Background & Aims
Alterations in salience and default mode networks have been reported in individuals with chronic pain [1,2]. The cingulate cortex plays a critical role in several facets of pain processing and is an integral component of both the saliency and default mode network. From a biochemical perspective, anterior-posterior variations in resting excitatory activity have been reported in the cingulate cortex using multi-single voxel magnetic resonance spectroscopy (MRS) [3]. In how far regional variabilities in metabolite levels, morphology, and metabolism across the cingulate cortex are related to inter-individual differences in pain sensitivity remains unclear. The aim of this study was to adopt a multimodal approach to identify the influence of biochemical, functional, and structural characteristics across the cingulate cortex on individual sensitivity to pain.
Methods
Forty-eight healthy individuals (25f; age 27.6±6.4 yrs) underwent 4×20 noxious laser stimuli (2.75, 3.0, 3.25, 3.5J) applied to the right volar forearm and rated each stimulus on a numeric rating scale (NRS: 0-no pain to 10-worst pain imaginable). All individuals underwent an MRS scan at 3T (sLASER; TE/TR = 21/5000ms) to estimate glutamate levels (Glu) in the anterior (ACC), anterior-mid (aMCC), posterior-mid (pMCC) and posterior cingulate cortices (PCC). In all 4 regions, cerebral blood flow (CBF) was assessed using arterial spin labelling and cortical thickness (CT) was measured from 3D T1w images (MP-RAGE; TE/TR = 4.33/9.296). Brain temperature (TB) was estimated by calculating the chemical shift difference between water and N-acetylaspartate for each voxel. K-means clustering was performed to identify clusters of pain sensitivity. A data-driven feature selection approach [FilterVarImp() in R] was used to identify variables most associated with pain sensitivity followed by a Lasso regression [glmnet() in R] to determine the effect of each variable on pain sensitivity.
Results
K-means clustering identified two clusters of pain sensitivity: high (NRS 4.9±1.1, n=30) and low sensitivity (NRS 2.5±0.8; n=18). Preliminary analyses revealed two variables with high importance (>0.6): TB-PCC, Glu-ACC, CT-ACC. In a multi-variable model, Glu-ACC was the only variable associated with pain sensitivity (estimate = 0.13), with higher pain related to higher Glu-ACC levels (12.48±2.46 mM) compared to low pain (10.93±2.23 mM).
Conclusions
This study identified metabolite activity as an important characteristic of the cingulate cortex influencing pain sensitivity. Glutamate levels in the ACC explained most of the variability in laser pain sensitivity, whereas glutamate levels in more posterior areas are less associated with pain sensitivity in this cohort. These findings suggest that glutamate in the ACC, as a proxy of activity in the saliency network, has a stronger influence on pain sensitivity than activity in more posterior cingulate areas. Glutamate in the PCC, as a proxy of activity in the default mode network, may be less relevant in this regard.
References
1. Borsook, D., Edwards, R., Elman, I., Becerra, L., and Levine, J. (2013). Pain and analgesia: The value of salience circuits. Preprint, 10.1016/j.pneurobio.2013.02.003 10.1016/j.pneurobio.2013.02.003.
2. Baliki, M.N., Mansour, A.R., Baria, A.T., and Apkarian, A.V. (2014). Functional reorganization of the default mode network across chronic pain conditions. PLoS One 9. 10.1371/journal.pone.0106133.
3. Dou, W., Palomero-Gallagher, N., van Tol, M.J., Kaufmann, J., Zhong, K., Bernstein, H.G., Heinze, H.J., Speck, O., and Walter, M. (2013). Systematic regional variations of GABA, glutamine, and glutamate concentrations follow receptor fingerprints of human cingulate cortex. Journal of Neuroscience 33, 12698–12704. 10.1523/JNEUROSCI.1758-13.2013.
Presenting Author
Paulina S Scheuren
Poster Authors
Paulina Scheuren
PhD
University of British Columbia
Lead Author
Cassandra Choles
MSc
International Collaboration on Repair Discoveries, University of British Columbia
Lead Author
Oscar Ortiz
International Collaboration on Repair Discoveries, University of British Columbia
Lead Author
Jessica Archibald
PhD
Weill Cornell Medicine
Lead Author
John LK Kramer
International Collaboration on Repair Discoveries, University of British Columbia
Lead Author
Topics
- Pain Imaging