• Eur J Pain · May 2018

    Machine-learned analysis of quantitative sensory testing responses to noxious cold stimulation in healthy subjects.

    • I Weyer-Menkhoff, M C Thrun, and J Lötsch.
    • Institute of Clinical Pharmacology, Goethe - University, Frankfurt am Main, Germany.
    • Eur J Pain. 2018 May 1; 22 (5): 862-874.

    BackgroundPain in response to noxious cold has a complex molecular background probably involving several types of sensors. A recent observation has been the multimodal distribution of human cold pain thresholds. This study aimed at analysing reproducibility and stability of this observation and further exploration of data patterns supporting a complex background.MethodPain thresholds to noxious cold stimuli (range 32-0 °C, tonic: temperature decrease -1 °C/s, phasic: temperature decrease -8 °C/s) were acquired in 148 healthy volunteers. The probability density distribution was analysed using machine-learning derived methods implemented as Gaussian mixture modeling (GMM), emergent self-organizing maps and self-organizing swarms of data agents.ResultsThe probability density function of pain responses was trimodal (mean thresholds at 25.9, 18.4 and 8.0 °C for tonic and 24.5, 18.1 and 7.5 °C for phasic stimuli). Subjects' association with Gaussian modes was consistent between both types of stimuli (weighted Cohen's κ = 0.91). Patterns emerging in self-organizing neuronal maps and swarms could be associated with different trends towards decreasing cold pain sensitivity in different Gaussian modes. On self-organizing maps, the third Gaussian mode emerged as particularly distinct.ConclusionThresholds at, roughly, 25 and 18 °C agree with known working temperatures of TRPM8 and TRPA1 ion channels, respectively, and hint at relative local dominance of either channel in respective subjects. Data patterns suggest involvement of further distinct mechanisms in cold pain perception at lower temperatures. Findings support data science approaches to identify biologically plausible hints at complex molecular mechanisms underlying human pain phenotypes.SignificanceSensitivity to pain is heterogeneous. Data-driven computational research approaches allow the identification of subgroups of subjects with a distinct pattern of sensitivity to cold stimuli. The subgroups are reproducible with different types of noxious cold stimuli. Subgroups show pattern that hints at distinct and inter-individually different types of the underlying molecular background.© 2018 European Pain Federation - EFIC®.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…