Behavior Genetic Approaches for Situation Research

2017 ◽  
pp. 24-39
Author(s):  
Daniel A. Briley
Keyword(s):  
Environmental Variables ◽  
Behavior Genetics ◽  
Behavioral Genetics ◽  
Situational Factors ◽  
Environment Interaction ◽  
Selection Effects ◽  
Personality Psychology ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
History Of

As a field, behavior genetics has a long and often underappreciated focus on environmental and situational factors. This chapter describes the methodological details and empirical findings of this line of work, as well as what situation research can gain from behavior genetics and vice versa. Genetically informative designs offer tools to quantify the extent to which people actively create their situational experiences as opposed to randomly encountering them, and novel advances in situation research have the potential to clarify the scattered history of environmental variables in behavioral genetics. Current progress in personality psychology will be highlighted. Parallels between behavior genetics and personality work can be found both in terms of mechanisms (e.g., gene-environment correlation and gene × environment interaction contrasting with selection effects and person × situation effects) and explanatory pitfalls. Researchers interested in delineating the pathways from situations to behavior would do well to draw from and build upon work in behavior genetics.

Influence of genetic factors and institutional environment on entrepreneurial activity: evidence from a twin study in Italy

2021 ◽  
Author(s):  
Diego Zunino
Keyword(s):  
Twin Study ◽  
Genetic Factors ◽  
Institutional Environment ◽  
Behavioral Genetics ◽  
Entrepreneurial Activity ◽  
Alternative Theory ◽  
Environment Interaction ◽  
Institutional Environments ◽  
Gene Environment Interaction ◽  
Gene Environment

Abstract Genetic factors influence entrepreneurial activity, but we know little about how genetic factors influence entrepreneurial activity when the institutional environment is favorable. Two theories from behavioral genetics explain the gene–environment interaction. One theory argues that a favorable environment favors the development of genetic factors and their influence. An alternative theory posits that unfavorable environment triggers the development of genetic factors and their influence. I test these two competing theories with a twin study based in Italy. I compare the influence of genetic factors in provinces where the institutional environment favors entrepreneurial activity with provinces where the institutional environment is unfavorable to entrepreneurial activity. I found consistent evidence that genetic factors exert a larger influence in favorable institutional environments, suggesting that favorable institutional environments complement genetic factors.

In Defense of Genopolitics

2013 ◽  
Vol 107 (2) ◽  
pp. 362-374 ◽  
Author(s):  
JAMES H. FOWLER ◽  
CHRISTOPHER T. DAWES
Keyword(s):  
Political Science ◽  
Voter Turnout ◽  
Church Attendance ◽  
Behavior Genetics ◽  
American Political Science Review ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
National Longitudinal Study ◽  
Gene Environment ◽  
American Political Science

The American Political Science Review recently published a critique of an article we published in the Journal of Politics in 2008. In that article we showed that variants of the genes 5HTT and MAOA were significantly associated with voter turnout in a sample of 2,300 subjects from the National Longitudinal Study of Adolescent Health. Here, we address the critique first by conducting a replication study using an independent sample of 9,300 subjects. This study replicates the gene-environment interaction of the 5HTT gene variant with church attendance, but not the association with MAOA. We then focus on the general argument of the critique, showing that many of its characterizations of the literature in genetics and in political science are misleading or incorrect. We conclude by illustrating the ways in which genopolitics has already made a lasting contribution to the field of political science and by offering guidelines for future studies in genopolitics that are based on state-of-the-art recommendations from the field of behavior genetics.

scholarly journals Gene-Environment Interplay in Twin Models

2013 ◽  
Vol 21 (3) ◽  
pp. 368-389 ◽  
Author(s):  
Brad Verhulst ◽  
Peter K. Hatemi
Keyword(s):  
Genetic Similarity ◽  
Behavior Genetics ◽  
Empirical Studies ◽  
Environment Interaction ◽  
Twin Design ◽  
Gene Environment Interaction ◽  
Twin Model ◽  
Gene Environment ◽  
Twin Models ◽  
Classical Twin Design

In this article, we respond to Shultziner's critique that argues that identical twins are more alike not because of genetic similarity, but because they select into more similar environments and respond to stimuli in comparable ways, and that these effects bias twin model estimates to such an extent that they are invalid. The essay further argues that the theory and methods that undergird twin models, as well as the empirical studies which rely upon them, are unaware of these potential biases. We correct this and other misunderstandings in the essay and find that gene-environment (GE) interplay is a well-articulated concept in behavior genetics and political science, operationalized as gene-environment correlation and gene-environment interaction. Both are incorporated into interpretations of the classical twin design (CTD) and estimated in numerous empirical studies through extensions of the CTD. We then conduct simulations to quantify the influence of GE interplay on estimates from the CTD. Due to the criticism's mischaracterization of the CTD and GE interplay, combined with the absence of any empirical evidence to counter what is presented in the extant literature and this article, we conclude that the critique does not enhance our understanding of the processes that drive political traits, genetic or otherwise.

