Advances in Alzheimer’s Disease Management || Diagnosis of Alzheimer’s disease

12 © 2011 Future Medicine1212 www.futuremedicine.com

About the Authors

Pedro Rosa-NetoPedro Rosa-Neto is an assistant professor of neurology, neurosurgery and psychiatry at McGill University, affiliated to the Douglas Research Centre (Canada). He is a clinical neurologist with expertise in quantification of brain function using imaging techniques, in particular PET. His research interests focus on imaging biomarkers for neurodegenerative diseases. He directs the laboratory for translational neuroimaging, which aims to use imaging techniques to advance the diagnosis of Alzheimer’s disease to a preclinical stage. He also conducts research on new treatments to prevent and treat dementia symptoms at the McGill Alzheimer’s Disease Research Unit.

Jared Rowley, Antoine Leuzy, Sara Mohades, Monica Shin, Marina T Dauar & Serge GauthierMcGill Centre for Studies in Aging, Translational Neuroimaging Laboratory, Verdun, Montreal, Quebec, Canada

For reprint orders, please contact: [email protected]

© 2012 Future Medicine 13

doi:10.2217/EBO.12.66

Chapter 2

Diagnosis of Alzheimer’s disease

Pedro Rosa-Neto, Jared Rowley, Antoine Leuzy, Sara Mohades, Monica Shin, Marina T Dauar & Serge Gauthier

Alzheimer’s disease (AD) accounts for approximately 70% of dementia cases, and is characterized by the need for specialized, high-cost long-term care. It is estimated that by the year 2050, AD will affect 13.5 million individuals within the USA alone, a prevalence rate representing 10% of that predicted at the global level [1]. As such, AD stands as one of the most important health challenges of the 21st Century.

Rationale for a revised nosology emphasizing the dynamic nature of AD pathology 14

NIA-AA criteria incorporate the current physiopathological paradigm for AD 14

NIA-AA criteria incorporate the concept of biomarkers of AD 15

Biomarkers of amyloid deposition 15

Biomarkers of neurodegeneration 19

Dynamic biomarker of AD pathological cascade hypothesis 23

Limitations for the use of biomarkers in clinical practice 23

NIA-AA criteria for presymptomatic, MCI & dementia phases of AD 24

Spectrum of clinical presentations associated with AD pathology 29

Clinical subtypes 29

Biomarkers in the differential diagnosis of AD dementia 34

Rosa-Neto, Rowley, Leuzy et al.

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The pathological signature of Alzheimer’s disease (AD) consists of extracellular deposits of amyloid plaques (APs) and neurodegenerative changes, such as intraneuronal inclusions of neurofibrillary tangles (NFTs), cell depletion and atrophy [2,3]. In typical cases, AD neuropathology (AD-P) begins in the mesial temporal lobe and slowly propagates to the temporal, parietal and frontal associative cortices in a limbic-heteromodal manner [4,5]. Occasionally, AD-P propagates within heteromodal cortices following atypical patterns [6]. Consequently, a spectrum of clinical presentations occurs in accordance with the pathways along which AD-P propagates during the course of the disease. Indeed, the dynamics of pathological progression dictates the severity of the clinical symptomatology (asymptomatic, mild or dementia).

Until recently, the diagnosis of AD was based on a ‘static’ association between an amnestic dementia syndrome and the AD-P. Today, the diagnosis of AD refers to a dynamic clinicopathological entity, now encompassing predementia syndromes, such as mild cognitive impairment (MCI) and preclinical AD. In this chapter, we summarize the diagnosis of AD based on the nosology proposed by the National Institute of Aging (NIA) and Alzheimer’s Association (AA), as well as propose an algorithm for evaluating typical and atypical presentations of AD.

Rationale for a revised nosology emphasizing the dynamic nature of AD pathologyUntil recently, AD diagnostic criteria were grounded in clinicopathological constructs of dementia developed during the 1970–1980s. The 1984 National Institute of Neurological and Communicative Disorders and Stroke – Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) criteria emerged from the need to refine research protocols, to assess the natural history of AD, and to reduce the high rate (>20%) of false positives among autopsied cases of AD [7].

The need for revisions to the NINCDS-ADRDA criteria result, at least in part, from the failure of treatments in individuals with the diagnosis of probable AD, issued on the basis of the NINCDS-ADRDA criteria. NINCDS-ADRDA revisions, initiated by Dubois and collaborators in 2007 [8], were further elaborated by various NIA-AA working groups. The NIA-AA revisions integrated scientific advances, recycled and expanded diagnostic criteria, which will ultimately accelerate the delivery of novel treatments for AD.

NIA-AA criteria incorporate the current physiopathological paradigm for ADAt the level of physiopathology, the NIA-AA criteria incorporate the notion of temporal progression, which assumes that AD-P initiates decades


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before the onset of dementia [9]. Thus, the new diagnostic criteria now includes preclinical AD, MCI due to AD and AD dementia as part of the spectrum of clinical severity secondary to brain AD-P. In addition, it recognizes focal cortical variants (language, working memory, visuoconstruction) of AD that do not necessarily follow the classic amnestic clinical presentation [6,10,11]. As a result, the new criteria now include clinical variants of AD not recognized previously by the NINCDS-ADRDA criteria [7]. Regarding genetic mutations, the NIA-AA criteria recognizes AD as a phenotype of specific genetic mutations, and provides a special category for mutation carriers [9,12]. The presence of PS1, PS2 and APP mutations now increases the diagnostic certainty in individuals with probable AD.

NIA-AA criteria incorporate the concept of biomarkers of ADThe value of imaging and fluid biomarkers for diagnosing and monitoring disease progression in living individuals has been acknowledged by the NIA-AA criteria [9]. Biomarker is defined as a “characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” [13]. As such, biomarkers play a fundamental role in identifying a diversity of neuropathological findings, which are critical to the diagnosis, risk assessment and decision-making process with AD patients [14–17]. The availability of biomarkers for quantifying AD-P in vivo tremendously advanced the understanding of AD as a dynamic clinicopathological entity. Indeed, biomarkers expand the intrinsic cross-sectional nature of neuropathology techniques by allowing longitudinal observations necessary to understand the temporal progression of neuropathology in neurodegenerative diseases.

