Sickle Cells Get Tripped up by Sticky Ones

Sickle Cells Get Tripped up by Sticky Ones
Abnormal hemoglobin, the protein that enables red blood cells to carry oxygen, causes sickle cells to acquire their crescent shape and rigidity (Ezume Images/Shutterstock)
8/2/2022
Updated:
8/2/2022

Using computer models, researchers have discovered it’s a sticky type of red blood cell that starts the blockage that leads to a “sickle cell crisis.”

The models show that the rigid, crescent-shaped red blood cells that are the hallmark of sickle cell disease don’t cause these blockages on their own. Instead, softer, deformable red blood cells known as SS2 cells start the process by sticking to capillary walls. The rigid sickle-shaped cells then stack up behind the SS2s, like traffic behind a car wreck.
While sickle-shaped cells are the hallmark of the disease, they’re not the only type of red blood cell present in people with the condition. (Credit: Rob Pongsajapan/Flickr)
The findings, published in Proceedings of the National Academy of Sciences, could provide a way to evaluate drug treatments aimed at easing or preventing sickle cell crisis, also known as vaso-occlusion.
“This is the first study to identify a specific biophysical mechanism through which vaso-occlusion takes place,” says George Karniadakis, professor of applied mathematics at Brown University and the study’s senior author. “It was a surprising result because the common wisdom was that it was just the sickle cells that block the capillary.”

Hereditary Disease

Sickle cell disease is a genetic condition that affects an estimated 75,000 to 100,000 people in the United States. Abnormal hemoglobin, the protein that enables red blood cells to carry oxygen, causes sickle cells to acquire their crescent shape and rigidity. That elongated shape and inability to bend were thought to be the reason sickle cells caused blockages in capillaries.

While sickle-shaped cells are the hallmark of the disease, they’re not the only type of red blood cell present in people with the condition. Research from the 1980s found that there are actually four types of sickle red blood cells, and not all of them are rigid and sickle-shaped. One cell type, the SS2 cell, retains the round shape and the soft malleability of normal red blood cells.

“They look like healthy cells,” Karniadakis says, “except they’re sticky.”

Sticky Cells

The SS2 cells have receptors on their membranes that cause them to adhere to the walls of blood vessels. Sickle-shaped cells have those same sticky proteins, but Karniadakis’s model showed that the SS2 cells are much more likely to get stuck. “Because [SS2 cells] are deformable—they have a larger contact area with the vessel wall, and so they stick better,” Karniadakis says.

Once those cells become stuck, they effectively make the vessel diameter smaller, causing the rigid sickle-shaped cells to get stuck behind them.

“In the end the rigid sickle cells are really playing a secondary role because the causality starts with the deformable cells that stick to the wall.”

The models, based on experimentally derived data on real cells, allow the researchers to manipulate the cells’ characteristics to see which ones cause blood blockages.

For example, if the researchers reduced the stickiness or softness of the SS2 cells, blockages failed to form. Likewise, if they reduced the rigidity of the sickle-shaped cells, blood kept flowing. It’s the two conditions working in tandem that causes the blockages, but the SS2 cells are the ones that start the cascade.

The researchers hope that the models could be used to evaluate drugs aimed at treating sickle cell crisis.

“If a drug is trying to target the cells’ adhesive properties, or if it’s trying to make cells more flexible, we can test them and see if they prevent occlusion in the model,” Karniadakis says.

The National Institutes of Health and the new Collaboratory on Mathematics for Mesocopic Modeling of Materials (CM4), supported by the Department of Energy funded the research. Computations were made possible by a DOE/Innovative and Novel Computational Impact on Theory and Experiment Award.

This article was originally published by Brown University. Republished via Futurity.org under Creative Commons License 4.0.
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