Tangled up. One of the hallmarks of Alzheimer’s disease is abnormalities in nerve cells in the brain known as neurofibrillary tangles, which involve the twisting of protein fibers that ordinarily support the physical shape of neurons and transport nutrients to them. Although it is not yet clear how these tangles are produced or exactly how they are associated with the loss of brain function, researchers at the Center for Polymer Studies are slowly unraveling the mystery.
Using BU’s IBM pSeries and Linux Cluster supercomputers, the researchers recently developed a new computational tool known as discrete molecular dynamics (DMD), which allows them to re-create and observe the process by which the tangles develop in silico, or in the computer.
They are examining specifically the amyloid-beta (A-beta) protein that makes up amyloid fibrils, or fiber-like protein deposits, found in the brains of people with Alzheimer’s. Recent studies have suggested that A-beta oligomers, or small assemblies of A-beta molecules whose formation precedes that of the amyloid fibrils, and not the fibrils themselves, may be the source of the toxicity that leads to neurodegeneration.
Jose M. Borreguero, a GRS physics postdoctoral research associate, and colleagues at the center and at the David Geffen School of Medicine at UCLA, recently used DMD to visualize the events that occur during the folding of a segment of A-beta known to be highly resistant to being broken down during normal cell processes — and therefore highly suspect as a player in the formation of amyloid fibrils. The researchers were able to observe several of the forces that appear to control folding in the protein, among them hydrophobic interactions, the same phenomenon that brings together oil droplets suspended in water.
By better understanding the dynamics of toxic oligomers at the atomic level, the researchers hope to develop drugs that can prevent their formation, and therefore, prevent Alzheimer’s disease.
This research was published in the April 26 Proceedings of the National Academy of Sciences.
Saving brain cells. Sickle-cell disease (SCD) is an inherited condition in which an abnormal form of hemoglobin, the protein in red blood cells that carries oxygen, deforms the normally flexible red blood cells into a stiff sickle shape. These stiffened cells can get stuck in tiny blood vessels, producing intense pain and possible organ damage. They also can cause strokes by lodging in vessels of the brain. In fact, about 11 percent of children with SCD experience a stroke before the age of 20 and many more show stroke-like damage visible on brain MRIs — damage associated with learning disorders and other cognitive deficits.
Today, children with SCD are assessed for stroke risk using a technique called transcranial Doppler (TCD) flow studies, which estimates the rate of blood flow to the brain. TCD, however, has a high error rate, with only 10 percent of children with an abnormal reading developing a stroke in the first year of observation and 20 percent of those with normal TCD having a stroke.
Paola Sebastiani, an SPH associate professor of biostatistics, Martin Steinberg, a MED professor and director of the BU Center of Excellence in Sickle Cell Disease, and Marco Ramoni, of Harvard Medical School and the Harvard Partners Genome Center, recently developed a diagnostic tool, based on genetics, that can accurately predict which children with SCD are at risk for strokes. They say it could lead to earlier identification of at-risk children and earlier treatments to reduce the risk of stroke and prevent brain damage.
The new tool is based on a method of analysis called a Bayesian network, which is a data structure used to understand the complex interdependence of numerous variables — in this case, disease complications and genetic variations. The researchers began with 80 possible genes known to be involved in cellular processes related to stroke risk, such as regulation of blood vessel size, inflammation, and coagulation. They analyzed 108 SNPs, genetic variations in those genes, from 1,398 African-Americans with SCD. They found that variations on 12 of the genes were implicated in stroke risk. When considered in relation to fetal hemoglobin level — another prognostic indicator of stroke in those with SCD — this information allowed them to predict with 98.2 percent accuracy which children were at risk. One of the genes identified had already been associated with stroke risk in the general population.
This research appeared in the April issue of the journal Nature Genetics.
Briefs" is written by Joan Schwartz in the Office of the Provost. To read
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