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AbstractThe study and identification of genotype–environment interactions (GxE) has been a hot topic in the field of human genetics for several decades. Yet the extent to which GxE contributes to human behavior variability, and its mechanisms, remains largely unknown. Nick Martin has contributed important advances to the field of GxE for human behavior, which include methodological developments, novel analyses and reviews. Here, we will first review Nick's contributions to the GxE research, which started during his PhD and consistently appears in many of his over 1000 publications. Then, we recount a project that led to an article testing the diathesis-stress model for the origins of depression. In this publication, we observed the presence of an interaction between polygenic risk scores for depression (the risk in our 'genotype') and stressful life events (the experiences from our 'environment'), which provided the first empirical support of this model.

Life history theory studies the evolution of traits related to reproductive fitness. Fertility and parental investment are key life history traits which, from an evolutionary standpoint, appear strongly interrelated. The aim of this work was to analyze the genetic and environmental structure and relationship of two behaviors associated with reproductive fitness: total number of offspring and mean duration of breastfeeding. A total of 1,347 women distributed in 239 monozygotic pairs, 236 dizygotic pairs, and 393 individual twins from opposite sex pairs provided information about their reproductive history. We conducted separate univariate analyses to study the sources of variance of both variables; and a bivariate analysis, with threshold liability models. The sources of variance for number of children and breastfeeding were best explained by a model including familial and unique environmental factors, being E = 0.54 (CI 95%: 0.44, 0.66) and E = 0.46 (CI 95%: 0.34, 0.61), respectively. The phenotypic correlation between number of children and breastfeeding was low but significant (r = 0.16, CI 95%: 0.07, 0.25). Familial correlation between these variables did not reach significance, but unique environmental correlation did (re = 0.20, CI 95%: 0.02, 0.37). In conclusion, results do not support the existence of a clear common structure for the number of children a woman has and the time she spends breastfeeding them, at least in modern societies. The relationship found was mainly due to unique environmental factors. More research on these and related phenotypes is needed to better understand women's reproductive decisions and how natural selection acts on the life history traits.

AbstractResearch has emphasized the genetic basis of individual differences in body mass index (BMI); however, genetic factors cannot explain the rapid rise of obesity. Eating behaviors have been stipulated to be the behavioral expression of genetic risk in an obesogenic environment. In this study, we decompose variation and covariation between three key eating behaviors and BMI in a sample of 698 participants, consisting of 167 monozygotic, 150 dizygotic complete same-sex female twins and 64 incomplete pairs from a population-based twin registry in the southeast of Spain, The Murcia Twin Registry. Phenotypes were emotional eating, uncontrolled eating and cognitive restraint, measured by the Three Factor Eating Questionnaire and objectively measured BMI. Variation in eating behaviors was driven by nonshared environmental factors (range: 56%−65%), whereas shared environmental and genetic factors were secondary. All three eating behaviors were correlated with BMI (r = .19–.25). Nonshared environmental factors explained the covariations (Emotional eating–Uncontrolled eating: rE = .54, 95% CI [.43, .64]; BMI–Cognitive restraint: rE = .15, 95% CI [.01, .28]). In contrast to BMI, individual differences in eating behaviors are mostly explained by nonshared environmental factors, which also accounted for the phenotypic correlation between eating behaviors and BMI. Due to the sample size, analyses were underpowered to detect contributions of additive genetic or shared environmental factors to variation and covariation of the phenotypes. Although more research is granted, these results support that eating behaviors could be viable intervention targets to help individuals maintain a healthy weight.

AbstractGenes associated with educational attainment may be related to or interact with adolescent alcohol, tobacco and cannabis use. Potential gene–environment interplay between educational attainment polygenic scores (EA-PGS) and adolescent alcohol, tobacco, and cannabis use was evaluated with a series of regression models fitted to data from a sample of 1871 adult Australian twins. All models controlled for age, age2, cohort, sex and genetic ancestry as fixed effects, and a genetic relatedness matrix was included as a random effect. Although there was no evidence that adolescent alcohol, tobacco or cannabis use interacted with EA-PGS to influence educational attainment, there was a significant, positive gene–environment correlation with adolescent alcohol use at all PGS thresholds (ps <.02). Higher EA-PGS were associated with an increased likelihood of using alcohol as an adolescent (ΔR2 ranged from 0.5% to 1.1%). The positive gene–environment correlation suggests a complex relationship between educational attainment and alcohol use that is due to common genetic factors.

