Biomarkers for Alzheimer disease: Classical and novel candidates' review

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Biomarkers for Alzheimer disease: Classical and Novel candidates Review Nadia El Kadmiri, Nadia Said, Ilham Slassi, Bouchra El Moutawakil, Sellama Nadifi

PII: S0306-4522(17)30487-6

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Reference: NSC 17894

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Received Date: 29 January 2017 Accepted Date: 9 July 2017

Please cite this article as: N. El Kadmiri, N. Said, I. Slassi, B. El Moutawakil, S. Nadifi, Biomarkers for Alzheimer disease: Classical and Novel candidates Review,

j.neuroscience.2017.07.017

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Nadia El Kadmiri

, Nadia Said

, Ilham Slassi

, Bouchra El Moutawakil

, Sellama Nadifi

Authors affiliations:

1 IBN ZOHR University, Polydisciplinary Faculty of Taroudant, B.P: 271, 83 000 Taroudant, Morocco.

2Hassan II University of Casablanca,Laboratory of Medical Genetics and Molecular Pathology, Faculty of Medicine and Pharmacy, B.P: 9154, Morocco.

3 IBN ROCHD Universitary Hospital, Neurology Department, , Casablanca, Morocco.

4Hassan II University of Casablanca,Laboratory of Pharmacology, Faculty of Medicine and Pharmacy, B.P: 9154, Morocco.

Running title: Biomarkers for AD.

Correspondence to Nadia El Kadmiri, Université Ibn Zohr, FacultéPolydisciplinaire de Taroudant, , Hay El Mohammadi (Lastah) B.P: 271, 83 000 Taroudant, Morocco. cell phone : + 212 6 41 61 98 35;

e-mail: elkadmiri1979@gmail.com

Abstract

The biomarkers may be useful for predictive diagnosis of Alzheimer's disease (AD). The current challenge is to diagnose it in its preclinical phase. The combination of cerebrospinal fluid (CSF) biomarkers and imaging has been investigated extensively for a number of years. It can provide an increased diagnostic accuracy. This review discusses the contribution of classical biomarkers to predict AD and highlightsnovel candidates identified as potential markers for AD. We referred to the electronic databases PubMed/Medline and Web of Science to search for articles that were published until February 2016. Sixty-two records were included in qualitative synthesis. In the first section, the results show the contribution of biomarkers to predict and track AD considered as classical biomarkers. In the second section, the results highlight the involvement of novel candidates that should be considered for future evaluation in the characterization of the AD progression. Reported findings open prospect to define noninvasive biomarkers to predict AD before symptoms onset.

Keywords: Biomarkers, diagnosis, Alzheimer's disease.

Introduction

Alzheimer’s disease (AD) is the most common form of neurodegenerative dementia in the elderly. AD refers to the neurodegenerative brain disorder regardless of clinical status. The pathological features that characterize AD are neuronal atrophy, synapse loss and the progressive accumulation of senile plaques. These plaques are composed of various amyloid beta (Aβ) peptides, including the 40 and 42 amino acid cleavage products (Aβ ₄₀ and Aβ₄₂) of the amyloid precursor protein, and intracellular neurofibrillar tangles (NFTs), containing hyperphosphorylated tau protein (Karran et al., 2011).

The identification of proteins altering neurodegeneration could lead to early diagnosis or new drug targets in the management of AD (El Kadmiri et al., 2014). A biological marker is a detectable or measurable component in biological fluids, such as blood, cerebrospinal fluid (CSF) or peripheral tissue. Besides, the biomarkercan help the detection of the pathology, especially since it is not present in normal subjects.

The characteristics of the ideal biomarker are summarized as follows:

 A sensitivity at least equal to 80%

 A specificity at least equal to 80%

 A positive predictive value close to 90%

 Involved in the neuropathology

 Allow an early detection of the disease

 Be reliable, non invasive and inexpensive

 Representing the pathophysiology of Alzheimer's disease

 Help differentiate Alzheimer's disease from other dementia

The main challenge of AD research is the discovery of reliable predictive markers to enable the diagnosis as early as possible, way before the loss of autonomy, setting the stage of dementia.

With the advent of novel therapies to slow the progression of lesions in AD, the race for

biomarkers’ research nowadays is top priority. Such a marker would be a huge asset, setting the

tone to newer and faster treatments. It would be an important indicator of disease progress,

improve treatment monitoring and be a valuable tool for epidemiological and therapeutic research.

