Given that the ultimate goal of ADNI is to develop biomarkers to facilitate clinical trials of AD therapeutics, it is germane to consider the perspective of those investigators in academia and the pharmaceutical industry on the development of these biomarkers. The aim of this section is to review those papers that focus on this issue.
While ADNI is a natural history study and it is not known whether its biomarkers can measure the effect of candidate treatments in drug trials, the primary focus of ADNI has been the development of diagnostic biomarkers for the early detection of AD and prognostic biomarkers that would be used to monitor disease progression [37
]. Mueller et al. [38
] and Weiner et al. [3
] reaffirmed the definition of an ideal biomarker formulated at the first meeting of the NIA working group on AD biomarkers which proposed that an ideal AD biomarker should detect a fundamental feature of AD pathology, be minimally invasive, simple to perform and inexpensive, and meet criteria with regard to specificity and sensitivity outlined in . Prognostic biomarkers should be representative of a stage of AD at which the treatment has maximal effect, and also be representative of the proposed mechanism of action of the treatment [3
Table 2 Characteristics of an ideal biomarker (adapted from  and ).
Both diagnostic and prognostic biomarkers are required for clinical trials. Such clinical trials have to date been frustratingly unsuccessful. It was thought that the failures of clinical trials of three high profile putative anti-amyloid therapies, flurizan and Alzhemed, were in part due to methodological difficulties such as the initial subject selection, and the statistical comparison of results from multiple centers [7
]. In the case of the first generation of clinical trials focusing on patients with MCI, there was a lack of consistency in numbers of patients progressing to AD over a certain time period, likely due to the heterogeneous nature of MCI; likely half of study participants did not have underlying AD pathology [7
]. Correctly distinguishing patients with AD pathology is critical, especially considering the overlap that exists between various late-life neurodegenerative pathologies. For example, the Lewy bodies that characterize Parkinson’s disease are found in more than 50% of patients with AD, in addition to neuritic plaques and tangles. There is therefore a real need for biomarkers that reliably distinguish between different types of dementias [8
Diagnostic biomarkers that meet the criteria outlined above are urgently needed for subject selection allowing the stratification and enrichment of clinical trials. There is a need to select subjects at an early stage of the Alzheimer’s continuum who are likely to progress through MCI to dementia, and also, to eliminate subjects with other pathologies. In phase I, II and III trials, biomarkers that detect the earliest indications of AD pathology, Aβ amyloid deposition, such as CSF Aβ42, and 11
C PiB PET are most likely to be useful. FDG-PET as a measure of metabolism could also have potential [41
The biomarkers used in a clinical trial will differ depending on the mechanism of action of the therapeutic, the goals of the trial, and questions at hand. In small, short Phase 1 trials, CSF and plasma measures can be used to monitor Aβ turnover in healthy subjects. In phase II Proof of Principle or Proof of Concept trials, Aβ amyloid biomarkers in brain can be used to confirm the mechanism of action of a new treatment and ‘target engagement’. For Phase II and III trials, CSF tau and phosphorylated tau, MRI, and Aβ amyloid PET can be used to determine whether there is evidence of an effect of treatment on disease progression. Clinical MRI is used routinely for subject selection, to exclude confounding medical conditions and detection of vasogenic edema as a safety endpoint of ‘immune’ based treatments [41
]. Finally, Aβ amyloid PET imaging, MRI, CSF and plasma biomarkers, and FDG-PET are candidates as prognostic biomarkers in Phase II trials for selection of non-demented subjects at risk for developing AD to test whether treatments have the potential of preventing or delaying the onset of AD. The predictive power of these biomarkers in isolation or in combination varies and will need to be factored into consideration. None of the current generation of treatments proposed to modify the progression of AD is free of safety concerns. Estimation of the probability of developing AD will be required for assessing the risk versus possible benefit of participating in research trials [41
]. shows ADNI biomarkers that could be used at different stages of the drug development process.
