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  • Review Article
  • OPEN ACCESS

Biomarkers and Their Implications in Alzheimer’s Disease: A Literature Review

  • Vincent Marcucci1,*  and
  • Jeremy Kleiman2
 Author information  Cite
Exploratory Research and Hypothesis in Medicine   2021;6(4):164-176

doi: 10.14218/ERHM.2021.00016

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder with a complex pathology that is not completely understood. Over time, AD reduces one’s cortical and subcortical functioning. The incidence and prevalence of AD is projected to increase as the worldwide population continues to grow older. While advances in the field of neurology and medicine continue to improve, there are presently no novel therapeutic agents to prevent, halt, or cure patients suffering from AD. The utilization of biomarkers that aid the diagnostic algorithm, drug response monitoring and disease progression that add to further our understanding of the pathophysiology of neurodegenerative disease is vastly expanding. The significance of amyloid plaque deposition, tau pathology, and neurofibrillary tangle accumulation have been well-studied in the realm of neurodegenerative diseases for decades and are proposed biomarkers. However, it has been difficult to stratify physiological biomarkers of blood/plasma, cerebrospinal fluid, saliva/urine/hair/nail for diagnostic utility and overall understanding in the pathogenesis of neurodegeneration. We aim to review the most relevant, up-to-date biomarkers and their implications in AD.

Keywords

Biomarker(s), Alzheimer’s disease, Neurodegeneration, Tau, Amyloid, Blood, CSF

Introduction

Alzheimer’s disease (AD) is a progressive, irreversible neurodegenerative disease that commonly affects an aged population. AD is the most common cause of dementia worldwide, and accounts for over 60% of all confirmed cases.1 The World Health Organization (WHO) claims that the total estimated cases of AD exceeds 6 million in the United States, and over 35 million globally.2,3 The American population over 65 years of age is expected to increase from 58 million in 2021 to over 85 million by 2050.4 According to the Alzheimer’s Association, the percentage of individuals suffering from AD more than doubles from ages 65–54 to 75–54 (5.3%→13.8%), and more than 34% of people over the age of 85 years are living with AD.3,4 With the growing global population, and advances in medicine allowing individuals to live longer than previous decades, the incidence and prevalence of AD is likely to increase if no curative measures are established.3

More than 95% of AD cases are sporadic in nature, with only 1–5% resulting from a genetic disposition.5 The accumulation of amyloid plaques or amyloid-B (Aβ) peptides in the extracellular neural tissue and neurofibrillary tangles (NFT) composed of hyper-phosphorylated tau proteins within the intracellular tissue of the brain are the main pathological signs of AD.2,6,7 However, several other factors have been described as significant contributors to the pathogenesis of AD. Prolonged activation of the brain’s macrophages and other immune cells producing an inflammatory reaction have been shown to worsen amyloid and tau pathology.8 Evidence has been found that the development of AD also correlates with increased oxidative stress from neural free radical production.9 Mitochondrial dysfunction, calcium-mediated excitotoxicity, vascular injury, and immuno-dysregulation also appear to contribute to the development and/or exacerbation of AD.2,10,11 These pathologies cause a neuronal cellular insult, resulting in impaired synaptic function, as well as an overall reduction in healthy functioning neural tissue.12 The resulting chronic neurodegenerative changes produce cognitive, behavioral, and functional abnormalities that manifest as memory deterioration, confusion, and difficulty understanding visual and spatial relationships amongst many other clinical signs and symptoms.2,11–13

It has become an urgent priority within the medical community to identify biological markers and blood testing protocols to better understand the pathogenesis of AD in order to improve the efficiency of diagnosis, reduce associated costs, and prevent the occurrence of neurodegenerative diseases. Several methods have been previously deployed for aiding in the diagnostic algorithm of AD, including positron emission tomography (PET) scans to measure amyloid plaque deposits, lumbar punctures directed towards quantifying the degree of tau protein in the cerebrospinal fluid (CSF), and analyzing the amount of cortical atrophy via magnetic resonance imaging (MRI).14,15 However, imaging to this degree is very costly and measuring protein levels within the CSF is an invasive procedure.5,14,15

Herein, we review the contributions made towards the relevance in blood testing and biomarker identification in the use for diagnosing AD. We discuss the current roles and propose future uses for biomarkers in improving diagnostic accuracy, cost efficiency, patient stratification, and monitoring disease staging and progression to novel treatments for AD. The focus of this review article is to improve our overall depth of comprehension of the role biomarkers play in understanding the pathogenesis and treatment of AD.

Pathogenesis and pathology

The pathogenesis and pathology of AD is important when discussing implicated biomarkers. Although the pathogenesis is not clear, the leading theory is that there is an accumulation of insoluble Aβ peptides.16 Amyloid precursor protein (APP) is a transmembrane glycoprotein that is physiologically cleaved by alpha and gamma secretases to form two physiologic proteins, one soluble and one membrane bound. In the amyloid-producing process, APP is enzymatically cleaved by beta and gamma secretases, leading to the formation of various isoforms of Aβ peptides. These peptides aggregate to form fibrils and oligomers, ultimately leading to Aβ plaque formation. This eventually leads to inflammation and neuronal cell death, a process known as the amyloid cascade hypothesis.16–18 Consequently, these neuritic plaques can be observed via microscopy of brain tissue from AD patients, along with neuronal synapse loss.19–21

Another protein involved in the suggested pathogenesis of AD is tau. Tau is an axonal, microtubule-associated protein (MAP) that regulates the assembly and function of microtubules, predominantly within neurons.22,23 Physiologically, tau is highly soluble and undergoes phosphorylation to regulate its microtubule binding affinity. In AD, tau is hyper-phosphorylated, forming an insoluble protein that aggregates into toxic NFTs within neurons.21,23 These NFTs are another characteristic pathological feature found in the brains of AD patients.21 Furthermore, it is thought that tau has a role in mediating Aβ toxicity in AD, though this mechanism is unclear.20

Additionally, there are several genes implicated in the development of AD, one of the most notable being the e4 allele of the apolipoprotein E gene (APOE).24 APOE plays a role in Aβ peptide clearance, and individuals with the e4 allele are at an increased risk of AD, most likely due to Aβ accumulation through unclear mechanisms.25 In rare cases, genetic mutations of APP or presenilin (PSEN) genes can be inherited in an autosomal dominant pattern that results in an early onset AD. PSEN is a protein in the enzymatic gamma secretase complex that is responsible for pathological cleavage of APP in the development of AD.24,26

Biological markers (biomarkers)

A biomarker is a metric of a particular biological state that can be quantified or measured.27 A biomarker may be used to evaluate normal physiological processes within the body, pathological processes, or a pharmacological response to medical intervention. Biomarkers have played valuable roles in the diagnostic algorithm of many diseases, as well as the assessment of disease progression and potential recurrence. What makes a biomarker such a useful tool for researchers and clinicians is the ability to detect a fundamental neuropathologic feature of AD and with a relatively high sensitivity and specificity (ability of a test to accurately identify individuals with versus without a disease).28 There have been many biomarkers identified within the human body that serve as valuable tools in diagnosing and monitoring AD progression. Table 1 summaries the biomarkers that are covered in this review and demonstrates the relevant changes associated in AD. Below is a comprehensive review of the biomarkers that have been identified and used in the diagnosis and treatment of AD. An illustrative overview of the pathological mechanisms covered in this paper are presented in Figure 1.

Table 1

Comprehensive list of the biomarkers identified within the CSF and blood plasma, noting the relative changes in AD patients

Pathological mechanismBiomarkerElevated levels in CSFReduced levels in CSFElevated levels in plasmaReduced levels in plasma
AmyloidAβ42XX
Aβ40XX
Aβ38X
Taup-tauXX
t-tauX
Amyloid precursorBACE1X
SynapseNgX
SNAP25X
Syt1X
GAP43X
NPTX/NPX
NeuronalNfLXX
VILIP1X
VascularVCAM1XX
ICAM1X
Flt1X
ANPX
ADMX
ET1X
InflammatoryIL6X
IL15X
IL18X
sIL1R2X
hFABPX
TNFaX
TREM2X
YKL40X
GFAPX
S100BX
DNA bindingTDP43X
MetabolitesPUFAX
Bile acidsX
TryptophanX
IronFerritinX

Aβ, Amyloid beta; ADM, Adrenomedullin; ANP, Atrial natriuretic peptide; BACE1, β-secretase 1; ET1, Endothelin-1; Flt1, fms-related receptor tyrosine kinase; GAP43, Growth-associated protein-43; GFAP, Glial fibrillary acidic protein; hFABP, heart-type fatty acid-binding protein; ICAM1, Intercellular adhesion molecule 1; IL, Interleukin; NfL, Neurofilament-light chain; Ng, Neurogranin; NP/NPTX, Neuronal pentraxins; p-tau, Phosphorylated tau; PUFA, Polyunsaturated fatty acid; S100B, S100 calcium-binding protein B; sIL1R2, Soluble interleukin-1 receptor 2; SNAP25, Synaptosome–associated protein-25; Syt1, synaptotagmin-1; TDP, TAR-DNA binding protein; TNFa, Tumor necrosis factor alpha; TREM2, Triggering receptor expressed on myeloid cells 2; t-tau, Total tau; VCAM1, Vascular cell adhesion protein 1; VILIP1, Visinin-like protein 1; YKL40, Chitinase-3-like protein 1.

Relevant physiological biomarkers and the proposed pathological mechanisms associated with AD.
Fig. 1  Relevant physiological biomarkers and the proposed pathological mechanisms associated with AD.

In this figure, the three-dimensional images reflect hypothetical relationships rather than direct causal links or specific cortical/subcortical locations of pathological mechanisms and neurodegeneration. This is not an all-inclusive list of pathophysiological mechanisms and/or implicated biomarkers in AD. Only the most relevant ones that are covered within this article are presented. Aβ, Amyloid beta; Flt1, fms-related receptor tyrosine kinase; hFABP, heart-type fatty acid-binding protein; IL, Interleukin; p-tau, Phosphorylated tau; S100B, S100 calcium-binding protein B; TNFa, Tumor necrosis factor alpha; TREM2, Triggering receptor expressed on myeloid cells 2; t-tau, Total tau.

