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As ADNI Turns Four, $64 Million Data Start Rolling In
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This is Part 1 of a six-part series. See also Parts 2, 3, 4, 5, 6. Read the entire series [.pdf].
14 October 2008. The Alzheimer Disease Neuroimaging Initiative (ADNI) is the largest AD study the National Institutes of Health have ever funded. Announced in October 2004 and set to run until 2010, this public-private consortium has engaged 59 research centers in the U.S. and Canada in a massive effort to follow 821 research volunteers for three years. The year 2005 went by preparing sites, building informatics tools, and enrolling the first patients, 2006 and 2007 were spent enrolling and seeing patients, and now in 2008 waves of data have begun flooding in. In terms of data gathering, the study is nearing its midway point. In terms of analysis, it is only scratching the surface of what is yet to come; hence, drawing major conclusions would be premature. Still, the beginning of ADNI’s final year is a good moment in time to take its pulse and peek at the preliminary scientific trends that are beginning to emerge.

Surface Rendering of a Shrunken Cortex in Alzheimer Disease. Image credit: Laboratory of Neuro Imaging (LONI), UCLA
As of now, seven papers on ADNI results have been published, two dozen manuscripts are submitted, some 60 abstracts dealing directly or indirectly with ADNI were presented at the recent International Conference on Alzheimer’s Disease (ICAD) last July in Chicago, and 300 investigators from across the world have downloaded ADNI data for their own analysis. Add-on studies for genetics and amyloid imaging are plugging along; neuropathology validation is set up and awaiting cases. ADNI has built on the clinical infrastructure established previously by the Alzheimer’s Disease Cooperative Study (ADCS). Pharmaceutical companies developing AD drugs have implemented ADNI methodologies in their newer clinical trials. Early data are confirming the main findings of many prior, much smaller imaging and biomarker studies. Early statistical calculations are already hinting that CSF and imaging markers have more power than clinical methods to measure disease progression. Baseline results on the normal control subjects indicate that some of them might have preclinical AD; these data warrant close observation of this population for years to come. ADNI scientists are beginning to plan for a hoped-for expansion, aka ADNI2. Finally, ADNI has caught on around the world, with similar efforts underway in Australia, Japan, Europe, and China. For more on each of these points, read our ADNI 2008 series.
This website has covered the motivation behind ADNI and its major purpose when the study started (see ARF related news story). ADNI itself has an informational website that offers a wealth of freely downloadable slide presentations, protocols, and other materials on ADNI’s organizational structure, goals, and related activities. In brief, ADNI is a longitudinal, observational study that tracks how various measures of structural, functional, and amyloid imaging, as well as fluid biomarkers, change over time in people who enter the study either cognitively normal or with a diagnosis of mild cognitive impairment (MCI), or AD. ADNI compares a host of candidate imaging analyses and biomarkers side-by-side in the same study population, and will relate each marker’s change over time to show how that person’s cognitive and clinical stage also changed over the same period. This can move the field past its current stage, where single-center studies tend to use different ways of acquiring and analyzing data on different candidate biomarkers in different, smaller sets of people. “The literature is full of reports of the value or technique X or method Y in tracking progression or in diagnosis; however, it is difficult to compare reports because the subject groups are always different,” Nick Fox wrote to ARF. Fox is at University College London, the only non-U.S. ADNI preparation and analysis center. ADNI aspires to help the field anoint consensus biomarkers that the pharmaceutical industry and ADCS will incorporate into their therapeutic trials. The goal is that drug trials will eventually treat validated biomarkers of AD instead of treating cognition with its noisy outcome measures. That would cut the cost and length of drug trials and make prevention trials of presymptomatic AD practical (see ARF related news story).

