Background

Oligodendrocyte progenitor cells (OPCs) and mature oligodendrocytes are both lost in central nervous system injury and disease. Activated microglia may play a role in OPC and oligodendrocyte loss or replacement, but it is not clear how the responses of OPCs and oligodendrocytes to activated microglia differ.

Methods

OPCs and microglia were isolated from rat cortex. OPCs were induced to differentiate into oligodendrocytes with thyroid hormone in defined medium. For selected experiments, microglia were added to OPC or oligodendrocyte cultures. Lipopolysaccharide was used to activate microglia and microglial activation was confirmed by TNFalpha ELISA. Cell survival was assessed with immunocytochemistry and cell counts. OPC proliferation and oligodendrocyte apoptosis were also assessed.

Results

OPCs and oligodendrocytes displayed phenotypes representative of immature and mature oligodendrocytes, respectively. Activated microglia reduced OPC survival, but increased survival and reduced apoptosis of mature oligodendrocytes. Activated microglia also underwent cell death themselves.

Conclusion

Activated microglia may have divergent effects on OPCs and mature oligodendrocytes, reducing OPC survival and increasing mature oligodendrocyte survival. This may be of importance because activated microglia are present in several disease states where both OPCs and mature oligodendrocytes are also reacting to injury. Activated microglia may simultaneously have deleterious and helpful effects on different cells after central nervous system injury.

Data-driven discovery in complex neurological disorders has potential to extract meaningful syndromic knowledge from large, heterogeneous data sets to enhance potential for precision medicine. Here we describe the application of topological data analysis (TDA) for data-driven discovery in preclinical traumatic brain injury (TBI) and spinal cord injury (SCI) data sets mined from the Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI) repository. Through direct visualization of inter-related histopathological, functional and health outcomes, TDA detected novel patterns across the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI. TDA also revealed that perioperative hypertension predicted long-term recovery better than any tested drug after thoracic SCI in rats. TDA-based data-driven discovery has great potential application for decision-support for basic research and clinical problems such as outcome assessment, neurocritical care, treatment planning and rapid, precision-diagnosis.