(2024) 21:187
Lista et al. Journal of Neuroinflammation
https://doi.org/10.1186/s12974-024-03163-yJournal of Neuroinflammation

Open Access

REVIEW

Tracking neuroinflammatory biomarkers
in Alzheimer’s disease: a strategy
for individualized therapeutic approaches?
Simone Lista1*†, Bruno P. Imbimbo2†, Margherita Grasso3, Annamaria Fidilio3, Enzo Emanuele4,
Piercarlo Minoretti5, Susana López‑Ortiz1, Juan Martín‑Hernández1, Audrey Gabelle6, Giuseppe Caruso3,7,Marco Malaguti8, Daniela Melchiorri9, Alejandro Santos‑Lozano1,10, Camillo Imbimbo11,
Michael T. Heneka12*† and Filippo Caraci3,7*†

Abstract
Background Recent trials of anti-amyloid-β (Aβ) monoclonal antibodies, including lecanemab and donanemab,
in early Alzheimer disease (AD) showed that these drugs have limited clinical benefits and their use comes with a sig‑
nificant risk of serious adverse events. Thus, it seems crucial to explore complementary therapeutic approaches.
Genome-wide association studies identified robust associations between AD and several AD risk genes related
to immune response, including but not restricted to CD33 and TREM2. Here, we critically reviewed the current knowl‑edge on candidate neuroinflammatory biomarkers and their role in characterizing the pathophysiology of AD.
Main body Neuroinflammation is recognized to be a crucial and contributing component of AD pathogenesis. The
fact that neuroinflammation is most likely present from earliest pre-stages of AD and co-occurs with the depositionof Aβ reinforces the need to precisely define the sequence and nature of neuroinflammatory events. Numerous clini‑
cal trials involving anti-inflammatory drugs previously yielded unfavorable outcomes in early and mild-to-moderate
AD. Although the reasons behind these failures remain unclear, these may include the time and the target selected
for intervention. Indeed, in our review, we observed a stage-dependent neuroinflammatory process in the AD brain.
While the initial activation of glial cells counteracts early brain Aβ deposition, the downregulation in the functional
state of microglia occurs at more advanced disease stages. To address this issue, personalized neuroinflammatory
modulation therapy is required. The emergence of reliable blood-based neuroinflammatory biomarkers, particularly
glial fibrillary acidic protein, a marker of reactive astrocytes, may facilitate the classification of AD patients basedon the ATI(N) biomarker framework. This expands upon the traditional classification of Aβ (“A”), tau (“T”), and neurode‑
generation (“N”), by incorporating a novel inflammatory component (“I”).

†

Simone Lista and Bruno P. Imbimbo contributed equally to this work.

†

Michael T. Heneka and Filippo Caraci are co-senior authorship.

*Correspondence:
Simone Lista
slista@uemc.es
Michael T. Heneka
michael.heneka@uni.lu
Filippo Caraci
fcaraci@unict.it
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/.

Lista et al. Journal of Neuroinflammation(2024) 21:187

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Conclusions The present review outlines the current knowledge on potential neuroinflammatory biomarkers and,
importantly, emphasizes the role of longitudinal analyses, which are needed to accurately monitor the dynamics
of cerebral inflammation. Such a precise information on time and place will be required before anti-inflammatory
therapeutic interventions can be considered for clinical evaluation. We propose that an effective anti-neuroinflam‑
matory therapy should specifically target microglia and astrocytes, while considering the individual ATI(N) statusof patients.
Keywords Alzheimer’s disease, Neuroinflammation, Biomarkers, GFAP, YKL-40, ATI(N) classification system, Microglia,
Astrocytes, Longitudinal studies, Clinical trials

Introduction
Alzheimer’s disease (AD), the predominant type of
dementia, accounts for approximately two-thirds of alldementia cases in individuals aged 60 years and older [1].
At present, it affects a staggering 33 million people globally and continues to grow at an alarming rate, with its
incidence doubling every 5–10 years [1]. Notably, developing countries play a substantial role in the increasing incidence of new AD cases [2]. This trend may be
attributed to the rapid growth of the older population inthese regions, which is increasingly affected by dementia. Recently, there has been a significant increase in thefocus on disease-modifying therapies that utilize monoclonal antibodies. One notable example is aducanumab,
an anti-amyloid agent that received conditional approval
from the U.S. Food and Drug Administration (FDA) in
2021 for the treatment of early-stage AD [3]. In 2023,
the FDA approved lecanemab, a monoclonal antibody
designed to target soluble amyloid-β (Aβ) protofibrils.
This groundbreaking approval came after the successful
outcomes of a phase III randomized, controlled clinical
trial. The results demonstrated, for the first time, that
reducing cerebral Aβ plaques through lecanemab led
to a noticeable deceleration in cognitive decline over an
18-month treatment period [4]. A recent phase III clinical trial evaluated the efficacy of donanemab, a monoclonal antibody targeting a pyroglutamate form of Aβ,
in individuals with prodromal AD and mild dementia due to AD [5]. The study revealed that donanemab
effectively slowed both cognitive and functional decline.
However, the magnitude of the clinical effects observedwith donanemab, along with other similar drugs, such asaducanumab and lecanemab, was limited. This suggeststhat additional mechanisms, including neuroinflammation [6], tau processing [7], apolipoprotein E (APOE) isoforms imbalance [8], mitochondrial dysfunction [9], andsynaptic degeneration [10], should be explored to fully
understand and address the pathogenesis of AD. Neuroinflammation refers to the activation of the brain’s innate
immune system in response to inflammatory challenges
such as injury, infection, toxin exposure, neurodegenerative diseases, or aging. Microglia, the innate immune cellsof the central nervous system (CNS), are pivotal in mediating these neuroinflammatory responses [11]. Activatedmicroglia and reactive astrocytes can phagocytize senile
plaques or dystrophic neurites, induce intraneuronal
inflammatory reactions towards neurofibrillary tangles,
and activate the complement cascade in response to vascular amyloid, thereby contributing to cerebral amyloid
angiopathy.
Currently, there are 164 ongoing clinical trials in phase
I, II, and III, evaluating the effectiveness of 127 distinct
drugs. Interestingly, in phase II, approximately 23% of
these compounds are specifically targeting inflammatory mechanisms [12]. These efforts highlight the urgent
requirement for innovative pharmacological treatmentsthat can effectively prevent or delay the onset of dementia, while also significantly slowing down the progressionof the disease. However, inflammatory mechanisms may
cycle between inflammation and resolution, and also
convert into a chronic type which means that any intervention will require a precise knowledge on the natureand site of inflammation to target.
In this context, the identification of reliable biomarkersof the initial pathological processes assumes paramountsignificance in disease management during all stages. Conducting biomarker studies becomes imperative in unraveling the intricate interplay between specific immune and/or
inflammatory molecules in the development and progression of AD clinical manifestations. Employing longitudinalbiomarker studies can unveil varying expression patterns
in the initial stages of AD pathology and thus potentiallyshed light on variances in treatment response [13]. Efforts
are currently underway to identify and validate innovative blood-based biomarkers that can effectively reflect
the pathophysiological mechanisms associated with AD at
a peripheral level. These biomarkers offer several advantages, such as being non-invasive and well-tolerated compared to brain imaging techniques and cerebrospinal fluid(CSF) biomarkers [14], which together will ease longitudinal assessment over years and decades. Plasma levels ofhyperphosphorylated tau at position 217 (p-tau217) havedemonstrated clinical performance that is equivalent to or
superior to the FDA-approved CSF tests in detecting brain

Lista et al. Journal of Neuroinflammation(2024) 21:187

Aβ pathology [15, 16]. Plasma neurofilament light chain(NfL) protein, which is a scaffolding cytoskeleton protein
released when neurons are damaged. Research has shownthat plasma NfL concentrations can effectively predict
brain imaging biomarkers of neurodegeneration and initialcognitive decline in middle-aged individuals [17].
Currently, there are several fluid biomarkers available
for detecting AD dementia development. The AT(N) biomarker framework, which assesses the brain deposition ofAβ (“A”), tau pathology (“T”), and neurodegeneration (“N”),
can be further expanded to include neuroinflammatory(“I”) candidate biomarkers, resulting in an ATI(N) system[18, 19]. By monitoring activated microglia and reactive
astrocytes, CSF and blood “I” biomarkers enable the tracking of neuroinflammatory processes [20].
In this review, we will provide an overview of the involvement of microglia and astrocytes in the neuroinflammatory
processes that impact the AD brain. Furthermore, we willconduct a thorough evaluation of the key studies focusing
on biomarkers that track the activation of microglial cells
and reactive astrocytes. We will also assess the ability of
longitudinal neuroinflammatory biomarker studies to predict the onset of AD and cognitive decline (see Table 1).
Lastly, we will analyze the significance of neuroinflammatory biomarkers in the diagnosis of AD and their role in AD
clinical trials.

Search strategy and selection criteria
This non-systematic literature review aims to provide an
informative overview of the current state of biomarkers
for neuroinflammation in AD. The manuscript is basedon a selective analysis of high-quality, contemporary articles on neuroinflammation biomarkers in AD. The primaryobjective is to identify trends and enhance understandingof the current landscape of neuroinflammation biomarkers
in AD. References for this review were identified throughsearches of PubMed databases for peer-reviewed articles
published in English between January 1, 2013, and December 31, 2023. The search terms employed included “Neuroinflammation” and “Alzheimer,” “longitudinal studies” and“Alzheimer,” “TREM2” and “Alzheimer,” “GFAP” and “Alzheimer,” and “YKL40” and “neurodegeneration.” Additionally, bibliographies of relevant papers were reviewed. Only
papers published in English were considered for inclusion.
The final list of references was selected by SL, MG, and AF,
and validated by BPI.
The role of microglia and astrocytes in Alzheimer’s
disease pathophysiology
Astrocytes and microglia, the brain-resident macrophages, are vital components in the developmentof neural circuits. These dynamic cells establish bidirectional communications with synapses, exerting a

