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VA RESEARCHERS LOOKING FOR NEW ALZHEIMER'S

CLUES -- "Ultimately, we hope that brain and biological

changes in Alzheimer's can be detected before

memory decline and other symptoms appear."

 

 

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Early Alzheimer's Detection by Gene 'Signature' In Blood Possible

With anticipation running high of breakthroughs in Alzheimer's disease therapies, reports of the latest results from studies on early detection of Alzheimer's took on added urgency.

The studies included examination of blood samples examined for a "signature" set of genes, an innovative analysis of both MRI and PET scan images, novel combinations of memory and cognitive tests, and a predictive model based on an easy-to-assess mixture of test results and health/lifestyle history.

"Potential disease modifying drugs for Alzheimer's are very likely on the horizon, so we need accurate and easy-to-use early identification techniques for Alzheimer's so that we can initiate treatment earlier," said William Thies, PhD, vice president of Medical and Scientific Relations at the Alzheimer's Association. "And until disease modifying drugs are available, early detection empowers people to plan for their future sooner, including financial and legal matters, along with getting access to resources such as support groups, disease information and research studies."

Improvements in early detection of Alzheimer's in recent years have granted researchers and service providers, such as the Alzheimer's Association, access to a population of people who are able to articulate their experiences and needs.

"By better understanding the experiences of people living with Alzheimer's, we can significantly improve clinical studies, medical practice, caregiving and services," Thies said.

Still, a large proportion of people with Alzheimer's are not diagnosed until the disease is in the moderate or advanced stages, according to the Alzheimer's Association.

"The National Institute on Aging, the Alzheimer's Association and industry are pushing hard for earlier detection and earlier intervention through efforts such as the Alzheimer's Disease Neuroimaging Initiative (ADNI)," said session moderator and neuroimaging expert Michael Weiner, MD, of the San Francisco Veterans Affairs Medical Center and the University of California, San Francisco, who is ADNI's principal investigator. "Ultimately, we hope that brain and biological changes in Alzheimer's can be detected before memory decline and other symptoms appear."

Gene "Signature" In Blood May Detect Alzheimer's

At the Alzheimer's Association Prevention Conference, scientists working for Norwegian biotech company, DiaGenic ASA, presented results of a study using an assay that detects a unique gene expression profile or "signature" in blood samples.

Researchers combed through many Alzheimer patient samples and several thousand genes to identify what they believe to be a common gene signature for Alzheimer's that they could test. The most informative genes isolated in these discovery phase studies were then used to design and develop customized test arrays. The scientists presented results from a cohort of 119 subjects (53 with Alzheimer's, 58 age matched controls, and 8 younger controls), using two different detection technology platforms. The researchers generated one gene "signature" using about 1,200 genes giving a specificity of 84 percent, a sensitivity of 86 percent and thus an accuracy of 85 percent. A second "signature" within a 96-gene setting gave a specificity of 73 percent, a sensitivity of 84 percent and an accuracy of 79.5 percent.

"As with all new diagnostic tests, ours will also require validation with a large number of Alzheimer's patients and control subjects at multiple centers. This is already in progress, and next year we'll know how well the test will perform," said Anders Lonneborg, PhD, Research Director at DiaGenic ASA.

Simultaneous Use of MRI and PET Scans May Improve Early Detection of Alzheimer's

Advanced imaging technologies, such as MRI and PET scans, are being investigated for use in early detection of Alzheimer's. Christos Davatzikos, PhD, of the Department of Radiology at the University of Pennsylvania, Philadelphia and colleagues used new computer-based image analysis techniques (advanced high-dimensional pattern classification methods) to analyze both MRI and PET images from 15 patients with mild cognitive impairment (MCI) and 15 cognitively healthy participants from the Baltimore Longitudinal Study of Aging, in collaboration with Dr. Susan Resnick from the National Institute on Aging and Dr. Michael Kraut from Johns Hopkins, with the goal of achieving better diagnosis of MCI on an individual patient basis.

By using these new techniques to analyze areas of brain atrophy (MRI) and reduced blood flow in the brain (PET), the scientists were able to identify complex spatial patterns of brain abnormality that are characteristic of MCI. Using these highly distinctive patterns, the scientists were able to distinguish between the MCI and healthy participants with 100 percent accuracy. This result is better than those obtained by MRI scans (90 percent) or PET scans (73 percent) alone.

"We believe our pattern analysis and classification technique provides, for the first time, the sensitivity and specificity for individual patient diagnosis of MCI," Davatzikos said. "Not only are the abnormalities in the MCI brain detected earlier than other techniques analyzing MRI scans, but, in many individuals, they can be identified and measured even before the patient's mental processes deteriorate to the point of clinical symptoms."

"Bedside" Model For Predicting an Individual's Risk of Developing Dementia

Physicians currently have a variety of tools to predict the likelihood that someone will develop heart disease over the next 10 years. Deborah E. Barnes, PhD, MPH, Assistant Professor of Psychiatry at the University of California, San Francisco, and colleagues sought to develop a similar tool to predict an individual's risk of developing dementia.

