We compare the power of two different approaches to detect passive genotype–environment (GE) covariance originating from cultural and genetic transmission operating simultaneously. In the traditional nuclear twin family (NTF) design, cultural transmission is estimated from the phenotypic covariance matrices of the mono- and dizygotic twins and their parents. Here, phenotyping is required in all family members. A more recent method is the transmitted–nontransmitted (T–NT) allele design, which exploits measured genetic variants in parents and offspring to test for effects of nontransmitted alleles from parents. This design requires two-generation genome-wide data and a powerful genome-wide association study (GWAS) for the phenotype in addition to phenotyping in offspring. We compared the power of both designs. Using exact data simulation, we demonstrate three points: how the power of the T–NT design depends on the predictive power of polygenic risk scores (PRSs); that when the NTF design can be applied, its power to detect cultural transmission and GE covariance is high relative to T–NT; and that, given effect sizes from contemporary GWAS, adding PRSs to the NTF design does not yield an appreciable increase in the power to detect cultural transmission. However, it may be difficult to collect phenotypes of parents and the possible importance of gene × age interaction, and secular generational effects can cause complications for many important phenotypes. The T–NT design avoids these complications.

Our current society is characterized by an increased availability of industrially processed foods with high salt, fat and sugar content. How is it that some people prefer these unhealthy foods while others prefer more healthy foods? It is suggested that both genetic and environmental factors play a role. The aim of this study was to (1) identify food preference clusters in the largest twin-family study into food preference to date and (2) determine the relative contribution of genetic and environmental factors to individual differences in food preference in the Netherlands. Principal component analysis was performed to identify the preference clusters by using data on food liking/disliking from 16,541 adult multiples and their family members. To estimate the heritability of food preference, the data of 7833 twins were used in structural equation models. We identified seven food preference clusters (Meat, Fish, Fruits, Vegetables, Savory snacks, Sweet snacks and Spices) and one cluster with Drinks. Broad-sense heritability (additive [A] + dominant [D] genetic factors) for these clusters varied between .36 and .60. Dominant genetic effects were found for the clusters Fruit, Fish (males only) and Spices. Quantitative sex differences were found for Meat, Fish and Savory snacks and Drinks. To conclude, our study convincingly showed that genetic factors play a significant role in food preference. A next important step is to identify these genes because genetic vulnerability for food preference is expected to be linked to actual food consumption and different diet-related disorders.

We seek to identify factors that facilitate or inhibit transmission of drug abuse (DA) from high-risk parents to their children. In 44,250 offspring of these parents, ascertained from a Swedish national sample for having a mother and/or father with DA, we explored, using Cox models, how the prevalence of DA was predicted by potentially malleable risk factors in these high-risk parents, their spouses and the rearing environment they provided. Analyses of offspring of discordant high-risk siblings and offspring of discordant sibling-in-laws and step-parents aided causal inference. Risk for DA in the children was associated with high-risk and married-in parental externalizing psychopathology, a range of other features of these parents (e.g., low education and receipt of welfare), and aspects of the rearing environment (e.g., neighborhood deprivation and number of nearby drug dealers). Offspring of discordant high-risk siblings, siblings-in-laws and step-parents suggested that nearly all these associations were partly causal. A multivariate analysis utilizing offspring of discordant high-risk siblings identified the six most significant potentially malleable risk factors for offspring DA: (1) criminal behavior (CB) in married-in parent, (2) community peer deviance, (3) broken family, (4) DA in high-risk parent, (5) CB in high-risk parent and (6) number of family moves. Children in the lowest decile of risk had a 50% reduction in their DA prevalence, similar to that seen in the general population. We conclude that transmission of DA from high-risk parents to children partly results from a range of potentially malleable risk factors that could serve as foci for intervention.

Mortality risk is known to be associated with many physiological or biochemical risk factors, and polygenic risk scores (PRSs) may offer an additional or alternative approach to risk stratification. We have compared the predictive value of common biochemical tests, PRSs and information on parental survival in a cohort of twins and their families. Common biochemical test results were available for up to 13,365 apparently healthy men and women, aged 17−93 years (mean 49.0, standard deviation [SD] 13.7) at blood collection. PRSs for longevity were available for 14,169 study participants and reported parental survival for 25,784 participants. A search for information on date and cause of death was conducted through the Australian National Death Index, with median follow-up of 11.3 years. Cox regression was used to evaluate associations with mortality from all causes, cancers, cardiovascular diseases and other causes. Linear relationships with all-cause mortality were strongest for C-reactive protein, gamma-glutamyl transferase, glucose and alkaline phosphatase, with hazard ratios (HRs) of 1.16 (95% CI [1.07, 1.24]), 1.15 (95% CI 1.04–1.21), 1.13 (95% CI [1.08, 1.19]) and 1.11 (95% CI [1.05, 1.88]) per SD difference, respectively. Significant nonlinear effects were found for urea, uric acid and butyrylcholinesterase. Lipid risk factors were not statistically significant for mortality in our cohort. Family history and PRS showed weaker but significant associations with survival, with HR in the range 1.05 to 1.09 per SD difference. In conclusion, biochemical tests currently predict long-term mortality more strongly than genetic scores based on genotyping or on reported parental survival.