Cerebrospinal fluid (CSF) biomarkers

The most widely studied CSF biomarkers related to neurodegenerative diseases are Aβ peptides, and in particular the Aβ42 protein, total tau (t-tau), and tau phosphorylated at threonine 181 (p-tau181). These biomarkers exhibit greater than 95% sensitivity and 85% specificity in regards to diagnosing AD.2 Low quantities of Aβ42 in the CSF are observed in AD individuals compared to controls,29 while elevated levels of hyper-phosphorylated tau and t-tau have been identified in the CSF in AD patients.2,30 Previous literature has shown that high t-tau and/or p-tau181 along with low Aβ42 in the CSF can be detected before patients with AD become symptomatic, and offer improved diagnostic accuracy of AD from other causes of dementia.31 The ratio of t-tau/Aβ42 or p-tau181/Aβ42 within the CSF are reliable predictors in the progression of AD and in determining future cognitive impairment in individuals without a current neurological deficit over a 10-year follow-up period.2,32,33

Amyloid (Aβ) peptides

Aβ peptides are formed after being cleaved from amyloid precursor proteins. The Aβ peptides are then released into the CSF. This biological process allows for the level of Aβ peptides to be measured fairly easily. It has been well documented that a low level of Aβ42 peptides in the CSF and a high amyloid plaque concentration in the brain are highly suggestive of AD.2,34,35 The pathogenesis of the diminished Aβ42 peptides in the CSF is a result of the aggregation of hydrophobic peptide-forming plaques.34–47 A reduced level of Aβ42 has also been noted in patients with Lewy body dementia.24,36 Enzyme-linked immunosorbent assay (ELISA) and mass spectrometry have been utilized for accurately measuring CSF levels of Aβ42 peptides.34,38

Measuring the CSF level of shortened Aβ peptides (Aβ38 and Aβ40) has proven to be of minimal reliability when diagnosing AD.2,35 It has been identified that measuring Aβ peptide ratios may be advantageous over measuring the total Aβ42 peptide levels within the CSF. CSF measurements of Aβ42/Aβ40 and Aβ42/Aβ38 ratios were shown to better differentiate AD from dementia of a non-AD cause. The ratios are more closely associated with overall amyloid plaque deposition on PET scans and may be a superior target measure for newly implemented clinical trials of amyloid-based treatments than of CSF Aβ42 alone.2,39,40 A limiting factor of measuring only Aβ42 is the potentially confounding effect that results from differences in CSF subtleties or the variable rate of amyloid production from person to person. Importantly, this limitation is corrected when using the CSF Aβ42/Aβ40 ratio instead.2,41 When CSF Aβ42 is measured in conjunction with CSF Aβ40, it provides a useful measure for target engagement of β-secretase (BACE1) modulators to inhibit Aβ peptide production and deposition.42 There have also been promising results in tracking the physiological response to treatment with γ-secretase inhibitors when low CSF Aβ42 and Aβ40 levels are found with increased amounts of shortened fragments of CSF Aβ37 and Aβ38.43

Phosphorylated Tau (p-tau)

NFTs are composed of aggregates of abnormally hyper-phosphorylated p-tau.2,34,44 Excessive amounts of p-tau in the CSF have been widely documented in AD patients, and are associated with an increased rate of disease progression.34,45,46 The hyper-phosphorylation of these proteins results in the dysfunction of axonal transport in the brain.47 ELISA offers an effective way to measure p-tau by recognizing specific epitopes.45 Tau proteins phosphorylated at threonine 181 (p-tau181) have been the most thoroughly studied form of tau in conjunction with neurodegenerative disease.2,34,44,45 However, recent literature that has studied p-tau231 and p-tau199 levels in the CSF confirmed a similar specificity to p-tau181 in differentiating AD from healthy controls.48 Furthermore, p-tau231 demonstrated high sensitivity and specificity as a reliable biomarker for differentiating AD from non-AD dementias.48

A study completed in 2020, found elevated levels of tau phosphorylated at threonine 217 (p-tau217) in the CSF in patients with AD and proved to more accurately differentiate AD from non-AD dementias than CSF p-tau181.49 In the same study, a higher level of p-tau217 in the CSF demonstrated a closer correlation with the measured amount of cortical amyloid present on PET scans and in the CSF compared to that of p-tau181.49 Lastly, baseline and longitudinal measurements of CSF p-tau217 correlated with cortical tau deposition to a better extent than CSF p-tau181 when measured by the PET tau tracer [18F] flortaucipir.49 Several other p-tau proteins have also been studied (235, 396, and 404) that may be of value as potential biomarkers after further research is performed to identify neurodegenerative disease states in the future.50

Total Tau (t-tau)

T-tau is utilized as an indicator for overall neurodegeneration.51 In healthy individuals, CSF t-tau increases with age: <300 pg/ml (21–10 yrs), <450 pg/ml (51–10 yrs), and <500 pg/ml (>70 yrs).52 CSF t-tau has also been found to be significantly elevated in AD patients when compared to age-matched controls (>600 pg/ml in AD patients >70 yrs).52,53 The t-tau level in the CSF is also potentiated as a prognostic marker for the conversion of mild cognitive impairment (MCI) to AD.52 High CSF t-tau levels have been found in over 90 % of patients diagnosed with MCI that progressed to AD.54 Interestingly, patients with stable MCI did not go on to develop AD.54 CSF levels of t-tau can be accurately measured by ELISA.55

Beta site-amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1)

BACE1 is a major β-secretase involved in plaque formation in the brain.34 BACE1 expression is influenced by an inflammatory state, and in AD, the upregulation of neuritic cytokines reduces the peroxisome proliferator-activated receptors (PPAR1) which acts as an inhibitor of BACE1.56 CSF levels of BACE1 have been previously measured by Western blot and ELISA in both MCI and AD patients, as well as healthy controls.57 Along these lines, a significantly increased level of CSF BACE1 was found in MCI subjects versus AD and healthy controls.57 The high BACE1 level in the CSF of MCI patients may reflect an overproduction of BACE1 by stressed neurons and/or glial cells in MCI, which then decreases while cells die during the progression to AD.57,58 Nevertheless, further analysis is needed before BACE1 can be considered a reliable CSF biomarker for AD.

Synaptic biomarkers

A synapse or neuronal junction is the site of transmission of electric impulses between neurons (nerve cells) or between a neuron and a gland or muscle cell.59 A synapse functions by storing neurotransmitters in presynaptic vesicles that are then released into the inter-neural space or synaptic cleft. This process allows communication via postsynaptic receptors with an adjacent cell or neuron after a cascade of electric stimuli traverses the nerve.60 Significant loss of synaptic volume and degeneration within the grey matter of the brain are hallmarks of the early stages AD and produce cerebral impairment.61 Numerous CSF biomarkers have been studied in regard to synaptic dysfunction in AD patients that may be useful for further advancing our understanding of the pathogenesis and treatment of AD.

The most promising biomarkers associated with synaptic dysfunction in AD patients are the postsynaptic protein neurogranin (Ng) and the presynaptic proteins synaptosome–associated protein-25 (SNAP25) and synaptotagmin-1 (Syt1).2 The overall neuronal specificity and abundant expression of Ng, SNAP25, and Syt1 allow these biomarkers to accurately reflect the degree of neuronal and synaptic injury. This is because the CSF level of these biomarkers correlate with damage to neuronal and synaptic structures, as well as with the release of neuronal or synaptic components into the extracellular compartment as neurodegeneration progresses.2,62,63 Cortical and hippocampal synaptic density is reduced by nearly 50 % in patients suffering from AD.64 This significant loss in brain volume is attributed to global neuronal loss and a reduction in synaptic density.64,65

Ng is a calmodulin-binding neuronal protein that is largely found in postsynaptic membranes of the hippocampus and basal forebrain.66 This protein plays a key role in the brain’s adaptability to learning and memory function, as well as long-term potentiation (LTP).2,62 Prior literature has discovered that baseline Ng levels in the CSF strongly correlate with neurodegeneration and cortical atrophy in AD patients.2,62,67 Research has shown that measuring CSF Ng levels can serve as a reliable marker for future impairment to a similar degree as CSF t-tau and Aβ42 in patients who are presently cognitively normal.2,62 Additionally, the abundance of CSF Ng may provide another way for researchers to differentiate AD from other neurodegenerative disorders with high reliability.68

The pre-synaptic protein SNAP25 is essential for exocytosis of synaptic vesicles via vesicle docking, neurotransmitter release, and neurite outgrowth.2,34,69 Elevated levels of fragmented SNAP25 have been found in the CSF of AD patients when compared to healthy controls.70 Also, the amount of CSF SNAP25 may be associated with cortical atrophy and the overall risk of cognitive deterioration over time.70,71 Two distinct variants of SNAP25 have been isolated; SNAP25a and SNAP25b.34,69 Further investigation is needed before either isoform can be credited as a reliable marker for AD and neurodegeneration.72

Another important pre-synaptic biomarker found in the CSF of AD patients is Syt1. This protein acts as a calcium sensor to allow neurotransmitter release into the synaptic cleft.73 Increased amounts of Syt1 levels were identified in the CSF in the early stages of AD and MCI compared to healthy controls when using mass spectrometry.2,74 A similar study concerning CSF biomarkers found low reliability in differentiating MCI due to AD and AD dementia when CSF Syt1 was compared to CSF levels of Ng and SNAP25a.75 The use of Syt1 needs more validation through future studies before being considered a reliable CSF biomarker for neurodegenerative diseases.

A lesser-studied CSF biomarker in AD is growth-associated protein-43 (GAP43, neuromodulin). GAP43 is a crucial component of the neuronal axon and presynaptic terminal, and is primarily responsible for growth or “synaptic plasticity”.76 This protein also functions in pre-synaptic vesicle recycling through communication with synaptophysin and SNAP25.2,77 A strong association has been found with increased GAP43 levels in the CSF with amyloid and p-tau/t-tau in AD patients, as well as most other neurodegenerative conditions.2 This biomarker may have strong potential for use in the diagnostic algorithm of neurodegenerative disease.2,78

Pre-synaptic glycoproteins, often referred to as neuronal pentraxins (NPTX, NP) are involved in excitatory synapse formation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and are responsible for apoptotic neuronal death.79 Aβ amyloid oligomers induce the pre-synaptic release of NP1, which is partially responsible for the synaptic and mitochondrial insult seen in the amyloid pathology of neurodegeneration.80 Previous studies have correlated higher CSF levels of the pentraxin receptor, with increased severity of dementia in patients suffering from early-onset AD symptoms.81 Current information available regarding the usefulness of neuronal pentraxins as CSF biomarkers of synaptic injury is inadequate, and further research is necessary.

