Suchergebnisse

AbstractThe Vietnam Era Twin Study of Aging (VETSA) is a longitudinal behavioral genetic study with a primary focus on cognitive and brain aging in men, particularly early identification of risk for mild cognitive impairment (MCI) and Alzheimer's disease (AD). It comprises a subset of over 1600 twins from the Vietnam Era Twin Registry. Twins live all over the USA. Assessments began when participants were in their 50s. Follow-ups were conducted every 5–6 years, and wave 3 has been completed as of this writing. The age range of participants is narrow (about 10 years). An extensive neurocognitive test battery has added precision in assessing differences in middle-aged adults, and predicting progression to MCI. Young adult cognitive test data (at an average age of 20 years) provide a means of disentangling aging effects from longstanding differences. Genome wide genotyping and plasma assays of AD biomarkers from waves 1 and 3 were conducted in wave 3. These features make the VETSA ideal for studying the heterogeneity of within-individual trajectories from midlife to old age, and for early detection of risk factors for cognitive decline.

The Vietnam Era Twin Study of Aging (VETSA) is a longitudinal behavioral genetic study with a primary focus on cognitive and brain aging in men. It comprises a subset of over 1,200 twins from the Vietnam Era Twin Registry. Like many other studies of aging, the VETSA includes many different phenotypes, but there are some key features that distinguish it from most other behavioral genetic aging studies. First, the initial assessment was conducted when all participants were middle-aged. Second, the age range of participants is narrow; all were in their 50s at the time of the initial recruitment. Third, the study includes an extensive and demanding neurocognitive test battery that was designed to provide good coverage of different cognitive abilities and avoid ceiling effects in middle-aged adults. Fourth, young adult cognitive test data (at an average age of 20 years) are available to provide a gauge of cognitive change. These features make the VETSA ideal for studying the heterogeneity of within-individual trajectories from midlife to old age, and for early detection of risk factors for cognitive decline.

Molecular genetic research has provided some evidence for the association between depression and metabolic disorders. We sought to determine if molecular findings are reflected in twin analyses testing if common genetic and environmental risk factors contribute to the co-occurrence of diabetes and depression. Data to derive depression and diabetes were collected from 1,237 male-male twins who participated in the 2005 Vietnam Era Twin Study of Aging (VETSA). The 1,237 twins were comprised of 347 MZ pairs, 3 MZ singletons, 267 DZ pairs and 6 unpaired twins. Depression was defined as a score below 46 on the Short Form-36 mental component summary score. Diabetes was defined by self report, use of anti-diabetic medications and insulin. Twin models were fit to estimate the correlation of genetic and environmental contributions to depression and diabetes. Consistent with other studies these data support the association between depression and diabetes (OR = 1.7; 95%CI: 1.1–2.7). Genetic vulnerability accounted for 50% (95%CI: 32%–65%) of the variance in risk for depression and 69% (95%CI: 52%–81%) of the variance in risk for diabetes. The genetic correlation between depression and diabetes was r = 0.19 (95%CI: 0–0.46) and the non-shared environmental correlation was r = 0.09 (95% CI: 0–0.45). Overall there is little evidence that common genetic and environmental factors account for the co-occurrence of depression and diabetes in middle aged men. Further research in female twins and larger cohorts is warranted.

We explored the comorbidity between panic attacks (PA), whose symptoms can include gastrointestinal discomfort, and gastrointestinal disorders (GD). Structural equation modeling was used to analyze data from 1,874 MZ and 1,498 DZ male–male twin pairs from the Vietnam Era Twin Registry. PA and GD were associated (relative risk for GD = 2). The percentage of liability due to genetic factors was estimated to be 37% for PA and 31% for GD. There was significant correlation between the genetic risk factors for PA and GD (estimated r = .55, 95% CI of 34% to 82%) and no evidence of correlation between the environmental causes of PA and GD. Therefore, PA and GD comorbidity can be explained by overlapping genetic factors and not overlapping environmental factors. Although these data cannot identify a biological pathway for such a shared liability, it suggests the presence of GD may be informative for genetic studies of panic.

AbstractWe examined the contributions of genetic and environmental factors to body mass index (BMI) over approximately 28 years. Participants were 693 male, predominantly middle-class, twins (355 monozygotic, 338 dizygotic) from the Vietnam Era Twin Registry. The phenotypic correlation between age 20 and age 48 BMI was 0.52; the genetic correlation was 0.60. Most of the remaining variance at both times was accounted for by nonshared environmental factors. Since genetic factors are not perfectly correlated, this indicates that other genes affect BMI at one or both time points, leaving room for further exploration of the genetics of body mass stability. Mean BMI increased significantly from 22.7 (normal) to 27.8 (overweight). Overweight BMI at age 20 predicted midlife adult onset diabetes (adjusted odds ratio = 4.62, 95% CI 1.91 to 11.18), but not hypertension. Depending on one's vantage point, the results indicate elements of both stability and change in BMI. Very similar phenotypic and genetic correlations were observed over a similar time period in a WW II twin sample, but without the substantial mean increase in BMI. It seems unlikely that different genes influence BMI in the two cohorts. Therefore, we argue that nonshared environmental factors are probably primarily responsible for the secular increase in midlife BMI. Our results also provide prospective evidence that early excess BMI may have serious long-term health consequences, and that this risk is not limited to minorities or adults of lower socioeconomic status.