Studies conducted in this field focus on blood and CSF analysis. However, CSF limits the ability to access DNA and RNA while blood biomarkers provide a rich source of genetic material and proteomic species for investigations. Currently in expert centers, total tau (T-tau), hyperphosphorylated tau (tau-P) and Aβ42 are the most explored CSF biomarkers. The combination of CSF biomarkers and imaging has been extensively investigated for a number of years, providing an increased accuracy in diagnosis. Researches have showed that the identification of CSF-Aβ42, CSF-tau-T, CSF-P-tau combined to neuroimaging and neuropsychological tools may help differentiate AD patients from MCI and control subjects (Vemuri et al., 2010; Richard et al., 2013; Blennow and Zetterberg, 2015). The current systematic review is divided in two main sections: the first one provides an insight of classical biomarkers’ role in predicting and monitoring AD progression whereas the second part highlights novel candidates recently identified.

Methods

The present review was carried out according to PRISMA guidelines (Moher et al., 2009).

Search and study selection:

An extensive search was conducted in PubMed/Medline and web of science databases. The articles used were from 1992 to February 2016. The search was based on a combination of keywords related to biomarkers (biomarkers, CSF biomarkers, Abeta, t-Tau, P-tau, biomarkers of AD, Plasma Biomarkers, Blood biomarkers, novel biomarker, AD, neuroimaging of AD). The articles were selected following a preliminary screening of the titles and abstracts. Studies that did not meet the eligibility criteria were excluded.

The selected articles were split in two sections: the first one regroups studies concerning the

biomarkers of AD assessed as classical biomarkers. In this group, the studies were not limited by

their publication time (year >1992). However, in the second section, the articles were selected

based on their publication date (year ≥ 2009). This group presents data concerning the novel AD

biomarkers.

Eligibility criteria

All studies meeting the following criteria were considered:

 Published in peer-reviewed journal.

 Written in the English language.

 Biomarkers assessed at least in AD group and or/MCI group.

 Biomarkers studied separately or combined to neuroimaging (p value, sensibility, specificity, significant involvement).

Results

From a total of 995 records, 440 duplicate records were removed. Then, titles and abstracts of 555 records were screened, leading to a 493 records’ exclusion for noneligibility.

The full texts of the remaining 62 reports were evaluated and included in a qualitative synthesis (Figure1).The results are showed in a two-section format: The first sectionincluded the papers evaluating classical biomarkers of AD and the second part deals with studies that recently revealed novel biomarkers of AD. The outcome of these data discussed in this review is summarized in Table1.

Classical biomarkers of AD

Identifying and understanding the mechanisms involved in the etiopathogenesis of AD shed light on several biological markers of the disease. The markers related to tau and Aβ42 proteins have so far been the most tested ones. They reflect the pathological features of AD, especially the neurofibrillary tangles and senile plaques. These “classical CSF biomarkers” can predict AD progression in individuals with mild cognitive impairment (MCI) and in cognitively normal individuals.

The AD is usually triggered by abnormal processing of β-amyloid (Aβ) peptide, ultimately

leading to formation of senile plaques in the brain. Indeed, the reduced CSF level of Aβ42 is due

to its deposition in senile plaques. On the other hand, an increased CSF level of P-tau reflects the

phosphorylation state of tau and the formation of neurofibrillary tangles in the brain. Thus, high

concentrations of CSF T-tau reflect the intensity of neuronal degeneration. Indeed, the CSF tau

increase revealed in AD may be explained by the release of tau from degenerating neurons and its large diffusion.

Several studies reported that CSF biomarkers amyloid beta 1–42 (Aβ42), total tau (tau), and tau phosphorylated at threonine 181(ptau-181) reflect the neuropathology development and progression in AD and MCI (Blennow et al., 2001; Hansson et al., 2006; Blennow and Zetterberg, 2015; Jiang et al., 2016). The carriers of FAD mutations showed decreased levels of CSF- Aβ42 and increased levels of CSF T-tau and P-tau as compared to the control group.

Studies have also highlighted a powerful association between plasma/serum Aβ and AD, demonstrating an increased plasma level of Aβ42 and a decreased level of Aβ40 in FAD cases.

In contrast, no difference in plasma/serum Aβ levels (Aβ40 and Aβ42) between sporadic (late- onset) AD and controls was revealed (Ringman et al., 2012). Concentration levels of T-tau, P- tau181, and Aβ42 in CSF are strongly related toAD development in patients with MCI presenting a sensitivity of 95% and specificity of 87% (Hansson et al., 2006). Over decades, autosomal dominant ADwas characterized bymany pathophysiological changes in CSF biomarkers (Bateman et al., 2012). It is worth mentioning that amyloid-beta Aβ42 concentration inCSF is prone to decline 25 years before expected symptom onset.

