Electroencephalography profiles as a biomarker of wellbeing: A twin study
Open accessAbstract
Alterations to electroencephalography (EEG) power have been reported for psychiatric conditions such as depression and anxiety, but not for mental wellbeing in a healthy population. This study examined the resting EEG profiles associated with mental wellbeing, and how genetics and environment contribute to these associations using twin modelling. Mental wellbeing was assessed using the COMPAS-W Wellbeing Scale which measures both subjective and psychological wellbeing. In 422 healthy adult monozygotic and dizygotic twins aged 18-61 years, we examined the association between mental wellbeing and EEG power (alpha, beta, theta, delta) using linear mixed models. This was followed by univariate and multivariate twin modelling to assess the heritability of wellbeing and EEG power, and whether the association was driven by shared genetics or environment. A significant association between wellbeing and an interaction of alpha, beta, and delta (ABD) power was found (β = -0.33, p < 0.001) whereby a profile of high alpha and delta and low beta was associated with higher wellbeing, independent of depression and anxiety symptoms. This finding was supported by a five-fold cross-validation analysis. A significant genetic correlation (rG = -0.43) was found to account for 94% of the association between wellbeing and the EEG power interaction. Together, this study has identified a novel EEG profile with a common genetic component that may be a potential biomarker of mental wellbeing. Future studies need to clarify the causal direction of this association.
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High alpha and delta power combined with low beta power was associated with elevated wellbeing.
“Chilver and colleagues found that high alpha and delta power combined with low beta power was associated with elevated wellbeing (Chilver et al. 2020).”
From Changes in Mental Health and EEG Biomarkers of Undergraduates Under Different Patterns of Mindfulness (2024) · cites this paper as Chilver et al. 2020
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References 39 · Cited by 19
- Authors
- Chilver, M. R., Keller, A. S., Park, H. R. P., Jamshidi, J., Montalto, A., Schofield, P. R., Clark, C. R., Harmon-Jones, E., Williams, L. M., & Gatt, J. M.
- Affiliations
- UNSW Sydney (AU)
- Stanford Medicine (US)
- Flinders University (AU)
- VA Palo Alto Health Care System (US)
- Corresponding author
- Gatt, Justine M.
- ORCID
- Venue
- Journal of Psychiatric Research
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 126
- Pages
- 114-121
- ISSN
- 0022-3956 (ISSN-L)
- PMC
- PMC11372816
- OpenAlex
- W3022983956
- Cited by
- 19
- References
- 39
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 3 · 2023: 3 · 2022: 4 · 2021: 1 · 2020: 1
- FWCI
- 2.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Psychiatric Research (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
- Funders
- National Health and Medical Research Council
- Australian Research Council
- Topics
- Social Sciences › Psychology › Social Psychology › Psychological Well-being and Life Satisfaction
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- psychological well-being, resting-state EEG, EEG spectral power, biomarkers, heritability, genetic correlation, monozygotic and dizygotic twins, alpha power, beta power, delta power, theta power, subjective well-being, shared environment
- MeSH terms
- Adolescent, Adult, Anxiety, Mental Disorders, Electroencephalography, Humans, Middle Aged, Twins, Dizygotic, Twins, Monozygotic, Biomarkers, Young Adult
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