A Composite Picture of Glucose Metabolism Using PET and the Tracer FDG
The AD patient on the right shows reduced glucose metabolism in temporoparietal cortex, a hallmark of the disease and a potential biomarker that is being explored in ADNI. Image credit: William Jagust
Inspiration for ADNI
Neil Buckholtz, who heads the Dementias of Aging program at the National Institute on Aging (NIA), is widely credited with spearheading support for ADNI by bringing different stakeholders together. In discussions with researchers from pharmaceutical companies as early as the mid-1990s, one problem was even then that the companies wanted to develop disease-modifying drugs for AD but had no guidelines from the FDA on how to show if such drugs worked. “We thought it would be useful to serve as a broker between pharmaceutical companies and academic scientists to develop the best instruments and methodologies to measure change over time, so that companies could later test if their drug modifies that progression,” Buckholtz recalled. Because this goal addressed a problem that bedevils all drug makers in the field, it fell into what is called “precompetitive space.” This buzzword denotes areas of common ground where companies that compete fiercely around their products can invest jointly, and even collaborate closely, to generate a set of data that is open to every player in the field. “The ability to standardize imaging approaches, to identify patients early in disease, and to monitor treatment with disease progression markers are hurdles shared across pharma, and ADNI has provided solutions to some of industry’s more intractable problems,” commented Holly Soares of Pfizer, a member of ADNI’s industry advisory board.
To build a public-private consortium, Buckholtz engaged the Foundation for the National Institutes of Health, which was set up by Congress to be able to solicit funds from private groups (the NIA itself cannot do that). The Foundation for the NIH raised money from more than a dozen pharma companies as well as the Alzheimer’s Association and the Alzheimer’s Disease Discovery Foundation (see also ADNI Sponsors), and transferred it to the NIA. The institute used it to fund a grant submitted by Michael Weiner of the University of California, San Francisco, ADNI’s principal investigator. Forty million dollars of that grant came from NIH, and about $24 million through the Foundation of the NIH. By summer 2008, the number of companies in the private consortium had grown to 15. It has supported extensions and add-on studies (see Part 5 of this series, and below). Foundation staff has helped identify industry partners for ADNI and organized a symposium to support communication between the ADNI consortium and regulatory agencies.
ADNI’s industry sponsors each dispatch a representative to an advisory board that supports the overall study, and they also have liaisons to individual ADNI cores, i.e., the scanner manufacturers to the imaging core, the bioassay company to the biomarker core, pharma companies to the clinical core, etc. Dubbed ISAB, this board lends its expertise to the design and execution of ADNI and its add-on studies. Their work is more than nominal. They meet once a month by phone and twice a year in person. For example, the board helped with developing best practices, guidelines, and standard operating procedures—the nitty-gritty stuff that is often boring to the academic investigator but that can sink multicenter studies. Moreover, the ISAB played a role in expanding the CSF component of ADNI from its original target of one fifth of participants to more than half of participants. It helped the clinical sites do that by developing short videos based on prior data Elaine Peskind at University of Washington, Seattle, had generated. Those videos on the one hand featured use of a smaller needle and generally trained clinical staff to conduct standardized lumbar punctures well, and on the other offered education that helped dispel misconceptions about lumbar puncture among volunteers. The private consortium then funded an ongoing extension of the original CSF study, which had planned to collect baseline and year 1 time points, to collect year 2 and 3 samples, as well. “The partnership has worked very well,” Buckholtz said. “The industry partners provide intellectual input. They do not push ADNI to their individual advantage.”
Importantly, ADNI data are open and freely accessible to a degree that is unprecedented in AD research. The study has an informatics core headed by Art Toga of the University of California, Los Angeles. Part of Toga’s charge was to build systems that make it possible for all 59 participating ADNI centers to upload their data to UCLA’s Laboratory of Neuro Imaging, and likewise, for any external scientist around the world who wants to analyze ADNI data to download it from the LONI site. ADNI’s clinical and neuropsychology data are available there, as well as its biomarker and imaging data. More than 32,000 MR and PET scans currently are on this site, and some 300 investigators have downloaded 340,000 images already, Weiner said during a lecture at ICAD. In addition, genetic data will be uploaded this October, according to Andrew Saykin of Indiana University School of Medicine, Indianapolis, who heads the genetics add-on studies, and some imaging data from the Australian AIBL study will follow in early 2009 (see Part 6 of this series).
ADNI is the first Alzheimer’s research study where scientists sitting at their computer anywhere in the world can obtain the data, analyze it, and then publish their results, without having to see a patient or tapping into a clinical system. “It is very easy to do a query and download images and associated cognitive and lab data,” wrote Sterling Johnson of the University of Wisconsin. “This accessibility reflects a shift in the way scientists think about the boundaries of data ownership. It also reflects the urgency we all feel about the growing problem of AD as the population ages, and the lack of effective interventions.” Beyond data, biofluids can be made available to non-ADNI scientists, as well. This access is tightly managed, however, because the fluids are precious and limited. ADNI’s resource allocation review committee welcomes requests, and assesses each individually.—Gabrielle Strobel.