The researchers studied 3,375 subjects in the Cardiovascular Health Cognition Study who did not have dementia at the beginning of the study and determined which combination of factors most accurately predicted whether or not they would develop dementia over the next six years. They developed two models: the "best" model included all possible factors and the "bedside" model included only those factors that could be easily assessed by a physician during a clinic visit.

The factors in the "best" model included: older age, lower cognitive test scores (Modified Mini-Mental State Exam, Digit Symbol Substitution Test), low body mass index (<18), slower physical function (time to put on a button a shirt, time to walk 15 feet), history of by-pass surgery, lack of alcohol consumption, possession of 1 or more apolipoprotein E e4 alleles, evidence of enlarged ventricles or white matter disease on cerebral magnetic resonance imaging scans, and thickening of the carotid artery wall on ultrasound. The "bedside" model included older age, lower cognitive test scores, low body mass index (<18), slower physical function, history of by-pass surgery, and lack of alcohol consumption.

The overall accuracy of the "best" model was 88 percent. Six percent of people with low scores on the "best" model developed dementia within six years compared to 25 percent of people with moderate scores and 52 percent of people with high scores. The overall accuracy of the "bedside" model was almost as good: 87 percent. Using the "bedside" model, the risk of dementia was six percent for people with low scores, 25 percent for people with moderate scores, and 54 percent for people with high scores.

"In this study population, it was possible to predict an individual's six- year risk of developing dementia with high accuracy," Barnes said. "The 'best' model was significantly better than the 'bedside' model, although the absolute difference between the models was relatively small. Future studies should validate these tools in other study populations."

The most effective method of detecting a disease in its earliest stages is to screen individuals who are at a higher risk for getting the disease (age is the most important risk factor for Alzheimer's disease). Effective screening tests should be useful for detecting abnormal cognitive performance among people from different racial and educational backgrounds. In this regard, the validity of currently used diagnostic instruments for Alzheimer's and dementia across ethnic/racial groups has been questioned.

Ranjan Duara, MD, Medical Director at the Wien Center for Alzheimer's Disease and Memory Disorders, Mt. Sinai Medical Center, Miami Beach, FL (Miller School of Medicine, University of Miami), evaluated 2,482 elderly individuals (average age = low 70s) with brief memory and other mental tests. About 1,800 white, English-speakers, 920 white Spanish-speakers and 120 English-speaking African Americans took part in this program over a 12-year period. The Mini-Mental State Exam (MMSE) was used as the gold standard to diagnose individuals as normal or cognitively impaired. Two other tests -- a memory test, the Multiple Delayed Recall Test or mDRT, and a test that combines language ability, memory and speed in performing these tests, the Category Fluency Test or CFT -- were used individually and in combination to distinguish normal from cognitively impaired individuals. Tests were conducted in each participant's primary language.

The results showed that both mDRT and CFT effectively distinguished normal from cognitively impaired individuals in each racial/ethnic group. Both mDRT and CFT scores were significantly different among normal and cognitively impaired subjects in all three ethnic groups, although the cut points for impairment were substantially different among the three ethnic groups.

"While these results need to be validated against a better gold standard than the MMSE score, it would appear that an effective brief screening test for cognitive impairment, which may be a precursor to Alzheimer's, could be devised using a combination of mDRT and CFT," Duara said. "This test should be useful for all ethnic groups, is easy to learn by most office medical office assistants and takes only five minutes to administer."

A current major focus in the prevention and treatment of dementia is the identification of the disease at its earliest possible stage, known as MCI. Interventions administered when people can still compensate for their impairment could substantially reduce the personal and socioeconomic burden of dementia.

Brenna Cholerton, PhD, Clinical Assistant Professor of Psychiatry and Behavioral Sciences at the University of Washington School of Medicine, and research clinical neuropsychologist at the VA Puget Sound Healthcare System Geriatric Research, Education, and Clinical Center (GRECC), and colleagues set out to identify a reliable cognitive screening procedure for the detection of MCI in a community-based sample -- in this case the Group Health Cooperative Adult Changes in Thought (ACT) study.

The researchers revised the cognitive screening examinations, which are administered every two years to all ACT participants, to allow the detection of MCI by raising the cutoff score on the standard cognitive screen and adding brief tests known to be sensitive to the early effects of cognitive decline (verbal recall and verbal fluency). Participants who fall .1 standard deviation below their expected results on any screening test prompt a complete medical and neuropsychological diagnostic workup.

To date, 366 study participants have completed the revised screening procedures, and 245 (69 percent) have met criteria for further diagnostic evaluation. Of the first 48 cases who completed full diagnostic procedures (age range 69-97, mean age=83), 29 have been diagnosed with MCI, 15 with dementia, and four were cognitively normal.

"The rate of people triggering diagnostic evaluations to date based on the revised screening criteria is higher than we originally anticipated, however, the number of those subsequently identified as cognitively normal is relatively low," Cholerton said. "These early data suggest that the prevalence of MCI may be much higher in this older cohort than we previously anticipated."

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Larry Scott  --