During the last years, research in AD has elaborated the construct that the fibrillar Ab-peptide, a major constituent of AP, constitutes the central neuropathological event [18–20] of AD by triggering a downstream cascade of neurodegenerative events leading to dementia (amyloid cascade hypothesis) [18–20]. This amyloidocentric disease model supports the basis for the classification of biomarkers as biomarkers of amyloid deposition or biomarkers of neurodegeneration (Table 2.1).

Biomarkers of amyloid depositionBiomarkers of amyloid deposition refer to indices of amyloid deposition obtained either by PET or the analysis of cerebrospinal fluid (CSF). Brain Ab-peptide [21] fibrillary deposits detected by increased retention of amyloid imaging PET agents or low Ab1–42-peptide CSF concentrations



Table 2

.1. B

iom

ark

ers

for dia

gno

sis

of Alzheim

er’s

disease

.

Neu

ropa

thol

ogic

al

proc

esse

sPr

oces

s of

inte

rest

Met

hod

Out

com

eIn

terp

reta

tion

Am

yloi

dosi

sFi

brill

ar a

myl

oid

avai

labi

lity

[11C]

PIB

PET

Incr

ease

d re

tenti

onA

myl

oid

depo

sitio

n

Fibr

illar

am

yloi

d av

aila

bilit

y[18

F]flo

rbet

apir

PET

Incr

ease

d re

tenti

onA

myl

oid

depo

sitio

n

Fibr

illar

am

yloi

d av

aila

bilit

y[18

F]flo

rbet

apen

PET

Incr

ease

d re

tenti

onA

myl

oid

depo

sitio

n

Fibr

illar

am

yloi

d av

aila

bilit

y[18

F]flu

tam

etam

ol P

ETIn

crea

sed

rete

ntion

Am

yloi

d de

posi

tion

Ab 1–

42 CS

F co

ncen

trati

ons

Ab 1–

42D

eclin

e in

CSF

co

ncen

trati

ons

Am

yloi

d de

posi

tion

Ab 1–

42 se

rum

leve

lsA

b 1–42

Dec

line

in s

erum

co

ncen

trati

ons

Am

yloi

d de

posi

tion

Neu

rode

gene

ratio

nBr

ain

met

abol

ism

[18F]

FDG

PET

Brai

n hy

pom

etab

olis

mSy

napti

c de

pleti

on

(Dow

nstr

eam

) To

tal T

au C

SF c

once

ntra

tions

Lum

bar

punc

ture

Incr

ease

d CS

F co

ncen

trati

onCe

ll de

pleti

on

Tau-

181

CSF

conc

entr

ation

sLu

mba

r pu

nctu

reIn

crea

sed

CSF

conc

entr

ation

Tau

phos

phor

ylati

on

Brai

n at

roph

y M

RID

ecre

ased

vol

ume

loss

Atr

ophy

Non

AD

Br

ain

lesi

ons

MRI

Brai

nTu

mor

, vas

cula

r di

seas

e

Met

abol

ism

[18F]

FDG

PET

Brai

nLB

D, F

TD

R/O

LBD

[123 I]i

oflup

ane

(DAT

) Br

ain

Redu

ction

of d

opam

ine

tran

spor

ters

R/O

CJD

Lum

bar

punc

ture

14–

3–3

CSF

Neu

rona

l dep

letio

n

CJD

: Cre

utzf

eldt

–Jak

ob d

isea

se; C

SF: C

ereb

rosp

inal

flui

d; ft

d: F

ront

al te

mpo

ral d

emen

tia; L

BD: L

ewy

body

dis

ease

.



constitute powerful means for in vivo detection of pathological brain amyloid concentrations [22].

Mega-aggregates of Ab-peptide form the core of APs in AD. The Ab1–40/2 peptides result from the proteolysis of an integral membrane protein called amyloid precursor protein (APP). The Ab1–42 peptide is secreted to the extracellular space via the amyloidogenic pathway, which refers to the sequential APP proteolysis by the enzymes b- and g-secretases. Once in the extracellular space, Ab1–42 molecules undergo a massive aggregation process, which generates the inert core of an AP. Importantly, a neurotoxic soluble amyloid conformation (oligomers) are transiently formed during the process of plaque formation [23]. In fact, oligomeric forms of Ab concentrations are increased in the CSF of AD patients [24,25]. The toxicity of Ab1–42 oligomers has been extensively demonstrated by numerous studies (reviewed in [26]). From the biomarker perspective, while amyloid PET agents detect abnormal fibrillar amyloid load in AD brain, CSF measures detect declines in Ab1–42concentrations. In fact, Ab1–42CSF concentrations and amyloid load detected by [11C]PIB are correlated [27,28]. Low Ab1–42CSF concentrations possibly occur due to excessive retention of Ab1–42 in the AD brain APs, the so-called sink effect.

The [11C]-labeled thioflavin-T derivative called Pittsburgh compound-B (PIB) (Figure 2.1) [29] is the prototype of amyloid imaging agents for PET.

[11C]PIB served as a proof-of-concept of amyloid imaging [30–32]. In summary, [11C]PIB imaging have demonstrated high sensitivity (98%) and good specificity (66%) of the amyloid imaging agents for quantifying fibrillary amyloid deposits in living AD patients. [11C]PIB specificity is due to the presence of abnormal amyloid load and is present in nearly 30% of cognitively intact individuals [33–36]. Interestingly, [11C]PIB shows amyloid pathology in a subset of patients with a clinical diagnosis of Lewy body dementia, cerebral amyloid angiopathy or frontotemporal dementia, suggesting, perhaps, mixed pathology [15,37–43]. [11C]PIB imaging in patients with subjective cognitive impairment (SCI) is similar to healthy elderly [44]. Nearly two-thirds of MCI individuals have pathological brain amyloid accumulation [45]. In those patients who are MCI carriers of AD pathology, amyloid load, as detected by [11C]PIB retention, seems to predict conversion to dementia [46–48].

Due to its short half-life (20 min), the use of [11C]PIB is restricted to centers with a cyclotron and radiochemistry facility. However, a new generation of [18F]-amyloid (half-life 110 min) agents, such as [18F]flutemetamol, [18F]florbetapir, [18F]florbetaben and [18F]AZD4694 have been developed for large-scale use and distribution. Similarly to [11C]PIB, [18F]amyloid agents



Figu

re 2

.1. A

vera

ge d

istr

ibuti

on o

f [11

C]PI

B (le

ft s

ide)

bin

ding

in in

divi

dual

s w

ith

NCI

(n =

13)

, MCI

(n =

52)

and

AD

(n =

27)

.

