Current perspectives on Alzheimer’s disease fluid biomarkers and future challenges: a narrative review

Introduction

Alzheimer’s disease (AD), first described by neuropathologist Alois Alzheimer and neurologist Gaetano Perusini in 1907, is the most common age-related dementia and is characterized by progressive memory loss and deterioration of cognitive function (1). AD has an estimated prevalence of 10–30% in the population older than 65 years with an incidence of 1–3% and is higher in women (2); aging is the major risk factor.

Most cases of AD (>95%) are sporadic, characterized by late onset and long preclinical and prodromal phases, but there are some forms of familial AD (<5%) in which symptoms develop earlier (typically between 30–50 years of age). The known forms of autosomal-dominant familial AD involve mutations in 3 genes: amyloid precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2) (3). Sporadic late-onset AD is likely determined by a complex interaction between genetic and environmental factors. In particular, the presence of the apolipoprotein E (APOE) ε4 allele is the major genetic risk factor for late-onset AD, dose-dependently increasing the risk and lowering the mean age of onset from 84 to 68 years old (4). Although this is the most relevant genetic risk factor, genomics studies have identified many other factors involved in inflammatory pathways, cholesterol metabolism, and endosomal vesicle recycling (5). There are many hypotheses about the pathogenetic mechanisms underlying the disease, but the most accepted one is based on the relentless extracellular deposition of β-amyloid (Aβ) plaques and the presence of intracellular neurofibrillary tangles of hyperphosphorylated tau protein (NFTs) (6). These processes progressively lead to neurodegeneration and atrophy of the brain, which are the immediate cause of cognitive decline and clinical progression (7). According to Hardy and Higgins’ amyloid-cascade hypothesis (6), Aβ deposition in the brain is the predominant driving force behind the pathogenesis of AD: accumulation and oligomerization of Ab42 peptides in the limbic and associative cortex, with subsequent involvement of microglia and astrocytes and immune response, appear to lead to activation of kinases that hyperphosphorylate microtubule-associated tau protein, resulting in NFTs formation, causing instability, synaptic dysfunction, neuronal loss, and eventually AD dementia (8).

Nevertheless, while Aβ plaques may be present as early as 20 years before cognitive impairment occurs and their prevalence in cognitively unimpaired subjects over 70 years old is higher than 30% (9), the occurrence of tauopathy has been demonstrated to correlate with the onset of cognitive symptoms and neurodegeneration more closely, both spatially and temporally (10-12). The loss of neurons and synapses typically parallels the formation of NFTs, so the clinical features and severity of AD are indeed more associated with tau pathology, while Aβ pathology deposition slows towards a plateau in the symptomatic phase of the disease (5). Moreover, while an abnormal Amyloid positron emission tomography (PET) may be compatible in cognitively unimpaired individuals, a highly abnormal tau PET is not (13). These findings support a dynamic biomarker model, in which Aβ plaques promote, by achieving some amount in the brain parenchyma, the spread of NFTs, with tauopathy being more associated with clinical progression. However, beta amyloid deposition is not the exclusive pathway leading to the formation of NFTs, and this mechanism is not yet fully known.

The objectives of this review are to provide a comprehensive overview of the progression of fluid biomarkers for AD, exploring the state of current biomarkers while underscoring the potential significance of novel fully automated, high-throughput plasma biomarker assays and emerging neuroinflammation biomarkers. We present this article in accordance with the Narrative Review reporting checklist (available at https://jlpm.amegroups.org/article/view/10.21037/jlpm-24-1/rc).

Methods

A thorough investigation was conducted utilizing the electronic scientific databases PubMed and Web of Science, using search terms such as “Alzheimer’s disease”, “neuroinflammation”, and “biomarkers”, and manually searching the reference lists of identified articles to identify other pertinent papers. The focus was primarily on publications from the last five years, with a preference for systematic reviews and meta-analyses. However, commonly referenced and highly regarded older publications were also included to ensure a comprehensive review. Papers not published in English and abstract-only articles were excluded. Information used to write this paper was collected from the sources listed in Table 1.

AD as a biological construct

The first diagnostic criteria for AD were introduced in 1984 by the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA). These were clinical exclusion criteria for “probable AD” in the dementia stage whereby the diagnosis of “definite AD” could only be made after death and autopsy examination (14). With a sensitivity of about 81% and specificity of about 70% (15), the accuracy of the clinical diagnosis of probable AD in predicting the presence of Aβ and NFTs was far from ideal.

In the 1990s, the early clinical stages of AD gained increasing attention and the concept of mild cognitive impairment (MCI) was introduced, which refers to the transitional state between normal aging and dementia represented by a cognitive impairment that, despite being beyond what should be normal for the age of the subjects, does not impact on the activities of daily living (16). The research interest was therefore moved towards the characterization of prodromal and preclinical phases of AD. Greater knowledge of the disease and scientific progress have made possible over the following decades the use of a number of instrumental methods to aid clinical evaluation, such as magnetic resonance imaging (MRI), PET with tracers for amyloid (amyloid PET), p-tau (TAU PET) or glucose metabolism (FDG-PET) (17,18). These methods allowed to investigate the association between brain amyloid and tau burden in AD and between regional brain glucose metabolism and cognition (19). Assessing the pathological progression of AD by evaluating its pathological processes in vivo was further made possible by the introduction of validated cerebrospinal fluid (CSF) measures of Aβ and phosphorylated tau protein.

