Biochemical and Radiological Markers of Alzheimer’s Disease Progression

Abstract

Alzheimer’s disease (AD) is a neurodegenerative, inevitably progressive disease with a rate of cognitive, functional, and behavioral decline that varies highly from patient to patient. Although several clinical predictors of AD progression have been identified, to our mind in clinical practice there is a lack of a reliable biomarker that enables one to stratify the risk of deterioration. Identification of biomarkers that allow the monitoring of AD progression could change the way physicians and caregivers make treatment decisions. This review summarizes the results of studies on potential biochemical and radiological markers related to AD progression.

Keywords

Alzheimer’s disease biomarkers cognitive decline deterioration progression

ALZHEIMER’S DISEASE PROGRESSION: MEASUREMENT AND ASSOCIATED FACTORS

Alzheimer’s disease (AD) is a neurodegenerative, inevitably progressive disease with a mean duration of 8 to 10 years after the onset of memory impairment [1]. The rate of cognitive decline in AD patients is highly variable from patient to patient and a clinician is not able to tell a patient how quickly (months, years) his or her disease will progress.

Several methods for evaluation and prediction of AD progression have been suggested [2]. Cognitive functioning is a key domain that is evaluated to monitor AD progression but full assessment of decline over time should also include functional, behavioral, and global outcomes. The cognitive functions are tested either with a comprehensive neuropsychological battery or with the abbreviated assessment instruments (e.g., Mini-Mental Status Examination, MMSE; Alzheimer’s Disease Assessment Scale cognitive subscale, ADAS cog). Global scales (e.g., Global Deterioration Scale, GDS; Clinical Dementia Rating, CDR) combine information about the patient’s performance across a wide range of cognitive and functional domains. Functional assessment scales (e.g., Instrumental Activities of Daily Livings, IADLs; Activities of Daily Livings, ADL) evaluate the patient’s ability to perform practical tasks, including everyday activities. Behavioral scales (e.g., the Neuropsychiatric Inventory, NPI; The Behavior Rating Scale for Dementia, BRSD) assess different behavioral manifestations of AD including agitation, anxiety, hallucinations, delusions, depression, and apathy.

MMSE is the most commonly used tool to assess AD progression. The annual MMSE decline in AD is 2 to 3 points [3]. Another efficacy measure frequently used to study the rate of progression in AD is ADAS cog. It is a global cognitive test that evaluates memory, praxis, and language. The disease progression in mild to moderate AD patients is estimated as 5.5 points per year [4]. The CDR, which is based on a semi-structured interview, examines the following areas: memory, orientation, judgment and problem solving, community affairs, home/hobbies, and personal care. Scores include a composite score (CDR-composite) and a sum of boxes (CDR-SB), which is a sum of ratings in each of six domains. The annual rate of change in CDR-SB scores was 1.43 (SE = 0.05) in patients with very mild AD (CDR 0.5) and 1.91 (SE = 0.07) in patients with mild AD (CDR 1) [5].

Approximately 10% to 30% of AD patients experience an aggressive course of disease. Various definitions for rapid AD progression have been proposed (for review, see [6, 7]). In most cases, the changes in MMSE scores were used as a tool to diagnose rapid AD.

A number of factors have been proposed as possibly partially accounting for the variability of AD progression. Table 1 lists factors associated with AD progression.

The identification of biomarkers that allow the monitoring of AD progression is important for several reasons. In the future, the ability to predict the disease’s progression could help physicians and caregivers in making more informed therapeutic decisions. If more invasive disease-modifying treatments for AD become available, the biomarkers could be helpful in selecting patients for more aggressive therapy. Moreover, identification of potential biomarkers may shed a light on the pathophysiological mechanisms responsible for the rate of AD progression.

This paper discusses the biochemical and radiological markers related to AD progression. We identified references for our review by searching PubMed from January 1970 up to September 2014 using combinations of the terms: “Alzheimer’s”, “deterioration”, “decline”, “progression”, “outcome”, “marker”. We restricted our search to articles published in English. We included only longitudinal studies. We excluded studies investigating conversion of mild cognitive impairment (MCI) to AD as well as studies including a non-homogenous cohort of participants (mixing AD, MCI, and cognitively intact persons) if they did not provide a sub-analysis of results limited to AD patients.