NC

IM

CI

AD

NC

IM

CI

AD

The

amyl

oid

load

in M

CI r

emai

ns in

bet

wee

n N

CI a

nd A

D le

vels

. Ave

rage

dis

trib

ution

of [

18F]

florb

etap

ir in

NCI

(n =

116

), M

CI (n

= 3

9) a

nd A

D (n

= 5

1) is

sh

own

on th

e ri

ght p

anel

. Not

e th

at th

e re

gion

al p

atter

n of

ret

entio

n of

am

yloi

d ag

ents

is s

imila

r bu

t not

the

sam

e. T

he c

olor

sca

le in

dica

tes

the

mea

n re

gion

al r

eten

tion

of [11

C]PI

B or

[18F]

florb

etap

ir.

AD

: Alz

heim

er’s

dis

ease

; MCI

: Mild

cog

niti

ve im

pair

men

t; N

CI: N

o co

gniti

ve im

pair

men

t.



have shown good in vitro/in vivo correlations and binding to the Ab1–40/2 b-sheet-rich fibrillar deposits of Ab (Figure 2.1) [21,49,50]. Not surprisingly, the preliminary evaluation of these novel imaging agents indicate similar sensitivity as PIB in research populations (Figure 2.1) [31,49,51–54]. In contrast to [11C]PIB [18F]flutemetamol, [18F]florbetapir and [18F]florbetaben have significant white matter binding, although [18F]AZD4694 seems to have less issues related to nonspecific binding compared to other radiopharmaceuticals (Figure 2.2) [55].

Soluble Ab1–42 and Ab1–40 result from amyloidogenic APP degradation. While Ab1–42CSF concentration has been extensively utilized as a reliable indicator of brain amyloid pathology [28], Ab1–40 concentrations fail to discriminate AD. Ab1–40 declines have been observed in certain cases of amyloid angiopathy [56]. In AD, it is expected that concentrations of CSF Ab1–42 be reduced by nearly 50% relative to age-matched controls [57–59]. Low CSF Ab1–42 concentrations in AD have been validated by two postmortem studies [60]. Low Ab1–42 concentrations have also been described in individuals with Lewy body dementia, perhaps indicating mixed pathology [61–65]. Similarly to amyloid imaging agents, CSF Ab1–42

Figure 2.2. [18F]florbetapir imaging form an amyloid-negative NCI individual (left) and an amyloid-positive AD patient (right).

Note that the grey-white matter contrast (left arrow) observed in controls is lost in AD due to cortical deposits of Ab1–42 (right arrow). AD: Alzheimer’s disease; NCI: No cognitive impairment.



concentrations are linked to the presence of APOE4 alleles [66,67]. Despite its utility in the differential diagnosis of dementia, CSF Ab1–42does not correlate with disease duration or severity [68,69] and does not significantly progress during the course of the disease [70]. The slow progression of Ab in AD – as revealed by [11C]PIB or CSF Ab1–42 concentrations – supports the idea that amyloid pathology occurs very early in the disease process and tend to stabilize by the time the first clinical signs of dementia appear [35,70].

In clinical settings, biomarkers of brain amyloid accumulation certainly add on the differential diagnosis of atypical presentations of dementia in conjunction with biomarkers of neurodegeneration. However, severity of amyloid pathology detected by biomarkers is not useful to monitor disease progression since it has a low correlation with AD clinical measures [71–77]. Moreover, current amyloid agents have limited application for predicting the rate of progression in cognitively normal individuals [3,4,34,72,78–81].

Biomarkers of neurodegenerationToday, PET [18F]-fluorodeoxyglucose ([18F]FDG ), MRI volumetry, CSF total tau (t-tau) or CSF phosphorylated tau (p-tau) are the most relevant biomarkers of neurodegeneration. They provide information regarding neurodegenerative process present in carriers of AD pathology [22]. Assuming an amyloidocentric framework proposed by the amyloid cascade hypothesis, declines in brain function revealed by biomarkers of neurodegeneration occur as a result of amyloid toxicity, although the mechanisms linking amyloid pathology and neurodegeneration remain elusive [26].

Decline of PET [18F]FDG uptake in allocortical and homotypical brain regions has been recognized as one of the earliest neurodegenerative signs of AD and has been interpreted as reflecting synaptic depletion [82–84]. AD is associated with a specific metabolic signature characterized by hypometabolism in the hippocampus, posterior cingulate and inferior parietal cortices (Figure 2.3). In fact, [18F]FDG hypometabolism is observed in cognitively normal individuals at genetic risk for AD [85]. In MCI individuals, the presence of [18F]FDG metabolic signature predicts development of dementia [86–88]. In advanced stages of dementia, the frontal and temporal neocortices also become hypometabolic [17,89]. In patients with AD, cortical hypometabolism has nearly 84–93% sensitivity and 73% specificity as compared with neuropathological diagnosis of AD [17]. Moreover, PET [18F]FDG improves the diagnostic accuracy of AD [14,22]. PET [18F]FDG plays an important role in differentiating AD from Lewy body dementia (cingulate island sign) and frontotemporal dementia with sensitivity of 91% and specificity of 71 and 65%, respectively [90–94]. While frontotemporal dementia show reduction in the frontal and temporal



lobes, Lewy body dementia is characterized by hypometabolism in the occipital lobe creating a cingulate island sign [92–94]. Interestingly, for monitoring disease progression or clinical severity, [18F]FDG uptake performs better than amyloid imaging agents [95–98], with hypometabolism detected by [18F]FDG correlating with cognitive impairment along the continuum of preclinical to dementia stages of AD [99]. Together, these elements support FDG-PET uptake as a valid biomarker with significant clinical applications in AD [100].

Structural MRI has been extensively studied in dementia as a biomarker of structural brain changes. In AD, atrophy of the hippocampus and entorhinal cortex as well as increased ventricular volume have an important diagnostic value in AD (Figure 2.4). MRI outcome measures of brain atrophy convey dendritic pruning, synaptic loss and neuronal depletion [101]. Manual or voxel-based estimates of brain atrophy strongly correlate with various cognitive deficits observed in clinical and preclinical phases of AD [102]. Rates of atrophy observed in the entorhinal cortex, hippocampus and temporal lobe as well as ventricular enlargement correlate with rates of cognitive decline [102–111]. Although brain atrophy detected by MRI is not necessarily specific, regional atrophy observed in AD patients overlaps with Braak staging at autopsy [112,113]. Finally, MRI provides crucial information regarding differential diagnosis, comorbidities with cerebrovascular disease or other brain pathologies underlying dementia syndromes [114].

