Current conceptions of the etiology and risk factors for Alzheimer s disease and their possible implications on the design of dementia clinical trials

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1 Current conceptions of the etiology and risk factors for Alzheimer s disease and their possible implications on the design of dementia clinical trials Clin. Invest. (2011) 1(11), Many of the clinical trials in Alzheimer s disease (AD) target the formation, accumulation or clearance of amyloid b (Ab), which is considered to be a pathological hallmark of the disease. These trials have not yet proven efficacy in treatment or prevention of the disease. The failure of these trials may be attributed to a misconception of the role of Ab and the second pathological hallmark of the disease, neurofibrillary tangles, in the most prevalent form of the disease, sporadic AD, compared with the rare early onset, familial AD. In this review, we discuss factors that may affect the results of clinical trials. In addition, the role of several risk factors for AD and their possible interactions with Ab will be reviewed, suggesting a conceptualization of sporadic AD as a heterogenous clinical entity. The implications of such an approach on clinical trials for the treatment and prevention of AD will be discussed. Ramit Ravona-Springer1 & Amos D Korczyn 2 Sheba Medical Center, Tel Hashomer, Israel Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel Author for correspondence: Tel.: neuro13@post.tau.ac.il 1 2 Keywords: Alzheimer s disease clinical trials dementia etiology patient selection prevention risk factors therapy The pathological hallmarks of Alzheimer s disease (AD) are considered to be amyloid plaques (AP) and neurofibrillary tangles (NFT). The amyloid cascade hypo-thesis postulates that amyloid b (Ab) deposition leads to formation of NFT and is toxic to the brain [1]. The typical clinical features of AD are those of progressive cognitive decline, initially characterized by episodic memory deficits and eventually affecting all cognitive domains, leading to severe functional decline. These clinical and pathological phenomenologies are common to the rare forms of autosomal-dominantly inherited AD (DIAD), and to the more prevalent form of the disease, sporadic AD [1,2]. It is reasonable to assume that Ab is etiologically responsible to DIAD, since the mutations, particularly in amyloid precursor protein (APP), affect amyloid metabolism [1,3]. In contrast, in sporadic, late onset AD (LOAD), the role of amyloid is less clear [4,5] as reflected in the results of clinical and pathological studies (Table 1) [6 12]. Several anti-amyloid treatments (either vaccinations aimed at removal of AP [13,14] and amyloid oligomers [14] or treatments aimed at prevention of formation of Ab from APP [14]) proved efficacious in animal models and may have even resulted in reduction of amyloid load in AD patients, but did not appreciably alter disease course [13]. Failure of these treatments may imply that amyloid does not have a causal role in LOAD but also the fact that the type or target of treatment (e.g., passive vs active immunization), target (Ab monomers vs oligomers) or that optimal timing for intervention (preclinical phases vs frank dementia) have not yet been identified [14]. Discrepancies between pathological and clinical findings may be explained in various ways: AP and NFT may not be etiologically important in LOAD, but rather markers of brain pathology or the final common pathway for many forms of brain insults. The presence of these markers may indicate a terminal stage of pathology, that is, a stage at which /CLI Future Science Ltd ISSN

2 Ravona-Springer & Korczyn Table 1. Arguments against a primary role of amyloid in Alzheimer s disease. Study (year) Argument Refs. Braak et al. (2011) Neuropathological studies have demonstrated that t pathology rather that amyloid deposition is more strongly associated with the presence and severity of dementia [6] Nelson et al. (2011) Both amyloid and NFT deposition have been demonstrated to reach advanced stages prior to appearance of clinical symptoms [7] Davis et al. (2011) Subjects with advanced pathology may be free from clinical dementia [8] Kramer et al. (2011) Similar pathology has been described in several clinically distinct variants of AD, even without dementia (e.g., posterior cortical atrophy) [9] Drachman et al. (2006) Amyloid deposits and NFT are not specific for AD and have been found in other neurodegenerative diseases as well as in normal aging Kwon and Schneider (2006, 2008) Several treatment strategies targeting Ab and NFT have failed in clinical trials [10] [11 12] Ab: Amyloid b; AD: Alzheimer s disease; NFT: Neurofibrillary tangles. treatment interventions cannot cure the pathology or ameliorate its clinical expression. The failure of therapeutic strategies may therefore be explained by the fact that treatment, even in mild stages of the disease, starts too late and/or that other targets (such that precede AP and NFT deposition) should be considered. Alternatively, more sensitive assessment tools may be able to capture subtle treatment effects, such that are not detected with the tools used today. In this regard, the clinical correlation (functional measurements, cost of treatment, quality of life) of statistically significant changes measured by sensitive tools should be considered. It is quite possible that the currently used, more direct assessments of the major clinical symptoms in AD would miss clinically relevant treatment effects, which would be picked up by the suggested