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Imaging biomarkers for amyloid: a new generation of probes and what lies ahead

Published online by Cambridge University Press:  13 February 2014

Antoine Leuzy
Affiliation:
Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, Montreal, Canada Alzheimer's Disease and Related Disorders Research Unit, McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, Montreal, Canada Email: [email protected]
Eduardo Rigon Zimmer
Affiliation:
Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, Montreal, Canada Alzheimer's Disease and Related Disorders Research Unit, McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, Montreal, Canada Email: [email protected] Department of Biochemistry, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
Venkat Bhat
Affiliation:
Department of Psychiatry, McGill University, Montreal, Canada
Pedro Rosa-Neto
Affiliation:
Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, Montreal, Canada Alzheimer's Disease and Related Disorders Research Unit, McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, Montreal, Canada Email: [email protected]
Serge Gauthier
Affiliation:
Alzheimer's Disease and Related Disorders Research Unit, McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, Montreal, Canada Email: [email protected]

Extract

Since the original 1984 criteria for Alzheimer's disease (AD), put forth by a work group jointly established by the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer's Disease and Related Disorders Association (ADRDA) (McKhann et al., 1984), important advances have occurred in our ability to detect AD pathophysiology, with the incorporation of biomarkers – defined as anatomic, biochemical, or physiologic parameters that provide in vivo evidence of AD neuropathology (Cummings, 2011) – that can improve the certainty of AD diagnosis. Use of imaging biomarkers such as positron emission tomography (PET) with amyloid ligands, particularly in asymptomatic and pre-dementia stages of AD, however, has been the subject of debate (Dubois et al., 2013), with arguments both for and against the biomarker driven diagnosis of AD.

Type
Guest Editorial
Copyright
Copyright © International Psychogeriatric Association 2014 

Introduction

Since the original 1984 criteria for Alzheimer's disease (AD), put forth by a work group jointly established by the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer's Disease and Related Disorders Association (ADRDA) (McKhann et al., Reference McKhann, Drachman, Folstein, Katzman, Price and Stadlan1984), important advances have occurred in our ability to detect AD pathophysiology, with the incorporation of biomarkers – defined as anatomic, biochemical, or physiologic parameters that provide in vivo evidence of AD neuropathology (Cummings, Reference Cummings2011) – that can improve the certainty of AD diagnosis. Use of imaging biomarkers such as positron emission tomography (PET) with amyloid ligands, particularly in asymptomatic and pre-dementia stages of AD, however, has been the subject of debate (Dubois et al., Reference Dubois, Gauthier and Cummings2013), with arguments both for and against the biomarker driven diagnosis of AD.

Revised conceptualization of AD: the role of amyloid imaging

In contrast to the original 1984 criteria the recently proposed revisions put forth by the International Working Group (IWG; Dubois et al., Reference Dubois2007) and the National Institute on Aging/Alzheimer's Association (NIA-AA; Sperling et al., Reference Sperling2011a) redefine AD as a clinicobiological entity, comprising a semantic and conceptual distinction between AD neuropathology and resulting clinical phenomenology. Currently, AD is conceptualized as a progressive pathophysiological process in which β-amyloid pathology is thought to accumulate during a silent “preclinical” phase followed by a dynamic cascade of neurodegenerative events including tau pathology, which ultimately cause cognitive impairment and dementia. This amyloidocentric framework incorporates the use of imaging biomarkers for amyloid in the form of abnormal PET amyloid tracer retention. The slow progression of β-amyloid deposition in AD supports the idea that amyloid pathology occurs very early in the disease process and tends to reach a plateau by the onset of the first clinical signs of dementia.

As novel amyloid directed therapeutics enter clinical trials, the role of amyloid imaging is increasingly clear given that its ability to allow for accurate, reliable, and reproducible quantification of both regional and global amyloid burden, and the growing consensus emerging from longitudinal studies that disease-modifying therapies targeting amyloid must be administered early on in the disease course (Sperling et al., Reference Sperling, Jack and Aisen2011b). In addition to serving as a diagnostic biomarker to guide population enrichment strategies, amyloid imaging can be used to calculate sample size and to increase statistical power via population stratification or through use as baseline predictors (Wu et al., Reference Wu, Rosa-Neto and Gauthier2011). In parallel, amyloid-imaging outcomes can serve as endpoint biomarkers to monitor the rate of disease progression, as well as response to therapy.

First generation of amyloid probes: 11C Pittsburgh Compound B

The 11C labeled thioflavin T derivative Pittsburgh Compound B (PIB) is the benchmark PET amyloid-imaging agent, demonstrating high sensitivity and specificity for in vivo quantification of fibrillar Aβ in both plaques and related Aβ containing lesions, such as diffuse plaques and cerebral amyloid angiopathy (Price et al., Reference Price2005; Lockhart et al., Reference Lockhart2007; Cohen et al., Reference Cohen, Rabinovici, Mathis, Jagust, Klunk and Ikonomovic2012). Importantly, on the basis of concentrations achieved during PET studies, cortical retention of 11C-PIB has been shown to reflect Aβ load as opposed to Lewy bodies or tau pathology (Fodero-Tavoletti et al., Reference Fodero-Tavoletti2007; Lockhart et al., Reference Lockhart2007; Ikonomovic et al., Reference Ikonomovic2008). In addition to accelerating current understanding of cerebral amyloidosis and advancing detection of AD pathology to an earlier stage (Klunk et al., Reference Klunk2004; Mintun et al., Reference Mintun2006; Rowe et al., Reference Rowe2007; Cohen et al., Reference Cohen, Rabinovici, Mathis, Jagust, Klunk and Ikonomovic2012), 11C-PIB has contributed to improvements in the differential diagnosis of neurodegenerative diseases (Ng et al., Reference Ng, Villemagne, Masters and Rowe2007; Rabinovici et al., Reference Rabinovici2007; Rowe et al., Reference Rowe2007). However, the short 20-minute half-life of carbon-11 probes limits their use to imaging centers possessing an onsite cyclotron and a radiochemistry department with expertise in the synthesis of 11C; the cost of 11C-PIB studies has precluded it's routine use in clinical settings.

Second and third generation amyloid probes: 18F-labeled radiopharmaceuticals

In order to address short half-life limitations a number of 18F labeled amyloid PET radiopharmaceuticals have been developed with a 110-minute half-life. Radiopharmaceuticals like [18F]3′-F-PIB (flutemetamol; Wolk et al., Reference Wolk2011), [18F]AV-45 (florbetapir; Clark et al., Reference Clark2012), [18F]-AV-1 or [18F]-BAY94–9172 (florbetapen; Rowe et al., Reference Rowe2008; Vallabhajosula, Reference Vallabhajosula2011), and [18F]AZD4694 or NAV4694 (Jureus et al., Reference Jureus2010; Cselenyi et al., Reference Cselenyi2012; Rowe et al., Reference Rowe2013) can facilitate the integration of PET into routine clinical use by allowing for centralized production and regional distribution (Rowe and Villemagne, Reference Rowe and Villemagne2013).

While 18F-florbetapir, 18F-florbetaben, and 18F-flutemetamol allow for clear differentiation of AD patients from healthy controls, cortical retention of 18F-florbetapir and 18F-florbetaben are inferior to that of 11C-PIB (Villemagne et al., Reference Villemagne2012) and are characterized by a more narrow dynamic range of standardized uptake value ratios (SUVRs), associated visually with elevated non-specific white matter (WM) binding (Vandenberghe et al., Reference Vandenberghe2010). Moreover, novel 18F amyloid tracers are associated with the loss of gray-white matter demarcation (Rowe and Villemagne, Reference Rowe and Villemagne2011), in contrast to 11C-PIB, where gray matter retention is visibly greater relative to subjacent WM uptake (Rowe and Villemagne, Reference Rowe and Villemagne2013). Though it has yet to pass through phase II trials, 18F-AZD4694 (NAV4694) is similar to 11C-PIB, possessing rapid kinetics, low non-specific WM binding, and a wider dynamic range when comparing AD to healthy control individuals (Cselenyi et al., Reference Cselenyi2012; Zimmer et al., Reference Zimmer2013). In a head-to-head comparison study with 11C-PIB among healthy controls and patients with AD and frontotemporal lobar degeneration (FTLD), 18FNAV4694 showed an r of 0.98 and a slope of 0.95, indicating significant overlap with 11C-PIB (Rowe et al., Reference Rowe2013).