Jack et al. in 2010 proposed a hypothetical model suggesting specific associations between clinical stages of AD and changes in specific biomarkers (20). These were accorded a key role in the diagnosis of AD, and were therefore incorporated into the criteria developed by the International Working Group (IWG) (21) and the National Institute on Aging and the Alzheimer’s Association Working Group (NIA-AA) criteria (22), which substantially retained the concept of AD as a clinicopathologic entity, using the presence of abnormal biomarkers to define the probability of the clinicopathologic link. Particularly in the latter criteria, a special interest was given to the diagnosis of subjects with prodromal and preclinical AD, delineating what has been defined as the “AD continuum”. The progression of AD, from brain changes that are imperceptible to the affected individual to brain dysfunctions that cause memory impairment and progressive disability, would thus be divided into three stages: preclinical AD, MCI due to AD and dementia due to AD (23).

After reviewing and updating the IWG criteria in 2014 (24), Jack and colleagues proposed the “A/T/N” (amyloid, tau, neurodegeneration) classification in 2016 (25), whereby each individual is assessed for presence of amyloid (CSF Aβ42 or Aβ42/Aβ40 ratio, or amyloid PET=“A”), hyperphosphorylated tau protein (CSF p-tau or tau PET=“T”) and neurodegeneration (MRI, FDG-PET or CSF t-tau =“N”) (26).

Although every biomarker exists on a continuous scale, each of them can be rated as positive or negative to facilitate the diagnostic categorization of individuals (e.g., A+/T+/N− or A−/T−/N− etc.). The ATN classification, therefore, represented the groundwork for the drafting of the new 2018 NIA-AA criteria, which shifted the focus from a clinical-biological diagnosis to a purely biological definition of the disease, considering AD “as a biological construct defined by neuropathological processes that can be documented by post-mortem examination or in vivo by biomarkers”, regardless of clinical characterization (7).

However, Jack and colleagues reiterate the purely research intent of these new criteria and the lack of applicability to routine clinical practice. In the last recommendations from the IWG in 2021 the main concerns and limitations of the NIA-AA criteria were addressed, such as: the difficulty in managing the treatment of patients with positive biomarkers without cognitive impairment and the problems due to the use of a binary system when it would be more practical to consider biomarkers as continuous variables (27).

Despite these limitations, the purely biological definition of the disease has been a major step forward in understanding the underlying neurobiological mechanisms and has proven crucial in identifying defined targets of patients for testing potential therapies to modify the disease course.

Core CSF biomarkers of AD

In late-onset AD, the severity of symptoms varies from patient to patient and the clinical picture overlaps with that of other dementias. This heterogeneity in symptomatology causes quite a few difficulties in the diagnosis of AD. CSF biomarkers represent a well-established tool for diagnosing AD: they reflect the key processes of AD providing important information at the diagnostic level, even in the early stages of the disease (28). CSF compared to blood is an optimal matrix as it is close to the brain parenchyma and is accessible by spinal tap, which is a lumbar puncture at the L2–L3 and L3–L4 levels (29). However, for possible applications in screening and longitudinal assessments of patients over time, serum or plasma biomarkers would be preferable. The past 20 years have seen a tremendous expansion of research on fluid biomarkers of AD. T-tau, p-tau, Ab42 and the Ab42/40 ratio have been evaluated in hundreds of neurochemical clinical trials with remarkably consistent results, demonstrating high diagnostic accuracy not only for AD dementia but also for prodromal AD (30). The enzyme-linked immunosorbent assay (ELISA) is the most widely used laboratory method for the detection of core biomarkers of AD in CSF. In 1993, the first ELISA test for tau in CSF consisting of a combination of monoclonal and polyclonal anti-tau antibodies in sandwich assay was born. Two years later, INNOTEST ELISA assays based only on monoclonal antibodies are introduced for the identification of total-tau, Aβ42 and phospho-tau (p-tau) in CSF (28). However, this traditional manual method often shows considerable inter- and intra-laboratory variability that precludes the use of standard cut-off values and the wide use of CSF biomarkers in clinical practice. For this purpose, Fujirebio Diagnostics and Roche Diagnostics have developed two different instrumental platforms for CSF biomarker analysis, both approved for clinical use. Roche uses fully automated immunoassays for the determination of CSF Aβ42, t-tau, and p-tau181 on Elecsys and Cobas analyzers, and the measurement is based on the change in electrochemiluminescence in a two-step sandwich assay (ECLIA) (31). Fujirebio implemented four analytes in CSF (Aβ42, Aβ40, t-tau, and p-tau181) on the Lumipulse G system. The measurement is based on a two-step chemiluminescence sandwich method (chemiluminescent enzyme-immunoassay, CLEIA) (32). These biomarkers have undergone a standardization phase, and new versions of the tests on fully automated instruments show excellent analytical performance and low intra- and inter-laboratory variation (33).

