Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples – the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

Increased production has been the major goal of animal breeding for many decades, and the correlated side-effects have grown to become a major issue in animal welfare. In this paper, the main genetic mechanisms in which such side-effects may occur are reviewed with examples from our own research in chickens. Pleiotropy, linkage and regulatory pathways are the most important means by which a number of traits may be affected simultaneously by the same selection pressure. Pleiotropy can be exemplified by the gene PMEL17 which causes a lack of black pigmentation in chickens and, simultaneously, predisposes them to become the victims of feather pecking. Linkage is a probable reason why a limited region on chicken chromosome 1 affects many different traits, such as growth, reproduction and fear-related behaviour. Gene regulation is affected by stress, and may cause modifications in behaviour and phenotype which are transferred from parents to offspring by means of epigenetic modifications. Insights into phenomena, such as these, may increase our understanding not only of how artificial selection works, but also evolution at large.

Psychiatric disorders overlap substantially at the genetic level, with family-based methods long pointing toward transdiagnostic risk pathways. Psychiatric genomics has progressed rapidly in the last decade, shedding light on the biological makeup of cross-disorder risk at multiple levels of analysis. Over a hundred genetic variants have been identified that affect multiple disorders, with many more to be uncovered as sample sizes continue to grow. Cross-disorder mechanistic studies build on these findings to cluster transdiagnostic variants into meaningful categories, including in what tissues or when in development these variants are expressed. At the upper-most level, methods have been developed to estimate the overall shared genetic signal across pairs of traits (i.e. single-nucleotide polymorphism-based genetic correlations) and subsequently model these relationships to identify overarching, genomic risk factors. These factors can subsequently be associated with external traits (e.g. functional imaging phenotypes) to begin to understand the makeup of these transdiagnostic risk factors. As psychiatric genomic efforts continue to expand, we can begin to gain even greater insight by including more fine-grained phenotypes (i.e. symptom-level data) and explicitly considering the environment. The culmination of these efforts will help to inform bottom-up revisions of our current nosology.

Genome-wide association studies have uncovered hundreds of loci associated with psychiatric disorders. Cross-disorder studies are among the prime ramifications of such research. Here, we discuss the methodology of the most widespread methods and their clinical utility with regard to diagnosis, prediction, disease aetiology and treatment in psychiatry.

According to the Sasang theory, humans can be categorized into one of the four Sasang constitution (SC) types. The four SC types are Tae-Yang (TY), Tae-Eum (TE), So-Yang (SY), and So-Eum (SE), which are determined mainly on the basis of anthropometric characteristics, personality, and the balance of the physiological functions of the major organ systems. There is a growing recognition in the complementary and alternative medicine area that SC types have the potential to be a useful scientific tool for the prevention, diagnosis, and treatment of diseases (Cooper, Evidence Based Complementary and Alternative Medicine, Vol. 6 (Suppl. 1), 2009, pp. 1–3). The main purposes of the present study are to estimate genetic and environmental influences on SC types, and to explore genetic and environmental correlations that affect phenotypic associations among the SC types. In total, 1,742 (365 monozygotic male, 173 dizygotic male, 675 monozygotic female, 271 dizygotic female, and 258 opposite-sex dizygotic) twins (mean age = 19.1 ± 3.1 year) completed a Sasang questionnaire. Univariate and multivariate model-fitting analyses were performed. Total (additive and non-additive) genetic influences were 71% for males and 81% for females in TE, 70% for males and 71% for females in SE, and 47% for both sexes in SY. Non-additive genetic effects were substantial, and shared environmental influences were negligible in most SC types. Multivariate model-fitting analysis revealed that non-additive genetic and individual-specific environmental correlations between TE and SE were -0.92 (95% CI [-0.89, -0.93]) and -0.62 (95% CI [-0.57, -0.68]), respectively. The corresponding estimates were -0.55 (95% CI [-0.48, -0.61]) and -0.44 (95% CI [-0.37, -0.51]) between TE and SY and 0.19 (95% CI [0.09, 0.29]) and -0.40 (95% CI [-0.32, -0.47]) between SE and SY. These results suggest that the phenotypic associations among SC types may be mediated by pleiotropic mechanism of genes.

Genetic influences play a significant role in risk for psychiatric disorders, prompting numerous endeavors to further understand their underlying genetic architecture. In this paper, we summarize and review evidence from traditional twin studies and more recent genome-wide molecular genetic analyses regarding two important issues that have proven particularly informative for psychiatric genetic research. First, emerging results are beginning to suggest that genetic risk factors for some (but not all) clinically diagnosed psychiatric disorders or extreme manifestations of psychiatric traits in the population share genetic risks with quantitative variation in milder traits of the same disorder throughout the general population. Second, there is now evidence for substantial sharing of genetic risks across different psychiatric disorders. This extends to the level of characteristic traits throughout the population, with which some clinical disorders also share genetic risks. In this review, we summarize and evaluate the evidence for these two issues, for a range of psychiatric disorders. We then critically appraise putative interpretations regarding the potential meaning of genetic correlation across psychiatric phenotypes. We highlight several new methods and studies which are already using these insights into the genetic architecture of psychiatric disorders to gain additional understanding regarding the underlying biology of these disorders. We conclude by outlining opportunities for future research in this area.

