This article describes the Australian Twin Attention-deficit/hyperactivity disorder (ADHD) Project (ATAP), the results of research conducted using this database and plans for future studies. Information has been actively collected from Australian families with twin children since 1991 for the ATAP database. The value of assessing siblings as well as twins is emphasized. Much work has gone into continuing the involvement of families in the study though this does become more difficult when twins reach maturity. The main focus of the project is ADHD in children and adolescents plus comorbid conditions including conduct disorder, oppositional defiant disorder, and generalized anxiety disorder. A major challenge has been how to retain continuity in the assessments, while at the same time covering changes in psychiatric classification, such as the move to Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994). Changes in the scale can affect the reports of twin similarity. Over the years, these twins have become part of other twin studies and future plans include linking different twin databases to investigate the relationships between childhood behavior and adult conditions. Recruitment, assessment and retention of twin families require a major commitment but create a significant resource for collaboration in areas outside the original aim.

In this article, we present the genomic DNA yield and the microsatellite and single nucleotide polymorphism (SNP) genotyping success rates of genomic DNA extracted from a large number of mouth swab samples. In total, the median yield and quality was determined in 714 individuals and the success rates in 378,480 genotypings of 915 individuals. The median yield of genomic DNA per mouth swab was 4.1 μg (range 0.1–42.2 μg) and was not reduced when mouth swabs were stored for at least 21 months prior to extraction. A maximum of 20 mouth swabs is collected per participant. Mouth swab samples showed in, respectively, 89% for 390 microsatellites and 99% for 24 SNPs a genotyping success rate higher than 75%. A very low success rate of genotyping (0%–10%) was obtained for 3.2% of the 915 mouth swab samples using microsatellite markers. Only 0.005% of the mouth swab samples showed a geno-typing success rate lower than 75% (range 58%–71%) using SNPs. Our results show that mouth swabs can be easily collected, stored by our conditions for months prior to DNA extraction and result in high yield and high-quality DNA appropriate for genotyping with high success rate including whole genome searches using microsatellites or SNPs.

In Australian twins participating in three different studies (1979–1996), the contribution of genetic and environmental influences to variation in resting systolic (SBP) and diastolic blood pressure (DBP) was studied. The sample consisted of 368 monozygotic and 335 dizygotic twin pairs with measurements for both individuals. Blood pressure measurements in two studies were available for 115 complete twin pairs, and 49 twin pairs had measurements in three studies. This allowed assessment of blood pressure tracking over an average period of 12 years in the age range of 23 to 45 years. Multivariate analyses showed significant heritability (h2) of blood pressure in all studies (SBP h2 = 19%–56%, DBP h2 = 37%–52%). In addition, the analyses showed that the blood pressure tracking was explained by the same set of genetic factors. These results replicate an earlier finding in Dutch twins that also showed stability of the contribution of genetic factors to blood pressure tracking.

Recent research has provided strong support for the existence of a familial risk for suicide, and efforts have been made to separate genetic from enviromental risk factors. Twin studies have played a major role in the identification of genetic factors, and the results indicate that the concordance rate for suicide is higher in identical than in fraternal twins (Baldessarini & Hennen, 2004). Moreover, Segal and Roy (1995) reported a significantly higher frequency of nonfatal suicidal attempts by monozygotic (MZ) than by dyzygotic (DZ) twins whose co-twins had committed suicide. However, doubts remain as to whether the increased risk of suicide in MZ twins is a response to the intense grief over the loss of a close relative, or whether a common genotype is associated with suicidal behavior. Sudden loss, which may carry a stigma in the case of a suicide, has been linked to increased persistent emotional stress and physiological changes (Epstein, 1993; Martin & Dean, 1993). A number of researchers have reported greater suicidal ideation among bereaved MZ twins as compared to DZ twins, suggesting that a loss due to suicide may increase the risk of suicidal behavior in the surviving co-twin (Segal & Bouchard, 1993; Segal & Roy, 1995; Segal et al., 1995). The aim of the present article is to address the issue of the intense grief experienced by twins after the co-twin suicide.

