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doi: 10.1111/joim.12192
Pathways to Alzheimer’s disease J. Hardy1, N. Bogdanovic2, B. Winblad3, E. Portelius4, N. Andreasen3, A. Cedazo-Minguez3 & H. Zetterberg1,4 From the 1Department of Molecular Neuroscience, Reta Lila Weston Research Laboratories, UCL Institute of Neurology, London, UK; 2 Section of Clinical Geriatrics, Karolinska Institutet; 3KI-Alzheimer Disease Research Center, Karolinska Institutet, NVS, Stockholm; and 4Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
Abstract. Hardy J, Bogdanovic N, Winblad B, Portelius E, Andreasen N, Cedazo-Minguez A, Zetterberg H (UCL Institute of Neurology, London, UK; Karolinska Institutet, Stockholm; Karolinska Institutet, NVS; and The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden). Pathways to Alzheimer’s disease. (Key Symposium). J Intern Med 2014; 275: 296–303. Recent trials of anti-amyloid agents have not produced convincing improvements in clinical outcome in Alzheimer’s disease; however, the reason for these poor or inconclusive results remains unclear. Recent genetic data continue to support
Introduction There is no doubt that for the last 20 years, the amyloid cascade hypothesis has dominated opinion about the aetiology and pathogenesis of Alzheimer’s disease (AD), as well as guided the efforts to find treatments. However, in the last 2 years, several clinical trials of agents targeting amyloid-b (Ab), including two c-secretase inhibitors (semagacestat and avagacestat) and two anti-Ab antibodies (bapineuzumab and solanezumab), have failed to reach their primary clinical endpoints. These trials have produced ambivalent results, with positive findings only in ad hoc secondary end-points, and have led to divergent opinions on whether it is worthwhile persevering with Ab therapies or whether this approach should be abandoned. It is not the primary purpose of this review to discuss these issues although we will offer our opinion. Rather, as the initial evidence supporting the amyloid cascade hypothesis came from genetic analysis of individuals with Down syndrome and autosomal dominant AD, our primary purpose is to assess more recent genetic data from genome-wide association studies and exome sequencing to consider the potential additional drug targets highlighted by these analyses
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the amyloid hypothesis of Alzheimer’s disease with protective variants being found in the amyloid gene and both common low-risk and rare high-risk variants for disease being discovered in genes that are part of the amyloid response pathways. These data support the view that genetic variability in how the brain responds to amyloid deposition is a potential therapeutic target for the disease, and are consistent with the notion that anti-amyloid therapies should be initiated early in the disease process. Keywords: Alzheimer’s disease, amyloid, cell biology, genetics, tau.
and discuss how they relate to the amyloid pathway. Deciphering the results of clinical trials of semagacestat, bapineuzumab and solanezumab The amyloid cascade hypothesis of AD, first postulated in the early 1990s, incorporates histopathological, genetic and biochemical information. It posits that the deposition of Ab in the brain parenchyma, due to an imbalance between the production and clearance of Ab initiates a sequence of events that ultimately lead to AD dementia [1–5]. The accumulation of Ab in the brain is thus the primary force driving the AD pathogenesis. The hypothesis is not simply an academic construct and will only have been useful if it leads to effective clinical management of the disease. Against this background, it is essential to reach a conclusion as soon as possible as to whether the results of clinical trials reported to date support or refute this hypothesis, or are inconclusive. A number of anti-Ab strategies are discussed below. Semagacestat and avagacestat Semagacestat and avagacestat are c-secretase inhibitors. c-Secretase has more than a hundred substrates including Notch, and we now know that
there is almost no selectivity of these drugs for different substrates. Therefore, the fact that cognitive decline was worse in the treatment arm, compared with placebo, in these trials is difficult to interpret at present [6–8]. Bapineuzumab and solanezumab The antibodies bapineuzumab and solanezumab target different epitopes at Ab. Bapineuzumab is a humanized monoclonal IgG1 antibody against the Ab N-terminus (Ab1–5), based on the murine antibody 3D6, which was intended to promote Ab clearance from the brain [9]. Solanezumab, on the other hand, is a humanized version of the mouse monoclonal antibody m266, raised against Ab13–28 [10, 11]. It differs from bapineuzumab in several ways. First, it recognizes various N-terminal truncated species (such as Ab4–42) that are known to exist alongside full-length Ab1–42 in AD plaques [12]. Secondly, whereas bapineuzumab binds amyloid plaques more strongly than soluble Ab, solanezumab selectively binds to soluble Ab with little or no affinity for the fibrillar form [13]. Thirdly, in small Phase I and Phase II studies [11], there was no clinical, cerebrospinal fluid (CSF) biomarker or imaging evidence of meningoencephalitis or vasogenic oedema, the latter of which has been a problem with bapineuzumab. Bapineuzumab had no clinical efficacy [9]. However, it was associated with reduced amyloidbinding as evidenced by Pittsburgh Compound B and decreased CSF tau levels suggesting that there was some reduction in neuronal damage, which was not clinically useful, at least in the Phase III trial that was recently stopped. However, it is important to note that 38% of enrolled patients did not fulfil criteria for AD. Likewise, in the overall analysis, solanezumab did not have an effect on clinical outcome. However, in the group of patients with mild AD, there was a small reduction in clinical worsening but this was not associated with a reduction in CSF tau levels. Taken together, the two antibody studies produced inconclusive results, which makes it difficult to draw any firm conclusions on whether or not the approach will be effective. Other issues concerning these and future trials As others have noted, all these trials illustrate the difficulties in testing the amyloid hypothesis [7, 14]. A consensus is emerging that drug candidates
Key Symposium: Pathways to Alzheimer’s disease
