Gene-environment interaction in atopic diseases: a population-based twin study of early-life exposures

2014 ◽  
Vol 9 (1) ◽  
pp. 79-86 ◽  
Author(s):  
Niklas Kahr ◽  
Vibeke Naeser ◽  
Lone Graff Stensballe ◽  
Kirsten Ohm Kyvik ◽  
Axel Skytthe ◽  
...  
Keyword(s):  
Twin Study ◽  
Early Life ◽  
Population Based ◽  
Environment Interaction ◽  
Atopic Diseases ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Early Life Exposures

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.

Poster #155 CHILD MALTREATMENT, COMT VARIABILITY AND ADULT COGNITION: GENE-ENVIRONMENT INTERACTION USING A TWIN STUDY

2012 ◽  
Vol 136 ◽  
pp. S147
Author(s):  
Ximena Goldberg ◽  
Mar Fatjó-Vilas ◽  
Silvia Alemany ◽  
Aldo Córdova ◽  
Igor Nenadic ◽  
...  
Keyword(s):  
Child Maltreatment ◽  
Twin Study ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Adult Cognition

Gene–environment interaction on cognition: A twin study of childhood maltreatment and COMT variability

2013 ◽  
Vol 47 (7) ◽  
pp. 989-994 ◽  
Author(s):  
Ximena Goldberg ◽  
Mar Fatjó-Vilas ◽  
Silvia Alemany ◽  
Igor Nenadic ◽  
Cristobal Gastó ◽  
...  
Keyword(s):  
Childhood Maltreatment ◽  
Twin Study ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment

scholarly journals A Gene–Environment Interaction Between Smoking and Gene polymorphisms Provides a High Risk of Two Subgroups of Sarcoidosis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Natalia V. Rivera ◽  
Karina Patasova ◽  
Susanna Kullberg ◽  
Lina Marcela Diaz-Gallo ◽  
Tomoko Iseda ◽  
...  
Keyword(s):  
Cigarette Smoking ◽  
Smoking Status ◽  
Interaction Model ◽  
Population Based ◽  
Environment Interaction ◽  
Additive Interaction ◽  
Swedish Population ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Löfgren’S Syndrome

AbstractThe influence and effect of cigarette smoking in sarcoidosis is unclear. Here, we evaluated gene-environment interaction between multiple genetic variants including HLA genes and smoking in sarcoidosis defined by two clinical phenotypes, Löfgren’s syndrome (LS) and patients without Löfgren’s syndrome (non-LS). To quantify smoking effects in sarcoidosis, we performed a gene-environment interaction study in a Swedish population-based case-control study consisting of 3,713 individuals. Cases and controls were classified according to their cigarette smoking status and genotypes by Immunochip platform. Gene-smoking interactions were quantified by an additive interaction model using a logistic regression adjusted by sex, age and first two principal components. The estimated attributable proportion (AP) was used to quantify the interaction effect. Assessment of smoking effects with inclusion of genetic information revealed 53 (in LS) and 34 (in non-LS) SNP-smoking additive interactions at false discovery rate (FDR) below 5%. The lead signals interacting with smoking were rs12132140 (AP = 0.56, 95% CI = 0.22–0.90), p = 1.28e-03) in FCRL1 for LS and rs61780312 (AP = 0.62, 95% CI = 0.28–0.90), p = 3e-04) in IL23R for non-LS. We further identified 16 genomic loci (in LS) and 13 (in non-LS) that interact with cigarette smoking. These findings suggest that sarcoidosis risk is modulated by smoking due to genetic susceptibility. Therefore, patients having certain gene variants, are at a higher risk for the disease. Consideration of individual’s genetic predisposition is crucial to quantify effects of smoking in sarcoidosis.

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