Page 3 of 24

profound influence on synaptic function. Contrary to
popular belief, synaptic information processing is not
solely dependent on neurons. Astrocytes envelop synapses and microglia interact with synapses in an activitydependent manner [21], collectively contributing to theintricate network of neural connectivity. Prior studies[22, 23] have also demonstrated that astrocytes, microglia, and synapses interact in a “quad-partite” model,
where the axon terminal and dendritic spine communicate directly with microglial and astrocytic processes.
Disruptions to this quad-partite arrangement can lead
to abnormal plasticity, which consequently affects theencoding of information in neuronal circuits (Fig. 1).
Astrocytes play a crucial role in the formation of synapses and regulating the release of neurotransmitters,
thereby maintaining the balance of glutamate in thebrain. This function of astrocytes is essential for promoting various physiological activities associated with synaptic plasticity and, consequently, cognitive function [24].
Moreover, astrocytes can facilitate neuroinflammatory
processes through the release of inflammatory cytokinesand chemokines. These cells are also involved in theclearance of Aβ, which subsequently activates them, leading them to encircle senile plaques. This, in turn, contributes to Aβ-induced damage to the BBB, ultimately
depriving neurons of their metabolic supply [25].
Microglia cells, which represent approximately 5–20%
of all glial cells, serve as the main type of macrophages
in the CNS. Their primary function is to regularly survey
brain regions for pathogens and cellular debris, ensuring the preservation of neuronal circuits. Additionally,
microglia protect and remodel synapses to support brain
function [26]. These cells express various receptors that
detect both internal and external insults to the CNS.
When triggered by pathological factors such as protein
aggregates or neuronal death, microglia migrate to thesite of injury and initiate innate immune responses [27].
During the inflammatory processes involved in thepathogenesis of AD, there is a transition from the resting to the active functional state of microglia. Inflammation is primarily triggered by the accumulation ofAβ aggregates, including soluble oligomers and insoluble fibrils [28]. In the early stages of AD, Aβ oligomers
and fibrils build up in the extracellular space, initiatinga pathological cascade that leads to neuronal apoptosis and depletion. Microglia also play a crucial role inclearing Aβ oligomers, fibrils, and dead cells throughphagocytosis and by secreting proteolytic enzymes.
Additionally, microglia surround plaques and fibrils,
forming a barrier that prevents their spread and limits
their toxicity [29]. As Aβ deposition becomes increasingly severe, microglia undergo a transition fromtheir normal, homeostatic state to a dysfunctional

2.7–3.4

4.6

Morenas-Rodríguez et al., 2022 [78] DIAN

Vanderbilt Memory and Aging Project

ADNI

Winfree et al., 2022 [76]Schmitz et al., 2020 [75]5.7

Malmo Cohort

Amsterdam Dementia Cohort

BIOMARKAPDINSIGHT-preAD

Olsson et al., 2013 [176]

Kester et, 2015 [91]

Lleó et al., 2019 [93]Vergallo et al., 2020 [97]

1–3

2.1

2.0

6

Craig-Schapiro et al., 2010 [92]

1.5

3–5

Edwin et al., 2020 [77]Meanfollow-up
period (years)
2

Study

Casati et al., 2018 [82]References

314 SMC

154 CU75 SCD128 MCI
110 AD

37 CU
61 MCI
65 AD

65 CU
170 NCI
96 AD

198 CU
65 very mild AD
29 mild AD

268 CU

83 CU
72 MCI

148 ADAD
91 CU

42 CU
231 AD

42 CU
57 MCI
50 AD

Population

Table 1 Main characteristics of selected longitudinal studies on neuroinflammatory biomarkers in AD (n = 27)

CSF YKL-40
Plasma YKL-40

CSF YKL-40

CSF YKL-40
CSF VILIP-1

CSF YKL-40
CSF sCD14

CSF YKL-40
Plasma YKL-40

CSF sTREM2
Blood C3

CSF sTREM2

CSF sTREM2

CSF sTREM2

Plasma sTREM2PBMC mRNA TREM2

Biomarkers

CSF YKL-40 levels increased longitudinally
CSF YKL-40 positively associated with memory
performance and negatively with brain Aβ
deposition

At baseline, MCI and AD groups showed
higher CSF YKl-40 levels than SCD and HC
CSF YKL-40 levels increased longitudinallyin all groups

CSF YKL-40 levels at baseline in MCI and AD
patients were higher than CU
CSF YKL-40 and VILIP-1 at baseline predicted
progression of MCI to AD
CSF YKL-40 increased longitudinally in MCI
and AD

Baseline YKL-40 and sCD14 increase in MCI
patients who converted into vasculardementia

CSF YKL-40 was higher in very mild and mild
AD-type dementia patients and correlated
to higher plasma YKL-40 levels
CSF YKL-40/Aβ42 ratio predicted risk of cogni‑
tive impairment development

Loss of basal forebrain volume was associ‑ated with greater longitudinal accumulationof CSF sTREM2 and higher peripheral blood
C3 expression

High CSF sTREM2 levels predict memory
declinePresymptomatic carriers: increase in CSF
sTREM2 correlated with a decrease in Aβ42
Symptomatic carriers: decrease in CSF Aβ42
and Aβ42/40 at baseline independently pre‑dicted annual rate of increase in CSF sTREM2Higher CSF sTREM2 was associated with slow
clinical progression

Higher TREM2 expression at baeseline in APOE
ε4 MCI patients which progressed to AD

Main results

Lista et al. Journal of Neuroinflammation(2024) 21:187
Page 4 of 24

17

ESTHER Cohort

PREVENT-AD cohort

TRIAD and MYHAT Cohorts

Cardiovascular Health Study

Baltimore Longitudinal Study of Aging

Health, Aging, and Body Composition

Stocker et al., 2023 [116]Yakoub et al., 2023 [177]Bellaver et al., 2023 [114]Cronjé et al., 2023 [118]

Varma et al., 2024 [119]Yaffe et al., 2003 [178]

2

10

17

2.3

4

3

SCIENCe and Amsterdam Dementia Cohort 3.0

O’Connor et al., 2023 [110]Verberk et al., 2021 [115]5.8

1Silva-Spínola et al., 2023 [111]

KARVIAH Cohort

Chatterjee et al., 2022 [112]2

4.7

BioFINDER-2

Pereira et al., 2021 [113]Meanfollow-up
period (years)

Cicognola et al., 2021 [109]Study

References

Table 1 (continued)

Serum GFAP

Serum GFAP

Plasma GFAP

Plasma GFAP

Plasma GFAPCSF GFAP

Biomarkers

3,031 CU

318 CU

1,712 CU

1,106 CU

373 CU

768 CU

Serum IL-6
Serum TNFαSerum CRP

Plasma GFAP

Serum GFAP

Plasma GFAP

Plasma GFAP

Plasma GFAP

23 pre-symptomatic ADAD Plasma GFAP

300 CU

106 MCI79 MCI47 MCI-AD
34 MCI-other

206 CU

288 CU
141 AD
75 non-AD

Population

Serum higher IL-6 and CRP levels prospec‑tively associated with cognitive decline

In individuals who later converted to AD,
elevated plasma levels of GFAP were detected
up to a decade before the manifestationof cognitive impairment

Serum GFAP was associated with a hazard
ratio of 1.38 for incident dementia, and 2.76
for dementia-specific mortality

Aβ-dependent tau accumulation occurred
only in individuals with plasma GFAP levels
above a pre-specified cutoff

Female sex showed accelerated increasein plasma GFAP over time compared to males

GFAP associated with incident AD 9–17 years
before diagnosis

In pre-symptomatic ADAD participants,
plasma GFAP concentration increases
over a decade prior to estimated symptom
onsetHigher serum GFAP levels at baseline
associated with increased risk of progression
to dementia

At baseline, serum GFAP levels were signifi‑
cantly increased in patients who progressed
to AD at follow-up

Plasma GFAP predicted conversion to AD
Longitudinal plasma GFAP slopes for Aβ+
and MCI who progressed to dementia weresignificantly steeper than those for Aβ−
and stable MCI

Increased plasma GFAP levels in Aβ+ individu‑
alsPlasma GFAP levels showed significant cor‑
relations with cognition

Plasma GFAP associated with both longitudi‑
nal Aβ-PET and cognitive decline

Main results

Lista et al. Journal of Neuroinflammation(2024) 21:187
Page 5 of 24

Amsterdam Dementia Cohort

Gogishvili et al., 2023 [131]196 CU
210 Demented

259 CU

198 CU48 MCI
193 AD

109 CU

691 CU

Population

SNPs at codons + 10T/C, + 25 G/C, and the CC
genotype associated with an increased con‑version from MCI into AD

In women higher IL-1β at baseline related
to poorer verbal learning and delayed recall
at 12 months

Higher IL-1 and TNF-α spontaneous produc‑tion may predict an AD risk in older individu‑
alsMain results

CSF TGF-β1

Demented fast-progressor had lower CSF TGFβ1 vs slow-progressor

TGF-β1 codon 10T > C Carriers of at least one ­Tlower allele showed
short-term decline in functional performance
Individuals with ­CChigher genotype demon‑
strated cognitive stability or improvement

gDNA
TGF-β1

Plasma IL-1β
Plasma IL-6
Plasma TNFαPBMCs IL-1
PBMCs IL-1RA
PBMCs TNF-α

Biomarkers

AD: Alzheimer’s disease; ADAD: Autosomal Dominant AD; ADNI: Alzheimer’s Disease Neuroimaging Initiative; Aβ−: Aβ-PET negative; Aβ+: Aβ-PET positive; C3: Complement component 3; CRP: C-reactive protein;
CU: cognitively unimpaired; DIAN: Dominantly Inherited Alzheimer Network; gDNA: genomic DNA; GFAP: glial fibrillar acidic protein; INSIGHT-preAD: INveStIGation of AlzHeimer’s PredicTors in Subjective Memory
Complainers; KARVIAH: Kerr Anglican Retirement Village Initiative in Ageing Health; MCI: mild cognitive impairment; MYHAT: Monongahela-Youghiogheny Healthy Aging Team; PBMCs: peripheral blood mononuclear
cells; PET: positron emission tomography; PREVENT-AD: Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer’s Disease; sCD14: soluble CD14; SCIENCe: Subjective Cognitive Impairment
Cohort. SMC: subjective memory complaint; sTREM2: soluble TREM; TRIAD: Translational Biomarkers in Aging and Dementia; VaD: vascular dementia; VILIP-1: visinin-like protein-1; WRAP: Wisconsin Registry for Alzheimer
Prevention

4

1

Pietà Study

1

Fraga et al., 2015 [135]Center of Biomedical Research Excellence

Caldwell et al., 2021 [180]1–2

4

Framingham Study

Tan et al., 2007 [179]Meanfollow-up
period (years)

Arosio et al., 2007 [133]Study

References

Table 1 (continued)

