BACKGROUND: To determine whether genetic risk factors for major depression (MD) and alcohol use disorder (AUD) interact with a potent stressor - death of spouse, parent, and sibling - in predicting episodes of, respectively, MD and AUD.
METHODS: MD and AUD registrations were assessed from national Swedish registries. In individuals born in Sweden 1960-1970, we identified 7586, 388 459, and 34 370 with the loss of, respectively, a spouse, parent, and sibling. We started following subjects at age 18 or the year 2002 with end of follow-up in 2018. We examined time to event - a registration for MD within 6 months or AUD within a year - on an additive scale, using the Nelson-Aalen estimator. Genetic risk was assessed by the Family Genetic Risk Score (FGRS).
RESULTS: In separate models controlling for the main effects of death of spouse, parent, and sibling, FGRS, and sex, significant interactions were seen in all analyses between genetic risk for MD and death of relative in prediction of subsequent MD registration. A similar pattern of results, albeit with weaker interaction effects, was seen for genetic risk for AUD and risk for AUD registration. Genetic risk for bipolar disorder (BD) and anxiety disorders (AD) also interacted with event exposure in predicting MD.
CONCLUSIONS: Genetic risk for both MD and AUD act in part by increasing the sensitivity of individuals to the pathogenic effects of environmental stressors. For prediction of MD, similar effects are also seen for genetic risk for AD and BD.

Foxtail millet (Setaria italica), a short-day plant, is one of the important crops for food security encountering climate change, particularly in regions where it is a staple food. Under the short-day condition in Taiwan, the heading dates (HDs) of foxtail millet accessions varied by genotypes and ambient temperature (AT). The allelic polymorphisms in flowering time (FT)-related genes were associated with HD variations. AT, in the range of 13°C-30°C that was based on field studies at three different latitudes in Taiwan and observations in the phytotron at four different AT regimes, was positively correlated with growth rate, and high AT promoted HD. To elucidate the molecular mechanism of foxtail millet HD, the expression of 14 key FT-related genes in four accessions at different ATs was assessed. We found that the expression levels of SiPRR95, SiPRR1, SiPRR59, SiGhd7-2, SiPHYB, and SiGhd7 were negatively correlated with AT, whereas the expression levels of SiEhd1, SiFT11, and SiCO4 were positively correlated with AT. Furthermore, the expression levels of SiGhd7-2, SiEhd1, SiFT, and SiFT11 were significantly associated with HD. A coexpression regulatory network was identified that shown genes involved in the circadian clock, light and temperature signaling, and regulation of flowering, but not those involved in photoperiod pathway, interacted and were influenced by AT. The results reveal how gene × temperature and gene × gene interactions affect the HD in foxtail millet and could serve as a foundation for breeding foxtail millet cultivars for shift production to increase yield in response to global warming.

Understanding how individual differences arise and how their effects propagate through groups are fundamental issues in biology. Individual differences can arise from indirect genetic effects (IGE): genetically based variation in the conspecifics with which an individual interacts. Using a clonal species, the Amazon molly (Poecilia formosa), we test the hypothesis that IGE can propagate to influence phenotypes of the individuals that do not experience them firsthand. We tested this by exposing genetically identical Amazon mollies to conspecific social partners of different clonal lineages, and then moving these focal individuals to new social groups in which they were the only member to have experienced the IGE. We found that genetically different social environments resulted in the focal animals experiencing different levels of aggression, and that these IGE carried over into new social groups to influence the behaviour of naive individuals. These data reveal that IGE can cascade beyond the individuals that experience them. Opportunity for cascading IGE is ubiquitous, especially in species with long-distance dispersal or fission-fusion group dynamics. Cascades could amplify (or mitigate) the effects of IGE on trait variation and on evolutionary trajectories. Expansion of the IGE framework to include cascading and other types of carry-over effects will therefore improve understanding of individual variation and social evolution and allow more accurate prediction of population response to changing environments.

Major depressive disorder (MDD) is a multifactorial disorder, where multiple susceptibility genes interact with environmental factors, predisposing individuals to the development of the illness. In this article, we reviewed different gene × environment interaction (G×E) studies shifting from a candidate gene to a genome-wide approach. Among environmental factors, childhood adversities and stressful life events have been suggested to exert crucial impacts on MDD. Importantly, the diathesis-stress conceptualization of G×E has been challenged by the differential susceptibility theory. Finally, we summarized several limitations of G×E studies and suggested how future G×E studies might reveal complex interactions between genes and environments in MDD.

Rodent models of brain disorders including neurodevelopmental, neuropsychiatric, and neurodegenerative diseases are essential for increasing our understanding of underlying pathology and for preclinical testing of potential treatments. Some of the most important outcome measures in such studies are behavioral. Unfortunately, reports from different labs are often conflicting, and preclinical studies in rodent models are not often corroborated in human trials. There are many well-established tests for assessing various behavioral readouts, but subtle aspects can influence measurements. Features such as housing conditions, conditions of testing, and the sex and strain of the animals can all have effects on tests of behavior. In the conduct of behavior testing, it is important to keep these features in mind to ensure the reliability and reproducibility of results. In this review, we highlight factors that we and others have encountered that can influence behavioral measures. Our goal is to increase awareness of factors that can affect behavior in rodents and to emphasize the need for detailed reporting of methods.

