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Updated: Sep 5, 2026

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain
Published on: July 12, 2012
Epigenetic clues: Predicting maternal depression through DNA methylation
Varghese Merin Jerusha1, Chinnasamy Thirumoorthy1, Kuppan Gokulakrishnan1
1Department of Neurochemistry, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bangalore, India.
Abstract:
Perinatal depression (PND) is a prevalent and multifactorial mood disorder affecting approximately 10-20 % of women globally, with higher burdens reported in low- and middle-income countries. Despite the availability of screening tools such as the Edinburgh Postnatal Depression Scale, these approaches primarily identify risk without elucidating underlying biological mechanisms. Emerging evidence highlights the role of epigenetic regulation particularly DNA methylation as a key mediator linking genetic susceptibility and environmental exposures during the perinatal period. This review synthesizes current knowledge on DNA methylation dynamics in maternal depression, emphasizing both candidate gene and epigenome-wide association study (EWAS) approaches. Candidate gene studies have identified differential methylation in stress-related pathways, including HPA axis genes (NR3C1, FKBP5), serotonergic signalling (SLC6A4), and oxytocin pathways (OXTR), though findings remain limited by poor reproducibility and small sample sizes. In contrast, EWAS provides a hypothesis-free framework, identifying novel differentially methylated positions and regions associated with PND, including predictive CpG panels with potential diagnostic utility. The review also highlights the importance of tissue specificity, temporal epigenetic remodeling across pregnancy, and the interplay between maternal and fetal epigenomes. Furthermore, methodological challenges such as heterogeneity in study design, lack of replication, and analytical inconsistencies remain barriers to clinical translation. Integrating genetic, epigenetic, and environmental data through multi-omics approaches may enhance predictive accuracy and improve early intervention strategies. Overall, DNA methylation represents a promising avenue for understanding the biological underpinnings of PND and developing robust biomarkers for risk prediction and personalized care.
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