Lista et al. Journal of Neuroinflammation(2024) 21:187
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Lista et al. Journal of Neuroinflammation(2024) 21:187

Page 7 of 24

Fig. 1 A Pathological interactions between glia and neurons in AD. Amyloid-beta species can be recognized by and activate microglia, which
contribute to activate astrocytes. These cells release pro-inflammatory cytokines and chemokines and lose their homeostatic functions, leading
to disruption of the BBB and neuronal damage. Deficit of anti-inflammatory cytokines (e.g. TGF-β1) also contributes to microglial activationand synaptic dysfunction. Disease associated microglia can also directly eliminate synaptic structures. B “Eat-me” signals and the quad-partite
synapse in AD. Neuronal eat-me signals are recognized by several phagocytic receptors on both astrocytes and microglia. Some of these signals
include milk fat globule-EGF factor 8 protein (MFGE8) and Protein S, both bound to exposed phosphatidylserine, and complement component
3 (C3) and 1q (C1q). Microglia use as cell-surface receptors the complement receptor 3 (CR3), vitronectin receptor (VNR), MER receptor tyrosine
kinase (MERTK) and triggering receptor expressed on myeloid cells 2 (TREM2) among others. Astrocytes may also contribute to synaptic engulfment
via the binding of C1q to multiple EGF-like domains 10 (MEGF10). Metabotropic glutamate receptor 5 (mGluR5) may also induce synaptotoxicity
via calcium dysregulation and complement activation, making the synapses a target for removal by astrocytes and microglia. Interactions
between α7 nicotinic acetylcholine receptors (α7nAChRs) and soluble amyloid-β (Aβ) can also contribute to reactive astrogliosis and neuronal
death, through the excessive release of glutamate from astrocytes in a Ca2 + -dependent manner. α7nAChRs α7 nicotinic acetylcholine receptors, Aβamyloid-β, AD Alzheimer disease, BBB blood–brain barrier, C1q complement component, C3 complement component 3, CR3 complement receptor
3 (CR3), IL interleukin, MEGF10 multiple EGF-like domains 10, MERTK MER, receptor tyrosine kinase, MFGE8 milk fat globule-EGF factor 8 protein,mGluR5 Metabotropic glutamate receptor 5, TGF-β1 transforming growth factor-beta 1, TNF tumor necrosis factor, TREM2 triggering receptor
expressed on myeloid cells 2, VNR vitronectin receptor

phenotype. This shift prompts the release of proinflammatory factors, oxidative stress, and neuroinflammation, while also reducing the secretion ofneurotrophic factors. Ultimately, this leads to synaptic
impairment and the exacerbation of neuronal damage[30, 31]. Despite the potential benefits of early activation, chronic activation of microglia by Aβ can be detrimental. This leads to amplified Aβ deposition andprolonged inflammatory processes, ultimately accelerating neurodegeneration. In advanced stages of thedisease, microglia can exacerbate AD by circulating
proinflammatory cytokines—such as interleukin-1β(IL-1β) and tumor necrosis factor-alpha (TNF-α)—
which cause neuronal cell death, as well as by stimulating astrocytes, which can impact neuronal survival[26].

Biomarkers of neuroinflammation in Alzheimer’s
diseaseBiomarkers play a crucial role in enhancing our understanding of the molecular mechanisms underlying theonset and progression of AD. Specifically, plasma biomarkers offer a convenient method to evaluate individuals at various stages of the disease continuum, including
healthy individuals, those at risk of developing AD, andpatients with AD. By monitoring these biomarkers overtime, we can gain valuable insights into the individual’s
longitudinal progression within the AD spectrum.
As of 2009, genome-wide association studies (GWAS)
led to the identification of novel genetic associations,revealing genome-wide statistically significant links
between AD and variants within the CLU, PICALM, andCR1 genes. Since then, more than 50 risk loci and over

Lista et al. Journal of Neuroinflammation(2024) 21:187

70 gene variants associated with an increased risk ofdeveloping sporadic late-onset AD (LOAD) have been
identified [32]. These findings underscore the interconnected network of molecular and cellular pathways thatsignificantly influence the progression and pathogenesis of AD. Interestingly, several of these identified variants are intertwined with genes that play a crucial role inimmune responses and inflammation. These include, but
are not limited to, TREM2, CD33, PILRA, CR1, MS4A,
CLU, ABCA7, EPHA1, and HLA-DRB1 [23, 33]. The
majority of these genes play significant roles in various
functions such as proinflammatory intracellular signaling, cytokines/interleukins/cell turnover, synaptic activity, lipid metabolism, and vesicle trafficking. The crucial
involvement of neuroinflammation is supported byextensive GWAS studies that reveal a notable rise in thelikelihood of developing LOAD in individuals carrying
rare variants of microglial immunoreceptors.
CD33 encodes a transmembrane receptor expressed on
myeloid lineage cells, functioning as a sialic acid-binding
immunoglobulin-like lectin that modulates innate immunity. The minor allele of the CD33 SNP rs3865444, which
confers protection against AD, has been associated with
reduced levels of insoluble Aβ42 in AD brains. In microglial cell cultures, CD33 inhibits the uptake and clearanceof Aβ42. Therefore, CD33 inactivation has been shown tomitigate Aβ pathology, suggesting that CD33 inhibition
could represent a novel therapeutic strategy for AD [34].
PILRA encodes the paired immunoglobulin-like type
2 receptor alpha, a cell surface inhibitory receptor thatrecognizes specific O-glycosylated proteins. PILRA isexpressed on various innate immune cell types, including
microglia. It has been proposed that the common PILRA
missense variant (G78R, rs1859788) protects individuals
from AD risk by reducing inhibitory signaling in microglia and microglial infection during herpes simplex virus
1 (HSV-1) recurrence [35]. Complement component(3b/4b) receptor 1 (CR1) is a notable candidate gene witha significant connection to AD. Polymorphisms in CR1
have been reported to be associated with LOAD susceptibility. A recent review identified that the rs6656401 variant in CR1 increases the risk of LOAD [36]. Additionally,a common variant in the membrane-spanning 4-domains
subfamily A (MS4A) gene, specifically MS4A4A, hasbeen linked to increased CSF sTREM2 concentrations
and a reduced risk of AD [37]. The CLU gene, which contains several AD-associated intronic SNPs, encodes clusterin, a secretory protein predominantly synthesized in
astrocytes. Clusterin levels are elevated in the brain tissues, CSF, and plasma of AD patients and may play antiamyloidogenic roles [38].
Rare variants of the ATP-binding cassette sub-family
A member 7 (ABCA7) gene are significantly enriched

Page 8 of 24

in patients with AD, while a common ABCA7 missense
variant may confer protection against the disease. Methylation at several CpG sites within the ABCA7 locus issignificantly associated with AD and correlates with amyloid deposition and brain morphology [39]. The EPHA1
gene encodes ephrin type-A receptor 1 (EphA1), a member of the ephrin receptor subfamily within the proteintyrosine kinase family. Ephrin receptors and related
proteins have been implicated in mediating immune
cell recruitment. The P460L variant of the EPHA1 geneis associated with an increased risk of LOAD and has
recently been shown to impact immune responses andblood vessel function in the brain [40]. HLA-DRB1 ispart of the human leukocyte antigen (HLA) class II beta
chain paralogues. This class II molecule is a heterodimer
composed of an alpha (DRA) and a beta (DRB) chain,both of which are membrane-anchored. HLA-DRB1
plays a pivotal role in the immune system by presenting
peptides derived from extracellular proteins. Specific
HLA-DRB1*04 alleles have been shown to confer protection against AD [41]. Below, we provide an in-depth
description of the TREM2 protein and other significant
neuroinflammatory proteins.
Soluble triggering receptor expressed on myeloid cells 2(sTREM2)

TREM2, a cell surface receptor, is predominantly
expressed on microglial cells. Its primary function
includes enhancing the phagocytic capabilities of microglia and macrophages while also modulating inflammatory signaling. TREM2 transduces its intracellularsignaling through the adapter protein DAP12 [42]. The
binding of TREM2 to ligands, including anionic lipids,
lipoproteins, and Aβ, initiates downstream signalingcascades that promote microglial survival, proliferation,
chemotaxis, and phagocytosis [43, 44]. The significanceof TREM2 in the pathogenesis of AD was underscoredby the discovery of a specific heterozygous mutation,
R47H, which substantially elevates the risk of developing
LOAD [45, 46]. Subsequent research has established that
TREM2 activation in microglia plays a crucial role in thepathological processes underlying AD [47]. This receptor
also plays a pivotal role in regulating microglial-related
activities, particularly in response to the presence of Aβplaques and tau tangles [48]. A soluble form of TREM2(sTREM2), which is generated through the proteolytic
cleavage of the receptor found on the surface of cells,
has the ability to promote microglial activation. Proper
receptor ligation is anti-inflammatory and facilitates
microglial survival.
TREM2 gene variants have been found to increase
the risk of developing AD by impairing the ability of
microglia cells to effectively clear Aβ and disrupting

Lista et al. Journal of Neuroinflammation(2024) 21:187

the normal proinflammatory response of these immune
cells [49]. Currently, approximately 50 variants of
the TREM2 gene have been studied in relation to AD[50]. The rare R47H variant of TREM2 (rs75932628)
has been linked to a two- to three-fold increase in therisk of developing AD in European and North American (Caucasian) populations [51–53]. The R47H variant
is believed to contribute to a loss of TREM2 function,
leading to a reduction of microglia and an increase inneuritic dystrophy at the site of Aβ deposition [54].
A meta-analysis involving more than 73,000 participants found that individuals carrying this variant had
a four-fold higher risk of developing AD compared to
non-carriers, which is similar to the effect size of the
APOE ε4 variant [55]. Additionally, it has been suggested that the R47H variant may be associated withan earlier age at AD onset [56]. However, this variant
is extremely rare or undetectable in African-American[57] and Asian populations [58, 59]. Another variant,
R62H (rs143332484) [60], has been associated with anincreased risk of AD in individuals of European descent[61]. Interestingly, patients with AD harboring TREM2
risk variants show an abundance of autophagic vesicles
in their microglia [62].
An additional variant, H157Y (rs2234255), is located at
the TREM2 site and is cleaved by two α-secretases (a disintegrin and metalloproteinase 10 and 17 [ADAM-10 and
ADAM-17]), resulting in increased shedding of TREM2
and reduced cell surface expression of the receptor [63].
Unlike the R47H and R62H variants, H157Y is more frequently observed in Asians and is particularly associatedwith an increased risk of AD in a Han Chinese cohort[64, 65]. Prior studies conducted on Caucasian, Japanese,and African-American cohorts did not find any significant association between this variant and AD. However,a comprehensive meta-analysis revealed a strong correlation with an odds ratio of 3.65 [65]. Additionally, further
analyses conducted on Chinese cohorts identified thepresence of the p.Ala130Val and p.Ala192Thr variants,
specifically observed in cases of LOAD. Another variant, p.Ser183Cys, was found to be more prevalent among
Chinese patients with AD [50]. The presence of multiple
variants associated with a higher susceptibility to developing AD in Chinese and African-American populations
highlights the presence of diverse mutations across different cohorts and ethnic groups. This underscores theneed to investigate various ethnic populations to discover specific disease risk variants and explore potential
associations between these variants and specific diseasephenotypes [50]. Notably, individuals carrying TREM2
variants exhibit an earlier onset of the disease and experience faster cerebral atrophy. Therefore, identifying
TREM2 carriers can be valuable in improving patient