Recently, hundreds of risk genes associated with psychiatric disorders have been identified. These are thought to interact with environmental stress factors in precipitating pathological behaviors. However, the individual phenotypes resulting from specific genotype by environment (G×E) interactions remain to be determined. Toward a more systematic approach, we developed a novel standardized and partially automatized platform for systematic behavioral and cognitive profiling (PsyCoP). Here, we assessed the behavioral and cognitive disturbances in Tcf4 transgenic mice (Tcf4tg) exposed to psychosocial stress by social defeat during adolescence using a \"two-hit\" G×E mouse model. Notably, TCF4 has been repeatedly identified as a candidate risk gene for different psychiatric diseases and Tcf4tg mice display behavioral endophenotypes such as fear memory impairment and hyperactivity. We use the Research Domain Criteria (RDoC) concept as framework to categorize phenotyping results in a translational approach. We propose two methods of dimension reduction, clustering, and visualization of behavioral phenotypes to retain statistical power and clarity of the overview. Taken together, our results reveal that sensorimotor gating is disturbed by Tcf4 overexpression whereas both negative and positive valence systems are primarily influenced by psychosocial stress. Moreover, we confirm previous reports showing that deficits in the cognitive domain are largely dependent on the interaction between Tcf4 and psychosocial stress. We recommend that the standardized analysis and visualization strategies described here should be applied to other two-hit mouse models of psychiatric diseases and anticipate that this will help directing future preclinical treatment trials.

This chapter focuses on new concepts and new paradigms shedding light on the complex issue of socioenvironmental factors that affect the psychologic development of the child. Longitudinal controlled studies have sorted out \"what leads to what under which circumstances,\" adding to the heuristic value of the addition of risks and of the Bronfenbrenner\'s ecologic model of development and disentangling the socioeconomic status (SES) from poverty. We emphasize the importance of taking attachment styles and attachment disorganization into account for a better understanding of both normal development and early psychopathology. Intervention studies demonstrate the real life effect of the gene-environment interaction with or without epigenetic processes. Thus, this chapter deals with paradigmatic situations as ADS, Prader-Willi, or prematurity as they allow us to learn more about early development and epigenetic influences.

Behavior genetics studies how genetic differences among people contribute to differences in their psychology and behavior. Here, I describe how the conclusions and methods of behavior genetics have evolved in the postgenomic era in which the human genome can be directly measured. First, I revisit the first law of behavioral genetics stating that everything is heritable, and I describe results from large-scale meta-analyses of twin data and new methods for estimating heritability using measured DNA. Second, I describe new methods in statistical genetics, including genome-wide association studies and polygenic score analyses. Third, I describe the next generation of work on gene × environment interaction, with a particular focus on how genetic influences vary across sociopolitical contexts and exogenous environments. Genomic technology has ushered in a golden age of new tools to address enduring questions about how genes and environments combine to create unique human lives.

BACKGROUND: When analyzing data from large-scale genetic association studies, such as targeted or genome-wide resequencing studies, it is common to assume a single genetic model, such as dominant or additive, for all tests of association between a given genetic variant and the phenotype. However, for many variants, the chosen model will result in poor model fit and may lack statistical power due to model misspecification.
OBJECTIVE: We develop power and sample size calculations for tests of gene and gene × environment interaction, allowing for misspecification of the true mode of genetic susceptibility.
METHODS: The power calculations are based on a likelihood ratio test framework and are implemented in an open-source R package (\"genpwr\").
RESULTS: We use these methods to develop an analysis plan for a resequencing study in idiopathic pulmonary fibrosis and show that using a 2-degree of freedom test can increase power to detect recessive genetic effects while maintaining power to detect dominant and additive effects.
CONCLUSIONS: Understanding the impact of model misspecification can aid in study design and developing analysis plans that maximize power to detect a range of true underlying genetic effects. In particular, these calculations help identify when a multiple degree of freedom test or other robust test of association may be advantageous.

Previous studies suggested that both maladaptive stress response and circadian dysregulation might have a role in the background of migraine. However, effects of circadian genes on migraine have not been tested yet. In the present study, we investigated the main effect of rs10462028 of the circadian locomotor output cycles kaput (CLOCK) gene and its interaction with different stress factors on migraine. In our cross-sectional study 2,157 subjects recruited from Manchester and Budapest completed the ID-Migraine questionnaire to detect migraine type headaches (migraineID). Additional stress factors were assessed by a shortened version of the Childhood Trauma Questionnaire, the List of Threatening Experiences questionnaire, and a validated questionnaire to identify financial difficulties. Rs10462028 showed no main genetic effect on migraineID. However, chronic stress indexed by financial difficulties showed a significant interaction effect with rs10462028 (p = 0.006 in recessive model) on migraineID. This result remained significant after correction for lifetime bipolar and unipolar depression and was replicated in both subsamples, although only a trend effect was reached after Bonferroni-correction, which is the strictest correction not considering interdependences. Childhood adversity (CHA) and Recent negative life events (RLE) showed no significant gene × stress interaction with rs10462028. In addition, in silico analysis demonstrated that the genetic region tagged by rs10462028 alters the binding of several miRNAs. Our exploratory study suggests that variations in the CLOCK gene, with moderating effect on gene function through miRNA binding, in interaction with financial difficulties might influence the risk of migraine-type headaches. Thus, financial hardship as a chronic stress factor may affect migraine through altering circadian rhythms.