BIOMARKERS OF ALZHEIMER’S DISEASE PROGRESSION

Cerebrospinal (CSF) and blood biomarkers

Amyloid-β (Aβ) and tau

CSF biomarkers including Aβ₄₂, tau, and phosphorylated tau (ptau) at threonine 181 serve as diagnostic markers of AD and reflect the neuropathology of this disease [34, 35]. Low CSF levels of Aβ₄₂ reflect the levels of amyloid deposition in the brain. CSF tau is considered a general marker of neuronal degeneration, while ptau is a more specific disease marker related to neurofibrillary tangle formation. Deposition of amyloid plaques and tau tangle formation are early events in AD that precede clinically detectable cognitive decline by as much as 10 to 15 years [36]. The CSF level of Aβ₄₂ and tau rises before the appearance of clinical symptoms and reaches a plateau when clinical symptoms appear [36]. In the symptomatic phase, the levels of disease-specific biomarker remain stable across time [37].

In patients with very mild AD (CDR 0.5), the progression of dementia was significantly more rapid in those with lower baseline CSF Aβ₄₂ levels, higher tau or ptau, or a high tau/Aβ₄₂ ratio [38]. Patients in whom the CSF Aβ₄₂ level was greater than 411 pg/mL (the highest tertile) showed a mean yearly increase in CDR-SB score of 0.32 (95% CI: –0.11–0.74), whereas those in whom CSF Aβ₄₂ values reached 411 pg/mL or less had a mean yearly increase of 1.10 (95% CI: 0.74–1.47) on the CDR-SB scale. Alternatively, in individuals in the highest tertile of tau/Aβ₄₂ ratio values (>0.81), the mean yearly increase in the CDR-SB score was 1.49 (95% CI: 0.99–1.98), whereas individuals with a tau/Aβ₄₂ ratio of 0.81 or less recorded a mean yearly increase 0.43 (95% CI: 0.08–0.76) in the CDR-SB score. The ability of CSF Aβ₄₂, tau and ptau to predict a rate of dementia progression was also confirmed by other studies [39 –41].

In individual psychometric composite scores, CSF tau, ptau, tau/Aβ₄₂, and ptau/ Aβ₄₂ ratios predicted change in episodic and semantic memory scores, but not working memory or visuospatial scores [40].

In the study by Kester et al. a low ptau/tau ratio was the strongest predictor of faster cognitive decline compared to other disease-specific markers [39]. The lowest quintile of ptau/tau ratio levels was associated with an annual rate of decline of 2.9 points on MMSE, while the highest quintile had a mean annual decline of 1.3 points on MMSE. This finding seems to be counterintuitive considering that high ptau predominantly reflects a specific AD pathology, neurofibrillary tangle formation, while total tau as a marker of neuronal injury represents the cumulative outcome of different pathologies. The authors have tried to explain their finding by a supposition that tau phosphorylation may help neurons avoid apoptosis. In this scenario, tau phosphorylation plays a compensatory role to rescue the neuron from cell death. To our best knowledge, there is no strong evidence supporting this hypothesis. An alternative explanation proposed by the authors is that many AD patients in fact have concomitant cerebrovascular disease or Lewy bodies.

Wallin et al. showed that a subgroup of patients with low CSF levels of Aβ₄₂ (mean±SD: 362±66 ng/L) and very high levels of tau (mean±SD: 1501±292 ng/L) and ptau (mean±SD: 139±39 ng/L) exhibited worse clinical outcomes including faster progression of cognitive deficits and higher mortality [43].

In contrast to Aβ₄₂, CSF Aβ₄₀ levels did not predict AD progression [38, 40]. Recent studies demonstrated that CSF Aβ₄₂/₄₀ ratio showed significantly better diagnostic performance compared to CSF Aβ₄₂ alone [44 –46]. CSF Aβ₄₂/₄₀ ratio might have an added value for discriminating AD patients from non-AD patients in case of intermediate ptau [44, 45]. The prognostic value of CSF Aβ₄₂/₄₀ for AD progression needs to be evaluated.

A few studies have investigated whether plasma Aβ is associated with the rate of cognitive and functional decline in AD patients. These studies yielded contradictory results. In a longitudinal study that included 122 AD patients, Locasio et al. found that low plasma Aβ₄₀ and Aβ₄₂ were associated with a significantly more rapid cognitive decline on the Blessed Dementia Scale [47]. Low Aβ₄₂ levels were also associated with quicker functional deterioration on Weintraub Activities of Daily Living Scale. In the French 3-City Study, the risk of cognitive decline indexed using Isaacs Set Test for overall fluency, decreased with a higher level of plasma Aβ₄₂, Aβ_n - 42, and with higher level of the two ratios: Aβ₄₂/Aβ₄₀ and Aβ_n - 42/Aβ_n - 40 [48]. In this study no significant association was found between plasma Aβ markers and changes in MMSE and Benton Visual Retention Test. In another study, higher plasma Aβ₄₂ levels, but not Aβ₄₀ levels, were associated with fast cognitive decline defined as a decrease of ≥5/year on MMSE [49].

Inflammatory markers

The results of animal studies suggest that systemic inflammation contributes to the exacerbation of chronic neurodegenerative diseases and may accelerate disease progression [50]. Consistently with these experimental findings, in AD patients, high baseline serum levels of tumor necrosis factor alpha (TNFα), a proinflammatory cytokine, were associated with a 4-fold increase in the rate of cognitive decline measured on ADAS cog [51]. In the study by Holmes et al., serum levels of C-reactive protein (CRP) did not predict disease progression. In contrast to these observations, in one study low plasma levels of CRP were associated with a more rapid cognitive and functional decline in AD patients [47]. The authors of this study proposed that inverse correlation between CRP and the rate of AD progression may be confounded by medications (including statins or non-steroidal anti-inflammatory drugs) or outliers.

Leung et al. [52] correlated the rate of cognitive decline and plasma levels of 27 cytokines and related proteins measured by multiplex array system using Luminex technology. AD patients were divided into groups with slow, intermediate, and fast speed of decline, based on yearly cognitive decline in MMSE, ADAS cog, and CDR. An annual MMSE, ADAS cog, and CDR score decline of 4 or more points was considered as fast decline, an annual MMSE score decline of 2–4 points was considered as intermediate decline and a score below 2 points was considered as slow decline. The authors found a significant increase in the levels of interleukin(IL)-4, IL-10 and granulocyte-colony stimulating factor (G-CSF) in patients with fast cognitive decline as compared with the slow cognitive decline group. Patients with intermediate cognitive decline showed significantly higher levels of IL-2, IL-4, interferon-gamma (INFγ), and platelet-derived growth factor (PDGF) compared to those with slow cognitive decline.

Platelet-related markers

Platelets have the highest amyloid-β protein precursor (AβPP) levels of all peripheral tissues. Platelet AβPP isoforms are processed using mechanisms similar to those in neuronal cells. Platelets activation leads to the secretion of AβPP and Aβ, resulting in the higher levels of these proteins in serum [53]. AβPP metabolism, consisting of a reduced ratio of the upper (120–130 kDa) to the lower (106–100 kDa) immunoreactivity band, was found to be specifically altered in the platelets of AD patients [54]. In this group of patients, the reduction in AβPP ratios correlated with the 3-year decline rate on the MMSE score: patients with the largest cognitive drop had the largest AβPP ratio reduction [55]. In another study, a lower platelet AβPP ratio at baseline predicted more rapid cognitive decline in AD patients treated with acetylcholinesterase inhibitors [56].

Platelet bound glycoprotein (GP)IIb-IIIa and P-selectin are involved in the adhesion of platelets on the endothelium at the sites of vascular lesions and in the recruitment of leukocytes on vascular wall. Higher baseline expression of these platelet activation markers was observed in AD patients with fast cognitive decline during a 1-year follow-up period [57].

Other CSF markers

Visinin-like protein-1 (VILIP-1) is a highly expressed neuronal calcium-sensory protein and can serve as a marker of neuronal injury [58]. Among 60 patients with very mild or mild AD, those with CSF VILIP-1 ≥560 pg/mL (corresponding to the highest tertile) progressed more rapidly in CDR-SB (1.61 boxes/year) and global psychometric scores (–0.53 points/year) than those with lower CSF VILIP-1 values (0.85 boxes/year and –0.15 points/year, respectively) over a mean follow-up period of 2.6 years. Individuals in the highest tertile of VILIP-1 or VILIP-1/Aβ₄₂ ratio values declined more rapidly in episodic memory scores than patients in the lower two tertiles [40].

The double-strand RNA dependent protein kinase (PKR) is a ubiquitous cellular kinase controlling protein synthesis. PKR activation could lead to tau phosphorylation and reduced expression of β-secretase 1 (BACE1), one of the key enzymes involved in Aβ production [59]. Higher levels of CSF phosphorylated PKR in AD patients were associated with a more marked decline of MMSE results during a mean follow-up period of 25.7 months [60].

Ascorbic acid is a potent antioxidant that is not synthesized in the brain. Neither CSF nor plasma ascorbic acid predicted the rate of cognitive decline in AD patients; however, the CSF/plasma ratio of ascorbic acid level was associated with cognitive decline measured over a 1 year period after controlling for age, gender, education, APOE4 status, and baseline cognitive test results [61]. Each unit increase in CSF/plasma ascorbic acid level ratio was associated with a 1.1 unit smaller point loss on MMSE and a 2.7 unit smaller loss on ADAS cog.

Other blood markers

The brain-derived neurotrophic factor (BDNF) plays an important role in the processes of memory and learning by modulating neuronal survival, synaptic transmission, and plasticity [62]. BDNF can protect against Aβ toxicity and prevent tau hyperphosphorylation by inactivation of glycogen synthase kinase-3 beta (GSK-3β) [63, 64]. AD patients with fast cognitive decline showed lower baseline serum BDFN levels than those with slow cognitive decline during 1-year follow-up period [65].

Raised homocysteine levels within the normal range predicted faster cognitive decline in AD patients [66]. This effect was only significant in patients who had not suffered a stroke and were below the age of 75. Two other reports did not find a clinically significant association between homocysteine levels and cognitive and functional decline in AD patients [47, 67].

In several studies, proteomics methods were used to identify plasma biomarkers related to AD progression. The candidate markers found in these studies include clusterin, transthyretin, and gelsolin.

Clusterin (apolipoprotein J) belongs to a family of extracellular chaperones that regulate amyloidal formation and clearance [68]. Experimental studies demonstrated that clusterin binds to Aβ enhances its clearance and efflux through the blood-brain barrier [69]. Higher plasma clusterin levels were associated with more rapid cognitive decline on the MMSE score over the period of 1 year [70].

Transthyretin is a carrier for thyroxine and retinol. It was suggested that this protein protects against Aβ deposition in the brain [71]. Transthyretin levels were significantly lower in AD patients with more rapid cognitive decline and predicted the rate of cognitive deterioration better than the patient’s baseline MMSE score [72].

Plasma gelsolin is an actin-scavenging protein that clears the circulation of actin filaments after cell death [73]. It binds to Aβ in a concentration-dependent manner, reduces the toxicity of Aβ fibrils, and lowers the Aβ load in the brain [74, 75]. Gelsolin levels had a negative correlation with MMSE decline per year (R = –0.3, p = 0.02), and patients with rapid cognitive decline had lower gelsolin levels at baseline than patients with slow cognitive decline [76].

Hye et al. [77] used multiplex bead assays (Luminex xMAP) to evaluate plasma biomarkers associated with AD. They found that levels of three proteins— NCAM (neural cell adhesion molecule), sRAGE (soluble receptor for advanced glycation end products), and ICAM (intracellular adhesion molecule) — were significantly associated with the rate of cognitive decline; NCAM and sRAGE were both negatively correlated with disease progression, while ICAM was positively correlated with it.

