Alzheimer’s Disease: Current Clinical and Neuropathologic Diagnostic Criteria

Abstract

Alzheimer’s disease is the most common cause of dementia, accounting for 50-60% of cases at clinical and autopsy series. Recent advances have enabled detailed understanding of the molecular pathogenesis of this devastating disease, and the updated consensus criteria for its clinical and neuropathological diagnosis have increased the diagnostic accuracy and sensitivity versus other dementias considerably. However, due to frequent overlap between dementing disorders and multiple confounding pathologies in the aged brain, both clinical and postmortem studies entail biases that affect both their general applicability and validity. This brief critical review discusses the diagnostic validity and limitations of currently used clinical and morphological criteria for the diagnosis of Alzheimer’s disease and gives recommendations for future clinico-pathologic research.

Keywords: Alzheimer’s disease; Diagnostic criteria; Neuropathology; Clinico-pathologic subtypes; Mixed pathologies

Abbreviations

AA: Alzheimer’s Association; AD: Alzheimer’s disease; ADRDA: Alzheimer’s disease and Related Disorders Association; Aβ: β-amyloid; CCCD: Canadian Consensus Conference on the Diagnosis and Treatment of Dementia; CERAD: Consortium to Establish a Registry for Alzheimer’Disease; CSF: Cerebrospinal Fluid; CVD: Cerebrovascular Disease; DLB: Dementia with Lewy Bodies; EFNS: European Federation of Neurological Societies; ENS: European Neurological Societies; IWG: International Working Group; MCI: Mild Cognitive Impairment; MRI: Magnetic Resonance Imaging; NACCR National Alzheimer’s Coordination Center Registry; NCD: Neurocognitive Disorder; NFT: Neurofibrillary Tangles; NIA: National Institute on Aging; NIA-RI: National Institute on Aging and Reagan Institute; NICDS: National Institute of Neurological Disorders and Stroke; PET: Positron Emission Tomography; TDP- 43: TAR DNA Binding Protein 43.

Introduction

Alzheimer’s disease (AD) is a form of Neurocognitive Disorders (NCD) characterized by a progressive multidomain cognitive impairment with profound decrease in the abilities to perform daily living activity [1]. AD affects more than 35 million people worldwide – 5.5 million in the USA. AD is the most common form of dementia, accounting for 50-60% of cases in clinical and autopsy series, however, it is frequently associated with other confounding pathologies in the elderly. The principal risk factor for AD is age; its incidence doubles every 5 year after age 65, and the odds for a diagnosis of AD after age 85 exceed one in three. With the disproportional growth of the elderly population, the prevalence of AD will approach around 100 million worldwide and 11 to 16 million cases in the USA in 2050 [2,3]. Thus, AD has become a major public health and socio-economic problem [4] that threatens to become the scourge of the 21st century.

Clinical diagnostic criteria

Early diagnosis of AD and its distinction from other dementing disorders is crucial to implement effective treatment strategies and management of AD patients. Diagnostic procedures play a major role in the detection process but evidence on their respective accuracy is still limited. Updated consensus criteria for the clinical diagnosis of AD include: revised NICDS-ADRDA guidelines recommended by the NIA-AA [5,6], EFNS- ENS guidelines for the diagnosis and management of disorders associated with dementia [7], consensus from the Canadian CCCD [8], and the IWG–2 criteria for AD [9]. All these updated diagnostic criteria for AD considering clinical phenotypes (typical and atypical forms, preclinical states and mixed AD), pathophysiological CSF biomarkers and neuroimaging procedures (volumetric MRI and fluorodeoxyglucose PET) are suggested to increase the clinical diagnostic accuracy of AD.

Combination of the best CSF and MRI data using standardized operating measures allowed a more precise diagnostic prediction [10,11], and will be further increased by using multimodal techniques and novel CSF biomarkers already in biomarker-positive early (preclinical) stages [12-16]. The validity of plasma biomarkers for the (preclinical) diagnosis of AD has been reviewed recently [16- 20]. A large proportion of cognitively healthy people who develop Aβ pathology have signs of neurodegeneration prior to amyloid positivity [12], but there are conflicting results with biomarker changes and disease progression [21-25]. Although identification of fibrillar Aβ by [11C]PiB-PET is feasable for both research and clinical settings, recent evidence comparing it with postmortem or biopsy results raised doubts about this method as representative of Aβ loads in the living human brain [26,27], since a 55% prevalence of PIBpositivity was observed in non-demented subjects over age 80 [28]. However, in some PIB-negative cases, a combination of pre-existent non-AD pathology or tau-mediated degeneration may occur prior to Aβ pathology [12]. Meanwhile, the advances in tau imaging ligands [29-31] will enable the identification of AD and non-AD tauopathypatients in clinical and research settings.

A review of two sets of autopsy cases from the NACCR database revealed a high diagnostic accuracy for AD (sensitivity from 70.9 to 87.3%,and 85%, respectively and a specificity of 44.3 to 70.8, and 51.1%, respectively), when the clinical diagnosis was confirmed by minimum levels of AD pathology [32]. A recent meta-analysis of 20 (among 1,189) records on the accuracy in distinguishing AD from other dementia types and healthy controls using autopsy as standard for truth calculated a sensitivity of 85.4% (95% CI 80.9-90.0%) and a specificity at 77.7% (95% CI 70.2-85.1%), both values being slightly better for imaging procedures than for CSF markers. This study also highlights the limited evidence on autopsy-confirmation and the heterogeneity of study design [33].