Figure 2.3. Distribution of [18F]FDG in individuals with NCI (n = 1), MCI (n = 1) and AD (n = 1).

NCI MCI AD

The arrow indicates hypometabolism in the inferior parietal cortex, a feature typically observed in AD patients. AD: Alzheimer’s disease; MCI: Mild cognitive impairment; NCI: No cognitive impairment.



t-Tau and p-Tau constitute the classic CSF biomarkers for neurodegeneration. The Tau protein is a constituent of neuronal microtubules, which are cell structures responsible for the motility of proteins and organelles within the neuron [115]. The functional expression of microtubules is modulated via phosphorylation of numerous serine and threonine residues present in the Tau protein [116]. Abnormal Tau hyperphosphorylation deposits in AD neurons is observed on NFTs, or dystrophic neurites present in the neuritic plaques [117]. CSF Tau and t-Tau concentrations increase nearly 40–50% in AD. In MCI Tau and t-Tau concentrations increases nearly 30–40% [118,119]. Synaptic injury or cellular death contributes to the leakage of Tau and p-Tau to the extracellular space. In fact, CSF t-Tau concentration is also increased in patients with encephalitis, trauma and stroke [120–122]. CSF Tau concentration is useful for distinguishing AD patients from control subjects as well as non-AD forms of dementia, although overlap at the level of pathology often exists [67,123].

Despite numerous threonine and serine phosphorylation sites present in Tau protein, AD is better characterized by hyperphosphorylation at the position 181 (p-Tau181) or 232 (p-Tau232). Particularly, discrimination between AD and dementia with Lewy bodies or FTD is maximized by p-Tau181 or p-Tau231 [124]. Indeed, Ab1–42/p-Tau ratio provides the highest diagnostic performance in terms of identifying the predementia stage of AD with a sensitivity of 83% and specificity of 72% [118,125–127].

Biomarkers for the integrity of nigrostriatal projections are particularly useful for differentiating Lewy body dementia from AD. PET [11C]DTBZ or

Figure 2.4. Representative T1-weighted structural MRI coronal slices obtained in NCI (n = 1), MCI (n = 1) and AD (n = 1).

NCI MCI AD

Note atrophy of the entorhinal cortex (yellow arrow) and hippocampus (orange arrow) as well as enlargement of the ventricles (red arrow). AD: Alzheimer’s disease; MCI: Mild cognitive impairment; NCI: No cognitive impairment.



SPECT [123I]iodoflupane show declines of binding in the nigrostriatal projections, which conveys high nigral Lewy body load [92,128–130]. Alternatively, [123I]MIBG epicardium imaging can be used to differentiate AD from Lewy body dementia. Reduced [123I]MIBG epicardic uptake conveys low tyrosine hydroxylase-immunoreactive nerve fiber density characteristic of Lewy body dementia but not AD or normal controls [131,132].

Dynamic biomarker of AD pathological cascade hypothesisPreliminary cross-sectional biomarker data provided the empirical basis for a disease model called ‘dynamic biomarker of AD pathological cascade’ (DBAPC). Proposed by Jack and collaborators, this model is widely accepted by the research community [22]. The DBAPC proposes progression of biomarker abnormalities as a surrogate for progressive neuropathological changes (Figure 2.5). Similarly to the amyloid cascade hypothesis, the DBAPC hypothesis assumes amyloidosis as an early event leading to a cascade of successive neurodegenerative processes (i.e., Tau-pathology, synaptic depletion and cell loss) resulting in dementia [100,133–135]. The

Figure 2.5. Dynamic biomarkers of Alzheimer’s disease pathological cascade, as proposed by Jack and collaborators.

No

rmal

ized

bio

mar

ker

mag

nit

ud

e

Clinical disease stage

Cognitively normal EMCI LMCI Dementia

AmyloidosisTau phosphorylationBrain structureMemoryClinical function

This model predicts a mild cognitive impairment and a preclinical state with pathological levels of amyloid, neurodegenerative changes and subclinical cognitive impairment. EMCI: Early mild cognitive impairment; LMCI: Late mild cognitive impairment. Adapted from [22].



model predicts initial abnormalities at the level of biomarkers for amyloidosis followed by sequential tissue functional abnormalities (hypometabolism), cell death (release of Tau and p-Tau in the CSF) and brain atrophy detectable by MRI [6–17]. The model also proposes that memory and functional declines occur as a function of neurodegeneration [22,136]. Importantly, the DBAPC hypothesis anticipates a clinical spectrum comprising preclinical, MCI and dementia AD stages, with each phase possessing specific biomarkers signatures.

Limitations for the use of biomarkers in clinical practiceBiomarkers of amyloid deposition and neurodegeneration tremendously advanced the identification of AD pathology in populations at risk for developing dementia. However, the process of translating these novel technologies is a challenge due to the complex interface between research and clinical practice. At this point, biomarkers are not recommended for screening asymptomatic individuals. For MCI individuals, the use of biomarkers in clinical practice still finds numerous obstacles, such as the lack of therapies able to arrest the clinical progression to dementia. Moreover, normative standards for fluid and imaging biomarker technologies are still a work in progress. For example, there are several issues regarding the feasibility of large-scale use of [18F]amyloid imaging agents due to the undesirable high uptake in the white matter (Figures 2.1 & 2.5).

Hitherto, it has been unclear whether a single or a combination of biomarkers is required to assess populations at risk for developing dementia. In fact, further population-based studies are necessary to define cut-off values, stability and the likelihood of progression to dementia for all biomarkers. Further research is also necessary to identify those biomarkers capable of identifying individuals ‘on the verge of conversion’ from those carriers of amyloid pathology who will remain stable for several years. Unfortunately, the current body of knowledge regarding biomarkers fails to provide a robust empirical framework for evaluating clinical scenarios characterized by ambiguous, indeterminate or conflicting results involving multiple biomarkers. Similarly, it is applicable regarding those clinical cases suggestive of mixed pathology. Thus, further studies are necessary to prioritize biomarkers and outline their validity in numerous clinical and research scenarios.

NIA-AA criteria for presymptomatic, MCI & dementia phases of ADAccording to the NIA-AA, the term AD encompasses a clinicopathological continuum characterized by a gradual cognitive decline associated with an evolving brain neuropathology [9,22,137]. Thus, the NIA-AA criteria consider



Table 2.2. Summary of NIA-AA diagnoses associated with stages or clinical presentations of Alzheimer’s disease.

AD stages Requirements Setting

Dementia stage

Probable AD core clinical criteria Clinical history/MRI CTR

Pathophysiologically proved AD dementia Neuropathology TR

Probable AD with increased level of certainty (documented decline)

Longitudinal cognitive assessments TR

Probable AD with increased level of certainty (mutation carrier)

Molecular diagnosis (PS1, PS2 and APP mutations)

TR

Probable AD with high level evidence of pathophysiological process

Corroborated by abnormal BOA or BON R

Probable AD with intermediate level evidence of pathophysiological process

Corroborated by abnormal BOA and BON

R

Possible AD core clinical criteria Atypical course, etiologically mixed presentations or comorbidities

CTR

Possible AD with evidence of pathophysiological process

Corroborated by BOA + BON or neuropathology

R

Dementia unlikely to be due to AD Evidence for an alternative diagnosis CTR

MCI stage

MCI due to AD core clinical criteria Clinical criteria CTR

MCI due to AD – high likelihood Corroborated by abnormal NPA, BOA and BON

R

MCI due to AD – intermediate likelihood Corroborated by abnormal NPA, BOA or BON

TR

MCI due to AD uninformative biomarker Borderline or conflicting BOA or BON results

R

MCI unlikely due to AD Corroborated by normal BOA and BON R

Preclinical stage

Stage III preclinical AD Corroborated by abnormal BOA, BON and NPA

R

Stage II preclinical AD Corroborated by abnormal BOA and BON

R

Stage I preclinical AD Corroborated by abnormal BOA and normal BON

R

AD: Alzheimer’s disease; APP: Amyloid precursor protein; BOA: Biomarker of amyloid accumulation; BON: Biomarker of neurodegeneration; C: Clinical setting; MCI: Mild cognitive impairment; NPA: Neuropsychology assessment; R: Research setting; T: Tertiary clinical setting.



preclinical AD, MCI due to AD and dementia sequential stages part of the natural history of AD. In addition, for each stage, NIA-AA criteria provide degrees of likelihood supporting the clinicopathological correlation based on progress in semiology, genetics and biomarkers accumulated since 1984. Table 2.2 summarizes NIA-AA clinical criteria for AD stages.

Diagnosis of probable AD dementia, possible AD dementia, dementia unlikely due to AD and MCI due to AD are intended for use in all clinical settings. By contrast, the diagnosis of pathophysiologically proved AD dementia, probable AD with increased level of certainty documented by cognitive decline or gene mutations requires clinical settings with appropriate infrastructure (neurosurgery, neuropsychology, genetic counselling and molecular diagnosis). Probable AD with evidence of pathophysiological processes, possible AD with evidence of pathophysiological processes, MCI due to AD (high/intermediate likelihood), MCI unlikely due to AD and preclinical AD are diagnoses restricted to research environments due to the need for biomarker corroboration.

The diagnostic criteria for dementia continue to refer to an abnormal decline of a premorbid cognitive performance, involving at least two functional domains, which imposes limitations to the normal activities of an individual. Thus, clinical history obtained from the patient and informant are crucial in the assessment of the cognitive syndrome

Box 2.1. NIA-AA dementia criteria.

1. Presence of two or more of the following symptoms: � Learning and memory: repetitive questions or conversations, misplacing personal belongings,

forgetting events or appointments, getting lost on a familiar route. � Reasoning: poor understanding of safety risks, inability to manage finances, poor decision-

making ability, inability to plan complex or sequential activities. � Visuospatial abilities: inability to recognize faces or common objects or to find objects in direct

view despite good acuity, inability to operate simple implements, or orient clothing to the body. � Language: difficulty for thinking of common words while speaking; hesitations; speech, spelling,

and writing errors. � Personality, behavior and comportment: uncharacteristic mood fluctuations such as agitation,

impaired motivation, initiative, apathy, loss of drive, social withdrawal, decreased interest in previous activities, loss of empathy, compulsive or obsessive behaviors, and socially unacceptable behaviors.

2. Corroborated by clinical history (patient + informant) and mental status examination or neuropsychology testing3. Decline from a normal premorbid functional level4. Not secondary to delirium or major psychiatric disorder5. Significant functional impact on daily activities (work or at usual activities)



particularly and its functional impact on the daily activities of an individual (Box 2.1).

The criteria for the dementia stage of AD (Box 2.2) are derived from the operational definition of dementia summarized in Box 2.1. Patients meeting 1984 NINCDS–ADRDA criteria for probable AD still meet the same diagnosis according to the NIA-AA classification; however, the reverse is not necessarily true due the incorporation of nonamnestic AD presentations. Note that, in contrast with the NINCDS-ADRDA classification, the NIA-AA criteria recognize language, visuospatial and executive presentations as AD syndromes although their frequency is relatively low compared with amnestic presentation of AD. The core clinical diagnostic criteria for probable AD dementia are summarized in Box 2.2.

The NIA-AA criteria includes under the category possible AD cases with an atypical course or mixed clinical presentation. Specifically, atypical course refers to either sudden onset of cognitive impairment or absence of progressive cognitive decline. Possible AD dementia includes all cases meeting criteria for AD dementia but with concomitant comorbidities such as cerebrovascular disease, or any other medical (neurological, psychiatric, clinical or drug-related) condition that could have a substantial effect on cognition. Possible AD dementia also includes all cases meeting

Box 2.2. NIA-AA probable Alzheimer’s disease dementia core clinical criteria.

A. Insidious onset (months to years) B. Evidence of progressive clinical declineC. Syndromes:

� Amnestic presentation: most common syndromic presentation of AD dementia. Impairment in learning and recall of recently learned information predominates over other deficits. There should also be evidence of an additional cognitive dysfunction.

