Dataset Information

Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being.

ABSTRACT: The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and educational achievement (EA)). Optimism and AD showed respectively a strong positive and negative phenotypic correlation with WB, the negative correlation of WB and AGG is lower and the correlation with EA is nearly zero. All four traits showed a large genetic contribution to the covariance with well-being. The genetic correlations of well-being with optimism and AD are strong and smaller for AGG and EA. We used the results of the models to explain what information is retrieved based on the bivariate heritability versus the genetic correlations and the (clinical) implications.

SUBMITTER: de Vries LP

PROVIDER: S-EPMC8093176 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being.

de Vries Lianne P LP van Beijsterveldt Toos C E M TCEM Maes Hermine H Colodro-Conde Lucía L Bartels Meike M

Behavior genetics 20210213 3

The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and ...[more]

PMID: 33582898

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Project description:IntroductionMental well-being is a core component of mental health, and resilience is a key process of positive adaptive recovery following adversity. However, we lack an understanding of the neural mechanisms that contribute to individual variation in the trajectories of well-being and resilience relative to risk. Genetic and/or environmental factors may also modulate these mechanisms. The aim of the TWIN-10 Study is to characterise the trajectories of well-being and resilience over 12 years across four timepoints (baseline, 1 year, 10 years, 12 years) in 1669 Australian adult twins of European ancestry (to account for genetic stratification effects). To this end, we integrate data across genetics, environment, psychological self-report, neurocognitive performance and brain function measures of well-being and resilience.Methods and analysisTwins who took part in the baseline TWIN-E Study will be invited back to participate in the TWIN-10 Study, at 10-year and 12-year follow-up timepoints. Participants will complete an online battery of psychological self-reports, computerised behavioural assessments of neurocognitive functions and MRI testing of the brain structure and function during resting and task-evoked scans. These measures will be used as predictors of the risk versus resilience trajectory groups defined by their changing levels of well-being and illness symptoms over time as a function of trauma exposure. Structural equation models will be used to examine the association between the predictors and trajectory groups of resilience and risk over time. Univariate and multivariate twin modelling will be used to determine heritability of the measures, as well as the shared versus unique genetic and environmental contributions.Ethics and disseminationThis study involves human participants. This study was approved by the University of New South Wales Human Research Ethics Committee (HC180403) and the Scientific Management Panel of Neuroscience Research Australia Imaging (CX2019-05). Results will be disseminated through publications and presentations to the public and the academic community. Participants gave informed consent to participate in the study before taking part.

Dataset Information

Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being.

Publications

Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being.

Similar Datasets

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