Neuronal biomarkers

A neuron is a highly specialized cell within the nervous system that is composed of several unique structures that include dendrites, a cell body and an axon. Few neuron-specific biomarkers have been studied in depth, however, the most relevant neuronal biomarkers found in the CSF include neurofilament-light chain (NfL) and visinin-like protein 1 (VILIP1).82

NfL is a measurable component of the CSF when using immunoassay.83 This marker is largely found within neuron axons and can be used to evaluate axonal damage in many neurological disorders.82 Elevated levels of CSF NfL may offer another reliable biomarker for grading AD severity and progression.2,82 Research has revealed elevated levels of NfL in the CSF during the early stages of symptom onset in AD.82 Furthermore, rising levels of CSF NfL have been associated with the degree of cortical atrophy, cognitive impairment, and overall death rate of AD.82

VILIP1 is a protein that is expressed in abundance within the cerebellum and functions as a calcium-sensing receptor that is responsible for controlling intracellular signaling pathways through that regulation of adenylyl cyclase.84 Previous literature has found a strong correlation between the level of VILIP1 in the CSF and overall cortical atrophy, as well as with amyloid/t-tau levels in patients displaying varying degrees of AD progression.32,85 Similar to other CSF biomarkers, VILIP1 levels were increased in patients with MCI as a result of AD, in addition to individuals with AD dementia, when compared to healthy controls.32 The ratio of CSF VILIP1/Aβ42 may serve as a better marker for determining whole-brain or regional cortical atrophy and cognitive deterioration when evaluated against some of the most widely studied CSF biomarkers that include t-tau, p-tau181, Aβ42 and t-tau/Aβ42 or p-tau181/Aβ42.85 CSF VILIP1 has been determined to be a promising marker for not only neuronal injury in AD, but also as a reliable marker of future impairment in patients who are intellectually normal.85,86

Vascular markers of the CSF

Vascular injury and insult have provided some promising potential CSF biomarkers regarding neurodegenerative disease. Some of the previously identified vascular CSF biomarkers include vascular cell adhesion protein 1 (VCAM1), which mediates the binding of immune cells when endothelial damage occurs inside of blood vessels,87 intercellular adhesion molecule 1 (ICAM1), a protein present on the surface of leukocytes that is responsible for cellular-vessel wall adhesion,88 interleukin-15 (IL15), a pro-inflammatory cytokine,89 and fms-related receptor tyrosine kinase (Flt1), a transmembrane domain responsible for angiogenic growth factor binding.90 A 2018 study demonstrated increased CSF level of VCAM1, ICAM1, IL15 and Flt1 in patients diagnosed with AD in symptomatic and pre-symptomatic states when compared to healthy controls.91 Adhesion proteins (ICAM1 and VCAM1) were also found to be strongly associated with future cognitive decline.91

A cytoplasmic cardiac protein called heart-type fatty acid-binding protein (hFABP), which is released during periods of myocardial ischemia,92 has been isolated in the CSF at elevated levels in patients with AD and vascular dementia.93 An increased level of hFABP in the CSF is also correlated with lower CSF Aβ42,94 as well as cortical deterioration in patients who displayed amyloid plaque accumulation.95 This may therefore be a potentially useful marker in distinguishing characteristics between vascular dementia, AD and other forms of neurodegeneration.

Cytokines and Inflammatory mediators

Neuro-inflammation is recognized as a fundamental component in the pathological process observed in AD. For over forty years, literature has indicated protective effects against AD when patients take anti-inflammatory agents for various other unrelated diseases.8,96 Research hypothesizes the overwhelmingly increased deposition of Aβ plaques and a prolonged inflammatory response in an attempt to combat this pathology. The results indicate a sustained activation of microglia in a feed-forward loop that causes inevitable progression of the disease.97,98

Tumor necrosis factor-alpha (TNFa) is a small signaling protein (cytokine) released from microglial cells and astrocytes in the brain in response to an inflammatory reaction.99 CSF levels of TNFa, as well as TNFa converting enzyme (TACE), have been found to be higher in AD patients when compared to healthy controls.2,100,101 Another well-studied inflammatory biomarker is triggering receptor expressed on myeloid cells 2 (TREM2). Research has described missense mutations of TREM2, which induces phagocytosis of amyloid plaques, as a significant risk for the development of AD and other neurodegenerative diseases.102 There have been similar reports from animal studies and human models that have identified elevated CSF levels of TREM2 in pre-symptomatic stages of AD patients.2,8 Recent literature also suggests that CSF TREM2 levels may be directly associated with the degree of tau and/or amyloid pathology present.2,8 An astrocytic pro-inflammatory biomarker called chitinase-3-like protein 1 (YKL40) has been studied to assess the diagnostic accuracy in the CSF of AD patients.103,104 In a study focusing on CSF YKL40 levels, researchers were able to positively discriminate AD from cognitively normal controls and patients with frontotemporal dementia (FTD).104 Furthermore, this same study found that the CSF level of YKL40 appropriately identified tau-positive individuals and AD pathophysiology-positive individuals from healthy controls and FTD patients.104 Increased levels of CSF YKL40 have shown a positive correlation with cortical thinning in AD patients who displayed the APOE4 mutation.105 CSF YKL40 has been positively associated with tau protein during the asymptomatic and preclinical stages of AD.106 YKL40 may also serve as a reliable biomarker for future cognitive decline.106 The utilization of CSF YKL40 as a biomarker in neurodegenerative diseases adds to the growing array of markers used for understanding and treating these diseases.

Glial fibrillary acidic protein (GFAP) is an intermediate filament expressed in astrocytes and ependymal cells throughout the central nervous system.107 Increased CSF levels of GFAP have been identified in several neurodegenerative diseases, including AD, FTD and Lewy body dementia.108 Another potentially useful biomarker is S100 calcium-binding protein B (S100B). This protein is exclusively expressed in astrocytes and has several theorized functions, such as neurite expansion and growth.109 Elevated CSF S100B levels may offer diagnostic value during the initial stages of AD, especially when evaluating short-term memory recall.110

Blood and Plasma Biomarkers

Amyloid (Aβ) peptides

Detecting Aβ in plasma and accurately using it as a biomarker for amyloid pathology has been difficult using ELISA.111 Not only are plasma Aβ levels much lower than in the CSF, but there is also a poor correlation between CSF and plasma levels of Aβ alone.111,112 For this reason, and due to the contribution of Aβ from other peripheral sources, there has been inconsistency in plasma measurements of Aβ in different laboratories using ELISA.111,113 This aside, one study showed that decreasing levels of Aβ42, an Aβ peptide with 42 residues that contributes to plaque formation, and decreasing ratios of Aβ42/Aβ40 in serial measurements using ELISA were associated with cognitive decline and the development of AD.114,115

The past decade has exhibited improvements in accurate measurements of Aβ using immunoaffinity-based assays, including single-molecule arrays (SIMOA) and mass spectrometry.116 Specifically, studies using these methods to measure Aβ42/Aβ40 or Aβ40/Aβ42 ratios in plasma have shown a correlation with AD pathology, suggesting that it can serve as a prognostic indicator.117–119 Plasma levels of Aβ42/Aβ40 were additionally able to predict amyloid pathology in patients without cognitive decline who were at risk for AD.118,119 Recent studies have used immunoprecipitation and mass spectrometry to test for plasma biomarkers in both cognitively normal and abnormal patients. These works showed that there is a strong correlation between both APP/Aβ42 and Aβ42/40 plasma levels with Aβ-PET scan burden and CSF levels of Aβ42, which are more established markers of amyloidosis seen in AD.2,117,118 The use of SIMOA to detect the plasma level of Aβ42/Aβ40 also showed a positive correlation with abnormal CSF level of Aβ42.120 In terms of prognosis, a lower plasma level of Aβ42/Aβ40 has been shown to be associated with a more rapid decline in cognitive function in patients with subjective cognitive decline.119

Another Aβ related plasma biomarker that has shown prognostic value in AD is the detection of Aβ mis-folding using immune-infrared-sensor technology.121 In one cohort study, the presence of Aβ mis-folding and Aβ42/Aβ40 plasma levels were tracked in patients with only subjective cognitive decline. The presence of mis-folding and positive Aβ ratios were strongly correlated with the progression to MCI and dementia due to AD.121

Tau

Detecting tau in plasma using immunoassay techniques and using it as a biomarker for AD pathology has shown promise in numerous studies.122–125 Several cohorts showed that an increased level of p-tau181 in plasma, as measured by SIMOA and solid-phase enzyme immunoassay, is highly accurate in confirming AD pathology and in differentiating it from other non-AD pathologies in dementia patients.122,123 Furthermore, a high plasma p-tau181 level more accurately predicted AD neuropathology compared to clinical diagnosis up to 8 years prior to postmortem examination of brain tissue.122 An association also exists between a high plasma p-tau181 level and the development of AD dementia in unimpaired patients and those with MCI. This correlates with CSF p-tau181 and is predictive of positive PET scans.124 Nevertheless, the plasma measurement of p-tau217 shows even more promise. Elevated plasma levels of p-tau217 discriminated AD dementia from other non-AD pathologies with greater accuracy than plasma p-tau181, plasma NfL and the detection of brain atrophy on MRI.125

Neurofilament Light Chain (NfL)

NfLs are components of axons that are another potential biomarker of use in AD.82,126,127 High plasma NfL levels, measured using SIMOA, have been associated with the diagnoses of MCI and AD with Aβ pathology, and are correlated with brain atrophy on neuroimaging scans associated with AD.126,127 Additionally, plasma NfL has been predictive of the rate of MRI brain atrophy in AD patients when using the Mini-Mental State Examination and Logical Memory Test for assessment.127 In that same study, serial NfL measurements showed a high rate of change in AD patients when changing from a pre-symptomatic to symptomatic alteration, demonstrating utility in predicting the progression of AD.127

Inflammatory markers

Due to the inflammation involved in the pathogenesis of AD, there are numerous changes in the level of peripheral inflammatory markers, especially IL1-related cytokines and receptors.128,129 Using ELISA, one study found an increase in serum sIL1R2 (soluble interleukin-1 receptor 2) and free IL18 in MCI, which also disappeared in AD.128 They also found an increase in IL1Ra (interleukin-1 receptor antagonist), sIL1R1, sIL1R4, and IL18BP (interleukin-18 binding protein) in patients with AD but not with MCI, which may aid in showing the progression from MCI to AD.128 Another peripheral cytokine of possible importance is interleukin-6 (IL6) which was found to be elevated in AD patients compared with healthy controls and showed an inverse correlation with Mini-Mental Status Examination Scores.129

Additionally, there are reported changes in peripheral T-cell presence and receptor expression in AD patients.130–132 One study found an “immune signature” consisting of an increase in CD8+T effector memory CD45RA+ (TEMRA) cells, which additionally showed a negative correlation with cognition.130 It has also been found that there are lower levels of CD45RA on CD4+T cells in AD patients compared to patients with other forms of dementia. In addition, the sensitivity and predictive value increased for classifying AD when combining CD45RA with the APOE genotype.131

