While the MCI classification is useful for identifying individuals who carry a heightened risk of converting to AD, the diagnostic criteria will ideally move into the asymptomatic stage of the disease. The pathological processes of AD are now believed to begin up to 20 years before the onset of cognitive impairment (65, 66). This prolonged prodromal stage of the disease provides a critical opportunity for therapeutic intervention, prior to the irreversible destruction of neuronal tissue (62, 67). Thus, the identification and validation of biomarkers of AD is increasingly important, for improving the predictions of those who are at risk of converting from normal cognition to MCI, and finally AD. Humpel et al. outlined a list of criteria which biomarkers of AD should ideally fulfil (64):
1. Reflect physiological aging processes
2. Reflect basic pathophysiological processes of the brain 3. React upon pharmacological intervention
4. Display high sensitivity
5. Display high specificity for the disease as compared with related disorders 6. Allow measurements repeatedly over time
7. Allow reproducibility in laboratories worldwide
8. Should be measurable in non-invasive, easy-to-perform tests 9. Should not cause harm to the individuals being assessed 10. Tests should be inexpensive and rapid
11. Samples should be stable to allow easy and cheap transport 12. Easy collection of fluids not only in hospitals
13. Changes should be at least twofold to allow differentiation of controls 14. Define good cut-off values to distinguish diseases
15. Data published in peer-reviewed journals
16. Data reproduced by at least two independent researchers
While researchers have yet to identify an AD biomarker which satisfies all of the above criteria, several biomarkers have shown sensitivity to early neuropathological changes in AD, and may be useful for the early diagnosis of the disease and evaluating the efficacy of candidate drugs (63).
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1.4.1 Cerebrospinal fluid
It is now known that molecular changes in the brain can be detected in the cerebrospinal fluid (CSF) (68). Candidate CSF biomarkers include: total tau (T-tau) as a marker of neuronal degradation, amyloid-β1-42 (Aβ-42), as a marker of amyloid-β metabolism and plaque formation; and phosphorylated tau (P-tau) as a marker for tau phosphorylation and the formation of NFTs (69).
A number of studies have reported a marked increase in CSF T-tau and P-tau, alongside decreases in Aβ-42 (69, 70). This pattern of changes is unique to AD, and therefore may find relevance in the differential diagnosis of AD over other forms of dementia (71). The performance of these biomarkers is high, with reported sensitivity and specificity of CSF biomarkers to discriminate between AD patients from healthy controls of 80 – 90% (69, 70). CSF biomarkers are believed by some to be the most sensitive biomarkers of AD neuropathology (68).
In order to extract CSF for biomarker analysis, a lumbar puncture (LP) must be performed (69). In the clinical scenario, a LP is often avoided due to the post-LP headache, thought to arise due to loss of CSF volume and the leaking of fluid into nearby tissue (72). An alternative, non-invasive method for quantifying amyloid-β and tau deposition in the brain is therefore highly desirable.
1.4.2 Positron emission tomography
One such method is positron emission tomography (PET). PET is a nuclear imaging technique which permits the quantification and distribution of a radiolabelled tracer to be assessed in vivo. These tracers can be engineered to bind to amyloid plaques and NFTs, which may allow the detection of these causative agents in the brain prior to the onset of cognitive decline (73, 74).
The most widely used PET compound for amyloid imaging is the 11C-labelled tracer Pittsburgh compound B (11C-PiB) (75). 11C-PiB is a radioactive analogue of thioflavin T; a histological stain which is traditionally used to identify amyloid oligomers – a precursor to amyloid plaques (76). It has been demonstrated that the regional uptake of 11C-PiB closely mirrors the post-mortem distribution of amyloid-β, supporting its application as a method for in vivo detection of amyloid plaques (77). In addition, high
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levels of 11C-PiB uptake have been shown to be a strong predictor for conversion from MCI to AD (78, 79).
Figure 1.5 PET scan of an AD patient and healthy control, showing high retention of the tracer in the AD
brain. SUV represents the standard uptake value: red = high uptake, blue = low uptake. Reproduced from Nordberg et al. (80)
However, the very short half-life of 11C (20 minutes) introduces some practical limitations to working with 11C-PiB, as the radioisotope must be produced in close proximity to the PET scanner in order to label the compound and inject the patient in sufficient time (81). In order to overcome these difficulties, several other tracers have been developed for in vivo amyloid imaging, such as florbetaben, florbetapir and flutemetamol (81). These agents are all labelled with the radioisotope 18F, which has a half-life of 110 minutes. Preliminary work using these compounds suggests high sensitivity and specificity to amyloid-β (81).
