The relationship between pitch-naming ability and childhood onset of music training is well established and thought to reflect both genetic predisposition and music training during a critical period. However, the importance of the amount of practice during this period has not been investigated. In a population sample of twins (N = 1447, 39% male, 367 complete twin pairs) and a sample of 290 professional musicians (51% male), we investigated the role of genes, age of onset of playing music and accumulated childhood practice on pitch-naming ability. A significant correlation between pitch-naming scores for monozygotic (r = .27, p < .001) but not dizygotic twin pairs (r = −.04, p = .63) supported the role of genetic factors. In professional musicians, the amount of practice accumulated between ages 6 and 11 predicted pitch-naming accuracy (p = .025). In twins, age of onset was no longer a significant predictor once practice was considered. Combined, these findings are in line with the notion that pitch-naming ability is associated with both genetic factors and amount of early practice, rather than just age of onset per se. This may reflect a dose–response relation between practice and pitch-naming ability in genetically predisposed individuals. Alternatively, children who excel at pitch-naming may have an increased tendency to practice.

The Interplay of Genes and Environment across Multiple Studies (IGEMS) is a consortium of 18 twin studies from 5 different countries (Sweden, Denmark, Finland, United States, and Australia) established to explore the nature of gene–environment (GE) interplay in functioning across the adult lifespan. Fifteen of the studies are longitudinal, with follow-up as long as 59 years after baseline. The combined data from over 76,000 participants aged 14–103 at intake (including over 10,000 monozygotic and over 17,000 dizygotic twin pairs) support two primary research emphases: (1) investigation of models of GE interplay of early life adversity, and social factors at micro and macro environmental levels and with diverse outcomes, including mortality, physical functioning and psychological functioning; and (2) improved understanding of risk and protective factors for dementia by incorporating unmeasured and measured genetic factors with a wide range of exposures measured in young adulthood, midlife and later life.

Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of -0.49 and -0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains.

Males and females score differently on some personality traits, but the underlying etiology of these differences is not well understood. This study examined genetic, environmental, and prenatal hormonal influences on individual differences in personality masculinity–femininity (M-F). We used Big-Five personality inventory data of 9,520 Swedish twins (aged 27 to 54) to create a bipolar M-F personality scale. Using biometrical twin modeling, we estimated the influence of genetic and environmental factors on individual differences in a M-F personality score. Furthermore, we tested whether prenatal hormone transfer may influence individuals’ M-F scores by comparing the scores of twins with a same-sex versus those with an opposite-sex co-twin. On average, males scored 1.09 standard deviations higher than females on the created M-F scale. Around a third of the variation in M-F personality score was attributable to genetic factors, while family environmental factors had no influence. Males and females from opposite-sex pairs scored significantly more masculine (both approximately 0.1 SD) than those from same-sex pairs. In conclusion, genetic influences explain part of the individual differences in personality M-F, and hormone transfer from the male to the female twin during pregnancy may increase the level of masculinization in females. Additional well-powered studies are needed to clarify this association and determine the underlying mechanisms in both sexes.

To our knowledge, no comprehensive, interdisciplinary initiatives have been taken to examine the role of genetic variants on patient-reported quality-of-life outcomes. The overall objective of this paper is to describe the establishment of an international and interdisciplinary consortium, the GENEQOL Consortium, which intends to investigate the genetic disposition of patient-reported quality-of-life outcomes. We have identified five primary patient-reported quality-of-life outcomes as initial targets: negative psychological affect, positive psychological affect, self-rated physical health, pain, and fatigue. The first tangible objective of the GENEQOL Consortium is to develop a list of potential biological pathways, genes and genetic variants involved in these quality-of-life outcomes, by reviewing current genetic knowledge. The second objective is to design a research agenda to investigate and validate those genes and genetic variants of patient-reported quality-of-life outcomes, by creating large datasets. During its first meeting, the Consortium has discussed draft summary documents addressing these questions for each patient-reported quality-of-life outcome. A summary of the primary pathways and robust findings of the genetic variants involved is presented here. The research agenda outlines possible research objectives and approaches to examine these and new quality-of-life domains. Intriguing questions arising from this endeavor are discussed. Insight into the genetic versus environmental components of patient-reported quality-of-life outcomes will ultimately allow us to explore new pathways for improving patient care. If we can identify patients who are susceptible to poor quality of life, we will be able to better target specific clinical interventions to enhance their quality of life and treatment outcomes.

Self-rated health questions have been proven to be a highly reliable and valid measure of overall health as measured by other indicators in many population groups. It also has been shown to be a very good predictor of mortality, chronic or severe diseases, and the need for services, and is positively correlated with clinical assessments. Genetic factors have been estimated to account for 25–64% of the variance in the liability of self-rated health. The aim of the present study was to identify Single Nucleotide Polymorphisms (SNPs) underlying the heritability of self-rated health by conducting a genome-wide association analysis in a large sample of 6,706 Australian individuals aged 18–92. No genome wide significant SNPs associated with self-rated health could be identified, indicating that self-rated health may be influenced by a large number of SNPs with very small effect size. A very large sample will be needed to identify these SNPs.

Optimism has a positive influence on mental and somatic health throughout lifetime and into old age. This association is mainly due to shared genetic influences, with some indication of sex differences in the heritability of these and related traits (e.g., depression and subjective wellbeing). Here we extend our initial study of Australian twins by combining with data available from Swedish twins, in order to increase the power to explore potential sex differences in the genetic architecture of optimism, mental and self-rated health and their covariation. Optimism, mental, and self-rated health were measured in 3053 Australian (501 identical female (MZf), 153 identical male (MZm), 274 non-identical female (DZf), 77 non-identical male (DZm), and 242 non-identical opposite-sex twin pairs, and 561 single twins; mean age 60.97 ± 8.76), and 812 Swedish (71 MZf, 53 MZm, 93 DZf and 67 DZm twin pairs, and 244 single twins; mean age 60 ± 14.3) twin individuals using the Life Orientation Test (LOT), the General Health Questionnaire (GHQ) and a single-item self-rating of overall health, respectively. In females all three traits were moderately heritable (.27–.47), whereas in males heritability was substantially lower (.08–.19), but genetic modeling showed that sex differences were not significant. The absence of significant sex differences, despite the consistent trend across the two cohorts, is likely due to a lack of power, raising the importance for future studies, on the same or similar traits, to utilize large samples and to keep the possibility of sex differences in mind when conducting their analyses.