Aretrospective study involving 972 twin births was conducted to evaluate the maternal and fetal outcomes of twin pregnancies complicated by single fetal death. The incidence of single fetal death in twin pregnancies after 20 weeks was 3.3%. Preterm birth rates for 37 and 32 gestational weeks were 81.3% and 41.6% respectively. The median interval between the diagnosis of fetal death and the delivery was 11 days (range 1–27 days). Eighteen (56%) infants were delivered by cesarean and 14 (43%) vaginally. Twin–twin transfusion syndrome (TTTS) was the cause of single fetal death in 8 of 32 twin pregnancies (25%). Ten of the surviving co-twins were lost in the neonatal period (31.3%) and half of those neonatal deaths were due to TTTS. TTTS is the major contributor for perinatal mortality in same-sex twins complicated by single fetal death. The death of one twin in utero should not be the only indication for preterm delivery, and in case of severe prematurity with a stable intrauterine environment; expectant management may be advisable until fetal lung maturation ensues.

The present study deals with the determination of zygosity in twins of childhood age by simple questionnaire. The subjects were 224 twin pairs and their mothers, consisting of 159 monozygotic and 65 same-sex dizygotic pairs, identified by genetic markers including DNA samples. Mothers of twins responded to 19 questionnaire items dealing with twin similarity in 16 items about physical features and 3 items about the degree of similarity and frequency of being mistaken (confusion of identity) when twins were about 1 year of age. The twins themselves responded to three questionnaire items dealing with only confusion of identity items. The results of stepwise logistic regression analysis were as follows: the total accuracy of the mothers' questionnaire was 91.5% when using only the items dealing with confusion of identity. This accuracy was slightly lower than that obtained by twins' self-reports dealing with nearly the same question items of confusion of identity, answered by both twins separately with 93.3% accuracy. The total accuracy of mothers' questionnaire responses rose to 95.1% when we used all 19 items. In addition to ‘the frequency of being mistaken‘, two physical features, namely ‘shape of fingers’ and ‘shape of eyebrow’, were very informative. In conclusion, twin zygosity can be estimated by the use of the mothers' simple questionnaire with sufficient accuracy even in very young twins about 1 year of age.

Following the Derom et al. paper recently published in Twin Research (2003, 6, 19–21), we investigated our French sample, studying the retrospective validity of information given by parents to determine the chorion type of their monozygotic twins. The sample included 44 MZ pairs of known chorion type. Chorion type was established by a pathologist specialising in the study of placenta and zygosity diagnosis using molecular genetic techniques. Results show that of the parents who had information, there was a high level of uncertainty of the chorion type. It therefore seems impossible to obtain valid retrospective determination from parents and the only solution is to have accurate information in the birth records.

Important genetic influence on intervertebral disc degeneration has been shown previously. However, the role of the disc in pain production is not clear and the genetic influence on the development of the symptoms of low back pain is largely unknown. Therefore, data on lifetime prevalence of low back pain from the young cohort in The Danish Twin Registry (aged 12–41) were analyzed with respect to heredity. Casewise concordance rates, odds ratios, tetrachoric correlation coefficients and biometric liability models were estimated in relation to gender and age. Finally, age-adjusted heritability of liability estimates were obtained. Both concordance rates and odds ratios show significant genetic influence on the liability to develop low back pain. Also, tetrachoric correlation coefficients show gnetic influence, but this is not statistically significant for all age groups. The biometric modeling demonstrates shared environment to be a strong component in the youngest age group (12–15), but not above age 15, and it also demonstrates some non-additive genetic effects in the older age groups. Age-adjusted heritability of liability is estimated to 44% (37–50) for males and 40% (34–46) for females aged 16 to 41. Thus, the various analyses all demonstrate significant genetic influence on the liability to low back pain. The shared environment is an important component until age 15. After age 15, this component is unimportant. As people grow older, the effect of the non-shared environment increases and non-additive genetic effects become more evident, indicating an increasing degree of genetic interaction as age increases.