The nature of Generalized Anxiety Disorder (GAD) and worry across the lifespan remains incompletely understood. We investigated genetic and environmental influences on GAD and the proportion of genetic and environmental variation in GAD that is shared with neuroticism in older adult twins. Participants included 1618 monozygotic and 2291 same-sexed dizygotic twin pairs from the Swedish Twin Registry aged 55 to 74. Participants provided personality information in 1973 and also participated in a telephone screening between 1998 and 2002 that included an assessment for lifetime GAD. Univariate biometric models indicated that both GAD and neuroticism were moderately heritable (.27 and .47, respectively), while the balance of variation reflected environmental factors unique to the individual. Bivariate analyses indicated that approximately one third of the genetic influences on GAD were in common with genetic influences on neuroticism, while individual specific environmental influences were virtually unshared between GAD and neuroticism. Analyses of sex effects suggested that men and women differed in the frequency of lifetime GAD and level of neuroticism; however, no sex differences for genetic and environmental influences for either trait were identified.

Previous studies have looked at the structure of attention-deficit/hyperactivity disorder (ADHD) using latent class analysis (LCA) of Child Behavior Checklist (CBCL) or Diagnostic and Statistical Manual of Mental Disorders (DSM) symptom structure. These studies have identified distinct classes of children with inattentive, hyperactive, or combined subtypes and have used these classes to refine genetic analyses. The objective of the current report is to determine if the latent class structure of ADHD subtypes is consistent across informant using the Conners' Rating Scales (CRS). LCA was applied to CRS forms from mother, father, and teacher reports of 1837, 1329 and 1048 latency aged Dutch twins, respectively. The optimal solution for boys was a 5-class solution for mothers, a 3-class solution for fathers, and a 4-class solution for teachers. For girls, a 4-class solution for mothers and a 3-class for fathers and teachers was optimal. Children placed into a class by one informant had markedly increased odds ratio of being placed into the same or similar class by the other informants. Results from LCA using Dutch twins with the CRS show stability across informants suggesting that more stable phenotypes may be accessible for genotyping using a multi-informant approach.

The aim of this study is to examine causes of individual differences in height, weight and body mass index (BMI) in 5-year-old children registered with the Netherlands Twin Register. In addition, we examine whether the results of twin studies can be expanded to the singleton population by comparing the data from twins to Dutch reference growth data and by looking at the twins' target height, which was derived from parental height. For 2996 5-year-old twin pairs, information on height and weight and on parental height was available. Univariate and bivariate genetic analyses of height and weight and univariate analyses of BMI were conducted. In order to compare the twins to the singleton population, standard deviation scores (SDS) for height, BMI and target height were calculated based on Dutch reference growth charts for the general population from 1997. Genetic influences were an important source of variation in height, weight and BMI and the main source of covariation between height and weight. Additive genetic factors accounted for 69% and 66% of the individual differences in height in boys and girls, respectively. For weight, heritability estimates were 59% in boys and 78% in girls and for BMI 34% and 74%. The influence of common environment on height was 25% and 27%, on weight 24% and 10% and on BMI 44% and 12% in boys and girls. The bivariate model showed a large overlap between the genes influencing height and weight. Genes explain 78% (in boys) and 76% (in girls) of the covariance between weight and height. At the age of 5 years, female twins were as tall as singleton children, while male twins were shorter than singletons. For both boys and girls, however, mean height SDS was 0.6 standard deviation scores below the mean target height. All twins had lower BMI than singletons. Twins grow fairly well compared to singletons, but they grow below their target height. This may be due to the above average height of twin parents.

Nitrite and nitrate are the stable end products of the L-arginine-NO pathway, and the sum of nitrite and nitrate (NOx) is a common way to measure nitric oxide (NO) production or secretion. To uncover any genetic influence on NO, we measured NOx in serum samples from monozygotic twin pairs after an overnight fast. Heritability was estimated as intraclass correlation coefficient. We arrived at a heritability estimate of .32 (95% confidence interval 0.17–0.45) for NOx. The numerical heritability estimate was higher for females than for males (0.38 vs. 0.21), and higher for nonsmokers than for smokers (0.36 vs. 0.22). The heritability estimate of NOx was lower than the heritability estimate for other cardiovascular risk factors. This study suggests a low degree of heredity for NOx levels.