types of tertiary outcome measures. The disease course of AD extends over decades, subsequently and prior to the first clinical manifestation of the disease. Thus, an intervention that reduces the rate of degeneration by 50% is not likely to be observed easily, particularly given the great individual variability in the rate of disease progression. Notable, none of the trials aiming at Ab used rate of decline as a primary end point. Another explanation for the failure of clinical trials may be the fact that the patient population participating in these trials may be heterogenous, with different pathologies, co-morbidities and rates of disease progression leading to failure of the end point used in clinical trials to capture treatment effect. The lack of significant benefit in clinical trials should lead clinicians and researchers to re-evaluate the patient population included in clinical trials for AD, as well as optimal timing for intervention. In addition, in an era in which several potentially modifiable risk factors for AD have been recognized, interventions in these domains should be considered Patient selection for clinical trials Insufficient diagnostic specificity for non-ad dementias, as well as pathological overlap of AD with other dementias (Lewy body disease, vascular brain disease) [12,15,16], may lead to inclusion of patients suffering from these dementing diseases in trials targeting AD, especially when inclusion criteria are based solely on clinical diagnosis. Although neuroimaging is used lately as a tool to exclude patients with brain infarcts, differentiation between vascular dementia (especially if resulting from white matter lesions) and AD continues to be challenging [17]. Inclusion of such patients has important consequences. On the one hand, it potentially lowers the signal of efficacy. Treatment of vascular risk factors may affect progression rate and thus reduce the power of the study as well. Implementation of biomarkers as inclusion criteria into clinical trials may reduce such heterogeneity [18]. Significant efforts have been made in recent years in the fields of biomarkers for AD, mainly neuroimaging and cerebro-spinal fluid (CSF) laboratory markers [18]. The results of such studies have been partially validated against clinical assessments and long term follow-up studies of populations at risk [18]. Based on these advances, it has been suggested to revise the criteria of AD as well as the definition criteria of patients at risk for development of AD and those with preclinical AD [18]. According to the revised criteria, structural and functional neuroimaging, Ab, total t and phospho-t levels in the CSF or other well-validated biomarkers to be discovered in the future should be used, in addition to clinical signs and symptoms as supportive diagnostic criteria [18]. These revisions are expected to permit greater uniformity in patient diagnosis and more accurate reference to patients who are not demented, but carry risk for development of dementia. Studies aimed at assessing the predictive validity

3 Etiology of Alzheimer s & its implications for the design of clinical trials of biomarkers have shown interesting results: use of volumetric MRI in the AD neuroimaging initiative in mild cognitive impairment (MCI) patients detected a pattern and extent of brain atrophy that was predictive for imminent conversion to dementia [19]. Measurement of cortical thickness showed advantage in prediction of conversion to AD over cognitive scores, especially in highly educated subjects [20]. A CSF signature based on the combination of Ab1 42 and total t has been demonstrated to effectively predict the converstion of MCI to dementia [21]. Others have argued that based on data from cohort studies, according to which the majority of preclinical AD and those already demented have positive amyloid biomarkers, from the clinical point of view, the currently developed biomarkers may not provide additional significant information [22]. In addition, the use of these biomarkers may increase the specificity of AD diagnosis, but cannot reduce the contamination of pure AD cases by those with additional vascular or synuclein pathology. Although such criteria still require validation against long-term follow-up and neuropathological studies, they are expected to enable several levels of intervention in clinical trials, each requiring a different study design: postponement of clinical signs of disease for subjects who are at risk or presymptomatic, modification of disease progression for prodromal AD or reduced rate of decline in frankly demented patients. Clinical improvement, a frequent end point in clinical studies, is not necessarily a biological consequence of the amyloid hypothesis. The interventions applied to populations at risk who are not yet clinically demented will have to be weighed against the cost and the safety profile in particular of such interventions. Also, future studies should aim at defining the optimal timing for intervention, follow-up periods and treatment target in yet asymptomatic patients at risk. Indeed, the association between neuropathologic findings and clinical dementia has been demonstrated by some to be stronger in younger old as compared with older old subjects [23]. Thus, age should be considered as a factor possibly affecting the efficacy of treatment interventions. The new diagnostic criteria, similar to the previous ones, is based on consensus rather than on evidence. Using pathology or Pittsburgh Compound B-binding is based on the amyloid hypothesis [1,24]. This hypothesis is far from validated [25,26] and other mechanisms have been suggested to play a key role in the pathology of the disease [27,28]. For example, both genetically-related disorders (e.g., due to APP mutations or Down syndrome) and LOAD are regarded as a single disorder based on these criteria, whereas these are probably different disorders, and would not necessarily respond to the same treatment. Many of the therapies presently being studied are directed at amyloid, which may be a downstream change. A better understanding of the early changes in the pathogenesis of AD is needed to overcome this problem. In addition to diagnosis-related heterogeneity of study populations, there are other heterogeneities that introduce noise to measurements of efficacy, such as range of ages and dementia severity in the population included in clinical trials. Most clinical trials to date target already demented or prodromal (MCI) patients [29]. In these trials, a wide age range is permitted, allowing the participation DIAD patients (in whom clinical symptoms usually start at ages [30]) as well as LOAD patients (in the majority of whom symptoms begin after the age of 65). As discussed above, despite clinical and neuropathological similarities, the primary etiology and pathogenesis are not identical, disease course may differ, being more aggressive in DIAD [31]. Differences in disease progression require adjustment of study design and assessment tools to the population studied. Even LOAD cases have been divided into those with onset before the age of 65 and those above that age; families in which there are both early onset and late onset cases have been suggested to represent a distinct subgroup [32]. The inclusion of patients with disease onset prior to the age of 65 in clinical trials for AD is controversial [33]. Also, in most clinical trials a large range of dementia severity is allowed, usually mild to moderate dementia. However, the rate of disease progression, at least as measured by scales, such as mini-mental state examination and Alzheimer s disease assessment scale cog, may differ by disease stage. Some have shown slow progression during initial and late stages of the disease and a faster rate of decline in intermediate stages [34]. It is not clear if the nonlinearity indeed reflects a difference in rate of the underlying biological process over time or reflects the limitations of the tools used to measure disease progression. As will be discussed later, certain factors, such as education and apolipoprotein E (ApoE) status [35] may further affect the rate of decline. An additional consideration will be the source (community or clinic based) from which patients will be recruited. Convenience samples comprising of AD patients, mostly from clinical settings, are not necessarily representative of the entire AD population [36] and have been demonstrated to be a demographically, clinically and ethnically [37] selected subgroup [38]. Some have also demonstrated neuropathological differences between community and clinic-based cohorts [39,40], showing more Lewy body as well as other pathologies in clinic-based samples, and less AD pathology and more cerebral infarcts in community-based samples [39,40]. Therefore, results from clinical trials based on a certain patient population may not necessarily be generalizable. Clin. Invest. (2011) 1(11) 1493

4 Ravona-Springer & Korczyn Treatments aimed for community samples at risk will require widespread cognitive screening of the elderly. However, at a stage in which the only treatments approved for AD have a modest effect [41,42], the motivation and compliance for such procedures may be problematic. Cognitive screening of elderly populations will project on cost of treatment and should be weighed against the efficacy, safety and ethical implications of early interventions. Such studies may require larger cohorts and longer follow-up and will, therefore, be more costly. Box 1 summarizes the weaknesses of currently performed clinical trials. As presented above, the population included to date in clinical trials for AD is heterogeneous, probably reflecting the multifactorial nature of senile dementia [43], the non-linear progression, and the discrepancies between pathological findings and clinical course. Future recommendations for the design of clinical trials in AD will be based on the ability to correctly stratify subjects into more homogenous groups. Clinical trials addressing different patient subpopulations and disease stages will require adjustment of regulatory guidelines, study design, study end points and tools used for assessment of treatment efficacy. The tools approved by regulatory agencies today are clinical. Once preventive strategies in asymptomatic subjects become available, more sensitive clinical assessment tools will be required, perhaps complemented with biomarkers. The biomarkers should be fitted to the timing of intervention [18], and should reflect dementia pathology and course, be able to predict conversion to dementia or cognitive deterioration and also reflect treatment efficacy. Such characterization of biomarkers is expected to require time and financial investment as well as further studies in cognitively normal individuals [44]. Future studies should determine the optimal timing and targets for intervention, as well as treatment duration. Finally, however, biomarkers are of different types and relevance to disease and, therefore, can support, but not replace, clinical outcomes. Preventive strategies The abundance of data regarding life-long risk factors for AD have led to the execution of