Criteria for appropriate use of amyloid PET imaging

Given that 18F-florbetapir is now approved by the Food and Drug Administration (FDA) for the clinical assessment of individuals with cognitive impairment, with additional 18F tracers likely to become available in the coming years, appropriate use criteria (AUC) are of chief importance owing to (1) the potential for harm if scans are performed for inappropriate reasons, are misinterpreted, and/or the information obtained incorrectly applied; and (2) the high cost associated with such investigations. Apropos the first instance, a suitable example is the disclosure of amyloid positivity in an individual without cognitive impairment. Given positive findings in close to 30% of cognitively normal individuals over the age of 70 – and the lack of sufficient longitudinal data to adequately characterize the potential risk of future cognitive decline – premature diagnosis of AD on the basis of a positive Aβ scan alone has been categorized as inappropriate given the potential for detrimental social, psychological, employment, lifestyle, and financial consequences (Rowe and Villemagne, Reference Rowe and Villemagne2013). In addition, among patients with cognitive complaints, precipitous conclusions could lead to lack of appropriate treatment for underlying alternative causes, such as depression. Moreover, from an economic perspective, the lack of established disease-modifying therapies necessitates a careful cost-benefit analysis, with the likelihood of improved diagnostic accuracy and altered treatment guiding a decision to opt for amyloid imaging. In short, amyloid findings must be situated within the context of a comprehensive investigatory framework, interpreted by a physician with requisite expertise, and, where possible, supported by additional markers suggestive of AD such as an amnestic syndrome of the hippocampal type (Dubois and Albert, Reference Dubois and Albert2004), hippocampal atrophy on magnetic resonance imaging (MRI), or a parietotemporal pattern of hypometabolism on 18F-FDG PET.

Assembled in late 2012 by the Alzheimer's Association (AA) and the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the Amyloid Imaging Taskforce (AIT) was charged with delineating AUC for amyloid PET imaging using available literature and a consensus-based approach among dementia experts. On the basis of this approach amyloid imaging was deemed appropriate in the following clinical contexts: (1) patients exhibiting unexplained mild cognitive impairment (MCI) that is persistent or progressive, (2) patients fulfilling core criteria for possible AD yet with a clinical course that is atypical or an etiologically mixed presentation, and (3) patients with rapidly progressive dementia and atypically young age at the onset. In a sister publication (Johnson et al., Reference Johnson2013b), clarification and expansion of three topics were discussed in the original publication (Johnson et al., Reference Johnson2013a), including the practical identification of physicians possessing the expertise required for appropriate integration of amyloid PET imaging; the importance of identifying the specific subset of MCI individuals for whom amyloid PET imaging would prove appropriate; and the creation of developing education programs aiming to augment awareness of the amyloid PET AUC and how best to integrate this technique into clinical decision-making algorithms.

Potential ethical issues tied to disclosure of amyloid positivity

With the increasing paradigmatic shift toward the uncoupling of AD pathophysiology from resulting clinical phenomenology – with the attendant implication of a diagnosis of AD issued during the presymptomatic/minimally symptomatic phase – appropriate legal revisions must occur in parallel to guard against privacy and confidentiality infringements (Karlawish, Reference Karlawish2011). Guidelines must also be put in place to address the well-established stigma tied to AD, and to guide assessment of the potential for negative psychological sequelae in a given individual following disclosure of biomarker information conferring an elevated risk of AD (e.g. amyloid positivity).

Although researchers are currently not under obligation to disclose biomarker findings to research participants owing to uncertainty regarding the clinical utility of this information – a case in point being the Alzheimer's Disease Neuroimaging Initiative's (ADNI) “no return policy” – a move toward clinical trials and increasing calls for disclosure of research results from the public (Shalowitz and Miller, Reference Shalowitz and Miller2008) makes clear the need to accelerate the development of appropriate guidelines. This reorientation toward disclosure has been, furthermore, strengthened by recent findings suggesting that ADNI investigators support disclosure of amyloid imaging results – as well as, more generally, other biomarker findings – to ADNI participants (Shulman et al., Reference Shulman, Harkins, Green and Karlawish2013). In addition, despite a lack of evidence supporting the predictive value associated with imaging biomarkers, some clinicians have already begun incorporating IWG and NIA-AA research diagnostic criteria for asymptomatic at risk and MCI/prodromal into clinical practice (Gauthier and Rosa-Neto, Reference Gauthier and Rosa-Neto2013).

As the field of AD moves rapidly forward, a growing need exists in terms of the incorporation of procedures addressing disclosure of biomarker findings into large-scale studies and the encouragement of research addressing the impact of disclosure of biomarker findings (Gauthier and Rosa-Neto, Reference Gauthier and Rosa-Neto2013). Importantly, those ADNI investigators who endorsed disclosure likewise, in a majority of cases, highlighted the importance of developing standardized protocols and participant educational materials addressing disclosure, as well as longitudinal outcome studies to assess the effects of this information on the well-being of participants (Shulman et al., Reference Shulman, Harkins, Green and Karlawish2013).

