#ScienceSaturday posts share exciting scientific developments and educational resources with the KAND community. Each week, Dr. Dominique Lessard and Dr. Dylan Verden of KIF1A.ORG summarize newly published KIF1A-related research and highlight progress in rare disease research and therapeutic development.
KIF17 Modulates Epileptic Seizures and Membrane Expression of the NMDA Receptor Subunit NR2B
Seizures are sudden changes in behavior caused by uncontrolled activity in the nervous system. This may sound like a broad definition, because it is; seizures can manifest as obvious convulsions or subtle lapses in awareness. For one KIF1A family’s experience with seizures, see Luke Rosen’s story of Susannah’s nighttime seizures. The cause of seizures can also vary widely: too many excitatory neurons, too few inhibitory neurons, cell death, or excessive crosstalk can all lead to the electrical storms we call seizures. This week’s paper discusses how kinesin family member KIF17 can contribute to another cause: too many electrical channels on neurons.
Like KIF1A, KIF17 is enriched in neurons where it carries cargo to dendrites that receive signals from other neurons. One of these cargo (NR2B) forms part of the NMDA receptor, which allows calcium to enter neurons and causes them to fire. Researchers found that KIF17 was expressed at higher levels in the brains of epileptic patients. Changing the expression level of KIF17 changed the frequency of seizures in an epileptic mouse model: mice overexpressing KIF17 had more NR2B in their dendrites and more seizures, while mice underexpressing KIF17 had less dendritic NR2B and less seizures. This speaks to the broad range of effects kinesins can have on cellular health.
So what is the relationship between KIF1A and seizures? We’re still trying to learn more, which is why studying patient-derived cells through our partnerships with NeuCyte is so crucial. You can also help us better understand KIF1A-related seizures by submitting EEG data to KIF1A researchers at Columbia University.
Learn more about seizure mechanisms
Drilling for rare disease therapeutics
One of the most persistent challenges for treating KAND is the sheer number of mutations present in our community, each of which can have different impacts on KIF1A structure and function. This is common in genetic disorders, and in other research spaces as well. Scientists at Scripps Research have taken computational models used by oil companies to determine oil well locations and applied it to cystic fibrosis (incredible, right?!). These models focus on spatial relationships to better understand structure—a few test wells can provide information about an oil reservoir, and a few genetic sequences can provide information about protein shape and function. By applying machine learning to these sequences, researchers were able to uncover common themes in CFTR mutations that cause cystic fibrosis, which may help to pinpoint more informed therapeutic strategies. The scientists plan to apply this strategy to other disorders as well.
“When you want to treat patients, you really have to appreciate that different therapeutics might target different variants in completely different ways, and that’s why our approach that looks at many different variants all at once is so powerful … Our approach not only reveals how these variants contribute to each patient’s biology, but also connects them in a way that each variant can inform how to manage the others.”Chao Wang, Scripps Research senior staff scientist