� Nonamnestic presentations: language presentation: characterized by deficits in word finding. Visuospatial presentation: characterized by deficits in spatial cognition, including object agnosia, impaired face recognition, simultanagnosia and alexia. Executive dysfunction: characterized by deficits in reasoning, judgment, and problem solving.

D. Absence of the following: � Substantial cerebrovascular disease: history of a stroke temporally related to the onset or

worsening of cognitive impairment; or the presence of multiple or extensive infarcts or severe white matter hyperintensity burden.

� Core features of other dementia syndromes: Lewy bodies, prominent features of behavioral variant frontotemporal dementia, prominent features of semantic variant primary progressive aphasia or non-fluent/agrammatic variant primary progressive aphasia.

� Absence of other causes of cognitive decline: any other comorbidity or use of medication that could have a substantial effect on cognition.



criteria for AD dementia but presenting with clinical features of Lewy body dementia. Thus, the diagnosis of possible AD according to 1984 NINCDS-ADRDA criteria does not necessarily translate into the same diagnosis based on the 2011 classification.

Diagnostic criteria for MCI due to AD core clinical criteria include objective cognitive deficits in a clinical context of functional independency and no dementia. The evaluation of MCI individuals should include clinical, neurological and psychiatric comorbidities capable of altering cognition. Therefore, history taking and clinical assessments to rule out other neurological conditions (i.e., cerebrovascular disease) are fundamental for the proper diagnosis of MCI.

The diagnostic criteria for MCI due to AD state that a knowledgeable informant should corroborate cognitive deficits reported by the patient (Box 2.3). Regarding clinical assessment of memory problems, although careful clinical assessment of cognitive deficits is valid, cognitive evaluation performed by a neuropsychologist is definitively superior. Typically, neuropsychology assessments in the range of 1–1.5 standard deviations below the mean adjusted for age and educational background is considered abnormal. It is highly desirable that longitudinal cognitive assessments be performed in order to capture cognitive decline in MCI. Declines can occur in a variety of cognitive domains, including memory, executive function, attention, language, and visuospatial skills. Episodic memory impairment is observed most commonly in MCI patients who subsequently progress to AD dementia.

Functional status should be properly addressed during the clinical assessment. MCI criteria emphasises functional independency despite mild problems performing complex tasks. The notion of progression in functional decline is a key element from the clinical history. Moreover, it is highly recommended to investigate MCI patients with structural imaging for assessment of mesial temporal atrophy, ventricle dilation and particularly to rule out other neurological causes of cognitive impairment

(Figure 2.4).

The incorporation of likelihood levels requiring the use of biomarkers certainly refines the MCI nosology by adding knowledge regarding the

Box 2.3. NIA-AA core clinical criteria for the MCI clinical and cognitive syndrome.

1. Concern regarding a change in cognition2. Impairment in one or more cognitive domains3. Preservation of independence in functional abilities4. Not demented



presence of disease physiopathology. Core clinical criteria for MCI due to AD with high likelihood indicate presence of a MCI clinical syndrome corroborated by at least a biomarker for amyloid deposition and a biomarker for neurodegeneration. Thus, the diagnosis of MCI due to AD with high likelihood conveys the highest level of certainty regarding the presence of AD physiopathology as well as eventual progression to AD dementia. The criteria for MCI due to AD with intermediate likelihood denote the presence of MCI clinical syndrome corroborated by only one biomarker (usually a structural MRI). These diagnostic criteria preclude the use of both biomarkers of neurodegeneration. MCI due to AD with uninformative biomarker is applicable to those cases where biomarkers of amyloid accumulation and neurodegeneration were required but the results are conflicting or borderline. The diagnosis of MCI unlikely due to AD is based on negative outcomes from biomarkers for amyloid deposition and neurodegeneration and conveys the lowest likelihood of the underlying pathophysiology being due to AD.

The identification of a preclinical stage of AD is perhaps one of the most significant advances in the NIA-AA classification. It embodies a theoretical framework that predicts a presymptomatic phase of AD characterized by the presence of AD-P in the brain of asymptomatic individuals. Therefore, biomarkers play a fundamental role in the definition of preclinical AD. These diagnostic criteria are restricted for research settings.

The presymptomatic AD stage one (asymptomatic cerebral amyloidosis stage) is characterized bybiomarker evidence of amyloid accumulation supported either by PET or CSF assay, but no detectable alterations suggestive of neurodegeneration (CSF, [18F]FDG, MRI) or cognitive symptoms.

The presymptomatic stage two (asymptomatic cerebral amyloidosis plus neurodegeneration stage) is characterized by amyloid positivity and presence of one or more markers of ‘downstream’ AD-P-related neuronal injury such as elevated CSF Tau or p-Tau, PET [18F]FDG hypometabolism signature (posterior cingulate, precuneus and/or temporoparetal cortices) and/or cortical thinning/grey matter loss in a specific anatomic distribution.

The presymptomatic AD stage three (symptomatic cerebral amyloidosis plus neurodegeneration stage) is characterized by amyloid positivity, evidence of neurodegeneration as well as subtle cognitive decline. It is expected that individuals meeting these criteria are approaching the border zone with the NIA-AA clinical criteria for MCI.



Spectrum of clinical presentations associated with AD pathologyIt is important to emphasize the significant variability underlying the key clinical features of AD (e.g., age at onset, heritability, clinical evolution). Although not extensively explored, clinical variability has been frequently used as the basis for classifying groups of AD patients. For example, regarding the age at onset of dementia, AD has been categorized as very early (<35 years of age), early (<65 years of age), typical (>65 and <85 years of age) or late AD onset (>85 years of age) [138]. From the genetic perspective, aside from the presence of the vulnerability factor APOE4 allele (AD APOE4 positive/negative), AD has either sporadic or familial presentations, with heritability presenting in either an autosomal dominant or recessive form [139–142]. According to the initial symptoms, while amnestic presentation is considered the canonical cognitive presentation, deficits predominantly in non-memory domains such as language, visuospatial, executive or motor functions have been categorized as atypical AD clinical variants [10,143]. Regarding the temporal progression of clinical symptoms, AD can be categorized as slow (months) or rapidly progressing (drop of three MMSE points in 24 weeks) [144,145]. Finally, AD cases are categorized as based on the predominance of tangles or plaques as the main pathological feature [146,147]. In terms of the distribution of tangles, aside from the typical limbic-heteromodal presentation, AD-P can display hippocampal-sparing or limbic-predominant subtypes, which are associated with atypical clinical presentations [11].