need to be administered early in the disease process in drug-na€ıve patients with AD, and possibly in carriers of amyloid precursor protein (APP) and PSEN1 and PSEN2 mutations. However, achieving the goals set out by this consensus is extremely challenging from an organizational and ethical perspective. APP and PSEN1 and PSEN2 mutation carriers are rare, and apart from the extended presenilin 1, pedigree in Colombia are under the care of a large number of clinical centres each of which has few patients. Many mutation carriers do not want to know their mutation status, complicating their involvement in clinical trials. Furthermore, these trials require extended clinical follow-up and sufficient patient numbers with high enough conversion rates. Despite these difficulties, randomized controlled trials on AD prevention (e.g. ADCS-A4, API and DIAN) are already underway, as discussed in other articles of this themed issue. Recent genetic data and the implications for pathways to AD A summary of all the currently known genetic loci for AD is shown in Fig. 1. APP and presenilin variability The role of APP and presenilin mutations in causing early AD has long been recognized. However, genetic analysis of late-onset AD has surprisingly revealed that these mutations are also pathogenic factors in some cases [15, 16]. Indeed, given the prevalence of late-onset disease, it is likely that there are more cases of disease with ages over 60 years who have APP and PSEN1 and PSEN2 Causes Alzheimer´s disease
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Fig. 1 Risk loci for Alzheimer’s disease. Adapted from Manolio et al. [20]. ª 2014 The Association for the Publication of the Journal of Internal Medicine Journal of Internal Medicine, 2014, 275; 296–303
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mutations than early-onset disease, although they still account for 3.0
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All the above loci were found by genome-wide association studies, except TREM2 that was found by exome sequencing.
[37]. Finally, the findings of recent studies suggest that ApoE may also affect AD risk by immunomodulation, which may make individuals more or less vulnerable to build-up of amyloid in the brain [38, 39]. Recent APP transgenic mouse data have clearly shown that experimental manipulation of brain cholesterol metabolism has therapeutic potential [40]. Recently, a unique aspect in the relationship between APP and cholesterol metabolism has emerged. Cholesterol forms a complex with the Ab domain of APP, suggesting that strategies aimed at preventing the binding of cholesterol to APP may have therapeutic potential in AD [41]. Moreover, a novel role of APP in neurons as been identified in controlling cholesterol biosynthesis and turnover, indicating for the importance of synaptic function in damage repair [42] Table 1. Indeed, the findings of genetic studies have implicated several genes related to cholesterol synthesis, transport, uptake or metabolism (i.e. APOE, ABCA7, ABCA1, CLU and CYP46A1) in AD [24, 43, 44]. This evidence suggests that altered cholesterol levels, transport and cellular distribution are intimately linked to amyloid accumulation and AD pathogenesis. However, a complete understanding of the exact underlying mechanisms is still lacking. The links between cholesterol and AD pathogenesis are summarized in Fig. 2.
Decreased synaptogenesis and repair
Fig. 2 Cholesterol-related pathways to Alzheimer disease (AD). Evidence supporting that altered cholesterol levels, transport and cellular distribution contribute to amyloid accumulation and AD pathogenesis: (i) The interplay between brain cholesterol homeostasis and Ab formation. (ii) Novel findings from GWAS on genes related to cholesterol metabolism (APOE, ABCA7, ABCA1, CLU, CYP46A1) in AD. (iii) The lack of function of apoE4 in transporting cholesterol to neurons and in clearing Ab from the brain. An unbalanced neuronal cholesterol homeostasis would lead to decreased synaptogenesis and repair mechanisms.
The innate immune system Neuropathological analysis of AD brains has long indicated a role of the complement cascade in the pathogenesis of AD [45] and indeed Ab has been shown to activate the complement cascade [46]. Morphological characteristics of an inflammatory response include a clustering of activated microglia and complement factors within amyloid plaques. Fibrillary amyloid can bind complement factor C1 and activate the classical complement pathway without involvement of antibodies [47, 48]. Inflammatory proteins contribute to pathological processes in the AD brain, including amyloid homeostasis, gliosis and phosphorylation of tau. Inflammation may have both beneficial effects, such as phagocytosis, and detrimental effects, such as off-target actions on neighbouring cells. Inflammation is a relatively early pathogenic event, which was revealed by neuroradiological and neuropathological observations in patients with mild cognitive impairment [49, 50]. Astroglia and microglia both play a crucial role in innate immunity and use Toll receptors to recognize fibrillar amyloid. Both types of receptors, Toll-like and CD14, are innate receptors that mediate activation of transcription factors and production of pro-inflammatory cytokines. Stimulation of the innate immune system reduces parenchymal and vascular amyloid. The innate ª 2014 The Association for the Publication of the Journal of Internal Medicine Journal of Internal Medicine, 2014, 275; 296–303
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immune system can be activated by interaction of amyloid and LDL in both AD and atherosclerosis; the latter is a major risk factor for late-onset AD. Thus, activated microglia can be, at the same time, in two functionally different activated states either as pro-inflammatory (detrimental) or involved in repair of the brain. Increased CSF levels of complement factors and microglial activation markers have been described in AD [51–53] but longitudinal data to determine the sequence of these alterations in relation to the onset of amyloid deposition and neurotoxicity markers are lacking. On the other hand, genetic analysis has now clearly shown that variability in innate immunity is an important determinant of risk of AD with several loci, for example the complement receptor 1 (CR1), clusterin and TREM2, mapping to this system [24]. Exome sequencing Exome sequencing has the potential to identify high-risk loci for disease. The expense and analytical burdens that these large-scale sequencing