Brain Imaging (MRI/PET) and Measurements of Proteins in Spinal Fluid May Improve...

Brain Imaging (MRI/PET) and Measurements of Proteins in Spinal Fluid May
Improve Alzheimer's Prediction and Diagnosis
New Results from ADNI Data Bring Us Closer to Earlier Detection of Alzheimer's

VIENNA, Austria, July 14 /PRNewswire-USNewswire/ -- Changes in the brain
measured with MRI and PET scans, combined with memory tests and detection of
risk proteins in body fluids, may lead to earlier and more accurate diagnosis
of Alzheimer's, according to new research reported today at the Alzheimer's
Association 2009 International Conference on Alzheimer's Disease (ICAD 2009)
in Vienna.

(Logo: http://www.newscom.com/cgi-bin/prnh/20090529/ICADLOGO )

The National Institute on Aging's (NIA) Alzheimer's Disease Neuroimaging
Initiative (ADNI), data from which forms the basis of these three studies, is
a $60 million, 5-year, public-private partnership to test whether imaging
technologies (such as MRI and PET), other biomarkers, and clinical and
neuropsychological assessment can be combined to measure progression toward
Alzheimer's. ADNI is the first study to examine a number of candidate
Alzheimer's biomarkers in the same individuals. The study is expected to be a
landmark for identifying Alzheimer's biomarkers, with data widely available to
researchers. ADNI is primarily funded by NIA, part of the National Institutes
of Health (NIH), with private sector support through the Foundation for NIH.
The Alzheimer's Association is one of the ADNI sponsors.*

A biomarker is a substance or characteristic that can be objectively measured
and evaluated as an indicator of normal body processes, disease processes, or
the body's response(s) to therapy. For example, blood pressure is a biomarker
that indicates risk of cardiovascular disease.

"With the continued aging of the population and the growing epidemic of
Alzheimer's, early detection of the disease is crucial for risk assessment,
testing new therapies, and eventual early intervention with better drugs, once
they are developed," said Ronald Petersen, PhD, MD, chair of the Alzheimer's
Association Medical & Scientific Advisory Council.

"It is widely believed that Alzheimer's disease brain changes, including
amyloid plaques and neurofibrillary tangles, begin many years before we see
symptoms. It is critical to identify affected individuals while they are still
relatively cognitively healthy so that future therapies can preserve healthy
memory and thinking function. And, in order to develop those new therapies, we
need to identify 'at risk' individuals now in order to steer them to clinical
trials," Petersen added.

Petersen is Professor of Neurology; Cora Kanow Professor of Alzheimer's
Disease Research; and Director, Mayo Alzheimer's Disease Research Center, Mayo
Clinic College of Medicine, Rochester, MN. He is one of the Principal
Investigators of ADNI.

Memory Tests and Hippocampal Volume May Accurately Diagnose Early Alzheimer's
Researchers led by Michael Ewers, PhD, senior research fellow at Trinity
College Institute of Neuroscience, Trinity College Dublin, Ireland, and Harald
Hampel, MD, MSc, Chair of Psychiatry, Trinity College Dublin, identified 345
ADNI participants (81 with Alzheimer's, 163 with amnestic MCI; 101 elderly
healthy controls) on whom there was available data including (a) cerebrospinal
fluid (CSF) concentration and ratios of Alzheimer's related proteins: total
tau, phosphorylated tau (p-tau181), and beta-amyloid (AB1-42), (b) MRI volume
measures of certain sections of the brain, including the left and right
hippocampus, entorhinal cortex, and medial temporal lobe, and (c) scores on
certain standard memory, learning and brain function tests, including the Rey
Auditory Verbal Learning test (RAVL) and the Alzheimer's Disease Assessment
Scale (ADAS).

From this data they used statistical methods to identify the best set of
predictors that correctly identified (a) healthy people versus those with
Alzheimer's, and (b) people with mild cognitive impairment (MCI) who
progressed to Alzheimer's (of which there were 50 people in the study who
converted over the next year and a half).

"The clinical symptoms of MCI alone are not enough to allow for early
diagnosis of Alzheimer's," Ewers said. "In fact, a substantial proportion of
people with MCI may revert back to normal or may not develop Alzheimer's for
years. Thus, the challenging task is to discern which of people with MCI have
the Alzheimer's brain changes that may be responsible for their initial memory
and thinking problems and their eventual progression to Alzheimer's, so that
they can be targeted for Alzheimer's-specific treatments."

