TLR 2 and 4 responsiveness from isolated peripheral blood mononuclear cells from rats and humans as potential chronic pain biomarkers

Background: Chronic pain patients have increased peripheral blood mononuclear cell Interkeukin-1β production following TLR2 and TLR4 simulation. Here we have used a human-to-rat and rat-to-human approach to further investigate whether peripheral blood immune responses to TLR agonists might be suitable for development as possible systems biomarkers of chronic pain in humans. Methods and Results: Study 1: using a graded model of chronic constriction injury in rats, behavioral allodynia was assessed followed by in vitro quantification of TLR2 and TLR4 agonist-induced stimulation of IL-1β release by PBMCs and spinal cord tissues (n = 42; 6 rats per group). Statistical models were subsequently developed using the IL-1β responses, which distinguished the pain/no pain states and predicted the degree of allodynia. Study 2: the rat-derived statistical models were tested to assess their predictive utility in determining the pain status of a published human cohort that consists of a heterogeneous clinical pain population (n = 19) and a pain-free population (n = 11). The predictive ability of one of the rat models was able to distinguish pain patients from controls with a ROC AUC of 0.94. The rat model was used to predict the presence of pain in a new chronic pain cohort and was able to accurately predict the presence of pain in 28 out of the 34 chronic pain participants. Conclusions: These clinical findings confirm our previous discoveries of the involvement of the peripheral immune system in chronic pain. Given that these findings are reflected in the prospective graded rat data, it suggests that the TLR response from peripheral blood and spinal cord were related to pain and these clinical findings do indeed act as system biomarkers for the chronic pain state. Hence, they provide additional impetus to the neuroimmune interaction to be a drug target for chronic pain.Yuen H. Kwok, Jonathan Tuke, Lauren L. Nicotra, Peter M. Grace, Paul E. Rolan, Mark R. Hutchinso

Summary of variables collected from rats post CCI in the central region.

<p>Summary of variables collected from rats post CCI in the central region.</p

Summary of variables collected from rats post CCI in the periphery region.

<p>Summary of variables collected from rats post CCI in the periphery region.</p

Summary of variables collected from humans in the periphery region.

<p>Summary of variables collected from humans in the periphery region.</p

Representation of the constructed models Model rat, Model rat to human and Model human that predicted the presence of pain in the expanded cohort.

<p>Bin center 0 represents no pain and 1 represents pain.</p

Best-fit logistic regression model results for the prediction of the pain severity in rats post CCI in neuronal and subcutaneous experimental groups.

<p>Best-fit logistic regression model results for the prediction of the pain severity in rats post CCI in neuronal and subcutaneous experimental groups.</p

Representation of ROC curves for the detection of pain presence.

<p>Models generated from (A) rat data and (B) human data obtained from peripheral collected output variables.</p

Best-fit logistic regression model results for the prediction of the pain severity in rats post CCI in neuronal experimental groups.

<p>Best-fit logistic regression model results for the prediction of the pain severity in rats post CCI in neuronal experimental groups.</p

Best-fit logistic regression model results for the prediction of pain for rats post CCI.

<p>Best-fit logistic regression model results for the prediction of pain for rats post CCI.</p

Allodynia quantification at day of cull (At least postoperative day 18).

<p>Graded neuropathy was induced by varying the number of chromic gut pieces ligating the nerve (N) and/or distributed in the subcutaneous (S) compartments. The treatment groups were N0S0, N0S4, N1S0, N1S3, N2S0, N2S2 and N4S0 (n = 6/group). At baseline all rats responded very similarly and was not included in the statistical analysis. A significant group effect was observed at day of cull (<i>P</i><0.0001) and with some of the experimental groups (*<i>P</i> = 0.03, N0S0 vs. N1S3; **<i>P</i> = 0.0002, N0S0 vs. N2S0, N0S0 vs. N2S2, N0S0 vs. N4S0; #<i>P</i> = 0.02, N0S4 vs. N2S0, N0S4 vs. N2S2, N0S4 vs. N4S4). Error bars on graphs represent standard error of the mean and significance is set at <i>P</i><0.05.</p