Beta-amyloid

Amyloid pathogenesis begins with altered cleavage of the APP by three major proteases α-, β-, and γ-secretases that are involved in the process through two different pathways (34) leading to different products with distinct intrinsic functional properties and pathophysiological implications (35). There are two major isoforms of Aβ: Aβ40 and Aβ42. Aβ40 does not cause pathological accumulation of amyloid, and it is subject to greater recycling. Aβ42, on the other hand, is the most dangerous and neurotoxic form, because of hydrophobic properties and increased rate of fibrillation it is responsible for the formation of senile plaques (SPs), a hallmark feature of AD. Aβ42 accumulates early in plaques and is sequestered from them, resulting in a decrease in the CSF of AD patients. The assay of this molecule shows some preanalytical difficulties compared with the more abundant Aβ40; the use of polypropylene tubes for CSF storage after lumbar puncture is essential to avoid false decrements of Aβ42, which can adsorb onto some materials because of its marked hydrophobicity (36). Several works have demonstrated the superiority of the Aβ42/Aβ40 ratio in identifying AD patients compared with Aβ42 as a single biomarker: Aβ42/Aβ40 ratio improves the accuracy of the Aβ42 assay, normalizes excessive increases in Aβ40, and correlates positively with PET status (37).

P-tau

Tau is a microtubule-associated protein normally located in the axon, where it physiologically facilitates axonal transport. Six different isoforms of tau, produced by alternative splicing from the microtubule-associated protein tau (MAPT) gene, are expressed in the adult human brain, each of which contains 3 (3R) or 4 (4R) repeated microtubule-binding domains (38). The tau protein undergoes a complex series of post-translational modifications of which phosphorylation is the most common (39). Therefore, it is possible that changes in protein kinase and/or phosphatase activities may increase tau phosphorylation on serine and threonine residues by mechanisms that are not fully known. Hyperphosphorylation and subsequent sequestration and aggregation of p-tau protein in insoluble NFTs reduce tau binding to microtubules causing instability and reduced axonal transport, consequently contributing to neuropathology (40).

NFTs can also occur, albeit rarely, in the absence of widespread amyloidopathy. An example of this is primary age-related tauopathy (PART), characterized by aggregated tau deposits in the medial temporal lobe, basal forebrain, brainstem, and olfactory areas, without Aβ plaques (41,42).

While methods assaying p-tau 181, p-tau 199, and p-tau 231 (hyperphosphorylated on different threonine residues) in CSF have similar performance in discriminating AD from other dementias and from controls (43), p-tau 217 in blood has shown higher performance compared with p-tau 181 and p-tau 231 (44). Levels of p-tau in CSF do not change in acute neuronal damage and remain almost unchanged during neurodegenerative diseases other than NFTs; in AD they are greatly increased even in early stages, before PET can identify fibrils, which is why p-tau is considered a biomarker of disease state. In contrast, tau PET is a biomarker of “disease stage” since it correlates with the stage of brain atrophy and the severity of cognitive deficits (28). Plasma p-tau is the leading blood biomarker candidate, and its increase is associated not only with extracellular Aβ plaque deposition in the asymptomatic phase of both sporadic and genetic forms of AD, but also with worsening brain atrophy and declining cognitive performance in individuals with elevated Aβ pathology (45).

Neurodegeneration: total-tau and neurofilament light chain (NfL)

The main neurodegeneration biomarker considered in the ATN system was CSF total tau (t-tau). A marked increase in t-tau in CSF is found in AD dementia patients such that it was proposed as a “state marker”, reflecting the intensity of neurodegeneration or the severity of neuronal damage (28). Total-tau levels increase in the days following acute injury and remain elevated for weeks until normalization. In chronic neurodegenerative disorders, the highest levels of t-tau in CSF are found in disorders with the most intense neurodegeneration, particularly in Creutzfeldt-Jakob disease, where levels are 10 to 20 times higher than in AD. So, t-tau is not specific to AD, but is considered a biomarker of the intensity of neurodegeneration. On the other hand, its increase alongside p-tau in AD is thought to be a direct response to Aβ pathology, reflecting Aβ-dependent neurodegeneration (46-48).