Genetic, environmental, and epigenetic factors in the development of personality disturbance

2009 ◽  
Vol 21 (4) ◽  
pp. 1031-1063 ◽  
Author(s):  
Richard A. Depue
Keyword(s):  
Environmental Variables ◽  
Extreme Values ◽  
Environment Interaction ◽  
Epigenetic Factors ◽  
Dimensional Model ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Main Factors ◽  
Personality Disturbance ◽  
Epigenetic Processes

AbstractA dimensional model of personality disturbance is presented that is defined by extreme values on interacting subsets of seven major personality traits. Being at the extreme has marked effects on the threshold for eliciting those traits under stimulus conditions: that is, the extent to which the environment affects the neurobiological functioning underlying the traits. To explore the nature of development of extreme values on these traits, each trait is discussed in terms of three major issues: (a) the neurobiological variables associated with the trait, (b) individual variation in this neurobiology as a function of genetic polymorphisms, and (c) the effects of environmental adversity on these neurobiological variables through the action of epigenetic processes. It is noted that gene–environment interaction appears to be dependent on two main factors: (a) both genetic and environmental variables appear to have the most profound and enduring effects when they exert their effects during early postnatal periods, times when the forebrain is undergoing exuberant experience–expectant dendritic and axonal growth; and (b) environmental effects on neurobiology are strongly modified by individual differences in “traitlike” functioning of neurobiological variables. A model of the nature of the interaction between environmental and neurobiological variables in the development of personality disturbance is presented.

Biometric and developmental gene–environment interactions: Looking back, moving forward

2007 ◽  
Vol 19 (4) ◽  
pp. 961-976 ◽  
Author(s):  
James Tabery
Keyword(s):  
Complex Traits ◽  
Environment Interaction ◽  
Developmental Gene ◽  
Statistical Interaction ◽  
Gene Environment Interaction ◽  
History Of Research ◽  
Gene Environment ◽  
Lancelot Hogben ◽  
History Of ◽  
Looking Back

AbstractA history of research on gene–environment interaction (G × E) is provided in this article, revealing the fact that there have actually been two distinct concepts of G × E since the very origins of this research. R. A. Fisher introduced what I call the biometric concept of G × E (G × EB), whereas Lancelot Hogben introduced what I call the developmental concept of G × E (G × ED). Much of the subsequent history of research on G × E has largely consisted of the separate legacies of these separate concepts, along with the (sometimes acrimonious) disputes that have arisen time and again when employers of each have argued over the appropriate way to conceptualize the phenomenon. With this history in place, more recent attempts to distinguish between different concepts of G × E are considered, paying particular attention to the commonly made distinction between “statistical interaction” and “interactionism,” and Michael Rutter's distinction between statistical interaction and “the biological concept of interaction.” I argue that the history of the separate legacies of G × EB and G × ED better supports Rutter's analysis of the situation and that this analysis best paves the way for an integrative relationship between the various scientists investigating the place of G × E in the etiology of complex traits.

scholarly journals GxEMM: Extending linear mixed models to general gene-environment interactions

2018 ◽  
Author(s):  
Andy Dahl ◽  
Na Cai ◽  
Jonathan Flint ◽  
Noah Zaitlen
Keyword(s):  
Major Depression ◽  
Mixed Models ◽  
Environmental Variables ◽  
Mixed Model ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Aggregate Effect ◽  
Additive Inheritance ◽  
Categorical Groups

