Abstract
Useful animal models of disease in neuroscience can make accurate predictions about a therapeutic outcome, a feature known as predictive validity. In this issue of the JCI, Knowland et al. provide an improved model to assess nicotinic acetylcholine receptor (nAChR) ligands for treating chronic pain. The authors identify two proteins, the voltage-dependent calcium channel auxiliary subunit BARP and the unfolded protein response sensor IRE1α, that are required for robust heterologous expression of α6β4, an nAChR subtype in dorsal root ganglia (DRG). This nAChR is a candidate for the analgesic effects of nicotine as well as the frog toxin epibatidine. Now researchers can efficiently screen for α6β4 nAChR-selective agonists using heterologous expression systems. Candidates that emerge will enable researchers to test the predictive validity of mouse models for chronic pain in the nAChR context. If all these steps work, one can envision a class of non-opioid nAChR-targeted analgesics for chronic pain.