The Louisville Twin Study (LTS) began in 1958 and became a premier longitudinal twin study of cognitive development. The LTS continuously collected data from twins through 2000 after which the study closed indefinitely due to lack of funding. Now that the majority of the sample is age 40 or older (61.36%, N = 1770), the LTS childhood data can be linked to midlife cognitive functioning, among other physical, biological, social, and psychiatric outcomes. We report results from two pilot studies in anticipation of beginning the midlife phase of the LTS. The first pilot study was a participant tracking study, in which we showed that approximately 90% of the Louisville families randomly sampled (N = 203) for the study could be found. The second pilot study consisted of 40 in-person interviews in which twins completed cognitive, memory, biometric, and functional ability measures. The main purpose of the second study was to correlate midlife measures of cognitive functioning to a measure of biological age, which is an alternative index to chronological age that quantifies age as a function of the breakdown of structural and functional physiological systems, and then to relate both of these measures to twins’ cognitive developmental trajectories. Midlife IQ was uncorrelated with biological age (−.01) while better scores on episodic memory more strongly correlated with lower biological age (−.19 to −.31). As expected, midlife IQ positively correlated with IQ measures collected throughout childhood and adolescence. Additionally, positive linear rates of change in FSIQ scores in childhood significantly correlated with biological age (−.68), physical functioning (.71), and functional ability (−.55), suggesting that cognitive development predicts lower biological age, better physical functioning, and better functional ability. In sum, the Louisville twins can be relocated to investigate whether and how early and midlife cognitive and physical health factors contribute to cognitive aging.
We used an alternate age variable, functional biological age (fBioAge), which was based on performance on functional body measures. The aim was to examine development of fBioAge across the adult life span, and to also examine potential gender differences and genetic and environmental influences on change with age. We used longitudinal data (n = 740; chronological age (ChronAge) range 45-85 at baseline) from the Swedish Adoption/Twin Study of Aging. The rate of increase in fBioAge was twice as fast after ChronAge 75 than before. fBioAge was higher in women than in men. fBioAge was fairly equally influenced by genetic and environmental factors. Whereas the rate of ChronAge cannot vary across time, gender, or individual, our analyses demonstrate that fBioAge does capture these within and between individual differences in aging, providing advantages for fBioAge in the study of aging effects.
Subjective health ratings are associated with dementia risk such that those who rate their health more poorly have increased risk for dementia. The genetic and environmental mechanisms underlying this association are unclear, as prior research cannot rule out whether the association is due to genetic confounds. The current study addresses this gap in two samples of twins, one from Sweden (N = 548) and one from Denmark (N = 4,373). Using genetically-informed, bivariate regression models, we assessed whether additive genetic effects explained the association between subjective health and dementia risk as indexed by a latent variable proxy measure. Age at intake, sex, education, depressive symptomatology, and follow-up time between subjective health and dementia risk assessments were included as covariates. Results indicate that genetic variance and other sources of confounding accounted for the majority of the effect of subjective health ratings on dementia risk. After adjusting for genetic confounding and other covariates, a small correlation was observed between subjective health and latent dementia risk in the Danish sample (rE = −.09, p <.05). The results provide further support for the genetic association between subjective health and dementia risk, and also suggest that subjective ratings of health measures may be useful for predicting dementia risk.
Despite emerging interest in gene-environment interaction (GxE) effects, there is a dearth of studies evaluating its potential relevance apart from specific hypothesized environments and biometrical variance trends. Using a monozygotic within-pair approach, we evaluated evidence of G×E for body mass index (BMI), depressive symptoms, and cognition (verbal, spatial, attention, working memory, perceptual speed) in twin studies from four countries. We also evaluated whether APOE is a 'variability gene' across these measures and whether it partly represents the 'G' in G×E effects. In all three domains, G×E effects were pervasive across country and gender, with small-to-moderate effects. Age-cohort trends were generally stable for BMI and depressive symptoms; however, they were variable-with both increasing and decreasing age-cohort trends-for different cognitive measures. Results also suggested that APOE may represent a 'variability gene' for depressive symptoms and spatial reasoning, but not for BMI or other cognitive measures. Hence, additional genes are salient beyond APOE.