numerous epidemiological and clinical studies assessing the efficacy of treatment of such risk factors in AD prevention. Cardiovascular risk factors, traditionally considered to increase risk for vascular pathology, have also been demonstrated to increase risk for AD. The importance of such risk factors relates to the fact that they are mostly modifiable. The questions are: when should treatment begin? How aggressive should it be? Should patients be treated with different therapeutic strategies (e.g., individualized to their vascular risk factors)? Is the control of such risk factors (e.g., blood glucose levels, blood pressure values [peak, trough or average], cholesterol and triglyceride levels) the global aim in dementia prevention or should subpopulations be treated differently? We shall now discuss some of the cardiovascular risk factors. Type 2 diabetes mellitus Among cardiovascular risk factors, diabetes and even prediabetes stages are consistently associated with dementia [45 47], MCI [48] and cognitive decline [49]. A systematic review of the effect of Type 2 Diabetes Mellitus (T2D) on dementia and cognitive decline concludes that cognitive impairment should be considered a consequence and disabling manifestation of T2D [50]. Box 1. Weaknesses of Alzheimer s disease trials. Factors related to disease Poor understanding about etiology of disease. Insufficient knowledge regarding optimal timing for therapeutic intervention. Factors related to clinical trials management & recruitment Inclusion of patients with mixed dementias. Heterogenic patient population due to difficulty in differentiating between different dementia disorders. Age range allowed in clinical trials is restricted, not allowing generalization. Range of disease severity allowed. Inclusion of autosomal-dominant inherited AD as well as sporadic AD. Inclusion of mainly clinic based samples and other factors which may bias the results and prevent generalization. Optimal therapy of co-morbid conditions (such as hypertension) may itself affect the progression of the disease. Factors related to ana lysis of results Reliance on changes in MMSE, ADAS-cog as if these are linear. Post hoc ana lysis of subgroups (e.g., disease severity or genetic factors) may be misleading. AD: Alzheimer s disease; ADAS: Alzheimer s disease assessment scale; MMSE: Mini-mental state examination

5 Etiology of Alzheimer s & its implications for the design of clinical trials The results of neuropathological studies, however, have not always been consistent with those of clinical studies. Midlife T2D increased the risk for late-life dementia both vascular dementia and AD in several longitudinal followup studies, including the Honolulu Asia Aging Study (HAAS) [51] and the Vantaa cohort [52]. Consistent with these findings, the neuropathological assessments of HAAS demonstrated that midlife diabetes, although only in ApoE4 carriers, was associated with higher loads of hippocampal neuritic plaques, cortical and hippocampal NFTs and higher risk for cerebral amyloid angiopathy [51]. However, in the neuropathological study of the Vantaa cohort, compared with nondiabetic subjects, diabetic subjects were less likely to have NFTs and APs but more likely to have cerebral infarcts [52]. Diabetic subjects had significantly less AD-associated neuropathology in another autopsy study of elderly subjects [53]. Other studies have found no relationship between T2D and AD neuropathology [51,54] or association of diabetes only with cerebral infarction [55]. In addition to the vascular mechanism, several other mechanisms have been proposed to explain the effect of diabetes on cognition: aggregation of advanced glycation end products [56], brain insulin pathways [57], competition of Ab and insulin on insulin degrading enzyme [46,58] and others. Midlife as well as late-life diabetes were shown to increase risk of dementia [46,47,54,59]. Interestingly, some have shown that in primarily non-demented elderly subjects, diabetes related characteristics, especially high insulin levels and insulin resistance, are associated with increased risk for AD only within 3 years of baseline assessment and not afterwards [58], suggesting that there is a window of opportunities for interventions that should be employed. Studies about the association of baseline diabetes diagnosis or impaired glucose metabolism and cognition are quite abundant. However, few studies have assessed the long-term effects of diabetes-related factors (glucose control, type of medications, presence of diabetes related complications) and cognitive impairment, thus preventing full understanding of the pathological mechanisms involved. Nevertheless, the association of long-term glucose levels (as measured by HbA1c levels) with hippo-campal volume [60] and cognitive function [61], as well as some encouraging results from several clinical trials in which antidiabetic strategies (rosiglitazone [62], insulin [63]) have been administered to AD patients, promote further deepening into this association. Dysregulation of blood glucose levels is associated with many other diabetes-related complications and good long-term glucose control has been demonstrated to prevent several of them [64]. Thus, intuitively, it could be assumed, that dementia could also be prevented by good long term glucose control. However, different treatment/preventive considerations may be applicable in different subpopulations of diabetic patients as demonstrated in prevention of other diabetic complications, namely stroke, myocardial infarction and death by vitamin E. The latter failed to demonstrate protection in unstratified cohorts of diabetic patients [65]. However, vitamin E was protective against these diabetes-related complications when subjects were stratified post hoc according to haptoglobin (Hp) genotype [66,67]. Hp is a hemoglobin binding protein, for which three genotypes exist: 11, 21 and 22 [68]. Hp 22 genotype provides inferior protection against hemoglobin-mediated oxidative stress [69] and has been consistently associated with increased risk of microvascular [70] and macrovascular [71] complications in T2D. Vitamin E administration was associated with 50% reduction in stroke, myocardial infarction, and cardiovascular death among subjects with Hp 22 genotype [66,67]. Similarly, prevention of cognitive decline may also differ according to haptoglobin genotype or other diabetes-related factors. Additional factors to be considered when designing strategies for prevention of cognitive decline in diabetic populations are age at onset of diabetes (midlife diabetes has been more consistently associated with cognitive decline compared with late-life diabetes), current patient s age (less aggressive strategies may be advised in older individuals) and presence of additional risk factors for cognitive decline. It is also important to consider the morbidity and mortality associated with strict diabetes control and the association of hypoglycemic episodes with increased risk for dementia, further highlighting the need to identify effective and safe preventive interventions in specific diabetic subpopulations. Hypertension The epidemiological association of hypertension with dementia and cognitive impairment is more complex, with some showing midlife as well as late-life hypertension to be risk factors for dementia [72 74], MCI [75] and cognitive impairment [76], while others showing that low blood pressure is associated with dementia [77]. Moreover, mild hypertension after age 70 was even demonstrated to be protective against AD neuropathology [78]. Such variability may suggest that the association of blood pressure with dementia has a U shaped curve, that is, that only extreme values of blood pressure (either too low or too high) are associated with increased risk for dementia [79]. Alternatively, hypertension may be a risk factor for dementia only in midlife, as reflected by the fact that in all studies showing a negative association between blood pressure and dementia, hypertension was assessed at old age [80 82]. Further complication of this association is embodied in the postulation that decline in blood pressure is part of the neurodegenerative process leading to dementia itself [83]. Clin. Invest. (2011) 1(11) 1495

6 Ravona-Springer & Korczyn Hypertension has been established to increase risk for cerebrovascular disease [84,85], suggesting that a vascular component is involved in the association of hypertension and clinical dementia. However, an increased load of AP and NFT [86] as well as hippocampal atrophy [87] have also been demonstrated in hypertensive subjects, suggesting that other mechanisms may be involved. It is not known which of these mechanisms contributes to the clinical expression of dementia [88]. Interestingly, hypertension was associated with higher occurrence of microinfarcts in subjects aged but not in those above age 80 [88], suggesting that different mechanisms may change with age or duration of hypertension. The effect of antihypertensive treatment on dementia incidence has not been consistent in the literature. Some have demonstrated that the use of antihypertensive medications was associated with reduced risk for AD [89 91], while others have shown that low diastolic blood pressure, especially in those treated with antihypertensive medications, is associated with increased risk for AD and dementia [74]. In addition, different types of antihypertensive drugs may differ in their effect on rate of cognitive decline [92]. For example, although not clinical evidence, a recent review has demonstrated that calcium channel blockers, diuretics and angiotensin converting enzyme inhibitors reduced risk for dementia, but only the latter two slowed rate of dementia progression [92]. As discussed above, the role of antihypertensive treatment in dementia progression is controversial, but this review stresses the importance of studying the role of specific mechanisms of action of antihypertensive treatment and not only achievement of blood pressure control as preventive strategies. The effect of antihypertensive treatment may differ not only according to age; ApoE status, gender, severity and duration of hypertension may also be important. It is also important to consider hypotension, a possible complication of antihypertensive treatment, as a risk factor for cognitive decline when implementing treatment for dementia prevention [93], particularly in older individuals with reduced capacity for autoregulation of cerebral blood flow. An important consideration in prevention studies is the length of the treatment required before an effect is seen. Studies of antihypertensive drugs are typically short, several months and up to a year or two. While such studies may be powered to show an effect on myocardial infarction or stroke, the effect on cognitive function may require much longer duration and thus may not be captured by these studies. Hyperlipidemia Midlife hyperlipidemia has been demonstrated to be associated with increased risk for AD [94,95], MCI or cognitive impairment. Results regarding late-life hypercholesterolemia are less consistent, with some showing no association [96,97] or even an inverse association [98]. An important factor to consider in this association is not only the total cholesterol level at a certain point in time, but also change over time. Indeed, in the Honolulu-Asia Aging study, the slope of 26 year change in total cholesterol was compared between men with incident dementia and those who remained cognitively intact. Cholesterol levels declined 15 years prior to dementia diagnosis and remained lower in men who subsequently developed dementia compared with those who did not [97]. These results suggest that temporal instability, rather than actual cholesterol levels are associated with increased risk for dementia. Low levels of cholesterol in late life may be a marker of decline on general health that also leads to neurodegeneration [97]. Statins, commonly prescribed drugs that block the key enzyme in the cholesterol synthesis pathway, have been suggested to protect against AD through several pathways unrelated to their effect on cholesterol itself: modulation of APP metabolism [99,100], reduction of inflammatory processes [101,102], lowered risk for cerebrovascular disease [103] and others. Some [ ], but not all epidemiological studies [ ] showed a protective effect of statins against dementia. In a 12 year followup study of more than 900 nondemented elderly persons, no relationship was found between use of statins and cognitive impairment, incident AD, AD pathology or cerebral infarctions [111]. Two recent Cochrane reviews concluded that statins given to individuals at risk for vascular disease at late life have no effect of dementia or AD prevention [112] and that there are insufficient data to recommend statins for the treatment or prevention of dementia [113]. Although the effects of hypertension and dyslipidemia are still controversial, heterogeneity in these factors in studied populations may obscure an effect of antidementia drugs, and should be considered when planning and interpreting such studies. One significant factor which should be considered is the study duration (time from initial exposure to treatment to time of outcome measurement). If a drug only delays the onset of dementia rather than reducing it, this may be reflected as an early reduced incidence, but the survivors may later catch up, leading to diminution or even apparent reversal of the initial effect. This has probably occurred in a nonsteroidal anti-inflammatory (NSAID) study [114]. This effect will be particularly obvious if the intervention (e.g., antihypertensive drugs) reduce mortality from competing causes and thus the neurodegenerative process may become evident. In contrast to the aforementioned risk factors, age, gender and genetic substrate are non-modifiable. Nevertheless, these risk factors may interact with

7 Etiology of Alzheimer s & its implications for the design of clinical trials modifiable risk factors, affecting AD incidence, rate of cognitive decline and mechanisms involved, thus potentially requiring adjustment in preventive strategies. Age is considered to be the most important risk factors for LOAD [115] ; however, the effect of age on rate of cognitive decline has not been consistent, with some studies showing no effect [116,117], while others show faster rate of cognitive decline with rising age [118] or a different effect of age at different stages of cognitive functioning [119]. Some have shown no effect of age per se on rate of cognitive decline but rather that the interaction of age with cardiovascular risk factors [98] or cerebrovascular disease [120] affects rate of decline. Inconsistencies may be ascribed to differences in methodologies: the populations studied, methods used for measurement of cognitive decline or baseline cognitive function. It is, therefore, important to consider the interaction of age with other risk factors for AD as well as its contribution to rate of cognitive decline at different ages and different stages of cognitive performance in order to optimize preventive strategies and choose the appropriate measurement tools. The genetic component is an important nonmodifiable risk factor for sporadic LOAD. Offspring of AD patients are at increased risk of developing AD compared with offspring of nondemented individuals [121,122]. The most established genetic modifier of LOAD is the ApoE4 allele, associated with increase lifetime risk for AD [123], earlier appearance of symptoms [124,125] and higher rates of conversion from MCI to dementia [126]. ApoE has been suggested to play a key role in maintenance and repair of neurons by promotion of lipid transfer to and from damaged neurons [127], as well as by several other mechanisms. There are three common isoforms for ApoE: ApoE2, ApoE3 and ApoE4, the latter being a major genetic risk factor for AD. Neuropathological studies have demonstrated that ApoE4 is associated with a higher load of AP and NFT [128], impaired synaptic plasticity [129], increased inflammation [130] and more prominent hippocampal atrophy [119]. ApoE4 is thought to affect brain function through Ab as well as other mechanisms [131]. ApoE has been demonstrated to interact with other, modifiable, risk and protective factors for dementia, such as T2D and prediabetes states, hyperlipidemia, exercise, alcohol consumption and sex hormones [126]. The co-occurrence of ApoE4 with other risk factors for dementia, such as diabetes, hyperlipidemia, traumatic brain injury and others has been demonstrated to increase the risk for dementia further than the risk predicted by the additive effect of both risk factors [51,132,133]. Furthermore, such co-occurrence