Looking at drug development as a whole, Cummings [37
] saw a wide variety of roles for biomarkers, from identifying disease pathology and tracking disease progression, to demonstrating pharmacokinetic effects of the body on the drug, to facilitating proof of principle and determining doses for subsequent trials, to determining drug efficacy, and finally in contributing to corporate decision making such as whether to proceed with riskier and more expensive later phase trials (). Fleisher et al. [9
] reviewed progress in developing neuroimaging biomarkers, either alone or in conjunction with CSF biomarkers for subject selection, and in developing biomarkers functioning at later stages in disease such as MRI measures of brain atrophy or changes in cerebral glucose metabolism detected by FDG-PET as outcome measures. This review also highlighted the need for biomarkers in drug development and discussed the use of imaging biomarkers in replacing cognitive endpoints in clinical trials.
Roles of biomarkers in AD drug development
Both common sense and regulatory policies of the FDA and regulators in other countries require that treatment trials need to demonstrate a significant effect on cognition and function. Although effects on biomarkers would provide additional evidence of treatment effect and evidence of disease modification, there are no validated surrogates for AD trials, and such surrogates will take many years to develop. Different biomarkers are likely to be effective over different phases of the disease [11
]. To be used as surrogates for clinical measures, biomarkers would need to be validated as reflecting clinical and/or pathological disease processes with a high degree of specificity and sensitivity. To qualify for validation as an outcome measure, the biomarker must be shown to predict clinical outcome over several trials and several classes of relevant agents by following subjects through disease progression and even possibly to autopsy [3
]. This validation process is likely to be aided by the contribution of ADNI to standardizing procedures, particularly for imaging techniques, to reduce measurement errors in clinical trials [42
]. A review by Petersen and Jack [11
] discussed neuroimaging and chemical biomarkers, either alone or in combination for the prediction of the development of dementia in MCI patients. They provided an excellent and succinct summary of the issues facing clinical trials for AD disease-modifying drugs and the role of both US and worldwide ADNI in developing biomarkers to facilitate these trials.
A detailed discussion of the position of the FDA on biomarker validation is given in Carrillo et al. [31
] and it is likely that the process will require a wider population of well-characterized subjects than is available through ADNI. To this end, and for the further study of therapeutic interventions for AD, Petersen [40
] proposed the establishment of a national registry of aging. In their editorial in the Journal of the American Medical Association, Petersen and Trojanowski [39
] introduced a paper that reports the evaluation of CSF biomarkers in a large multi-center study. Placing this in the context of other work in the same area and in research undertaken as part of ADNI, they concluded that as biomarkers become more sophisticated, they will play ever greater roles in AD clinical trials, and may one day be of used in clinical practice in a diagnostic capacity. Hill [41
] concluded in his perspective on neuroimaging and its role in assessing safety and efficacy of disease modifying therapies for AD: “…․there is now sufficient experience of imaging for Alzheimer’s disease in both natural history and therapeutic trials for a clear recipe for success to be emerging”. Weiner et al. [43
] concluded that the use of biomarkers to select cognitively normal subjects who have AD like pathology and as validated outcome measures in clinical trials “is the path to the prevention of AD”.
ADNI has proven to be a rich dataset for industry sponsored research including an assessment of disease progression in the Alzheimer’s disease population [44
]. ADNI data have been combined with additional placebo data from clinical trials conducted in AD and are publicly available on the Coalition Against Major Disease (CAMD) website (http://www.c-path.org/CAMDcodr.cfm
) for additional datamining. Modeling efforts have highlighted the importance of age, baseline cognitive status and APOE
status on disease progression rates and a model is currently under qualification review through newly developed EMA and FDA qualification procedures. These types of models will inform clinical trial design and streamline analysis for drug studies conducted in mild-moderate Alzheimer’s disease.
ADNI has also enabled clinical studies in predementia and many have been posted to www.clinicaltrials.gov
highlighting the use of CSF and amyloid PET biomarkers in cognitively impaired subjects to enrich for pre-dementia clinical trials. Application to registration level, Phase III studies remains a challenge as the biomarkers in ADNI have not yet been qualified for use or received regulatory approval. To address some of the remaining challenges, precompetitive and industry sponsored initiatives were recently conducted to qualify CSF Aβ42 and total tau as biomarkers for enrichment in predementia study with the EMA and a positive qualification opinion was posted on the EMA site for these particular biomarkers. Additional efforts are ongoing with the FDA. For the most part, industry has been utilizing the biomarkers as enrichment tools in predementia and mild-moderate AD studies and as secondary or exploratory efficacy measures to assess impact of exploratory drugs on biomarker measures of disease progression.