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High-resolution whole-genome DNA methylation revealedunique signatures of painful diabetic neuropathy

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posted on 2025-01-08, 18:28 authored by Katarzyna Malgorzata Kwiatkowska, Paolo Garagnani, Massimiliano Bonafé, Maria G. Bacalini, Claudia Sala, Gastone Castellani, Davide Gentilini, Luciano Calzari, Dan Ziegler, Monique M. Gerrits, Catharina G. Faber, Rayaz A. Malik, Margherita Marchi, Erika Salvi, Giuseppe Lauria, Chiara Pirazzini

The aim of this work was to describe the DNA methylation signature and to identify genes associated with neuropathic pain in type 2 diabetes mellitus.

We analyzed two independent diabetic neuropathy cohorts: PROPGER consisting of 72 painful and 67 painless patients recruited at the German Diabetes Center in Düsseldorf (DE), and PROPENG comprising 27 painful and 65 painless diabetic neuropathy patients recruited at the University of Manchester (UK). Genome-wide methylation data was generated using Illumina Infinium Methylation EPIC v1.0 BeadChip. We used four different selection criteria to identify promising pain-related genes.

Our findings revealed significant differences in methylation patterns between painful and painless diabetic neuropathy and identified a set of individual CpG sites of unique candidate genes associated with the painful phenotype. Several of these genes, including GCH1, MYT1L and MED16, have been previously linked to pain-related phenotypes or diabetes. Through pathway enrichment analysis, we demonstrated that specific epigenetic signatures could contribute to the complex phenotype of diabetic neuropathy and cluster analyses highlighted significant epigenetic dissimilarities between painful and painless phenotypes.

Our results uncovered epigenetic differences between painful and painless diabetic neuropathy patients and identified targeted genes linked to neuropathic pain through DNA methylation mechanisms. This approach holds promise for investigating other chronic pain conditions, such as secondary chronic pain from cancer treatment, thoracic surgery, and various transplant settings.

Funding

This work was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 721841 PainNET and the Italian Ministry of Health (RRC).

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