Page 9 of 24

stratification for clinical trials and supporting the development of personalized therapeutic approaches [33].
In general, the published literature has shown a slightincrease in CSF sTREM2 concentrations in patients withAD [66–68] and individuals with mild cognitive impairment (MCI) [69] compared to CU controls. However,other studies did not find significant differences in CSF
sTREM2 levels between AD or MCI participants and CU
controls [70]. Notably, increasing CSF sTREM2 concentrations were associated with changes in brain structure,
specifically an increase in grey matter volume in regions
such as the bilateral inferior and middle temporal cortices, precuneus, supramarginal and angular gyri, in individuals with MCI. This suggests that sTREM2 may play arole in modulating neuroinflammatory responses to earlyneurodegeneration [71].
Despite the fact that CSF sTREM2 values are higher inpatients with AD compared to CU controls, this potential
biomarker lacks sufficient discriminatory power. Specifically, it falls short of the 80–90% range required in clinical diagnostic practice to effectively differentiate between
patient groups [69]. However, the increase in CSF
sTREM2 concentrations during the early stages of AD
may indicate a change in microglial activation status due
to neurodegeneration. This suggests that sTREM2 exhibits a dynamic response linked to microglial activity as thedisease progresses. These findings highlight the potentialof CSF sTREM2 as a biomarker for tracking the progression from preclinical AD/MCI to AD dementia [68, 72].
Consequently, it may also serve as a valuable biomarker
in clinical trials focusing on secondary AD prevention.
The dynamics of CSF sTREM2 should be investigatedin relation to the key pathophysiological mechanisms ofAD, namely Aβ and tau pathologies. Decreased levelsof CSF sTREM2 are linked to Aβ pathology [73] while
increased levels are associated with tau-related neurodegeneration [74]. In a cross-sectional study of 127 individuals with autosomal dominant AD (ADAD) mutations,
it was observed that CSF sTREM2 concentrations began
to rise five years before symptom onset, but quite a longtime after the accumulation of Aβ in the brain [72].
Significant insights have also been gained from longitudinal studies on CSF sTREM2. For instance, a 1.5-year
study involving 268 CU individuals with initial brain Aβ
deposition revealed that a decline in basal forebrain volume was associated with a greater accumulation of CSF
sTREM2 over time [75]. In another longitudinal study
spanning 4 years and including 72 individuals with MCI,
it was found that CSF sTREM2 levels correlated withthe progression of CSF Aβ and tau [76]. Additionally, a
3-year study on 231 AD patients showed that higher
CSF sTREM2 levels at baseline were linked to slower
clinical progression [77]. Finally, a 3-year study on 148

Lista et al. Journal of Neuroinflammation(2024) 21:187

pre-symptomatic ADAD patients indicated that higher
annual rates of increase in CSF sTREM2 corresponded
to a reduced rate of cognitive decline [78]. These studies
suggest that sTREM2 should be considered not an earlymarker, but indicative of the MCI to AD conversion,
although further studies are needed to validate its role asbiomarker in this scenario.
Limited reports have investigated the dynamics of
TREM2 in blood. However, the available research suggests that both TREM2 mRNA and protein expression
levels are elevated in monocytes of patients with ADcompared to controls. Furthermore, these increased
levels were found to be inversely correlated with cognitive performance, as measured by the Mini-Mental State
Examination (MMSE). A positive correlation between
TREM2 mRNA and protein expression was observedin monocytes. In addition, a tendency towards upregulation of TREM2 protein was also noticed in granulocytes and plasma [79]. Other studies have demonstrated
higher expression levels of TREM2 mRNA in leukocytesof patients with AD than in controls, which were foundto be associated with cognitive decline and hippocampal atrophy [80, 81]. In a longitudinal study involving 57
individuals with MCI, higher plasma TREM2 levels andmRNA expression were detected in peripheral bloodmononuclear cells (PBMCs) of APOE ε4 positive individuals who later developed AD during the two-year
follow-up period [82]. Another investigation focusing on
peripheral leukocytes revealed higher expression levelsof TREM2 in LOAD compared to early-onset AD. Interestingly, the expression of this receptor was markedly
increased in LOAD individuals who carried the APOE ε4
allele [83].
Chitinase‑3‑like protein 1 (YKL‑40)

The glycoprotein YKL-40, also known as chitinase-3-likeprotein 1 (CHI3L1), is detected primarily in various cell
types, including macrophages, chondrocytes, fibroblasts,
vascular smooth muscle cells, endothelial cells, and evencertain cancer cells [84]. Expression is most prominent
in reactive astrocytes [85]. While the exact physiological role of YKL-40 is still debated, there is consensus
regarding its involvement in tissue remodeling and renovation during inflammation, as well as in angiogenic
mechanisms that affect the infiltration, differentiation,and maturation of macrophages. Consequently, YKL-40
is considered a candidate biomarker for inflammationand endothelial dysfunction [84], a specific biomarker
for human macrophage activation/differentiation and its
expression is induced in reactive astrocytes by the presence of activated macrophages [86]. A critical reviewof the literature has identified YKL-40 as a pathophysiological biomarker indicating the activation of glial cells,

Page 10 of 24

including astrocytes and microglia, which are associated with tau pathology [87, 88]. In addition, prior studies have shown that CSF levels of YKL-40 are linked tobiomarkers of neurodegeneration (total tau, t-tau), damage to large-caliber myelinated axons (NfL), tau-mediated toxicity (p-tau), and synaptic damage (neurogranin,
SNAP-25) in various neurodegenerative diseases [89].
Interest in YKL-40 in AD was sparked by initial observations that CSF levels of YKL-40 were significantly
higher in individuals with AD and MCI compared tocontrols [90, 91]. Notably, early histopathological studies have demonstrated that YKL-40 expression is localized near Aβ plaques and tau neurofibrillary tangles[92]. YKL-40 can effectively differentiate patients withovert dementia from CU individuals [91–94]. Secondly,
YKL-40 serves as a predictor of cognitive decline, allowing for the identification of individuals progressing
from preclinical AD to prodromal AD and later stagesof dementia. Finally, it aids in distinguishing individuals
with MCI who will convert to AD from those who willremain stable at five years [86]. However, it should be
noted that CSF YKL-40 is not clinically useful in differentiating the characteristic AD phenotype (i.e., amnestic
syndrome of hippocampal type) from other atypical presentations of AD [95]. In addition, patients exhibited a significant correlation with the corresponding CSF values.
Significantly, patients in a 6-year longitudinal study by
Craig-Schapiro and colleagues (2010) exhibited a strong
association between YKL 40 levels in CSF and plasma[92]. Moreover, plasma YKL-40 concentrations were
found to be elevated in individuals with very mild andmild AD dementia (CDR = 0.5 and CDR = 1, respectively)
compared to control individuals (CDR = 0) [92]. Anotherstudy discovered a significant increase in plasma YKL-40
levels in patients with early AD than in individuals with
MCI and healthy older controls. Moreover, YKL-40 demonstrated a positive correlation with neuropsychologicaltest results in both MCI and early AD [96]. In a longitudinal study conducted by Vergallo et al. (2020) [97], it
was found that plasma YKL-40 concentration can serve
as a valuable biomarker to assess the severity of AD. The
investigation focused on a cohort of CU individuals at
risk for AD and revealed a positive association between
plasma YKL-40 and episodic memory performance(assessed using the Free and Cued Selective Rating Test).
Conversely, a negative association was observed between
plasma YKL-40 and brain Aβ accumulation [97]. Thesefindings suggest that glia activation, reflected by elevated
YKL-40 levels, may have a potentially protective effecton initial brain Aβ deposition and neuronal homeostasis, without causing clinical harm. Moreover, the study
also observed a sexual dimorphism, with men exhibiting
higher YKL-40 concentrations than women [97]. AnotherLista et al. Journal of Neuroinflammation(2024) 21:187

study investigating biomarker differences across different
ethnicities reported elevated plasma YKL-40 concentrations specifically in Hispanic women with prodromal AD
compared to both CU controls and prodromal AD participants of African or Caucasian origins. This emphasizes the impact of potential modulating factors on thevariability of YKL-40 levels [98].
YKL-40 has also emerged as a compelling candidate
biomarker for investigating the clinical evolution of AD.
Its potential role in clinical trials lies in its ability to trackthe dynamics of glial neuroinflammatory mechanisms
in relation to neurodegeneration. According to Baldacci et al. (2017), CSF YKL-40 exhibits a correlation withelevated levels of CSF t-tau, even in asymptomatic andpreclinical AD individuals. This suggests an early association between YKL-40 and tau protein during the courseof neurodegeneration [86].
In conclusion, exploring the connection between YKL40 and AD features could shed light on the intricate
relationship between Aβ dysmetabolism, neuronal activity, and neuroinflammation. YKL-40 thus represents apromising biomarker for accurate classification of neuroinflammatory phenotypes, facilitating advancements inneuroinflammatory clinical trials [97].
Glial fibrillary acidic protein (GFAP)