projects entail have only recently begun to be overcome and the first data from what will undoubtedly be a large number of projects are starting to be reported. Rare, heterozygous loss of function mutations in the TREM2 gene have very recently been found to increase the risk of AD by up to fivefold [26, 54]. TREM2 has being shown to suppress the inflammatory response by inhibiting cytokine production and secretion in microglia [55]. TREM2 is also involved in the regulation of phagocytic pathways that are responsible for the removal of cell debris and possibly of amyloid. Thus, a lack of function of TREM2 could result in increased systemic inflammation, damage of neurons and accumulation of amyloid. The findings of these studies, and of those mentioned above, point to the microglial activation state as a key determinant of the pathogenesis of AD. Recently, Pottier and colleagues [56] found a high frequency of potentially pathogenic SORL1 mutations in autosomal dominant early-onset AD. SORL1 is an important mediator of APP localization and its access to secretases, and was previously linked to the disease; in addition, SORL1 was found to be a risk gene in genome-wide association studies. Moreover, a mutation in NOTCH3 (p.R1231C), previously found to cause cerebral autosomal 300
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dominant arteriopathy with subcortical infarcts and leukoencephalopathy was observed in a Turkish family with AD [57], indicating that this method could contribute to the differential diagnosis. These new findings indicate the presence of genetic heterogeneity in AD that involves other genes besides the Mendelian forms of APP and presenilin genes. Exome sequencing will allow the identification of unexpected genetic causes, clinical phenotypes and therefore of unknown pathways contributing to the disease pathogenesis. An attempt at synthesizing the genetic data into a model for disease It is clearly too early to attempt to construct a scheme that explains all the genetic loci for AD, but there is certainly some predictability in the identified genes. We suggest that Ab deposition remains central to the disease process. Endosomal processing of APP is a determinant of this deposition process. Ab deposition is modulated by ApoE by mechanisms that remain unclear. Microglia respond to Ab deposition, at first by phagocytosis of amyloid deposits, but eventually microglial activation switches to an inflammatory phenotype with abundant cytokine production, which is both neurotoxic and leads to progression of the clinical disease process (Fig. 3). Tangle pathology is downstream of this process as illustrated by the fact that tau mutations cause tangle pathology in the absence of amyloid pathology in frontotemporal dementia as well as by the finding that APP transgenes potentiate tangle pathology in MAPT transgenic mice (reviewed in [5]) Of note, it has proven very difficult to find a direct biochemical link between Ab and tau pathology, and these recent findings implicating the innate immune system may suggest that the link is not direct and cell autonomous but instead is mediated through an inflammatory process. It is also clear that the recent data showing that Ab and tangle pathology can spread independently of each other, by what we presume is a template mechanism, is an important consideration with respect to the relationship between these pathologies [58]. A testable, detailed prediction of this model is that biomarkers of imbalanced endosomal processing of APP would be the first to indicate increased risk of disease, followed by a drop in CSF Ab42 levels and an increase in amyloid positron emission
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Fig. 3 Effects of Ab on microglia activation and the effects of genetic variability in CLU, CR1 and TREM2.
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tomography (PET) signal in individuals who are truly progressing towards AD. This latter change may be linked to ApoE or other cholesterol-related factors. The importance of cholesterol for vesicle formation and Ab formation is clear. Moreover, new data showing that APP controls cholesterol synthesis and turnover further strengthen a molecular link between AD and cholesterol. Although some controversies remain, all results indicate that there are clear relationships between dysregulation of cholesterol metabolism or transport and both cognitive dysfunction and AD pathology.
Aβ build-up, plaque formation and toxicity
Apoptotic cell bodies and hinders repair
Microglia
Brain amyloid pathology is initially relatively nontoxic, as evidenced by normal CSF tau levels, absence of brain atrophy on imaging and normal cognition but, eventually, through unknown mechanisms, Ab aggregates over-activate microglia, which mediate neurotoxicity through cytokine production, release of proteases and activation of complement proteins. Microglial over-activation (the inflammatory M1 phenotype) should be detectable using PET ligands and/or microglial activation markers in CSF, and would according to this model result in neurotoxicity, indicated by ª 2014 The Association for the Publication of the Journal of Internal Medicine Journal of Internal Medicine, 2014, 275; 296–303
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increased CSF tau levels, brain atrophy and cognitive decline towards dementia. To test this model, we need (i) better markers of endosomal APP processing, (ii) better markers of different forms of microglial activation and (iii) true longitudinal studies with repeated biomarker sampling and clinical evaluations in the same individuals over extended periods of time, spanning preclinical to fully symptomatic AD. Recommendations for future research goals Several future research goals have been identified. First, delineation of the genetic architecture of the disease, especially with respect to the microglial response to Ab deposition, should be continued. Secondly, larger cohorts of genetically defined disease should be identified to test therapies at the presymptomatic stage. And finally the development of screening methods is essential to identify agents that modify microglial responses. Conflict of interest statement Professor Hardy has been consulting for Eisai and Eli Lilly speaker Bureau. The other authors have no conflict of interest to declare. Acknowledgements We thank Christer Olofsson, Bengt Marklund and Anders Marklund at Camp Gauto for facilitating the completion of the manuscript.