Phenotypic research on leadership style has long considered the importance of individual differences in personality when identifying the behaviors associated with good leaders. Although leadership and many personality traits have been separately shown to be heritable, these constructs have not been examined with genetically informative data to identify common sources of heritability in the two domains. A logical extension to current research, therefore, is to examine the extent to which factors of personality are predictive of leadership dimensions and the extent to which unique genetic contributions to the relationship between personality and leadership style may be identified. Adult twin pairs (183 MZ and 64 same-sex DZ) completed the Multifactor Leadership Questionnaire (MLQ) and the Personality Research Form (PRF). Univariate analyses indicated that both leadership factors (transformational and transactional leadership) and all five of the “Big Five” factors (openness, conscientiousness, extraversion, disagreeableness, and neuroticism) were best fit by genetic models. Multivariate genetic analyses suggest that transformational leadership shows a statistically significant positive genetic correlation with conscientiousness, extraversion, and openness to experience. Transactional leadership shows a significant negative genetic correlation with conscientiousness and extraversion, and a significant positive genetic correlation with disagreeableness. These results underscore the importance of conscientiousness and extraversion in predicting leadership style, and illustrate important differences between transformational and transactional leaders.

The roles of genetic and environmental influences on stressful life events were examined in 3938 twin pairs (MZ, same-sex DZ, and opposite-sex DZ) using a sex-limitation model. Life events were assessed by personal interview, and were categorized as being either personal (i.e., events that occur directly to the individual) or network (i.e., events that occur to someone within the individual's social network, thus affecting the individual indirectly). Consistent with previous reports, genetic factors were found to exert more influence on personal events than network events. Genetic correlations between males and females suggest that many of the same genetic factors are acting within both genders.

Because the determinants of anxiety and depression in late adolescence and early adulthood may differ from those in later life, we investigated the temporal stability and magnitude of genetic and environmental correlates of symptoms of anxiety and depression across the life span. Data were collected from a population-based Australian sample of 4364 complete twin pairs and 777 singletons aged 20 to 96 years who were followed-up over three studies between 1980 and 1996. Each study contained the 14-item self-report DSSI/sAD scale which was used to measure recently experienced symptoms of anxiety and depression. Symptom scores were then divided and assigned to age intervals according to each subject's age at time of participation. We fitted genetic simplex models to take into account the longitudinal nature of the data. For male anxiety and depression, the best fitting simplex models comprised a single genetic innovation at age 20 which was transmitted, and explained genetic variation in anxiety and depression at ages 30, 40, 50 and 60. Most of the lifetime genetic variation in female anxiety and depression could also be explained by innovations at age 20 which were transmitted to all other ages; however, there were also smaller age-dependent genetic innovations at 30 for anxiety and at 40 and 70 for depression. Although the genetic determinants of anxiety and depression appear relatively stable across the lifespan for males and females, there is some evidence to support additional mid-life and late age gene action in females for depression. The fact that mid-life onset for anxiety occurs one decade before depression is also consistent with a causal relationship (anxiety leading to depression) between these conditions. These findings have significance for large scale depression prevention projects.

Although members of monozygotic twin pairs are identical in genome sequence, they may differ in patterns of gene expression. One early and irreversible process affecting gene expression, which can create differences within pairs of female monozygotic twins, is X inactivation — one twin can express mainly paternally-received genes on the X chromosome while the other twin expresses mainly maternally-received genes. It follows that non-identical X chromosome expression may cause female monozygotic twins to correlate less strongly than male monozygotic twins on complex behavioural traits affected by X-linked loci. We tested this hypothesis using data from around 4000 same-sex twin pairs on 9 social, behavioural and cognitive measures at ages 2, 3 and 4. Consistent with our hypothesis, monozygotic males were generally more similar than monozygotic females. Three of four significant differences were in traits showing higher correlations in males than females, and these traits — prosocial behaviour, peer problems, and verbal ability — have all been proposed previously in the literature as being influenced by genes on the X chromosome. Interestingly, dizygotic twins showed the reverse pattern of correlations for similar variables, which is also consistent with the X inactivation hypothesis; taken together, then, our monozygotic and dizygotic results suggest the presence of quantitative trait loci on the X chromosome.