In a recent article McArdle and Prescott (2005) showed how simultaneous estimation of the bio-metric parameters can be easily programmed using current mixed-effects modeling programs (e.g., SAS PROC MIXED). This article extends these concepts to deal with mixed-effect modeling of longitudinal twin data. The biometric basis of a polynomial growth curve model was used by Vandenberg and Falkner (1965) and this general class of longitudinal models was represented in structural equation form as a latent curve model by McArdle (1986). The new mixed-effects modeling approach presented here makes it easy to analyze longitudinal growth-decline models with biometric components based on standard maximum likelihood estimation and standard indices of goodness-of-fit (i.e., χ2, df, εa). The validity of this approach is first checked by the creation of simulated longitudinal twin data followed by numerical analysis using different computer programs (i.e., Mplus, Mx, MIXED, NLMIXED). The practical utility of this approach is examined through the application of these techniques to real longitudinal data from the Swedish Adoption/Twin Study of Aging (Pedersen et al., 2002). This approach generally allows researchers to explore the genetic and nongenetic basis of the latent status and latent changes in longitudinal scores in the absence of measurement error. These results show the mixed-effects approach easily accounts for complex patterns of incomplete longitudinal or twin pair data. The results also show this approach easily allows a variety of complex latent basis curves, such as the use of age-at-testing instead of wave-of-testing. Natural extensions of this mixed-effects longitudinal approach include more intensive studies of the available data, the analysis of categorical longitudinal data, and mixtures of latent growth-survival/ frailty models.

Our studies of the teeth and faces of Australian twins commenced at the School of Dentistry, The University of Adelaide in the early 1980s. There are now over 900 pairs of twins enrolled in our continuing investigations, together with 1200 relatives. There are 3 main cohorts of participants. The first cohort comprises around 300 pairs of teenage twins for whom various records have been collected, including dental casts, facial photographs, finger and palm prints and information on laterality, including handedness. The second cohort comprises around 300 pairs of twins who have been examined at 3 stages of dental development from approximately 4 years of age to about 14 years: at primary, mixed, and permanent dentition (excluding 3rd molars) stages. The most recent study of tooth emergence and oral health, for which we are currently recruiting twins, will provide a third cohort of around 500 twin pairs aged from around birth to 3 to 4 years of age. Our broad aim in these studies has been to improve our understanding of how genetic and environmental factors contribute to variation in dental and facial features, and to oral health. We have also used our data to investigate aspects of the determination of laterality, particularly the fascinating phenomenon of mirror imaging. We plan to maximize the use of the longitudinal data and DNA we have collected, and continue to collect, by performing genome-wide scans for putative genetic linkage peaks for a range of dental features, and then to test for association between a series of likely candidate genes and our phenotypes.

This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a ‘self-medicating’ subgroup is needed.

Conduct disorder (CD) symptoms and substance dependence commonly co-occur. Both phenotypes are highly heritable and a common genetic influence on the covariation has been suggested. The aim of this study was to determine the extent to which genes and environment contribute to the covariance between CD and drug dependence using twins from the Colorado Longitudinal Twin Sample and the Colorado Twin Registry. A total of 880 twin pairs (237 monozygotic [MZ] female, 195 MZ male, 116 dizygotic [DZ] female, 118 DZ male and 214 DZ opposite-sex) aged 13 to 18 (mean = 15.65) were included in the analysis. CD was assessed by lifetime Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) symptom count and a polysubstance dependence vulnerability index was developed from responses to the Composite International Diagnostic Interview — Substance Abuse Module. A bivariate Cholesky Decomposition model was used to partition the cause of variation and covariation of the two phenotypes. No sex-limitation was observed in our data, and male and female parameter estimates were constrained to be equal. Both CD symptoms and dependence vulnerability were significantly heritable, and genes, shared environment and nonshared environment all contributed to the covariation between them. Genes contributed 35% of the phenotypic covariance, shared environment contributed 46%, and nonshared environmental influences contributed the remaining 19% to the phenotypic covariance. Therefore, there appears to be pleiotropic genetic influence on CD symptoms and dependence vulnerability.