was associated with worse cognitive performance, even in non-demented subjects [134]. In diabetes for example, several mechanisms have been suggested for the synergistic effect of T2D and ApoE4: impaired neuronal repair mechanism in ApoE4 carriers that is further challenged by the neuronal damage associated with diabetes, lower levels of insulin degrading enzyme in ApoE4 carriers, confronting higher need for insulin degradation in diabetes and so on [134]. Interestingly, the salutary effects of some preventive strategies have been demonstrated to be more prominent in ApoE4-positive subjects (e.g., a-linoleic acid consumption was protective from AD only in ApoE4 carriers in the Chicago Health and Aging Study [135]), while others in ApoE4 negative subjects (e.g., estrogen use was associated with less cognitive decline in ApoE4 negative women but not in ApoE4 positive women participating in the cardiovascular health study [136]). These findings, although mostly from post hoc analyses, and with need for replication in further studies, may indicate an important specific interaction with the strongest genetic risk factor for dementia and stress the need to study preventive strategies in populations at risk, with stratification to different subpopulations. An important observation is that the ApoE effect is age-dependent, and weakens in advanced age [137]. It is not clear what the explanation of this phenomenon is, but it should be taken into account when designing and interpreting the results of anti-dementia studies. It is also not clear whether treatments delaying the onset of dementia will delay or advance the age at which the effect of ApoE is less prominent. The genetic risk for AD, attributable to the ApoE gene, in the general population is probably lower than 20% [138], suggesting the involvement of other genes. Indeed, several other genetic risk factors have been identified. These are of much smaller effect than ApoE4, but since the effect of several interventions are affected by ApoE status, a similar modifying effect can be expected by additional genetic polymorphisms and, therefore, genetic status of the patient needs to be available to allow ana lysis of such possible interactions. There is a growing amount of evidence showing that variants on the SORL1 gene affect the risk for AD [139]. SORL1 is considered to protect APP from b-secretase activity by diverting it to alternative pathways. Thus, in the absence of SORL1 activity, APP tends to enter the amyloidogenic pathways [140,141], such as Clusterin, CR1 and PICALM, suggested to have a role in Ab clearance, and that have been demonstrated to be associated with increased risk for AD [142]. Genetic alterations in multiple GAPD gene family members [143], IL-10 gene promoter polymorphism [144], variability in the IDE gene [145] and others [138]. Thus, further studies regarding gene environment interaction in AD and dementia are needed. However, the importance of these genetic risk factors is likely to be small. Clin. Invest. (2011) 1(11) 1497

8 Ravona-Springer & Korczyn Gene environment interactions are also important. Even monogenic DIAD, like the cases of APP or PSEN mutations, only manifest at late adulthood. It is possible that a second hit needs to occur, and identifying such environmental factors is important. Despite the abundance of data pointing towards the association of cardiovascular and genetic risk factors for AD, cognitive impairment and dementia, preventive strategies are still not available. Further studies should elucidate the mechanisms involved and the optimal interventions in specific subpopulations of patients at risk. There are several difficulties in the execution of primary prevention trials: such trials require thousands (or more) of participants [146] and many years to complete [146]. There are also difficulties resulting from the variation in methodologies used in different epidemiological studies which constitute, at least partially, the basis for preventive intervention. In non-interventional, longitudinal epidemiological studies, there is currently much heterogeneity regarding the outcome measures; cognitive performance, MCI, dementia or neuropathology (for example, see above varying associations between baseline diabetes and clinical type of dementia, rate of cognitive deterioration and neuropathology). Such heterogeneity affects the results, and if used as a basis for primary prevention interventions, may affect the duration of intervention, duration of follow-up, cost of treatment as well as the risk:benefit ratio that will be part of an interventional study. An additional significant factor, which should be considered, is the study duration (time from initial exposure to treatment to time of outcome measurement). The role of a certain treatments in primary prevention of a disease may differ from their role in treatment of an already existing disease, as exemplified in the AD Anti-inflammatory Prevention Trial (ADAPT) [147] in which NSAID treatment was associated with increased rate of progression in already demented individuals; however, in asymptomatic individuals, treatment with naproxen was associated with reduced AD incidence (although only after 2 3 years). This complexity is further stressed in AD since the preclinical stages of the disease probably start decades prior to clinical diagnosis. Future studies should form the basis for determination of the optimal time for intervention as well as optimal time for follow-up of cognitive outcome. Dementia incidence in primary prevention trials performed until now has been low compared