AbstractGene-environment interaction (GxE) is a well-known source of non-additive inheritance. GxE can be important in applications ranging from basic functional genomics to precision medical treatment. Further, GxE effects elude inherently-linear LMMs and may explain missing heritability. We propose a simple, unifying mixed model for polygenic interactions (GxEMM) to capture the aggregate effect of small GxE effects spread across the genome. GxEMM extends existing LMMs for GxE in two important ways. First, it extends to arbitrary environmental variables, not just categorical groups. Second, GxEMM can estimate and test for environment-specific heritability. In simulations where the assumptions of existing methods do not hold, we show that GxEMM improves estimates of ordinary and GxE heritability and increases power to test for polygenic GxE. We then use GxEMM to prove that the heritability of major depression (MD) is reduced by stress, which we previously conjectured but could not prove with prior methods, and that a tail of polygenic GxE effects remains unexplained by MD GWAS.

scholarly journals Digenic Inheritance and Gene-Environment Interaction in a Patient With Hypertriglyceridemia and Acute Pancreatitis

2021 ◽  
Vol 12 ◽  
Author(s):  
Qi Yang ◽  
Na Pu ◽  
Xiao-Yao Li ◽  
Xiao-Lei Shi ◽  
Wei-Wei Chen ◽  
...  
Keyword(s):  
Acute Pancreatitis ◽  
Gene Interaction ◽  
Response To Treatment ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Digenic Inheritance ◽  
Gene Environment ◽  
Heavy Alcohol Consumption ◽  
History Of ◽  
The Common

The etiology of hypertriglyceridemia (HTG) and acute pancreatitis (AP) is complex. Herein, we dissected the underlying etiology in a patient with HTG and AP. The patient had a 20-year history of heavy alcohol consumption and an 8-year history of mild HTG. He was hospitalized for alcohol-triggered AP, with a plasma triglyceride (TG) level up to 21.4 mmol/L. A temporary rise in post-heparin LPL concentration (1.5–2.5 times of controls) was noted during the early days of AP whilst LPL activity was consistently low (50∼70% of controls). His TG level rapidly decreased to normal in response to treatment, and remained normal to borderline high during a ∼3-year follow-up period during which he had abstained completely from alcohol. Sequencing of the five primary HTG genes (i.e., LPL, APOC2, APOA5, GPIHBP1 and LMF1) identified two heterozygous variants. One was the common APOA5 c.553G > T (p.Gly185Cys) variant, which has been previously associated with altered TG levels as well as HTG-induced acute pancreatitis (HTG-AP). The other was a rare variant in the LPL gene, c.756T > G (p.Ile252Met), which was predicted to be likely pathogenic and found experimentally to cause a 40% loss of LPL activity without affecting either protein synthesis or secretion. We provide evidence that both a gene-gene interaction (between the common APOA5 variant and the rare LPL variant) and a gene-environment interaction (between alcohol and digenic inheritance) might have contributed to the development of mild HTG and alcohol-triggered AP in the patient, thereby improving our understanding of the complex etiology of HTG and HTG-AP.

scholarly journals Case-control vs. case-only estimates of gene-environment interactions with common and misclassified clinical diagosis

2019 ◽  
Author(s):  
Iryna Lobach ◽  
Ying Sheng ◽  
Siarhei Lobach ◽  
Lydia Zablotska ◽  
Chiung-Yu Huang
Keyword(s):  
Clinical Diagnosis ◽  
Environmental Variables ◽  
False Negative ◽  
Case Control ◽  
Outcome Variable ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Disease States ◽  
Gene Environment ◽  
Negative Findings

ABSTRACTGenetic studies provide valuable information to assess if the effect of genetic variants varies by the non-genetic (“environmental”) variables, what is traditionally defined to be gene-environment interaction. A common complication is that multiple disease states present with the same set of symptoms, and hence share the clinical diagnosis. Because 1) disease states might have distinct genetic bases; and 2) frequencies of the disease states within the clinical diagnosis vary by the environmental variables, analyses of association with the clinical diagnosis as an outcome variable might result in false positive or false negative findings. We develop estimates for assessment of GxE in a case-only study and compare the case-control and case-only estimates. We report extensive simulation studies that evaluate empirical properties of the estimates and show the application to a study of Alzheimer’s disease.

“Reports of My Death Were Greatly Exaggerated”: Behavior Genetics in the Postgenomic Era

2021 ◽  
Vol 72 (1) ◽  
pp. 37-60 ◽  
Author(s):  
K. Paige Harden
Keyword(s):  
Large Scale ◽  
Behavior Genetics ◽  
Behavioral Genetics ◽  
Association Studies ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
New Methods ◽  
Gene Environment ◽  
Meta Analyses ◽  
And Behavior

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.

Sign in / Sign up

Export Citation Format

Share Document