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. 2022 Apr 29;145(3):1098-1110.
doi: 10.1093/brain/awab336.

Neuroimmune signatures in chronic low back pain subtypes

Affiliations

Neuroimmune signatures in chronic low back pain subtypes

Zeynab Alshelh et al. Brain. .

Abstract

We recently showed that patients with different chronic pain conditions (such as chronic low back pain, fibromyalgia, migraine and Gulf War illness) demonstrated elevated brain and/or spinal cord levels of the glial marker 18-kDa translocator protein (TSPO), which suggests that neuroinflammation might be a pervasive phenomenon observable across multiple aetiologically heterogeneous pain disorders. Interestingly, the spatial distribution of this neuroinflammatory signal appears to exhibit a degree of disease specificity (e.g. with respect to the involvement of the primary somatosensory cortex), suggesting that different pain conditions may exhibit distinct 'neuroinflammatory signatures'. To explore this hypothesis further, we tested whether neuroinflammatory signal can characterize putative aetiological subtypes of chronic low back pain patients based on clinical presentation. Specifically, we explored neuroinflammation in patients whose chronic low back pain either did or did not radiate to the leg (i.e. 'radicular' versus 'axial' back pain). Fifty-four patients with chronic low back pain, 26 with axial back pain [43.7 ± 16.6 years old (mean ± SD)] and 28 with radicular back pain (48.3 ± 13.2 years old), underwent PET/MRI with 11C-PBR28, a second-generation radioligand for TSPO. 11C-PBR28 signal was quantified using standardized uptake values ratio (validated against volume of distribution ratio; n = 23). Functional MRI data were collected simultaneously to the 11C-PBR28 data (i) to functionally localize the primary somatosensory cortex back and leg subregions; and (ii) to perform functional connectivity analyses (in order to investigate possible neurophysiological correlations of the neuroinflammatory signal). PET and functional MRI measures were compared across groups, cross-correlated with one another and with the severity of 'fibromyalgianess' (i.e. the degree of pain centralization, or 'nociplastic pain'). Furthermore, statistical mediation models were used to explore possible causal relationships between these three variables. For the primary somatosensory cortex representation of back/leg, 11C-PBR28 PET signal and functional connectivity to the thalamus were: (i) higher in radicular compared to axial back pain patients; (ii) positively correlated with each other; (iii) positively correlated with fibromyalgianess scores, across groups; and finally (iv) fibromyalgianess mediated the association between 11C-PBR28 PET signal and primary somatosensory cortex-thalamus connectivity across groups. Our findings support the existence of 'neuroinflammatory signatures' that are accompanied by neurophysiological changes and correlate with clinical presentation (in particular, with the degree of nociplastic pain) in chronic pain patients. These signatures may contribute to the subtyping of distinct pain syndromes and also provide information about interindividual variability in neuroimmune brain signals, within diagnostic groups, that could eventually serve as targets for mechanism-based precision medicine approaches.

Keywords: chronic pain; functional connectivity; glial cells; inflammation; neuropathic.

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Figures

Figure 1
Figure 1
Region of interest analyses. Group differences in 11C-PBR28 signal in a priori regions of interest. A priori regions were selected as they demonstrated 11C-PBR28 PET SUVR elevations in chronic low back pain patients compared to healthy controls. Average ± SD SUVR extracted showing differences between cLBPRAD and cLBPAX (adjusted for scanner and genotype). *Significant difference between groups (P < 0.05). Triangle denotes data from Protocol 1, circle denotes data from Protocol 2. The range of the y-axis is set depending on the distribution of individual data-points.
Figure 2
Figure 2
Voxel-wise group differences in 11C-PBR28 signal. (A) Maps displaying areas with significantly elevated 11C-PBR28 SUVR in cLBPRAD compared to cLBPAX in a voxelwise analysis, adjusted for protocol and genotype. (B) Average ± SD SUVR extracted from several clusters identified as statistically significant in the voxelwise SUVR analysis from A (adjusted for scanner and genotype). The range of the y-axis is set depending on the distribution of individual data-points. (C) BOLD functional MRI localizing the somatotopic representation of S1 area for the Back+Leg and the overlap between Back+Leg e-stim and 11C-PBR28 SUVR signal in cLBPRAD > cLBPAX. IPS = intraparietal sulcus; PCC = posterior cingulate cortex; WM = white matter. Triangle denotes data from Protocol 1, circle denotes data from Protocol 2.
Figure 3
Figure 3
Thalamic voxelwise group difference in connectivity with S1. (A) Volumetric maps displaying areas within the thalamus with significantly elevated connectivity with S1 (seed region of interest displayed on top left in green) in cLBPRAD compared to cLBPAX in a thalamic specific voxelwise analysis. (B) Average ± SD connectivity scores extracted from statistically significant cluster in the voxelwise connectivity analysis from A. Triangle denotes data from Protocol 1, circle denotes data from Protocol 2. Data adjusted for protocol. The range of the y-axis is set depending on the distribution of individual data-points. VLp = ventral lateral posterior nucleus; VPL = ventral posterior lateral nucleus.
Figure 4
Figure 4
S1 11C-PBR28 signal correlates with S1-thalamus connectivity. The 11C-PBR28 SUVR signal was extracted from the S1 cluster that was significant in the PET group comparisons (Fig. 2). Connectivity scores were extracted from the thalamic cluster that was significant in the S1 connectivity analyses (Fig. 3). All data have been adjusted for protocol and genotype. Triangle denotes data from Protocol 1, circle denotes data from Protocol 2. The range of the y-axis is set depending on the distribution of individual data-points.
Figure 5
Figure 5
11C-PBR28 signal in the S1 and S1-thalamus connectivity correlations with Fibromyalgia Survey Scores. Top: Average SUVR was extracted from S1 (see Fig. 4 caption) and plotted against Fibromyalgia Survey Scores (data have been adjusted for scanner and genotype). Bottom: S1-thalamus connectivity values were extracted (see Fig. 4 caption) and plotted against Fibromyalgia Survey Scores (data have been adjusted for scanner). Triangle denotes data from Protocol 1, circle denotes data from Protocol 2. The range of the y-axis is set depending on the distribution of individual data-points.
Figure 6
Figure 6
Fibromyalgia Survey Scores mediate the relationship between S1-thalamus connectivity and S1 11C-PBR28 signal. A bootstrapped mediation analysis revealed that Fibromyalgia Survey Scores significantly mediated the relationship between S1-thalamus connectivity and S1 11C-PBR28 signal. Values within parentheses represent bootstrap standard errors for each path. *P < 0.05; **P < 0.01.

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