Background & Aims

It is now well established that the brain is key in the development and maintenance of chronic pain. However, brain imaging studies have reported a variety of sometimes conflicting findings, largely due to the inclusion of small and heterogeneous datasets. Inspired by the vision and success of the Enhancing NeuroImaging Genetics through Meta-Analyses (ENIGMA) consortium [1], the Chronic Pain working group was established in November 2022. This working group aims to bring together chronic pain research groups to mutualise neuroimaging and genetic databases towards large-scale studies of brain structure, function, neurophysiology and molecular underpinnings of chronic pain. The ENIGMA-Chronic Pain working group aims to identify brain regions and networks involved in the neurobiology of chronic pain and identify targets for more effective interventions.

Methods

This newly formed ENIGMA working group will use large-scale analyses of neuroimaging data, including T1-weighted magnetic resonance imaging scans (MRI), diffusion-weighted imaging (DWI), and resting-state functional MRI (fMRI), to identify large and subtle brain markers that are common and/or specific to various chronic pain conditions. To reach its aims, the working group will use planned, standardized image processing and statistical analysis protocols, using FreeSurfer to derive measures of cortical thickness [2], surface area, subcortical volumes, FSL TBSS to extract white matter microstructural measures [3], and ENIGMA-HALFpipe [4], based on fmriprep, to process resting state fMRI data.

Results

As of January 2024, the ENIGMA-Chronic Pain working group includes around 30 independent datasets from North America, Europe and Australia, bringing together brain imaging and clinical data from over 1,800 people with chronic pain and over 4,000 matched pain-free individuals, as well as integrating existing large-scale datasets (e.g., United Kingdom Biobank, Adolescent Brain Cognitive Development study). Through this effort, we will establish the largest worldwide brain imaging initiative to identify brain markers of chronic pain. Groups have processed their data using the proposed ENIGMA standardised pipelines, and the first analyses are underway. Future studies may also include electroencephalography (EEG), task-based fMRI, magnetic resonance spectroscopy (MRS), as well as studies across the lifespan and studies investigating the relationship with mental health and addiction.

Conclusions

The ENIGMA-Chronic Pain working group is establishing a platform for large-scale international collaborative efforts aiming to understand the aetiology of and identify brain phenotypes associated with chronic pain conditions. In collaboration with other ENIGMA working groups, we aim to understand the role and impact of comorbid conditions, including but not limited to, anxiety disorders, depressive disorders, posttraumatic stress disorder, addiction or traumatic brain injury. The ENIGMA-Chronic Pain working group looks forward to welcoming new partners, interested in expanding this largest international collaborative effort to understand the brain markers of chronic pain conditions.

References

[1] Thompson, P.M., et al., ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries. Transl Psychiatry, 2020. 10(1): p. 100
[2] Fischl, B., et al., Automatically parcellating the human cerebral cortex. Cereb Cortex, 2004. 14(1): p. 11-22
[3] Smith, S.M., et al., Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage, 2006. 31(4): p. 1487-505
[4] Waller, L., et al., ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting-state and task-based fMRI data. Hum Brain Mapp, 2022. 43(9): p. 2727-2742.

Presenting Author

Yann Quide

Poster Authors

Yann Quidé

PhD

UNSW Sydney

Lead Author

E-mail

Neda Jahanshad

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, USC, USA

Lead Author

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Sophia Thomopoulos

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, USC, USA

Lead Author

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Paul Thompson

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, USC, USA

Lead Author

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Sylvia Gustin

UNSW

Lead Author

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Topics

  • Pain Imaging