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term ‘metabolomics’ refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.

Nick Martin was a doctoral student of mine at the University of Birmingham in the mid 1970s. In this review, I discuss two of Nick’s earliest and most seminal contributions to the field of behavior genetics. First, Martin and Eaves’ (1977) extension of the model-fitting approach to multivariate data, which laid the theoretical groundwork for a generation of multivariate behavior genetic studies. Second, the Martin et al.’s (1978) manuscript on the power of the classical twin design, which showed that thousands of twin pairs would be required in order to reliably estimate components of variance, and has served as impetus for the formation of large-scale twin registries across the world. I discuss these contributions against the historical backdrop of a time when we and others were struggling with the challenge of figuring out how to incorporate gene-by-environment interaction, gene–environment correlation, mate selection and cultural transmission into more complex genetic models of human behavior.

Anxiety symptoms co-occur with cardiovascular health problems, with increasing evidence suggesting the role of autonomic dysfunction. Yet, there is limited behavior genetic research on underlying mechanisms. In this twin study, we investigated the phenotypic, genetic and environmental associations between a latent anxiety factor and three cardiovascular autonomic function factors: interbeat interval (IBI, time between heart beats), heart rate variability (HRV, overall fluctuation of heart-beat intervals) and baroreflex sensitivity (BRS, efficiency in regulating blood pressure [BP]). Multivariate twin models were fit using data of female twins (N = 250) of the Twin Interdisciplinary Neuroticism Study (TWINS). A significant negative association was identified between latent anxiety and BRS factors (r = −.24, 95% CI [−.40, −.07]). Findings suggest that this relationship was mostly explained by correlated shared environmental influences, and there was no evidence for pleiotropic genetic or unique environmental effects. We also identified negative relationships between anxiety symptoms and HRV (r = −.17, 95% CI [−.34, .00]) and IBI factors (r = −.13, 95% CI [−.29, .04]), though these associations did not reach statistical significance. Findings implicate that higher anxiety scores are associated with decreased efficiency in short-term BP regulation, providing support for autonomic dysfunction with anxiety symptomatology. The baroreflex system may be a key mechanism underlying the anxiety–cardiovascular health relationship.

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.

Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n = 3261) completing the C-19 COVID-19 symptom tracker app allowed classical twin studies of COVID-19 symptoms, including predicted COVID-19, a symptom-based algorithm to predict true infection, derived from app users tested for SARS-CoV-2. We found heritability of 49% (32−64%) for delirium; 34% (20−47%) for diarrhea; 31% (8−52%) for fatigue; 19% (0−38%) for anosmia; 46% (31−60%) for skipped meals and 31% (11−48%) for predicted COVID-19. Heritability estimates were not affected by cohabiting or by social deprivation. The results suggest the importance of host genetics in the risk of clinical manifestations of COVID-19 and provide grounds for planning genome-wide association studies to establish specific genes involved in viral infectivity and the host immune response.

Previous genetic association studies have failed to identify loci robustly associated with sepsis, and there have been no published genetic association studies or polygenic risk score analyses of patients with septic shock, despite evidence suggesting genetic factors may be involved. We systematically collected genotype and clinical outcome data in the context of a randomized controlled trial from patients with septic shock to enrich the presence of disease-associated genetic variants. We performed genomewide association studies of susceptibility and mortality in septic shock using 493 patients with septic shock and 2442 population controls, and polygenic risk score analysis to assess genetic overlap between septic shock risk/mortality with clinically relevant traits. One variant, rs9489328, located in AL589740.1 noncoding RNA, was significantly associated with septic shock (p = 1.05 × 10–10); however, it is likely a false-positive. We were unable to replicate variants previously reported to be associated (p < 1.00 × 10–6 in previous scans) with susceptibility to and mortality from sepsis. Polygenic risk scores for hematocrit and granulocyte count were negatively associated with 28-day mortality (p = 3.04 × 10–3; p = 2.29 × 10–3), and scores for C-reactive protein levels were positively associated with susceptibility to septic shock (p = 1.44 × 10–3). Results suggest that common variants of large effect do not influence septic shock susceptibility, mortality and resolution; however, genetic predispositions to clinically relevant traits are significantly associated with increased susceptibility and mortality in septic individuals.

Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10–09; observational measure lead SNP rs11803731, p = 2.1 × 10–17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures.

Defective color vision comes in various forms and its frequency varies from population to population. This article is concerned with only the sex-linked form of essential hereditary color blindness. A model of a ‘small’ population is constructed to explore the dynamics of occurrence of color blindness. Different mutation rates are introduced for eggs and sperm. Birth and death rates of affected individuals are assumed to be the same as those in the unaffected. Simulation demonstrates that large changes in frequency occur randomly from the combined effects of mutation, transmission of genes from generation to generation and births and deaths. A reference is made to the hypothesis that observed differences in rates are due to selection in the transition from hunter-gatherer to farmer.