CSF assessment of T-tau and Aβ1-42 levels revealed a remarkable sensitivity but a lower

specificity to AD compared to other dementia disorders (Blennow, 2004). Studies have found a

strong correlation between decreased levels of Aβ42 in CSF and high numbers of plaques in the

neocortex and hippocampus (Strozyk et al., 2003). Moreover, within the living brain, high

retention of Pittsburgh Compound-B (PIB) in positron emission tomography (PET) scans

directly reflect plaque accumulation (Fagan et al., 2006; Forsberg et al., 2008). In controversy,

other studies found a significant reducedlevel in CSF-Aβ42 in some disorders without Aβ

plaques like Creutzfeldt–Jakob disease (CJD), amyotrophic lateral sclerosis and multiple system

atrophy(Sjögren et al., 2002; Holmberg et al., 2003).These findings suggest that other factors can

induce low CSF Aβ42 in addition to Aβ deposition in plaques. Therefore, the Aβ1-42 genesis

and its clearance are not well established which renders the interpretation of CSF Aβ1-42 more

difficult. Interestingly, recent studies in patients presenting familial AD show that the

Aβ42/Aβ40 ratio may be more efficientto monitor AD than the absolute value of Aβ42 (Bentahir

et al., 2006; Kumar-Singh et al., 2006). Nevertheless, the value of CSF Aβ40 is either unchanged

or slightly increased in AD (Fukuyama et al., 2000; Mehta et al., 2000; Hansson et al., 2007).

However, a decrease in the ratio of Aβ42/Aβ40 is more common than the mere decline of CSF Aβ42 alone (Vigo-Pelfrey et al., 1993; Hansson et al., 2007).

In literature, many researchers have measured plasma levels of Aβ in AD but the findings are contradictory. Indeed, some groups showedhigh plasma concentrations of Aβ42 or Aβ40 while other groups presented no modification(Irizarry, 2004). It was also found that Aβ42levels in plasma were considerably higher in non-demented elderly people who later converted to AD when compared to non-converters (Mayeux et al., 2003; Pomara et al., 2005). In contrast, Van Oijen et al., 2006 found an association between high Aβ40, low Aβ42, and risk of dementia.

Thesediscrepancies may be due to analytical difficulties or technical divergence(van Oijen et al., 2006). To this day, researchers and clinicians continue to debate the sensitivity and specificity of various biomarkers especially CSF Aβ42.

The combination of decreased amyloid Aβ42, increased T-Tau and phosphorylated tau P-Tau in CSF can help identify groups with MCI who convert later to AD by a high sensitivity, specificity with predictive value. Recently, these biomarkers have been definedas specific markers for pre- clinical AD.Many imaging methods such as FDDNPPET, Pittsburgh Compound-B PET, magnetic resonance spectroscopy, functional magnetic resonance imaging, combined to CSF biomarkers, and computerized memory tests — appear to improve the diagnosis(Doraiswamy, 2007; Gilbert, 2007).Baseline CSF Aβ42 levels correlate with MMSE decline over 8 year follow-up in cognitively normal elderly women (n=55)(Gustafson et al., 2007).

Amyloid PET and CSF biomarkers can enable early AD detection with high accuracy. The oldest

and more widely studied PET tracer for AmyPET is the Carbon11 labeled Pittsburgh compound

B (PiB)(Klunk et al., 2004). According to a study by Minoshima et al., PET could differentiate

between autopsy-confirmed pure AD patients versus dementia with Lewy bodies patients who

had ante mortem PET imaging and autopsy confirmation with a sensitivity of 90% and a

specificity of 80% (Minoshima et al., 2001). Foster et al. demonstrated that adding

fluorodeoxyglucose-positron emission tomography (FDG-PET) to clinical summaries improve

diagnostic accuracy and efficiency for both AD and temporal dementia(FTD)patients (Foster et

al., 2007).Besides, FDG-PET is more sensitive than MRI to the degeneration occurring in

preclinical and mild AD, suggesting that an MRI finding may be a more suitable clinical

biomarker for early AD identification(Karow et al., 2010).The first human study of a novel amyloid-imaging PET tracer, termed Pittsburgh Compound-B (PIB) was conducted in 16 patients with diagnosed mild AD and 9 controls. They found that PET imaging coupled to the novel tracer, PIB, can provide quantitative measures of amyloid deposits in living individuals(Klunk et al., 2004). Furthermore, Devanand et al. evaluated the amyloid level in the brain using (11) C-PIB- PET and cerebral glucose metabolism with florodeoxy glucose ((18)F- FDG) PET in patients with mild AD (n = 18), MCI(n = 24), and controls (CTR; n = 18) . The (11)C-PIB PET BP(ND) clearly differentiated diagnosed groups with (18)F-FDG PET regional cerebral metabolic rate for glucose (Devanand et al., 2010).