The researchers found that results of three subunits of the memory tests could
be combined to reach a classification accuracy of 89.9% for distinguishing
people who progressed from MCI to Alzheimer's versus healthy people. They
found that by adding in results from MRI volume measurements of the left
hippocampus - a brain region closely linked to memory and Alzheimer's - they
could increase classification accuracy to 94%. When, as a means to validate
the findings, the same set of tests and measures was applied to distinguish
the healthy people from those with Alzheimer's, classification accuracy was
95.7%.

When the researchers also included measures of tau and beta amyloid in CSF and
presence or absence of a known Alzheimer's risk genotype (ApoE-e4), they could
correctly identify people with MCI who progressed to Alzheimer's within 1.5
years with 95.6% accuracy, but the model including only memory tests plus
hippocampus was the most robust predictor set.

"Our results show that a relatively simple prediction model, including the
combination of hippocampus volume measured by MRI with memory tests, may be
able to accurately diagnose Alzheimer's at a very early stage in the disease,"
Ewers said. "We believe this is the first large-scale, multi-center study to
use this variety of biomarker candidates in MCI and Alzheimer's. This
diagnostic model needs to be validated in autopsy-confirmed Alzheimer's
cases."

Poor Results on PET Brain Measurements and Memory Test Scores Increase
Alzheimer's Risk 15 Times for People with MCI
Susan M. Landau, PhD, of the Helen Wills Neuroscience Institute at the
University of California, Berkeley, and colleagues used data from 85 ADNI
participants with MCI (ages 55-90) to compare the utility of a variety of
baseline measurements for predicting decline in MCI and conversion from MCI to
Alzheimer's over a two-year period.

Candidate predictors of decline included hippocampal volume measured with MRI;
relative rates of glucose metabolism in certain, prespecified brain regions
measured with FDG-PET scans; number of apolipoprotein E4 (ApoE4) alleles,
which is an Alzheimer's risk gene; CSF measurement of Alzheimer's related
proteins, including beta amyloid (AB1-42), total tau (t-Tau), and tau
phosphorylated in the 181 threonine position (p-tau181); and a test of memory
recall ability (AVLT). Participants were evaluated at approximately 6 month
intervals to determine whether decline to Alzheimer's had occurred.
Approximately 17% (1 in 6) MCI patients converted to Alzheimer's disease per
year in this study.

The researchers found that low baseline FDG-PET measurements and poor memory
recall in people with MCI reliably predicted progression to Alzheimer's over
the two year follow up period of the study.

"The novel finding of our analysis is that when we directly compared all the
potential predictors to one another, we found that the amount of glucose
metabolism, as measured by FDG-PET, and memory recall ability, measured by
AVLT total recall, were the most predictive of conversion from MCI to
Alzheimer's," Landau said. "People who did poorly on those two measurements -
that is, low glucose metabolism combined with poor memory performance - were
15 times more likely to convert to Alzheimer's compared to individuals who
were normal on those measurements."

"When the measurements are considered individually, p-tau (a CSF protein) and
hippocampal volume also significantly predict conversion from MCI to
Alzheimer's. Specifically, MCI patients in our study who were low on these
measures had a 2 to 4 times higher risk of progressing to Alzheimer's," Landau
added.

Additionally, all measurements (ApoE4 status, hippocampal volume, FDG-PET, CSF
biomarkers, and memory recall ability) played a role in predicting cognitive
decline, regardless of whether the patients converted to Alzheimer's or not.
P-tau181 had the strongest value in predicting subsequent cognitive decline.

According to the researchers, the selection of a biomarker, or set of
biomarkers, will be critical in research to select participants who are most
likely to experience Alzheimer's over time, and enable these individuals to
participate meaningfully in clinical studies, such as those for Alzheimer's
drug treatments.

PET Measurements of the Hippocampus May Improve Alzheimer's Diagnosis
According to Dawn Matthews, Chief Executive Officer and President of Abiant,
Inc., and colleagues at New York University School of Medicine, declines in
regional cerebral glucose metabolism (rCMglc) in the brain as measured with
Positron Emission Tomography (PET) imaging have been demonstrated to correlate
to the progression of Alzheimer's, and to differentiate between dementias.
Recent studies have shown that the accuracy of Alzheimer's diagnosis may be
improved by including measurement of rCMglc in the hippocampus (HIP), a region
of the brain that is critical to the formation of new memories. However,
according to the researchers, HIP rCMglc cannot be accurately and practically
sampled in broad populations using conventional techniques. This is because
the hippocampus has an irregular shape and undergoes varying degrees of
shrinkage during aging and when affected by disease, such as Alzheimer's.
Conventional analysis techniques rely on the ability to align images of each
patient's brain to a template brain map, and there is loss of sensitivity and
precision due to the difficulty of aligning this irregular shape.