Astrogliosis refers to the abnormal activation and proliferation of astrocytes that occurs in response to initialbrain damage [99]. This process leads to significant cellular, molecular, and functional changes. In acute brain
injuries—as well as in AD, other neurodegenerative diseases, and low-grade astrocytoma—astrocytes adopt
a reactive phenotype [99]. Transcriptomic analyses ofhuman patients and disease models have demonstrated
the presence of multiple putative reactive astrocyte substates. In CNS disorders, there is a marked upregulation
and reorganization of intermediate filament proteins,
leading to the formation of an intricate network comprising various isoforms of GFAP (ten isoforms), vimentin,synemin, and nestin [100]. GFAP, a type III intermediate filament protein, serves as a key cytoskeletal component in astrocytes. In AD, astrocytes exhibit a complex
response to both neurofibrillary tangles and Aβ plaques,
which may exert either neuroprotective or deleterious
effects [101]. The capacity of astrocytes to colocalize withAβ plaques in the AD brain has been demonstrated usinglabeled tracers [102]. Moreover, studies have reported asignificant correlation between GFAP expression levels
and the density of Aβ plaques in the hippocampus andentorhinal cortex of AD brains [103]. Interestingly, elevated concentrations of GFAP within the CSF have beenreported in patients with AD and other forms of dementia compared to healthy individuals [104]. An increase

Page 11 of 24

in plasma GFAP concentrations was also noted in both
early-onset AD and LOAD [105, 106]. This increase
was positively correlated with the extent of white matter injury, as determined through the quantification ofwhite matter hyperintensities [105, 106], whereas cognitive function assessed with MMSE showed an inverse
association [106]. When combined with plasma Aβ1-42/
Aβ1-40 ratio, the APOE ε4 status, and/or age, the diagnostic value of plasma GFAP was found to be increased[107–109].
The potential of blood GFAP as a biomarker for AD has
been significantly highlighted by longitudinal investigations. A study conducted over 3 years on 23 asymptomatic AD patients revealed an increase in plasma GFAP
concentrations in mutation carriers compared to noncarrier controls. This suggests that plasma GFAP alterations can be detected up to a decade before the onset of
AD clinical symptoms [110]. Additionally, a 6-year longitudinal study on 106 individuals with MCI found thatbaseline serum GFAP levels were significantly higher
in patients who progressed to AD at follow-up [111].
In a cross-sectional analysis conducted in preclinical AD, a plasma biomarker panel consisting of GFAP,
p-tau181, and p-tau231 exhibited increased levels in CU
Aβ-positron emission tomography (PET)-positive individuals compared to those who tested negative [112].
The study subsequently confirmed the longitudinal predictive value of two of the three biomarkers (GFAP and
p-tau181), emphasizing their diagnostic and monitoring
potential in preclinical AD [112]. In a 2-year, longitudinal
study, researchers examined 288 CU individuals and 141
patients. The study found that plasma GFAP levels wereassociated with both longitudinal Aβ-PET deposition andcognitive decline [113]. Another extensive 2-year longitudinal study involving 1,106 CU participants revealed
that Aβ-dependent tau accumulation occurred only inindividuals who tested positive for astrocyte reactivity—which was defined by plasma GFAP levels above a
specified cutoff (mean + 2.0 standard deviations of controls without Aβ pathology) [114]. These data suggestthat secondary astrocytosis caused by Aβ aggregation
might promoting tau accumulation, although further
longitudinal studies are needed. A 5-year longitudinal
study involving 169 individuals with MCI showed thathigher baseline plasma GFAP concentrations were associated with the progression to AD and faster rates ofcognitive decline [109]. Another 3-year longitudinal
study conducted on 300 CU older individuals found thathigher serum GFAP levels at baseline were linked to
an increased risk of incident dementia [115]. An analysis conducted within the ESTHER cohort, a German
population-based study of older individuals living in
the community, revealed a substantial early association

Lista et al. Journal of Neuroinflammation(2024) 21:187(spanning between 9 and 17 years prior to clinical diagnosis) of plasma GFAP with the incidence of AD. Notably, this association was found to be significantly earlier
than that of NfL and p-tau181, which were typically associated within approximately 9 years of diagnosis [116].
These results suggested that GFAP may serve as a more
effective prognostic biomarker for incident AD dementia
compared to NfL [115]. The diverse prognostic values ofthese cytoskeletal proteins are believed to stem from different underlying mechanisms. Notably, NfL is released
into the bloodstream following axonal degeneration,
while increased levels of GFAP are a response to damage
triggered by Aβ and tau aggregates [101]. Continual activation of astrocytes in response to this damage leads to a
pro-inflammatory neurotoxic state, which further exacerbates neurodegeneration [117].
A recent 17-year longitudinal study involving 1712 CU
participants found that serum GFAP levels at baseline
were associated with a hazard ratio of 1.38 (95% confidence interval = 1.15–1.66) for incident dementia and2.76 (95% confidence interval = 1.73–4.40) for dementiaspecific mortality, supporting the notion that circulating GFAP can be a valuable tool for assessing dementia
risk and prognosis [118]. In another recent study involving 318 CU participants, including 158 individuals wholater converted to AD and 160 who remained cognitively
unimpaired, the authors observed elevated plasma levels of GFAP in AD-converters up to 10 years before theonset of cognitive impairment [119]. This finding suggests that increased astrocyte reactivity, as indicated byhigher GFAP levels, is an early event in the progressionof blood biomarker changes during the preclinical stageof AD. Taken as a whole, these results indicate that GFAP
holds promise an early blood-based biomarker for reactive astrogliosis associated with Aβ pathology in preclinical AD. Consequently, this marker could be used to
identify individuals at risk of AD before the onset of clinical symptoms [108].
Transforming growth factor‑beta 1 (TGF‑β1)

Recent studies indicate that a deficiency in anti-inflammatory cytokines, particularly transforming growth
factor-β1 (TGF-β1), in the brains of patients with AD
significantly contributes to microglia activation andneuroinflammation, thereby playing a crucial role in thepathophysiological mechanisms underlying cognitive
decline in AD. [120, 121].
Building on this evidence, researchers have exploredthe potential of TGF-β1 as a novel biomarker for AD[120]. The deficit of TGF-β1 can contribute to neurodegeneration through multiple mechanisms. Notably, TGFβ1 plays a constitutive role in suppressing inflammation
and regulates the degree of microglial activation in the

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CNS in an age-dependent manner [122]. TGF-β1 also
plays a pivotal role in synaptic plasticity and memory formation by facilitating the transition from early to late hippocampal long-term potentiation [123] and stimulating
the uptake of Aβ by microglia [122]. Notably, numerous
studies have shown that the TGF-β1 signaling pathway
is selectively impaired in the early stages of AD, leading
to microglia activation, neuroinflammation, increased
neuronal vulnerability to Aβ oligomers, hippocampal
atrophy, and cognitive decline [121, 124]. In addition,
the AD brain exhibits a reduced expression of TGF-βR2,
a specific receptor which correlates with the pathological hallmarks of the disease [125]. When evaluating thepotential of TGF-β1 as a novel biomarker for early AD, it
is essential to consider the differing results obtained fromits measurement in the plasma versus the CSF of AD
patients. AD patients display decreased concentrations ofactive and inactive forms of TGF-β1 in their plasma [126]as well as a decline in its secretion from PBMCs [127].
TGF-β1 levels were found to be elevated in the CSF andbrain of AD patients compared to non-demented individuals, and positively correlated with the extent of cerebrovascular Aβ deposition [128].
Consequently, patients with AD exhibit elevated levelsof TGF-β1 in their CSF [129], while decreased concentrations of both total and cleaved (active) forms of this molecule have been observed in their plasma [130]. Theseseemingly contradictory findings can be clarified by longitudinally assessing TGF-β1 levels at various stages of
AD in future prospective long-term observational studies. We hypothesize that elevated levels of TGF-β1 may
act as a neuroprotective factor in the early phases of AD
pathogenesis, while decreased levels contribute to neurodegeneration and cognitive decline in individuals with
MCI [121]. Interestingly, a study on patients with dementia found lower CSF concentrations of TGF-β1 in individuals with fast disease progression compared to those withslower progression [131]. Genetic investigations haveprovided only preliminary and partial evidence regarding
the deficit of TGF-β1 in AD [121].
The TGF-β1 gene is located on chromosome 19q13.1–3
and contains multiple functional single nucleotide polymorphisms (SNPs) in the upstream and transcript
regions [132]. Two studies demonstrated that the SNPs
at codons + 10 (T/C) and + 25 (G/C), as well as the CC
genotype of the TGF-β1 gene, which are associated with
reduced TGF-β1 levels, have been linked to an increased
conversion from MCI to AD [133, 134], whereas anotherresearch involving oldest-old individuals aged over 75
demonstrated that carriers of at least one minor T allele
displayed a significant decline in cognitive and functional performance in the short-term, while those harboring the CC genotype of the TGF-β1 codon + 10 T > C

Lista et al. Journal of Neuroinflammation(2024) 21:187

polymorphism remained stable [135]. Building on theevidence obtained from AD patients, various studies havebeen conducted in animal models of AD to validate therole of TGF-β1 as both a novel biomarker and a potential
pharmacological target [136]. It has been hypothesizedthat the selective deficit of the canonical TGF-β1/Smadpathway in AD may impair the cross-talk between astrocytes and microglia, subsequently leading to microgliamediated neurodegeneration [136]. APOE ε4 impairs the
microglial response in AD by inducing TGFβ1-mediatedcheckpoints, suggesting a neurobiological link between
APOE ε4 and the deficit of TGFβ1 signaling in the disease process [137]. Despite conflicting findings regarding
TGF-β1 levels at various stages of AD, this anti-inflammatory cytokine has emerged as one of the leading 20
CSF candidate biomarkers associated with the rate ofcognitive decline in dementia patients, as demonstrated
in longitudinal studies [131]. To validate the role of TGFβ1 as a novel biomarker in early AD, future prospective
long-term observational studies are essential.
Other neuroinflammatory biomarkers

