Literature DB >> 33063322

Time course of DNA methylation in pain conditions: From experimental models to humans.

Lonnie Møller Johansen1, Maria Carla Gerra2, Lars Arendt-Nielsen2.   

Abstract

BACKGROUND AND
OBJECTIVE: Throughout the last decade, research has uncovered associations between pain and epigenetic alterations caused by environmental factors. Specifically, studies have demonstrated correlations between pain conditions and altered DNA methylation patterns. Thus, DNA methylation has been revealed as a possible modulator or contributor to pain conditions, providing a potential therapeutic target for treatment by DNA methylation modification. To develop such treatments, it is necessary to clarify a wide number of aspects on how DNA methylation affects pain perception; first and foremost, the temporal dynamics. The objective of the present review is to provide an overview of current knowledge on temporal dynamics of DNA methylation in response to pain, and to investigate if a timeframe can be established based on the data of currently published studies. DATABASES AND DATA TREATMENT: PubMed, MEDLINE, Google Scholar and Embase were searched comprehensively for studies of DNA methylation in neuropathic, inflammatory and alternative animal pain models, and in chronic pain patients including Complex Regional Pain Syndrome, chronic postsurgical pain, chronic widespread pain, fibromyalgia and Crohn's disease.
RESULTS: We identified 34 articles highlighting variations in temporal dynamics of DNA methylation across species and between different types of pain. These studies represent a starting point to uncover new insights in the DNA methylation time course in pain.
CONCLUSIONS: No timeframe can currently be made for the DNA methylation response to pain in any of the reviewed conditions, highlighting an important focus area for future research.
© 2020 European Pain Federation - EFIC®.

Entities:  

Year:  2020        PMID: 33063322     DOI: 10.1002/ejp.1674

Source DB:  PubMed          Journal:  Eur J Pain        ISSN: 1090-3801            Impact factor:   3.931


  1 in total

1.  Machine-Learning Analysis of Serum Proteomics in Neuropathic Pain after Nerve Injury in Breast Cancer Surgery Points at Chemokine Signaling via SIRT2 Regulation.

Authors:  Jörn Lötsch; Laura Mustonen; Hanna Harno; Eija Kalso
Journal:  Int J Mol Sci       Date:  2022-03-23       Impact factor: 5.923

  1 in total

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