Descending control of pain

Introduction

Pain is a large societal and health problem. Although often thought of as an invariant representation of active nociceptors, pain varies a lot under the influence of different affective states, sometimes with near complete analgesia. Such modulation of pain is thought to occur through a descending pathway originating in the brain and to be executed by Rostral Ventromedial Medulla (RVM) neurons that project to the spinal cord.

Challenges in Understanding Pain

Deciphering the complexity of the cell types involved and how they contribute to the descending control of pain has been challenging. However, recent advances in single-cell omics, computational biology, and advanced genetic technologies now open the door for unbiased system-wide insights.

Project Overview

DescendPain will uncover the power of the brain to control pain. We will classify RVM neuron types by single-cell RNA-sequencing and use scRNAseq-based stimulus-to-cell-type mapping to identify neuronal ensembles conferring analgesia and hyperalgesia during:

1. Morphine
2. Naloxone
3. Stress
4. Sleep-deprivation
5. Exercise

Methodology

Using activity-based mouse genetics, we will reveal the full complexity of the combinations of neurons engaged and unravel their role in pain modulation. This will allow us to identify for the first time the cellular basis for how affective states modulate pain.

We will also use novel intersectional strategies for dual capturing of active neurons to determine how the descending RVM controls the transmission of pain in the ascending pathway of the spinal cord.

Chronic Pain Investigation

Finally, we will identify the memory substrate underlying chronic pain, providing evidence for the existence of RVM neuron ensembles of chronic pain and revealing underlying cellular and molecular mechanisms.

Conclusion

This project takes a new system-wide strategy in the pain field that should fundamentally change the view of pain. It will provide a cellular basis for how pain is continuously scaled by mental states and uncover mechanisms of chronic pain, which may provide strategies for designing effective pain therapies.