dc.contributor.author
Segura, Alex G.
dc.contributor.author
Martínez Pinteño, Albert
dc.contributor.author
Gassó Astorga, Patricia
dc.contributor.author
Rodríguez Ferret, Natalia
dc.contributor.author
Bioque Alcázar, Miquel
dc.contributor.author
Cuesta, Manuel J.
dc.contributor.author
González Peñas, Javier
dc.contributor.author
García Rizo, Clemente
dc.contributor.author
Lobo, Antonio
dc.contributor.author
González-Pinto, Ana
dc.contributor.author
García Alcón, Alicia
dc.contributor.author
Roldán, Alexandra
dc.contributor.author
Vieta i Pascual, Eduard, 1963-
dc.contributor.author
Castro Fornieles, Josefina
dc.contributor.author
Mané Santacana, Anna
dc.contributor.author
Saiz Ruiz, Jerónimo
dc.contributor.author
Bernardo Arroyo, Miquel
dc.contributor.author
Mas Herrero, Sergi
dc.contributor.author
Mezquida Mateos, Gisela
dc.contributor.author
PEPs Group
dc.date.issued
2023-03-17T15:04:59Z
dc.date.issued
2023-03-17T15:04:59Z
dc.date.issued
2022-05-31
dc.date.issued
2023-03-17T15:05:00Z
dc.identifier
https://hdl.handle.net/2445/195454
dc.description.abstract
Objective: Metabolic syndrome is a health-threatening condition suffered by approximately one third of schizophrenia patients and largely attributed to antipsychotic medication. Previous evidence reports a common genetic background of psychotic and metabolic disorders. In this study, we aimed to assess the role of polygenic risk scores (PRSs) on the progression of the metabolic profile in a first-episode psychosis (FEP) cohort. Method: Of the 231 FEP individuals included in the study, 192-220 participants were included in basal analysis and 118-179 in longitudinal 6-month models. Eleven psychopathologic and metabolic PRSs were constructed. Basal and longitudinal PRSs association with metabolic measurements was assessed by statistical analyses. Results: No major association of psychopathological PRSs with the metabolic progression was found. However, high risk individuals for depression and cholesterol-related PRSs reported a higher increase of cholesterol levels during the follow-up (FDR ≤ 0.023 for all analyses). Their effect was comparable to other well-established pharmacological and environmental risk factors (explaining at least 1.2% of total variance). Conclusion: Our findings provide new evidence of the effects of metabolic genetic risk on the development of metabolic dysregulation. The future establishment of genetic profiling tools in clinical procedures could enable practitioners to better personalize antipsychotic treatment selection and dosage.
dc.format
application/pdf
dc.format
application/pdf
dc.publisher
Elsevier B.V.
dc.relation
Reproducció del document publicat a: https://doi.org/10.1016/j.schres.2022.05.021
dc.relation
Schizophrenia Research, 2022, vol. 244, p. 101-110
dc.relation
https://doi.org/10.1016/j.schres.2022.05.021
dc.rights
cc-by-nc-nd (c) Elsevier B.V., 2022
dc.rights
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Fonaments Clínics)
dc.subject
Trastorns del metabolisme
dc.subject
Síndrome metabòlica
dc.subject
Factors de risc en les malalties
dc.subject
Disorders of metabolism
dc.subject
Metabolic syndrome
dc.subject
Risk factors in diseases
dc.subject
Antipsychotic drugs
dc.title
Metabolic polygenic risk scores effect on antipsychotic-induced metabolic dysregulation: A longitudinal study in a first episode psychosis cohort
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion