Shoghi-Jadid and colleagues at UCLA are to be congratulated for their publication in Am. J. Geriatric Psychiatry, which represents the first full publication of an attempt to image amyloid and neurofibrillary tangle (NFT) deposition with PET in Alzheimer's disease (AD) patients. This is a very important goal, since such a technique could provide important insights into the pathophysiology of AD and could aid in the early (perhaps even pre-clinical) diagnosis of AD and help evaluate the efficacy of anti-amyloid therapies currently in early clinical trials (Aβ immunization and secretase inhibitors).
Members of this same group, most notably Gary Small, have also made significant contributions to the use of [18F]FDG PET imaging of the regional cerebral metabolic rate for glucose rCMRglu for early diagnosis of AD. While both techniques use PET imaging and compounds with similar abbreviations, it is important to point out that these are very different technologies at very different stages of development. The UCLA group has recently published a widely publicized study (Silverman et al. 2001), in which they suggest that the well-established [18F]FDG imaging technique can identify abnormalities in glucose metabolism two-three years prior to the onset of AD. In the present study, Shoghi-Jadid et al. use the new amyloid-binding agent [18F]FDDNP, developed by corresponding author Jorge Barrio, in an attempt to specifically label deposits of amyloid plaques and NFT in living AD patients. [18F]FDDNP is an 18F derivative of a very lipohilic, viscosity- and solvent-sensitive compound called DDNP. Shoghi-Jadid et al. cross-sectionally study patients already diagnosed with AD, with mild to moderate severity, and make no claims of pre-clinical diagnosis—although they allude to that potential.
The UCLA group first presented similar data in preliminary form at scientific meetings over two years ago. These preliminary reports generated considerable controversy in the PET imaging community due to difficulty in interpreting the data, a difficulty that has not been entirely overcome in the current publication. Problems in interpreting the data arise in a number of areas and stem largely from the fact that human amyloid imaging data were presented prior to any significant in-vitro characterization of [18F]FDDNP. Critical characteristics such as percent specific binding to synthetic Aβ and to homogenates of post-mortem AD brain have never been addressed and represent the major problem in the human study, as well.
Other important characteristics such as: 1) quantitative binding affinity (Kd) and binding stoichiometry (Bmax) for synthetic Aβ fibrils; 2) reversibility of binding; 3) specificity for staining Aβ and NFT deposits in post-mortem AD brain; 4) quantitative differentiation of [18F]FDDNP binding to homogenates of AD, control and non-AD dementia brains; 5) peripheral and brain metabolism and pharmacokinetics of [18F]FDDNP in animals; 6) quantitative screening for binding to other CNS receptor sites; 7) validation using ex vivo and microPET studies in transgenic mice which deposit Aβ in the brain; and 8) toxicity (determined by standard toxicological studies normally required for FDA approval) were not reported before human studies were presented, and most of these issues remained poorly defined.
A recent online publication in the Journal of Neuroscience (Agdeppa et al., 2001) has addressed some of these issues. I discuss these Agdeppa et al. findings here because they have strong bearing on the major weakness of the human study, i.e., demonstrated binding specificity in vitro and in vivo to Aβ. In Agdeppa, binding affinity to synthetic Aβ was studied by a fluorescent technique that relies on the capacity of FDDNP to change its fluorescence properties in different environments (being a solvent- and viscosity-sensitive fluorophore). The fluorescence binding technique cannot measure specific vs. non-specific binding (a critical issue in the human studies discussed below). This is because of differences in fluorescence in the two environments (fluorescence was shown to increase upon binding to Aβ). Agdeppa et al. do briefly mention attempts at 18F binding determinations that show a 50-fold lower affinity, but still report no data on specific binding.
Specificity of fluorescent labeling of plaques and tangles in port-mortem AD brain is also difficult to interpret from the Agdeppa study, since the fields of view are cropped to contain only a single plaque or single NFT. Furthermore, NFTs are reported to stain faintly, leading one to conclude that most binding may represent Aβ deposits in plaques and cerebrovascular amyloid. Autoradiographic studies performed in AD and control brain with [18F]FDDNP were more impressive, but are somewhat tarnished by the need to use 90 percent ethanol to differentiate the binding from background. Even so, some of the [18F]FDDNP binding still shows a poor correlation with plaques and NFT deposits, most notably demonstrated by an intense area of [18F]FDDNP binding located over a hole in the tissue. Thus, many questions regarding the basic pharmacological and pharmacokinetic characteristics of [18F]FDDNP remain, as does the difficulty in interpreting the current study by Shoghi-Jadid et al.
