Do polygenic risk and stressful life events predict pharmacological treatment response in obsessive compulsive disorder? A gene–environment interaction approach
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Springer Nature
Abstract
The rate of response to pharmacological treatment in Obsessive-compulsive disorder (OCD) oscillates between 40 and
70%. Genetic and environmental factors have been associated with treatment response in OCD. This study analyzes the
predictive ability of a polygenic risk score (PRS) built from OCD-risk variants, for treatment response in OCD, and the
modulation role of stressful life events (SLEs) at the onset of the disorder. PRSs were calculated for a sample of 103
patients. Yale–Brown Obsessive Compulsive Scale (YBOCS) scores were obtained before and after a 12-week treatment.
Regression analyses were performed to analyze the influence of the PRS and SLEs at onset on treatment response. PRS
did not predict treatment response. The best predictive model for post-treatment YBOCS (post YBOCS) included basal
YBOCS and age. PRS appeared as a predictor for basal and post YBOCS. SLEs at onset were not a predictor for treatment
response when included in the regression model. No evidence for PRS predictive ability for treatment response was
found. The best predictor for treatment response was age, agreeing with previous literature specific for SRI treatment.
Suggestions are made on the possible role of neuroplasticity as a mediator on this association. PRS significantly
predicted OCD severity independent on pharmacological treatment. SLE at onset modulation role was not evidenced.
Further research is needed to elucidate the genetic and environmental bases of treatment response in OCD.
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Alemany-Navarro, M., Costas, J., Real, E. et al. Do polygenic risk and stressful life events predict pharmacological treatment response in obsessive compulsive disorder? A gene–environment interaction approach. Transl Psychiatry 9, 70 (2019). https://doi.org/10.1038/s41398-019-0410-0
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https://doi.org/10.1038/s41398-019-0410-0Sponsors
This study was supported in part by the Carlos III Health Institute (PI13/01958,
PI13/00918, PI14/00413 and PI16/00950); FEDER funds (‘A way to build Europe’)
and by the Agency of University and Research Funding Management of the
Catalan Government (2014SGR1672). We also acknowledge support of the
Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia
Severo Ochoa 2017-2021’, SEV-2016-0571 and of the Spanish MINECO
SAF2013-49108-R Plan Estatal. M.A. was supported by the Secretariat for
Universities and Research of the Ministry of Business and Knowledge of the
Government of Catalonia. Grant co-funded by the European Social Fund (ESF)
“ESF, Investing in your future” (2017 FI_B 00327). E.R. was supported by a Juan
Rodés contract (JR14/00038)
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© The Author(s) 2019. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/








