Scientists know that Alzheimer’s disease begins to take root decades before its initial symptoms appear. One of the great challenges for researchers is to pinpoint the earliest signs of Alzheimer’s before it can start to devastate a person’s brain structure, memories, and reasoning. After years of collecting data, the NIA-supported Alzheimer’s Disease Neuroimaging Initiative (ADNI) is yielding promising results about the structural and biochemical changes in the brain and the genetic variations that mark the onset and progression of Alzheimer’s disease.
Launched in October 2004, this landmark study and public-private partnership has gathered and analyzed thousands of brain scans, genetic profiles, and biomarkers in blood and cerebrospinal fluid (CSF) in an ongoing effort to find more sensitive and accurate methods to detect Alzheimer’s disease at earlier stages and mark its progress. (Biomarkers are proteins and other substances in the body that can be used to measure the progress of disease or the effects of treatment.)
“We’re trying to understand this disease at earlier and earlier stages so that we can provide patients with a therapy that will slow or halt the disease process,” says Dr. Neil Buckholtz, chief of the Dementias of Aging Branch in the NIA’s Division of Neuroscience . Although such a therapy may be years away, ADNI is working now to standardize the procedures and measures that scientists will use as they search for and test treatments that target the underlying disease.
The original goal of ADNI was to define biomarkers for use in clinical trials, specifically to determine the best way to measure treatment effects in Alzheimer’s disease, says Principal Investigator Dr. Michael W. Weiner. “However, as the field has evolved, the goal has now extended to the use of biomarkers to detect Alzheimer’s at a pre-dementia stage.” Dr. Weiner directs the Center for Imaging of Neurodegenerative Diseases at the Veterans Affairs Medical Center in San Francisco and is a professor at the University of California, San Francisco.
Preliminary data from ADNI are yielding some exciting results. For example, Weiner and colleagues found that structural magnetic resonance imaging (MRI),  a technique that can determine, noninvasively, the detailed three-dimensional anatomy of the brain, has “huge potential” as a way to identify brain changes that are associated with Alzheimer’s disease onset and progression. Another promising outcome is the development of a possible cerebrospinal fluid biomarker profile  (pattern of biomarkers) for the onset of mild Alzheimer’s disease. ADNI researchers are also examining variations in genetic profiles that may be related to Alzheimer’s risk.
Much recent work has focused on developing reliable ways to identify people with mild cognitive impairment (MCI) who will progress to Alzheimer’s disease, so that we can determine the kinds of disease changes that warrant further investigation. People with MCI often progress to Alzheimer’s—but they sometimes revert to normal cognition.
An assessment of multiple measures helps to identify Alzheimer’s disease. These may include, for example:
- Volume of the hippocampus—a region of the brain involved in learning and memory
- Glucose metabolism in the brain
- Performance on tests of memory
- Identification of certain proteins in cerebrospinal fluid
- Plaques in the brain
The challenge for clinicians and researchers is to determine the specific combination of images and biomarkers that best predicts the development and progression of MCI and Alzheimer’s disease.
The Search for Brain Changes and Biomarkers
ADNI Study Cores and Substudies
ADNI involves dozens of scientists at 59 study sites—54 in the United States and 5 in Canada—and is organized around eight core and two substudy areas (see box). The 821 ADNI participants include about 200 older adults with Alzheimer’s, some 400 individuals with MCI, and about 200 cognitively normal people. Scientists have followed the participants with Alzheimer’s disease through visits every 6 months for 2 years and have followed the other participants for 3 years.
Some of the leading-edge technologies under study are brain-imaging techniques, such as positron emission tomography (PET), including FDG-PET (which measures glucose metabolism in the brain); PET using a radioactive compound (PiB) that measures brain beta-amyloid; and structural MRI. Brain scans are showing scientists how the brain’s structure and function change as Alzheimer’s disease starts and progresses.
Biomarkers in cerebrospinal fluid are revealing other changes that could identify which patients with MCI will develop Alzheimer’s. Scientists are looking at levels of beta-amyloid and tau in cerebrospinal fluid. (Abnormal amounts of the amyloid and tau proteins in the brain are hallmarks of Alzheimer’s disease.)
According to Dr. Buckholtz, the idea is to correlate the cognitive assessments and other methods currently used to diagnose and follow the disease with precise brain scan results, measurements of fluid biomarkers, and genetic analyses. This would relate the results of these tests to the symptoms a person may be having. Current evaluation methods alone cannot tell doctors and researchers whether a beneficial cognitive effect in an individual with Alzheimer’s or MCI results from the drug having a purely symptomatic benefit or whether it is actually slowing the progression of the disease, he says. It’s hard to say without additional data. ADNI is designed to help researchers overcome that limitation.
“In medicine, there is almost never one best way,” Dr. Weiner says. “I think that as we learn more about Alzheimer’s disease biomarkers, different methods will be useful for different purposes.”
Early Results Starting To Roll In
Dozens of early studies based on ADNI data have already been published, with many more to come as further data are collected and analyzed. These early findings have generated excitement among researchers. For example, a structural MRI study of 449 participants by Weiner and colleagues found that people with Alzheimer’s and MCI lost more volume in the hippocampus more quickly than did cognitively normal people, as shown by results of MRI scans at 6 and 12 months after obtaining baseline data. (The hippocampus, which plays a major role in learning and memory, is one of the first areas of the brain affected by Alzheimer’s. disease.)
