Neuroimaging biomarkers in Alzheimer’s disease and other dementias

Accepted Manuscript Title: Neuroimaging biomarkers in Alzheimer’s disease and other dementias Author: Victor L. Villemagne Ga¨el Ch´etelat PII: DOI: Reference:

S1568-1637(16)30004-6 http://dx.doi.org/doi:10.1016/j.arr.2016.01.004 ARR 635

To appear in:

Ageing Research Reviews

Received date: Revised date: Accepted date:

11-12-2015 21-1-2016 22-1-2016

Please cite this article as: Villemagne, Victor L., Ch´etelat, Ga¨el, Neuroimaging biomarkers in Alzheimer’s disease and other dementias.Ageing Research Reviews http://dx.doi.org/10.1016/j.arr.2016.01.004 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Neuroimaging biomarkers in Alzheimer’s disease and other dementias Running title: Aβ imaging, metabolism and inflammation Victor L. Villemagne MDa,b,d* [email protected], Gaël Chételat PhDd,e,f,g a

Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Victoria 3084, Australia. b Department of Medicine, University of Melbourne, Austin Health, Victoria 3084, Australia. c The Florey Institute of Neuroscience and Mental Health, Victoria 3052, Australia. d Institut National de la Santé et de la Recherche Médicale (Inserm), Unité 1077, Caen, France. e Université de Caen Basse-Normandie, Unité Mixte de Recherche (UMR), S1077, Caen, France. f Ecole Pratique des Hautes Etudes, UMR-S1077, 14000, Caen, France. g Unité 1077, Centre Hospitalier Universitaire de Caen, 14000, Caen, France. * Corresponding author at: Department of Nuclear Medicine, Centre for PET, Austin Health, 145 Studley Road, Heidelberg, Vic. 3084, Australia. Tel.: +61-3-9496 3321. Fax +61-3-9496 5663.

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ABSTRACT In vivo imaging of amyloid ( has transformed the assessment of  pathology and its changes over time, extending our insight into A deposition in the brain by providing highly accurate, reliable, and reproducible quantitative statements of regional or global A burden in the brain. This knowledge is essential for therapeutic trial recruitment and for the evaluation of anti- treatments. Although cross sectional evaluation of  burden does not strongly correlate with cognitive impairment, it does correlate with cognitive (especially memory) decline and with a higher risk for conversion to AD in the aging population and MCI subjects. This suggests that  deposition is a protracted pathological process starting well before the onset of symptoms. Longitudinal observations, coupled with different disease-specific biomarkers to assess potential downstream effects of A are required to confirm this hypothesis and further elucidate the role of  deposition in the course of Alzheimer‟s disease.

Keywords: Alzheimer‟s disease; A; positron emission tomography; neurodegenerative disorders; brain imaging

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1.

INTRODUCTION

Alzheimer‟s disease (AD) is a progressive and irreversible neurodegenerative disorder clinically characterized by memory loss and cognitive decline that severely affect the activities of daily living (Masters et al., 2006). AD is the leading cause of dementia in the elderly, leading invariably to death, usually within 7-10 years after diagnosis (Khachaturian, 1985). The progressive nature of the neurodegeneration suggests an age-dependent process that ultimately leads to synaptic failure and neuronal damage in cortical areas of the brain essential for memory and other cognitive domains (Isacson et al., 2002). AD not only has devastating effects on the sufferers and their caregivers, but it also has a tremendous socioeconomic impact on families and the health system; a burden which will only increase in the upcoming years as the population of most countries ages (Johnson et al., 2000). In the absence of reliable biomarkers, direct pathologic examination of brain tissue derived from either biopsy or autopsy remains the only definitive method for establishing a diagnosis of AD (O'Brien et al., 2000). The typical macroscopic picture is gross cortical atrophy, whilst microscopically, there is widespread cellular degeneration and diffuse synaptic and neuronal loss, accompanied by reactive gliosis and the presence of the pathological hallmarks of the disease: intracellular neurofibrillary tangles (NFT) and extracellular -amyloid () plaques (Jellinger, 1990; Masters, 2005; Masters and Beyreuther, 2005). Whilst NFT are intraneuronal bundles of paired helical filaments mainly composed of the aggregates of an abnormally phosphorylated form of tau protein, (Jellinger and Bancher, 1998; Michaelis et al., 2002) neuritic plaques consist of dense extracellular aggregates of , (Masters et al., 1985) surrounded by reactive gliosis and dystrophic neurites.  is a 4 kDa 39–43 amino acid metalloprotein derived from the proteolytic cleavage of the amyloid precursor protein (APP), by  and -secretases (Cappai and White, 1999). To date, all available genetic, pathological, biochemical and cellular evidence strongly supports the notion that an imbalance between the production and removal of leading to its progressive accumulation is central to the 3

pathogenesis of AD (Villemagne et al., 2006). The “Acentric theory” (Masters et al., 2006) postulates that A plaque deposition is the primary event in a cascade of effects that lead to neurofibrillary degeneration and dementia (Hardy, 1997), while other hypotheses postulate that A deposition occurs in parallel with other interacting pathological events, as a necessary, but not sufficient, cause of the pathological processes leading to AD dementia (Chetelat, 2013; Pimplikar et al., 2010; Small and Duff, 2008).

While biomarkers play a crucial role in the new diagnostic criteria for AD, (McKhann et al., 2011), the clinical diagnosis of AD is still largely based on progressive impairment of memory and decline in at least one other cognitive domain, as well as excluding other conditions that might also present with dementia such as frontotemporal lobar degeneration (FTLD), dementia with Lewy-bodies (DLB), stroke, brain tumour, normal pressure hydrocephalus or depression (Cummings et al., 1998; Larson et al., 1996). A variable period of up to five years of prodromal decline in cognition characterized by a relatively isolated impairment in recent episodic memory that may also be accompanied by impairments of working memory, known as amnestic Mild Cognitive Impairment (MCI), usually precedes the formal diagnosis of AD (Petersen, 2000; Petersen et al., 1999). At this point there is no cure for AD nor proven way to slow the rate of neurodegeneration. Symptomatic treatment with an acetylcholinesterase inhibitor or a glutamatergic moderator provides modest benefit in some patients usually by temporary stabilization rather than a noticeable improvement in memory function (Masters and Beyreuther, 2006).