Abstract

Objectives
Subjective health (SH) is not just an indicator of physical health, but also reflects active cognitive processing of information about one's own health and has been associated with emotional health measures, such as neuroticism and depression. Behavior genetic approaches investigate the genetic architecture of SH, that is, genetic and environmental influences on individual differences in SH and associations with potential components such as physical, cognitive, and emotional health. Previous twin analyses have been limited by sex, sample size, age range, and focus on single covariates.


Methods
The current analysis used data from 24,173 adults ranging in age from 40 to 90 years from the international Interplay of Genes and Environment across Multiple Studies consortium to investigate the genetic architecture of 3 measures of SH: self-rated health, health compared to others, and impact of health on activities. Independent pathways model of SH included physical health, depressive symptoms, and episodic memory, with age, sex, and country included as covariates.


Results
Most or all of the genetic variance for SH measures were shared with physical health, depressive symptoms, and episodic memory. Genetic architecture of SH differed across measures, age groups (40–65, 66–90), and sexes. Age comparisons indicated stronger correlations with all 3 covariates in older adults, often resulting from greater shared genetic variance.


Discussion
The predictive value of SH has been amply demonstrated. The higher genetic contributions to associations between SH and its components in older adults support the increasing conceptualization with age of SH as an intuitive summation of one's vital reserve.

In this longitudinal study we examined the stability of general cognitive ability (GCA), as well as heterogeneity and genetic and environmental influences underlying individual differences in change. We investigated GCA from young adulthood through late midlife in 1,288 Vietnam Era Twin Study of Aging participants at ages ~20, ~56, and ~62 years. The correlations among the three occasions ranged from .73 to .85, reflecting substantial stability. The heritability was significant on each of the three occasions and ranged from .59 to .66. The influence of the shared environment was not significant at any of the ages. The genetic correlations across the three occasions ranged from .95 to .99 and did not differ significantly from 1.0. The nonshared environmental correlations ranged from .21 to .47. Latent growth curve analysis was applied to characterize trajectories over the 42 year period. Slope was significantly different from 0 and indicated that there was modest change over time. There was a significant genetic influence on initial level of GCA (h2 = .67), but not change (h2 = .23). Genetic factors primarily contribute to stability, while change reflects the influence of nonshared environmental influences. There was a significant negative correlation between initial level of GCA and change (r = −.31). Latent class growth analysis identified four trajectories. In general, the four groups followed parallel trajectories and were differentiated mainly by differences in AFQT performance level at the time of military induction.

The Interplay of Genes and Environment across Multiple Studies (IGEMS) group is a consortium of eight longitudinal twin studies established to explore the nature of social context effects and gene-environment interplay in late-life functioning. The resulting analysis of the combined data from over 17,500 participants aged 25–102 at baseline (including nearly 2,600 monogygotic and 4,300 dizygotic twin pairs and over 1,700 family members) aims to understand why early life adversity, and social factors such as isolation and loneliness, are associated with diverse outcomes including mortality, physical functioning (health, functional ability), and psychological functioning (well-being, cognition), particularly in later life.

AbstractThe Interplay of Genes and Environment across Multiple Studies (IGEMS) is a consortium of 18 twin studies from 5 different countries (Sweden, Denmark, Finland, United States, and Australia) established to explore the nature of gene–environment (GE) interplay in functioning across the adult lifespan. Fifteen of the studies are longitudinal, with follow-up as long as 59 years after baseline. The combined data from over 76,000 participants aged 14–103 at intake (including over 10,000 monozygotic and over 17,000 dizygotic twin pairs) support two primary research emphases: (1) investigation of models of GE interplay of early life adversity, and social factors at micro and macro environmental levels and with diverse outcomes, including mortality, physical functioning and psychological functioning; and (2) improved understanding of risk and protective factors for dementia by incorporating unmeasured and measured genetic factors with a wide range of exposures measured in young adulthood, midlife and later life.

Understanding the genetic and environmental contributions to measures of brain structure such as surface area and cortical thickness is important for a better understanding of the nature of brain-behavior relationships and changes due to development or disease. Continuous spatial maps of genetic influences on these structural features can contribute to our understanding of regional patterns of heritability, since it remains to be seen whether genetic contributions to brain structure respect the boundaries of any traditional parcellation approaches. Using data from magnetic resonance imaging scans collected on a large sample of monozygotic and dizygotic twins in the Vietnam Era Twin Study of Aging, we created maps of the heritability of areal expansion (a vertex-based area measure) and cortical thickness and examined the degree to which these maps were affected by adjustment for total surface area and mean cortical thickness. We also compared the approach of estimating regional heritability based on the average heritability of vertices within the region to the more traditional region-of-interest (ROI)-based approach. The results suggested high heritability across the cortex for areal expansion and, to a slightly lesser degree, for cortical thickness. There was a great deal of genetic overlap between global and regional measures for surface area, so maps of region-specific genetic influences on surface area revealed more modest heritabilities. There was greater inter-regional variability in heritabilities when calculated using the traditional ROI-based approach compared to summarizing vertex-by-vertex heritabilities within regions. Discrepancies between the approaches were greatest in small regions and tended to be larger for surface area than for cortical thickness measures. Implications regarding brain phenotypes for future genetic association studies are discussed.