Several points in the Shoghi-Jadid et al. study require further clarification. This study can be considered analogous to the many neuroreceptor studies commonly accomplished with PET ligands—with binding sites located on amyloid plaques and NFT being the "receptors" of interest. Results of PET neuroreceptor studies are typically quantified in terms of distribution volume (DV), which is proportional to the density of binding sites (Bmax in units of moles/1000 mL tissue).The radioactivity associated with a good neuroreceptor ligand will homogeneously distribute throughout the brain within minutes after bolus injection, and then clear more quickly from brain areas that lack receptor sites, leaving specifically bound ligand in areas rich in receptor sites. After allowing 60-90 minutes for clearance of free and non-specifically bound ligand, the differential in radioactivity concentration between receptor-rich and receptor-poor brain areas often exceeds 3-fold for good neuroreceptor ligands. In the Shoghi-Jadid study, [18F]FDDNP initially accumulates most in pons (an area without significant numbers of plaques or tangles) and least in hippocampus (an area of severe pathology). Five to 10 min after injection, the radioactivity in the pons exceeds that in the hippocampus by 1.6-fold. Differential clearance then results in a reversal and, at best, a 1.4-fold increase in residual radioactivity in hippocampus over the pons. Rather than presentation in standard DV terms, the authors use an unconventional parameter, the "relative residence time," to present their results. This parameter is affected both by the greater initial uptake as well as the more rapid clearance of [18F]FDDNP from the pons. The reasons given for not applying standard DV techniques of analysis are not at all convincing at the molecular level.
At some point, one must set the data analysis techniques aside and simply look at the pictures. Visual examination of the [18F]FDDNP images from human brain presented by Shoghi-Jadid et al. is remarkable for the lack of obvious specific localization of [18F]FDDNP to amyloid-rich brain areas and the intense localization in amyloid-poor regions such as the pons. This is the major weakness of this study.
Absence of imaging data in the cerebellum, a commonly used reference region for PET neuroreceptor studies, is a major oversight in the Shoghi-Jadi publication. This brain region is known to have very low densities of plaques and NFT's in AD subjects. Analysis of [18F]FDDNP binding kinetics in this region would be very helpful in understanding the nature of non-specific binding.
Another potential problem may arise from the very high lipophilicity of [18F]FDDNP (logPoct = 3.92), which is a full log unit above the optimum value for good brain imaging agents. A very high permeability across the blood-brain barrier (high PS value) may cause brain uptake and clearance to be dependent on regional cerebral blood flow—a characteristic of typical cerebral blood-flow imaging agents. This may be a partial explanation of the rapid accumulation and clearance in pons and occipital cortex and the relatively slow accumulation and clearance in hippocampus. Therefore, the potential blood flow dependence of the [18F]FDDNP results need to be carefully assessed.
Despite these difficulties, Shoghi-Jadid et al. manage to discern some remarkably significant differences of "relative residence times" between AD and control and remarkably significant correlations of "relative residence time" to cognitive performance, the most intriguing and strongest aspect of this study.
Given that the most significant weakness of this first human amyloid imaging agent, [18F]FDDNP, appears to be lack of demonstration of specificity, one can conclude the following. Either [18F]FDDNP is binding to a multitude of sites in addition to plaques and tangles that change in the same direction in AD vs. control, or the amyloid signal in AD brain is so intense that even a non-specific or weakly specific probe can demonstrate it. Keep in mind that the concentration of fibrillar amyloid deposits in AD brain is 100- to 1,000-fold higher than that of typical neurotransmitter receptors. Despite this, if the signal in AD brain is dominated by [18F]FDDNP binding to sites other than plaques and tangles, then any interpretation of the data remains open to question.
In spite of these problems, Shoghi-Jadid and colleagues at UCLA achieve an important milestone in being the first to attempt to image brain amyloid in human studies. Their early findings in this relatively small group of patients may or may not stand the test of time, but they certainly herald an era of a new technology for the study of amyloid deposition in living AD patients. Once fully developed by this or other groups of investigators, this technology could provide the first direct window into the characteristic neuropathology of AD in living patients - a pathology now seen only after death. Such technology could provide confirmatory diagnostic evidence in AD and perhaps even pre-clinical diagnosis, since amyloid deposition is thought to begin a decade or more before the first clinical symptoms of AD.
Perhaps the most important short-term use of this emerging imaging technology will be speeding the development of the eagerly awaited anti-amyloid therapies. By what better means can the effectiveness of these therapies at preventing or reversing amyloid deposition be determined in living subjects? How else can effective dose levels in a given patient be determined? Although this study must be regarded with the questions typical of many first attempts, it should be welcomed as breaking new ground in our fight against this terrible illness.
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I recommend this paper