This is Part 1 of a six-part series. See also Parts 2, 3, 4, 5, 6. Read the entire series [.pdf].
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Comment by: alessio dalla libera
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Submitted 25 October 2008
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Posted 29 October 2008
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Related Paper: Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects.
Comment by: Florian Muller
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Submitted 13 September 2009
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Posted 13 September 2009
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I recommend this paper
I wonder whether the segregation power of this assay would be further strengthened if a marker of gliosis (GFAP, Iba1) or neuronal cell lysis (neurofilament) were added to the set. View all comments by Florian Muller
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Related News: Boston: Drug Development Strategies for Neuro Diseases
Comment by: Ashley Bush
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Submitted 29 April 2009
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Posted 29 April 2009
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Barry Greenberg is quoted as saying “...[NAP] and Dimebon are the only [drugs] that have been reported in Phase 2 to improve patients over background rather than just slow the rate of decline....”
PBT2 should be added to this small but important list. It improved cognitive function above baseline within 12 weeks in a recent Phase 2 trial.
Ashley Bush on behalf of the PBT2 study group.
References: Lannfelt L, Blennow K, Zetterberg H, Batsman S, Ames D, Harrison J, Masters CL, Targum S, Bush AI, Murdoch R, Wilson J, Ritchie CW; PBT2-201-EURO study group. Safety, efficacy, and biomarker findings of PBT2 in targeting Abeta as a modifying therapy for Alzheimer's disease: a phase IIa, double-blind, randomised, placebo-controlled trial.
Lancet Neurology 2008; 7, 779-786. Abstract
View all comments by Ashley Bush
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Related News: ADNI: One-year Data Narrow Field of MRI, FDG-PET Approaches
Comment by: William Potter
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Submitted 22 May 2009
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Posted 22 May 2009
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I am wildly enthusiastic about the ADNI results to date and am confident that much more will emerge that can be tested in subsequent studies.
From my perspective, the one item of greatest relevance to industry that needs clarification is whether ADNI 1 data is sufficient to specify, at least provisionally, standardized approaches to MRI data. I emphasize this since we heard at the ADNI Data Presentations meeting that structural MRI could provide a biomarker of 25 percent drug effect on disease progression in a one-year trial using fewer than 100 subjects per arm.
Anyone wanting to implement this for internal decision-making would need to specify the exact measure and analytic plan. So, at some point it would be nice to say that ADNI 1 has provided us with a standard approach to set our primary measure. Others could be secondary. One could then include in ADNI 2 a test of whether the standardized approach we took holds up as the most robust and well-behaved measure in a subsequent study.
Obviously, if we all come to believe that the FDG-PET data is clear enough to...
Read more
I am wildly enthusiastic about the ADNI results to date and am confident that much more will emerge that can be tested in subsequent studies.
From my perspective, the one item of greatest relevance to industry that needs clarification is whether ADNI 1 data is sufficient to specify, at least provisionally, standardized approaches to MRI data. I emphasize this since we heard at the ADNI Data Presentations meeting that structural MRI could provide a biomarker of 25 percent drug effect on disease progression in a one-year trial using fewer than 100 subjects per arm.
Anyone wanting to implement this for internal decision-making would need to specify the exact measure and analytic plan. So, at some point it would be nice to say that ADNI 1 has provided us with a standard approach to set our primary measure. Others could be secondary. One could then include in ADNI 2 a test of whether the standardized approach we took holds up as the most robust and well-behaved measure in a subsequent study.
Obviously, if we all come to believe that the FDG-PET data is clear enough to support standardization around a single common approach, all the better. My sense was that more work remained to be done to have a reasonable expectation of a clear consensus in terms of setting a primary approach to generating and analyzing the data.
View all comments by William Potter
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Related News: ADNI: One-year Data Narrow Field of MRI, FDG-PET Approaches
Comment by: Michael Weiner
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Submitted 23 May 2009
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Posted 23 May 2009
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ADNI is a scientific project with scientific goals, and one of the goals is to find the best methods to use for clinical trials. We are accomplishing this. The ADNI data for structural MRI now show very clearly that the greatest rate of change is in the hippocampal area and that measurements of tissue in this area have the highest statistical power to detect change. This does not mean that this region is the best or only region that will be affected by a treatment. Hence, other measurements of the brain, including whole brain volume, should be included and considered.
