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Epigenetic, chromatin-associated, and epitranscriptomic regulation in chronic pain: mechanisms and translational prospects

Sep 2026 · Frontiers in Genetics · 0 citations · 80 references
Histone Deacetylase Inhibitors Research

TL;DR

It is argued that future progress will depend on cell-resolved longitudinal multi-omics, causal epigenome editing, human tissue validation, and biomarker studies designed around prespecified clinical utility rather than statistical association alone.

Abstract

Chronic pain is sustained by durable yet dynamic changes in gene regulation across sensory neurons, spinal circuits, glial and immune cells, and higher brain regions. This review critically evaluates three related but conceptually distinct regulatory layers: chromatin-associated epigenetic mechanisms, including DNA methylation and hydroxymethylation, histone modifications, and chromatin accessibility; non-coding RNAs that directly interface with chromatin-regulatory machinery; and RNA N6-methyladenosine (m6A), an epitranscriptomic mechanism that acts primarily at the RNA level. Across pain models, the most reproducible mechanistic theme is not a uniform increase or decrease in one epigenetic mark, but locus-, cell-, and stage-specific reprogramming that can silence anti-nociceptive genes while activating pro-nociceptive or inflammatory programs. Evidence is strongest where locus-specific perturbation connects a regulatory change to transcription, cellular excitability, synaptic function, and pain behavior; bulk-tissue associations remain mainly hypothesis-generating. Human blood and tissue studies have identified candidate methylation signatures, but none is sufficiently validated for routine diagnosis, prognosis, or treatment selection. Likewise, broad DNMT, HDAC, or histone-modifying interventions show analgesic activity mainly in animals, whereas the negative phase two trial of the HDAC6 inhibitor ricolinostat illustrates the translational gap. We therefore argue that future progress will depend on cell-resolved longitudinal multi-omics, causal epigenome editing, human tissue validation, and biomarker studies designed around prespecified clinical utility rather than statistical association alone.

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