Small and his team performed PET after injection of 2-(1-{6- [(2[F18]fluoroethyl)(methyl)amino]-2 naphthyl}ethylidene) malononitrile (FDDNP), a molecule that binds to plaques and tangles in vitro. They showed that FDDNP-PET scanning could distinguish individuals with MCI from those with AD and thosewith no cognitive impairment.

This test is a noninvasive method to determine regional cerebral patterns of amyloid plaques and tau neurofibrillary tangles(Small et al., 2006). Regional hypometabolism on 18F-FDG/PET and specific brain regions atrophy on MRI have been considered as “neuronal injury” biomarkers and used for classifying various types of dementia (Tartaglia et al., 2011).Researchers reported that FDG-PET and episodic memory performance were the strongest predictors of MCI to AD conversion, whereas CSF tau and Aβ combined with FDG-PET predicted cognitive deterioration onset (Landau et al., 2010; Dukart et al., 2011, 2013; Teipel et al., 2015; Weise et al., 2015).Imaging methods (MRI and PET) and CSF studies have been considered as biomarkers candidates of AD.Recently, a new MRI technique has been introduced i.e T1rho (T1 ρ; the spin lattice relaxation time constant in the rotating frame). It detects the decay of transfer magnetization in presence of “spin-lock” radio-frequency field (Borthakur et al., 2004, 2006b;

Wheaton et al., 2005). Therefore Haris et al., 2015 aimed to evaluate the performance of T1ρ and

CSF biomarkers in distinguishing the AD from MCI and control subjects. T1ρ analysis showed

higher affinity while CSF biomarkers showed greater accuracy in delineating MCI and AD from

controls. Indeed, the use of T1ρ and CSF biomarkers to track the MCI to AD progression may

improve the early diagnosis of AD(Haris et al., 2015 p.1).

Novel candidate biomarkers:

Since miRNAs are deregulated in the brain, CSF and blood, they could be used as biomarkers in AD diagnosis. A study by Kiddle et al. using Soma Logic’s SOMA scan proteomics technology was conducted on 94 out of 163 candidates from 21 published studies in plasma samples. These designated proteins wee associated to AD phenotype and may therefore be considered as potential biomarkers (Kiddle et al., 2014). Another research examined the possible role of miRNAs serum as another alternative biomarkers for AD, revealing that serum miR-125b may be used as a noninvasive biomarker for AD (Tan et al., 2014). This cell-free miR-125b is reduced in serum of AD patients when compared to the non-inflammatory neurological controls with a 82% accuracy rate (Galimberti et al., 2014).

Afterwards, Leidinger et al. introduced 12 miRNAs and its involvement in AD. They managed to distinguish between AD and controls with an accuracy of 93%, a specificity of 95% and a sensitivity of 92% (Leidinger et al., 2013). Lugliet al. assessed the expression of microRNAs in a plasma fraction enriched in exosomes by differential centrifugation, using Illumina deep sequencing. Twenty miRNAs presented significant changes in the AD group using initial screening (miR-23b-3p, miR-24-3p, miR-29b-3p, miR-125b-5p, miR-138- 5p, miR-139-5p, miR-141-3p, miR-150-5p, miR-152-3p, miR-185-5p, miR-338-3p, miR- 342-3p, miR-342-5p, miR-548at-5p, miR-659-5p, miR-3065-5p, miR-3613-3p, miR-3916,miR-4772-3p, miR-5001- 3p).These findings, combined to other data may provide efficient and reliable biomarkers in AD(Lugli et al., 2015).Later, Müller et al. measuredthe expression levels of 4 miRNAs by quantitative PCR in CSF samples of AD patients. miR-29awas strongly expressed in CSF of AD patients. Hence, miR-29a may be selected as a candidate biomarker for AD in cell-free CSF(Müller et al., 2015).

