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Article

Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, Including New Insights into Stochastic Epigenetic Mutations and Epivariations

by
Giulia Nicole Baldrighi
1,†,
Rebecca Cavagnola
1,†,
Luciano Calzari
2,
Davide Sacco
1,3,
Lucy Costantino
3,
Fulvio Ferrara
4 and
Davide Gentilini
1,2,*
1
Department of Brain and Behavioral Sciences, Università di Pavia, 27100 Pavia, Italy
2
Bioinformatics and Statistical Genomics Unit, Istituto Auxologico Italiano IRCCS, 20095 Cusano Milanino, Italy
3
Medical Genetics Laboratory, Centro Diagnostico Italiano, 20147 Milan, Italy
4
Integrated Laboratory Medicine Services, Centro Diagnostico Italiano, 20147 Milan, Italy
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Biomedicines 2024, 12(10), 2181; https://doi.org/10.3390/biomedicines12102181
Submission received: 19 August 2024 / Revised: 18 September 2024 / Accepted: 19 September 2024 / Published: 25 September 2024
(This article belongs to the Special Issue Epigenetic Regulation and Its Impact for Medicine)
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Abstract

Background/Objectives: Major depressive disorder (MDD) is a mental health condition that can severely impact patients’ social lives, leading to withdrawal and difficulty in maintaining relationships. Environmental factors such as trauma and stress can worsen MDD by interacting with genetic predispositions. Epigenetics, which examines changes in gene expression influenced by the environment, may help identify patterns linked to depression. This study aimed to explore the epigenetic mechanisms behind MDD by analysing six public datasets (n = 1125 MDD cases, 398 controls in blood; n = 95 MDD cases, 96 controls in brain tissues) from the Gene Expression Omnibus. Methods: As an innovative approach, two meta-analyses of DNA methylation patterns were conducted alongside an investigation of stochastic epigenetic mutations (SEMs), epigenetic age acceleration, and rare epivariations. Results: While no significant global methylation differences were observed between MDD cases and controls, hypomethylation near the SHF gene (brain-specific probe cg25801113) was consistently found in MDD cases. SEMs revealed a gene-level burden in MDD, though epigenetic age acceleration was not central to the disorder. Additionally, 51 rare epivariations were identified in blood tissue and 1 in brain tissue linked to MDD. Conclusions: The study emphasises the potential role of rare epivariations in MDD’s epigenetic regulation but calls for further research with larger, more diverse cohorts to confirm these findings.
Keywords: MDD; epigenetic drift; rare epivariations; epigenetics MDD; epigenetic drift; rare epivariations; epigenetics

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MDPI and ACS Style

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 Mutations and Epivariations. Biomedicines 2024, 12, 2181. https://doi.org/10.3390/biomedicines12102181

AMA Style

Baldrighi GN, 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 Mutations and Epivariations. Biomedicines. 2024; 12(10):2181. https://doi.org/10.3390/biomedicines12102181

Chicago/Turabian Style

Baldrighi, Giulia Nicole, Rebecca Cavagnola, Luciano Calzari, Davide Sacco, Lucy Costantino, 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 Mutations and Epivariations" Biomedicines 12, no. 10: 2181. https://doi.org/10.3390/biomedicines12102181

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 Mutations and Epivariations. Biomedicines, 12(10), 2181. https://doi.org/10.3390/biomedicines12102181

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