2. A IMAGING IN ALZHEIMER’S DISEASE The development of PET tracers for  deposition has allowed in vivo assessment of  pathology. Since the first study published more than 10 years ago (Klunk et al., 2004), several hundreds of  PET studies have been performed, improving our knowledge on the 4

topography, timing, propagation, rates of accumulation and covariates of  accumulation in the living Human brain. On visual inspection, cortical 11C-PiB retention is usually higher in AD than in cognitively intact controls. Quantitative PET studies using diverse  radiotracers have shown a robust difference in retention between AD patients and age-matched controls (Barthel et al., 2011; Camus et al., 2012; Cselenyi et al., 2012; Fleisher et al., 2011; Furst et al., 2010; Jack et al., 2008a; Klunk et al., 2004; Kudo et al., 2007; Mintun et al., 2006; Morris et al., 2009; Pike et al., 2007; Price et al., 2005; Rabinovici et al., 2007; Rowe et al., 2010; Rowe et al., 2007; Villemagne et al., 2011a). The binding is more particularly elevated in frontal, cingulate, precuneus, striatum, parietal, and lateral temporal cortices, while occipital, sensorimotor and mesial temporal cortices are much less affected. Both quantitative and visual assessment of PET images present a pattern of radiotracer retention that seems to replicate the sequence of  deposition found at autopsy (Braak and Braak, 1997), with initial deposition in the orbitofrontal cortex, inferior temporal, cingulate gyrus and precuneus, followed by the remaining prefrontal cortex, lateral temporal and parietal cortices (Figure 1). Multimodal neuroimaging studies in early AD have shown that the regional pattern of  deposition is similar to the anatomy of the „default network‟, (Buckner et al., 2005; Sperling et al., 2009) a specific, anatomically defined brain system responsible for internal modes of cognition, such as self-reflection processes, conscious resting state, or episodic memory retrieval (Buckner et al., 2008; Wermke et al., 2008).

While the overall pattern of  deposition is roughly the same across different phenotypes, there are some particular cases associated with a particular regional distribution of 11C-PiB retention – e.g. carriers of mutations associated with familial AD have particularly elevated retention in subcortical gray matter nuclei, while congophilic angiopathy (CAA) and posterior

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cortical atrophy present a posterior pattern of tracer retention (Klunk et al., 2007; Koivunen et al., 2008b; Villemagne et al., 2009a). Longitudinal studies with 11C-PiB have shown that significant, albeit small, increases in  deposition can be measured, and that these increases in  deposition are present in the whole spectrum of cognitive stages, from cognitively unimpaired individuals to AD dementia patients (Engler et al., 2006; Jack et al., 2009; Okello et al., 2009b; Resnick et al., 2010; Rinne et al., 2010; Sojkova et al., 2011; Villain et al., 2012; Villemagne et al., 2011b). accumulation is also observed in individuals considered to have low  loads with about 7% of them progressing above the threshold in about 2.5 years (Vlassenko et al., 2011). In fact, both accumulators and non-accumulators could be identified, especially within individuals with low- deposition.  deposition has been estimated to take about 11 years for a PIB-negative subject to reach the threshold of PiB positivity (1·5 SUVR), and about 1520 years to go from this threshold to the levels usually observed in mild AD (Jack et al., 2013b; Villain et al., 2012; Villemagne et al., 2013). accumulation is thus a slow process that is thought to remain relatively constant across clinical stages i.e. similar in cognitively normal, and MCI accumulators (Jack et al., 2013b; Villemagne et al., 2013), yet tends to accelerate with increasing  load and to slow down, approaching a plateau, at the latest stages of amyloidosis (i.e. in individuals with highest  burden) (Jack et al., 2013b; Villain et al., 2012; Villemagne et al., 2013). This slower rate of  deposition might be attributed to a saturation of the process and/or to the extensive neuronal death that precludes production.

3. A DEPOSITION IN NON DEMENTED INDIVIDUALS AND ITS RELATION WITH COGNITION

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About 25-35% of elderly subjects performing within normal limits on cognitive tests present with high cortical

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C-PiB retention, predominantly in the prefrontal and posterior

cingulate/precuneus regions (Aizenstein et al., 2008; Mintun et al., 2006; Mormino et al., 2009; Reiman et al., 2009; Rowe et al., 2010; Rowe et al., 2007; Villemagne et al., 2008b). These findings are in perfect agreement with post mortem reports that ~25% of non-demented older individuals over the age of 75 have A plaques, (Davies et al., 1988; Forman et al., 2007; Morris and Price, 2001). Furthermore, the prevalence of subjects with high

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C-PiB

retention increases each decade at the same rate as the reported prevalence of plaques in nondemented subjects in autopsy studies (Rowe et al., 2010). Within patients with MCI, approximately 50-70% present with high cortical

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C-PiB retention (Forsberg et al., 2008;

Jansen et al., 2015; Kemppainen et al., 2007; Klunk, 2011; Lowe et al., 2009; Mormino et al., 2009; Pike et al., 2007; Price et al., 2005). Most studies found that subjects classified as nonamnestic MCI, especially the single-domain subtype, show low  levels in the brain consistent with a non-AD underlying pathological process (Lowe et al., 2009; Pike et al., 2007), although other reports did not (Wolk et al., 2009). The detection of A pathology at the presymptomatic stage is of crucial importance in order to both identify the group that may benefit the most from therapies aimed at reducing or eliminating  from the brain, as well as assess the potential effects of  deposition on cognition and/or neurodegeneration at the early stages of the disease process (Chetelat et al., 2010a; Chetelat et al., 2012).