Both growth and immune capacity are important traits in animal breeding. The animal quantitative trait loci (QTL) database is a valuable resource and can be used for interpreting the genetic mechanisms that underlie growth and immune traits. However, QTL intervals often involve too many candidate genes to find the true causal genes. Therefore, the aim of this study was to provide an effective annotation pipeline that can make full use of the information of Gene Ontology terms annotation, linkage gene blocks and pathways to further identify pleiotropic genes and gene sets in the overlapping intervals of growth-related and immunity-related QTLs. In total, 55 non-redundant QTL overlapping intervals were identified, 1893 growth-related genes and 713 immunity-related genes were further classified into overlapping intervals and 405 pleiotropic genes shared by the two gene sets were determined. In addition, 19 pleiotropic gene linkage blocks and 67 pathways related to immunity and growth traits were discovered. A total of 343 growth-related genes and 144 immunity-related genes involved in pleiotropic pathways were also identified, respectively. We also sequenced and genotyped 284 individuals from Chinese Meishan pigs and European pigs and mapped the single nucleotide polymorphisms (SNPs) to the pleiotropic genes and gene sets that we identified. A total of 971 high-confidence SNPs were mapped to the pleiotropic genes and gene sets that we identified, and among them 743 SNPs were statistically significant in allele frequency between Meishan and European pigs. This study explores the relationship between growth and immunity traits from the view of QTL overlapping intervals and can be generalized to explore the relationships between other traits.

Asthma and hay fever are likely to share hundreds if not thousands of genetic risk variants. Despite this, the extent to which the power to identify shared risk variants could be improved by considering information from both diseases when designing or analyzing genetic studies has not been studied in detail. Simulations were performed to quantify the power to detect an association between case-control status and a bi-allelic risk variant shared between asthma and hay fever across a range of disease and genetic models, as well as different ascertainment and analytical strategies. For a fixed sample size, when designing a new genome-wide association study (GWAS), selecting for genotyping cases with both asthma and hay fever (A+H+), and controls with neither disease (A-H-) was the study design that provided the greatest power to identify a shared risk variant. On the other hand, when analyzing an existing GWAS, power was greatest across a wide range of scenarios, when cases were defined as individuals who suffered from either disease (A+ or H+) and controls as those who suffered from neither (A-H-). Bivariate analysis of asthma and hay fever provided comparable but slightly decreased power. In conclusion, new GWAS can be designed and existing GWAS reanalyzed more efficiently to identify risk variants for allergic disease by using ascertainment or analytical strategies that consider both asthma and hay fever information.

Comorbidity — the clustered occurrence of two traits or disorders — may be studied in genetically informative designs such as the classical twin study, to test whether genetic and/or environmental factors underlying the two disorders are correlated. When a genetic correlation is found, this can be explained by several mechanisms, including pleiotropy (the same genes influencing multiple traits), and causality (one trait causing the other). With a cotwin control design, it can be investigated which scenario is most plausible. In this design, monozygotic twin pairs discordant for the first trait (i.e., one twin is affected, the other is not) are compared in terms of their risk for the second trait: under a causal model, only the twins affected for the first trait will be at increased risk for the second trait. Under genetic pleiotropy, this risk will be increased in both twins because they share the same risk genes. We first discuss the cotwin control design and then illustrate its application with data on migraine and neuroticism that were collected in 5,200 Dutch twins, including 1,648 complete twin pairs (981 monozygotic and 667 dizygotic pairs). There was a significant association between migraine and neuroticism, which could be attributed to genetic and environmental correlations (rG = .27 and rE = .19). In monozygotic and dizygotic twin pairs discordant for neuroticism, the risk of migraine was significantly higher in the twins with a high neuroticism score. This pattern of results is consistent with a causal relationship, suggesting that neuroticism increases the risk of migraine.

The hypothesis that ornaments can honestly signal quality only if their expression is condition-dependent has dominated the study of the evolution and function of colour traits. Much less interest has been devoted to the adaptive function of colour traits for which the expression is not, or is to a low extent, sensitive to body condition and the environment in which individuals live. The aim of the present paper is to review the current theoretical and empirical knowledge of the evolution, maintenance and adaptive function of colour plumage traits for which the expression is mainly under genetic control. The finding that in many bird species the inheritance of colour morphs follows the laws of Mendel indicates that genetic colour polymorphism is frequent. Polymorphism may have evolved or be maintained because each colour morph facilitates the exploitation of alternative ecological niches as suggested by the observation that individuals are not randomly distributed among habitats with respect to coloration. Consistent with the hypothesis that different colour morphs are linked to alternative strategies is the finding that in a majority of species polymorphism is associated with reproductive parameters, and behavioural, life-history and physiological traits. Experimental studies showed that such covariations can have a genetic basis. These observations suggest that colour polymorphism has an adaptive function. Aviary and field experiments demonstrated that colour polymorphism is used as a criterion in mate-choice decisions and dominance interactions confirming the claim that conspecifics assess each other's colour morphs. The factors favouring the evolution and maintenance of genetic variation in coloration are reviewed, but empirical data are virtually lacking to assess their importance. Although current theory predicts that only condition-dependent traits can signal quality, the present review shows that genetically inherited morphs can reveal the same qualities. The study of genetic colour polymorphism will provide important and original insights on the adaptive function of conspicuous traits.