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Diurnal preference changes across the lifespan. However, the mechanisms underlying this age-related shift are poorly understood. The aim of this twin study was to determine the extent to which genetic and environmental influences on diurnal preference are moderated by age. Seven hundred and sixty-eight monozygotic and 674 dizygotic adult twin pairs participating in the University of Washington Twin Registry completed the reduced Morningness-Eveningness Questionnaire as a measure of diurnal preference. Participants ranged in age from 19 to 93 years (mean = 36.23, SD = 15.54) and were categorized on the basis of age into three groups: younger adulthood (19-35 years, n = 1715 individuals), middle adulthood (36-64 years, n = 1003 individuals) and older adulthood (65+ years, n = 168 individuals). Increasing age was associated with an increasing tendency towards morningness ( r = 0.42, p < 0.001). Structural equation modeling techniques parsed the variance in diurnal preference into genetic and environmental influences for the total sample as well as for each age group separately. Additive genetic influences accounted for 52%[46-57%], and non-shared environmental influences 48%[43-54%], of the total variance in diurnal preference. In comparing univariate genetic models between age groups, the best-fitting model was one in which the parameter estimates for younger adults and older adults were equated, in comparison with middle adulthood. For younger and older adulthood, additive genetic influences accounted for 44%[31-49%] and non-shared environmental influences 56%[49-64%] of variance in diurnal preference, whereas for middle adulthood these estimates were 34%[21-45%] and 66%[55-79%], respectively. Therefore, genetic influences on diurnal preference are attenuated in middle adulthood. Attenuation is likely driven by the increased importance of work and family responsibilities during this life stage, in comparison with younger and older adulthood when these factors may be less influential in determining sleep-wake timing. These findings have implications for studies aimed at identifying specific non-shared environmental influences, as well as molecular genetic studies aimed at identifying specific polymorphisms associated with diurnal preference. [ABSTRACT FROM AUTHOR]

In 1984, Hrubec and Robinette published what was arguably the first review of the role of twins in medical research. The authors acknowledged a growing distinction between two categories of twin studies: those aimed at assessing genetic contributions to disease and those aimed at assessing environmental contributions while controlling for genetic variation. They concluded with a brief section on recently founded twin registries that had begun to provide unprecedented access to twins for medical research. Here we offer an overview of the twin research that, in our estimation, best represents the field has progress since 1984. We start by summarizing what we know about twinning. We then focus on the value of twin study designs to differentiate between genetic and environmental influences on health and on emerging applications of twins in multiple areas of medical research. We finish by describing how twin registries and networks are accelerating twin research worldwide. [ABSTRACT FROM AUTHOR]

Background: Studies have found a modest association between depression and obesity, especially in women. Given the substantial genetic contribution to both depression and obesity, we sought to determine whether shared genetic influences are responsible for the association between these two conditions. Methods: Data were obtained from 712 monozygotic and 281 dizygotic female twin pairs who are members of the community-based University of Washington Twin Registry. The presence of depression was determined by self-report of doctor-diagnosed depression. Obesity was defined as body mass index of ≥30 kg/m2, based on self-reported height and weight. Generalized estimating regression models were used to assess the age-adjusted association between depression and obesity. Univariate and bivariate structural equation models estimated the components of variance attributable to genetic and environmental influences. Results: We found a modest phenotypic association between depression and obesity (odds ratio=1.6, 95% confidence interval=1.2–2.1). Additive genetic effects contributed substantially to depression (57%) and obesity (81%). The best-fitting bivariate model indicated that 12% of the genetic component of depression is shared with obesity. Conclusions: The association between depression and obesity in women may be in part due to shared genetic risk for both conditions. Future studies should examine the genetic, environmental, social, and cultural mechanisms underlying the relationship between this association. Depression and Anxiety, 2010. © 2010 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]