Numerous cross-sectional studies have assessed the relationships between Adeposition and memory performances in demented and non-demented populations. While there is general agreement that Aburden does not correlate with memory impairment or disease severity at the dementia stage, the assessment of controls is more controversial, with studies reporting small or no significant relationships (Aizenstein et al., 2008; Jack et al., 2008a; Mintun et al., 2006; Rowe et al., 2010), while others reporting one (Pike et al., 2007; Sperling et al., 2012), 7

often restricted to specific conditions (e.g. only in females (Pike et al., 2011); only in nonApoE4 carriers (Pike et al., 2011); mainly in APOE4 carriers (Kantarci et al., 2012), or in low-educated individuals (Rentz et al., 2010). Some reports even found higher performance in Apositive controls compared to the A-negative (Chetelat et al., 2010b). In MCI patients, there is a more general agreement for a link between high Aburden and lower episodic memory performance (Mormino et al., 2009; Ong et al., 2013; Pike et al., 2007). The inconsistency in the findings of the relationship between Aand cognition might reflect several, sometimes convergent, sometimes divergent, facts i) Aimaging measures the aggregated fibrillar form of Awhile it has been postulated that only the soluble form of Ais toxic; ii) it is the presence but not the quantity of A deposition that matters; iii) fibrillar A is not directly causing cognitive impairment, but indirectly through other pathological processes, such as tau, that in turn drives neurodegeneration (f.e., A-related cognitive impairment was shown to be mediated by hippocampal atrophy in MCI patients (Mormino et al., 2009; Villeneuve et al., 2014; Wirth et al., 2013). Moreover, iv) cognitive reserve has been shown to impact not only on Adeposition but also on its association to cognition or neuronal injury (Rentz et al., 2010; Roe et al., 2008). Finally, it is also possible that v) the delay between A accumulation (which might start more than 15 years before the onset of dementia) and cognitive deficits/neurodegeneration (which generally occur later) prevents the detection of a link between these measures in cross-sectional studies. At the AD stage, there seems to be no longer correlation between glucose metabolism, cognition and  burden (Furst et al., 2010). This might reflect the fact that Ahas almost reach a plateau, or that the dose-dependent relationship of A to cognition and neurodegeneration only occurs in the early stage of amyloidosis (see also (Chetelat et al., 2010a)). While the results of cross-sectional studies relating A and cognition are discrepant, findings are more consistent in longitudinal studies assessing the effects of A deposition and later

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change on cognitive decline and/or disease progression. Thus, high 11C-PiB cortical retention in non-demented elderly subjects is consistently associated with a greater risk of cognitive decline (Resnick et al., 2010; Villemagne et al., 2011b; Villemagne et al., 2008b). For example, the evaluation of either the cognitive trajectories (Resnick et al., 2010; Villemagne et al., 2008b) or changes in cognition prospectively (Doraiswamy et al., 2012b; Morris et al., 2009; Villemagne et al., 2011b) show that cognitively intact individuals with substantial  deposition are more likely to present with cognitive decline. Studies in MCI patients show that about 40-80% of MCI subjects with high

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C-PiB retention progressed to AD over 2-3

years, being >10 times more likely to progress to AD than those with low A burden, highlighting the clinical relevance and potential impact in patient management of Aβ imaging (Doraiswamy et al., 2012a; Doraiswamy et al., 2014; Forsberg et al., 2008; Okello et al., 2009b; Ong et al., 2015; Rowe et al., 2013; Villemagne et al., 2011b; Wolk et al., 2009). 4. RELATION OF A IMAGING WITH OTHER BIOMARKERS

Another rapidly growing area is the exploration of the potential association between A burden as measured by PET, and CSF biomarkers of A deposition or neuroimaging biomarkers of neurodegeneration (Albert et al., 2011; Blennow et al., 2007; Clark et al., 2008; de Leon et al., 2006; Jack et al., 2010; McKhann et al., 2011; Morris et al., 2005; Shaw et al., 2007; Storandt et al., 2012; Sunderland et al., 2005; Thal et al., 2006; Wahlund and Blennow, 2003)(Jack et al., 2010; Jack et al., 2008a).

4.1

CSF

Analysis of CSF allows simultaneous measurement of the concentration of the two main hallmarks of AD, A and tau. It has been reported to be highly accurate in the diagnosis of AD as well of predicting cognitive decline (Blennow et al., 2007; de Leon et al., 2007; Hansson et al., 2007; Mattsson et al., 2011; Mattsson et al., 2009). The typical CSF profile in 9

AD is low A1-42 and high total (t-tau) and phosphorylated tau (p-tau) (Hampel et al., 2010; Strozyk et al., 2003). Slower A clearance from the brain (Bateman et al., 2006; Mawuenyega et al., 2010) is likely to lead to A deposition in the brain and lower CSF A concentrations. While there is no correlation between

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C-PiB retention and CSF t-tau or p-

tau (Forsberg et al., 2010; Tolboom et al., 2009), several studies have reported a strong inverse correlation between A deposition in the brain as measured by 11C-PiB and CSF A142

(Fagan et al., 2006; Fagan et al., 2009; Fagan et al., 2007; Forsberg et al., 2008; Grimmer et

al., 2009; Koivunen et al., 2008a). Overall, there is about an 88% agreement between PIBPET and CSF in classifying cases as positive or negative, agreement that is higher (94%) in demented patients. Longitudinal A imaging and CSF studies have shown than while A accumulation in the brain followed a sigmoidal trajectory (Jack et al., 2013b; Villemagne et al., 2013), decreases in CSF A1-42 did not (Toledo et al., 2013). Moreover, a positive CSF in the absence of Adetected at PET is more frequent than the reverse. This likely reflects the fact that each technique is measuring a different pool of A(Toledo et al., 2015). While A imaging measures an insoluble fibrillar form of A, CSF measures reflect a more soluble diffusible form of A suggesting that changes in soluble A occur first (Toledo et al., 2013).