Vascular markers

Vascular and microvascular dysregulation has been suggested as a causal role for AD and may precede neurodegeneration with up to 30 % of AD cases presenting with cerebrovascular pathology.93,133,134 One study showed elevated levels of soluble E-selectins and VCAM1 in patients with AD compared to healthy controls.135 Additionally, altered levels of the endothelin regulator and vasodilators endothelin-1 (ET1), atrial natriuretic peptide (ANP), and adrenomedullin (ADM) have been found in AD patients using special immunoassays to detect their precursors.133,136 These assays measured C-terminal endothelin-1 precursor fragment (CT-proET1), mid-regional pro-adrenomedullin (MR-proADM), and mid-regional pro-atrial natriuretic peptide (MR-proANP) in the plasma since their final products have short half-lives.133,136 In patients with AD, there were increased blood levels of MR-proADM and MR-proANP with decreased levels of CT-proET1. Additionally, both the sensitivity and specificity were increased when measuring the MR-proANP/CT-proET1 ratio.136 Furthermore, increased plasma levels of MR-proANP and MR-proADM showed predictive value for progression from MCI to AD.137 It is important to note that these markers might represent systemic microvascular or inflammatory changes, and may warrant further investigation for their clinical utility in diagnosing and predicting AD.133

TAR-DNA binding protein (TDP43)

TDP43 is an RNA and DNA binding protein that is involved in regulating splicing and transcriptional repression, and is a major component of cytoplasmic inclusions within neurons in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD).138 It has recently been shown that 25–50 % of AD cases present with TDP43 pathological changes, which may be a factor in the development of AD, especially in more severe cases.139–142 Increased plasma levels of TDP43 and TDP43 variants have been detected in both AD and MCI before conversion to AD.141,143 Due to increased levels of TDP43 in other neurodegenerative disorders, its clinical utility may be limited in distinguishing between various disorders, but it could still be used to narrow-down potential diagnoses.141

Metabolites

Dysregulation of several metabolic pathways with changes in plasma metabolites has been associated with and may contribute to AD pathology and impairment.5 Cholesterol metabolism, fatty acid (FA) metabolism, bile acid synthesis, and amino acid metabolism may be the most associated with AD. Therefore, changes in plasma FAs, bile acids, and amino acids are some of the most apparent alterations reported in previous studies.5,144–146

The reduction in the level of polyunsaturated fatty acids (PUFA), particularly docosahexaenoic acid (DHA), has been associated with cognitive impairment due to AD and may be due to impaired FA metabolism in the liver.5,147,148 One study showed that cognitive performance improved with dietary supplementation of DHA in AD patients, which could have been due to neuroprotective properties of PUFAs.148,149 To further implicated liver dysfunction, the level of the bile acids cholic acid, chenodeoxycholic acid, and allocholic acid all increased with disease severity in AD.5 The role of bile acids as biomarkers in AD is further propounded by evidence of association between the traditional AD biomarkers, Aβ and tau, and bile acid profiles.5,150

Regarding alterations in FA metabolism, studies have shown declining acyl-carnitines across subjects from healthy individuals to those with MCI and AD, with significantly reduced levels of medium- and long-chain acyl-carnitines in those with AD.5,151 Impaired energy metabolism is further indicated by one study that analyzed RNA transcripts to find decreased beta-oxidation, mitochondrial transport, and carnitine shuttle activity in patients with AD.152

Amino acid metabolism may also play a role in the use of metabolic profiles as biomarkers of AD, as reduced levels of tryptophan have been found in AD subjects, along with its derivatives of serotonin and indole-3-lactic acid.5 The decrease in tryptophan and indole-3-lactic acid levels were further associated with disease severity of AD, which may serve as a biomarker for AD disease progression.5 This follows our physiologic understanding of tryptophan’s role as a precursor for neurotransmitters and their role in neuronal activity.153

Noninvasive biomarkers

Saliva is an extracellular fluid that functions primarily to aid in the digestion of food and maintain appropriate oral hygiene.154 It is composed largely of water, and a very minuscule amount of electrolytes, mucus, antibacterial compounds and various enzymes.154 Salivary testing offers an excellent alternative to expensive laboratory blood tests and invasive CSF measures via lumbar puncture. The most relevant finding has been the elevated salivary cortisol level in AD patients compared to healthy controls.155 In the same study, the level of evening cortisol was lower in AD patients than in control subjects.155 Despite these results, more research is needed before any salivary components can be reliably used as biomarkers in AD and neurodegeneration.

Another potential low-cost biomarker that can be easily collected and stored is a hair sample. Hair is a protein filament composed of keratin that grows from the dermis of the skin.156 What makes hair follicles a potential biomarker for neurodegenerative disease is the fact that elemental components in its structure can be maintained for extended periods of time.2,157 Several elemental metals have been shown to be elevated in AD patients’ hair samples, including Br, K, Na and Zn. By contrast, Al, Ca, Co, Cu, Fe, Hg and Pb levels were reduced in the same hair samples.2,157

Nails are a keratinous plate at the fingertips and toe-tips, and similar to hair, are able to store elemental components for an extended amount of time.158 Zinc is an abundant element within the brain and may play a role in several pathways relevant to the pathogenesis of AD, most importantly the processing of APP and aggregation of Aβ.159 The level of zinc and numerous other metal chelators were shown to be decreased in nail samples of patients with AD.2,159 However, there is no reliable literature that has consistently linked the use of elemental findings from nail samples as biomarkers in AD, and therefore further analysis is indicated.

The urinary tract may offer the most promise in identifying biomarkers that may distinguish neurodegeneration. Testing urine samples from AD patients is thought to recognize markers or patterns of free radical damage, or oxidative stress that may point to a pathological process of AD.2 8-hydroxy-2-deoxy-guanosine (8OHdG) is a major product of DNA oxidative damage160 and serves as a widely studied biomarker. Previous literature has found elevated 8OHdG levels in the urine by more than ten-fold in AD patients when compared to cognitively normal controls.161 Isoprostanes and neuroprostanes are prostaglandin-like compounds formed from free radical-catalyzed peroxidation of fatty acids,162 and are excreted in the urine and may be reliable biomarkers for AD. The level of isoprostanes was shown to be elevated in patients with MCI compared to healthy controls and elevated to a higher extent in AD compared to MCI.2 Lastly, urinary levels of amino acids are also theorized to be potential biomarkers of AD.2,163 Elevated levels of glycine, histidine, 3-methyl histidine and carnosine were isolated in urinary samples of AD patients.2,164 While these results demonstrate the increasing use of urine components as biomarkers, the reliability of these components needs further development.

Iron overload

Iron plays several important roles within the brain to maintain homeostatic function. Iron is responsible for neuronal oxygen transportation, DNA and myelin synthesis and appropriate mitochondrial functioning.165,166 However, iron overload may be detrimental to neuronal health. Previous research has found an increased amount of iron deposits within the brain of patients with AD167 and MCI.168 Interestingly, iron facilitated the aggregation of Aβ plaques and p-tau by influencing the function of APP.169 The utilization of brain imaging (MRI and PET scans) confirmed increased levels of iron in the brain in patients with elevated Aβ deposits, suggesting that iron may accelerate the aggregation of amyloid pathology in this population.170 Research also points in favor of ferritin as a potential biomarker of AD.165,169 Elevated ferritin levels in the CSF have been previously documented in APOE-e4 carriers and reflect a faster cognitive decline in MCI patients as they progress to AD.171 However, plasma levels of ferritin have not demonstrated a strong correlation with CSF findings in AD and MCI patients.171 While data is limited on ferritin as a biomarker, it may be more useful as a prognostic marker in the CSF when evaluating AD.

Prospect

Medical advancements and drug therapy trials targeting neurodegeneration have largely failed to provide any significant advancement in the detection, treatment, and prevention of neurodegeneration.165,172,173 AD treatment is trending in the direction of a precision-based model to individualize diagnostic algorithms and treatment plans. By incorporating the accuracy and reliability of more physiological biomarkers, we may be able to better understand the patient population at higher risk for neurodegeneration and slow disease progression. Individualized biomarkers in AD and other neurodegenerative diseases may provide a path towards prevention and potential curative measures.

Conclusions

Biomarkers have played a crucial role in improving the diagnostic efficiency, cost analysis, and overall enhancement of our understanding of the pathophysiology in neurodegeneration. Biomarker inclusion has remained an overwhelming target in AD research, with the most reliable and widely studied ones comprising amyloid and tau pathology. More data is needed to standardize and stratify biomarkers indicating vascular pathology, neuro-inflammatory response, and reliable noninvasive markers outside of the blood and CSF.

Abbreviations

Aβ: 

Amyloid beta

AD: 

Alzheimer’s disease

ADM: 

Adrenomedullin

ANP: 

Atrial natriuretic peptide

APP: 

Amyloid Precursor Protein

BACE1: 

β-secretase 1

CSF: 

Cerebrospinal fluid

ELISA: 

Enzyme linked immunosorbent assay

ET1: 

Endothelin-1

Flt1: 

fms-related receptor tyrosine kinase

GAP43: 

Growth-associated protein-43

GFAP: 

Glial fibrillary acidic protein

hFABP: 

heart-type fatty acid-binding protein

ICAM1: 

Intercellular adhesion molecule 1

MAP: 

Microtubule associated protein

MCI: 

Mild cognitive impairment

MRI: 

Magnetic resonance imaging

NfL: 

Neurofilament-light chain

NFT: 

Neurofibrillary tangles

Ng: 

Neurogranin

NP/NPTX: 

Neuronal pentraxins

PET: 

Positron-emission tomography

PPAR1: 

Peroxisome proliferator-activated receptor

PSEN: 

Presenilin

p-tau: 

Phosphorylated tau

PUFA: 

Polyunsaturated fatty acid

S100B: 

S100 calcium-binding protein B

sIL-1R2: 

Soluble interleukin-1 receptor 2

SIMOA: 

Single-molecule arrays

SNAP25: 

Synaptosome–associated protein-25

Syt1: 

synaptotagmin-1

TDP: 

TAR-DNA binding protein

TREM2: 

Triggering receptor expressed on myeloid cells 2

VCAM1: 

Vascular cell adhesion protein 1

VILIP1: 

Visinin-like protein 1

YKL40: 

Chitinase-3-like protein 1

Declarations

Acknowledgement

We thank Kimberly Castellano for designing and creating the image represented in Figure 1.

Funding

This work did not receive funding for the development or writing of this manuscript.

Conflict of interest

The authors have no financial conflicts of interest or conflicts of any interests to disclose.