The concentration of NfL in CSF and/or plasma is now being considered as a more promising biomarker of neuroaxonal injury potentially preferable to total t-tau as an index of neurodegeneration (N) (49). NfL and t-tau levels reflect distinct pathophysiological mechanisms of neurodegeneration (independent and dependent on Aβ pathology, respectively) therefore are not interchangeable, but their combination shows high accuracy in distinguishing MCI due to AD from frontotemporal dementia (FTD) (46). Neurofilaments are intermediate filaments (IFs) expressed in neurons and are particularly abundant in myelinated axons, to which they confer structural stability by allowing radial growth and thus modulating nerve conduction velocity (50). In case of axonal damage, intracellular neurofilaments are released into the extracellular space, leading to an increase in their concentration in the CSF; an increase in NfL levels may also be age-related, probably due to reduced CSF turnover or slow axonal damage associated with normal aging. NfL rises in CSF in several inflammatory, traumatic, and neurodegenerative neurological diseases including Parkinson’s disease and atypical parkinsonian disorders, amyotrophic lateral sclerosis, and multiple sclerosis (51,52). Regarding AD, NfL levels have been shown to be higher in patients with dementia and MCI than in cognitively unimpaired controls, but they are thought to have limited utility in the differential diagnosis between various neurodegenerative diseases (53,54). Because of this lack of specificity for AD, their use as a nonspecific screening marker for neurological diseases has recently been suggested, like C-reactive protein for systemic inflammation (55).

Validation studies have established a satisfactory correlation between the CSF and blood levels of NfL. Blood NfL levels may pre-date symptom onset as early as around 6.8 years in individuals carrying AD familial disease mutations. However, due to the lack of specificity of NfL, it has its best utility in a panel of biomarkers including amyloid and tau markers (56).

Role of APOE4

The APOE gene has three alleles, ε2, ε3 and ε4, which encode for three distinct isoforms of APOE. In terms of AD risk, apoE3 is considered neutral, apoE2 is protective, and apoE4 is harmful. APOE can influence Aβ formation, cytoskeleton integrity and neuronal repair efficacy: apoE4, Aβ, and tau, in combination with other factors, may act in concert in a pathogenic cascade that contributes to neuroinflammation, neurodegeneration, and ultimately clinically observable cognitive decline (57). APOE4 carriers are characterized by earlier Aβ deposition, more rapid disease progression, and greater brain atrophy than noncarriers of apoE4 (58). Because of this growing evidence, studies are underway on possible therapeutic strategies that can reduce APOE4 levels and increase APOE2 levels in the brain (59). In addition, it is advised to ascertain the APOE genotype status before initiating anti-amyloid immunotherapy. These novel disease-modifying treatments have been linked to a high incidence of amyloid-related imaging abnormalities (ARIA) accompanied by cerebral edema or hemorrhage; APOE4 is strongly associated with ARIA and has a gene dose effect; therefore, ascertaining the APOE genotype status has been recommended to enhance risk assessment for ARIA and heighten physician vigilance (60). C2N has developed the Clinical Laboratory Improvement Amendments (CLIA)-approved PrecivityAD™ test (61) that uses a two-liquid chromatography tandem mass spectrometry (LC-MS/MS) based assay that simultaneously quantifies Aβ isoforms in human blood and identifies the presence or absence of plasma APOE isoform-specific peptide used to determine an individual’s APOE genotype. This combination of markers can be used to both quantify Aβ isoforms in human blood and determine the common APOE genotype with excellent sensitivity and specificity in predicting the presence of amyloidopathy.

Need for novel biomarkers for AD

Core CSF biomarkers for AD are now part of routine clinical practice, and increased use of these diagnostic tests in routine clinical practice is expected. However, the widespread use of these methods remains limited due to their limited availability, invasiveness of spinal tap, and high cost. Despite this, CSF still represents the most reliable biological fluid for the detection of biomarkers of central nervous system (CNS) disorders, allowing the most accurate elucidation of the molecular processes that occur during neurodegeneration. Compared with blood, CSF has the advantage of being close to the brain parenchyma and containing brain proteins secreted directly from the brain’s extracellular space (62). An optimal blood biomarker for AD should have features such as reliability, reproducibility, noninvasiveness, ease of measurement, and cost-effectiveness. The limited permeability of the blood-brain barrier (BBB) to brain-derived proteins, the tendency of Aβ42 to aggregate into clumps in the blood, and the low sensitivity of the test have been obstacles to finding a reliable blood-based biomarker (56). However, recent technological advances have enabled the development of new assays for AD biomarkers in plasma, mostly based on immunoassay and MS methods (63). The development of ultrasensitive immunoassay techniques has led to tremendous improvements in the analytical sensitivity. Simoa, a bead-based immunoassay (digital ELISA) by Quanterix, enables the measurement of biomarkers at very low concentrations and it is also being used to develop homebrew assays of novel biomarkers (64,65). The Ella instrument, a microfluidic automated immunoassay platform designed by ProteinSimple, is based on easy-to-use disposable microfluidic cartridges, enabling single and multiplex measurements of a huge number of analytes (61,66). Among the chemiluminescent immunoassays, Lumipulse platform developed by Fujirebio currently enables the quantification of p-tau181, p-tau217, Aβ42, Aβ40 and NfL on plasma (67), while among the electrochemiluminescent immunoassays Elecsys Amyloid Plasma Panel has been recently developed by Roche (68). Lumipulse plasma assays have shown good performance in differentiating both AD-demented patients from controls (58) and amyloid-positive from amyloid-negative amnestic MCI (aMCI) subjects (69), and due to their accessibility and easy handling, they may facilitate widespread clinical implementation of plasma biomarkers. A recent study compared the diagnostic accuracy for AD of Simoa and Lumipulse novel plasma biomarkers, revealing similar performances (65,70). However, several publications have demonstrated the superiority of quantitative targeted MS technique over immunoassay for core AD blood biomarkers (71,72): its very high specificity, its ability to distinguish between different isoforms, as well as high multiplexing capability and no need for labeling, can improve the amount of biological information obtained from patient samples. Nevertheless, MS has some limitations that make it less applicable than immunoassay for routine use, such as low reproducibility, high cost, and the complexity of this technique, which requires highly trained personnel, available only in specialized laboratories (63).