Lisa Mosconi, PhD, and colleagues in the Center for Brain Health at New York
University (NYU) School of Medicine, directed by Mony de Leon, PhD, developed
and tested an automated method that achieves accurate, rapid sampling of many
brain regions, including the hippocampus. Matthews and her team collaborated
with NYU to apply the automated method to 250 subjects from the ADNI database
(78 female/172 male, age 59-88; 79 healthy, 111 MCI, 60 Alzheimer's). Using
the automated approach, rCMglc was measured by PET in 32 brain regions.
Participants were divided into seven subgroups across normal, MCI, and AD
categories, based upon their initial diagnosis and results of subsequent
memory and thinking tests up to 3 years after the scan.

The researchers observed a significant correlation between rCMglc in several
brain regions and the progression from "stable normal" to "normal with
subsequent clinical decline", to subcategories of MCI and Alzheimer's. They
also found that HIP rCMglc was a sensitive predictor of decline and
discriminator between disease stages. As compared to people considered "stable
normal," HIP rCMglc was reduced by 5% in "normal with subsequent clinical
decline", 12% in "stable MCI," 14% in "MCI with subsequent clinical decline"
(p<0.05), and 24% in Alzheimer's (p<0.001).

"We found that glucose metabolism levels were highest in the healthy
participants who did not decline to MCI, lower in healthy people who later
declined, and progressively lower in people with MCI who remained MCI, lower
in MCI patients who declined to AD, and lowest in those with Alzheimer's,"
Matthews said. "These results demonstrate the feasibility of achieving highly
specific diagnosis by incorporating glucose metabolism measurements from the
hippocampus."

About ICAD 2009
The 2009 Alzheimer's Association International Conference on Alzheimer's
Disease (ICAD 2009) brings together more than 5,000 researchers from 60
countries to share groundbreaking research and information on the cause,
diagnosis, treatment and prevention of Alzheimer's disease and related
disorders. As a part of the Association's research program, ICAD 2009 serves
as a catalyst for generating new knowledge about dementia and fostering a
vital, collegial research community. ICAD 2009 will be held in Vienna, Austria
at Messe Wien Exhibition and Congress Center from July 11-16.

About the Alzheimer's Association
The Alzheimer's Association is the leading voluntary health organization in
Alzheimer care, support and research. Our mission is to eliminate Alzheimer's
disease through the advancement of research, to provide and enhance care and
support for all affected, and to reduce the risk of dementia through the
promotion of brain health. Our vision is a world without Alzheimer's. For more
information, visit www.alz.org.

* A list of ADNI sponsors is here:
http://www.adni-info.org/index.php?option=com_content&task=view&id=8&Itemid=30

-- Michael Ewers, et al - Biomarker Based Diagnosis Of Very Mild
Alzheimer's Disease: A Multicenter Study (Funders: Science
Foundation Ireland (SFI), the Health Service Executive (HSE), the
Health
Research Board (HRB) of Ireland, National Institute on Aging,
Foundation
for the National Institutes of Health, National Institutes of Health,
Evelyn F. McKnight Brain Institute of the University of Arizona, State
of Arizona and Arizona Department of Health Services, Pfizer, Eisai,
Janssen, Novartis, Lilly, Astra Zeneca, Sanofi, Canadian Institutes of
health Research, Alzheimer Society of Canada, Michael Smith Health
Research Foundation.)
-- Susan Landau, et al - Comparing predictors of conversion: Data from
the
Alzheimer's Disease Neuroimaging Initiative (Funders: National
Institute on Aging, ADNI Partnership)

-- Dawn C. Matthews, et al - Hippocampal glucose metabolism predicts
cognitive decline and correlates to disease progression in the ADNI
population (Funder: Abiant, Inc.)

SOURCE Alzheimer's Association

Alzheimer's Association media line: +1-312-335-4078, media@alz.org; or ICAD
2009 press room, July 11-16: +43 (0)1 931020 7501