs. 2.8 (4.0), 2.4 (3.6) cm², P < 0.05], but there were no significant differences within the other three groups. These data indicate that sex may influence changes in regional CSA after ST, whereas age does not influence regional muscle gain or loss due to ST or detraining.     

Sex Differences in Genetic Variation in Weight: a Longitudinal Study of Body Mass Index in Adolescent Twins

Genes that influence a phenotype earlier in life may differ from those influencing the same phenotype later, particularly during significant development periods such as puberty, when it is known that new genetic and environmental influences may become important. In the present study, body mass index (BMI) data were collected from 470 monozygotic twin pairs and 673 dizygotic twin pairs longitudinally at ages 12, 14 and 16, roughly straddling puberty. In order to examine whether there are qualitative and quantitative differences in genetic and environmental influences affecting BMI in males and females, during development, a general sex-limitation simplex model (which represents the longitudinal time series of the data) was fitted to the repeated measurements of BMI. The ADE simplex model provided the best fit to the adolescent data, with disparity in the magnitude of additive genetic influences between sexes, but no differences in the non-additive genetic (epistasis or dominance) or environmental influences. Results found may reflect many genetic and environmental influences during puberty, including the possible complex interaction between genes involved in the biological mechanism of weight regulation and the development of likely peer pressured activities such as severe exercise and diet regimes. Although, over 1,000 pairs of twins were used, this study still lacked the power to properly discriminate between additive and non-additive genetic variance. Edited by David Allison.     

Genetic and Shared Environmental Influences on Adolescent BMI: Interactions with Race and Sex

The present study uses a behavioral genetic design to investigate the genetic and environmental influences on variation in adolescent body mass index (BMI) and to determine whether the relative influences of genetic and environmental factors on variation in BMI are similar across racial groups and sexes. Data for the present study come from the National Longitudinal Study on Adolescent Health (Add Health), a large, nationally representative study of adolescent health and health-related behaviors. The Add Health sample contains a subset of sibling pairs that differs in levels of genetic relatedness, making it well suited for behavioral genetics analyses. The present study examines whether genetic and environmental influences on adolescent BMI are the same for males and females and for Black and White adolescents. Results indicate that genetic factors contribute substantially to individual differences in adolescent BMI, explaining between 45 and 85% of the variance in BMI. Furthermore, based on an analysis of opposite-sex sibling pairs, the genes that influence variation in adolescent BMI are similar for males and females. However, the relative importance of genetic and environmental influences on variation in BMI differs for males and females and for Blacks and Whites. Although parameter estimates could be constrained to be equal for Black and White males, they could not be constrained to be equal for Black and White females. Moreover, the best-fitting model for Black females was an ADE model, for White females it was an ACE model, and for males it was an AE model. Thus, shared environmental influences are significant for White female adolescents, but not for Black females or males. Likewise, nonadditive genetic influences are indicated for Black females, but not for White females or males. Implications of these results are discussed.     

Age Differences in Genetic and Environmental Variations in Stress-Coping During Adulthood: A Study of Female Twins

The way people cope with stressors of day to day living has an important influence on health. The aim of the present study was to explore whether genetic and environmental variations in stress-coping differ over time during adulthood. The brief COPE was mailed to a large sample of the UK female twins (N = 4,736) having a wide range of age (20–87 years). Factor analyses of the items of the brief COPE yielded three coping scales: ‘Problem-Solving’, ‘Support Seeking’, and ‘Avoidance’. Monozygotic and dizygotic twin correlations tended to become lower with age for all three scales, suggesting that unique environmental factors may become more important with age during adulthood. Model-fitting results showed that relative influences of unique environmental factors increased from 60 % at age 20 years to 74% at age 87 years for ‘Problem-Solving’ and 56 % at age 20 years to 76% at age 87 years for ‘Avoidance’. During the same age period, genetic factors decreased from 40 to 26 % for ‘Problem-Solving’ and from 44 to 24 % for ‘Avoidance’. For ‘Seeking Support’, the magnitude of genetic and unique environmental factors was not significantly different across the adulthood. For all three scales, shared environmental effects were negligible. Overall, our findings implicate that the effects of environment that stem from idiosyncratic experience of stressful life events accumulate and become increasingly important in adulthood.     

The Etiology of Stability and Change in Religious Values and Religious Attendance

Studies have demonstrated little to no heritability for adolescent religiosity but moderate genetic, shared environmental, and nonshared environmental influences on adult religiosity. Only one longitudinal study of religiosity in female twins has been conducted (Koenig et al., Dev Psychol 44:532?C543, 2008), and reported that persistence from mid to late adolescence is due to shared environmental factors, but persistence from late adolescence to early adulthood was due to genetic and shared environmental factors. We examined the etiology of stability and change in religious values and religious attendance in males and females during adolescence and early adulthood. The heritability of both religious values and religious attendance increased from adolescence to early adulthood, although the increase was greater for religious attendance. Both genetic and shared environmental influences contributed to the stability of religious values and religious attendance across adolescence and young adulthood. Change in religious values was due to both genetic and nonshared environmental influences specific to early adulthood, whereas change in religious attendance was due in similar proportions to genetic, shared environmental, and non-shared environmental influences.     

