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Genetic susceptibility, inflammation and specific types of depressive symptoms: evidence from the English Longitudinal Study of Ageing

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Philipp Frank, Olesya Ajnakina, Andrew Steptoe, Dorina Cadar

Original languageEnglish
Article number140
JournalTranslational psychiatry
Issue number1
Publication statusPublished - 1 Dec 2020

King's Authors


Genetic susceptibility to depression has been established using polygenic scores, but the underlying mechanisms and the potentially differential effects of polygenic scores on specific types of depressive symptoms remain unknown. This study examined whether systemic low-grade inflammation mediated the association between polygenic scores for depressive symptomatology (DS-PGS) and subsequent somatic versus cognitive-affective depressive symptoms. The sample consisted of 3510 men and women (aged 50+) recruited from the English Longitudinal Study of Ageing. DS-PGS were derived using the results of a recent genome-wide association study. Plasma C-reactive protein (CRP) was measured at wave 6 (2012/13). Depressive symptoms were assessed at wave 8 (2016/17), using the eight-item version of the Centre for Epidemiological Studies Depression Scale. Covariates (wave 2, 2004/05) included age, sex and ten principal components (PCs) to control for population stratification. Confirmatory factor analysis was performed to corroborate a previously identified two-factor structure of the CES-D, distinguishing between cognitive-affective and somatic symptoms. Longitudinal structural equation modelling was used to investigate the mediating role of CRP in the relationship between DS-PGS and cognitive-affective versus somatic symptoms. Our results showed that participants with a higher polygenic susceptibility to DS were significantly more likely to report cognitive-affective and somatic symptoms at follow-up. Mediation analyses revealed that CRP mediated the relationship between DS-PGS and somatic symptoms, but not the association between DS-PGS and cognitive-affective symptoms. These differential effects highlight the importance of considering individual differences in depression profiles in future studies. Ultimately, this will inform healthcare professionals to design more targeted treatments.

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