Authors’ contributions

Study concept and design (JK), acquisition of data (VM, JK), manuscript writing (VM, JK), critical revision of the manuscript for important intellectual content (VM, JK), analysis and interpretation of data (VM, JK).

References

  1. Cass SP. Alzheimer’s Disease and Exercise: A Literature Review. Curr Sports Med Rep 2017;16(1):19-22 View Article
  2. Tarawneh R. Biomarkers: Our Path Towards a Cure for Alzheimer Disease. Biomark Insights 2020;15:1177271920976367 View Article
  3. The Alzheimer’s Association. 2021 Alzheimer’s Disease Facts and Figures. Alzheimer’s Dement 2021;17(3):327-406 View Article
  4. Rajan KB, Weuve J, Barnes LL, McAninch EA, Wilson RS, Evans DA. Population estimate of people with clinical AD and mild cognitive impairment in the United States (2020-2060). Alzheimers Dement 2021;17. In press
  5. Shao Y, Ouyang Y, Li T, Liu X, Xu X, Li S, et al. Alteration of Metabolic Profile and Potential Biomarkers in the Plasma of Alzheimer’s Disease. Aging Dis 2020;11(6):1459-1470 View Article
  6. Serrano-Pozo A, Frosch MP, Masliah E, Hyman BT. Neuropathological alterations in Alzheimer disease. Cold Spring Harb Perspect Med 2011;1(1):a006189 View Article
  7. Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 1991;82(4):239-259 View Article
  8. Kinney JW, Bemiller SM, Murtishaw AS, Leisgang AM, Salazar AM, Lamb BT. Inflammation as a central mechanism in Alzheimer’s disease. Alzheimers Dement 2018;4:575-590 View Article
  9. Markesbery WR. Oxidative stress hypothesis in Alzheimer’s disease. Free Radic Biol Med 1997;23(1):134-147 View Article
  10. Swerdlow RH. Mitochondria and mitochondrial cascades in Alzheimer’s disease. J Alzheimers Dis 2018;62(3):1403-1416 View Article
  11. Wang R, Reddy PH. Role of glutamate and NMDA receptors in Alzheimer’s disease. J Alzheimers Dis 2017;57(4):1041-1048 View Article
  12. Chen Y, Fu AKY, Ip NY. Synaptic dysfunction in Alzheimer’s disease: Mechanisms and therapeutic strategies. Pharmacol Ther 2019;195:186-198 View Article
  13. Bature F, Guinn BA, Pang D, Pappas Y. Signs and symptoms preceding the diagnosis of Alzheimer’s disease: a systematic scoping review of literature from 1937 to 2016. BMJ Open 2017;7(8):e015746 View Article
  14. Bayer AJ. The role of biomarkers and imaging in the clinical diagnosis of dementia. Age Ageing 2018;47(5):641-643 View Article
  15. Xu XH, Huang Y, Wang G, Chen SD. Metabolomics: a novel approach to identify potential diagnostic biomarkers and pathogenesis in Alzheimer’s disease. Neurosci Bull 2012;28(5):641-8 View Article
  16. Gremer L, Schölzel D, Schenk C, Reinartz E, Labahn J, Ravelli RBG, et al. Fibril structure of amyloid-ß(1-42) by cryo-electron microscopy. Science 2017;358(6359):116-119 View Article
  17. Uddin MS, Kabir MT, Rahman MS, Behl T, Jeandet P, Ashraf GM, et al. Revisiting the Amyloid Cascade Hypothesis: From Anti-Aβ Therapeutics to Auspicious New Ways for Alzheimer’s Disease. Int J Mol Sci 2020;21(16):5858 View Article
  18. Zhang H, Zheng Y. β Amyloid Hypothesis in Alzheimer’s Disease: Pathogenesis, Prevention, and Management. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 2019;41(5):702-708 View Article
  19. DeKosky ST, Scheff SW. Synapse loss in frontal cortex biopsies in Alzheimer’s disease: correlation with cognitive severity. Ann Neurol 1990;27(5):457-464 View Article
  20. Ittner LM, Ke YD, Delerue F, Bi M, Gladbach A, van Eersel J, et al. Dendritic Function of Tau Mediates Amyloid-β Toxicity in Alzheimer’s Disease Mouse Models. Cell 2010;142(3):387-397 View Article
  21. Ballatore C, Lee VMY, Trojanowski JQ. Tau-mediated neurodegeneration in Alzheimer’s disease and related disorders. Nat Rev Neurosci 2007;8(9):663-672 View Article
  22. Medina M, Avila J. The role of extracellular Tau in the spreading of neurofibrillary pathology. Front Cell Neurosci 2014;8:113 View Article
  23. Iba M, Guo JL, McBride JD, Zhang B, Trojanowski JQ, Lee VMY. Synthetic Tau Fibrils Mediate Transmission of Neurofibrillary Tangles in a Transgenic Mouse Model of Alzheimer’s-Like Tauopathy. J Neurosci 2013;33(3):1024-1037 View Article
  24. Reitz C, Mayeux R. Alzheimer disease: Epidemiology, Diagnostic Criteria, Risk Factors and Biomarkers. Biochem Pharmacol 2014;88(4):640-651 View Article
  25. Castellano JM, Kim J, Stewart FR, Jiang H, DeMattos RB, Patterson BW, et al. Human apoE isoforms differentially regulate brain amyloid-β peptide clearance. Sci Transl Med 2011;3(89):89ra57 View Article
  26. Weggen S, Beher D. Molecular consequences of amyloid precursor protein and presenilin mutations causing autosomal-dominant Alzheimer’s disease. Alzheimers Res Ther 2012;4(2):9 View Article
  27. Hirsch MS, Watkins J. A comprehensive review of biomarker use in the gynecologic tract including differential diagnoses and diagnostic pitfalls. Adv Anat Pathol 2020;27(3):164-192 View Article
  28. Tapiola T, Alafuzoff I, Herukka SK, Parkkinen L, Hartikainen P, Soininen H, et al. Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol 2009;66(3):382-389 View Article
  29. Fagan AM, Mintun MA, Mach RH, Lee SY, Dence CS, Shah AR, et al. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol 2006;59(3):512-519 View Article
  30. Andreasen N, Minthon L, Davidsson P, Vanmechelen E, Vanderstichele H, Winblad B, et al. Evaluation of CSF-tau and CSF-Abeta42 as diagnostic markers for Alzheimer disease in clinical practice. Arch Neurol 2001;58(3):373-379 View Article
  31. Ferreira D, Perestelo-Pérez L, Westman E, Wahlund LO, Sarría A, Serrano-Aguilar P. Meta-review of CSF core biomarkers in Alzheimer’s disease: The state of-the-art after the new revised diagnostic criteria. Front Aging Neurosci 2014;6:47 View Article
  32. Tarawneh R, D’Angelo G, Macy E, Xiong C, Carter D, Cairns NJ, et al. Visinin-like protein-1: diagnostic and prognostic biomarker in Alzheimer disease. Ann Neurol 2011;70(2):274-285 View Article
  33. Fagan AM, Roe CM, Xiong C, Mintun MA, Morris JC, Holtzman DM. Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. Arch Neurol 2007;64(3):343-349 View Article
  34. Mohapatra D, Jena S, Prusty SK, Sahu PK. Biomarkers of Alzheimer’s disease: A review. Sys Rev Pharm 2020;11(6):151-158 View Article
  35. Olsson B, Lautner R, Andreasson U, Öhrfelt A, Portelius E, Bjerke M, et al. CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: a systematic review and meta-analysis. Lancet Neurol 2016;15(7):673-684 View Article
  36. Andreasen N, Blennow K. β-Amyloid (Aβ) protein in cerebrospinal fluid as a biomarker for Alzheimer’s disease. Peptides 2002;23(7):1205-1214 View Article
  37. Motter R, Vigo-Pelfrey C, Kholodenko D, Barbour R, Johnson-Wood K, Galasko D, et al. Reduction of betaamyloid peptide42 in the cerebrospinal fluid of patients with Alzheimer’s disease. Ann Neurol 1995;38(4):643-648 View Article
  38. Seubert P, Vigo-Pelfrey C, Esch F, Lee M, Dovey H, Davis D, et al. Isolation and quantification of soluble Alzheimer’s beta-peptide from biological fluids. Nature 1992;359(6393):325-327 View Article
  39. Janelidze S, Zetterberg H, Mattsson N, Palmqvist S, Vanderstichele H, Lindberg O, et al. CSF Aβ42/Aβ40 and Aβ42/Aβ38 ratios: better diagnostic markers of Alzheimer disease. Ann Clin Transl Neurol 2016;3(3):154-165 View Article
  40. Wiltfang J, Esselmann H, Bibl M, Hüll M, Hampel H, Kessler H, et al. Amyloid beta peptide ratio 42/40 but not A beta 42 correlates with phospho-Tau in patients with low- and high-CSF A beta 40 load. J Neurochem 2007;101(4):1053-1059 View Article
  41. Gervaise-Henry C, Watfa G, Albuisson E, Kolodziej A, Dousset B, Olivier JL, et al. Cerebrospinal Fluid Aβ42/Aβ40 as a Means to Limiting Tube- and Storage-Dependent Pre-Analytical Variability in Clinical Setting. J Alzheimers Dis 2017;57(2):437-445 View Article
  42. Kennedy ME, Stamford AW, Chen X, Cox K, Cumming JN, Dockendorf MF, et al. The BACE1 inhibitor verubecestat (MK-8931) reduces CNS β-amyloid in animal models and in Alzheimer’s disease patients. Sci Transl Med 2016;8(363):363ra150 View Article
  43. Olsson F, Schmidt S, Althof V, Munter LM, Jin S, Rosqvist S, et al. Characterization of intermediate steps in amyloid beta (Aβ) production under near-native conditions. J Biol Chem 2014;289(3):1540-1550 View Article
  44. Grundke-Iqbal I, Iqbal K, Tung YC, Quinlan M, Wisniewski HM, Binder LI. Abnormal phosphorylation of the microtubule-associated protein tau (tau) in Alzheimer cytoskeletal pathology. PNAS 1986;83(13):4913-4917 View Article
  45. Meredith JE, Sankaranarayanan S, Guss V, Lanzetti AJ, Berisha F, Neely RJ, et al. Characterization of novel CSF Tau and ptau biomarkers for Alzheimer’s disease. PloS One 2013;8(10):e76523 View Article
  46. Bjerke M, Engelborghs S. Cerebrospinal fluid biomarkers for early and differential Alzheimer’s disease diagnosis. J Alzheimers Dis 2018;62(3):1199-1209 View Article
  47. Ittner LM, Götz J. Amyloid-β and tau-a toxic pas de deux in Alzheimer’s disease. Nat Rev Neurosci 2011;12(2):65-72 View Article
