Background & Aims

Nociplastic pain, a pain without evidence of tissue damage, is observed in conditions like irritable bowel syndrome (IBS), fibromyalgia and complex regional pain syndrome (CRPS). If untreated, non-nociplastic conditions can develop a nociplastic component due to prolonged CNS sensitization – a process thought to be tied to shared neurophysiological mechanisms involving multiple organ systems1-4.

While most research has focused on pain’s temporal transition from acute to chronic, the spatial spread of pain, progressing from one site to multiple body sites, has been commonly seen in nociplastic pain conditions5-8. However, its spatiotemporal dynamics remain largely unexplored. Here, we apply unsupervised machine learning to identify subtype patterns of pain spread. We hypothesize that nociplastic conditions will show distinct spatial spreading compared to non-nociplastic conditions.

Methods

The UK Biobank (UKB) is a comprehensive biomedical database with genetic and health data from 500,000 UK participants over 40 years old9.Of the 167,184 who completed the UKB pain questionnaire, 81,600 individuals with chronic pain rated their pain intensity across 12 sites and reported pain across 19 lateralized body sites10.

To capture the pattern of pain spread, we fitted these data using SuStaIn11, a Subtype and Stage Inference Model. This cutting-edge, unsupervised machine learning algorithm merges disease progression modeling with traditional clustering. It extracts probabilistic spatiotemporal partitioning and classification from cross-validated cross-sectional data12-14. Subtypes were then compared based on their pain spread trajectories, diagnoses, and non-pain symptomatology.

Results

We found that axial subtype exhibited greater odds of nociplastic diagnoses while non-nociplastic greater odds of nociceptive (OR=1.3-2.0). We found nociplastic conditions being predominantly axial from the spine, thorax, pelvic, and head regions.
We identified four different subtypes (S1-4) associated with distinct putative trajectories of pain spread emerging from upper-lower and axial-limb body sites. These trajectories were characterized based on the spread (# pain sites, R2=37-38%) and intensity (pain rating; R2=32-40%) of pain but could also capture the impact of pain (brief pain interference; R2=25-34%).
Each subtypes exhibited varying predominant body sites, combinations of pain diagnoses (nociceptive, neuropathic, and nociplastic), and multi-system symptomatology (e.g., cardiological, respiratory, GI). Across all subtypes, pain spread trajectories were associated with greater signs of neuropathic symptoms localized at their most bothersome pain site (DN4; r=0.23-0.40).

Conclusions

In conclusion, using a data-driven approach, we derive a putative model of chronic pain spread to compare patterns of chronic spread in nociplastic and non-nociplastic conditions. Greater spread of pain exhibited more neuropathic signs with distinct pain diagnoses and complex symptomatology. Understanding these trajectories holds the potential to inform the etiology of chronic pain and provide insights into effective pain management strategies.

References

Referencess
1. Canavero, S., & Bonicalzi, V. Central pain syndrome. Cham: Springer International Publishing (2018).

2. Fitzcharles, M. A., Cohen, S. P., Clauw, D. J., Littlejohn, G., Usui, C., & Häuser, W. Nociplastic pain: towards an understanding of prevalent pain conditions. The Lancet, 397, 2098-2110 (2021).

3. Kosek, E., Clauw, D., Nijs, J., Baron, R., Gilron, I., Harris, R. E., … & Sterling, M. Chronic nociplastic pain affecting the musculoskeletal system: clinical criteria and grading system. Pain, 162, 2629-2634 (2021).

4. Walsh, D. A. Nociplastic pain: helping to explain disconnect between pain and pathology. Pain, 162, 2627-2628 (2021).

5. Apkarian, A. V., Baliki, M. N. & Geha, P. Y. Towards a theory of chronic pain. Progress in Neurobiology, 87, 81-97 (2009).

6. Coghill, R. C. The distributed nociceptive system: a framework for understanding pain. Trends in Neurosciences, 43, 780-794 (2020).

7. Khoury, S., Parisien, M., Thompson, S. J., Vachon-Presseau, E., Roy, M., Martinsen, A. E., … & Diatchenko, L. Genome-wide analysis identifies impaired axonogenesis in chronic overlapping pain conditions. Brain, 145, 1111-1123 (2022).

8. Tanguay-Sabourin, C., Fillingim, M., Guglietti, G. V., Zare, A., Parisien, M., Norman, J., … & Vachon-Presseau, E. A prognostic risk score for development and spread of chronic pain. Nature Medicine, 29, 1821-1831 (2023).

9. Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., … & Marchini, J.The UK Biobank resource with deep phenotyping and genomic data. Nature, 562, 203-209 (2018).

10. Baskozos, G., Hébert, H. L., Pascal, M. M., Themistocleous, A. C., Macfarlane, G. J., Wynick, D., … & Smith, B. H. Epidemiology of neuropathic pain: an analysis of prevalence and associated factors in UK Biobank. Pain Reports, 8, e1066 (2023).

11. Young, A. L., Marinescu, R. V., Oxtoby, N. P., Bocchetta, M., Yong, K., Firth, N. C., … & Alexander, D. C. Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference. Nature Communications, 9, 4273 (2018).

12. Vogel, J. W., Young, A. L., Oxtoby, N. P., Smith, R., Ossenkoppele, R., Strandberg, O. T., … & Hansson, O. Four distinct trajectories of tau deposition identified in Alzheimer’s disease. Nature Medicine, 27, 871-881 (2021).

13. Eshaghi, A., Young, A. L., Wijeratne, P. A., Prados, F., Arnold, D. L., Narayanan, S., … & Ciccarelli, O. Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data. Nature Communications, 12, 2078 (2021).

14. Li, M., Lan, L., Luo, J., Peng, L., Li, X., & Zhou, X. Identifying the Phenotypic and Temporal Heterogeneity of Knee Osteoarthritis: Data From the Osteoarthritis Initiative. Frontiers in Public Health, 9, 726140 (2021).

Presenting Author

Christophe Tanguay-Sabourin

Poster Authors

Christophe Tanguay Sabourin

MSc

University of Montreal

Lead Author

Azin Zare

McGill University

Lead Author

Luda Diatchenko

McGill University

Lead Author

Pierre Rainville

Université de Montréal

Lead Author

E. Vachon-Presseau

McGill University

Lead Author

Topics

  • Specific Pain Conditions/Pain in Specific Populations: Nociplastic and chronic widespread pain