Sphingolipids including ceramides and sphingomyelins are enriched in the central nervous system. They are major components of cell membranes and act as a second messenger to modulate a wide variety of cellular events. Perturbations in sphingolipids metabolism contribute to AD pathophysiology via Aβ formation, trafficking, and clearance [78]. In one longitudinal study, higher plasma levels of sphingomyelins, dihydrosphingomyelins, sphingomyelins/ceramides, and dihydrosphingomyelins/dihydroceramides ratios were associated with slower AD progression measure by MMSE and ADAS cog tests [79].

The biochemical markers of AD progression are summarized in Table 2.

Imaging biomarkers

The constant progress in neuroimaging techniques provides growing insight into cerebral structure, metabolism, function, and amyloid load. Although the role of imaging in the diagnostic process of AD is unquestionable, its usefulness as a tool to predict the speed of progression of the disease remains to be established. In many studies, different aspects of neuroimaging were investigated in order to define radiologic prognostic biomarkers. Two main approaches were used: single, baseline neuroimaging with repetitive cognitive assessment, and repetitive imaging studies with repetitive cognition testing. The size of the studied groups ranged between 8 and 193 AD patients. The longest follow-up period was 5 years, but in many studies follow-up duration was between 1 and 2 years. In some studies patients were divided into slowly versus rapidly progressors or stabilized versus non-stabilized subjects based on the absolute change in test scores. Most researchers analyzed correlations between changes in cognition and imaging measures. What is important from the point of view of clinical practice and usefulness of imaging biomarkers in everyday routine practice, for none of the potential biomarkers had defined cut-off values. Thus, radiological measurements performed in a single person cannot be used as a predictive tool.

MRI-based studies

Structural brain imaging was used mainly to investigate the progression of atrophy of different brain structures. The most widely analyzed parameters included rates of whole brain atrophy, hippocampal atrophy, and entorhinal cortex atrophy as well as the rate of expansion of ventricles. Four studies demonstrated that whole brain atrophy rate was associated with faster progression of the disease [80 –83]. In 5 out of 6 studies, ventricular expansion rate correlated with cognitive decline [80 , 84–86], whereas one study failed to find such a relationship [87]. In contrast, the rate of hippocampal atrophy was not associated with changes in neuropsychological test results [80 , 88]. Data on the entorhinal cortex are ambiguous: one study showed correlation with Delayed List Recall results [88], while another failed to find any relationship with cognitive function test results [80]. In one study, corpus callosum was investigated and only the progression of atrophy of its isthmus and splenium correlated with decline in MMSE [89].

In studies with only baseline MRI, associations with changes in cognition were found for cortical gray matter volume [90], cerebral atrophy [81], whole brain volume and entorhinal cortex thickness [91] as well as medial parietooccipital atrophy [92]. Hippocampal volume in one study was a predictor of cognitive decline [90] and in two studies [91, 93] was not shown to correlate with disease progression.

Structural abnormalities were also investigated in relation to AD progression. Data on white matter hyperintensities (WMHs) are not unequivocal. Brickman et al. [81] showed an association between WMHs severity and decrease in MMSE score, while other researchers did not observe such a relationship [90 , 94–96]. Interestingly, subcortical hyperintensities in cholinergic pathways were associated with results of the Wisconsin Card Sorting Tests [97]. Microbleeds [98] and leukoaraiosis load [86] did not correlate with cognitive decline.

The study by Leow et al. [99] using tensor based morphometry failed to find an association between temporal lobe atrophy and worsening of cognition.

There were also studies investigating cerebral metabolites with proton magnetic resonance spectroscopy. They showed that AD progression correlated with decline in N-acetyl aspartate (NAA), a marker for neurons, and NAA/Cr (Cr stands for creatine) as well as Cho/Cr ratio (Cho stands for choline, a cell membrane marker) [86 , 101].

Table 3 summarizes the results of MRI-based studies.

SPECT and PET studies

Single-photon emission computed tomography (SPECT) enables investigation of cerebral blood flow. The most widely used ligand in AD studies was 99mTc-hexamethylpropyleneamineoxime (99mTc-HMPO) and in two studies N-isopropyl-p-[123I]-iodoamphetamine (123I-IMP) was used. Follow-up SPECT imaging was performed in three studies. In two studies, cognitive decline correlated with more severe reduction of regional cerebral blood flow (rCBF) predominantly in frontal areas [102, 103]. Nobili et al. found that progressive hypoperfusion mainly affecting the right cerebral hemisphere corresponded with a faster decline in MMSE scores [104].