Neuropathologic diagnostic criteria

Histopathologic examination of the brain establishes that ADrelated lesions are present in sufficient densities and extension to distinguish AD from age-related and other degenerative disorders [34]. The current algorithms for the neuropathologic diagnosis of AD are based on semiquantiative assessment of senile plaques and NFTs, providing reasonable interrater agreement when using standardized criteria [35]. Guidelines for the neuropathologic diagnosis of AD include (a) cut-off quantitative values for senile plaques and tangles [36-38], (b) their semiquantiative assessement and age-adjustment in the CERAD protocol [39], (c) topographic staging of neuritic/tau pathology [40], re-evaluated recently by using immunohistochemistry [35,41], and (d) the progress and distribution of Aβ deposition which is different from tau pathology [42]. The causes of Aβ accumulation in sporadic AD remain unclear and its relation ot tau pathology, microglia and neuronal/synaptic activity are under discussion [43]. Using semiquantitative assessment of NFTs and neuritic plaques, good agreement can be reached in diagnosis only when the lesions are substantial, having involved isocortical structures (Braak neuritic stage V and VI), with 91% absolute agreement, while for mild lesions it was poorer (Braak stage I and II, agreement 50%), thereby limiting the possibility to make accurate correlation of cognitive status and morphologic findings [35,44].

The combination of the CERAD and Braak scores in the NIA-RI criteria relates dementia to AD-typical lesions with high, intermediate and low likelihood, which, however, applies only to demented persons [45]. Evaluation of the NIA-RI criteria confirmed their easy use in AD and non-demented individuals, high Braak and CERAD stages identifying 54% and 97% of AD cases, respectively, and eliminating between 62 and 100% of non-demented ones with low Braak and CERAD stages, whereas among non-AD dementias only between 8 and 42% were identified [44]. Although the sensitivity and specificity of the NIA-RI criteria has been suggested to be around 90%, only 30 to 57% of the brains of patients with the clinical diagnosis of probable AD showed “pure” AD pathology [46], thus reducing their predictive value to 38–44% [47]. A retrospective clinico-pathologic study of 1700 elderly demented patients from two large chronic hospital in Vienna, Austria, (MMSE score < 20; mean age at death 84.3±6.0 SD years) revealed AD-related pathology in 83.2%, but “pure” AD (ABC levels 3/3/3) without other essential pathologies in only 41.0%, AD with concomitant pathologies in 44.8%, vascular encephalopathy and other disorders in 10.7% and 5.5%, respectively, while 0.9% showed no pathologic changes [44]. Although cognitively intact elderly subjects often show variable pathologies [48-50], in general, the density of isocortical NFTs correlates best with the severity of cognitive impairment, and the predictive value of widespread tau pathology (Braak neuritic stages V and VI) for dementia is high [51].Other studies suggested that both diffuse and neuritic plaques, rather than tangles in neocortical regions distinguish non-demented and AD subjects with high sensitivity and specificity [52], while reduction of neuronal numbers in hippocampus and cerebral cortex relates to dementia, but not to plaques and tangles [53]. The cortical Aβ burden usually does not correlate with disease duration and the stage of tau pathology [54]. Correlations between AD pathology and cognitive status have been reviewed critically [51].

The recent NIA-AA guidelines for the neuropathologic assessment of AD consider levels of AD pathology regardless of the clinical history of a given individual [36,38]. They include: 1. the recognition that AD pathology may occur in the apparent absence of cognitive impairment, 2. an “ABC” score of AD pathology that incorporates histologic assessements of Aβ plaques (A), based on its phase assessement [42], staging of NFTs (B) based on the Braak staging system [40,41], and scoring of neuritic plaques, based on semiquantitative assessment in at least five neocortical regions (C), based on CERAD criteria [39]. Table 1 illustrates how each of the A (amyloid), B (Braak), and C (CERAD) scores are transformed to state the level of AD neuropathologic change on a four tiered scale (Non, low, intermediate and high). 3. More detailed approaches for assessing co-morbid conditions, such as Lewy body disease, vascular brain injury, and TDP-43 immunoreactive lesions are considered [36]. Preliminary testing of the revised NIA-AA neuropathology guidelines in 390 autopsy cases including 199 non-demented subjects distinguished pure AD and non-AD dementia from non-demented cases with a sensitivity of 71% and a specificity of 99%. The sensitivity increased after exclusion on non-AD dementia cases, indicating that cognitive status and morphologic assessment according to the NIAAA guidelines appear excellent for distinguishing pure AD from non- AD dementia, preclinial AD and non-demented controls [55].

  

    
 
    
 
    
Level of AD    neuropathologic change
    
 
    
 
  
  

    
Thal phase for Aβ plaques
    
A
    
 
    
B
    
 
    
C
    
CERAD
  
  

    
 
    
0 or 1
    
2
    
3
    
 
  
  

    
0
    
0
    
Not
    
Not
    
Not
    
0
    
neg
  
  

    
1 or 2
    
1
    
Low
    
Low
    
Low
    
0 or 1
    
neg or A
  
  

    
1 or 2
    
1
    
Low
    
Intermediate
    
Intermediate
    
2 or 3
    
B or C
  
  

    
3
    
2
    
Low
    
Intermediate
    
Intermediate
    
any C
    
neg or A to C
  
  

    
4 or 5
    
3
    
Low
    
Intermediate
    
Intermediate
    
0 or 1
    
neg or A
  
  

    
4 or 5
    
3
    
Low
    
Intermediate
    
High
    
2 or 3
    
B or C
  
  

    
 
    
 
    
Braak 0-II
    
Braak III-IV
    
Braak V-VI
    
 
    
 
  
  

    
The level of AD neuropathologic    change is determined by assessing A, B and C scores. A scores are related to    phases of Aβ deposition (first column), B scores to neurofibrillary Braak    stages (bottom row) and C scores to CERAD stages (last column). Modified from    [36]. 
  

Table 1: ABC criteria for the diagnosis of Alzheimer’disease related pathology.