  48. Hampel H, Buerger K, Zinkowski R, Teipel SJ, Goernitz A, Andreasen N, et al. Measurement of phosphorylated tau epitopes in the differential diagnosis of Alzheimer disease: a comparative cerebrospinal fluid study. Arch Gen Psychiatry 2004;61(1):95-102 View Article
  49. Janelidze S, Stomrud E, Smith R, Palmqvist S, Mattsson N, Airey DC, et al. Cerebrospinal fluid p-tau217 performs better than p-tau181 as a biomarker of Alzheimer’s disease. Nat Commun 2020;11(1):1683 View Article
  50. Blennow K. CSF biomarkers for Alzheimer’s disease: use in early diagnosis and evaluation of drug treatment. Expert Rev Mol Diagn 2005;5(5):661-672 View Article
  51. Blennow K, Hampel H. CSF markers for incipient Alzheimer’s disease. Lancet Neurol 2003;2(10):605-613 View Article
  52. Humpel C. Identifying and validating biomarkers for Alzheimer’s disease. Trends Biotechnol 2011;29(1):26-32 View Article
  53. Sjogren M, Vanderstichele H, Agren H, Zachrisson O, Edsbagge M, Wikkelsø C, et al. Tau and Abeta42 in cerebrospinal fluid from healthy adults 21-93 years of age: establishment of reference values. Clin Chem 2001;47(10):1776-1781 View Article
  54. Blennow K. CSF biomarkers for mild cognitive impairment. J Intern Med 2004;256(3):224-234 View Article
  55. Vandermeeren M, Mercken M, Vanmechelen E, Six J, van de Voorde A, Martin JJ, et al. Detection of tau proteins in normal and Alzheimer’s disease cerebrospinal fluid with a sensitive sandwich enzyme-linked immunosorbent assay. J Neurochem 1993;61(5):1828-1834 View Article
  56. Vassar R, Bennett BD, Babu-Khan S, Kahn S, Mendiaz EA, Denis P, et al. Beta-secretase cleavage of Alzheimer’s amyloid precursor protein by the transmembrane aspartic protease BACE. Science 1999;286(5440):735-741 View Article
  57. Decourt B, Gonzales A, Beach TG, Malek-Ahmadi M, Walker A, Sue L, et al. BACE1 levels by APOE genotype in non-demented and Alzheimer’s post-mortem brains. Curr Alzheimer Res 2013;10(3):309-315 View Article
  58. Decourt B, Sabbagh MN. BACE1 as a potential biomarker for Alzheimer’s disease. J Alzheimers Dis 2011;24(Suppl 2):53-59 View Article
  59. Südhof TC, Malenka RC. Understanding synapses: past, present, and future. Neuron 2008;60(3):469-476 View Article
  60. Jones RA, Harrison C, Eaton SL, Llavero Hurtado M, Graham LC, Alkhammash L, et al. Cellular and Molecular Anatomy of the Human Neuromuscular Junction. Cell Rep 2017;21(9):2348-2356 View Article
  61. Masliah E, Mallory M, Alford M, DeTeresa R, Hansen LA, McKeel DW, et al. Altered expression of synaptic proteins occurs early during progression of Alzheimer’s disease. Neurology 2001;56(1):127-129 View Article
  62. Tarawneh R, D’Angelo G, Crimmins D, Herries E, Griest T, Fagan AM, et al. Diagnostic and Prognostic Utility of the Synaptic Marker Neurogranin in Alzheimer Disease. JAMA Neurol 2016;73(5):561-571 View Article
  63. Mattsson N, Insel PS, Palmqvist S, Portelius E, Zetterberg H, Weiner M, et al. Cerebrospinal fluid tau, neurogranin, and neurofilament light in Alzheimer’s disease. EMBO Mol Med 2016;8(10):1184-1196 View Article
  64. Schef SW, Price DA, Schmitt FA, Mufson EJ. Hippocampal synaptic loss in early Alzheimer’s disease and mild cognitive impairment. Neurobiol Aging 2006;27(10):1372-1384 View Article
  65. Terry RD, Masliah E, Salmon DP, Butters N, DeTeresa R, Hill R, et al. Physical basis of cognitive alterations in Alzheimer’s disease: synapse loss is the major correlate of cognitive impairment. Ann Neurol 1991;30(4):572-580 View Article
  66. Represa A, Deloulme JC, Sensenbrenner M, Ben-Ari Y, Baudier J. Neurogranin: immunocytochemical localization of a brain-specific protein kinase C substrate. J Neurosci 1990;10(12):3782-3792 View Article
  67. Torsell A, Bjerke M, Gobom J, Brunhage E, Vanmechelen E, Andreasen N, et al. Neurogranin in cerebrospinal fluid as a marker of synaptic degeneration in Alzheimer’s disease. Brain Res 2010;1362:13-22 View Article
  68. Wellington H, Paterson RW, Portelius E, Törnqvist U, Magdalinou N, Fox NC, et al. Increased CSF neurogranin concentration is specific to Alzheimer disease. Neurology 2016;86(9):829-835 View Article
  69. Antonucci F, Corradini I, Fossati G, Tomasoni R, Menna E, Matteoli M. SNAP-25, a known presynaptic protein with emerging postsynaptic functions. Front Synaptic Neurosci 2016;8:7 View Article
  70. Zhang H, Terriault J, Kang MS, Ng KP, Pascoal TA, Rosa-Neto P, et al. Cerebrospinal fluid synaptosomal-associated protein 25 is a key player in synaptic degeneration in mild cognitive impairment and Alzheimer’s disease. Alzheimers Res Ther 2018;10(1):80 View Article
  71. Brinkmalm A, Brinkmalm G, Honer WG, Frölich L, Hausner L, Minthon L, et al. SNAP-25 is a promising novel cerebrospinal fluid biomarker for synapse degeneration in Alzheimer’s disease. Mol Neurodegener 2014;9:53 View Article
  72. Bark IC, Wilson MC. Human cDNA clones encoding two different isoforms of the nerve terminal protein SNAP-25. Gene 1994;139(2):291-292 View Article
  73. Courtney NA, Bao H, Briguglio JS, Chapman ER. Synaptotagmin 1 clamps synaptic vesicle fusion in mammalian neurons independent of complexin. Nat Commun 2019;10(1):4076 View Article
  74. Öhrfelt A, Brinkmalm A, Dumurgier J, Brinkmalm G, Hansson O, Zetterberg H, et al. The pre-synaptic vesicle protein synaptotagmin is a novel biomarker for Alzheimer’s disease. Alzheimers Res Ther 2016;8(1):41 View Article
  75. Tible M, Sandelius Å, Höglund K, Brinkmalm A, Cognat E, Dumurgier J, et al. Dissection of synaptic pathways through the CSF biomarkers for predicting Alzheimer disease. Neurology 2020;95(8):e953-e961 View Article
  76. Rosskothen-Kuhl N, Illing RB. Gap43 transcription modulation in the adult brain depends on sensory activity and synaptic cooperation. PLoS One 2014;9(3):e92624 View Article
  77. Holahan MR. A shift from a pivotal to supporting role for the growth-associated protein (GAP-43) in the coordination of axonal structural and functional plasticity. Front Cell Neurosci 2017;11:266 View Article
  78. Sandelius Å, Portelius E, Källén Å, et al. Elevated CSF GAP-43 is Alzheimer’s disease specific and associated with tau and amyloid pathology. Alzheimers Dement 2019;15(1):55-64 View Article
  79. Hsu YC, Perin MS. Human neuronal pentraxin II (NPTX2): conservation, genomic structure, and chromosomal localization. Genomics 1996;28(2):220-227 View Article
  80. Abad MA, Enguita M, DeGregorio-Rocasolano N, Ferrer I, Trullas R. Neuronal pentraxin 1 contributes to the neuronal damage evoked by amyloid-β and is overexpressed in dystrophic neurites in Alzheimer’s brain. J Neurosci 2006;26(49):12735-12747 View Article
  81. Begcevic I, Tsolaki M, Brinc D, Brown M, Martinez-Morillo E, Lazarou I, et al. Neuronal pentraxin receptor-1 is a new cerebrospinal fluid biomarker of Alzheimer’s disease progression. F1000Res 2018;7:1012 View Article
  82. Khalil M, Teunissen CE, Otto M, Piehl F, Sormani MP, Gattringer T, et al. Neurofilaments as biomarkers in neurological disorders. Nat Rev Neurol 2018;14(10):577-589 View Article
  83. Zetterberg H, Skillbäck T, Mattsson N, Trojanowski JQ, Portelius E, Shaw LM, et al. Association of Cerebrospinal Fluid Neurofilament Light Concentration With Alzheimer Disease Progression. JAMA Neurol 2016;73(1):60-67 View Article
  84. Burgoyne RD. Neuronal calcium sensor proteins: generating diversity in neuronal Ca2+ signaling. Nat Rev Neurosci 2007;8(3):182-193 View Article
  85. Tarawneh R, Head D, Allison S, Buckles V, Fagan AM, Ladenson JH, et al. Cerebrospinal Fluid Markers of Neurodegeneration and Rates of Brain Atrophy in Early Alzheimer Disease. JAMA Neurol 2015;72(6):656-665 View Article
  86. Tarawneh R, Lee J-M, Ladenson JH, Morris JC, Holtzman DM. CSF VILIP-1 predicts rates of cognitive decline in early Alzheimer disease. Neurology 2012;78(10):709-719 View Article
  87. Marui N, Offermann MK, Swerlick R, Kunsch C, Rosen CA, Ahmad M, et al. Vascular cell adhesion molecule-1 (VCAM-1) gene transcription and expression are regulated through an antioxidant-sensitive mechanism in human vascular endothelial cells. J Clin Invest 1993;92(4):1866-1874 View Article
  88. Bui TM, Wiesolek HL, Sumagin R. ICAM-1: A master regulator of cellular responses in inflammation, injury resolution, and tumorigenesis. J Leukoc Biol 2020;108(3):787-799 View Article
  89. Guo Y, Luan L, Patil NK, Sherwood ER. Immunobiology of the IL-15/IL-15Rα complex as an antitumor and antiviral agent. Cytokine Growth Factor Rev 2017;38:10-21 View Article
  90. Maynard SE, Venkatesha S, Thadhani R, Karumanchi SA. Soluble Fms-like tyrosine kinase 1 and endothelial dysfunction in the pathogenesis of preeclampsia. Pediatr Res 2005;57(5 Pt 2):1R-7R View Article
  91. Janelidze S, Mattsson N, Stomrud E, Lindberg O, Palmqvist S, Zetterberg H, et al. CSF biomarkers of neuroinflammation and cerebrovascular dysfunction in early Alzheimer disease. Neurology 2018;91(9):e867-e877 View Article