Clinical subtypesClinical AD variants that emerged from clinicopathological studies have been recently corroborated by imaging biomarker studies that revealed a range of focal cortical syndromes associated with AD-P [6,10]. These clinical variants probably represent distinct patters of focal cortical neurodegeneration and propagation observed during symptomatic stages. While amnestic cases suggest mesiotemporal vulnerability, visuospatial, language, executive or behavior variants are associated with neurodegeneration predominantly in the temporo–parital–occipito, left perisylvian, dorsolateral and ventromesial prefrontal cortex, respectively.

Amnestic variantAmnestic variant of AD (AVAD) is by far the most frequent presentation. Dementia (Table 2.1) typically starts after 65 years of age with the majority of cases considered sporadic despite frequent positive family history. The frequency of APOE4 carriers is higher compared to the general population. It has been proposed that, in amnestic forms, AD-P initiates in



the mesiotemporal structures and propagate to heterotypical cortices [148]. Typically, the clinical course is slow and the dementia phase is preceded by anamnestic or multiple domains MCI syndrome (Table 2.2) that insidiously progress over the course of months or years. Anterograde long-term episodic memory deficits in AVAD cases are attributable to neurodegeneration in those entorhinal neurons projecting to the hippocampus. Therefore, storage of memory traces in the brain is particularly affected. AVAD patients typically describe loss of memory for facts, specific events and contexts (episodic memory), while memory for vocabulary and concepts (semantic memory) only deteriorates later in the course of the disease. As such, episodic memory impairment with sparing of procedural memory or motor learning is the hallmark of typical AD.

Several neuropsychological batteries are sensitive to demonstrate the progression of episodic memory deficits in AD, particularly versions of the verbal learning test (VLT), that normalize encoding and retrieval [149,150]. Major depression is a behavioral symptom frequently observed in cases of typical AD. In early stages of typical AD, fluctuations of cognitive function, dramatic personality changes or severe language deficits are infrequent although various degrees of apraxia, language and working memory symptoms develop during the dementia phase. AVAD’s imaging signature consistently shows ‘diffuse’ amyloid deposits which predominate in the anterior and posterior cingulate, precuneus, prefrontal cortex and temporal lobe (Figure 2.1) [151–154]. Hypometabolism initially observed in the posterior cingulate, inferior parietal cortex and hippocampusby [18F]FDG spreads to the temporal and prefrontal neocortex during disease progression (Figure 2.3) [155]. Structural MRI shows hippocampal, entorhinal and perirhinal atrophy as well as ventricular enlargement

(Figure 2.4) [68]. CSF levels of A b1–42 are low already in MCI phases of AD indicating amyloidosis [68,156]. High t-Tau and p-Tau on the serine 181 (pTau181) indicate neurodegeneration and Tau hyperphosphorylation in these patients [59,157].

Visuospatial variant of ADThe visuospatial variant of AD (VVAD) represents nearly 5% of memory clinic patients. Dementia onset ranges from 50 to 70 years of age and the progression rate is variable [158,159]. Familial presentations are rare, and the frequency of APOE4 is comparable to sporadic AD [159]. VVAD patterns of neuropathology progression are not well understood; however, marked brain amyloid accumulation and neurodegeneration have been observed either on the primary visual cortex, dorsal, or ventral associative visual areas [160]. VVAD invariably meet clinical criteria for posterior cortical atrophy



(PCA), which also can be caused by other neurodegenerative diseases [161–163]. The clinical course of VVAD tends to be slow with dementia preceded by a MCI stage characterized by visual–spatial symptoms that in general encompass either a primary visual, occipitotemporal or biparietal subvariant [6]. Few cases have been described with primary visual variant [10,164]. The occipitotemporal variant features alexia, apperceptive agnosia and/or prosopagnosia. The biparietal variant is characterized by apraxia, visuospatial deficits or agraphia. During the MCI phase, these patients report frequent visits to optometrists or ophthalmologists for reading or driving difficulties and frequent car accidents secondary to various degrees of visual impairment. Less commonly, these patients have visual hallucinations. These initial symptoms often progress to ideomotor, constructional and/or dressing apraxia, Balint’s syndrome (ocular apraxia, optic ataxia, simultanagnosia), and/or Gerstmann’s syndrome (acalculia, agraphia, finger agnosia, left-right disorientation). Memory dysfunction is significant in advanced cases. PET [18F]FDG (Figure 2.6) reveals predominant hypometabolic changes and atrophy of the posterior cortex. CSF profile is indistinguishable from AD [165,166]. It is debatable whether VVAD has a specific signature revealed by amyloid imaging [165,166].

Language variant of ADThe language variant of AD (LVAD) represents nearly 5% of memory clinic patients. Dementia starts typically in patients younger than 65 years of age and the majority of cases are considered sporadic. The frequency of APOE4 carriers is comparable to the general populations [167]. In LVADs, neurodegeneration occurs predominantly in language-related circuits on the vicinity of the perysylvian cortex or frontal operculum; however, the neuropathology does not necessarily predominate in the left hemisphere [168–170]. In LVAD patients frequently meet criteria for logopenic primary progressive aphasia (L-PPA), less frequently for nonfluent PPA (NF-PPA), and rarely for semantic dementia [168,169,171,172]. Usually, LVAD patients without apraxia of speech and agramatism have early memory impairment. In these individuals, logopenia is characterized by word-finding hesitations and phonemic paraphasias, which progresses to comprehension deficits and difficulties to repeat unusual sentences. Naming is impaired but improves on phonemic cueing. Repetition may be impaired. Fluent output can alternate with dysfluent speech and spelling can be impaired. Motor speech, grammar, and single word comprehension is relatively spared in these patients, particularly in early phases of the disease. NF-PPA shows nonfluent speech, agrammatism, AOS, hesitancy and effortfulness attributable to impaired planning of articulation. Imaging studies with [18F]



FDG PET indicate hypometabolic areas, predominantly in the left hemisphere [173]. [11C]PIB uptake is diffuse and indistinguishable from the pattern in matched AD patients [173]. CSF biomarkers are similar to the AVAD [174].