4.2

MRI

Hippocampal and cortical grey matter atrophy along with ventricular enlargement are typical MRI findings in AD and MCI (Drago et al., 2011; Frisoni et al., 2010). Furthermore, it has been shown that the rates of hippocampal atrophy might be predictive of conversion from MCI to AD (Jack et al., 2008b). The relationships between  deposition measured with PET and atrophy measured with MRI appears to be more complex and intricate. In AD, no relationship is usually found between deposition and atrophy (La Joie et al., 2012), and no association has been observed between hippocampal A load and hippocampal atrophy at any stage of the disease 10

spectrum. When comparing A-negative to A-positive non-demented individuals, results are rather discrepant with studies reporting hippocampal atrophy in the elderly with high global PiB (Jack et al., 2008a; Storandt et al., 2009) while others did not (Bourgeat et al., 2010; Dickerson et al., 2009). Similarly, significant correlations between global neocortical PiB and hippocampal atrophy has been reported in normal controls and MCI patients in some studies (Bourgeat et al., 2010; Mormino et al., 2009; Rowe et al., 2010), but not in others (Bourgeat et al., 2010; Dickerson et al., 2009). Moreover, between-group differences or correlations were inconsistently found in other brain areas, e.g. in the temporal pole (Dickerson et al., 2009) or anterior and posterior cingulate cortex (Becker et al., 2011; Storandt et al., 2009) or prefrontal and lateral parietal cortex (Becker et al., 2011). Interestingly, when assessing the links between regional A deposition and local atrophy (voxelwise), a significant relationship was found in the posterior cingulate-precuneus and anterior cingulate-medial prefrontal areas (with a trend in the temporo-parietal area), i.e. in the regions of highest  deposition (Chetelat et al., 2010a). This relationship was only found in elderly with subjective cognitive impairment but not in the MCI or in the AD patients, suggesting that this relationship occurs at a very particular stage of the disease, before objective memory impairment can be demonstrated. Also, a reverse relationships (larger temporal lobe volume in individuals with high A deposition) was found in the cognitively intact elderly, which might reflect brain reserve (Chetelat et al., 2010b). As mentioned above, education was found to modify the relation of plaques to cognition so that highly educated subjects have less susceptibility to -related cognitive impairment than those with lower education (Bennett et al., 2003; Rentz et al., 2010). It is thus possible that the high-PiB healthy controls represent those subjects with particularly high brain reserve reflected by larger brain (temporal) volume allowing them to better and/or longer tolerate the presence of A deposition. Moreover, the relationships between deposition and neurodegeneration might be further complicated by a different susceptibility/vulnerability to  at either a cellular - frontal neurons seems to be more 11

resistant to  than hippocampal neurons - (Resende et al., 2007; Roder et al., 2003), and/or by a regional compensatory upregulation of choline acetyltranserase (ChAT) activity in the frontal cortex and hippocampi of MCI and early AD subjects (DeKosky et al., 2002).

4.3

FDG

In FDG studies the typical „AD pattern‟ is of temporoparietal and posterior cingulate hypometabolism with sparing of the basal ganglia, thalamus, cerebellum, and primary sensorimotor cortex (Coleman, 2005; Devanand et al., 1997; Jagust et al., 2007; Salmon et al., 1994). Due to its high sensitivity (>90%) for detecting temporoparietal and posterior cingulate hypometabolism FDG-PET has improved diagnostic and prognostic accuracy in patients with probable AD (Kennedy et al., 1995a; Salmon et al., 1994; Silverman et al., 2002; Silverman et al., 2001; Small et al., 1995). A similar pattern of hypometabolism has been reported in MCI, (Chetelat et al., 2003; Chetelat et al., 2005; Mosconi et al., 2006a) asymptomatic subjects with mutations associated with familial AD, (Kennedy et al., 1995b; Rossor et al., 1996) and in subjects with a strong family history of AD (Mosconi et al., 2006b). FDG hypometabolism is correlated with cognition (Furst et al., 2010; Landau et al., 2009) and is predictive of future cognitive decline (Drzezga et al., 2005; Drzezga et al., 2003; Mosconi et al., 2004).

Overall, results regarding the relationships between FDG and A are similar as those between atrophy and A. Thus, no relationship is usually found in AD (La Joie et al., 2012) and discrepant findings are reported in non-demented individuals. Some studies found a significant link between PIB and local metabolism in the parietal and temporal cortex (Cohen et al., 2009; Edison et al., 2007; Klunk et al., 2004) but other studies reported no correlation in any brain region (Forsberg et al., 2008; Furst et al., 2010). In a recent report in a large sample of controls, MCI and AD assessing regional associations between A and hypometabolism, the authors concluded that regional fibrillar A deposition has little to no 12

association with regional hypometabolism showing that correlations were rather negative and low (or inexistent) in AD and healthy controls, but mostly positive in MCI patients (Altmann et al., 2015). As mentioned before for the temporal lobe volume (Chetelat et al., 2010b), this finding suggests that higher basal metabolism could reflect a reserve mechanism allowing to tolerate more A deposition while not showing cognitive impairment.

4.4

Neuroinflammation

Microglia are the primary resident immune surveillance cells in the brain and are thought to play a significant role in the pathogenesis of several neurodegenerative disorders including AD (Venneti et al., 2006). Activated microglia can be measured using radioligands for the translocator protein (TSPO), formerly known as the peripheral benzodiazepine receptor. The TSPO is upregulated on activated macrophages and microglia, and has been established as a biomarker of neuroinflammation in the central nervous system. Most reports found that in AD there is no association between A deposition and microglial activation measured by [11C]PK11195 (Edison et al., 2008a; Okello et al., 2009a; Wiley et al., 2009), while there is an association between [11C]PK11195 binding and both glucose hypometabolism and severity of dementia (Edison et al., 2008a; Yokokura et al., 2011). Another study used the MAO-B inhibitor L-deprenyl as a PET marker for astrocytosis, together with PIB to measure A, but no regional correlations were found between both PET tracers (Carter et al., 2012).