These new techniques have overall allowed investigation of the potential clinical utility of plasma biomarkers. The diagnostic accuracy of blood amyloid biomarkers is substantially limited due to their low fold-change in amyloid-positive subjects and the elevated risk of pre-analytical errors (68,73), therefore their robustness is increased when quantified in conjunction with plasma tau biomarkers.

Like neuroimaging and CSF-based biomarkers, blood-based biomarkers are not stand-alone tests, and the appropriate use recommendations for blood biomarkers proposed by the Alzheimer’s Association emphasize how they should always be combined with clinical assessment and other exams (74). The most appropriate use for novel blood-biomarkers will probably be used as a first diagnostic assessment to determine the likelihood of AD and reduce the number of invasive and costly confirmatory tests, which will be used as a second diagnostic evaluation only in uncertain cases. Among the p-tau epitopes, p-tau217 is emerging as the most promising target for detecting AD with high diagnostic accuracy (75-77). Recent studies have shown that approaches for predicting Aβ status in the clinical settings based on plasma p-tau217 and followed by second-level exams only in uncertain cases, can achieve high diagnostic accuracy by reducing the number of confirmatory tests by up to 80% (45,54,78). Moreover, recent investigations have revealed the prognostic potential of plasma p-tau217 in accurately predicting the evolution from subjective cognitive decline and MCI to dementia (79). Future studies should focus on determining the clinical robustness of plasma biomarkers for AD in real-world clinical practice in extended prospective studies with appropriate reference standards.

The heterogeneity of pathology in late-onset AD requires an expansion of the range of biomarkers that reflect other aspects of AD pathophysiology. The most promising candidates are the neuroinflammatory components, on which research is largely focusing, obtaining valuable findings in terms of prognostic efficacy (80). The precise relationship between Aβ deposition, tauopathy, neurodegeneration, and clinical progression remains uncertain at the individual level, and for this reason, new models of pathogenesis are being considered, highlighting the role of inflammation, synaptic dysfunction, lipid metabolism, vascular dysregulation, iron toxicity, α-synuclein pathology, TDP43 inclusions, etc. (81). Alterations in the activity of dendritic micro RNAs (miRNAs) deserve mention, as they have been linked to the pathogenesis of psychosis and neurodegenerative diseases. MiRNAs implicated in cognitive dysfunction and neurodegeneration have been identified in CSF and postmortem brains of AD patients and in mouse models of AD (82). According to recent evidence miRNAs could be potential biomarkers for the presymptomatic stages of AD, due to new inexpensive methods for their detection: they could be useful in screening people for AD risk, to identify individuals who need further evaluation, such as CSF analysis and imaging studies measuring AT(N) markers (83). A study by Jia et al. identified an association between a panel of miRNAs in serum and the p-tau/Aβ42 ratio in the CSF of AD patients, suggesting that miRNAs are a promising tool to predict Aβ42 and p-tau levels in AD patients and to easily differentiate AD from other dementias, given the crucial role of miRNAs in the expression of key genes for AD pathology, their relative stability, tissue enrichment, and ease of quantitative measurement (84).

Understanding alternative pathological pathways could be important to improve diagnostic algorithms, achieve a better prognostic performance and develop new therapeutic strategies to arrest cognitive decline.

Role of biomarkers of neuroinflammation

Even if the ATN classification system especially emphasizes the three core CSF biomarkers (namely, amyloid-β, t-tau and p-tau), it is expandable to incorporate new biomarkers (7,34). Several novel fluid biomarkers have been proposed, even if not yet been validated.

Neuroinflammation has been proposed as a major player in AD pathogenesis, and for this reason, biomarkers of neuroinflammation are also being proposed as “Biomarkers of non-specific processes involved in AD pathophysiology” in the novel diagnostic criteria for AD, which are currently being drafted by the NIA-AA (https://aaic.alz.org/diagnostic-criteria.asp).