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25 Rogaeva E, Meng Y, Lee JH et al. The neuronal sortilin-related receptor SORL1 is genetically associated with Alzheimer disease. Nat Genet 2007; 39: 168–77. 26 Guerreiro R, Wojtas A, Bras J et al. TREM2 variants in Alzheimer’s disease. N Engl J Med 2013; 368: 117–27. 27 Cedazo-Minguez A. Apolipoprotein E and Alzheimer’s disease: molecular mechanisms and therapeutic opportunities. J Cell Mol Med 2007; 11: 1227–38. 28 Reiman EM, Chen K, Liu X et al. Fibrillar amyloid-beta burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease. Proc Natl Acad Sci U S A 2009; 106: 6820–5. 29 Castellano JM, Kim J, Stewart FR et al. Human apoE isoforms differentially regulate brain amyloid-beta peptide clearance. Sci Transl Med 2011;3:89ra57. 30 Bales KR, Liu F, Wu S et al. Human APOE isoform-dependent effects on brain beta-amyloid levels in PDAPP transgenic mice. J Neurosci 2009; 29: 6771–9. 31 Liu CC, Kanekiyo T, Xu H, Bu G. Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol 2013; 9: 106–18. 32 Kivipelto M, Rovio S, Ngandu T et al. Apolipoprotein E epsilon4 magnifies lifestyle risks for dementia: a population-based study. J Cell Mol Med 2008; 12: 2762–71. 33 Maioli S, Puerta E, Merino-Serrais P et al. Combination of apolipoprotein E4 and high carbohydrate diet reduces hippocampal BDNF and arc levels and impairs memory in young mice. J Alzheimers Dis 2012; 32: 341–55. 34 Riddell DR, Christie G, Hussain I, Dingwall C. Compartmentalization of beta-secretase (Asp2) into low-buoyant density, noncaveolar lipid rafts. Curr Biol 2001; 11: 1288–93. 35 Liu Q, Zerbinatti CV, Zhang J et al. Amyloid precursor protein regulates brain apolipoprotein E and cholesterol metabolism through lipoprotein receptor LRP1. Neuron 2007; 56: 66–78. 36 Jiang Q, Lee CY, Mandrekar S et al. ApoE promotes the proteolytic degradation of Abeta. Neuron 2008; 58: 681–93. 37 Deane R, Sagare A, Hamm K et al. apoE isoform-specific disruption of amyloid beta peptide clearance from mouse brain. J Clin Invest 2008; 118: 4002–13. 38 Wang H, Anderson LG, Lascola CD et al. Apolipoprotein E mimetic peptides improve outcome after focal ischemia. Exp Neurol 2013; 241: 67–74. 39 Ghosal K, Stathopoulos A, Thomas D, Phenis D, Vitek MP, Pimplikar SW. The apolipoprotein-E-Mimetic COG112 protects amyloid precursor protein intracellular domain-overexpressing animals from Alzheimer’s disease-like pathological features. Neurodegener Dis. 2013; 12: 51–8. 40 Cramer PE, Cirrito JR, Wesson DW et al. ApoE-directed therapeutics rapidly clear beta-amyloid and reverse deficits in AD mouse models. Science 2012; 335: 1503–6. 41 Barrett PJ, Song Y, Van Horn WD et al. The amyloid precursor protein has a flexible transmembrane domain and binds cholesterol. Science 2012; 336: 1168–71. 42 Pierrot N, Tyteca D, D’Auria L et al. Amyloid precursor protein controls cholesterol turnover needed for neuronal activity. EMBO Mol Med 2013; 5: 608–25.
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43 Bjorkhem I, Leoni V, Meaney S. Genetic connections between neurological disorders and cholesterol metabolism. J Lipid Res 2010; 51: 2489–503. 44 Bettens K, Sleegers K, Van Broeckhoven C. Genetic insights in Alzheimer’s disease. Lancet Neurol 2013; 12: 92–104. 45 McGeer PL, McGeer EG. The possible role of complement activation in Alzheimer disease. Trends Mol Med 2002; 8: 519–23. 46 Velazquez P, Cribbs DH, Poulos TL, Tenner AJ. Aspartate residue 7 in amyloid beta-protein is critical for classical complement pathway activation: implications for Alzheimer’s disease pathogenesis. Nat Med 1997; 3: 77–9. 47 Rogers J, Cooper NR, Webster S et al. Complement activation by beta-amyloid in Alzheimer disease. Proc Natl Acad Sci U S A 1992; 89: 10016–20. 48 Rogers J, Schultz J, Brachova L et al. Complement activation and beta-amyloid-mediated neurotoxicity in Alzheimer’s disease. Res Immunol 1992; 143: 624–30. 49 Okello A, Koivunen J, Edison P et al. Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 2009; 73: 754–60. 50 Okello A, Edison P, Archer HA et al. Microglial activation and amyloid deposition in mild cognitive impairment: a PET study. Neurology 2009; 72: 56–62. 51 Daborg J, Andreasson U, Pekna M et al. Cerebrospinal fluid levels of complement proteins C3, C4 and CR1 in Alzheimer’s disease. J Neural Transm 2012; 119: 789–97. 52 Mattsson N, Tabatabaei S, Johansson P et al. Cerebrospinal fluid microglial markers in Alzheimer’s disease: elevated chitotriosidase activity but lack of diagnostic utility. Neuromolecular Med 2011; 13: 151–9. 53 Craig-Schapiro R, Perrin RJ, Roe CM et al. YKL-40: a novel prognostic fluid biomarker for preclinical Alzheimer’s disease. Biol Psychiatry 2010; 68: 903–12. 54 Jonsson T, Stefansson H, Steinberg S et al. Variant of TREM2 associated with the risk of Alzheimer’s disease. N Engl J Med 2013; 368: 107–16. 55 Jiang T, Yu JT, Zhu XC, Tan L. TREM2 in Alzheimer’s disease. Mol Neurobiol 2013; 48: 180–5. 56 Pottier C, Hannequin D, Coutant S et al. High frequency of potentially pathogenic SORL1 mutations in autosomal dominant early-onset Alzheimer disease. Mol Psychiatry 2012; 17: 875–9. 57 Guerreiro RJ, Lohmann E, Kinsella E et al. Exome sequencing reveals an unexpected genetic cause of disease: NOTCH3 mutation in a Turkish family with Alzheimer’s disease. Neurobiol Aging 2012; 33: 1008 e17–23. 58 Hardy J, Revesz T. The spread of neurodegenerative disease. N Engl J Med 2012; 366: 2126–8. Correspondence: John Hardy, Department of Molecular Neuroscience, Reta Lila Weston Research Laboratories, UCL Institute of Neurology, London WC1N 3BG, UK. e-mail: [email protected]. uk).