Neuro-inflammation process was discovered in post mortem brains of AD patients. Additionally, increasedoxidative stress markers were revealed in brain specimens of MCI subjects (Antonell et al., 2014). Chronic inflammation is considered as a mechanism alteration found in AD patients(Blennow and Hampel, 2003). Indeed, many researchers sought to understand its process:

Kester et al. hypothesized that biomarkers involved in neuroinflammation and neurodegeneration

could be quantified to monitor AD progression. Chitinase-3-like protein 1 YKL-40 and Visinin-

like protein-1 (VILIP-1) play an important role in neuroinflammation and their CSF values

could contribute to differentiate subjects with symptomatic AD from controls. CSF levels of YKL-40 and VILIP-1 were assessed in 37 cognitively normal, 61 MCI and 65 AD patients. A high expression rate of YKL-40 was found in patients with MCI and AD contrarily to cognitively normal subjects. However, VILIP-1levels only augmentedin MCI. This result highlights the potential involvement YKL-40 and VILIP-1 in AD and opens new perspectives for the use of these biomarkers to monitor the progression of AD instead of the classical ones(Kester et al., 2015). Aβhas been shown to increase expression of interleukin 6 (IL-6) in astrocytes and microglia in culture. In hippocampal neurons, Aβ and IL-6 induce synaptic defection. Elevated levels of plasma IL-6 and areducedrate of plasma TRAIL were reported by Wu et al. in the disease group. Plasma levels of IL-6 and TRAIL were significantly correlated with their CSF levels. The researchers suggested that the plasma IL-6 and TRAIL may be considered as potential biomarkers at an early stage of AD(Wu et al., 2015). Moreover, increased levels of IL- 18 were found in AD patients(Motta et al., 2007; Yu et al., 2009; Swardfager et al., 2010). This ILis directly involved inneuromodulating synaptic plasticity and numerous inflammatory processes(Alboni et al., 2010). Maynard et al. assessed various cellular parameters related to mitochondrial bioenergetics and DNA damage in peripheral blood mononuclear cells (PBMCs) of 53 AD of a mild to a moderate degree and 30 healthy controls. Their results haverevealed an abnormal biochemical activity such as defectuous mitochondrial respiration, altered dNTP pools

and decreased DNA repair activity

in PBMCs of AD patients. This data suggest that these cellular parameters may be useful as biomarkers for AD(Maynard et al., 2015).The MRM-based mass spectral analysis showed that 4

biomarkers (pro-orexin, LAMP1, transthyretin and

ectonucleotidepyrophosphatase/phosphodiesterase 2 (ENPP2/autotaxin)) were significantly

moreincreased in the CSF of AD when compared to control cohort (Heywood et al., 2015).Kim

et al. examined the lymphocyte expression of cell cycle proteins in AD patients. Cell cycle

proteins CDK2, CDK4, CDK6, cyclin B, and cyclin D were highly expressed in AD patients as

well. Cell cycle dysregulation in peripheral lymphocytes may present a promising starting point

for detecting peripheral biomarkers of AD(Kim et al., 2016). Recent genetic studies have

identified a Cluster of Differentiation 33 (CD33) as a strong genetic locus associated to AD. The

level of CD33 was high in the AD brain, which positively correlate with amyloid plaque burden

and disease severity. CD33 may provide novel alternatives for AD therapeuticpathways (Jiang et

al., 2014). Buchhave et al., 2008 reported that the baseline levels of sCD40, but not sCD40L, were increased in MCI-AD cases when compared to age-matched controls (Mann-Whitney U- test, p = 0.02). They concluded that CD40-signalling may be involvedin the pathogenesis of early AD(Buchhave et al., 2009).

Discussion

This review attempts to provide an overview about the predictive and monitoring value of published biomarkers for AD into two sections.

Studies included in the first part highlight the significant involvement of biomarkers considered as classical markers,taking into considerationthe complexity of AD; it is a difficult to imagine that only one marker is sufficient to produce an accurate diagnosis. First, wefocused on Aβ1-42 andtau protein whoreflect the senile plaque and neurofibrillar degeneration and are already considered as potential markers.Studies investigated the interest of Tauisoforms dosage in CSF.

Theyrevealed a significant increase in the total concentration of tau proteins in CSF of AD patients. In addition,Aβ1-40 and Aβ 1-42 are significantly altered in CSF whereas Tau scarcely appears especially in carriers of the ε4 allele(Mehta et al., 2000; Vemuri et al., 2010). Therefore, researchers are moving towards the pathological form: P-tau metering. Different phosphorylation sites of Tau are under study and results confirm the efficiency of this marker for diagnosis.