Numerous cytokines and chemokines, commonly linked
to inflammation, vascular injury, and angiogenesis, haveemerged as potential neuroinflammatory biomarkers.
Among these, eight can be measured in serum—including basic fibroblast growth factor (bFGF), C-reactive
protein (CRP), interleukin-16 (IL-16), soluble fms-liketyrosine kinase-1 (sFLT-1), soluble intercellular adhesion molecule-1 (sICAM1), the Tie-2 receptor tyrosine
kinase, vascular endothelial growth factor-C (VEGF-C),and vascular endothelial growth factor-D (VEGF-D).
Three others, interleukin-15 (IL-15), monocyte chemoattractant protein-1 (MCP-1), and sFLT-1, are quantifiablein the CSF[138]. The addition of these neuroinflammatory biomarkers to traditional AD biomarkers improved
diagnostic accuracy by 13.9% and 12.5%, respectively, inolder individuals with cognitive decline [139]. However,further studies are needed to confirm their utility in clinical settings.
A multicenter study has highlighted the significanceof complement dysregulation as a potential predictor of
disease progression in MCI [140]. Specifically, the results
revealed higher levels of Factor B enzyme and lower levels of Factor H regulator in MCI progressors as compared
to non-progressors. Collectively, these findings suggestthat the dysregulation of the complement system’s amplification loop may act as an early event that predisposes to
AD progression [140].
Multiple meta-analyses have explored the potential ofvarious molecules as biomarkers for AD. In one metaanalysis, which included 54 studies measuring cytokine
concentrations (40 in peripheral blood and 14 in the

Page 13 of 24

CSF), patients with AD exhibited higher concentrations of IL-6, TNF-α, IL-1β, TGF-β, IL-12, and IL-18 inperipheral blood, and elevated levels of TGF-β in CSF,
compared to healthy controls [141]. Another meta-analysis comprising 175 studies on peripheral blood revealed
increased levels of IL-1β, IL-2, IL-6, IL-18, interferon-γ,
homocysteine, high-sensitivity CRP (hs-CRP), C-X-C
motif chemokine-10, epidermal growth factor, vascularcell adhesion molecule-1, TNF-α converting enzyme,
soluble TNF receptors 1 and 2, α1-antichymotrypsin, as
well as decreased concentrations of IL-1 receptor antagonist and leptin in patients with AD compared to controls[142].
A comprehensive meta-analysis of 170 studies revealed
significantly elevated blood concentrations of various
proteins including hs-CRP, IL-6, soluble tumor necrosis factor receptors 1 and 2 (sTNFR1 and TNFR2),
α1-antichymotrypsin (α1-ACT), IL-1β, and soluble CD40
ligand (sCD40L) in patients with AD compared to controls. Additionally, the CSF concentrations of certain proteins such as IL-10, MCP-1, TGF-β1, sTREM2, YKL-40,
α1-ACT, nerve growth factor, and visinin-like protein-1(VILIP-1) were also found to be higher in AD [143]. Furthermore, patients with MCI exhibited increased peripheral blood concentrations of sTNFR2, IL-6, MCP-1,
and decreased concentrations of IL-8. The authors also
observed elevated CSF concentrations of YKL-40, VILIP1, and sTREM2 in MCI patients compared to controls.
Finally, patients with AD were found to have increased
peripheral blood concentrations of sTNFR1 and sTNFR2
compared to those with MCI [143]. Another meta-analysis comprising 88 studies found increased levels of CRP,
IL-1β, IL-2, IL-6, IL-12, IL-18, MCP-1, MCP 3, IL-8, andinterferon-γ-inducible protein 10 (IP-10) in patients withAD [144]. These findings were at least in part consistent
with a separate meta-analysis involving 13 studies thatindicated an association between inflammatory candidate proteins—including CRP, IL-6, α1-ACT, lipoproteinassociated phospholipase A2, and fibrinogen—and anincreased risk of all-cause dementia, although these biomarkers were not specific to AD [145].

The role of neuroinflammatory biomarkers
in Alzheimer’s disease diagnosis and therapy
Role of neuroinflammatory biomarkers in the diagnostic
work‑up of Alzheimer’s disease

The definitive diagnosis of AD—in the absence of neuropathological confirmation—continues to pose a significant challenge. Despite extensive research into themolecular and biological mechanisms underlying the disease, the effective identification of AD remains an elusive
task. This poses limitations on therapeutic interventions,as they are often initiated after the onset of symptoms.

Lista et al. Journal of Neuroinflammation(2024) 21:187

In this scenario, there is a growing interest in studying
and treating the prodromal stages of AD. One unresolved
question in understanding AD pathophysiology is why aconsiderable percentage of brain Aβ-positive CU individuals do not develop detectable downstream tau pathology and subsequent clinical decline. Recent research has
shown that elevated levels of phosphorylated tau in the
blood are associated with Aβ accumulation in the brain
only in individuals with abnormally high blood levels of
GFAP [114]. These findings suggest that astrocyte reactivity, evaluated through the measurement of plasma
GFAP, is a significant precursor event that connects brain
Aβ accumulation to the onset of tau pathology. This connection may have important implications for the biological characterization of preclinical AD. Furthermore,considering that neurotoxic reactive astrocytes are stimulated by activated microglia [117], the availability of abiomarker for activated microglia becomes essential in
identifying individuals who are at a higher risk of developing AD. While CSF sTREM2 and 18 kDa translocator
protein (TPSO)-PET imaging are effective for identifying
activated microglia, they do not inform about the precise
molecular and functional cellular status. Furthermore, areliable blood biomarker remains elusive. The availabilityof blood-based biomarkers for both activated microglia
and reactive astrocytes could assist in the clinical recognition of MCI and AD, or even earlier stages[138, 146].
Moreover, these biomarkers could facilitate tracking disease progression over time in patients as a part of therapeutic strategies and potentially provide personalized
drug targets for early intervention in MCI and AD cases.

Page 14 of 24

Role of neuroinflammatory biomarkers in anti‑Alzheimer’s
disease trials and individualized therapy

Targeting neuroinflammation may prove to be an
extremely effective strategy for AD prevention and therapy during the preclinical stage before significant neuronal loss occurs. Figure 2 shows the number of ongoing
AD clinical trials with anti-neuroinflammatory agents[12].
Overall, there are 25 ongoing clinical trials targeting
neuroinflammation in AD: four in phase 1, 19 in phase2, and two in phase 3 [masitinib (tyrosine-kinase inhibitor) and NE3107 (insulin-sensitizing agent)]. Promising
results have been observed in several phase I/II clinical trials that targeted TNF-α, TREM2, or CD33. We
strongly advocate for the utilization of neuroinflammatory biomarkers, such as blood GFAP for tracking
reactive astrocytes and CSF-sTREM2 for monitoring
microglial activation, throughout clinical trials [147]. In
our view, these biomarkers present a significant potential for tracking disease progression within the AD continuum in the field of drug development, including
trials with compounds not directly impacting biologicalinflammatory targets. Accordingly, blood GFAP concentrations have already been successfully employed as abiomarker in clinical trials evaluating anti-Aβ monoclonal antibodies, such as lecanemab [148] and donanemab[149]. In general, we are confident that adopting a biomarker-guided strategy for AD treatment, which tailors
specific interventions to relevant molecular pathways,
will enhance therapeutic effectiveness, as witnessed in
the field of oncology. This approach has already seenFig. 2 Presently ongoing clinical trials in AD by mechanism of action of the tested agents. Twenty-five trials are testing anti-neuroinflammatory
agents. AD Alzheimer disease, APOE Apolipoprotein E. Modified from Cummings et al. Alzheimers Dement (N Y). 2024 [12]

Lista et al. Journal of Neuroinflammation(2024) 21:187

application in the NSAID treatment of AD. A post-hoc
analysis of a trial of naproxen and rofecoxib for mild-tomoderate AD demonstrated that those who responded
favorably exhibited a distinct plasma neuroinflammatory
profile (TNF-α, CRP, IL-6 and IL-10) [150]. These results
imply that the use of anti-inflammatory drugs for AD
should be reserved for patients who show clear signs ofsystemic inflammation. A Phase II trial, conducted more
recently, with donanemab—a potent anti-Aβ(p3-42)
monoclonal antibody—exclusively enrolled patients who,as confirmed by [­18F]flortaucipir-PET scans, exhibited
pathologic tau deposition (> 1.10 SUVR), but with quantitative tau levels below a specific upper threshold (1.46
SUVR) [151]. This strategic approach was undertaken
to address concerns surrounding the limited efficacy of
donanemab in advanced disease situations, as suggestedby the presence of extensive tau pathology. Another significant investigation is the AHEAD prevention study,
currently in its fourth year. This research is analyzing theeffects of lecanemab in CN participants at risk of developing AD due to the presence of brain Aβ accumulation,
as evidenced by Aβ-PET scans [152]. This investigation isdivided into two sub-studies (AHEAD 45 and AHEAD 3).
AHEAD 45 focuses on participants exhibiting elevatedbrain Aβ-PET pathology, specifically above 40 Centiloids, measured during the screening phase. In contrast,
AHEAD 3 is being conducted on individuals with intermediate brain Aβ pathology levels, defined as 20 to 40
Centiloids, also measured during the screening process.
The primary purpose of this comprehensive study is
twofold. Firstly, it aims to determine if lecanemab treatment outperforms a placebo in modifying baseline Preclinical Alzheimer Cognitive Composite 5 (PACC5) after
216 weeks of treatment (A45 Trial). Secondly, it seeks toestablish if lecanemab treatment is superior to a placeboin mitigating brain Aβ accumulation, as measured by
PET scans, following 216 weeks of treatment (A3 Trial)[152]. We posit that the integration of a reliable bloodbiomarker of neuroinflammation is essential for theeffective and predictive ATN(I) categorization of the AD
continuum. During the pathological progression of AD,a pivotal moment occurs when innate immune and glial
cells begin to sustain an excessively expressed chronic
inflammatory response. This process acts in synergy withthe accumulation of Aβ and tau proteins, driving synaptotoxicity and neurodegeneration in a self-perpetuating
cycle. The precise timing of this neuroinflammatory shift
in individual cases remains elusive, possibly explaining why past clinical trials exploring anti-inflammatorycompounds have failed to yield successful results. Plasma
GFAP displays a compelling ability to predict individual
clinical AD risk and is thus suggested as a potential preliminary screening tool for AD risk stratification in the