The cells of innate immunity primarily involved in the process of neuroinflammation are microglia and astrocytes. Excessive activation of these cells could cause harmful effects that outweigh the beneficial ones, increasing Aβ synthesis and tau hyperphosphorylation (85). In case of external damage, activated microglia, astrocytes and macrophages migrate through the damaged BBB; once activated, they lose homeostatic functions, reducing secretion of neurotrophic factors and producing increased amounts of proinflammatory cytokines and chemokines, which promote elimination of pathogens or toxins, but at the same time induce synaptic dysfunction and neuronal damage, constituting a chronic and self-feeding process (80). Astrocytes are the predominant non-neuronal cell population in the CNS (about 50%) and the most phenotypically diverse. They are specialized glial cells that make up the entire CNS scaffold, communicate with other cells, synapses, and blood vessels, and finally play a primary role in the expression of tight junction proteins, including occludin, claudin-5, and zonula occludens-1 (ZO-1), contributing to the maintenance of BBB integrity (86). Unlike microglia, which are at the forefront of the inflammatory response process, astrocytes do not have receptors that recognize pathogens, but they can become reactive, release mediators of inflammation or even phagocytize unwanted materials, cooperating closely with other glial cells. In response to a pathogenic noxa, these cells go into “reactive astrogliosis” (87), characterized by complex morphological and molecular changes. This phenomenon would appear to be closely related to Aꞵ deposition and NFTs formation in AD: reactive astrocytes would surround amyloid plaques as an endogenous defense mechanism, and there would be also a colocalization between these cells and tau oligomers (88). Although the exact role of astrocytosis is unclear, according to several studies, reactive astrocytes penetrate Aβ plaques by their own processes, perhaps to isolate them from the surrounding neuropil and phagocytose them (89). Further studies have shown that reactive astrocytes follow the same spatial distribution as Aβ plaques in the associative cortex of patients with AD. Finally, these cells can express different molecular phenotypes in AD and are responsible for the production of proteins such as Glial fibrillary acidic protein (GFAP) and protein 1 chitinase-3-like (YKL-40). In recent years, biological advances from human genetics have removed any doubt that microglia also play an important role in the pathogenesis of AD. Indeed, aggregation of plaques and tangles is followed by recruitment of microglial cells that surround the plaques and promote activation of the local inflammatory response contributing to neurotoxicity (90). When the deposition of amyloid Aβ and p-tau is such that it saturates the clearance mechanism of microglia, this brings to excessive release of pro-inflammatory factors such as IL-1β and tumor necrosis factor α (TNF-α) that compromise the integrity of synapses leading to AD progression. In neurodegenerative processes, chronically activated microglia release inflammatory cytokines, such as TNF-α, IL-6 and IL-1β, reactive oxygen species (ROS) and other substances through which microglia could exert both damaging and protective effects, depending on the type of microenvironment (91). In AD, the brain environment is highly perturbed locally, so microglia undergo a proliferation process called “reactive microgliosis”, with a hypertrophic or amoeboid form. In the context of AD, microglia initially respond to oligomers of Aβ, tau and myelin debris, adopting characteristics of disease-associated and interferon (IFN)-responsive microglia through pathways that are partly TREM2 or APOE-dependent: these pathways are characterized by downregulation of homeostatic genes (Hexb, P2ry12, Tmem119 and Tgfbr1) and upregulation of genes involved in inflammation (Il-1β, Ccl6), in phagocytosis (Trem2, Tyrobp, Axl), cell survival (Csf1, Igf1), lysosome function (Cst7, Cd68, Cstb/d, Lyz2) and lipid metabolism (Apoe, Lpl, Ch25h) (92).

The gradual transition of microglia to a pathological stage is manifested by upregulation of AD-associated genes such as APOE and TREM2 (93). In Aβ pathology, TREM2 and APOE act as a barrier to limit Aβ-induced neuronal toxicity by inducing microglial clustering (92). One notable feature of TREM2 involves the release of its ectodomain, achieved by cleavage mediated by ADAM10/17 at histidine 157 (H157) within the stalk region. This process leads to the formation of soluble TREM2 (sTREM2), which levels can be quantified in CSF. There is increasing evidence that microglia protect against the incidence of AD, as reduced microglial activity, and altered microglial responses to Aβ are associated with increased risk of AD.

Indeed, there are many new possible candidates as biomarkers of neuroinflammation (94), including the aforementioned GFAP, YKL40 and sTREM2.