Nonnormal phenotypic distributions introduce significant problems in the estimation and selection of genetic models. Here, a semiparametric maximum likelihood approach to analyzing non-normal phenotypes is described. In this approach, distributions are explicitly modeled together with genetic and environmental effects. Distributional parameters are introduced through mixture constraints, where the distribution of effects are discretized and freely estimated rather than assumed to be normal. Semiparametric maximum likelihood estimation can be used with a variety of genetic models, can be extended to a variety of pedigree structures, and has various advantages over other approaches to modeling nonnormal data.

The East Flanders Prospective Twin Survey (EFPTS) is a prospective, population-based registry of multiple births in the province of East Flanders, Belgium. EFPTS has several unique features: it is population based and prospective, with the possibility of long-term follow-up; the twins (and higher order multiple births) are ascertained at birth; basic perinatal data recorded; chorion type and zygosity established; and since 1969 placental biopsies have been taken and frozen at −20 °C for later determination of genetic markers. The EFPTS is the only large register that includes placental data and allows differentiation of 3 subtypes of monozygotic (MZ) twins based on the time of the initial zygotic division: the dichorionic–diamnionic pairs (early, before the 4th day after fertilization), the monochorionic–diamnionic pairs (intermediate, between the 4th and the 7th day post fertilization), and the monochorionic–monoamnionic pairs (late, after the 8-day post fertilization). This added a new dimension to didymology (the science of twins; didymos is the Greek word for twin): the timing of MZ twinning. Studies can be initiated taking into account primary biases, those originating in utero. Such studies could throw new light on the controversy over the validity of the classic twin method, the consequences of early embryological events (before and just after implantation of the embryo), the origin of congenital malformations, the sex proportion of multiples, the gene–environment interactions as far as intrauterine environment is concerned, to name but a few.

We tested the hypothesis that energy intake among women with twin pregnancies decreases in late gestation, as the uterus enlarges and they become increasingly uncomfortable. We asked women to recall dietary intake for the previous 24 hours, every 2 weeks from around 29 weeks of gestation, using a photographic atlas and other strategies to estimate portion size. Eighty women provided data at around 29, 31, 33 and 35 weeks of gestation. We calculated total energy intake, and energy intake from carbohydrate, fat and protein. Data were log transformed to reduce skewness. Using mixed effects linear regression models, we found minimal evidence that total energy intake changed over this time period, either before or after adjustment for potential confounding factors (95% confidence interval for relative change per week: −1.4%, 0.6%). There was weak evidence of a small decline in carbohydrate intake over time, both before and after controlling for energy intake. We cannot exclude change in energy intake or diet composition before 29 weeks or after 35 weeks of twin gestation.

The second to fourth finger length ratio (2d:4d) has been the subject of much recent work and is thought to be related to diverse gender and hormone-related traits including sports ability, disease susceptibility, attractiveness and sexuality. It is established in utero and remains constant in adulthood. Familial clustering has been thought to contribute to the development of 2d:4d from early studies but no twin studies exploring heritability have been reported to date. In this study, a sample of 456 female twin pairs (148 monozygotic [MZ], 308 dizygotic [DZ]) aged 18 to 79 years was used to estimate the heritability of 2d:4d for the right and left hands. Finger lengths were derived from hand xrays. Variance components analysis was used to estimate and contrast genetic and environmental effects on this phenotype. The mean 2d:4d was 0.92 (SD = 0.001) for both hands. The MZ intraclass correlation was higher than in DZ (.66 vs. .35 for right 2d:4d, and .71 vs. .37 for left 2d:4d). The best fit model included additive polygenic and unique environmental effects (‘AE’ model), with no significant common environmental effects detected. Heritability was estimated to be approximately 66% for 2d:4d (95% confidence interval 0.5–0.78). These results suggest a substantial genetic contribution to the determination of this hormonally related skeletal ratio in women, which could be more influential than the effects of common prenatal environmental factors. However the current study design does not preclude the possibility of confounding between heritability estimates and unobserved prenatal effects.