However, the assessment in the CSF requires a spinal tap which is not a trivial matter and is difficult to implement in clinical practice. Currently, in the expert centers and specialized networks, assessment in CSF of three biomarkers are explored to facilitateAD diagnosis: t- tau, phospho-Tau and Aβ1-42 peptide. Used separately, each three assays has a superior sensitivity and specificity to 80% for detecting AD. The combination of dosage Aβ1-42 and tau protein can increase the sensitivity (80-85%) in the diagnosis of AD without decreasing specificity. They predict in MCI cases the progression to AD.

From 12 studiesincluding n=668AD, n= 668 MCI and n= 745controls, classical CSF biomarkers

assessed were reported useful to predict AD.Indeed, the current challenge in this pathology is to

detect and diagnose it in its preclinical stage, when the neuropathological lesions are just starting

to develop. At this stage, the symptoms are still absent or consist of MCI, which must be

distinguished from others due to aging. In MCI patients, those that evolved to AD (called

"converters") show an elevated level of t-tau and P-tau and reduced level ofAβ1-42 in CSF(Fukuyama et al., 2000; Mehta et al., 2000; Sjögren et al., 2002; Strozyk et al., 2003;

Hansson et al., 2006, 2007; Kumar-Singh et al., 2006; Forsberg et al., 2008; Vemuri et al., 2010;

Bateman et al., 2012; Ringman et al., 2012; Richard et al., 2013). To improve early and differential diagnosis of AD, novel biomarkers have been investigated in CSF, plasma and blood.

Which was the objective of the second section of this current review.Itregroups the studies ( n=745 AD, n= 396 controls)that usednovelcandidates that couldguide the diagnosis of AD.Indeed, these molecules MicroRNAs,YKL-40, VILIP-1, IL-18, IL-6, TRAIL, CDK2, CDK4, CDK6, cyclin B, cyclin D, sCD40, PBMCs mayplay a potentialrole in AD. Thus, they should be considered for future investigation in the characterization of the AD progression(Buchhave et al., 2009; Yu et al., 2009; Swardfager et al., 2010; Leidinger et al., 2013; Antonell et al., 2014;

Galimberti et al., 2014; Kester et al., 2015; Lugli et al., 2015; Maynard et al., 2015; Müller et al., 2015; Wu et al., 2015; Kim et al., 2016).

Limitations of the current review wasthe small number of studies conducted to date.In addition, this review couldn’t cover all biomarkers investigated in this area, but it opens prospects for others reviews to report the others findings and complete each one.

Conclusion

Blood is an attractive source for biomarkers due to minimal discomfort to the patient.Unfortunately, the sensitivity and specificity of blood biomarkersfor detecting AD remain lower than those from CSF. Most new drug candidates are targeted oninhibiting Aβ production and aggregation. Indeed, it is important to define biomarkers to monitor and predict AD. Genetic risk factors and neuroimaging will certainly play a crucial role as biomarkers of AD.

Accordingly, studiesmust be intensified to define noninvasive biomarkersto predict AD before

symptoms onset. The ultimate goal is to develop simple, noninvasive and inexpensive diagnostic

tests based on blood cells and/or molecules present in blood for the early detection of

AD.However, despite extensiveresearch worldwide, no diagnostic methods are currently

available for preclinical AD, and existing AD treatments are only symptomatic.

Conflict of interest

The authors declare that no competing interests exist.

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Figures legends

Figure 1: The process of study selection according to PRISMA flow diagram.

Tables legends

Table 1: A summarized table regrouping studies included in thissystematic review.

Type of marker

s

Study Total of samples

Nature of specimen

Biomarkers assessed

Aim of the study

Outcomes of study

P value

Classical markers

(Vemuri et al. 2010)

N= 109 Controls N = 192 aMCI N = 98 AD

CSF CSF Aβ (1- 42) levels.

Evaluate the

effect of

apolipoprotein E epsilon4 status on biomarkers of neurodegenerati on

A clear epsilon4 allele dose effect was seen on CSF Aβ (1-42) levels within each clinical group.

p <

0.001

(Richard et al.

2013)

N =100 MCI stable N =81 MCI progressio n

CSF MRI and CSF- analysis.

To assess the incremental value of MRI and

cerebrospinal fluid (CSF) analysis after a short memory

test for

predicting progression to AD

MRI and CSF all substantially contribute to the differentiation of

those MCI

patients who remain stable during follow-up from those who progress to develop AD.

p<0.001

(Hansson et al.