GFAP

GFAP is present in most CNS astrocytes but expressed differently in different brain regions. GFAP is also expressed by nonmyelinating Schwann cells, enteric glia, neurogenic stem cells from the subgranular zone in the hippocampus and the subventricular zone surrounding the lateral ventricles (95). It is a type III IF protein with a molecular weight of 50 kDa that can occur in several isoforms (α, γ, δ/ε and κ in human brain, β in rodents) among which the α isoform is the most abundant. The general function of GFAP is to mechanistically support the astrocyte cytoskeleton and BEE structure together with vimentin and desmin: this makes it the best structural marker for studying the complex morphology of mature astrocytes (86). Lawrence Eng discovered this protein in the brain tissue of patients with multiple sclerosis, and later Eric Shooter presented its amino acid composition for the first time at the International Society of Neurochemistry meeting in September 1969 (96). During the process of astrocytosis, the hypertrophy that astrocytes undergo causes an increase in the expression of IFs, resulting in the release of high concentrations of GFAP into the blood. Several studies have used biomarkers such as GFAP to measure astrocytosis in vivo in CSF and, more recently, in serum and plasma (68). GFAP has recently attracted attention particularly because of evidence suggesting a better performance of the plasma biomarker than its CSF counterpart in detecting AD pathology. GFAP in CSF has been associated with amyloidopathy only in cognitively impaired individuals and is significantly elevated even in patients with disorders unrelated to AD (97), while plasma GFAP seems to more accurately discriminate Aβ-positive from Aβ-negative individuals than CSF GFAP does (97). Serum levels of GFAP have also been found to be increased in AD and correlate with Mini-Mental State Examination score. Therefore, GFAP may be a sensitive blood biomarker to detect and track reactive astrogliosis related to Aβ pathology (98). Reactive astrocytes also interact with tau, but mainly in the advanced stages of AD (89). This is important for several reasons, including the fact that amyloid-β and tau pathologies are not independent processes, but show a synergistic and complex interaction during AD that may be exacerbated in the presence of other disease processes such as astrocytosis. The presence of abnormal astrocytic reactivity may trigger tau pathology in cognitively unimpaired individuals with Aβ plaques: these results suggest that astrocyte reactivity abnormality could be placed as an early upstream event, in the hypothetical biomarker models of AD progression (99).

It is worth mentioning that increased blood GFAP can also be present under conditions of temporary BEE disruption in situations of acute neuronal damage such as head injury, ischemia, and intracranial hemorrhage (100). GFAP along with another neuronal protein, ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1), have recently been cleared by the U.S. Food and Drug Administration (FDA) as an aid in the evaluation of patients with traumatic brain injury (TBI) who are likely to have traumatic intracranial abnormalities on brain computed tomography (CT) (101). Abbott Laboratories has produced an ARCHITECT^® core laboratory platform with the ability to measure GFAP and UCH-L1 in whole blood, serum, and plasma with a 15-minute turnaround time. Most published studies to date on GFAP in AD have been carried out using ELISA assays. Roche has developed the NeuroToolKit (NTK), a panel of 12 robust exploratory prototype assays of CSF biomarkers (Aβ42, Aβ40, p-tau181, t-tau, NfL, neurogranin, α-synuclein, YKL-40, GFAP, sTREM2, SB100, and IL-6) run on a fully automated Roche Elecsys^® platform and developed through a collaboration between academic and industrial researchers (102). Therefore, it would be desirable to be able to study GFAP in AD using accessible automated platforms since a better understanding of novel neuroinflammatory biomarkers is crucial for determining their clinical value as diagnostic or prognostic tools, as well as for the development of new drugs in clinical trials (89).

YKL-40

YKL-40, also called human cartilage glycoprotein-39 (HC gp-39) or chitinase-3-like protein-1 (CHI3L1), is named after its first three N-terminal amino acids-tyrosine (Y), lysine (K) and leucine (L)-and molecular weight of 40 kDa. The human gene responsible for encoding YKL-40 was discovered in 1997 and is located on chromosome 1q31-q32 (103). YKL-40 is expressed by macrophages, chondrocytes, neutrophils, and synovial fibroblasts and is involved in the inflammatory response and remodeling of the extracellular matrix (104). Moreover, abundant expression of YKL-40 is present in astrocytes under neuroinflammatory conditions: transcription of this protein can be induced by cytokines released by macrophages, resulting in morphological changes and alterations in astrocyte mobility (104). Regarding AD, the presence of this glycoprotein has been detected in astrocytes near Aβ plaques (105) and it has been reported that YKL-40 levels correlate with age and are associated with the presence of the APOE ε4 allele (106). Solid evidence from several studies has documented a fair ability to differentiate individuals with AD from controls and to predict clinical progression along the AD continuum, illustrating its potential as a diagnostic and prognostic biomarker (105,107). Associations have also been reported between YKL-40 levels and the degree of tauopathy, that is, to the cortical extent of the tau protein aggregation process (108).

sTREM2

TREM2 is part of a receptor family expressed in specific myeloid cell types such as dendritic cells, granulocytes, and tissue-specific macrophages like osteoclasts, Kupffer cells, and alveolar macrophages and has several physiological functions, including promoting microglial proliferation, phagocytosis, and cytokine secretion (109). Within the brain, microglia are the exclusive cellular expression site for TREM2. Its expression has been shown to correlate with age (110) and is upregulated in several inflammation-related contexts, including AD (111). TREM2 gene variants have been associated with a substantially increased risk of developing late-onset AD (112,113) and levels of the sTREM2 correlate with p-tau and T-tau levels but are not associated with Aβ42 (114). Although the role of sTREM2 in AD pathology has yet to be fully elucidated, it is currently being considered as an attractive target for pharmacological modulation: the monoclonal antibody AL002, developed to bind TREM2 and modulate its signaling, is currently being tested in humans by Alector and AbbVie (115).