Having consensus conferences to help standardize analytical methods would be a good idea, and I'd be happy to participate. But it has never been ADNI's role to define a standard or suggest a specific method. Here are some of the problems:
1. The field continues to emerge.
2. We only have one-year data so far. With two-year data, the results could be different.
3. Scientists are refining their methods as we speak.
4. There are all kinds of commercial and intellectual property issues. ADNI can be aware...
Read more
ADNI is a scientific project with scientific goals, and one of the goals is to find the best methods to use for clinical trials. We are accomplishing this. The ADNI data for structural MRI now show very clearly that the greatest rate of change is in the hippocampal area and that measurements of tissue in this area have the highest statistical power to detect change. This does not mean that this region is the best or only region that will be affected by a treatment. Hence, other measurements of the brain, including whole brain volume, should be included and considered.
Having consensus conferences to help standardize analytical methods would be a good idea, and I'd be happy to participate. But it has never been ADNI's role to define a standard or suggest a specific method. Here are some of the problems:
1. The field continues to emerge.
2. We only have one-year data so far. With two-year data, the results could be different.
3. Scientists are refining their methods as we speak.
4. There are all kinds of commercial and intellectual property issues. ADNI can be aware of these issues, but we cannot solve them.
5. It would be difficult to identify a method for brain structural analysis to recommend as the "standard" FDA method. There are so many competing methods. It is unclear at this point which would be the best method for clinical trials with patient populations different from those in ADNI, and each treatment may have its own different effects on the brain.
That said, I have suggested that the PET and MRI groups consider setting up consensus conferences to discuss how to standardize acquisitions, processing, and analysis for PET and MRI data for clinical trials. It will take time to achieve consensus. ADNI can lead continued discussion on standardization of such methods, but this is an expansion of the original goals of ADNI.
We are happy to expand, but with limited or even diminishing financial resources, we have to focus on our major goals:
1. Developing new scientific information.
2. Comparing different methods in different ways.
3. Developing clinical scenarios that help inform clinical trials.
4. Developing methods for early detection of AD.
Finally, I don't think we need a "standard method" right now. It would be nice, but we don't need it. Each trial that goes to the FDA specifies its methodology, and the FDA is very flexible about this. The ADNI data set provides a range of reasonable choices.
View all comments by Michael Weiner
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Related News: ADNI: One-year Data Narrow Field of MRI, FDG-PET Approaches
Comment by: Vincent Marchesi, ARF Advisor
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Submitted 25 May 2009
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Posted 26 May 2009
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It seems clear that modern scanning methods have essentially replaced the tissue diagnostic criteria of the autopsy in defining the anatomical changes that accompany clinical Alzheimer's dementia. It also appears, at least to an outsider, that what are believed to be early precursors to frank clinical disease might also be identified. If these results are confirmed and extended, they might be effective ways to monitor responses to therapy, an inability that now greatly hampers drug development.
But here are my concerns. Are these imaging methods capable of detecting the earliest pathologic changes that lead to clinical dementia? This is a hard question to address, since we don’t know what these earliest changes are, or when and where in the brain they occur. It seems that what is now needed are reliable and patho-physiologically relevant biomarkers. Measuring levels of Aβ and tau in the CSF has been correlated with existing clinical dementia, but why do we believe that they are reliable reporters of the earliest stages of the disease?
I am also surprised by the...
Read more
It seems clear that modern scanning methods have essentially replaced the tissue diagnostic criteria of the autopsy in defining the anatomical changes that accompany clinical Alzheimer's dementia. It also appears, at least to an outsider, that what are believed to be early precursors to frank clinical disease might also be identified. If these results are confirmed and extended, they might be effective ways to monitor responses to therapy, an inability that now greatly hampers drug development.
But here are my concerns. Are these imaging methods capable of detecting the earliest pathologic changes that lead to clinical dementia? This is a hard question to address, since we don’t know what these earliest changes are, or when and where in the brain they occur. It seems that what is now needed are reliable and patho-physiologically relevant biomarkers. Measuring levels of Aβ and tau in the CSF has been correlated with existing clinical dementia, but why do we believe that they are reliable reporters of the earliest stages of the disease?
