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Genetic predisposition for negative affect predicts mental health burden during the COVID-19 pandemic.

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Title: Genetic predisposition for negative affect predicts mental health burden during the COVID-19 pandemic.
Authors: Schowe, Alicia M. (AUTHOR), Godara, Malvika (AUTHOR), Czamara, Darina (AUTHOR), Adli, Mazda (AUTHOR), Singer, Tania (AUTHOR), Binder, Elisabeth B. (AUTHOR)
Source: European Archives of Psychiatry & Clinical Neuroscience. Feb2025, Vol. 275 Issue 1, p61-73. 13p.
Subjects: COVID-19 pandemic, Mental health services, COVID-19, Public health, Stay-at-home orders, Loneliness
Abstract: The coronavirus disease 2019 (COVID-19) pandemic was accompanied by an increase in mental health challenges including depression, stress, loneliness, and anxiety. Common genetic variants can contribute to the risk for psychiatric disorders and may present a risk factor in times of crises. However, it is unclear to what extent polygenic risk played a role in the mental health response to the COVID-19 pandemic. In this study, we investigate whether polygenic scores (PGSs) for mental health-related traits can distinguish between four resilience-vulnerability trajectories identified during the COVID-19 pandemic and associated lockdowns in 2020/21. We used multinomial regression in a genotyped subsample (n = 1316) of the CovSocial project. The most resilient trajectory characterized by the lowest mental health burden and the highest recovery rates served as the reference group. Compared to this most resilient trajectory, a higher value on the PGS for the well-being spectrum decreased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.3%). Conversely, a higher value on the PGS for neuroticism increased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.2%). Latent change in mental health burden extracted from the resilience-vulnerability trajectories was not associated with any PGS. Although our findings support an influence of PGS on mental health during COVID-19, the small added explained variance suggests limited utility of such genetic markers for the identification of vulnerable individuals in the general population. [ABSTRACT FROM AUTHOR]
Copyright of European Archives of Psychiatry & Clinical Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Genetic predisposition for negative affect predicts mental health burden during the COVID-19 pandemic.
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  Data: <searchLink fieldCode="AR" term="%22Schowe%2C+Alicia+M%2E%22">Schowe, Alicia M.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Godara%2C+Malvika%22">Godara, Malvika</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Czamara%2C+Darina%22">Czamara, Darina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Adli%2C+Mazda%22">Adli, Mazda</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Singer%2C+Tania%22">Singer, Tania</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Binder%2C+Elisabeth+B%2E%22">Binder, Elisabeth B.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22European+Archives+of+Psychiatry+%26+Clinical+Neuroscience%22">European Archives of Psychiatry & Clinical Neuroscience</searchLink>. Feb2025, Vol. 275 Issue 1, p61-73. 13p.
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  Data: <searchLink fieldCode="DE" term="%22COVID-19+pandemic%22">COVID-19 pandemic</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health+services%22">Mental health services</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Public+health%22">Public health</searchLink><br /><searchLink fieldCode="DE" term="%22Stay-at-home+orders%22">Stay-at-home orders</searchLink><br /><searchLink fieldCode="DE" term="%22Loneliness%22">Loneliness</searchLink>
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  Data: The coronavirus disease 2019 (COVID-19) pandemic was accompanied by an increase in mental health challenges including depression, stress, loneliness, and anxiety. Common genetic variants can contribute to the risk for psychiatric disorders and may present a risk factor in times of crises. However, it is unclear to what extent polygenic risk played a role in the mental health response to the COVID-19 pandemic. In this study, we investigate whether polygenic scores (PGSs) for mental health-related traits can distinguish between four resilience-vulnerability trajectories identified during the COVID-19 pandemic and associated lockdowns in 2020/21. We used multinomial regression in a genotyped subsample (n = 1316) of the CovSocial project. The most resilient trajectory characterized by the lowest mental health burden and the highest recovery rates served as the reference group. Compared to this most resilient trajectory, a higher value on the PGS for the well-being spectrum decreased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.3%). Conversely, a higher value on the PGS for neuroticism increased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.2%). Latent change in mental health burden extracted from the resilience-vulnerability trajectories was not associated with any PGS. Although our findings support an influence of PGS on mental health during COVID-19, the small added explained variance suggests limited utility of such genetic markers for the identification of vulnerable individuals in the general population. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of European Archives of Psychiatry & Clinical Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Feb2025
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