Genetic and Environmental Contributions to Relationships and Divorce Attitudes.
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ABSTRACT:
SUBMITTER: Hatemi PK
PROVIDER: S-EPMC4235137 | biostudies-literature | 2015 Jan
REPOSITORIES: biostudies-literature
Publications
Genetic and Environmental Contributions to Relationships and Divorce Attitudes.
Hatemi Peter K PK McDermott Rose R Eaves Lindon L
Personality and individual differences 20150101
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Project description:Background: Twin studies indicate that genetic and environmental factors contribute to both psychological resilience and coping style, but estimates of their relative molecular and shared environmental contributions are limited. The degree of overlap in the genetic architectures of these traits is also unclear. Methods: Using data from a large population- and family-based cohort Generation Scotland (N = 8,734), we estimated the genetic and shared environmental variance components for resilience, task-, emotion-, and avoidance-oriented coping style in a linear mixed model (LMM). Bivariate LMM analyses were used to estimate the genetic correlations between these traits. Resilience and coping style were measured using the Brief Resilience Scale and Coping Inventory for Stressful Situations, respectively. Results: The greatest proportion of the phenotypic variance in resilience remained unexplained, although significant contributions from common genetic variants and family-shared environment were found. Both task- and avoidance-oriented coping had significant contributions from common genetic variants, sibling- and couple-shared environments, variance in emotion-oriented coping was attributable to common genetic variants, family- and couple-shared environments. The estimated correlation between resilience and emotion-oriented coping was high for both common-variant-associated genetic effects (r G = -0.79, se = 0.19), and for the additional genetic effects from the pedigree (r K = -0.94, se = 0.30). Genetic correlations between resilience and task- and avoidance-oriented coping did not meet statistical significance. Conclusions: Both genetics and shared environmental effects were major contributing factors to coping style, whilst the variance in resilience remains largely unexplained. Strong genetic overlap between resilience and emotion-oriented coping suggests a relationship whereby genetic factors that increase negative emotionality also lead to decreased resilience. We suggest that genome-wide family-based studies of resilience and coping may help to elucidate tractable methodologies to identify genetic architectures and modifiable environmental risk factors to protect against psychiatric illness, although further work with larger sample sizes is needed.
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Project description:The variation and covariation for many cardiometabolic traits have been decomposed into genetic and environmental fractions, by using twin or single-nucleotide polymorphism (SNP) models. However, differences in population, age, sex, and other factors hamper the comparison between twin- and SNP-based estimates. Twenty-four cardiometabolic traits and 700,000 genotyped SNPs were available in the study base of 10 682 twins from TwinGene cohort. For the 27 highly correlated pairs (absolute phenotypic correlation coefficient ≥0.40), twin-based bivariate structural equation models were performed in 3870 complete twin pairs, and SNP-based bivariate genomic relatedness matrix restricted maximum likelihood methods were performed in 5779 unrelated individuals. In twin models, the model including additive genetic variance and unique/nonshared environmental variance was the best-fitted model for 7 pairs (5 of them were between blood pressure traits); the model including additive genetic variance, common/shared environmental variance, and unique/nonshared environmental variance components was best fitted for 4 pairs, but estimates of shared environment were close to zero; and the model including additive genetic variance, dominant genetic variance, and unique/nonshared environmental variance was best fitted for 16 pairs, in which significant dominant genetic effects were identified for 13 pairs (including all 9 obesity-related pairs). However, SNP models did not identify significant estimates of dominant genetic effects for any pairs. In the paired t test, twin- and SNP-based estimates of additive genetic correlation were not significantly different (both were 0.67 on average), whereas the nonshared environmental correlations from these 2 models differed slightly from each other (on average, twin-based estimate=0.64 and SNP-based estimate=0.68). Beside additive genetic effects and nonshared environment, nonadditive genetic effects (dominance) also contribute to the covariation between certain cardiometabolic traits (especially for obesity-related pairs); contributions from the shared environment seem to be weak for their covariation in TwinGene samples.
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Project description:IntroductionKeratoconus (KC) is a complex, genetically heterogeneous, multifactorial degenerative disorder that is accompanied by corneal ectasia which usually progresses asymmetrically. With an incidence of approximately 1 per 2000 and 2 cases per 100,000 population presenting annually, KC follows an autosomal recessive or dominant pattern of inheritance and is, apparently, associated with genes that interact with environmental, genetic, and/or other factors. This is an important consideration in refractive surgery in the case of familial KC, given the association of KC with other genetic disorders and the imbalance between dizygotic twins. The present review attempts to identify the genetic loci contributing to the different KC clinical presentations and relate them to the common genetically determined comorbidities associated with KC.MethodsThe PubMed, MEDLINE, Google Scholar, and GeneCards databases were screened for KC-related articles published in English between January 2006 and November 2017. Keyword combinations of "keratoconus," "risk factor(s)," "genetics," "genes," "genetic association(s)," and "cornea" were used. In total, 217 articles were retrieved and analyzed, with greater weight placed on the more recent literature. Further bibliographic research based on the 217 articles revealed another 124 relevant articles that were included in this review. Using the reviewed literature, an attempt was made to correlate genes and genetic risk factors with KC characteristics and genetically related comorbidities associated with KC based on genome-wide association studies, family-based linkage analysis, and candidate-gene approaches.ResultsAn association matrix between known KC-related genes and KC symptoms and/or clinical signs together with an association matrix between identified KC genes and genetically related KC comorbidities/syndromes were constructed.ConclusionTwenty-four genes were identified as potential contributors to KC and 49 KC-related comorbidities/syndromes were found. More than 85% of the known KC-related genes are involved in glaucoma, Down syndrome, connective tissue disorders, endothelial dystrophy, posterior polymorphous corneal dystrophy, and cataract.
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Project description:One of the grand challenges faced by neuroscience is to delineate the determinants of interindividual variation in the comprehensive structural and functional connection matrices that comprise the human connectome. At present, this endeavor appears most tractable at the macroanatomic scale, where intrinsic brain activity exhibits robust patterns of synchrony that recapitulate core functional circuits at the individual level. Here, we use a classical twin study design to examine the heritability of intrinsic functional network properties in 101 twin pairs, including network activity (i.e., variance of a network's specific temporal fluctuations) and internetwork coherence (i.e., correlation between networks' specific temporal fluctuations). Five of 7 networks exhibited significantly heritable (23.3-65.2%) network activity, 6 of the 21 internetwork coherences were significantly heritable (25.6-42.0%), and 11 of the 21 internetwork coherences were significantly influenced by common environmental factors (18.0-47.1%). These results suggest that the source of interindividual variation in functional connectome has a modular architecture: individual modules represented by intrinsic connectivity networks are genetic controlled, while environmental factors influence the interplays between the modules. This work further provides network-specific hypotheses for discovery of the specific genetic and environmental factors influencing functional specialization and integration of the human brain.
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2019-12-01 | GSE135472 | GEO