In the initial draft of novel AD diagnostic criteria by NIA-AA (released in July 2023) (https://aaic.alz.org/releases_2023/new-alzheimers-diagnostic-criteria-unveiled.asp), the role of different biomarkers of neuroinflammation was considered, including GFAP, which was acknowledged as already appropriate for clinical use (serving purposes such as staging, prognosis, and indicating biological treatment effect), and YKL-40 and sTREM2, which were recognized as “currently suitable for AD research and possibly for future clinical use”. However, this distinction was eliminated in the revised draft (released in October 2023) (https://aaic.alz.org/diagnostic-criteria.asp). The updated version explicitly identified only GFAP as a suitable biomarker for neuroinflammation, thereby reshaping the roles of other biomarkers. Nevertheless, the distinctive characteristics of sTREM2 and YKL-40 may still play a significant role in the future of AD diagnostics and research.

Conclusions

In contrast to CSF biomarkers, serum/plasma biomarkers would allow a more practical monitoring of patients over time, to assess the evolution of the disease during the follow-up and evaluate the biological effect of disease-modifying treatments. The use of fully automated platforms, with methods that are more robust and sensitive than conventional ELISA, could implement the use of blood-based biomarkers in clinical routine thanks to the high throughput and the accessibility of the platforms (Figure 1).

Figure 1 Fluid biomarkers of AD and main current measurement technologies. AD, Alzheimer’s disease; CLEIA, chemiluminescent enzyme-immunoassay; ECLIA, electrochemiluminescence immunoassay; ELISA, enzyme-linked immunosorbent assay.

However, appropriate criteria for the use of blood-based biomarkers need to be developed, standardization of tests is needed, and appropriate cut-offs for various biomarkers need to be defined. Levels of optimal specificity and sensitivity must be agreed upon to serve as reference standards that can confidently indicate AD pathology in the brain. Additionally, opting for a universal binary threshold to distinctly separate negative and positive subjects may not be the most suitable approach for blood biomarkers. Instead, employing diverse cutoffs tailored to specific purposes, whether prioritizing high sensitivity for initial screening programs or implementing multiple risk thresholds to identify individuals at high, intermediate, and low risk of AD, may be more appropriate. The integration of novel blood biomarkers with other accessible and cost-effective biomarkers, such as cognitive tests and APOE genotyping, will be crucial for comprehensive and cost-effective evaluations, and should be explored in future studies.

Most articles discussed into this review relied on data derived from retrospective studies conducted on research cohorts. Consequently, there arises a compelling need for the validation of these novel biomarkers through prospective studies, along with a thorough evaluation of their potential impact within real-world clinical scenarios. The subsequent critical phase will involve defining the application of these biomarkers at the individual patient level.

Looking at a not-too-distant future, it is probable that individuals with cognitive concerns will have the option to request a blood p-tau measurement from their primary care physicians or even private laboratories. Regardless of the potential affordability, practicality, and accessibility of this test in the coming years, it is relevant to emphasize the indispensable role of clinical assessment, including at least a basic neurological examination and a brief cognitive testing, alongside biomarkers quantification. At the individual patient level, these novel blood biomarkers are going to be crucial in helping clinicians in the decision-making processes. However, they should complement rather than replace traditional clinical evaluations and reasoning. The nature of a syndromic presentation may indicate that symptoms have a low likelihood of being attributable to AD despite the positivity of biomarkers. Since reliable biomarkers for most non-AD causes of cognitive impairment are lacking, clinical judgment should remain the most important factor in decision-making.

Additionally, in cases of uncertainty, confirmatory assessments should be conducted to ensure accuracy and reliability. Furthermore, in the absence of approved interventions for cognitively unimpaired individuals, quantifying biomarkers in healthy individuals should currently be avoided, except for research purposes. Therefore, biomarker assessments should always be conducted under the guidance of a physician.

There is growing evidence that alternative pathogenetic mechanisms need to be investigated further, because of the uncertain relationship between amyloid plaques, tau tangles and disease evolution, the need for new drug therapies, and the serious worldwide impact that AD will have in the coming years. Neuroinflammation biomarkers may play an important role not only in the pathogenesis but also in the prognosis of AD, and precisely because of this, the validation for clinical use of commercially available assays for biomarkers of neuroinflammation would be desirable.

Looking forward, with the advent of promising disease-modifying therapies targeting not only amyloid but also tau protein and neuroinflammation, the quantification of novel CSF and blood biomarkers may prove pivotal in treatment selection and monitoring. Characterizing various AD profiles with distinct progression rates and different responses to different treatments will be crucial in the next decades. As therapeutic options diversify, personalized approaches integrating biologic and clinical data may become essential for optimizing patient care and treatments effectiveness.

Acknowledgments

Funding: None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://jlpm.amegroups.org/article/view/10.21037/jlpm-24-1/rc

Peer Review File: Available at https://jlpm.amegroups.org/article/view/10.21037/jlpm-24-1/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jlpm.amegroups.org/article/view/10.21037/jlpm-24-1/coif). S.B. serves as the unpaid Editorial Board member of Journal of Laboratory and Precision Medicine from May 2023 to April 2025. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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