Trajectories and stability of self‐reported short sleep duration from adolescence to adulthood

The trajectories and stability of self‐reported sleep duration recorded at ages 13, 15, and 23 years on reported sleep duration at age 30 years among 1105 students (55% male) who participated in the Norwegian Longitudinal Health and Behaviour Study were examined. Questionnaire data were used to obtain demographic and sleep variables. Dichotomised short sleep duration was based on normative values and set as ≤8.5 h (age 13 years), ≤8 h (age 15 years) and ≤7 h (ages 23 and 30 years). Results indicated a significant overall reduction in total sleep duration (h per night) across age groups. Sleep duration (continuous) at age 15 and 23 years (whole group) was moderately but positively correlated with sleep duration at age 30 years (P < 0.01). When split by sex, at age 15 years, this association was present among females only (P < 0.01); however, at age 23 years, this association was present in both male and females (both P < 0.001). Categorical short sleep at age 23 years (whole group) was associated with short sleep at age 30 years (unadjusted odds ratio = 3.67, 95% confidence interval 2.36–5.69). Following sex stratification, this effect was significant for both males (unadjusted odds ratio = 3.77, 95% confidence interval: 2.22–6.42) and females (unadjusted odds ratio = 2.71, 95% confidence interval: 1.46–5.04). No associations were noted for categorical short sleep at ages 13 or 15 years, and subsequent short sleep at 30 years. Habitual short sleep duration during middle adulthood is not sustained from the time of early adolescence. Rather, these trends appear to be formed during early adulthood.     

Characterizing near-infrared spectroscopy responses to forearm post-occlusive reactive hyperemia in healthy subjects

During post-occlusive reactive hyperemia (PORH) there is a temporary increase in the total hemoglobin + myoglobin (T[Hb+Mb]) signal as measured by near-infrared spectroscopy (NIRS). This transient increase predicts differences in the kinetic responses of deoxy[Hb+Mb] and oxy[Hb+Mb] during PORH. The purpose of this study was to determine whether sigmoidal (Gompertz or logistic) or exponential functions better describe these response curves during PORH. The fit of the three functions (exponential, Gompertz and logistic) to the NIRS responses, as determined from residual sum of squares, was compared using repeated measures ANOVA on Ranks. The Gompertz function provided a better fit to the oxy[Hb+Mb] response curve than did either the exponential or logistic function (χ ² = 21.7, df = 2, p < 0.001). The logistic function provided a better fit for the deoxy[Hb+Mb] response (χ ² = 22.9, df = 2, p < 0.001) than did either the Gompertz or exponential functions. For both NIRS signals, the better fitting sigmoidal functions fit the data well, with an average r value of 0.99 or greater. Adipose tissue thickness was correlated with parameters related to signal strength (amplitude, r = 0.86–0.89; baseline, r = 0.67–0.75; all p < 0.001) but was not related to kinetic parameters (time constant and inflection point; p > 0.05 for all comparisons). These results suggest that during PORH distinct sigmoidal mathematical functions best describe the responses of the oxy[Hb+Mb] (Gompertz) and deoxy[Hb+Mb] (logistic) as measured by NIRS. Further, differences in both the kinetic and amplitude aspects for the responses of oxy[Hb+Mb] and deoxy[Hb+Mb] predict the observed transient change in T[Hb+Mb]. Our methods provide a technique to evaluate and quantify NIRS responses during PORH, which may have clinical utility.     

Obesity,adipokines and asthma

Background: The prevalence of asthma and obesity is increasing concomitantly, but many aspects of this link are unclear. Our objective was to examine whether obesity is associated with asthma in three time points of life, and whether immunomodulatory adipokines, leptin and adiponectin are linked to overweight‐associated asthma. Methods: We studied the association between obesity and asthma at ages 3–18 years [mean (SD), 10 years (5), n = 3582, year 1980], 9–24 years [16 years (5), n = 2764, 1986] and 24–39 years [32 years (5), n = 2620, 2001] in a prospective cohort study and further tested for associations with serum leptin and adiponectin concentrations. Data on allergy status, smoking and other laboratory values (serum insulin, plasma C‐reactive protein and serum lipid values) were also analyzed. Results: Allergy and parental asthma were significantly associated with asthma at all ages. At ages 24–39 years, but not earlier, body mass index (BMI) (odds ratio, OR 1.05; P = 0.019) and female gender (OR 1.56; P = 0.031) were independently associated with asthma. Increase in BMI was also associated with incident asthma during adulthood (OR 1.08; P = 0.030). Levels of leptin, adiponectin or any other obesity‐related biomarker were not independently associated with asthma. Conclusions: Asthma is linked with obesity in adults, but our results do not support a significant role for leptin, adiponectin or any other obesity‐related biomarker studied in this association. Other factors should be sought for better understanding the connection between obesity and asthma.