I am also surprised by the absence of any discussion of blood-based biomarkers in the ADNI program. Are serum samples being collected and systematically stored for future studies? Surely any widespread clinical testing program will have to be based on more accessible clinical material than cerebrospinal fluid.
View all comments by Vincent Marchesi
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Related News: ADNI: One-year Data Narrow Field of MRI, FDG-PET Approaches
Comment by: William Potter
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Submitted 26 May 2009
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Posted 26 May 2009
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Reply to Michael Weiner
From a scientific viewpoint, I agree with Mike that we should remain open as to the best structural MRI method. But from an industry viewpoint, if the field can agree on a standard measure, it would make planning and powering registration studies much simpler. Gaining widespread industry appreciation of the value of ADNI 2 will be facilitated if we can agree that a "good enough" measure has been identified which we will see replicated and validated in this subsequent study. View all comments by William Potter
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Related News: ADNI: One-year Data Narrow Field of MRI, FDG-PET Approaches
Comment by: Michael Weiner
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Submitted 26 May 2009
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Posted 26 May 2009
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Reply to William Potter
All of us in ADNI recognize the importance of developing standard methods for performing clinical AD trials. We've made considerable headway with 1) standardized MRI acquisition, 2) standardized FDG-PET acquisition, and 3) use of the Luminex platform for blood/CSF biomarkers. Furthermore, following the meeting in Seattle there has been considerable discussion among ADNI Core leaders and others to set up some working groups that would address the standardization issues. We'll get there. View all comments by Michael Weiner
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Related News: CSF Biomarkers Track With Atrophy, Cognition in Normal Aging
Comment by: Agneta Nordberg
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Submitted 12 February 2010
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Posted 12 February 2010
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This is a study of 105 normal controls, 175 MCI, and 90 AD patients followed for on to two years. CSF biomarker and brain atrophy were used as predictive parameters for clinical changes in AD. Surprisingly the authors reported that MCI patients with CSF levels of Aβ42 comparable controls and of CSF tau below controls showed more atrophy than controls. The authors concluded that morphometry predicts cognitive progression better than CSF biomarkers.
I think it would have been interesting to know the mean ages of these patients (only age range is given).
CSF biomarkers, especially Aβ42, are considered to be (together with brain amyloid imaging by PET) comparable to atrophy changes. However, when studying the progression of the AD, disease atrophy as well as cerebral glucose metabolism better correlate with cognitive decline compared to CSF biomarkers. CSF Aβ42 could be considered as a biomarker to detect prodromal AD (preclinical AD), but there is no data so far that convincingly show changes in CSF Aβ levels with progression of the disease. Long-term...
Read more
This is a study of 105 normal controls, 175 MCI, and 90 AD patients followed for on to two years. CSF biomarker and brain atrophy were used as predictive parameters for clinical changes in AD. Surprisingly the authors reported that MCI patients with CSF levels of Aβ42 comparable controls and of CSF tau below controls showed more atrophy than controls. The authors concluded that morphometry predicts cognitive progression better than CSF biomarkers.
I think it would have been interesting to know the mean ages of these patients (only age range is given).
CSF biomarkers, especially Aβ42, are considered to be (together with brain amyloid imaging by PET) comparable to atrophy changes. However, when studying the progression of the AD, disease atrophy as well as cerebral glucose metabolism better correlate with cognitive decline compared to CSF biomarkers. CSF Aβ42 could be considered as a biomarker to detect prodromal AD (preclinical AD), but there is no data so far that convincingly show changes in CSF Aβ levels with progression of the disease. Long-term follow-up of PIB amyloid imaging (we have data up to five years) show stable amyloid levels in AD and MCI. We still have to perform more studies to obtain a deeper understanding of how these different biomarkers, for example CSF Aβ42, could be used as early biomarkers.
MCI patients with no changes in CSF Aβ42, but with atrophy, would have been interesting to study also with PIB imaging, and one can also question whether these MCI patients with atrophy but normal CSF Aβ42 could represent prodromal non-AD. I have examined several AD cases who have normal Aβ42 in CSF but high uptake of PIB in brain. These patients do very often show very little atrophy in the earlier stage of the disease.
View all comments by Agneta Nordberg
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