On hypotheses and facts (and their interpretation) Different hypotheses have been postulated on the sequence of biomarker changes leading to AD dementia (Jack et al., 2013a; Teipel et al., 2015) The dominant view of the physiopathological mechanisms underlying AD is that Aβ triggers a cascade of events that eventually leads to neurofibrillary tangle formation, followed by synaptic and neuronal injury and finally cognitive decline (Hardy, 1992; Hardy and Selkoe, 2002). Translating this

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theoretical model in a biomarker model, it has been proposed that in preclinical AD,  deposition appears first, followed by biomarkers of neuronal injury (including FDG-PET hypometabolism and/or hippocampal atrophy), and then cognitive decline (Jack et al., 2013a; Jack et al., 2010). This biomarker model has been translated in criteria for preclinical AD with three stages corresponding to Aβ (CSF or PET) only (stage 1, A+N-), Aβ plus neuronal injury (stage 2, A+N+) and Aβ, neuronal injury and subtle cognitive change (stage 3) (Sperling et al., 2011a). In support of this Aβ-centric hypothesis we observe that: i) all known forms of autosomal-dominant AD involve genes related with the production of Aβ; ii)  deposition is detected with PET in normal individuals with no evidence of cognitive impairment or neuronal injury (Chetelat et al., 2013; Jack et al., 2012); iii)  deposition has been shown to be a slow and protracted process that starts >20 years before the onset of dementia (Jack et al., 2013b; Villain et al., 2012; Villemagne et al., 2013); iv) preclinical  deposition is associated with a higher rate of atrophy and conversion to MCI and AD (Chetelat et al., 2013; Chetelat et al., 2012; Morris et al., 2009).

However, the repeated and dismal record of therapeutic trials failures (Cummings et al., 2014; Doody et al., 2014; Doody et al., 2013; Salloway et al., 2014) and more specifically the lack of positive effects of anti- therapy on neuronal injury and/or cognitive markers casts serious doubts not only on the alleged efficacy of the therapeutic agents but also on Aβ as the single driver of the disease process. The other main counterargument have risen from neuropathology studies who have demonstrated that “tau comes first”, that tau pathology is found in the brain of cognitively normal elderly devoid of Aβ, and even reported evidence for tau pathology in children and young adults, decades before Aβ deposition (Braak and Braak, 1991, 1997; Braak and Del Tredici, 2011; Duyckaerts, 2011). To harmonize the biomarker model with the neuropathological evidence, a modified version of the model has been proposed where tau pathology in the mesial temporal cortex appears before Aβ, but at a 14

subthreshold level, not yet detectable with biomarkers (Jack et al., 2013a). According to this updated model, Aβ appears later but is detectable first, so the proposed sequence of biomarkers remains unchanged. However, several lines of evidence from neuroimaging studies are seen as not consistent with this view. More specifically, the postulated sequence of “Aβ first” has been questioned. First, regional variation in the relative degree of atrophy, hypometabolism and Aβ deposition, and low relationships between Aβ and neurodegeneration markers rather support to the view that AD is a multi-causal disease with different possible pathways and sequences of events (La Joie et al., 2012). Second, some cognitively normal elderly have evidence of neuronal injury without Aβ (A-N+). They have been classified as having “suspected non-AD pathophysiology” (SNAP) as they didn‟t fit with the postulated sequence of biomarker. As i) some of these patients will developed MCI and dementia (Knopman et al., 2012) while they don‟t present with more markers of non-AD pathophysiological processes (Knopman, 2013) ii) some A-N+ will convert to A+N+ and/or AD and iii) multimodal neuroimaging studies showed evidence for AD-like neurodegeneration independently from, or before, Aβ deposition (Altmann et al., 2015; Bateman et al., 2012; Jack et al., 2013c; Jagust et al., 2012; Reiman et al., 2012; Sheline et al., 2010), eventually, both Aβ-first and neurodegenerationfirst models of late-onset AD have been postulated (Chetelat, 2013; Jack and Holtzman, 2013). Another issue to be considered carefully is perithrehold values for both Aand neurodegeneration, that results in a classification that might not truly reflect the underlying pathological process(es). Yet, the debate remains on whether or not this AD-like neurodegeneration is part of the AD spectrum or not. As nicely phrased by Jack (Jack, 2014), “Some in the imaging/biomarker community argue that evidence of -amyloid deposition is required to label an individual as being in the “AD pathophysiological pathway” on the basis of biomarkers and hence SNAP is correctly labeled a non-AD condition. Others argue that because the neurodegenerative biomarkers in SNAP are AD-like, SNAP represents a “pre

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fibrillar amyloid” part of the AD spectrum.” Still another position is to consider that, being labelled AD or not, the same should applied to both A+N- and A-N+, as there is no more reason to call preclinical AD the A+N- than the A-N+. Longitudinal studies will help clarify this issue.

This has led to the postulation of alternative models (Chetelat, 2013; Pimplikar et al., 2010; Small and Duff, 2008), re-opening intensive debates around the question of the role and relationships between tau and Aβ (Chetelat, 2013; Fox, 2012; Scheltens, 2013; Vishnu, 2013; Weiner, 2013). It has been proposed for instance that both cortical Aβ and mesial temporal tau-related pathological processes may occur independently of each other (Chetelat, 2013; Duyckaerts, 2011) and that, under the influence of environmental, genetic or yet unknown factors, they interact to promote the pathological processes leading to AD dementia (Chetelat, 2013). These models postulate that all neuroimaging biomarkers (atrophy, hypometablism, A deposition) should be considered as carrying the same weight, independently from the sequence they appear, where the addition of each biomarker is reflected in an incremental risk of progression to AD.

Neuroimaging (and especially A neuroimaging) offers an unique opportunity to test in vivo and longitudinally many of our hypotheses that could hardly be tested before. Yet, we have to remember that we are measuring macroscopic events detectable with neuroimaging techniques that are all limited by a sensitivity threshold and some measures that are just the end product of a biological/pathological process, not the biological process per se. Moreover, most of the results are amenable to multiple, even contradictory interpretations, where the same reports are cited in support of different hypotheses. So we need to be cautious.