2006)

N = 137 MCI N = 39 controls

CSF CSF

concentration s of Aβ (1- 42) (Aβ42), total tau (T- tau), and phosphorylat ed tau (P- tau181)

To assess the association between CSF biomarkers and incipient AD in patients with mild cognitive impairment (MCI).

Concentrations of T-tau, P- tau181, and Aβ42 in CSF are strongly

associated with future

development of AD in patients with MCI.

p<0.000 1

(Ringman et al.

2012)

N=18 AD CSF Aβ42, t-tau, and p-tau₁₈₁ levels

Evaluation of the levels of CSF Aβ42, t-tau, and p-tau₁₈₁ in a larger cohort to define the levels

of such

biomarkers in relation to subjects

proximity to the typical age of disease

diagnosis in their family.

Diminished CSF levels of Aβ42, and increased levels of t-tau and p-tau₁₈₁ relative to non- mutation- carrying family members.

p<0.001

(Bateman et al.

2012)

N =128 AD

CSF Concentratio ns in the CSF of Aβ1–42, t- tau, and P- tau181.

Cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to

A series of pathophysiologi cal changes over decades in CSF biochemical markers of AD.

P<0.05

determine the relative order and magnitude of

pathophysiologi cal changes.

(Strozyk et al. 2003)

N=155 AD

CSF CSF Aβ 42 levels.

To investigate the relationship of amyloid neuropathology to postmortem CSF Aβ 42 levels in an autopsy sample

Lower Aβ 42 levels reflect neuropathologic processes implicated in amyloid-related pathologies.

P<0.05

(Hansson et al.

2007)

N = 137 MCI

CSF CSF

Aβ42/Aβ40

Assessment of the usefulness of the Aβ42/Aβ40 ratio as a predictive biomarker for AD.

The Aβ42/Aβ40

ratio was

superior to Aβ42 concentration with regard to identifying incipient AD in MCI.

P<0.05

(Forsberg et al.

2008)

N=21 MCI N=27 AD N= 6 controls

CSF (11)C-PIB (18)F-fluoro- deoxy- glucose (FDG) CSF Aβ1-42 CSF t- tau, CSF P- tau181.

Assessment of PIB retention

and CSF

biomarkers.

Correlations between PIB retention and CSF Aβ (1-42), total Tau and episodic

memory.

P<0.05

(Sjögren et al. 2002)

N=19 AD N=14 FTD N=11 ALS N= 15 PD N=17 HC

CSG CSF Aβ1-42 CSF P- tau181.

Assessment of CSF biomarkers.

These proteins may reflect pathophysiologi cal mechanisms

P< 0.05

(Kumar- Singh et al. 2006)

N=7 FAD CSF Aβ40 levels Aβ42levels Aβ42/Ab40

Aβ and APP processing on a novel ELISA

and their

correlation with

brain Ab

analyzed by image

densitometry

and mass

spectrometry

A valid tool for assaying the pathogenic potential of clinical PSEN mutations in a molecular diagnostic setting.

P<0.05

(Fukuyam a et al.

2000)

N=23 AD N=33 controls

CSF CSF Aβ 40 CSF Aβ42

To address an age-dependent alteration in the concentration of Aβs within the central nervous system and its

The

physiological metabolism of soluble Aβs in the brain is regulated in an age-dependent

P<0.05

probable

predisposition to amyloidgenesis in AD.

manner.

(Mehta et al. 2000)

N=114 AD N= 90 controls

CSF and Plasma

CSF Aβ40, Aβ42 Plasma Aβ40,Aβ42

To examine plasma and CSF levels of Aβ40 and Aβ42 levels in AD patients in relation to the apolipoprotein E

(Apo E)

genotype and dementia severity.

Aβ40 levels are elevated in sporadic AD and influenced by

Apo E

genotype.Aβ42 levels were lower in the AD group than in controls.

P<0.05

(Pomara et al. 2005)

N= 34 elderly subjects

Plasma Plasma Aβ40,Aβ42

To determine cognitive level and plasma Aβ40 and Aβ42

Alterations in plasma Aβ42 levels in elderly subjects

P<0.05

(van Oijen et al.

2006)

N=392 dementia cases

Plasma Plasma Aβ40,Aβ42

Investigation of the association between plasma Aβ

concentrations and risk of dementia

A potential role of plasma Abeta concentrations as a marker of incipient

dementia

P<0.05

(Mayeux et al.

