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Blood Biomarkers for Alzheimer’s Disease
Several studies have investigated plasma Aβ levels in AD.
13–15,21,22
results indicate that the model may also be able to predict AD with a
Although one study showed an increase in Aβ levels,
22
the majority of reasonable degree of specificity to other forms of dementia.
29
The model
studies have found no significant differences between AD and control was also effective in predicting those mild cognitive impairment (MCI)
cases.
13,14,16,17,23
Increased Aβ40 and sometimes Aβ42 correlate strongly patients who later converted to AD.
29
with age.
15,23
A broad overlap in plasma Aβ levels between AD and
control cases suggests that plasma Aβ cannot reliably differentiate Unbiased Approaches
sporadic AD from control cases. Although not useful for diagnosis, plasma Unbiased approaches have also been pursued to evaluate a broad range
Aβ measurement could be evaluated in the context of AD prediction, of proteins (proteomics), small-molecule metabolites (metabolomics) or
progression and therapeutic monitoring. Studies have suggested that transcripts (transcriptomics) in blood.
high plasma Aβ levels are a risk factor for developing AD.
22,24,25
In one of
the studies, plasma Aβ42 declined more rapidly over three years in Proteins
individuals who developed AD.
21
In other studies, no correlation between A proteomic study in plasma identified more than 70 proteins using 2D
plasma Aβ levels and disease progression or severity was observed.
22,24
electrophoresis (2D-PAGE).
30
The study included a limited number of
Interestingly, the results from a recent study suggest that an increased samples, and further studies are needed to determine whether the
level of Aβ42 is an indicator of increased risk of developing AD. However, identified proteins can be used as potential biomarkers for AD. Another
conversion to AD was accompanied by a significant decline in Aβ42 and study divided the 100 samples into two equal sets: a test set and a
a decreased Aβ42/Aβ40 ratio.
25
A dynamic change with a peak level of replication set. In the replication set, 27 proteins were present in
Aβ42 ahead of conversion to AD followed by a decline can help explain different amounts in AD compared with control samples.
31
When
some of the discrepant results observed between different studies. including all identified proteins, 34 of the 50 samples were correctly
predicted and gave a sensitivity of 56% and specificity of 80%.
31
The
Markers of Inflammation complexity of serum and plasma, imprecision in peak matching in mass
Amyloid deposition in the AD brain elicits a range of reactive spectroscopy and spot matching in 2D-PAGE and difficulties in assay
inflammatory responses.
26
Whether the accumulation of cytokines and standardisation make these approaches challenging, but advances in
acute-phase reactants within the brain is also reflected in serum or technology platforms and bioinformatics will allow broader applicability
plasma is not straightforward because many of these proteins do not to diseases such as AD.
32
easily cross the blood–brain barrier. Alternatively, AD may be associated
with a more widespread immune dysregulation that is detectable in RNA
plasma. There is some controversy in the literature regarding the The uniform chemical nature of RNA make transcriptome studies less of a
measurement of immune mediators in AD serum or plasma. Inflammatory challenge than both proteome and metabolome studies, and the potential
molecules including C-reactive protein (CRP), interleukin (IL)-1β, tumour use of blood-based gene expression profiling in the diagnosis of brain
necrosis factor (TNF)-β, IL6, IL-6 receptor complex, β1-antichymotrypsin disorders has been described by several independent groups.
33–35
Extensive
and transforming growth factor (TGF)-β show inconsistent changes across studies have shown that with careful control in the experimental design, the
studies, while other cytokines such as IL-12, interferon (INF)-α and INF-β microarray data are reproducible both between labs and between
remain unchanged.
27
experiments within a lab.
36
This is also true for realtime reverse transcriptase-
polymerase chain reaction (RT-PCR).
37
A study by Sullivan et al.
38
evaluating
Multicomponent Biomarkers the comparability of gene expression in blood suggested that whole blood
Given the multiplicity of pathophysiological processes implicated in AD, shares significant gene expression similarities with multiple central nervous
the diagnostic accuracy may be further improved by combining several system (CNS) tissues. A supportive example of this is a recent study that
markers. The standard approach using only a single marker or a few showed that the Parkinson’s-disease-linked β-synuclein gene was
related markers may not be enough to include all the variants of a upregulated both in blood and in the substantia nigra of patients with
heterogeneous disease such as AD. Parkinson’s disease.
39
Thus, there are studies supporting the idea that
expression of a selected set of genes in blood has potential as
Knowledge-based Approaches multicomponent biomarkers for different brain diseases, including AD.
Developing a multicomponent biomarker can be approached in two ways.
It can be a ‘knowledge-based’ approach, incorporating known putative Several gene expression studies have been performed for AD biomarker
biomarkers, or it can be an unbiased survey of many hundreds or thousands discovery using blood as the clinical sample. A pilot study of 16 AD patients
of biomolecules. A few knowledge-based approaches have attempted to and controls using a complementary DNA (cDNA) microarray, including
integrate data of selected molecules known to be involved in AD.
28
In one probes for 3,200 genes, identified a set of 20 candidate probes that showed
study, a panel of 29 serum biomarkers for inflammation, homocysteine an altered expression in AD.
40
Screening a set of 6,424 cDNA clones
metabolism, cholesterol metabolism and brain-specific proteins were representing unique genes with RNA isolated from blood mononuclear cells
evaluated. A model incorporating IL-6 receptor, cysteine, protein fraction β1 from 14 AD and 14 controls, 19 upregulated and 136 downregulated genes
and cholesterol levels proved to be the best combination to discriminate AD common to both males and females were identified.
41
Clear gender
from controls, although specificity to other cognitive disorders and differences were seen and many genes were differentially expressed in either
Parkinson’s disease was weaker.
28
In another study examining archived males or females. No model for AD prediction was generated using these
plasma samples, 120 different signalling proteins were evaluated. From genes. In another pilot study including 19 AD patients and 24 healthy age-
these proteins, a model was generated that included 18 proteins, which matched controls using 663 randomly picked cDNA clones, a set of 33
predicted a test set of 42 AD and 39 non-demented controls with high clones was able to generate a model that correctly predicted 34 out of 37
accuracy (89%).
29
Although the number of samples tested was low, the samples.
42
This study, with few samples and also few cDNA clones, should
EUROPEAN NEUROLOGICAL REVIEW 29
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