Spinal cord injury (SCI) remains a major unmet medical challenge, often resulting in permanent paralysis and disability with no effective treatments. Now, researchers at University of California San Diego School of Medicine have harnessed bioinformatics to fast-track the discovery of a promising new drug for SCI. The results will also make it easier for researchers around the world to translate their discoveries into treatments. The findings are published in the journal Nature.

One of the reasons SCI results in permanent disability is that the neurons that form our brain and spinal cord cannot effectively regenerate. Encouraging neurons to regenerate with drugs offers a promising possibility for treating these severe injuries.

The researchers found that under specific experimental conditions, some mouse neurons activate a specific pattern of genes related to neuronal growth and regeneration. To translate this fundamental discovery into a treatment, the researchers used data-driven bioinformatics approaches to compare their pattern to a vast database of compounds, looking for drugs that could activate these same genes and trigger neurons to regenerate.

A recent study led by Tiffany Schmidt, Ph.D., associate professor of Ophthalmology and of Neurobiology in the Weinberg College of Arts and Sciences, has discovered previously unknown cellular mechanisms that shape neuron identity in retinal cells, findings that may improve the understanding of brain circuitry and disease. The study is published in Nature Communications.

Schmidt’s laboratory studies melanopsin-expressing, intrinsically photosensitive retinal ganglion cells (ipRGCs), a type of neuron in the retina that plays a key role in synchronizing the body’s internal clock to the daily light/dark cycle.

There are six subtypes of ipRGCs—M1 to M6—and each expresses a different amount of the protein melanopsin, which makes the ipRGCs directly sensitive to light. However, the mechanisms which give rise to each ipRGCs subtype’s unique structural and functional features have previously remained elusive.

Previous studies suggest that individual differences in intelligence correlate with circuit complexity and dendritic arborization in the brain. Here the authors use NODDI, a diffusion MRI technique, to confirm that neurite density and arborization are inversely related to measures of intelligence.