Background & Aims

The single nucleotide polymorphism (SNP) rs4680 in the catechol-O-methyltransferase gene (COMT) is the most commonly analyzed in the context of pain [1]. It is a missense variant causing the substitution of the amino acid valine for methionine at codon 158 (Val158Met) and it is associated with altered activity of the COMT enzyme involved in different functions in the pain pathways [2]. However, there are controversial results on this SNP in patients with the painful fibromyalgia (FM) syndrome, probably because the data collected so far are highly heterogeneous and show several discrepancies: sample with small size, the use of old diagnostic criteria for recruitment, and lack of control of additional comorbidities. This study aims to investigate the possible role of the SNP rs4680 in the symptomatology of FM in more stratified groups of FM patients.

Methods

The SNP rs4680 was analyzed using Taq-Man Genotyping Assays in a sample of 294 FM patients and 209 healthy controls, excluding patients with comorbidities and controls with chronic pain. All participants were subjected to a complete phenotype characterization, questionnaires, and a systematic clinical interview. The genotypic distribution of FM patients was also analyzed regarding pain intensity. Finally, since dopamine system dysfunction has been associated with both depression symptoms and sleep problems [3,4], the concurrent impact of depression and sleep impairment on FM risk was also tested.

Results

At the allelic level, significant differences were observed: the prevalence of the G allele was notably higher in the FM group in contrast to the control group (p = 0.037). Additionally, logistic regression analysis revealed that individuals with the GG genotype (Val/Val) have a 2 times higher risk of having FM compared to those with the AA genotype (p = 0.038). Conversely, the presence of depression and sleep impairment escalated the risk by 12 and 8 times, respectively (p < 0.001). Age was reaffirmed as a significant factor associated with the disease. Furthermore, examining only the FM patients group, the AA (Met/Met) homozygous genotype was significantly linked to severe pain intensity (p = 0.007).

Conclusions

Previous studies have found a higher prevalence of the G/Val allele in FM patients and that the COMT enzyme related to the GG genotype breaks down dopamine faster than the AA-related form [2,5], suggesting a link between dopaminergic dysfunction and vulnerability to develop chronic pain. Further studies should explore the SNP Val158Met in FM patients in conjunction with COMT enzymatic activity, and their role in pain and other symptoms connected with the dopaminergic system as depression or sleep impairment.

References

[1] Vetterlein, A., Monzel, M. & Reuter, M. Are catechol-O-methyltransferase gene polymorphisms genetic markers for pain sensitivity after all? – A review and meta-analysis. Neurosci Biobehav Rev 148, 105112 (2023).
[2] Chen, J. et al. Functional analysis of genetic variation in catechol-O-methyltransferase (COMT): effects on mRNA, protein, and enzyme activity in postmortem human brain. Am J Hum Genet 75, 807–821 (2004).
[3] Dauvilliers, Y., Tafti, M. & Landolt, H. P. Catechol-O-methyltransferase, dopamine, and sleep-wake regulation. Sleep Med Rev 22, 47–53 (2015).
[4] Klein, M., Schmoeger, M., Kasper, S. & Schosser, A. Meta-analysis of the COMT Val158Met polymorphism in major depressive disorder: the role of gender. World J Biol Psychiatry 17, 147–158 (2016).
[5] Lotta, T. et al. Kinetics of human soluble and membrane-bound catechol O-methyltransferase: a revised mechanism and description of the thermolabile variant of the enzyme. Biochemistry 34, 4202–4210 (1995).

Presenting Author

Maria Carla Gerra

Poster Authors

Maria Carla Gerra, Ph.D.

Ph.D.

Universitá di Parma

Lead Author

E-mail

Cristina Dallabona

Ph.D.

Universitá di Parma

Lead Author

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Matteo Manfredini

Ph.D.

University of Parma

Lead Author

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Rocco Giordano

Center for Neuroplasticity and Pain, HST, Faculty of Medicine, Aalborg University, Aalborg, DK

Lead Author

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Camilla Capritotti

M.Sc.

Aalborg University

Lead Author

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Alberto González-Villar

Ph.D.

University of Minho

Lead Author

E-mail

Yolanda Triñanes

Ph.D.

University of Santiago de Compostela

Lead Author

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Lars Arendt-Nielsen

PhD

Aalborg University

Lead Author

E-mail

Maria Teresa Carrillo-de-la-Peña

Ph.D.

University of Santiago de Compostela

Lead Author

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Topics

  • Genetics