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Pathways to Alzheimer’s disease J. Hardy1, N. Bogdanovic2, B. Winblad3, E. Portelius4, N. Andreasen3, A. Cedazo-Minguez3 & H. Zetterberg1,4 From the 1Department of Molecular Neuroscience, Reta Lila Weston Research Laboratories, UCL Institute of Neurology, London, UK; 2 Section of Clinical Geriatrics, Karolinska Institutet; 3KI-Alzheimer Disease Research Center, Karolinska Institutet, NVS, Stockholm; and 4Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
Abstract. Hardy J, Bogdanovic N, Winblad B, Portelius E, Andreasen N, Cedazo-Minguez A, Zetterberg H (UCL Institute of Neurology, London, UK; Karolinska Institutet, Stockholm; Karolinska Institutet, NVS; and The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden). Pathways to Alzheimer’s disease. (Key Symposium). J Intern Med 2014; 275: 296–303. Recent trials of anti-amyloid agents have not produced convincing improvements in clinical outcome in Alzheimer’s disease; however, the reason for these poor or inconclusive results remains unclear. Recent genetic data continue to support
Introduction There is no doubt that for the last 20 years, the amyloid cascade hypothesis has dominated opinion about the aetiology and pathogenesis of Alzheimer’s disease (AD), as well as guided the efforts to find treatments. However, in the last 2 years, several clinical trials of agents targeting amyloid-b (Ab), including two c-secretase inhibitors (semagacestat and avagacestat) and two anti-Ab antibodies (bapineuzumab and solanezumab), have failed to reach their primary clinical endpoints. These trials have produced ambivalent results, with positive findings only in ad hoc secondary end-points, and have led to divergent opinions on whether it is worthwhile persevering with Ab therapies or whether this approach should be abandoned. It is not the primary purpose of this review to discuss these issues although we will offer our opinion. Rather, as the initial evidence supporting the amyloid cascade hypothesis came from genetic analysis of individuals with Down syndrome and autosomal dominant AD, our primary purpose is to assess more recent genetic data from genome-wide association studies and exome sequencing to consider the potential additional drug targets highlighted by these analyses
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the amyloid hypothesis of Alzheimer’s disease with protective variants being found in the amyloid gene and both common low-risk and rare high-risk variants for disease being discovered in genes that are part of the amyloid response pathways. These data support the view that genetic variability in how the brain responds to amyloid deposition is a potential therapeutic target for the disease, and are consistent with the notion that anti-amyloid therapies should be initiated early in the disease process. Keywords: Alzheimer’s disease, amyloid, cell biology, genetics, tau.
