DNA methylation patterns and epigenetic aging associated with suicide attempts in bipolar disorder

Background: Suicidal thoughts and behaviors (STBs) are a public health issue highly prevalent in bipolar disorder (BD). Multiple factors contribute to STBs, and new evidence highlights the significant role of epigenetics, specifically DNA methylation (DNAm). Additionally, recent studies found accele...

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Detalhes bibliográficos
Autores: Mitjans Niubó, Marina, Acosta-Díez, Miriam, Giménez Palomo, Anna, Zafrilla-López, Marina , Saiz, Pilar A., Barrot i Feixat, Carme, Jiménez Martínez, Esther, Papiol, Sergi, Defez Torán, Javier, Xifró Collsamata, Alexandre, Ortega Sánchez, Marisa, Ruiz, Victoria, Gavín, Patrícia, García Portilla González, María Paz, 1962-, González-Blanco, Leticia, Bobes García, Julio, Schulze, Thomas G., Vieta i Pascual, Eduard, 1963-, Benabarre, Antonio, Arias Sampériz, Bárbara
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2025
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositório:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/227024
Acesso em linha:https://hdl.handle.net/2445/227024
Access Level:Acceso aberto
Palavra-chave:Trastorn bipolar
Conducta suïcida
Epigenètica
Manic-depressive illness
Suicidal behavior
Epigenetics
Descrição
Resumo:Background: Suicidal thoughts and behaviors (STBs) are a public health issue highly prevalent in bipolar disorder (BD). Multiple factors contribute to STBs, and new evidence highlights the significant role of epigenetics, specifically DNA methylation (DNAm). Additionally, recent studies found accelerated epigenetic aging (EA) in both BD and STBs. This study aimed to detect epigenetic risk factors for STBs, particularly for suicide attempts (SAs), comparing DNAm patterns and EA between BD patients with (BD/SA) and without (BD/non-SA) a history of SAs. Moreover, EA was calculated to explore age acceleration (AgeAccel) in the BD/SA group. Methods: Genome-wide DNAm patterns of blood samples from 46 BD/SA and 32 BD/non-SA were assessed using Infinium HumanMethylationEPIC v1.0 BeadChip (Illumina). Differentially methylated positions (DMPs) and regions (DMRs) were compared between groups. Gene network analysis was performed using genes mapped to DMPs and DMRs. Lastly, EA from different epigenetic clocks was estimated and compared between groups. Results: We identified 18 DMPs and 2 DMRs (adjusted p-value < 0.05) between BD/SA and BD/non-SA. Among the 18 genes mapped to DMPs and DMRs, the MAD1L1 gene was previously associated with severe SAs. Trends of AgeAccel using the GrimAge and GrimAge2 clocks (p-value ≤ 0.022; adjusted p-value > 0.05) were found in BD/SA. Limitations: Relatively small sample size, cross-sectional design, and use of peripheral blood. Conclusions: Our findings highlight the importance of considering epigenetic markers when studying SAs in mental disorders. These results may contribute to a better understanding of the biological basis of SAs in BD, which could ultimately help identify at-risk individuals for SAs.