  92. Ye XD, He Y, Wang S, Wong GT, Irwin MG, Xia Z. Heart-type fatty acid binding protein (H-FABP) as a biomarker for acute myocardial injury and long-term post-ischemic prognosis. Acta Pharmacol Sin 2018;39(7):1155-1163 View Article
  93. Iturria-Medina Y, Sotero RC, Toussaint PJ, Mateos-Pérez JM, Evans AC, Alzheimer’s Disease Neuroimaging Initiative. Early role of vascular dysregulation on late-onset Alzheimer’s disease based on multifactorial data-driven analysis. Nat Commun 2016;7(1):11934 View Article
  94. Leung YY, Toledo JB, Nefedov A, Polikar R, Raghavan N, Xie SX, et al. Identifying amyloid pathology-related cerebrospinal fluid biomarkers for Alzheimer’s disease in a multicohort study. Alzheimers Dement (Amst) 2015;1(3):339-348 View Article
  95. Desikan RS, Tompson WK, Holland D, Hess CP, Brewer JB, Zetterberg H, et al. Heart fatty acid binding protein and Aβ-associated Alzheimer’s neurodegeneration. Mol Neurodegener 2013;8:39 View Article
  96. Rogers J, Luber-Narod J, Styren SD, Civin WH. Expression of immune system-associated antigens by cells of the human central nervous system: relationship to the pathology of Alzheimer’s disease. Neurobiol Aging 1988;9:339-349 View Article
  97. Hickman SE, Allison EK, El Khoury J. Microglial dysfunction and defective beta-amyloid clearance pathways in aging Alzheimer’s disease mice. J Neurosci 2008;28(33):8354-8360 View Article
  98. Meda L, Cassatella MA, Szendrei GI, Otvos L, Baron P, Villalba M, et al. Activation of microglial cells by beta-amyloid protein and interferon-gamma. Nature 1995;374(6523):647-650 View Article
  99. Chu WM. Tumor necrosis factor. Cancer Lett 2013;328(2):222-225 View Article
  100. Jiang H, Hampel H, Prvulovic D, Wallin A, Blennow K, Li R, et al. Elevated CSF levels of TACE activity and soluble TNF receptors in subjects with mild cognitive impairment and patients with Alzheimer’s disease. Mol Neurodegener 2011;6:69 View Article
  101. Tarkowski E, Andreasen N, Tarkowski A, Blennow K. Intrathecal inflammation precedes development of Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2003;74(9):1200-1205 View Article
  102. Kurisu K, Zheng Z, Kim JY, Shi J, Kanoke A, Liu J, et al. Triggering receptor expressed on myeloid cells-2 expression in the brain is required for maximal phagocytic activity and improved neurological outcomes following experimental stroke. J Cereb Blood Flow Metab 2019;39(10):1906-1918 View Article
  103. Llorens F, Thüne K, Tahir W, Kanata E, Diaz-Lucena D, Xanthopoulos K, et al. YKL-40 in the brain and cerebrospinal fluid of neurodegenerative dementias. Mol Neurodegener 2017;12(1):83 View Article
  104. Baldacci F, Toschi N, Lista S, Zetterberg H, Blennow K, Kilimann I, et al. Two-level diagnostic classification using cerebrospinal fluid YKL-40 in Alzheimer’s disease. Alzheimers Dement 2017;13(9):993-1003 View Article
  105. Gispert JD, Monté GC, Suárez-Calvet M, Falcon C, Tucholka A, Rojas S, et al. The APOE ε4 genotype modulates CSF YKL-40 levels and their structural brain correlates in the continuum of Alzheimer’s disease but not those of sTREM2. Alzheimers Dement (Amst) 2016;6:50-59 View Article
  106. Baldacci F, Lista S, Cavedo E, Bonuccelli U, Hampel H. Diagnostic function of the neuroinflammatory biomarker YKL-40 in Alzheimer’s disease and other neurodegenerative diseases. Expert Rev Proteomics 2017;14(4):285-299 View Article
  107. Eng LF. Glial fibrillary acidic protein (GFAP): the major protein of glial intermediate filaments in differentiated astrocytes. J Neuroimmunol 1985;8(4-6):203-214 View Article
  108. Ishiki A, Kamada M, Kawamura Y, Terao C, Shimoda F, Tomita N, et al. Glial fibrillar acidic protein in the cerebrospinal fluid of Alzheimer’s disease, dementia with Lewy bodies, and frontotemporal lobar degeneration. J Neurochem 2016;136(2):258-261 View Article
  109. Astrand R, Undén J. Clinical Use of the Calcium-Binding S100B Protein, a Biomarker for Head Injury. Methods Mol Biol 2019;1929:679-690 View Article
  110. Christl J, Verhülsdonk S, Pessanha F, Menge T, Seitz RJ, Kujovic M, et al. Association of Cerebrospinal Fluid S100B Protein with Core Biomarkers and Cognitive Deficits in Prodromal and Mild Alzheimer’s Disease. J Alzheimers Dis 2019;72(4):1119-1127 View Article
  111. Blennow K, Zetterberg H. Understanding biomarkers of neurodegeneration: Ultrasensitive detection techniques pave the way for mechanistic understanding. Nat Med 2015;21(3):217-219 View Article
  112. Shin HS, Lee SK, Kim S, Kim HJ, Chae WS, Park SA. The Correlation Study between Plasma Aβ Proteins and Cerebrospinal Fluid Alzheimer’s Disease Biomarkers. Dement Neurocogn Disord 2016;15(4):122-128 View Article
  113. Hansson O, Zetterberg H, Vanmechelen E, Vanderstichele H, Andreasson U, Londos E, et al. Evaluation of plasma Abeta(40) and Abeta(42) as predictors of conversion to Alzheimer’s disease in patients with mild cognitive impairment. Neurobiol Aging 2010;31(3):357-367 View Article
  114. Seppala TT, Herukka S-K, Hanninen T, Tervo S, Hallikainen M, Soininen H, et al. Plasma A 42 and A 40 as markers of cognitive change in follow-up: a prospective, longitudinal, population-based cohort study. J Neurol Neurosurg Psychiatry 2010;81(10):1123-1127 View Article
  115. Gu L, Guo Z. Alzheimer’s Aβ42 and Aβ40 peptides form interlaced amyloid fibrils. J Neurochem 2013;126(3):305-311 View Article
  116. Zetterberg H, Mörtberg E, Song L, Chang L, Provuncher GK, Patel PP, et al. Hypoxia Due to Cardiac Arrest Induces a Time-Dependent Increase in Serum Amyloid β Levels in Humans. PLoS One 2011;6(12):e28263 View Article
  117. Nakamura A, Kaneko N, Villemagne VL, Kato T, Doecke J, Doré V, et al. High performance plasma amyloid-β biomarkers for Alzheimer’s disease. Nature 2018;554(7691):249-254 View Article
  118. Schindler SE, Bollinger JG, Ovod V, Mawuenyega KG, Li Y, Gordon BA, et al. High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis. Neurology 2019;93(17):e1647-e1659 View Article
  119. Verberk IMW, Hendriksen HMA, van Harten AC, Wesselman LMP, Verfaillie SCJ, van den Bosch KA, et al. Plasma amyloid is associated with the rate of cognitive decline in cognitively normal elderly: the SCIENCe project. Neurobiol Aging 2020;89:99-107 View Article
  120. Verberk IMW, Slot RE, Verfaillie SCJ, Heijst H, Prins ND, van Berckel BNM, et al. Plasma Amyloid as Prescreener for the Earliest Alzheimer Pathological Changes. Ann Neurol 2018;84(5):648-658 View Article
  121. Stockmann J, Verberk IMW, Timmesfeld N, Denz R, Budde B, Lange-Leifhelm J, et al. Amyloid-β misfolding as a plasma biomarker indicates risk for future clinical Alzheimer’s disease in individuals with subjective cognitive decline. Alzheimers Res Ther 2020;12(1):169 View Article
  122. Lantero Rodriguez J, Karikari TK, Suárez-Calvet M, Troakes C, King A, Emersic A, et al. Plasma p-tau181 accurately predicts Alzheimer’s disease pathology at least 8 years prior to post-mortem and improves the clinical characterisation of cognitive decline. Acta Neuropathol 2020;140(3):267-278 View Article
  123. Tatebe H, Kasai T, Ohmichi T, Kishi Y, Kakeya T, Waragai M, et al. Quantification of plasma phosphorylated tau to use as a biomarker for brain Alzheimer pathology: pilot case-control studies including patients with Alzheimer’s disease and down syndrome. Mol Neurodegener 2017;12(1):63 View Article
  124. Janelidze S, Mattsson N, Palmqvist S, Smith R, Beach TG, Serrano GE, et al. Plasma P-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia. Nat Med 2020;26(3):379-386 View Article
  125. Palmqvist S, Janelidze S, Quiroz YT, Zetterberg H, Lopera F, Stomrud E, et al. Discriminative Accuracy of Plasma Phospho-tau217 for Alzheimer Disease vs Other Neurodegenerative Disorders. JAMA 2020;324(8):772-781 View Article
  126. Mattsson N, Andreasson U, Zetterberg H, Blennow K. Association of Plasma Neurofilament Light With Neurodegeneration in Patients With Alzheimer Disease. JAMA Neurol 2017;74(5):557-566 View Article
  127. Preische O, Schultz SA, Apel A, Kuhle J, Kaeser SA, Barro C, et al. Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease. Nat Med 2019;25(2):277-283 View Article
  128. Italiani P, Puxeddu I, Napoletano S, Scala E, Melillo D, Manocchio S, et al. Circulating levels of IL-1 family cytokines and receptors in Alzheimer’s disease: new markers of disease progression?. J Neuroinflammation 2018;15(1):342 View Article
  129. Lai KSP, Liu CS, Rau A, Lanctôt KL, Köhler CA, Pakosh M, et al. Peripheral inflammatory markers in Alzheimer’s disease: a systematic review and meta-analysis of 175 studies. J Neurol Neurosurg Psychiatry 2017;88(10):876-882 View Article
  130. Gate D, Saligrama N, Leventhal O, Yang AC, Unger MS, Middeldorp J, et al. Clonally expanded CD8 T cells patrol the cerebrospinal fluid in Alzheimer’s disease. Nature 2020;577(7790):399-404 View Article
  131. Tan J, Town T, Abdullah L, Wu Y, Placzek A, Small B, et al. CD45 isoform alteration in CD4+ T cells as a potential diagnostic marker of Alzheimer’s disease. J Neuroimmunol 2002;132(1–2):164-172 View Article
