Regulatory Hub Discovery in MDD Methylome: Hypotheses for Molecular Subtypes via Computational Analysis

Mingyan Liu; Min Huang

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arXiv · 2601.18498

Regulatory Hub Discovery in MDD Methylome: Hypotheses for Molecular Subtypes via Computational Analysis

Mingyan Liu·Min Huang

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Abstract

Major Depressive Disorder (MDD) is a clinically heterogeneous syndrome with diverse etiological pathways. Traditional Epigenome-Wide Association Studies (EWAS) have successfully identified risk loci based on differential methylation magnitude. As a complementary perspective, effect-size-based ranking alone may not fully capture regulatory nodes that exhibit modest methylation changes but occupy critical upstream positions in biological networks. Here, we report findings and hypotheses from a two-tier computational analysis of DNA methylation data (GSE198904; $n=206$ ), combining conventional statistical approaches with machine learning-assisted regulatory inference.

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Mingyan Liu, Min Huang. 2026-01-26. Regulatory Hub Discovery in MDD Methylome: Hypotheses for Molecular Subtypes via Computational Analysis. https://arxiv.org/abs/2601.18498

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