The negative effects of very low birthweight on intellectual development have been well documented, and more recently this effect has been shown to generalise to birthweights within the normal range. In this study we investigate the etiology of this relationship by using a classical twin design to disentangle the contributions of genes and environment. A previous Dutch study (Boomsma et al., 2001) examining these effects indicated that genes were important in mediating the association of birthweight to full IQ measured at ages 7 and 10, but not at ages 5 and 12. Here the association between birthweight and IQ at age 16 is considered (N = 523 twin pairs). Using variance components modeling we found that the genetic variance in birthweight (4%) completely overlapped with that in verbal IQ but not performance or full IQ. Results further showed the importance of shared environmental effects on birthweight (~ 60%) but not on IQ (with genes explaining up to 72% of IQ variance). Models incorporating a direction of causation parameter between birthweight and IQ provided adequate fit to the data in either causal direction for performance and full IQ, but the model with verbal IQ causing birthweight was preferred to one in which birthweight influenced verbal IQ. As the measurement of birthweight precedes the measurement of twins' IQ at age 16, the influence of verbal IQ might be better considered as a proxy for parents' IQ or education, and it is possible that brighter mothers provide better prenatal environments for their children.

Although personality measures such as neuroticism (N), extraversion (E) and novelty-seeking (NS) are associated with the use and abuse/dependence of illicit drugs, little is known about the degree to which these associations are due to genetic or environmental factors. The goal of this analysis was to estimate the extent of genetic and environmental overlap between three dimensions of personality (N, E and NS) and illicit psychoactive substance use and abuse/dependence. Using data from adult male and female twins from the Mid-Atlantic Twin Registry, we used the structural equation modeling package Mx to perform bivariate Cholesky decompositions for personality measures of N, E and NS, individually with cannabis, cocaine, sedatives, stimulants and hallucinogens. This was done separately for use and for a polychotomous diagnosis of abuse and/or dependence. Sex differences were tested. The phenotypic relationship between personality and use and abuse/dependence of illicit drugs were moderate and most of the covariance was explained by genetic factors. Sexes could be equated for N and E but not for NS. For NS, use and abuse/dependence of illicit drugs showed greater phenotypic and genetic overlap in males than females. Of the personality measures, NS and illicit drug use and abuse/dependence were most closely related. NS was most closely related to cannabis use while N showed significant genetic overlap with sedative use. NS in males appears to be a good indicator of risk for cannabis use. This result may be useful for candidate gene studies.

We examined whether there are crosscultural differences in the magnitude of genetic and environmental contributions to risk of becoming a regular smoker and of persistence in smoking in men and women. Standard methods of epidemio-logic and genetic analysis were applied to questionnaire data on history of cigarette use obtained from large samples of male and female like-sex twins from three different countries: Australia (N = 2284 pairs), Sweden (N = 8651 pairs), and Finland (N = 10,948 pairs). Samples were subdivided into three age groups (AG), 18–25 years, 26–35 years, and 36–46 years of age. The magnitude of genetic influence for lifetime smoking was found to be consistent across country and AG for women (46%) and men (57%), and estimates of the contribution from environmental influences shared by twin and co-twin could be equated across all countries by AG for the women (from youngest to oldest AG: 45%, 35%, and 26%), but not for men, with separate estimates obtained for the Scandinavian (33%, 29%, and 19%) and the Australian men (26%, 9%, and 11%). There was no evidence for an important role for shared environmental influences on persistent smoking, and the genetic contribution was found to be consistent in magnitude in men and women, and the same acrosscountry and AG (52%). There are strong genetic influences on smoking behavior, and that risk of becoming a smoker (but not persistence in smoking) may be modified by experiences shared by twins that differ by AG and, at least for men, cultural background.

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.