Manolis Kellis

if you understand protein structure through modeling of geometric relationships, through geometric deep learning and graph neural networks.

So one of the things that we're doing with Marinka is trying to sort of project these structural graphs at the domain level rather than the protein level.

along with chemicals so that we can start building specific chemicals for specific protein domains.

And then we are working with the chemistry department and Brad to basically synthesize those.

So what we're trying to create is this new center at MIT for genomics and therapeutics that basically says, can we facilitate this translation?

We have thousands of these genetic circuits that we have uncovered.

I mentioned last time in the New England Journal of Medicine, we had published this dissection of the strongest genetic association with obesity.

And we showed how you can manipulate that association to switch back and forth between fat burning cells and fat storing cells.

In Alzheimer's, just a few weeks ago, we had a paper in Nature in collaboration with Lihue Cai looking at APOE4, the strongest genetic association with Alzheimer's.

And we showed that it actually leads to a loss of being able to transport cholesterol in myelinating cells known as oligodendrocytes that basically protect the neurons.

And when the cholesterol gets stuck inside the oligodendrocytes,

It doesn't form myelin, the neurons are not protected, and it causes damage inside the oligodendrocytes.

If you just restore transport, you basically are able to restore myelination in human cells and in mice, and to restore cognition in mice.

So all of these circuits are basically now giving us handles to truly transform the human condition.

We're doing the same thing in cardiac disorders, in Alzheimer's, in neurodegenerative disorders, in psychiatric disorders, where we have now these thousands of circuits that if we manipulate them, we know we can reverse disease circuitry.

So what we want to build in this coalition that we're building is a center where we can now systematically test these underlying molecules in cellular models for heart, for muscle, for fat, for macrophages, immune cells, and neurons, to be able to now screen through these newly designed drugs through deep learning

and to be able to sort of ask which ones act at the cellular level, which combinations of treatment should we be using.

And the other component is that we're looking into decomposing complex traits like Alzheimer's and cardiovascular and schizophrenia into hallmarks of disease.

So that for every one of those traits, we can kind of start speaking the language of what are the building blocks of Alzheimer's.

And maybe this patient has building blocks one, three, and seven, and this other one has two, three, and eight.