Page 15 of 24

older adult population [153]. The presence of plasma
GFAP “positivity” may be a straightforward indicator
for initiating a comprehensive therapy. This treatment—
which would combine anti-inflammatory drugs withagents that modulate either Aβ or tau—may be particularly applicable to those with preclinical AD or individuals at risk of developing AD.
Risk stratification tools tailored to each individual are
crucial for applying precision medicine principles in AD.
Blood biomarkers for AD offer a promising strategy thatis both time and cost-effective. They hold potential toidentify and categorize patients at risk of developing AD,
thereby enhancing the screening procedures for potential participants in AD clinical trials. Additionally, thesebiomarkers can significantly improve patient management in clinical settings. This includes making informed
decisions about treatment, such as choosing a diseasemodifying therapy based on altered biomarker profiles,
or referring patients to specialized memory clinics forfocused care [19].
Tracking neuroinflammatory biomarkers could also
be crucial for monitoring amyloid-related imaging
abnormalities (ARIA), a significant adverse event associated with anti-Aβ monoclonal antibodies, including
lecanemab and donanemab [154]. These ARIA manifest
as brain edema (ARIA-E), microbleeds, and occasionally large brain hemorrhages (ARIA-H), and have been
associated with some fatalities in clinical trials. ARIA are
considered an inflammatory reaction to cerebral amyloid
angiopathy. Specifically, ARIA-E resembles cerebral amyloid angiopathy-related inflammation, a rare and serious condition caused by auto-antibodies to Aβ. Anti-Aβ
antibodies may bind to vascular amyloid, triggering thecomplement cascade to attack cerebral blood vessels.
This process can create small holes, leading to fluid leaks
and microbleeds. It is recommended to identify preexisting medical disorders that may predispose individuals to
ARIA or increase the likelihood of ARIA-related complications. Such conditions include pre-existing autoimmune or inflammatory disorders, seizures, transientischemic attacks, cerebrovascular disease, or significant
changes in brain white matter.
AD is frequently associated with cerebrovascular disorders, which may contribute to neuronal dysfunction
and death. Notably, both conditions share common risk
factors, including APOE ε4, hyperlipidemia, and obesity [155]. Several lines of evidence support the role ofneuroinflammation and cerebrovascular dysfunctionin AD. A study involving 508 CU older individuals and313 patients with MCI and AD found that CSF levels of
five biomarkers of neuroinflammation and cerebrovascular dysfunction (YKL-40, ICAM-1, VCAM-1, IL-15, andFlt-1) were elevated in AD, even during the preclinicalLista et al. Journal of Neuroinflammation(2024) 21:187

and prodromal stages, and were associated with CSF
tau. Additionally, longitudinal data suggested that higher
levels of these neuroinflammatory and cerebrovascular biomarkers were linked to cognitive decline and anincreased risk of subsequent development of AD [156].

Regulatory perspectives on neuroinflammatory
biomarkers in Alzheimer’s disease
In the past decade, the identification of biomarkers relevant to AD has become a crucial tool in the development of disease-modifying therapies. Regulatory bodies
such as the FDA (https://​www.​fda.​gov/​regul​atory-​infor​
mation/​ s earch-​ f da-​ g uida​ n ce-​ d ocum​ e nts/​ q uali ​ f icat​
ion- ​proce ​ss-​drug-​devel​opment- ​tools-​g uida​nce-​indus​
try-​and-​fda-​staff ) and the European Medicines Agency(EMA)(https://​www.​ema.​europa.​eu/​en/​human-​regul​
atory/ ​ r esea ​ r ch- ​ d evel​ o pment/​ s cien​ t ific-​ a dvice-​ p roto​
col-​a ssis​tance/​novel-​metho​dolog​ies-​bioma​rkers/​opini​
ons-​lette​rs-​suppo​rt-​quali​ficat​ion-​novel-​metho​dolog​ies-​
medic​ine-​devel​opment) have established pathways forthe qualification of these biomarkers to facilitate drug
development. A qualified biomarker may be defined asa”tool that, within the stated context-of-use, can be relied
upon to have a specific interpretation and application
in medical product development and regulatory review”[157]. However, despite the initial EMA opinion on the
CSF biomarkers positive signature, which includes low
Aβ1-42 and high p-tau concentrations, as a predictor for
dementia evolution in individuals with MCI (https://​www.​ema.​e uropa.​e u/​en/​docum​ents/​regul​atory-​proce​dural-​guide​line/​quali​ficat​ion-​opini​on-​alzhe​imers-​disea​
se-​novel-​metho​dolog​ies/​bioma​rkers-​use-​cereb​rospi​nal-​
fluid-​amylo​id-​beta-1-​42-t-​tau-​signa​ture/​posit​ron-​emiss​ion-​tomog​raphy-​amylo​id-​imagi​ng-​posit​ive), only a small
number of biomarkers have undergone a formal regulatory process for qualification. Significantly, the absence ofqualified biomarkers for diagnosing AD, predicting disease prognosis, and evaluating treatment efficacy remains
a notable issue. This can be attributed to our limited
understanding of the neurobiology of AD and its connection to cognitive and behavioral decline over time. The
disease progresses along a continuum of states, which
are not fully characterized presently, and exhibits considerable variability among patients. Consequently, theidentification and validation of prognostic and predictive
biomarkers are urgently required, but their achievement
poses substantial challenges.
The FDA recent approval of aducanumab for the treatment of AD through the accelerated approval pathway
was met with criticism due to the lack of demonstrated
clinical benefit. While the drug induced a reduction in
the Aβ biomarker, the EMA did not replicate the FDA
approval. The recent FDA full approval of lecanemab,

Page 16 of 24

which reduces brain Aβ burden but shows limited cognitive and clinical benefit, further highlights the challenge
of using individual biomarkers as efficacy endpoints in
AD. The results of recent clinical trials in AD indicate theimportance of identifying a broader range of positive biomarker signatures. These should include inflammatory
biomarkers, as well as other markers of brain damage orsusceptibility to damage. Such biomarkers can be used tomonitor and anticipate disease progression across various stages, and to measure the effectiveness of new disease-modifying drugs.

Discussion
In the AD brain, neuroinflammation is a multifaceted biological process that entails the recruitment of
peripheral immune cells, the activation of intracellularsignaling pathways, and the release of various proinflammatory cytokines. The key contributors to the neuroinflammatory process are microglia and astrocytes. Theirinvolvement exhibits distinct phenotypic variations,both spatially and temporally, which can be observed at
different stages of disease progression [99, 158]. Recent
GWAS have provided compelling evidence supporting
the significant involvement of the innate immune system and neuroinflammation in the pathogenesis of AD.
A comprehensive GWAS conducted on over 1 million
participants has specifically highlighted the relevance of
microglia and immune cells in the pathogenesis of LOAD
[159]. Furthermore, the identification of several AD risk
genes associated with immune response and microglia, such as CD33 and TREM2, through GWAS has
shed light on their role in the disease [160]. In addition
to these genes, sTREM2 and YKL-40, as well as otheremerging cytokines, such as IL-6, MCP-1, and TGF-β1
are showing promising potential as inflammatory candidate biomarkers. However, to fully comprehend the clinical implications of these neuroinflammatory biomarkers,
it is paramount to conduct large-scale longitudinal studies across the entire AD continuum [13].
sTREM2 has emerged as a promising biomarker ofactivated microglia and has been validated in longitudinal studies in both pre-clinical and early AD. However, its
widespread use is impeded by the fact that it can be easily
measured in CSF, but not in blood. Despite this limitation, TREM2 is still considered a promising therapeutictarget for AD. One such investigational therapy is AL002,
a humanized monoclonal IgG1 antibody that enhances
TREM2 signaling to improve microglia survival and proliferation [161]. AL002 is currently undergoing investigation in a 96-week, double-blind, placebo-controlled study
that involves 265 patients with early AD (INVOKE-2
study, ClinicalTrials.gov NCT04592874). The primaryobjective of this phase 2 study is to evaluate the impact

Lista et al. Journal of Neuroinflammation(2024) 21:187

of AL002 on disease progression, measured through theClinical Dementia Rating Sum Boxes (CDR-SB).
Numerous cross-sectional and longitudinal studies
have consistently shown the potential of YKL-40 as areliable biomarker of neuroinflammation in AD. YKL40 serves as an indicator of both activated microglia andreactive astrocytes and can be detected in both CSF andblood samples. Notably, several studies in the field of AD
have highlighted the diagnostic significance of plasma
YKL-40 levels in the early stages of dementia, such as
MCI and mild clinical AD [92, 96, 97]. In addition, elevated plasma concentrations of YKL-40 have been foundto be positively associated with cognitive performancein individuals with subjective cognitive complaints [97].
However, it is important to note that increased YKL-40
concentrations in CSF or plasma do not exclusively indicate an inflammatory biomarker specific to AD or otherneurodegenerative diseases. Accordingly, elevated YKL40 concentrations have also been observed in other conditions such as stroke, atrial fibrillation, hypertension,and diabetes, as well as in association with vascular risk
factors [86]. The non-specificity of YKL-40 expression
in various age-related pathological conditions, including neoplastic and cardiovascular diseases, as well as
inflammatory disorders of different etiologies, poses a
constraint on its future application as a biomarker in theolder adult population [84, 162]. Moreover, while CSF
YKL-40 concentrations have shown a moderately positive
correlation with p-tau and t-tau, there was no correlation
with Aβ, further substantiating its lack of specificity forAD [163]. Therefore, when utilizing YKL-40 in diagnostic examinations, it is crucial to gather a comprehensive
medical history of patient comorbidities to avoid misinterpretation of biomarker values [164].
IL-6 shows promise as a potential peripheral inflammatory biomarker for evaluating the severity of cognitive
decline. However, there is currently a lack of a standardized molecular panel of fluid inflammatory biomarkers
that can be effectively used for screening purposes [33].
It is important to note that the literature on inflammatory biomarkers and their ability to track the progressionof AD contains some seemingly contradictory findings.
A recent 10-year longitudinal study involving CU older
individuals identified a positive correlation between CSF
sTREM2 levels and the risk of CDR conversion [165].
Conversely, other studies have found that elevated CSF
sTREM2 levels are associated with a slower cognitive andclinical decline in AD [166] and in Aβ-PET-positive MCI[167]. Therefore, TREM2-related immune activation may
influence the progression of age-related cognitive decline
and AD symptoms differently, depending on the diseasestatus and amyloid pathology. It has been hypothesizedthat throughout the AD continuum, neuroinflammatory