Work incapacity is a major public health challenge and an economic burden to both society and individuals. Understanding the underlying causes is becoming ever more relevant as many countries face an aging workforce. We examined stability and change in genetic and environmental factors influencing work incapacity from age 18 until retirement, and sex differences in these effects. The large population-based sample comprised information from 28,759 twins followed for up to 23 years combined with high-quality national registry data. We measured work incapacity as the total proportion of potential workdays lost due to sickness absence, rehabilitation and disability benefits. Structural equation modeling with twin data indicated moderate genetic influences on work incapacity throughout life in both men and women, with a high degree of genetic stability from young to old adulthood. Environmental influences were mainly age-specific. Our results indicate that largely the same genetic factors influence individual differences in work incapacity throughout young, middle and older adulthood, despite major differences in degree of work incapacity and probable underlying medical causes.

The Academic Development Study of Australian Twins was established in 2012 with the purpose of investigating the relative influence of genes and environments in literacy and numeracy capabilities across two primary and two secondary school grades in Australia. It is the first longitudinal twin project of its kind in Australia and comprises a sample of 2762 twin pairs, 40 triplet sets and 1485 nontwin siblings. Measures include standardized literacy and numeracy test data collected at Grades 3, 5, 7 and 9 as part of the National Assessment Program: Literacy and Numeracy. A range of demographic and behavioral data was also collected, some at multiple longitudinal time points. This article outlines the background and rationale for the study and provides an overview for the research design, sample and measures collected. Findings emerging from the project and future directions are discussed.

There is a commonly observed association between chronic disease and psychological distress, but many potential factors could confound this association. This study investigated the association using a powerful twin study design that can control for unmeasured confounders that are shared between twins, including genetic and environmental factors. We used twin-paired cross-sectional data from the Adult Health and Lifestyle Questionnaire collected by Twins Research Australia from 2014 to 2017. Linear regression models fitted using maximum likelihood estimations (MLE) were used to test the association between self-reported chronic disease status and psychological distress, measured by the Kessler Psychological Distress Scale (K6). When comparing between twin pairs, having any chronic disease was associated with a 1.29 increase in K6 (95% CI: 0.91, 1.66; p < .001). When comparing twins within a pair, having any chronic disease was associated with a 0.36 increase in K6 (95% CI: 0.002, 0.71; p = .049). This within-pair estimate is of most interest as comparing twins within a pair naturally controls for shared factors such as genes, age and shared lived experiences. Whereas the between-pair estimate does not. The weaker effect found within pairs tells us that genetic and environmental factors shared between twins confounds the relationship between chronic disease and psychological distress. This suggests that associations found in unrelated samples may show exaggerated estimates.

Loneliness is related to mental and somatic health outcomes, including borderline personality disorder. Here, we analyze the sources of variation that are responsible for the relationship between borderline personality features (including four dimensions, affective instability, identity disturbance, negative relationships, self-harm and a total score) and loneliness. Using genetically informative data from two large nonclinical samples of adult twin pairs from Australia and the Netherlands (N = 11,329), we estimate the phenotypic, genetic and environmental correlations between self-reported borderline personality features and loneliness. Individual differences in borderline personality and loneliness were best explained by additive genetic factors with heritability estimates h2 = 41% for the borderline personality total score and h2 = 36% for loneliness, with the remaining variation explained by environmental influences that were not shared by twins from the same pair. Genetic and environmental factors influencing borderline personality (total score and four subscales separately) were also partial causes of loneliness. The correlation between loneliness and the borderline personality total score was rph = .51. The genetic correlation was estimated at rg = .64 and the environmental correlation at re = .40. Our study suggests common etiological factors in loneliness and borderline personality features.

We performed a candidate single-nucleotide polymorphism association study of cleft lip and palate in 1992 which earned more citations than it had subjects (N = 230).

We explored the genetic architecture of metabolic risk factors of cardiovascular diseases (CVDs) and their clustering in Chinese boys and girls. Seven metabolic traits (body mass index [BMI], waist circumference [WC], systolic blood pressure [SBP], diastolic blood pressure [DBP], total cholesterol [TC], triglyceride [TG], and uric acid [UA]) were measured in a sample of 1016 twins between 8 and 17 years of age, recruited from the Qingdao Twin Registry. Cholesky, independent pathway, and common pathway models were used to identify the latent genetic structure behind the clustering of these metabolic traits. Genetic architecture of these metabolic traits was largely similar in boys and girls. The highest heritability was found for BMI (a2 = 0.63) in boys and TC (a2 = .69) in girls. Three heritable factors, adiposity (BMI and WC), blood pressure (SBP and DBP), and metabolite factors (TC, TG, and UA), which formed one higher-order latent phenotype, were identified. Latent genetic, common environmental, and unique environmental factors indirectly impacted the three factors through one single latent factor. Our results suggest that there is one latent factor influencing several metabolic traits, which are known risk factors of CVDs in young Chinese twins. Latent genetic, common environmental, and unique environmental factors indirectly imposed on them. These results inform strategies for gene pleiotropic discovery and intervening of CVD risk factors during childhood and adolescence.

A healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.