PreprintArticleVersion 1This version is not peer-reviewed
Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, including New Insights into Stochastic Epigenetic Muta-Tions and Epivariations
Version 1
: Received: 20 August 2024 / Approved: 20 August 2024 / Online: 21 August 2024 (04:40:20 CEST)
How to cite:
Baldrighi, G. N.; Cavagnola, R.; Calzari, L.; Sacco, D.; Costantino, L.; Ferrara, F.; Gentilini, D. Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, including New Insights into Stochastic Epigenetic Muta-Tions and Epivariations. Preprints2024, 2024081504. https://doi.org/10.20944/preprints202408.1504.v1
Baldrighi, G. N.; Cavagnola, R.; Calzari, L.; Sacco, D.; Costantino, L.; Ferrara, F.; Gentilini, D. Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, including New Insights into Stochastic Epigenetic Muta-Tions and Epivariations. Preprints 2024, 2024081504. https://doi.org/10.20944/preprints202408.1504.v1
Baldrighi, G. N.; Cavagnola, R.; Calzari, L.; Sacco, D.; Costantino, L.; Ferrara, F.; Gentilini, D. Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, including New Insights into Stochastic Epigenetic Muta-Tions and Epivariations. Preprints2024, 2024081504. https://doi.org/10.20944/preprints202408.1504.v1
APA Style
Baldrighi, G. N., Cavagnola, R., Calzari, L., Sacco, D., Costantino, L., Ferrara, F., & Gentilini, D. (2024). Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, including New Insights into Stochastic Epigenetic Muta-Tions and Epivariations. Preprints. https://doi.org/10.20944/preprints202408.1504.v1
Chicago/Turabian Style
Baldrighi, G. N., Fulvio Ferrara and Davide Gentilini. 2024 "Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, including New Insights into Stochastic Epigenetic Muta-Tions and Epivariations" Preprints. https://doi.org/10.20944/preprints202408.1504.v1
Abstract
Major depressive disorder (MDD) is a prevalent mental health condition with substantial social and economic consequences. This study focuses on the interplay between genetic and environmen-tal factors in MDD, with particular emphasis on epigenetic mechanisms such as stochastic epige-netic mutations (SEMs), epigenetic age acceleration, and epigenetic drift. We conducted a meta-analysis of DNA methylation patterns across six datasets (n=1125 MDD cases, 398 controls in whole blood; n=95 MDD cases, 96 controls in brain tissues) from the Gene Expression Omnibus. The analysis did not reveal significant global methylation differences between MDD cases and controls. However, a brain-specific probe (cg25801113) near the SHF gene consistently exhibited hypomethylation, suggesting its potential relevance to MDD. SEMs were assessed, revealing a dis-tinct burden at the gene level in MDD cases, though no significant findings emerged for epigenetic age acceleration, indicating it may not play a central role in MDD. The study also identified rare epivariations in specific genes unique to MDD cases. In blood tissue, 51 genes were associated with these unique epivariations, while 1 gene was highlighted in the brain tissue. These results un-derscore the importance of exploring rare epivariations in understanding the molecular mecha-nisms underlying MDD and offer potential targets for further investigation.
Medicine and Pharmacology, Psychiatry and Mental Health
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