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Yet, encompassing these two different broad perspectives on AD physiopathology and biomarkers sequence, the following sequence proposed by Jack (Jack, 2014) seems to cover all aspects of what is known –and not yet known- to date: 1.

Most often before any significant A deposition, tau starts accumulating in the mesial

temporal cortex. Everyone in the population develops tau deposition at some point early in life. By itself, however, tau deposition in the mesial temporal cortex produces none to mild clinical symptomatology. 2.

Independently from tau accumulation in the mesial temporal cortex, A starts

accumulating in neocortical areas. 3.

At some point in time, A and tau interact, through some yet undetermined

mechanism(s), triggering the spreading of tauopathy from mesial temporal to widespread neocortical association areas that parallels progression of cognitive decline towards dementia. 4.

Progression of neurodegeneration and severe clinical symptoms reflect the accelerated

and expanding neocortical tauopathy, independently from the degree of A deposition.

Ongoing longitudinal studies will help identify those subjects that despite substantial A deposition do no develop the AD phenotype, thus allowing to isolate genetic or environmental factors that may convey resistance to A (Sojkova and Resnick, 2011). Perhaps selective tau imaging will help elucidate or bridge the gap between A deposition and the persistent decline in cognitive function observed in AD (Johnson et al., 2015; Villemagne et al., 2012). Preliminary A and tau imaging studies suggest that high cortical A and high hippocampal tau burden can be present in cognitively unimpaired individuals, suggesting that significant cognitive impairment is only observed when tau spreads into neocortical association areas (Delacourte et al., 2002; Villemagne et al., 2014).

17

5. A IMAGING IN OTHER NEURODEGENERATIVE CONDITIONS

A imaging in a wide spectrum of neurodegenerative conditions has allowed the assessment of the presence or absence in these different conditions. Although slightly lower than in AD, similar patterns of

11

C-PiB retention are usually observed in DLB (Gomperts et al., 2008;

Maetzler et al., 2009; Rowe et al., 2007). Cortical 11C-PiB retention, specifically in occipital areas, is also higher in subjects diagnosed with CAA (Johnson et al., 2007), while there is usually no cortical

11

C-PiB retention in patients with FTLD (Drzezga et al., 2008; Engler et

al., 2008; Rabinovici et al., 2007; Rowe et al., 2007).

8.1

Cerebral Amyloid Angiopathy

CAA, characterized by Aβ deposits in and around the media of small arteries and arterioles of the cerebral cortex and leptomeninges has been found to be present in most patients with AD (Jellinger and Attems, 2005). To this date, neuropathologic examination of the brain remains the only definitive method for diagnostic confirmation of CAA. However the combination of A imaging with 11C-PiB-PET and T2* susceptibility weighted (SWI) MR imaging (Knudsen et al., 2001) allows for the concomitant assessment of molecular and structural changes invivo. The combination of cerebral microhaemorrhages (MH) and superficial siderosis (SS) have been suggested as radiological markers for CAA (Feldman et al., 2008). A imaging studies have shown that both processes may be intimately associated with A deposition (Dhollander et al., 2011; Dierksen et al., 2010), preferentially in posterior areas of the brain, showing a distinct pattern of

11

C-PiB retention than the one observed in sporadic AD

(Johnson et al., 2007). Furthermore, focal A deposition might be useful in predicting new MH in CAA patients (Gurol et al., 2012). While deep subcortical MH are generally associated with vascular risk factors (VRF), lobar MH (particularly posterior) (Pettersen et al., 2008), are usually attributed to CAA (Knudsen et al., 2001; Vernooij et al., 2008). Lobar MH are a 18

frequent finding in AD patients or even in cognitively-normal older individuals, and they are strongly associated with increasing age and Aβ deposition (Yates et al., 2011). This association between A and vascular lesions has crucial implications not only for the selection and risk stratification of individuals undergoing anticoagulant therapies, but also in those enrolled in anti-A therapeutic trials (Weller et al., 2009).

8.2

Lewy Body Diseases

While AD is the most common cause of dementia in the elderly, DLB accounts for 20% of the cases (McKeith et al., 2005). The pathological hallmark of DLB is the presence of synuclein containing Lewy bodies (LB) within the neocortical and limbic regions, (McKeith et al., 2005) as well as substantial loss of pigmented dopaminergic neurons in the substantia nigra, reflected in a marked dopaminergic terminal denevation in the striatum (McKeith and Mosimann, 2004). More refined neuropathological techniques have revealed extensive synaptic deposits of -synuclein, more concordant with the DLB clinical phenotype than the usually sparse cortical LB (Schulz-Schaeffer, 2010). The overlap of cognitive symptoms early in the disease course of both AD and DLB present a challenge for clinicians that might find the differential diagnosis difficult to make. Post mortem histopathological studies have identified that 50-80% of DLB cases often have cortical A deposits with characteristics and a distribution similar to AD patients (Edison et al., 2008b; McKeith et al., 2005; Rowe et al., 2007). This has also been described as „mixed‟ DLB/AD or „Lewy body variant of AD‟. Socalled „pure‟ DLB is much less common and it is not clear if the clinical characteristics and prognosis differ from the mixed-pathology cases. On visual inspection, cortical

11

C-PiB

retention in DLB is generally lower and more variable than in AD, probably reflecting a larger spectrum of  deposition (Gomperts et al., 2008; Maetzler et al., 2009; Rowe et al., 2007). Therefore A imaging is not a useful tool in differentiating between AD and DLB, but

19

might assist in the differential diagnosis of those cases („pure‟ DLB) without A deposition in the brain (Armstrong et al., 2000). The contribution of A to the development of Lewy body diseases remains unclear, but cortical A deposits are associated with extensive -synuclein lesions and higher levels of insoluble -synuclein lesions (Pletnikova et al., 2005), as well as exacerbation of neuronal injury (Masliah et al., 2001). While A imaging cannot contribute to the differential diagnosis between AD and DLB, it may have prognostic relevance in these Lewy body diseases. For example,  burden in DLB patients was inversely correlated with the interval from onset of cognitive impairment to the full development of the DLB phenotype (Rowe et al., 2007).

