Ion Channels in Perinatal Asphyxia: Understanding the Pathology to Improve Treatment

Perinatal asphyxia often leads to serious health complications and cognitive impairment and is a significant contributor to neonatal mortality. The current treatments for perinatal asphyxia are limited and therefore it is important that we understand the pathology that results from hypoxia at birth and how we can minimise damage and promote regeneration.

Oligodendrocyte precursor cells (OPCs) and oligodendrocytes are particularly susceptible to reduced energy availability. During hypoxia, a rise in glutamate excitotoxicity is thought to preferentially damage oligodendrocyte lineage cells. However, recent work from the Hamilton lab indicates that when glutamate concentrations rise, this occurs alongside changes in local potassium concentrations which lead to activation of TRP channels on oligodendrocyte lineage cells that allow harmful calcium into the cells that trigger cell death.

The work so far has focused on mature oligodendrocytes, but whether OPCs or oligodendrocytes differentiating and myelinating perinatally are also susceptible to TRP channel mediated cell death during perinatal hypoxia is unknown. Here, I will determine whether TRP channels are activated during a rodent model of perinatal hypoxia and whether TRP channel block can prevent neurodegeneration and promote remyelination.

The aim of this investigation is to use electrophysiology (compound action potential recording and patch-clamping) and calcium imaging techniques to investigate how OPCs and oligodendrocytes die during hypoxia. When mechanisms are discovered we will then test how blocking candidate mechanisms affects cell damage caused in a rodent model of perinatal asphyxia.

There is growing concern about the reproducibility of data. To overcome this problem, I will do the following: (1) Blind myself to the experimental conditions where possible, by changing labels, hiding genotypes and using image blinding generators in ImageJ for instance, to remove bias; (2) Make sure that the sample sizes have statistical power >80% (p