and discuss how they relate to the amyloid pathway. Deciphering the results of clinical trials of semagacestat, bapineuzumab and solanezumab The amyloid cascade hypothesis of AD, first postulated in the early 1990s, incorporates histopathological, genetic and biochemical information. It posits that the deposition of Ab in the brain parenchyma, due to an imbalance between the production and clearance of Ab initiates a sequence of events that ultimately lead to AD dementia [1–5]. The accumulation of Ab in the brain is thus the primary force driving the AD pathogenesis. The hypothesis is not simply an academic construct and will only have been useful if it leads to effective clinical management of the disease. Against this background, it is essential to reach a conclusion as soon as possible as to whether the results of clinical trials reported to date support or refute this hypothesis, or are inconclusive. A number of anti-Ab strategies are discussed below. Semagacestat and avagacestat Semagacestat and avagacestat are c-secretase inhibitors. c-Secretase has more than a hundred substrates including Notch, and we now know that
there is almost no selectivity of these drugs for different substrates. Therefore, the fact that cognitive decline was worse in the treatment arm, compared with placebo, in these trials is difficult to interpret at present [6–8]. Bapineuzumab and solanezumab The antibodies bapineuzumab and solanezumab target different epitopes at Ab. Bapineuzumab is a humanized monoclonal IgG1 antibody against the Ab N-terminus (Ab1–5), based on the murine antibody 3D6, which was intended to promote Ab clearance from the brain [9]. Solanezumab, on the other hand, is a humanized version of the mouse monoclonal antibody m266, raised against Ab13–28 [10, 11]. It differs from bapineuzumab in several ways. First, it recognizes various N-terminal truncated species (such as Ab4–42) that are known to exist alongside full-length Ab1–42 in AD plaques [12]. Secondly, whereas bapineuzumab binds amyloid plaques more strongly than soluble Ab, solanezumab selectively binds to soluble Ab with little or no affinity for the fibrillar form [13]. Thirdly, in small Phase I and Phase II studies [11], there was no clinical, cerebrospinal fluid (CSF) biomarker or imaging evidence of meningoencephalitis or vasogenic oedema, the latter of which has been a problem with bapineuzumab. Bapineuzumab had no clinical efficacy [9]. However, it was associated with reduced amyloidbinding as evidenced by Pittsburgh Compound B and decreased CSF tau levels suggesting that there was some reduction in neuronal damage, which was not clinically useful, at least in the Phase III trial that was recently stopped. However, it is important to note that 38% of enrolled patients did not fulfil criteria for AD. Likewise, in the overall analysis, solanezumab did not have an effect on clinical outcome. However, in the group of patients with mild AD, there was a small reduction in clinical worsening but this was not associated with a reduction in CSF tau levels. Taken together, the two antibody studies produced inconclusive results, which makes it difficult to draw any firm conclusions on whether or not the approach will be effective. Other issues concerning these and future trials As others have noted, all these trials illustrate the difficulties in testing the amyloid hypothesis [7, 14]. A consensus is emerging that drug candidates
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need to be administered early in the disease process in drug-na€ıve patients with AD, and possibly in carriers of amyloid precursor protein (APP) and PSEN1 and PSEN2 mutations. However, achieving the goals set out by this consensus is extremely challenging from an organizational and ethical perspective. APP and PSEN1 and PSEN2 mutation carriers are rare, and apart from the extended presenilin 1, pedigree in Colombia are under the care of a large number of clinical centres each of which has few patients. Many mutation carriers do not want to know their mutation status, complicating their involvement in clinical trials. Furthermore, these trials require extended clinical follow-up and sufficient patient numbers with high enough conversion rates. Despite these difficulties, randomized controlled trials on AD prevention (e.g. ADCS-A4, API and DIAN) are already underway, as discussed in other articles of this themed issue. Recent genetic data and the implications for pathways to AD A summary of all the currently known genetic loci for AD is shown in Fig. 1. APP and presenilin variability The role of APP and presenilin mutations in causing early AD has long been recognized. However, genetic analysis of late-onset AD has surprisingly revealed that these mutations are also pathogenic factors in some cases [15, 16]. Indeed, given the prevalence of late-onset disease, it is likely that there are more cases of disease with ages over 60 years who have APP and PSEN1 and PSEN2 Causes Alzheimer´s disease
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Fig. 1 Risk loci for Alzheimer’s disease. Adapted from Manolio et al. [20]. ª 2014 The Association for the Publication of the Journal of Internal Medicine Journal of Internal Medicine, 2014, 275; 296–303
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mutations than early-onset disease, although they still account for 3.0
Lipid metabolism
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All the above loci were found by genome-wide association studies, except TREM2 that was found by exome sequencing.
[37]. Finally, the findings of recent studies suggest that ApoE may also affect AD risk by immunomodulation, which may make individuals more or less vulnerable to build-up of amyloid in the brain [38, 39]. Recent APP transgenic mouse data have clearly shown that experimental manipulation of brain cholesterol metabolism has therapeutic potential [40]. Recently, a unique aspect in the relationship between APP and cholesterol metabolism has emerged. Cholesterol forms a complex with the Ab domain of APP, suggesting that strategies aimed at preventing the binding of cholesterol to APP may have therapeutic potential in AD [41]. Moreover, a novel role of APP in neurons as been identified in controlling cholesterol biosynthesis and turnover, indicating for the importance of synaptic function in damage repair [42] Table 1. Indeed, the findings of genetic studies have implicated several genes related to cholesterol synthesis, transport, uptake or metabolism (i.e. APOE, ABCA7, ABCA1, CLU and CYP46A1) in AD [24, 43, 44]. This evidence suggests that altered cholesterol levels, transport and cellular distribution are intimately linked to amyloid accumulation and AD pathogenesis. However, a complete understanding of the exact underlying mechanisms is still lacking. The links between cholesterol and AD pathogenesis are summarized in Fig. 2.
Decreased synaptogenesis and repair
Fig. 2 Cholesterol-related pathways to Alzheimer disease (AD). Evidence supporting that altered cholesterol levels, transport and cellular distribution contribute to amyloid accumulation and AD pathogenesis: (i) The interplay between brain cholesterol homeostasis and Ab formation. (ii) Novel findings from GWAS on genes related to cholesterol metabolism (APOE, ABCA7, ABCA1, CLU, CYP46A1) in AD. (iii) The lack of function of apoE4 in transporting cholesterol to neurons and in clearing Ab from the brain. An unbalanced neuronal cholesterol homeostasis would lead to decreased synaptogenesis and repair mechanisms.