  132. Rezai-Zadeh K, Gate D, Szekely CA, Town T. Can peripheral leukocytes be used as Alzheimer’s disease biomarkers?. Expert Rev Neurother 2009;9(11):1623-1633 View Article
  133. Ewers M, Mielke MM, Hampel H. Blood-based Biomarkers of Microvascular Pathology in Alzheimer’s disease. Exp Gerontol 2010;45(1):75-79 View Article
  134. Kalaria RN, Ballard C. Overlap between pathology of Alzheimer disease and vascular dementia. Alzheimer Dis Assoc Disord 1999;13(Suppl 3):S115-123 View Article
  135. Zuliani G, Cavalieri M, Galvani M, Passaro A, Munari MR, Bosi C, et al. Markers of endothelial dysfunction in older subjects with late onset Alzheimer’s disease or vascular dementia. J Neurol Sci 2008;272(1–2):164-170 View Article
  136. Buerger K, Ernst A, Ewers M, Uspenskaya O, Omerovic M, Morgenthaler NG, et al. Blood-based microcirculation markers in Alzheimer’s disease-diagnostic value of midregional pro-atrial natriuretic peptide/C-terminal endothelin-1 precursor fragment ratio. Biol Psychiatry 2009;65(11):979-984 View Article
  137. Buerger K, Uspenskaya O, Hartmann O, Hansson O, Minthon L, Blennow K, et al. Prediction of Alzheimer’s disease using midregional proadrenomedullin and midregional proatrial natriuretic peptide: a retrospective analysis of 134 patients with mild cognitive impairment. J Clin Psychiatry 2011;72(4):556-563 View Article
  138. Arai T, Hasegawa M, Akiyama H, Ikeda K, Nonaka T, Mori H, et al. TDP-43 is a component of ubiquitin-positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Biochem Biophys Res Commun 2006;351(3):602-611 View Article
  139. Wilson AC, Dugger BN, Dickson DW, Wang DS. TDP-43 in aging and Alzheimer’s disease - a review. Int J Clin Exp Pathol 2011;4(2):147-155
  140. Huang W, Zhou Y, Tu L, Ba Z, Huang J, Huang N, et al. TDP-43: From Alzheimer’s Disease to Limbic-Predominant Age-Related TDP-43 Encephalopathy. Front Mol Neurosci 2020;13:26 View Article
  141. Foulds P, McAuley E, Gibbons L, Davidson Y, Pickering-Brown SM, Neary D, et al. TDP-43 protein in plasma may index TDP-43 brain pathology in Alzheimer’s disease and frontotemporal lobar degeneration. Acta Neuropathol 2008;116(2):141-146 View Article
  142. Tomé SO, Vandenberghe R, Ospitalieri S, Van Schoor E, Tousseyn T, Otto M, et al. Distinct molecular patterns of TDP-43 pathology in Alzheimer’s disease: relationship with clinical phenotypes. Acta Neuropathol Commun 2020;8(1):61 View Article
  143. Williams SM, Schulz P, Rosenberry TL, Caselli RJ, Sierks MR. Blood-Based Oligomeric and Other Protein Variant Biomarkers to Facilitate Pre-Symptomatic Diagnosis and Staging of Alzheimer’s Disease. J Alzheimers Dis 2017;58(1):23-35 View Article
  144. Snowden SG, Ebshiana AA, Hye A, An Y, Pletnikova O, O’Brien R, et al. Association between fatty acid metabolism in the brain and Alzheimer disease neuropathology and cognitive performance: A nontargeted metabolomic study. PLoS Med 2017;14(3):e1002266 View Article
  145. Tynkkynen J, Chouraki V, van der Lee SJ, Hernesniemi J, Yang Q, Li S, et al. Association of branched-chain amino acids and other circulating metabolites with risk of incident dementia and Alzheimer’s disease: A prospective study in eight cohorts. Alzheimers Dement 2018;14(6):723-733 View Article
  146. Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat Med 2014;20(4):415-418 View Article
  147. Cunnane SC, Schneider JA, Tangney C, Tremblay-Mercier J, Fortier M, Bennett DA, et al. Plasma and Brain Fatty Acid Profiles in Mild Cognitive Impairment and Alzheimer’s Disease. J Alzheimers Dis 2012;29(3):691-697 View Article
  148. Astarita G, Jung K-M, Berchtold NC, Nguyen VQ, Gillen DL, Head E, et al. Deficient Liver Biosynthesis of Docosahexaenoic Acid Correlates with Cognitive Impairment in Alzheimer’s Disease. PLoS One 2010;5(9):e12538 View Article
  149. Swanson D, Block R, Mousa SA. Omega-3 Fatty Acids EPA and DHA: Health Benefits Throughout Life1. Adv Nutr 2012;3(1):1-7 View Article
  150. Nho K, Kueider-Paisley A, MahmoudianDehkordi S, Arnold M, Risacher SL, Louie G, et al. Altered Bile Acid Profile in Mild Cognitive Impairment and Alzheimer’s Disease: Relationship to Neuroimaging and CSF Biomarkers. Alzheimers Dement 2019;15(2):232-244 View Article
  151. Cristofano A, Sapere N, La Marca G, Angiolillo A, Vitale M, Corbi G, et al. Serum Levels of Acyl-Carnitines along the Continuum from Normal to Alzheimer’s Dementia. PLoS One 2016;11(5):e0155694 View Article
  152. Stempler S, Yizhak K, Ruppin E. Integrating Transcriptomics with Metabolic Modeling Predicts Biomarkers and Drug Targets for Alzheimer’s Disease. PLoS One 2014;9(8):e105383 View Article
  153. Adachi Y, Shimodaira Y, Nakamura H, Imaizumi A, Mori M, Kageyama Y, et al. Low plasma tryptophan is associated with olfactory function in healthy elderly community dwellers in Japan. BMC Geriatr 2017;17(1):239 View Article
  154. Roberts KB. Essentials of Human Physiology. Can Med Assoc J 1979;121(3):335-336
  155. Giubilei F, Patacchioli FR, Antonini G, Monti MS, Tisei P, Bastianello S, et al. Altered circadian cortisol secretion in Alzheimer’s disease: clinical and neuroradiological aspects. J Neurosci Res 2001;66(2):262-265 View Article
  156. Sinclair RD. Healthy hair: what is it?. J Investig Dermatol Symp Proc 2007;12(2):2-5 View Article
  157. Koseoglu E, Koseoglu R, Kendirci M, Saraymen R, Saraymen B. Trace metal concentrations in hair and nails for Alzheimer’s disease patients with clinical severity. J Trace Elem Med Bio 2017;39:124-128 View Article
  158. de Berker D. Nail anatomy. Clin Dermatol 2013;31(5):509-515 View Article
  159. Lovell MA. A potential role for alterations of zinc and zinc transport proteins in the progression of Alzheimer’s disease. J Alzheimers Dis 2009;16(3):471-483 View Article
  160. de Souza-Pinto NC, Eide L, Hogue BA, Thybo T, Stevnsner T, Seeberg E, et al. Repair of 8-oxodeoxyguanosine lesions in mitochondrial dna depends on the oxoguanine dna glycosylase (OGG1) gene and 8-oxoguanine accumulates in the mitochondrial dna of OGG1-defective mice. Cancer Res 2001;61(14):5378-5381
  161. Zengi O, Karakas A, Ergun U, Senes M, Inan L, Yucel D. Urinary 8-hydroxy-2′-deoxyguanosine level and plasma paraoxonase 1 activity with Alzheimer’s disease. Clin Chem Lab Med 2011;50(3):529-534 View Article
  162. Montuschi P, Barnes PJ, Roberts LJ. Isoprostanes: markers and mediators of oxidative stress. FASEB J 2004;18(15):1791-1800 View Article
  163. Tang Z, Liu L, Li Y, Dong J, Li M, Huang J, et al. Urinary Metabolomics Reveals Alterations of Aromatic Amino Acid Metabolism of Alzheimer’s Disease in the Transgenic CRND8 Mice. Curr Alzheimer Res 2016;13(7):764-776 View Article
  164. Socha E, Koba M, Kośliński P. Amino acid profiling as a method of discovering biomarkers for diagnosis of neurodegenerative diseases. Amino Acids 2019;51(3):367-371 View Article
  165. Molinuevo JL, Ayton S, Batrla R, Bednar MM, Bittner T, Cummings J, et al. Current state of Alzheimer’s fluid biomarkers. Acta Neuropathol 2018;136(6):821-853 View Article
  166. Ward RJ, Zucca FA, Duyn JH, Crichton RR, Zecca L. The role of iron in brain ageing and neurodegenerative disorders. Lancet Neurol 2014;13(10):1045-1060 View Article
  167. Loeffler DA, Connor JR, Juneau PL, Snyder BS, Kanaley L, DeMaggio AJ, et al. Transferrin and iron in normal, Alzheimer’s disease, and Parkinson’s disease brain regions. J Neurochem 1995;65(2):710-724 View Article
  168. van Bergen JM, Li X, Hua J, Schreiner SJ, Steininger SC, Quevenco FC, et al. Colocalization of cerebral iron with Amyloid beta in Mild Cognitive Impairment. Sci Rep 2016;6:35514 View Article
  169. Cristóvão JS, Santos R, Gomes CM. Metals and Neuronal Metal Binding Proteins Implicated in Alzheimer’s Disease. Oxid Med Cell Longev 2016;2016:9812178 View Article
  170. Ayton S, Fazlollahi A, Bourgeat P, Raniga P, Ng A, Lim YY, et al. Cerebral quantitative susceptibility mapping predicts amyloid-β-related cognitive decline. Brain 2017;140(8):2112-2119 View Article
  171. Ayton S, Faux NG, Bush AI, Alzheimer’s Disease Neuroimaging Initiative. Ferritin levels in the cerebrospinal fluid predict Alzheimer’s disease outcomes and are regulated by APOE. Nat Commun 2015;6:6760 View Article
  172. Ferretti MT, Iulita MF, Cavedo E, Chiesa PA, Schumacher Dimech A, Santuccione Chadha A, et al. Sex differences in Alzheimer disease - the gateway to precision medicine. Nat Rev Neurol 2018;14(8):457-469 View Article
  173. Hampel H, O’Bryant SE, Castrillo JI, Ritchie C, Rojkova K, Broich K, et al. PRECISION MEDICINE—the Golden Gate for detection, treatment and prevention of Alzheimer’s disease. J Prev Alzheimers Dis 2016;3(4):243-259 View Article
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Biomarkers and Their Implications in Alzheimer’s Disease: A Literature Review

Vincent Marcucci, Jeremy Kleiman
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