Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank

Interactions between Polygenic Scores and Environments: Methodological and Conceptual Challenges

Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data-in particular, polygenic scores-in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key challenges, provide new perspectives on the study of gene-environment interactions, and end by offering some practical guidance for conducting research in this area. Given the sudden availability of well-powered polygenic scores, we anticipate a substantial increase in research testing for interaction between such scores and environments. The issues we discuss, if not properly addressed, may impact the enduring scientific value of gene-environment interaction studies.

Schizophrenia: Developmental Variability Interacts with Risk Factors to Cause the Disorder: Nonspecific Variability-Enhancing Factors Combine with Specific Risk Factors to Cause Schizophrenia

A new etiological model is proposed for schizophrenia that combines variability-enhancing nonspecific factors acting during development with more specific risk factors. This model is better suited than the current etiological models of schizophrenia, based on the risk factors paradigm, for predicting and/or explaining several important findings about schizophrenia: high co-morbidity rates, low specificity of many risk factors, and persistence in the population of the associated genetic polymorphisms. Compared with similar models, e.g., de-canalization, common psychopathology factor, sexual-selection, or differential sensitivity to the environment, this proposal is more general and integrative. Recently developed research methods have proven the existence of genetic and environmental factors that enhance developmental variability. Applying such methods to newly collected or already available data can allow for testing the hypotheses upon which this model is built. If validated, this model may change the understanding of the etiology of schizophrenia, the research models, and preventionbrk paradigms.

Genetic background and diet affect brown adipose gene coexpression networks associated with metabolic phenotypes

Adipose is a dynamic endocrine organ that is critical for regulating metabolism and is highly responsive to nutritional environment. Brown adipose tissue is an exciting potential therapeutic target; however, there are no systematic studies of gene-by-environment interactions affecting function of this organ. We leveraged a weighted gene coexpression network analysis to identify transcriptional networks in brown adipose tissue from LG/J and SM/J inbred mice fed high- or low-fat diets and correlate these networks with metabolic phenotypes. We identified eight primary gene network modules associated with variation in obesity and diabetes-related traits. Four modules were enriched for metabolically relevant processes such as immune and cytokine response, cell division, peroxisome functions, and organic molecule metabolic processes. The relative expression of genes in these modules is highly dependent on both genetic background and dietary environment. Genes in the immune/cytokine response and cell division modules are particularly highly expressed in high fat-fed SM/J mice, which show unique brown adipose-dependent remission of diabetes. The interconnectivity of genes in these modules is also heavily dependent on diet and strain, with most genes showing both higher expression and coexpression under the same context. We highlight several genes of interest, Col28a1, Cyp26b1, Bmp8b, and Ngef, that have distinct expression patterns among strain-by-diet contexts and fall under metabolic quantitative trait loci previously mapped in an F16 generation of an advanced intercross between LG/J and SM/J. Each of these genes have some connection to obesity and diabetes-related traits, but have not been studied in brown adipose tissue. Our results provide important insights into the relationship between brown adipose and systemic metabolism by being the first gene-by-environment study of brown adipose transcriptional networks.

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration

Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identify 143 independent loci in 112 1-Mb regions, providing insights into the physiology of vitamin D and implicating genes involved in lipid and lipoprotein metabolism, dermal tissue properties, and the sulphonation and glucuronidation of 25OHD. Mendelian randomization models find no robust evidence that 25OHD concentration has causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes have (direct or indirect) causal effects on 25OHD concentration, clarifying the epidemiological relationship between 25OHD status and the health outcomes examined in this study.

Quantification of the overall contribution of gene-environment interaction for obesity-related traits

The growing sample size of genome-wide association studies has facilitated the discovery of gene-environment interactions (GxE). Here we propose a maximum likelihood method to estimate the contribution of GxE to continuous traits taking into account all interacting environmental variables, without the need to measure any. Extensive simulations demonstrate that our method provides unbiased interaction estimates and excellent coverage. We also offer strategies to distinguish specific GxE from general scale effects. Applying our method to 32 traits in the UK Biobank reveals that while the genetic risk score (GRS) of 376 variants explains 5.2% of body mass index (BMI) variance, GRSxE explains an additional 1.9%. Nevertheless, this interaction holds for any variable with identical correlation to BMI as the GRS, hence may not be GRS-specific. Still, we observe that the global contribution of specific GRSxE to complex traits is substantial for nine obesity-related measures (including leg impedance and trunk fat-free mass).

Most gene-by-environment interaction methods rely on the availability of the interacting environment. Here, the authors propose a robust maximum likelihood method for estimating the overall statistical interaction between a genetic risk score for a continuous outcome and all environmental variables.

WNT Signaling and Bone: Lessons From Skeletal Dysplasias and Disorders

Skeletal dysplasias are a diverse group of heritable diseases affecting bone and cartilage growth. Throughout the years, the molecular defect underlying many of the diseases has been identified. These identifications led to novel insights in the mechanisms regulating bone and cartilage growth and homeostasis. One of the pathways that is clearly important during skeletal development and bone homeostasis is the Wingless and int-1 (WNT) signaling pathway. So far, three different WNT signaling pathways have been described, which are all activated by binding of the WNT ligands to the Frizzled (FZD) receptors. In this review, we discuss the skeletal disorders that are included in the latest nosology of skeletal disorders and that are caused by genetic defects involving the WNT signaling pathway. The number of skeletal disorders caused by defects in WNT signaling genes and the clinical phenotype associated with these disorders illustrate the importance of the WNT signaling pathway during skeletal development as well as later on in life to maintain bone mass. The knowledge gained through the identification of the genes underlying these monogenic conditions is used for the identification of novel therapeutic targets. For example, the genes underlying disorders with altered bone mass are all involved in the canonical WNT signaling pathway. Consequently, targeting this pathway is one of the major strategies to increase bone mass in patients with osteoporosis. In addition to increasing the insights in the pathways regulating skeletal development and bone homeostasis, knowledge of rare skeletal dysplasias can also be used to predict possible adverse effects of these novel drug targets. Therefore, this review gives an overview of the skeletal and extra-skeletal phenotype of the different skeletal disorders linked to the WNT signaling pathway.