Three groups of researchers are reporting progress on the early detection of Alzheimer's disease - advances that, if validated, could aid patients and drug developers alike, experts say.
In one study, a Norwegian team identified a gene expression "signature" that distinguishes people with Alzheimer's from healthy individuals with an up-to-85 percent accuracy.
In other research, US scientists reported that a combination of brain imaging techniques with sophisticated "pattern recognition software" could differentiate those with mild cognitive impairment (an early form of Alzheimer's) from those without the condition with 100 percent accuracy.
Finally, another US study reveals that key diagnostic algorithms can predict an individual's six-year risk of developing dementia with at least 87 percent accuracy.
The results were announced at the Alzheimer's Association's International Conference on Prevention of Dementia in Washington, DC.
There is no cure
There currently is no cure for Alzheimer's disease. Existing treatments can slow progression of the brain-wasting disease, but by the time an individual has been diagnosed the disease has typically been at work for years and extensive, irreparable tissue damage has already occurred. Diagnosis is currently done simply by observing patients and is only about 80 percent accurate.
According to Greg Cole, associate director of research for the Geriatric Research Education and Clinical Centre at the Greater Los Angeles Veterans Administration Medical Centre, early detection of Alzheimer's disease can aid both patients and those scientists searching for a cure.
Patients benefit, he says, because earlier treatment can minimise tissue loss and thus improve quality of life.
"It's like termite damage," he said. "You want to repair the damage before they destroy your house, you will be so much better off."
Pharmaceutical companies, on the other hand, can more confidently identify affected populations, which can reduce the size and cost of clinical trials, and thus enable them to perform more of them.
Genes betraying Alzheimer’s
The Norwegian study, led by Anders Lonneborg, research director at DiaGenic ASA in Oslo, focused on gene expression profiling of an individual's blood.
Using a 1 200-gene DNA microarray, his team could distinguish those with Alzheimer's disease from those who were healthy with 85 percent accuracy. Using a smaller set of genes (fewer than 96) and a technique called RT-PCR, the team achieved an accuracy of 79.5 percent.
But that was using samples from individuals whose disease was so far advanced that they could be diagnosed clinically, anyway. It remains to be seen, Cole said, if the test can pick out individuals much earlier in the disease process, when treatment might be more effective.
That, Lonneborg added, is the next step. "Now we will test [the diagnostic] on risk groups who have minor memory problems and see if we can predict who will develop Alzheimer's disease in a few years. This will be very interesting to see how it works," he said.
Using brain imaging
A second study tackled early diagnosis using sophisticated brain imaging. The technique was developed by a team led by Christos Davatzikos, of the department of radiology at the University of Pennsylvania in Philadelphia.
Combining MRIs of brain structure with positron emission tomography (PET) measurements of cerebral blood flow, the new test uses pattern recognition software to identify spatial patterns that pinpoint with 100 percent accuracy whether an individual does or does not have mild cognitive impairment.
Using data from the Baltimore Longitudinal Study of Ageing, Davatzikos' team gained access to individual patients' brain images and blood work from over a period of years.
"We found that even before the most subtle clinical symptoms, when they were healthy, we were able to see abnormality scores that were indicative of mild cognitive impairment in at least half of them," said Davatzikos. "So there were early signs."
Cole applauded this test's accuracy, but noted that it is unlikely to have wide application because of its cost - several thousand dollars. Davatzikos said his team is now working to balance the test's accuracy and cost, for instance, by optimising the accuracy of MRI-based tests alone.
A special formula
Finally, a team led by Deborah Barnes, assistant professor of psychiatry at the University of California, San Francisco, is using a special "bedside" algorithm, or formula, to try and predict an individual's dementia risk.
This tool - akin to similar methods for calculating the risk of cardiovascular disease or diabetes - predicts with up to 88 percent accuracy whether an individual will develop dementia over the next six years.
Based on such variables as age, cognitive function and physical performance, the index is an inexpensive, fast and practical algorithm that groups individuals into low-, medium-, and high-risk categories. Those in the low-risk group have a 6 percent risk of developing dementia, compared to 54 percent for those in the high-risk category.
According to Barnes, such an index can provide comfort to those least likely to develop disease while motivating those at higher risk to adopt a healthier lifestyle.
At the same time, it provides information so their families may begin planning for whatever the future may bring, she added. – (HealthDayNews)