Simultaneous analysis of handedness data from 35 samples of twins (with a combined sample size of 21,127 twin pairs) found a small but significant additive genetic effect accounting for 25.47% of the variance (95% confidence interval [CI] 15.69–29.51%). No common environmental influences were detected (C = 0.00; 95% CI 0.00–7.67%), with the majority of the variance, 74.53%, explained by factors unique to the individual (95% CI 70.49–78.67%). No significant heterogeneity was observed within studies that used similar methods to assess handedness, or across studies that used different methods. At an individual level the majority of studies had insufficient power to reject a purely unique environmental model due to insufficient power to detect familial aggregation. This lack of power is seldom mentioned within studies, and has contributed to the misconception that twin studies of handedness are not informative.

Twin pregnancies are becoming common as a result of increased assisted reproduction. Studies have shown that the smaller twin of a pair is at greater risk of morbidity and mortality. Our aim was to determine if there is a relation between birth-weight discordancy and neonatal morbidity and mortality and to test the occurrence of respiratory distress syndrome (RDS) in discordant twins. For 5 years all twins admitted to our intensive care unit were included in the study. Discordance was calculated as the difference between twins' weights divided by the heavier weight. Diagnosis of RDS was made by typical clinical and radiographic methods. Multiple logistic regression was performed with gender, weight order and birth order as the independent variables and RDS as the dependent variable. Two hundred and sixty-six twin pairs with a mean gestation of 33 weeks and a mean birthweight of 1890 g were evaluated. Multiple logistic regression revealed that being the heavier twin was a more important risk factor for RDS (odds ratio 4.5; 95% confidence interval 2.2–9.2) than being the male or second-born twin. Based on neonatal outcomes a birthweight discordance equal or greater than 20% in twin pairs was accepted as the discordance criterion. Discordant and concordant groups were statistically different in neonatal mortality, necrotizing enterocolitis, polycytemia and hypoglycemia. Our data demonstrated that being the heavier twin is a risk factor for RDS and a birth-weight difference of 20% or more in twin pairs should be accepted as discordance.

Numerous studies have reported association between variants in the dystrobrevin binding protein 1 (dysbindin) gene (DTNBP1) and schizophrenia. However, the pattern of results is complex and to date, no specific risk marker or haplotype has been consistently identified. The number of single nucleotide polymorphisms (SNPs) tested in these studies has ranged from 5 to 20. We attempted to replicate previous findings by testing 16 SNPs in samples of 41 Australian pedigrees, 194 Australian cases and 180 controls, and 197 Indian pedigrees. No globally significant evidence for association was observed in any sample, despite power calculations indicating sufficient power to replicate several previous findings. Possible explanations for our results include sample differences in background linkage dis-equilibrium and/or risk allele effect size, the presence of multiple risk alleles upon different haplotypes, or the presence of a single risk allele upon multiple haplotypes. Some previous associations may also represent false positives. Examination of Caucasian HapMap phase II genotype data spanning the DTNBP1 region indicates upwards of 40 SNPs are required to satisfactorily assess all nonredundant variation within DTNBP1 and its potential regulatory regions for association with schizophrenia. More comprehensive studies in multiple samples will be required to determine whether specific DTNBP1 variants function as risk factors for schizophrenia.

Twin registries form an exceptionally rich source of information that is largely unexploited for phenotypic analyses. One obstacle to straightforward phenotypic statistical analysis is the inherent dependency, which is due to the clustering of cases within families. The present simulation study gauges the degree of the bias produced by the dependency of family data on the estimates of standard errors and chi-squared, when they are treated as independent observations in a phenotypic model, and assesses the efficiency of an estimator, which corrects for dependency. When family-clustered data are used for phenotypic analysis, in treating individuals as independent, and using standard maximum likelihood estimation, there is a tendency for the chi-square statistic to be overestimated, and the standard errors of the parameters to be underestimated. The bias increases with family resemblance, due to heritability or shared environment. The source of family resemblance — either heritability (h2) and/or shared environment (c2) — interacts with the composition of the sample. In the absence of c2, samples with twins, parents and spouses show the lowest bias, whereas in the presence of c2 samples with only twins show the lowest bias. In all conditions the bias remained below 15%. The use of the ‘complex option’ available in Mplus (clustering corrected robust maximum likelihood estimation) reduces the bias to the levels observed when only independent cases are considered. Thus with the use of robust estimates the bias due to family dependency becomes practically negligible in all conditions of dependency. In conclusion, the present study shows that the bias due to dependency in family data does not form a serious obstacle to phenotypic data analysis.