The innate immune system Neuropathological analysis of AD brains has long indicated a role of the complement cascade in the pathogenesis of AD [45] and indeed Ab has been shown to activate the complement cascade [46]. Morphological characteristics of an inflammatory response include a clustering of activated microglia and complement factors within amyloid plaques. Fibrillary amyloid can bind complement factor C1 and activate the classical complement pathway without involvement of antibodies [47, 48]. Inflammatory proteins contribute to pathological processes in the AD brain, including amyloid homeostasis, gliosis and phosphorylation of tau. Inflammation may have both beneficial effects, such as phagocytosis, and detrimental effects, such as off-target actions on neighbouring cells. Inflammation is a relatively early pathogenic event, which was revealed by neuroradiological and neuropathological observations in patients with mild cognitive impairment [49, 50]. Astroglia and microglia both play a crucial role in innate immunity and use Toll receptors to recognize fibrillar amyloid. Both types of receptors, Toll-like and CD14, are innate receptors that mediate activation of transcription factors and production of pro-inflammatory cytokines. Stimulation of the innate immune system reduces parenchymal and vascular amyloid. The innate ª 2014 The Association for the Publication of the Journal of Internal Medicine Journal of Internal Medicine, 2014, 275; 296–303
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immune system can be activated by interaction of amyloid and LDL in both AD and atherosclerosis; the latter is a major risk factor for late-onset AD. Thus, activated microglia can be, at the same time, in two functionally different activated states either as pro-inflammatory (detrimental) or involved in repair of the brain. Increased CSF levels of complement factors and microglial activation markers have been described in AD [51–53] but longitudinal data to determine the sequence of these alterations in relation to the onset of amyloid deposition and neurotoxicity markers are lacking. On the other hand, genetic analysis has now clearly shown that variability in innate immunity is an important determinant of risk of AD with several loci, for example the complement receptor 1 (CR1), clusterin and TREM2, mapping to this system [24]. Exome sequencing Exome sequencing has the potential to identify high-risk loci for disease. The expense and analytical burdens that these large-scale sequencing projects entail have only recently begun to be overcome and the first data from what will undoubtedly be a large number of projects are starting to be reported. Rare, heterozygous loss of function mutations in the TREM2 gene have very recently been found to increase the risk of AD by up to fivefold [26, 54]. TREM2 has being shown to suppress the inflammatory response by inhibiting cytokine production and secretion in microglia [55]. TREM2 is also involved in the regulation of phagocytic pathways that are responsible for the removal of cell debris and possibly of amyloid. Thus, a lack of function of TREM2 could result in increased systemic inflammation, damage of neurons and accumulation of amyloid. The findings of these studies, and of those mentioned above, point to the microglial activation state as a key determinant of the pathogenesis of AD. Recently, Pottier and colleagues [56] found a high frequency of potentially pathogenic SORL1 mutations in autosomal dominant early-onset AD. SORL1 is an important mediator of APP localization and its access to secretases, and was previously linked to the disease; in addition, SORL1 was found to be a risk gene in genome-wide association studies. Moreover, a mutation in NOTCH3 (p.R1231C), previously found to cause cerebral autosomal 300
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dominant arteriopathy with subcortical infarcts and leukoencephalopathy was observed in a Turkish family with AD [57], indicating that this method could contribute to the differential diagnosis. These new findings indicate the presence of genetic heterogeneity in AD that involves other genes besides the Mendelian forms of APP and presenilin genes. Exome sequencing will allow the identification of unexpected genetic causes, clinical phenotypes and therefore of unknown pathways contributing to the disease pathogenesis. An attempt at synthesizing the genetic data into a model for disease It is clearly too early to attempt to construct a scheme that explains all the genetic loci for AD, but there is certainly some predictability in the identified genes. We suggest that Ab deposition remains central to the disease process. Endosomal processing of APP is a determinant of this deposition process. Ab deposition is modulated by ApoE by mechanisms that remain unclear. Microglia respond to Ab deposition, at first by phagocytosis of amyloid deposits, but eventually microglial activation switches to an inflammatory phenotype with abundant cytokine production, which is both neurotoxic and leads to progression of the clinical disease process (Fig. 3). Tangle pathology is downstream of this process as illustrated by the fact that tau mutations cause tangle pathology in the absence of amyloid pathology in frontotemporal dementia as well as by the finding that APP transgenes potentiate tangle pathology in MAPT transgenic mice (reviewed in [5]) Of note, it has proven very difficult to find a direct biochemical link between Ab and tau pathology, and these recent findings implicating the innate immune system may suggest that the link is not direct and cell autonomous but instead is mediated through an inflammatory process. It is also clear that the recent data showing that Ab and tangle pathology can spread independently of each other, by what we presume is a template mechanism, is an important consideration with respect to the relationship between these pathologies [58]. A testable, detailed prediction of this model is that biomarkers of imbalanced endosomal processing of APP would be the first to indicate increased risk of disease, followed by a drop in CSF Ab42 levels and an increase in amyloid positron emission
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Phagocytic response
Aβ
Complement activation Promotes protective functions
CR1 CLU
Acts as a lock on microglial inflammatory responses, promoting protective functions
Low cytokine and neurotrophin production
CR1 CLU
TREM2
Phagocytosis Aβ deposition, plaque formation and toxicity
Survival and repair
Neuron
TREM1
Inflammatory activation Apoptotic bodies and aids repair
Microglia
Inflammatory Response
Aβ
Complement activation Promotes protective functions
CR1 CLU
CR1 CLU
TREM2
TREM1
Cytokine production e.g. TNFa secreation
Inflammatory activation
Phagocytosis
Fig. 3 Effects of Ab on microglia activation and the effects of genetic variability in CLU, CR1 and TREM2.