Acne vulgaris is a skin disease with a multifactorial and complex pathology. While several twin studies have estimated that acne has a heritability of up to 80%, the genomic elements responsible for the origin and pathology of acne are still undiscovered. Here we performed a twin-based structural equation model, using available data on acne severity for an Australian sample of 4,491 twins and their siblings aged from 10 to 24. This study extends by a factor of 3 an earlier analysis of the genetic factors of acne. Acne severity was rated by nurses on a 4-point scale (1 =absentto 4 =severe) on up to three body sites (face, back, chest) and on up to three occasions (age 12, 14, and 16). The phenotype that we analyzed was the most severe rating at any site or age. The polychoric correlation for monozygotic twins was higher (rMZ= 0.86, 95% CI [0.81, 0.90]) than for dizygotic twins (rDZ= 0.42, 95% CI [0.35, 0.47]). A model that includes additive genetic effects and unique environmental effects was the most parsimonious model to explain the genetic variance of acne severity, and the estimated heritability was 0.85 (95% CI [0.82, 0.87]). We then conducted a genome-wide analysis including an additional 271 siblings — for a total of 4,762 individuals. A genome-wide association study (GWAS) scan did not detect loci associated with the severity of acne at the threshold of 5E-08 but suggestive association was found for three SNPs: rs10515088 locus 5q13.1 (p= 3.9E-07), rs12738078 locus 1p35.5 (p= 6.7E-07), and rs117943429 locus 18q21.2 (p= 9.1E-07). The 5q13.1 locus is close toPIK3R1, a gene that has a potential regulatory effect on sebocyte differentiation.

AbstractMortality 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.

AbstractBiomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.

Neuroticism, a 'Big Five' personality trait, has been associated with sub-clinical traits of both autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). The objective of the current study was to examine whether causal overlap between ASD and ADHD traits can be accounted for by genetic and environmental risk factors that are shared with neuroticism. We performed twin-based structural equation modeling using self-report data from 12 items of the Neo Five-Factor Inventory Neuroticism domain, 11 Social Responsiveness Scale items, and 12 Adult ADHD Self-Report Scale items obtained from 3,170 young adult Australian individual twins (1,081 complete pairs). Univariate analysis for neuroticism, ASD, and ADHD traits suggested that the most parsimonious models were those with additive genetic and unique environmental components, without sex limitation effects. Heritability of neuroticism, ASD, and ADHD traits, as measured by these methods, was moderate (between 40% and 45% for each respective trait). In a trivariate model, we observed moderate phenotypic (between 0.45 and 0.62), genetic (between 0.56 and 0.71), and unique environmental correlations (between 0.37and 0.55) among neuroticism, ASD, and ADHD traits, with the highest value for the shared genetic influence between neuroticism and self-reported ASD traits (rg = 0.71). Together, our results suggest that in young adults, genetic, and unique environmental risk factors indexed by neuroticism overlap with those that are shared by ASD and ADHD.

AbstractLoneliness 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.

AbstractWe recently reported an association of offspring educational attainment with polygenic risk scores (PRS) computed on parent's non-transmitted alleles for educational attainment using the second GWAS meta-analysis article on educational attainment published by the Social Science Genetic Association Consortium. Here we test the replication of these findings using a more powerful PRS from the third GWAS meta-analysis article by the Consortium. Each of the key findings of our previous paper is replicated using this improved PRS (N = 2335 adolescent twins and their genotyped parents). The association of children's attainment with their own PRS increased substantially with the standardized effect size, moving from β = 0.134, 95% CI = 0.079, 0.188 for EA2, to β = 0.223, 95% CI = 0.169, 0.278, p < .001, for EA3. Parent's PRS again predicted the socioeconomic status (SES) they provided to their offspring and increased from β = 0.201, 95% CI = 0.147, 0.256 to β = 0.286, 95% CI = 0.239, 0.333. Importantly, the PRS for alleles not transmitted to their offspring — therefore acting via the parenting environment — was increased in effect size from β = 0.058, 95% CI = 0.003, 0.114 to β = 0.067, 95% CI = 0.012, 0.122, p = .016. As previously found, this non-transmitted genetic effect was fully accounted for by parental SES. The findings reinforce the conclusion that genetic effects of parenting are substantial, explain approximately one-third the magnitude of an individual's own genetic inheritance and are mediated by parental socioeconomic competence.

The Murcia Twin Registry (MTR) was created in 2006, under the auspices of the University of Murcia and the regional Health Authority, aiming to develop a research resource in Spain intended to stimulate current research and new investigation on the analysis of genetic factors related to health and health-related behaviors. The MTR development strategy was designed as a step-by-step process. Initially, it was focused on women's health but nowadays it includes males and opposite-sex twins. The database comprises 2,281 participants born between 1940 and 1966 in the region of Murcia, in Spain. There have been three waves of data collection and today the MTR databases include questionnaire and anthropometric data as well as biological samples. The current main areas of research interest are health and health-related behaviors, including lifestyle, health promotion, and quality of life. Future short-term development points to the completion of the biobank and continuing the collection of longitudinal data.

AbstractThe Murcia Twin Registry (MTR) is the only population-based registry in Spain. Created in 2006, the registry has been growing more than a decade to become one of the references for twin research in the Mediterranean region. The MTR database currently comprises 3545 adult participants born between 1940 and 1977. It also holds a recently launched satellite registry of university students (N = 204). Along five waves of data collection, the registry has gathered questionnaire and anthropometric data, as well as biological samples. The MTR keeps its main research focus on health and health-related behaviors from a public health perspective. This includes lifestyle, health promotion, quality of life or environmental conditions. Future short-term development points to the expansion of the biobank and the continuation of the collection of longitudinal data.