4.5 Article

Inter-Individual Differences Explain More Variance in Conditioned Pain Modulation Than Age, Sex and Conditioning Stimulus Intensity Combined

Journal

BRAIN SCIENCES
Volume 11, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/brainsci11091186

Keywords

conditioned pain modulation; endogenous analgesia; conditioning stimulus; interindividual factors; CPM variability

Categories

Funding

  1. German Research Association (DFG) [RTG2175]
  2. Graduate School of Systemic Neurosciences

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Individual differences account for a significant portion of variance in CPM compared to age, sex, and CS intensity. This suggests that predictive capability of commonly considered factors may be limited and future models should take into account individual differences.
Conditioned pain modulation (CPM) describes the reduction in pain evoked by a test stimulus (TS) when presented together with a heterotopic painful conditioning stimulus (CS). CPM has been proposed to reflect inter-individual differences in endogenous pain modulation, which may predict susceptibility for acute and chronic pain. Here, we aimed to estimate the relative variance in CPM explained by inter-individual differences compared to age, sex, and CS physical and pain intensity. We constructed linear and mixed effect models on pooled data from 171 participants of several studies, of which 97 had repeated measures. Cross-sectional analyses showed no significant effect of age, sex or CS intensity. Repeated measures analyses revealed a significant effect of CS physical intensity (p = 0.002) but not CS pain intensity (p = 0.159). Variance decomposition showed that inter-individual differences accounted for 24% to 34% of the variance in CPM while age, sex, and CS intensity together explained <3% to 12%. In conclusion, the variance in CPM explained by inter-individual differences largely exceeds that of commonly considered factors such as age, sex and CS intensity. This may explain why predictive capability of these factors has had conflicting results and suggests that future models investigating them should account for inter-individual differences.

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