Other less frequent AD variantsSeveral studies and case reports have demonstrated AD neuropathological signatures in brain specimens of individuals with a clinical diagnosis of cortical basal syndrome (CBS), frontolobar behavioral syndrome or severe dysexecutive syndromes [6,161]. The frequency of APOE4 genotype in these syndromes is unknown. CBS due to AD pathology has been described as asymmetric apraxia, extrapyramidal syndrome followed by memory impairment in more advanced cases of the disease [175]. The absence of visuoperceptual symptoms helps to differentiate CBS from VVAD (biparietal syndrome) patients.

Figure 2.6. 59-year-old female with progressive visuocontructional deficits, initially characterized by reading difficulties.

Patient progressed to ideomotor apraxia, finger agnosia and alexia without agraphia. Memory is mildly affected. Note mild biparietal atrophy and significant posterior hypometabolism (right >> left).



Behavioral variant of AD is another rare and possibly underdiagnosed presentation of AD corresponding to 7–17% of autopsy cases of the behavioral variant of frontotemporal degeneration [176]. In fact, 20–30% of patients with behavioral frontotemporal syndrome have amyloid accumulation detected by [11C]PIB [15,41,42,177]. The majority of cases are considered sporadical though a PS2 and several PS1 mutations have frontotemporal syndrome as major phenotype [178,179]. In these patients clinical onset ranges from 45 to 65 years of age and usually starts as a depressive state or irritability and progresses to a clinical picture undistinguishable from the behavioral variant of frontotemporal degeneration [180]. Memory dysfunction constitutes a late symptom. The clinical evolution is variable and some patients rapidly deteriorate [6,180,181]. Further studies are necessary to clarify clinical and genetic phenotypes.

Biomarkers in the differential diagnosis of AD dementiaThere is no clear consensus regarding the use of biomarkers in clinical practice, except that it is still too early to use biomarkers for screening asymptomatic individuals. For MCI, the value of biomarkers remains debatable since it is not yet known the accuracy with which biomarkers predict progression to dementia, and since no disease-modifying treatments are currently available. By contrast, it has been proposed that patients would better plan their lives knowing the risk of developing dementia. However, there is a growing consensus that biomarkers definitively aid in the differential diagnostic of dementia. Figure 2.7 exemplifies three general clinical scenarios emerging from syndromic characterization of patients in which biomarkers provide clinically relevant information.

The first scenario depicts individuals older than 65 years who exhibit a slow progressive cognitive decline characterized by episodic memory deficits. Clinical examination shows no focal neurological signs and the mental status examination shows a predominance of memory deficits not recovered with cueing as the main clinical feature. Here, T1-weighed MRI serves for conducting clinical assessment of mesial temporal entorhinal cortex and hippocampal atrophy and ventricle enlargement [103,182]. Moreover, MRI fluid attenuation inversion recovery (FLAIR, a routine in many centers) assesses vascular pathology and presence of structural lesions other than atrophy. Cognitive assessment would certainty refines the clinical finding, however rarely adds to the clinical diagnosis. Genetic screening is recommended for individuals with a pedigree suggestive of autosomal dominant inheritance and at least two affected individuals in two generations. Addition of [11C]PIB [18F]FDG might add diagnostic accuracy needed in specific disease modifying clinical trials, but rarely will add to the final clinical/MRI assessment.



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The second scenario encompasses atypical presentations including all individuals younger than 65 years of age with progressive cognitive decline or individuals with focal cortical syndromes at any age. Genetic screening is recommended for individuals with a pedigree suggestive of autosomal dominant inheritance and at least two affected individuals in two generations. Neuropsychological assessment is important particularly in cases marked by an early presentation of cognitive deficits. Assessment with T1-weighed MRI, FLAIR and diffusion-weighed imaging (DWI) provides information regarding structural changes or the presence of vascular pathology. [18F]FDG PET significantly contributes to the investigation of these patients, particularly in early presentations of dementia, when structural changes are still modest. As previously described, [18F]FDG PET reveals specific signatures for frontotemporal degeneration, Lewy body dementia, all progressive aphasias, posterior cortical atrophy or AD [15,16,90,183]. [18F]FDG PET may be helpful in cases of atypical depression. Regarding biomarkers for amyloid accumulation, several studies using amyloid imaging agents or CSF biomarkers provide additional insights regarding pathological processes underlying atypical presentations that could translate into personalized care for dementia patients [42,171,177,184,185]. For example, patients with cortical basal of frontotemporal syndrome could benefit from cholinesterase inhibitors if carriers of AD pathology. Dopamine presynaptic imaging agents (i.e., DAT scans) might be useful in the diagnose workup in the differential diagnosis between atypical Lewy body dementia and AD [92,129,128].

The third scenario encompasses individuals with rapidly progressive dementia. It is important to emphasize that 9–20% of these patients have AD [145,186] although the vast majority of these patients have prion diseases, immunological causes of dementia, frontotemporal degeneration or tauopathies [181]. Some series suggests that 10% of AD patients meet criteria for rapidly progressive AD [187]. Therefore, in addition to complete screening for prion, paraneoplastic, systemic/immumologiocal autoantibodies, complete CSF and electroencephalogram, T1-weighted MRI, FLAIR, DWI are also mandatory for the investigation of these cases. In addition, one should consider [18F]FDG PET, which might reveal the AD signature when conducted early on in the course of the disease although in late phases, AD and Creutzfeldt–Jakob disease glucose uptake can be indistinguishable [188–191]. [11C]PIB scans should be considered to support the diagnosis of rapidly progressive AD. In fact, although few cases have been investigated, [11C]PIB is negative in Creutzfeldt–Jakob disease [192]. Again, genetic screening is recommended for individuals with a pedigree suggestive of autosomal dominant inheritance and at least two affected individuals in two generations.



Acknowledgements

The Alzheimer’s Association, new investigator award (NIRG-08–92090) ; Nussia and André Aisenstadt foundation, Douglas Research Institute; Canada Foundation for Innovation and the Canada Research Chairs programme. Canadian Institute of Helath Research CIHR (MOP-115131) FRSQ, Funds de Recherché en Santé du Quebec (Chercheur Boursier Salary Award).

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organi-zation or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, con-sultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

Summary.

� Alzheimer’s disease now encompasses a spectrum of clinical syndromes associated with a commom neuropathological substrate.

� New diagnostic criteria incorporates recent scientific advances in the neurobiology of disease � It is expected that advances on clinical definitions will allow early therapeutic interventions

capable to modify the natural history of Alzheimer’s disease.

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