2003)

N= 79 AD N=451 controls

Plasma Plasma Aβ40 and Aβ42 levels.

Assess plasma Aβ40 and Aβ42 levels.

Plasma Aβ40

and Aβ42

increase with age and are strongly

correlated with each other.

P<0.05

miRNA markers

(Galimbert i et al.

2014)

n=22 AD n=18 NINDCs n=8 INDCs

Serum miR- 125bmiR- 23amiR-26b

To profile circulating

miRNAs in

serum.

miR-125b serum levels are decreased in serum from patients with AD as compared with controls.

P<0.05

(Leidinger et al.

2013)

n=48 AD Blood 12-miRNA signature

To present a novel miRNA- based signature for detecting AD from blood samples.

Deregulated

miRNAs in

blood might be

used as

biomarkers in the diagnosis of AD or other neurological diseases.

P<0.05

(Lugli et al. 2015)

n=46 AD

Plasma fraction

microRNAs To assess the

value of

exosomal

miRNAs as

biomarkers for Alzheimer

Twenty miRNAs showed

significant differences in the AD group in initial screening

P<0.05

disease (Müller et

al. 2015)

n=18AD

CSF

for AD

diagnosis

miR-29a may be a candidate biomarker for AD.

P<0.05

Neuroinflammatory markers

(Kester et al. 2015)

n=61 MCI n= 65 AD

CSF CSF levels of YKL-40 and VILIP-1

To assess these proteins as a markers to monitor AD.

These CSF

biomarkers

should be

considered for future evaluation

in the

characterization of the natural history of AD.

P<0.05

(Antonell et al.

2014)

N=18 pre- AD N=22 Prod-AD N=12 iRBD N= 43 controls

CSF CSF YKL-40 Assessment of YKL-40 levels.

CSF YKL-40

may be a

valuable marker to detect early physiopathologi cal changes potentially linked with the neurodegenerati ve process.

P<0.05

(Yu et al.

2009)

N=109 AD N=109 controls

Lymphocy te

Interleukin (IL)-18

The effect of two functional polymorphisms

in IL-18

promoter: -607 C/A (rs1946518) and -137 G/C (rs187238) for the risk of LOAD.

Polymorphisms

in IL-18

promoter may be involved in the

risk of

developing sporadic LOAD.

P<0.05

(Swardfag er et al.

2010)

N=131 /9 4

CSF and blood

Interleukin (IL)-18

To measure cytokine

concentrations in AD

AD is

accompanied by an inflammatory response

P<0.05

(Wu et al.

2015)

N= 41AD N= 40 controls

Plasma Plasma IL-6 and TRAIL

To identify biomarkers of Alzheimer's disease

Plasma IL-6 and TRAIL were identified as potential

biomarkers of AD.

P<0.05

(Kim et al.

2016)

N=36 AD N=31 DC N=50 controls

Lymphocy te

CDK2, CDK4, CDK6, cyclin B, and cyclin D

To examine the lymphocyte expression of cell cycle proteins in AD patients

The levels of cell cycle proteins CDK2, CDK4, CDK6, cyclin B, and cyclin D were significantly higher in AD.

p<0.005

(Buchhave N=136 Plasma plasma levels Investigation of CD40-signalling p<0.01

AD , Alzheimer’s disease; aMCI, amnestic subjects with mild cognitive impairment; NINDCs , non-inflammatory neurological controls ; INDCs, inflammatory neurological controls ; DC, dementia Controls; CSF, Cerebrospinal fluid; Abeta, Amyloid beta; YKL-40 , Chitinase-3-like protein 1; VILIP-1, Visinin-like protein-1; IL6 , Interleukin 6; TRAIL, tumor necrosis factor-related apoptosis-inducing ligand, CDK, cyclin-dependent kinase. iRBD, idiopathic REM sleep behavior disorder. LOAD, sporadic late onset Alzheimer's disease

et al.

2009)

MCI-AD N=30 controls

of sCD40 the CD40 plasma levels

might play a role in the

pathogenesis of early AD.

(Maynard et al.

2015)

N=53 AD N=30 Controls

PBMCs PBMCs Measuring

various cellular parameters in PBBCs of AD for biomarkers discovery

Several biochemical activities may be useful as biomarkers for AD

P<0.05

Highlights:

 This review summarizes the contribution of classical and novel biomarkers to AD diagnosis



CSF classical biomarkers and imaging can provide an increased diagnostic accuracy.



Novel candidates recently showed a significant involvement in AD.