Neurodegeneration
Neuron
tomography (PET) signal in individuals who are truly progressing towards AD. This latter change may be linked to ApoE or other cholesterol-related factors. The importance of cholesterol for vesicle formation and Ab formation is clear. Moreover, new data showing that APP controls cholesterol synthesis and turnover further strengthen a molecular link between AD and cholesterol. Although some controversies remain, all results indicate that there are clear relationships between dysregulation of cholesterol metabolism or transport and both cognitive dysfunction and AD pathology.
Aβ build-up, plaque formation and toxicity
Apoptotic cell bodies and hinders repair
Microglia
Brain amyloid pathology is initially relatively nontoxic, as evidenced by normal CSF tau levels, absence of brain atrophy on imaging and normal cognition but, eventually, through unknown mechanisms, Ab aggregates over-activate microglia, which mediate neurotoxicity through cytokine production, release of proteases and activation of complement proteins. Microglial over-activation (the inflammatory M1 phenotype) should be detectable using PET ligands and/or microglial activation markers in CSF, and would according to this model result in neurotoxicity, indicated by ª 2014 The Association for the Publication of the Journal of Internal Medicine Journal of Internal Medicine, 2014, 275; 296–303
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increased CSF tau levels, brain atrophy and cognitive decline towards dementia. To test this model, we need (i) better markers of endosomal APP processing, (ii) better markers of different forms of microglial activation and (iii) true longitudinal studies with repeated biomarker sampling and clinical evaluations in the same individuals over extended periods of time, spanning preclinical to fully symptomatic AD. Recommendations for future research goals Several future research goals have been identified. First, delineation of the genetic architecture of the disease, especially with respect to the microglial response to Ab deposition, should be continued. Secondly, larger cohorts of genetically defined disease should be identified to test therapies at the presymptomatic stage. And finally the development of screening methods is essential to identify agents that modify microglial responses. Conflict of interest statement Professor Hardy has been consulting for Eisai and Eli Lilly speaker Bureau. The other authors have no conflict of interest to declare. Acknowledgements We thank Christer Olofsson, Bengt Marklund and Anders Marklund at Camp Gauto for facilitating the completion of the manuscript.
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43 Bjorkhem I, Leoni V, Meaney S. Genetic connections between neurological disorders and cholesterol metabolism. J Lipid Res 2010; 51: 2489–503. 44 Bettens K, Sleegers K, Van Broeckhoven C. Genetic insights in Alzheimer’s disease. Lancet Neurol 2013; 12: 92–104. 45 McGeer PL, McGeer EG. The possible role of complement activation in Alzheimer disease. Trends Mol Med 2002; 8: 519–23. 46 Velazquez P, Cribbs DH, Poulos TL, Tenner AJ. Aspartate residue 7 in amyloid beta-protein is critical for classical complement pathway activation: implications for Alzheimer’s disease pathogenesis. Nat Med 1997; 3: 77–9. 47 Rogers J, Cooper NR, Webster S et al. Complement activation by beta-amyloid in Alzheimer disease. Proc Natl Acad Sci U S A 1992; 89: 10016–20. 48 Rogers J, Schultz J, Brachova L et al. Complement activation and beta-amyloid-mediated neurotoxicity in Alzheimer’s disease. Res Immunol 1992; 143: 624–30. 49 Okello A, Koivunen J, Edison P et al. Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 2009; 73: 754–60. 50 Okello A, Edison P, Archer HA et al. Microglial activation and amyloid deposition in mild cognitive impairment: a PET study. Neurology 2009; 72: 56–62. 51 Daborg J, Andreasson U, Pekna M et al. Cerebrospinal fluid levels of complement proteins C3, C4 and CR1 in Alzheimer’s disease. J Neural Transm 2012; 119: 789–97. 52 Mattsson N, Tabatabaei S, Johansson P et al. Cerebrospinal fluid microglial markers in Alzheimer’s disease: elevated chitotriosidase activity but lack of diagnostic utility. Neuromolecular Med 2011; 13: 151–9. 53 Craig-Schapiro R, Perrin RJ, Roe CM et al. YKL-40: a novel prognostic fluid biomarker for preclinical Alzheimer’s disease. Biol Psychiatry 2010; 68: 903–12. 54 Jonsson T, Stefansson H, Steinberg S et al. Variant of TREM2 associated with the risk of Alzheimer’s disease. N Engl J Med 2013; 368: 107–16. 55 Jiang T, Yu JT, Zhu XC, Tan L. TREM2 in Alzheimer’s disease. Mol Neurobiol 2013; 48: 180–5. 56 Pottier C, Hannequin D, Coutant S et al. High frequency of potentially pathogenic SORL1 mutations in autosomal dominant early-onset Alzheimer disease. Mol Psychiatry 2012; 17: 875–9. 57 Guerreiro RJ, Lohmann E, Kinsella E et al. Exome sequencing reveals an unexpected genetic cause of disease: NOTCH3 mutation in a Turkish family with Alzheimer’s disease. Neurobiol Aging 2012; 33: 1008 e17–23. 58 Hardy J, Revesz T. The spread of neurodegenerative disease. N Engl J Med 2012; 366: 2126–8. Correspondence: John Hardy, Department of Molecular Neuroscience, Reta Lila Weston Research Laboratories, UCL Institute of Neurology, London WC1N 3BG, UK. e-mail: [email protected]. uk).
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