8.3

Frontotemporal Lobar Degeneration

FTLD is a syndrome that can also be clinically difficult to distinguish from early onset AD, especially at the initial stages of the disease. Based on clinical phenotype, FTLD has been categorised mainly into two classes: behavioural variant of FTLD (bvFTLD) with distinct changes in behaviour and personality with little effect on language functions, and progressive aphasias (comprised by semantic dementia (SD), progressive non-fluent aphasia (PNFA), and logopenic aphasia (LPA)) showing progressive language deficits, with less obvious personality and behavioural changes (Rabinovici and Miller, 2010).

A deposition is not a pathological trait of FTLD, and definitive differential diagnosis can only be established after post mortem examination of the human brain. Neuropathological examination of the brain in FTLD shows variable frontal and temporal atrophy (Cairns et al., 2007; Hodges and Patterson, 2007; Snowden et al., 2007), microvacuolation and neuronal loss, with white matter myelin loss, astrocytic gliosis as well as neuronal and glial inclusions (Cairns et al., 2007). Three intraneuronal inclusion types have been identified in FTLD: (i) hyperphosphorylated tau (FTLD-tau), (ii) ubiquitin-hyperphosphorylated and proteolysed 20

TAR-DNA binding protein 43 (FTLD-TDP-43) and (iii) fused sarcoma positive (FUS) (Mott et al., 2005; Neumann et al., 2009; Neumann et al., 2006; Taniguchi et al., 2004). Taupositive inclusions account for approximately 40% of all FTLD cases, the remainder being tau negative and TDP-43/ubiquitin positive (Josephs et al., 2004). In bvFTLD, both tau and TDP-43 are equally prevalent; and while 90% of the SD cases show TDP-43 pathology, PNFA presents predominantly (70%) tau pathology (Josephs et al., 2004; Mackenzie et al., 2008). In contrast, LPA is though to be a language presentation of AD, with typical A and NFT (Leyton et al., 2011).

A imaging has been helpful in the differential diagnosis between FTLD and AD (Drzezga et al., 2008; Engler et al., 2008; Rabinovici et al., 2007; Rowe et al., 2007). Furthermore, A imaging has been used to ascertain the absence of AD pathology in the different FTLD aphasias (Drzezga et al., 2008; Leyton et al., 2011; Rabinovici et al., 2008). Despite displaying similar specificities, the diagnostic performance of A imaging proved to be more sensitive for the diagnosis of FTLD than FDG (Rabinovici et al., 2011).

8.4

Prion Diseases

No cortical 11C-PiB retention was observed in sporadic Creutzfeldt-Jakob disease (CJD) cases (Villemagne et al., 2009b). Due to the rapid progression and relatively short duration of symptomatic illness, sporadic CJD patients do not demonstrate appreciable PrP-plaque deposition at autopsy (Liberski, 2004). Although some sporadic CJD molecular sub-types can manifest larger PrP plaques (Hill et al., 2003), the most common subtype usually demonstrates only very fine “synaptic” and small perivacuolar deposits (Hill et al., 2003; Liberski, 2004). A preliminary study in transmissible spongiform encephalopathies showed that A imaging with 11C-BF227 might be able to distinguish between Gerstmann-Straussler-

21

Scheinker disease (GSS) and sporadic CJD disease with clear tracer retention in brain regions of PrP deposition (Okamura et al., 2010).

6. A

IMAGING

IN

THE

DEVELOPMENT

OF

DISEASE-SPECIFIC

THERAPEUTICS

Aβ imaging with PET is also contributing to the development of more effective therapies by allowing better selection of patients for anti-A therapy trials and providing a means to measure their impact on A burden (Ostrowitzki et al., 2011; Rinne et al., 2010). While these studies represent one of the principal applications of A imaging, they have brought forward an issue that needs to be addressed, namely that the advent of novel A tracers with differing pharmacological and pharmacokinetics properties, summed to the diverse arsenal of quantitative approaches and contrasting criteria for the selection of internal scaling region pose a challenge when trying to compare results from therapeutic trials that use different Atracers or quantitative tools.

Another aspect to be considered is prediction of therapeutic response. As new therapies enter clinical trials, the role of A imaging in vivo is becoming increasingly crucial.  imaging allows the in vivo assessment of brain  pathology and its changes over time, providing highly accurate, reliable, and reproducible quantitative statements of regional or global A burden in the brain. As mentioned before, therapies, especially those targeting irreversible neurodegenerative processes, have a better chance to succeed if applied early, making early detection of the underlying pathological process so important. Therefore, Aβ imaging is an ideal tool for the selection of adequate candidates for anti-Aβ therapeutic trials, while also monitoring -and potentially predicting- treatment response, thus aiding in reducing sample size, minimizing cost while maximizing outcomes. Preliminary studies are already showing 22

the utility of this technique (Ostrowitzki et al., 2011; Rinne et al., 2010). These preliminary results, taken together with the results from longitudinal studies, support the growing consensus that anti-Aβ therapy to be effective may need to be given early in the course of the disease, perhaps even before symptoms appear, (Sperling et al., 2011b) and that downstream mechanisms may also need to be addressed to successfully prevent the development of AD. Furthermore, the slow rate of A deposition indicates that the time window for altering A accumulation prior to the full manifestation of the clinical phenotype may be very wide (Villemagne et al., 2011b).