Future directions

In research, amyloid-imaging agents can serve to enrich clinical trial populations, monitor disease progression, or assess the effect of amyloid-targeted interventions. While PET amyloid probes have yet to find application in routine general clinical practice, FDA approval of 18F florbetapir – with approval of additional 18F compounds likely in the coming years – requires careful adherence to, and promulgation of, current AUC. Moreover, as new data are gathered, and, in particular, should new effective therapies emerge, these criteria will likely require re-evaluation and, possibly, redefinition. In the interim, special care must be paid to the potential consequences associated with inappropriate use of amyloid PET imaging. Further, given the increasing attitudinal shift toward disclosure of research results it is vital that psychosocial research keep apace with developments in the area of AD biomarkers.

References

Clark, C. M. et al. (2012). Cerebral PET with florbetapir compared with neuropathology at autopsy for detection of neuritic amyloid-beta plaques: a prospective cohort study. Lancet Neurology, 11, 669678. doi:10.1016/S1474-4422(12)70142-4.Google Scholar
Cohen, A. D., Rabinovici, G. D., Mathis, C. A., Jagust, W. J., Klunk, W. E. and Ikonomovic, M. D. (2012). Using Pittsburgh Compound B for in vivo PET imaging of fibrillar amyloid-beta. Advances in Pharmacology, 64, 2781. doi:10.1016/B978-0-12-394816-8.00002-7.Google Scholar
Cselenyi, Z. et al. (2012). Clinical validation of 18F-AZD4694, an amyloid-beta-specific PET radioligand. Journal of Nuclear Medicine, 53, 415424. doi:10.2967/jnumed.111.094029.Google Scholar
Cummings, J. L. (2011). Biomarkers in Alzheimer's disease drug development. Alzheimer's & Dementia, 7, e1344. doi:10.1016/j.jalz.2010.06.004.Google Scholar
Dubois, B. and Albert, M. L. (2004). Amnestic MCI or prodromal Alzheimer's disease? Lancet Neurology, 3, 246248. doi: 10.1016/S1474-4422(04)00710-0.Google Scholar
Dubois, B. et al. (2007). Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurology, 6, 734746. doi:10.1016/S1474-4422(07)70178-3.Google Scholar
Dubois, B., Gauthier, S. and Cummings, J. (2013). The utility of the new research diagnostic criteria for Alzheimer's disease. International Psychogeriatrics, 25, 175177. doi:10.1017/S1041610212002098.CrossRefGoogle ScholarPubMed
Fodero-Tavoletti, M. T. et al. (2007). In vitro characterization of Pittsburgh compound-B binding to Lewy bodies. The Journal of Neuroscience, 27, 1036510371. doi:10.1523/JNEUROSCI.0630-07.2007.Google Scholar
Gauthier, S. and Rosa-Neto, P. (2013). Dementia: disclosure of results to participants in dementia research. Nature Reviews Neurology, 9, 608609. doi:10.1038/nrneurol.2013.213.Google Scholar
Ikonomovic, M. D. et al. (2008). Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer's disease. Brain, 131, 16301645. doi:10.1093/brain/awn016.Google Scholar
Johnson, K. A. et al. (2013a). Appropriate use criteria for amyloid PET: a report of the Amyloid Imaging Task Force, the Society of Nuclear Medicine and Molecular Imaging, and the Alzheimer's Association. Alzheimer's & Dementia, 9, e-116. doi:10.1016/j.jalz.2013.01.002.Google Scholar
Johnson, K. A. et al. (2013b). Update on appropriate use criteria for amyloid PET imaging: dementia experts, mild cognitive impairment, and education. Journal of Nuclear Medicine, 54, 10111013. doi:10.2967/jnumed.113.127068.Google Scholar
Jureus, A. et al. (2010). Characterization of AZD4694, a novel fluorinated Abeta plaque neuroimaging PET radioligand. Journal of Neurochemistry, 114, 784794. doi:10.1111/j.1471-4159.2010.06812.x.Google Scholar
Karlawish, J. (2011). Addressing the ethical, policy, and social challenges of preclinical Alzheimer disease. Neurology, 77, 14871493. doi:10.1212/WNL.0b013e318232ac1a.CrossRefGoogle ScholarPubMed
Klunk, W. E. et al. (2004). Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Annals of Neurology, 55, 306319. doi:10.1002/ana.20009.Google Scholar
Lockhart, A. et al. (2007). PIB is a non-specific imaging marker of amyloid-beta (Abeta) peptide-related cerebral amyloidosis. Brain, 130, 26072615. doi:10.1093/brain/awm191.Google Scholar
