Estimating Two-Stage Models for Genetic Influences on Alcohol, Tobacco or Drug Use Initiation and Dependence Vulnerability in Twin and Family Data

Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.

Developmental expression of a class IV POU gene in the gastropod Haliotis asinina supports a conserved role in sensory cell development in bilaterians

POU-IV genes regulate neuronal development in a number of deuterostomes (chordates) and ecdysozoans (arthropods and nematodes). Currently their function and expression in the third bilaterian clade, the Lophotrochozoa, comprising molluscs, annelids and. their affiliates, is unclear. Herein we characterise the developmental expression of HasPOU-IV in the gastropod mollusc, Haliotis asinina. The POU-IV gene is transiently expressed in I I distinct larval territories during the first 3 days of development. HasPOU-IV is first expressed in sets of ventral epidermal cells in the newly hatched trochophore larvae. As larval morphogenesis proceeds, we observe HasPOU-IV transcripts in cells that putatively form a range of sensory systems including chemo- and mechanosensory cells in the foot, cephalic tentacles, the ctenidia. the geosensory statocyst and the eyes. By comparing HasPOU-IV expression with POU-IV genes in other bilaterians we infer that this class of POU-domain genes had an ancestral role in regulating sensory cell development.

Genetic and environmental contributions to cannabis dependence in a national young adult twin sample

Background. This paper examines genetic and environmental contributions to risk of cannabis dependence. Method. Symptoms of cannabis dependence and measures of social, family and individual risk factors were assessed in a sample of 6265 young adult male and female Australian twins born 1964-1971. Results. Symptoms of cannabis dependence were common: 11(.)0% of sample (15(.)1% of men and 7(.)8% of women) reported two or more symptoms of dependence. Correlates of cannabis dependence included educational attainment, exposure to parental conflict, sexual abuse, major depression, social anxiety and childhood conduct disorder. However, even after control for the effects of these factors, there was evidence of significant genetic effects on risk of cannabis dependence. Standard genetic modelling indicated that 44(.)7% (95% CI = 15-72(.)2) of the variance in liability to cannabis dependence could be accounted for by genetic factors, 20(.)1% (95 CI = 0-43(.)6) could be attributed to shared environment factors and 35(.)3% (95% CI = 26(.)4-45(.)7) could be attributed to non-shared environmental factors. However, while there was no evidence of significant gender differences in the magnitude of genetic and environmental influences, a model which assumed both genetic and shared environmental influences on risks of cannabis dependence among men and shared environmental but no genetic influences among women provided an equally good fit to the data. Conclusions. There was consistent evidence that genetic risk factors are important determinants of risk of cannabis dependence among men. However, it remains uncertain whether there are genetic influences on liability to cannabis dependence among women.