By YOHAN J. JOHN | Kempner Institute Research

3 min read

A series of irregularly spiky, black horizontal lines on a white background
An EEG recording of the brain captures a seizure in a person with epilepsy. Image: iStock/Getty Images Plus

At a glance:

  • Researchers are combining a sophisticated genetic technique with a new desktop supercomputer to study 6,000 genetic mutations that may contribute to epilepsy.

  • Findings could shed light on how genetic alterations drive neuronal changes that cause the disease.

  • This information could someday help scientists identify new drug targets for epilepsy.

Researchers at Harvard Medical School and the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University have launched a new project to uncover how genetic mutations in the brain give rise to epilepsy.

The project combines a pioneering genetic technique developed at HMS with a compact desktop supercomputer, allowing the team to quickly and efficiently analyze thousands of mutations that may be involved in the disease.

Get more HMS news

Studying how these mutations alter the structure and function of neurons in the brain could provide new insights into the role of genetic variation in epilepsy. Eventually, this information may help scientists identify new treatment targets for the disease.

A new window into the brain

Epilepsy is marked by seizures caused by overactivity of brain circuits. The neurons that make up these brain circuits generally fall into two categories: excitatory and inhibitory. Excitatory neurons increase the activity of other neurons, while inhibitory neurons suppress it. Seizures are thought to emerge when this delicate balance is disrupted.

Understanding how certain genetic mutations cause neurons to become hyperactive is critical to explaining why seizures occur. Yet mutations in inhibitory neurons often present a paradox.

Promo to Earn a Master's degree from Harvard Medical School. Applications are now open, apply today

“You’d think that they would make the brain less active, right?” said Bernardo Sabatini, the Alice and Rodman W. Moorhead III Professor of Neurobiology in the Blavatnik Institute at HMS and co-director of the Kempner Institute. But in many cases, the opposite occurs: Increased activity in inhibitory neurons co-occurs with overactivity in brain circuits.

“We need a combination of experimental data and simulations to resolve this counterintuitive phenomenon,” Sabatini said. He is co-leading the project with Beth Stevens, HMS associate professor of neurology at Boston Children’s Hospital.

The researchers recently developed a transformative technique that allows them to introduce a different single genetic mutation into thousands of individual cells in the brain.

This precise manipulation provides an unprecedented opportunity to study in parallel how each mutation affects the activity of specific neurons, including different types of neurons.

Modeling proteins at scale

The team is studying roughly 6,000 mutations in excitatory and inhibitory neurons, focusing on how these genetic changes affect the structure and function of the proteins the genes encode. This is where desktop supercomputing comes in.

The researchers are using a desktop supercomputer equipped with a powerful protein structure prediction model to simulate the effects of the mutations that they are also studying experimentally.

They hope to create a prediction map that would help identify which mutations are most likely to produce meaningful changes in neuronal function, allowing the researchers to focus experimental efforts where they matter most.

Protein structure prediction is notoriously computationally intensive, requiring vast amounts of processing power. Sabatini and his team will leverage the desktop supercomputer in the early stages of research, which require repeated rounds of testing and refinement.

“We’re asking whether a person in a biology lab can use a workhorse on their desk, where they can do this kind of analysis in a weekend without all the infrastructure that a supercomputing cluster provides,” Sabatini said.

Preliminary results could then inform larger-scale, more resource-intensive projects on the Kempner Institute’s AI cluster.

The team has successfully used the desktop supercomputer to screen for mutations in small test proteins, which has given them a sense of how long each screen takes. Now, they are scaling up to screen for mutations in an inhibitory receptor protein within brain cells.

By charting how mutations shape the proteins that govern neuronal function, the researchers are uncovering fundamental rules for how diverse cell types in the brain form circuits that process information.

“This is our first step toward trying to understand the fundamental building blocks of each one of those cells,” Sabatini said.

Adapted from a Kempner Institute news story.