with incidence in population based cohorts [146, ], requiring larger sample sizes or prolongation of follow-up periods. The financial implication of the latter should be considered. In addition, the optimal duration and timing of intervention are unknown, with some studies (e.g., NSAIDs or hormone replacement therapy) showing increased risk for AD, depending on the stage of disease at which they were introduced and duration of treatment [147,151,152]. Some preventive treatments may expose the subjects to increased risk for other complications (depending on treatment type). These risks present ethical challenges. Prospective randomized controlled trials of treatment of cardiovascular risk factors are also inappropriate since it is unethical to give placebos instead of active medications to control these risk factors, particularly since some of these studies are very long and may need to start in midlife. Thus, additional knowledge about the mechanism of action and associated risk of preventive interventions at different stages of the disease should be gathered before such interventions can be implemented in large populations for prolonged periods of time. Further recommendations for designs of clinical trials aimed to assess the efficacy of treatment of cardiovascular risk factors in preventing or postponing AD are also limited due the complexity of interaction between these factors and the lack of available, highly reliable consensus-based diagnostic criteria for cognitive decline, MCI and AD. In addition, in different studies performed up to date the available criteria have not been uniformly applied [153] and have not used the homogenous outcomes (some have used dementia as an outcome, while others have used specific type of dementia, neuropathology, cognitive performance in tests). This complexity is exemplified in the conclusions of the NIH Conference [153] regarding the prevention of AD and cognitive decline, and in a recent review of the literature on the role of risk and protective factors for AD, both of which concluded that further research that addresses the limitations of existing studies is needed before making recommendations on interventions [154]. A better understanding of the role of cardiovascular factors may be accomplished by bridging the discrepancies between results from different epidemiological studies. Such discrepancies may result from baseline characteristics, such as ethnicity and genetic factors, differences in health-related life-style factors and other relevant factors such as education, smoking, physical and intellectual activities and obesity, as well as from methodological issues such as age range of populations studied, type of cohort (clinical vs population), duration of follow-up, definition of risk factors (self report, medical records, objective measurement), dynamics of risk factors over time and definition of end point (cognitive performance, dementia incidence, volumetric brain imaging or neuropathology). Some advances can be achieved by adding a cognitive outcome to future trials for the treatment of cardiovascular risk factors in currently cognitively intact subjects. These trials should include an outcome of

9 Etiology of Alzheimer s & its implications for the design of clinical trials cognition and have a follow-up of sufficient duration to assess this outcome. The populations studies should be stratified according to cardiovascular disease and its duration, severity, age at exposure and efficacy of treatment on risk factor control. The significant implication of attrition rates and costs of such long trials should be taken into consideration. These trials will aim to control the cardiovascular risk factors and a secondary end point can be to delay cognitive decline according to consensus-reached and homogenous criteria, and will be based on understanding of the natural course of the risk factors discussed with advancing age and their effect on cognitive decline at different ages of exposure. In light of the ethical, methodological and other limitations associated with initiating primary prevention studies primarily aimed at dementia prevention (rather than risk factor control), an additional possible bridging strategy that may be used is to enroll only those at higher risk for dementia (family history, genetic susceptibility, preclinical phases of disease), although the results of these studies will not necessarily apply to people not fulfilling those criteria. Future perspective As the dementia epidemic materializes, new thinking must lead us in our fight against it. Attempts to cure or stop the disease are hampered by a lack of understanding of the very early changes leading to neurodegeneration, and possibly mistaken assumption that amyloid has an important role in the early stages of the disease. AD is heterogeneous in its cause and phenomenology, including its age of onset and rate of progression. Most AD patients suffer from co-morbid conditions, which may affect disease progression. Several genetic contributions are also important. All these factors must be taken into account when designing a clinical study or interpreting its results. Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert t estimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript. Executive summary Many clinical trials in Alzheimer s disease (AD) have failed. The etiology of the most common form of the disease, late onset AD is not well understood and is not necessarily identical to the rare form of autosomal dominantly inherited familial AD. 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