Plasma proteomic analysis on neuropathic pain in idiopathic peripheral neuropathy patients

Abstract

Background and Aims

Why only half of the idiopathic peripheral neuropathy (IPN) patients develop neuropathic pain remains unknown. By conducting a proteomics analysis on IPN patients, we aimed to discover proteins and new pathways that are associated with neuropathic pain.

Methods

We conducted unbiased mass-spectrometry proteomics analysis on blood plasma from 31 IPN patients with severe neuropathic pain and 29 IPN patients with no pain, to investigate protein biomarkers and protein–protein interactions associated with neuropathic pain. Univariate modeling was done with linear mixed modeling (LMM) and corrected for multiple testing. Multivariate modeling was performed using elastic net analysis and validated with internal cross-validation and bootstrapping.

Results

In the univariate analysis, 73 proteins showed a p-value <.05 and 12 proteins showed a p-value <.01. None were significant after Benjamini–Hochberg adjustment for multiple testing. Elastic net analysis created a model containing 12 proteins with reasonable discriminatory power to differentiate between painful and painless IPN (false-negative rate 0.10, false-positive rate 0.18, and an area under the curve 0.75). Eight of these 12 proteins were clustered into one interaction network, significantly enriched for the complement and coagulation pathway (Benjamini–Hochberg adjusted p-value = .0057), with complement component 3 (C3) as the central node. Bootstrap validation identified insulin-like growth factor-binding protein 2 (IGFBP2), complement factor H-related protein 4 (CFHR4), and ferritin light chain (FTL), as the most discriminatory proteins of the original 12 identified.

Interpretation

This proteomics analysis suggests a role for the complement system in neuropathic pain in IPN.