Results of studies with only one baseline SPECT provided less consistent data. One group noticed that temporal hypoperfusion was associated with a decline in MMSE results [105]; another found that lower rCBF in the left parietal and temporal areas were related to worsening in only language function [106], while Nishimura et al. [107] observed that hypoperfusion of the temporal and parietal cortex predicted worse results in cognitive tests. Nagahama et al. found correlations between decreased rCBF in frontal and parietal regions and faster progression of the disease [108]. There was also one negative study comprising 80 AD patients, in which no relationships were found between the perfusion index in five predefined regions of interest and more rapid cognitive decline [109].

Another method to acquire insight into the functional status of the brain is analysis of glucose metabolism through positron emission tomography (PET) with ¹⁸F-fluorodeoxyglucose (FDG). Most typically in AD patients hypometabolism occurs in temporoparietal areas and the frontal cortex with preservation of the primary sensory-motor cortex and cerebellum [110]. We identified four studies with repeated FDG-PET imaging. In general, the results showed that progressive hypometabolism in certain brain areas was associated with faster AD progression. That was true for the following areas: the parietal cortex [111], angular, temporal, and posterior cingulate regions [112, 113], and the middle temporal and precuneus regions [114]. In studies with a single FDG-PET scan, two groups of researchers did not predefine brain regions of interest and they found that lower glucose metabolism was associated with cognitive decline [115, 116]. Two other reports provided less consistent results, i.e., clinical worsening was associated with hypometabolism in frontal lobes [117] or posterior temporal and primary visual cortex [118].

Amyloid load in all studies was measured through PET with [11C]-Pittsburgh compound B (PIB) retention. In addition, Ossenkoppele et al. used also a second tracer –2-(1-6-[(2-[18F]fluoroethyl)(methyl)amino]-2-naphthylethylidene)malononitritile ([¹⁸F]FDDNP) [116]. All but one study performed repeated PET scan to analyze longitudinally amyloid deposition in relation to AD progression. In three reports, no differences were noticed in [¹¹C]PIB uptake changes between progressors and non-progressors [87 , 119]. This finding was explained by a high amyloid burden present in patients with AD diagnosis. Förster et al. found an association between change in [¹¹C]PIB uptake in temporal and precuneus areas and decline in delayed verbal recall and constructional praxis [114]. Another group of researchers observed that faster amyloid deposition was associated with faster memory decline [120]. Results of two studies showed that higher baseline [¹¹C]PIB retention correlated with faster progression of disease [111, 116].∥In comparison to amyloid imaging, in vivo tau imaging methods are at their early phase of development. So far, several PET ligands that could be used in human studies have been developed (for review, see [121, 122]). Among them [¹⁸F]FDDNP is known to bind both amyloid plaques and neurofibrillary tangles. However, there are no data on the predictive potential of tau PET imaging for AD progression.∥Table 4 summarizes the results of SPECT/PET studies.

CONCLUSIONS

Overall, the conducted studies so far have failed to find a reliable biomarker that would allow the identification of AD patients at risk of fast disease progression. Although several biomarkers, such as CSF Aβ₄₂ and tau as well as whole brain atrophy, seem to be promising candidates, their clinical usefulness needs to be tested in independent studies and widely accepted cut-off points for the stratification of AD progression need to be established. Better understanding of the mechanisms underlying AD progression might be needed for progress in researching new, potential biomarkers. There is also a need to determine widely accepted clinical criteria for defining the rate of AD progression. Without such criteria, it will be impossible to compare the results of different studies that use different definitions and diagnostic tools for measuring AD progression.

Footnotes

ACKNOWLEDGMENTS

This study was supported by a grant from The National Centre for Research and Development (1/BIOMARKAPD/2012). BM is supported by the Leading National Research Centre (KNOW), Medical University of Bialystok, Poland. The costs of publication were defrayed by KNOW (Medical Faculty of Jagiellonian University).

Authors’ disclosures available online ().

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