The contribution of Aβ imaging to the selection of patients for therapeutic trials needs to be complemented with adequate MRI sequences such as SWI or gradient recalled echo (GRE) for the detection of vascular pathology to rule out the possibility of vascular complications such as  related imaging abnormalities (ARIA), either as "vasogenic edema" and/or sulcal effusion (ARIA-E), or as hemosiderin deposits including MH and SS (ARIA-H) (Cordonnier, 2010; Sperling et al., 2011c). The presence of MH is impacting on patient selection in therapeutic trials, and some anti-Aβ immunotherapy trials are already excluding individuals with MH. To make matters worse, about one third of non-demented individuals with high Aβ burden and no prior history of cerebrovascular disease showed MH (Yates et al., 2011). While focal Aβ deposition might be a better predictor of a vascular event (Gurol et al., 2012), only longitudinal follow up of large cohorts of patients will allow elucidation of the relevant risk factors for lobar MH.

Finally, and given that there is no cure for AD, diagnosing the presence or absence of AD pathology in vivo raises ethical issues. While the presence of  deposition has undoubtedly been associated with a significantly greater risk of cognitive decline, there is still not enough longitudinal data available to attach a firm prognostic clinical significance to a “positive”

23

scan. This is especially true in cognitively normal elderly. In this situation, is it ethical to disclose the  scan result while it is not associated with a diagnosis so that it is an information on the risk of AD but not on the diagnosis? Also, is it ethical to deliver this information while there is no treatment that has proven efficacy against AD pathological process yet? Of course, this is useful for anti- clinical trials that are on-going, but these are still on the development/research stages. From the patient perspective, it is important to take into account their right to know, as well as their right not to know. More work is needed to evaluate the psychological impact of  PET result disclosure and determine the right way to disclose this information, as well as to further anticipate related societal and legislative impacts.

7. CODA

The clinical diagnosis of AD is typically based on progressive cognitive impairments whilst excluding other diseases. Clinical diagnosis of sporadic disease is challenging, however, often presenting mild and non-specific symptoms attributable to diverse and overlapping pathology presenting similar phenotypes. Overall, the accuracy of clinical diagnosis of AD compared to neuropathological examination ranges between 70-90% (Beach et al., 2012). While clinical criteria, together with current structural neuroimaging techniques (CT or MRI), are sufficiently sensitive and specific for the diagnosis of AD at the mid to late stages of the disease, they are focused on relatively non-specific features such as memory and functional activity decline or brain atrophy. Confirmation of diagnosis of AD still relies on autopsy. But how reliable is pathology? How much of a “gold standard” is autopsy? (Jellinger, 2010; Scheltens and Rockwood, 2011). A more sensible paradigm, adopting a more fluid model that integrates all cognitive, biochemical and imaging biomarkers that can provide a better predictive framework, has been proposed in the new diagnostic criteria for AD, (Dubois et al.,

24

2010; McKhann et al., 2011; Sperling and Johnson, 2010) MCI, (Albert et al., 2011) and preclinical AD (Sperling et al., 2011a). Along the same lines, Scheltens and Rockwood suggest that “a shift in focus from why people with AD have plaques and tangles to why not all people with plaques and tangles have AD would be welcome” (Scheltens and Rockwood, 2011). While most people with AD pathology develop AD dementia, there are some that while having the pathology do not. What makes them different? What conveys resistance to some or, conversely, what makes others more vulnerable to the same pathological burden? Identifying these factors will allow a more discerning selection of individuals that will benefit from early intervention with anti-A medication, while also providing insights into potential preventive strategies or even new therapeutic approaches (Sojkova and Resnick, 2011; Sperling et al., 2011b). While the new diagnostic criteria has blurred once again the boundaries between MCI and AD (Morris, 2012), it also allows for earlier diagnosis and therapeutic intervention, arguing that when there is a clear history of progressive cognitive decline, objective evidence from psychometric tests of episodic memory impairment and characteristic abnormalities in the CSF and/or neuroimaging studies such as A imaging, dementia might not be required for the diagnosis of probable AD (Dubois et al., 2010; McKhann et al., 2011; Sperling and Johnson, 2010). Thus, as the criteria for the diagnosis of AD changes, A imaging is likely to play an increasingly important role in clinical practice provided it is accessible and affordable (Villemagne and Rowe, 2010).

The pathological process usually begins decades before symptoms are evident, making it difficult to identify individuals at the earliest stage of pathology. This in turn precludes early intervention with disease-modifying medications during the presymptomatic period, which by arresting neuronal loss would presumably achieve the maximum benefits of such therapies (Villemagne et al., 2008a). Therefore, a change in the diagnostic paradigm is warranted, where diagnosis moves away from identification of signs and symptoms of neuronal failure –

25

indicating that central compensatory mechanisms have been exhausted and extensive synaptic and neuronal damage is present – to the non-invasive detection of specific biomarkers for particular traits underlying the pathological process (Clark et al., 2008). Given the complexity and sometimes overlapping characteristics of these disorders, and despite recent advances in molecular neurosciences, it is unlikely that a single biomarker will be able to provide the diagnostic certainty required for the early detection of neurodegenerative diseases like AD. Therefore, a multimodality approach combining biochemical and neuroimaging methods is warranted (Shaw et al., 2007).

ACKNOWLEDGEMENTS This work was supported in part by grant 1071430 of the National Health and Medical Research Council (NHMRC) of Australia. VLV is supported by the NHMRC through a Senior Research Fellowship. The Institut National de la Santé et de la Recherche Médicale (Inserm), the Fondation Plan Alzheimer (Alzheimer Plan 2008-2012), Programme Hospitalier de Recherche Clinique (PHRC National 2011, complément PHRC 2012), Agence Nationale de la Recherche (ANR LONGVIE 2007), and Région Basse Normandie also supported this work.

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Figure Captions

Figure 1: Left: Schematics showing the stages of A deposition in the human brain as proposed by Braak and Braak (Braak and Braak, 1997) Right: Representative surface projection PET images showing the regional brain distribution of

11

C-PIB in two asymptomatic healthy age-matched controls (HC), one with low and one

with high A burden, a subject classified as mild cognitive impairment (MCI) with significant A deposition in the brain, and an Alzheimer‟s disease (AD) patient with even a higher A burden in the brain. The pattern of

18

F-NAV4694 retention replicates the sequence of 

deposition described from post-mortem studies (Braak and Braak, 1997).

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