An international study finds epigenetic signals — chemical modifications that regulate gene activity without altering DNA, often influenced by environmental factors such as pollution or stress — associated with bipolar disorder, a mental illness characterised by extreme mood changes, alternating depression and euphoria, which could help to develop more accurate clinical prediction tools.
The study, published in the scientific journal EBioMedicine under the title DNA methylation signatures associated with bipolar disorder in peripheral blood improve prediction models, represents the largest meta-analysis on epigenetics in bipolar disorder carried out so far at an international level. The participation of researchers linked to the Hospital Universitari Institut Pere Mata (HUIPM) and the Institut de Recerca Biomèdica Catalunya Sud (IRB CatSud, formerly IISPV) has been especially relevant, as they have provided their own sample of participants, one of the 12 that have contributed to the study. The research has also included the participation of the Universitat Rovira i Virgili (URV) and the team from the Consorci Sanitari del Maresme — both integrated into the national network Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) — and the Universitat Autònoma de Barcelona (UAB).
The research analysed a sample of 3,476 people in total — of whom 1,729 had the disorder and 1,747 were healthy — aged between 16 and 53 years, with 56% women, coming from 12 international samples from different countries. The objective was to identify epigenetic changes associated with bipolar disorder.
Among the most important results, the research team identified 47 regions with epigenetic modification associated with the diagnosis of bipolar disorder and, among these, several are genetic regions involved in processes related to neurotransmission, immune response and cell regulation. In addition, the study also shows that polymethylation scores, which are epigenetic indicators that integrate multiple chemical marks in DNA that can activate or deactivate genes, combined with current genetic models, can improve the predictive ability for bipolar disorder, especially in bipolar disorder type I.
“These results reinforce the idea that epigenetic factors, which are more influenced by environmental factors, can provide additional information to genetics (which is more stable) and contribute, in the future, to the development of useful biological indicators for diagnosis, as well as for clinical decision-making in mental health,” says Elisabet Vilella, one of the researchers involved in the study.
The study has also involved research centres and universities from Europe, North America and Australia, within a large international collaboration under the framework of the Psychiatric Genomics Consortium Bipolar Disorder Working Group.
The publication represents a new recognition of research driven from the region in the field of psychiatry and mental health, and consolidates the position of the participating centres as references in translational research and biomedical innovation.
Bibliographic reference
Tesfaye, M., Stavrum, A. K., Höffler, K. D., O’Connell, K. S., David, F. S., Garrett, M. E., Hesam-Shariati, S., Overs, B. J., Pisanu, C., Spano, L., Watkeys, O. J., Weihs, A., Ardau, R., Ashley-Koch, A. E., Athanasiu, L., Beckham, J. C., Bourassa, K. J., Chillotti, C., Djurovic, S., Drange, O. K., … Le Hellard, S. (2026). DNA methylation signatures associated with bipolar disorder in peripheral blood improve prediction models. EBioMedicine, 128, 106284. https://doi.org/10.1016/j.ebiom.2026.106284
Researcher Noelia Ramírez from IISPV took part on November 28 in the Eurecat Reus symposium on epigenetic and metabolic interactions
The researcher from the Pere Virgili Health Research Institute (IISPV), Noelia Ramírez, participated in the 3rd Eurecat Symposium on Epigenetic and Metabolic Interactions, held on November 28 at Eurecat’s headquarters in Reus. Her presentation was part of a talk entitled “Advancing Precision Environmental Health: From comprehensive exposure characterisation to metabolic and epigenetic markers of effect.”
In her conclusions, she explained that environmental exposures are dynamic, come from multiple sources, and are biologically complex. “To address their impact on health, we need integrated and high-resolution approaches that combine chemistry, biology, and data science,” Ramírez said.
She added that the paradigm of Precision Environmental Health integrates “a detailed characterisation of exposure with the evaluation of effects through omics sciences, in order to reveal how specific environmental mixtures influence molecular pathways, identify early biomarkers of susceptibility, and guide more effective prevention strategies.”