A number of tau radiotracers are currently being developed for in vivo tau quantification; these include the compounds 18F-808 (82) and 18F-THK-5015 (83). As tau burden correlates with cognitive decline in AD (84), tracers which permit in vivo quantification of the distribution of tau pathology may potentially enable ante-mortem Braak staging
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of the disease (85). Both of the aforementioned tracers have enabled the differentiation of AD patients from healthy controls, with high uptake in regions vulnerable to NFT deposition (82, 83).
Another popular PET tracer for investigating neurodegeneration in AD patients is flurodeoxyglucose (18F-FDG). 18F-FDG is a glucose analogue, and can be used to measure brain metabolism. It is believed that cerebral glucose metabolism measured with 18F-FDG reflects synaptic activity (86); in AD, regional reductions in glucose metabolism have therefore been attributed to an impairment in synaptic activity that accompanies neurodegeneration (63). Hypometabolism detected using 18F-FDG has a distinct topographical pattern which is distinct from other dementias, enabling the differential diagnosis of AD over other forms of dementia (87, 88). It has been shown that 18F-FDG can identify MCI patients who will convert to AD, and may be useful in the early diagnosis of the disease (89, 90).
Figure 1.6 18F-FDG PET scan of (A) a healthy control subject, and (B) a patient with an MCI diagnosis.
Regional decreases in 18F-FDG uptake can be observed in the frontal parietal and temporal cortex of the MCI
patient. SUV represents the standard uptake value: red = high uptake, blue = low uptake. Reproduced from Mosconi et al. (91).
However, the short half-life of the PET radioisotopes (both 11C and 18F) has restricted the widespread and routine use of PET for early diagnosis of AD. In addition, the use of PET tracers in longitudinal studies is problematic, owing to the exposure risks
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associated with radioactive isotopes; the radiation dose is greatly increased when an anatomical computed tomography (CT) scan is acquired simultaneously, to enable improved localisation of tracer uptake in the brain (92).
1.4.3 Magnetic resonance imaging
Structural MRI is an alternative method for assessing AD-related neuropathological changes.
Structural MRI is able to accurately detect grey matter loss in characteristically vulnerable brain regions, such as the hippocampus and entorhinal cortex (93). These alterations have been shown to be indicative of progression from MCI to AD and other forms of dementia (94). The characteristic topographical pattern of atrophy in the AD brain can also be readily visualised using structural MRI, aiding differential diagnosis of the disease (93).
Figure 1.7 Structural MRI scans of (A) a healthy control subject, (B) a patient diagnosed with amnestic MCI,
and (C) and AD patient. Atrophy in the medial temporal lobes can be readily visualized in the aMCI and AD images. Reproduced from Vemuri et al. (95)
The structural changes which can be visualised using structural MRI have been shown to reflect neuronal loss, decreased synaptic density and cell shrinkage (96). As structural changes quantified using MRI correlate well with NFT deposition (97), they can be
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considered a measure of tau-related neurodegeneration (98). It therefore may find clinical relevance in the therapeutic assessment of tau-mediating therapies.
Recently, advanced image processing techniques have been developed to support the analysis of structural MRI datasets, enabling the detection to atrophy in an automated and unbiased fashion (93). These techniques have facilitated high throughput analysis of large cohort data sets, such as those generated within the Alzheimer’s Disease Neuroimaging Initiative (ADNI); a shared resource of AD research data which includes PET and MRI scans, alongside cognitive testing and genetics (99). Advanced image processing techniques have also enabled the detection of structural MRI changes up to 10 years prior to the development of AD, in the prodromal phase of the disease (100).
Other MRI techniques are increasingly being used to study AD-related changes. Diffusion tensor imaging (DTI), for example, is a technique that has shown sensitivity to microstructural changes in the white matter of the AD brain (101). More information about other MRI techniques which may offer sensitivity to neurodegenerative changes can be found in the proceeding chapters.