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D. and Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA work group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology, 34, 939944.Google Scholar
Mintun, M. A. et al. (2006). [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology, 67, 446452. doi:10.1212/01.wnl.0000228230.26044.a4.Google Scholar
Ng, S. Y., Villemagne, V. L., Masters, C. L. and Rowe, C. C. (2007). Evaluating atypical dementia syndromes using positron emission tomography with carbon 11 labeled Pittsburgh Compound B. Archives of Neurology, 64, 11401144. doi:10.1001/archneur.64.8.1140.Google Scholar
Price, J. C. et al. (2005). Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. Journal of Cerebral Blood Flow & Metabolism, 25, 15281547. doi:10.1038/sj.jcbfm.9600146.Google Scholar
Rabinovici, G. D. et al. (2007). 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology, 68, 12051212. doi:10.1212/01.wnl.0000259035.98480.ed.Google Scholar
Rowe, C. C. and Villemagne, V. L. (2011). Brain amyloid imaging. Journal of Nuclear Medicine, 52, 17331740. doi:10.2967/jnumed.110.076315.Google Scholar
Rowe, C. C. and Villemagne, V. L. (2013). Brain amyloid imaging. Journal of Nuclear Medicine Technology, 41, 1118. doi:10.2967/jnumed.110.076315.Google Scholar
Rowe, C. C. et al. (2007). Imaging beta-amyloid burden in aging and dementia. Neurology, 68, 17181725. doi:10.1212/01.wnl.0000261919.22630.ea.Google Scholar
Rowe, C. C. et al. (2008). Imaging of amyloid beta in Alzheimer's disease with 18F-BAY94–9172, a novel PET tracer: proof of mechanism. Lancet Neurology, 7, 129135. doi: 10.1016/S1474-4422(08)70001-2.Google Scholar
Rowe, C. C. et al. (2013). Head-to-head comparison of 11C-PiB and 18F-AZD4694 (NAV4694) for beta-amyloid imaging in aging and dementia. Journal of Nuclear Medicine, 54, 880886. doi:10.2967/jnumed.112.114785.Google Scholar
Shalowitz, D. I. and Miller, F. G. (2008). Communicating the results of clinical research to participants: attitudes, practices, and future directions. PLoS Medicine, 5, e91. doi:10.1371/journal.pmed.0050091.Google Scholar
Shulman, M. B., Harkins, K., Green, R. C. and Karlawish, J. (2013). Using AD biomarker research results for clinical care: a survey of ADNI investigators. Neurology, 81, 11141121. doi:10.1212/WNL.0b013e3182a55f4a.Google Scholar
Sperling, R. A. et al. (2011a). Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's & Dementia, 7, 280292. doi:10.1016/j.jalz.2011.03.003.Google Scholar
Sperling, R. A., Jack, C. R., Jr. and Aisen, P. S. (2011b). Testing the right target and right drug at the right stage. Science Translational Medicine, 3, 111cm133. doi:10.1126/scitranslmed.3002609.Google Scholar
Vallabhajosula, S. (2011). Positron emission tomography radiopharmaceuticals for imaging brain Beta-amyloid. Seminars in Nuclear Medicine, 41, 283299. doi:10.1053/j.semnuclmed.2011.02.005.Google Scholar
Vandenberghe, R. et al. (2010). 18F-flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial. Annals of Neurology, 68, 319329. doi:10.1002/ana.22068.Google Scholar
Villemagne, V. L. et al. (2012). Comparison of 11C-PiB and 18F-florbetaben for Abeta imaging in ageing and Alzheimer's disease. European Journal of Nuclear Medicine and Molecular Imaging, 39, 983989. doi:10.1007/s00259-012-2088-x.Google Scholar
Wolk, D. A. et al. (2011). Association between in vivo fluorine 18-labeled flutemetamol amyloid positron emission tomography imaging and in vivo cerebral cortical histopathology. Archives of Neurology, 68, 13981403. doi:10.1001/archneurol.2011.153.Google Scholar
Wu, L., Rosa-Neto, P. and Gauthier, S. (2011). Use of biomarkers in clinical trials of Alzheimer disease: from concept to application. Molecular Diagnosis & Therapy, 15, 313325. doi:10.2165/11595090-000000000-00000.Google Scholar
Zimmer, E. et al. (2013). [18F]NAV4694 shows higher binding and wider dynamic range compared with [11C]PiB in Alzheimer's disease postmortem tissue. Alzheimer's & Dementia, 9, P2223. doi:10.1016/j.jalz.2013.05.1161.Google Scholar