These losses were associated with deteriorating scores on cognitive assessments. In people with Alzheimer’s, higher rates of loss in hippocampal volume also correlated with the presence of the apolipoprotein E (ApoE) ε4 gene, a risk factor for Alzheimer’s. In people with MCI, higher rates of hippocampal loss were associated with lower levels of the peptide amyloid-beta 1-42 (Aβ1-42) in the cerebrospinal fluid.
“The finding of accelerating hippocampal loss is important for understanding the natural history of the disease and emphasizes the need for early diagnosis and therapeutic intervention,” the researchers write.
Other ADNI studies, including one published by Jack and colleagues , have shown that PET imaging holds potential for a different use: the identification of people with Alzheimer’s pathology who have not yet developed dementia. Weiner notes, “Detection of brain beta-amyloid can be used as a risk factor to predict future decline to Alzheimer’s disease.”
In another recently published ADNI study  by Dr. Leslie Shaw and colleagues at the University of Pennsylvania Medical School, cerebrospinal fluid samples from 410 volunteers showed lower levels of beta-amyloid, especially the insoluble type Aβ1-42, and higher levels of tau in people with the disease than in people with MCI. Likewise, people with MCI had lower Aβ1-42 and higher tau levels than did cognitively normal controls. These findings confirm the results of previous smaller studies.
Of the 37 volunteers with MCI at the start of the study, 33 were diagnosed with probable Alzheimer’s a year later, while the other 4 were not. Regardless of outcome, cerebrospinal fluid biomarkers correlated well with those changes. Biomarkers in individuals who progressed from MCI to Alzheimer’s disease were similar to those of participants with Alzheimer’s disease, while biomarkers for people who reverted to normal were similar to those of normal participants.
“We’re very keen on the idea of testing the use of biomarkers for grouping study participants into those at highest risk of developing Alzheimer’s disease and those at least risk,” says Dr. Shaw. This stratification could help identify the best candidates for future clinical trials, he explains.
Another major ADNI contribution to the field has been the creation of a publicly accessible database . As it moves into the third year of data collection, the database contains more than 3,200 MRI scans, about 1,600 FDG-PET scans, about 960 cerebrospinal fluid measurements, genetic information, and other information, all maintained by the Laboratory of Neuro Imaging (LONI) at UCLA.
“One of the successes of ADNI is that these data are freely available,” Buckholtz says. “The data are posted in real time. Any qualified researcher can request a password to access the data.” So far, thousands of researchers worldwide have accessed the data.
Practical Benefits of ADNI
Pharmaceutical companies also are starting to incorporate ADNI techniques into their trials, says Holly Soares, director of translational medicine at Pfizer Global Research and Development in Groton, CT, and chair of the ADNI industry scientific advisory board, which represents ADNI’s private partners.
The value of the ADNI results lies in their utility for clinical trials of new drugs. Biomarker-based clinical trials will broaden the types of trials that drug makers conduct, Soares says. Some companies are beginning to plan for prevention studies, and having biomarkers that reliably predict who will progress to Alzheimer’s disease will help researchers identify ideal study participants.
This ability to identify the best candidates for drug trials is perhaps ADNI’s greatest contribution to clinical-trial design, Soares adds. Biomarkers will help pinpoint people in the early stages of disease, define differences in the way the disease progresses, and reduce the number of participants needed to gain statistically powerful results. Smaller samples mean lower costs, too.
A more targeted study population makes it easier to show whether new treatments work, says Dr. Russell Katz, director of the U.S. Food and Drug Administration’s Division of Neurology Products: “You can better focus your study on participants who are more likely to respond to your drug.”
“Eventually,” Dr. Katz says, “we want to be able to say that when we fix the marker, we are likely to be helping the patient.” He adds, “The hope is that we’ll be able to treat people earlier and earlier. ADNI is laying the groundwork to do that.”
As scientists collect and analyze more data, conferences are in the works to help reach a consensus on ways to standardize ADNI methods for clinical trials, according to Dr. Weiner.
October 1, 2009, marks the start of the sixth and final year of ADNI under current funding. Investigators are hoping to obtain funding to continue the study for 5 more years. ADNI is currently supported by a $67 million public-private partnership. The Federal Government’s $40 million comes from the NIA primarily and the National Institute of Biomedical Imaging and Bioengineering, both parts of the National Institutes of Health. ADNI was recently awarded a Grand Opportunities grant from NIH as part of the American Recovery and Reinvestment Act.
As a major aspect of this study, the researchers will add people with early-stage MCI to the study population, says Dr. Buckholtz. Dr. Shaw adds that investigators would like to continue to analyze the thousands of cerebrospinal fluid and plasma samples collected, testing the performance of amyloid and tau to predict conversion from MCI to Alzheimer’s, and looking to other biomarkers to refine the biomarker profile for Alzheimer’s.
Jack, C.R., et al. Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer’s disease: implications for sequence of pathological events in Alzheimer’s disease. Brain. 2009. 132(5):1355-65.
Schuff, N., et al. MRI of hippocampal volume loss in early Alzheimer’s disease in relation to ApoE genotype and biomarkers. Brain. 2009. 132(4):1067-77.
Shaw, L.M., et al. Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol. 2009. 65:403-13.