Page 17 of 24

biomarkers in blood and CSF exhibit a complex temporal progression, with distinct profiles for CSF and bloodsTREM2, GFAP, and YKL-40 [168] (Fig. 3).
This complexity accounts for the apparent discrepancies in the results of some neuroinflammatory biomarker
studies and may also partially explain the failure of antiinflammatory therapies across the AD continuum to date.
It is reasonable to assume that anti-inflammatory drugs
were tested without considering the inflammatory status of the trial participants. This situation is analogous to
the initial studies with anti-Aβ drugs, which were tested
in AD patients without assessing their brain Aβ deposition and tau load status. Ideally, future anti-inflammatory
candidates should be tested in homogeneous subject
populations, characterized by reactive astrocytosis (estimated via plasma GFAP levels) and microglial activation(estimated via CSF sTREM2 levels).
A crucial consideration when utilizing AD neuroinflammatory biomarkers is their lack of specificity. For
instance, it is well-established that blood GFAP elevations are not exclusive to AD, as they are also observedin other acute CNS conditions such as ischemic stroke ortraumatic brain injury [169]. Similarly, while low plasmasTREM2 has been associated with Aβ accumulation
and CSF p-tau levels, a comparable decrease has beenreported in vascular dementia [170]. To enhance specificity, a combination of inflammatory biomarkers might bea viable option [139].
However, we posit that the lack of disease specificity inblood biomarkers should not be viewed as a limitation.
Instead, it could serve as a valuable initial screening tool.
A positive result for a specific blood biomarker test could
be interpreted as a non-specific signal of neuroinflammation, neurodegeneration, or Aβ brain deposition, underscoring the need for additional confirmatory testing andfurther clinical examinations [171].
Currently, the AT(N) classification system is extensively
utilized as a biological staging model for AD. It assesses
three specific classes of biomarkers, i.e., Aβ, tau pathology, and neurodegeneration/neuronal injury. Recent
advancements have identified promising blood-based
biomarkers for each category—including Aβ1-42/Aβ1–40
ratio, phosphorylated tau, and NfL. The Alzheimer’s
Association has published recommendations for bloodbased biomarkers, emphasizing the need for longitudinal and observational clinical trials to establish changes
in peripheral biomarkers over time in patients with AD.
These trials should also monitor changes in clinically relevant outcomes, such as cognition and motor functions[172, 173]. Recently, there has been a proposal to enhance
the AT(N) matrix by introducing the ATI(N) system,with the addition of a neuroinflammatory biomarker
denoted as “I”. The Alzheimer’s Association workgroup

Lista et al. Journal of Neuroinflammation(2024) 21:187

Page 18 of 24

Fig. 3 Hypothetical time course profiles of main fluid neuroinflammatory biomarkers (GFAP, sTREM2, and YKL-40) across the AD continuum. The
biomarker levels presented in the graph are referred to their normal range and should not be compared with each other. AD Alzheimer disease, CSF
cerebrospinal fluid, GFAP glial fibrillary acidic protein, MCI mild cognitive impairment, sTREM2 soluble triggering receptor expressed on myeloid cells
2, YKL-40 chitinase-3-like protein 1

is proposing the inclusion of glial GFAP as a biomarker
of inflammation and astrocyte activation in their revised
diagnostic criteria for AD. This proposal is based on thegrowing evidence supporting the role of astrocyte reactivity in the pathogenesis of AD. In the near future, it isanticipated that specific “threshold” serum GFAP levels will be established to define “astrogliosis positivity”
along the AD continuum [171], providing a standardized approach for assessing astrocyte activation in AD
patients. To support this endeavor, a study involving 371
healthy Danish volunteers aged between 21 and 90 years
has already determined the normal range of serum GFAP
levels across different age groups [174]. This expanded
plasma ATI(N) system, in combination with APOE genotyping and cognitive testing, presents an opportunity for
personalized assessment, enabling a therapy approach
tailored to the specific biomarker profiles of patients withAD.

Conclusion and future directions
Recent longitudinal studies have successfully recruitedlarge cohorts of individuals with accurate clinical characterizations, leading to the identification of potentially reliable blood-based candidate biomarkers ofneuroinflammation in AD. These markers offer a practical and non-invasive means of screening and monitoring the inflammatory status of the brain in the AD
continuum and hold potential to identify and categorize
patients at risk of developing AD, thereby enhancing thescreening procedures for potential participants in AD
clinical trials and choosing a disease-modifying therapy
based on altered biomarker profiles [19].
Longitudinal studies suggest that CSF sTREM-2 exhibits a dynamic response linked to microglial activity as thedisease progresses and increased CSF sTREM-2 concentrations are associated with high levels of NfL, indicating
axonal injury [76]. CSF sTREM-2 might be validated asa new biomarker for tracking the progression from preclinical AD/MCI to AD dementia that correlates with theprogression of CSF Aβ and tau. However, the widespreaduse of sTREM-2 is impeded by the fact that it can be easily measured in CSF, but not in blood. Despite this limitation, TREM-2 is still considered a promising therapeutictarget for AD. One such investigational therapy is AL002,
a humanized monoclonal IgG1 antibody that enhances
TREM-2 signaling to improve microglia survival and proliferation [161]. AL002 is currently undergoing investigation in a 96-week, double-blind, placebo-controlled study

Lista et al. Journal of Neuroinflammation(2024) 21:187

that involves 265 patients with early AD (INVOKE-2
study, ClinicalTrials.gov NCT04592874). The primaryobjective of this phase 2 study is to evaluate the impact
of AL002 on disease progression, measured through theClinical Dementia Rating Sum Boxes (CDR-SB).
According to cross-sectional and longitudinal studies YKL-40 possesses a good potential as a reliable biomarker of neuroinflammation in AD, because its levels
are increased in preclinical AD [92] and linked to biomarkers of neurodegeneration (total tau, t-tau), taumediated toxicity (p-tau) [89]. YKL-40 might be helpful
in distinguishing individuals with MCI who will convert
to AD from those who will remain stable at 5 years [86].
Additionally, serum concentrations of YKL-40 can effectively distinguish between CU individuals and those withmild dementia, with a sensitivity and specificity of 85%[164], although it is not clinically useful in differentiating the characteristic AD phenotype and increased YKL40 concentrations in CSF or plasma have been found invarious age-related pathological conditions, posing a
constraint on its future application as a biomarker in theolder population [84].
When considering all neuroinflammatory biomarkers
and all recent longitudinal studies, GFAP emerges as themost promising biomarker, effectively tracking reactive
astrocytes and enabling the identification of Aβ-positive
CU individuals who exhibit early signs of p-tau pathology, with its plasma concentrations being indicative ofearly-stage dementia and in MCI who progress into AD[175]. By assessing a combination of plasma biomarkers,
such as the ratio between the Aβ1–42 and Aβ1-40, p-tau217,
NfL, and GFAP concentrations, it may be possible to create a novel effective panel for assessing the risk of developing AD [19, 116].
According to the evidence discussed in the present
review, we believe that enhancing the AT(N) matrix
by introducing the ATI(N) system, with the addition ofneuroinflammatory biomarkers denoted as “I” (CSF andblood “I” biomarkers), such as GFAP, might significantly
improve, in combination with the other biomarkers andcognitive testing, both the early diagnosis of AD and thedevelopment of disease-modifying drugs in future AD
clinical trials.
Abbreviations
AD	Alzheimer’s disease
ADAD	Autosomal dominant AD
APOE	Apolipoprotein E gene
ARIA	Amyloid-related imaging abnormalities
Aβ	Amyloid-beta
BBB	Blood–brain barrier
bFGF	BBasic fibroblast growth factor
CDR-SB	Clinical Dementia Rating Sum Boxes
CHI3L1 (YKL-40)	Chitinase-3-like protein 1
CNS	Central nervous system
CRP	C-reactive protein

Page 19 of 24

CSF	Cerebrospinal fluid
CU	Cognitively unimpaired
FDA	Food and Drug Administration
GFAP	Glial fibrillary acidic protein
GWAS	Genome-wide association studies
hs-CRP	High-sensitivity CRP
IL-15	Interleukin-15
IL-16	Interleukin-16
IL-1β	Interleukin-1beta
IP-10	Interferon-γ-inducible protein 10
LOAD	Late-onset AD
MCI	Mild cognitive impairment
MCP-1	Monocyte chemoattractant protein-1
MMSE	Mini-Mental State Examination
NfL	Neurofilament light chain
NGF	Nerve growth factor
PACC5	Preclinical Alzheimer Cognitive Composite 5
PBMCs	Peripheral blood mononuclear cells
sCD40L	Soluble CD40 ligandsFLT-1	Soluble fms-like tyrosine kinase-1
sICAM1	Soluble intercellular adhesion molecule-1
SNPs	Single nucleotide polymorphisms
sTREM-2	Soluble triggering receptor expressed on myeloid cells 2
TGF-β1	Transforming growth factor-beta 1
TNF-α	Tumor necrosis factor-alpha
TNFR1	Tumor necrosis factor receptor 1
TNFR2	Tumor necrosis factor receptor 2
TPSO	Translocator protein
VEGF-C	Vascular endothelial growth factor-C
VEGF-D	Vascular endothelial growth factor-D
VILIP-1	Visinin-like protein-1α1-ACT​	α1-Antichymotrypsin
Acknowledgements
Not applicable.
Author contributions
S.L., B.P.I., M.T.H., and F.C.: project administration and conceptualization of themanuscript. S.L., B.P.I., M.G., A.F., C.I., and F.C.: literature search. S.L., B.P.I., M.G.,
A.F., A.S.-L., and M.T.H.: writing—original draft. S.L., B.P.I., and C.I.: preparation of
the figures. E.E., P.M., S.L.-O., J.M.-H., A.G., G.C., M.M., and D.M.: writing—review& editing. S.L., B.P.I., M.T.H., and F.C.: supervision of the manuscript. All Authors
reviewed and approved the final version of the manuscript.
Funding
Research by S.L.-O. is funded by the Spanish Ministry of Science and Innova‑
tion (Grant number FPU19/02117).
Availability of data and materials
Not applicable.

Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
B.P.I. is an employee at Chiesi Farmaceutici. He is listed among the inventors of
a number of Chiesi Farmaceutici’s patents of anti-Alzheimer drugs. E.E. is theunique owner of 2E Science, a for-profit private scientific company. Neither E.E.
nor 2E Science have any commercial interest or financial tie in relation withthis article. S.L., M.G., A.F., P.M., S.L.-O., J.M.-A., A.G., G.C., M.M., D.M., A.S.-L., C.I.,
M.T.H., and F.C. declare no competing interests.
Author details
1
i+HeALTH Strategic Research Group, Department of Health Sciences,
Miguel de Cervantes European University (UEMC), 47012 Valladolid,

Lista et al. Journal of Neuroinflammation(2024) 21:187

Spain. 2 Department of Research and Development, Chiesi Farmaceutici,
43122 Parma, Italy. 3 Oasi Research Institute-IRCCS, 94018 Troina, Italy. 4 2E Sci‑ence, 27038 Robbio, Italy. 5 Studio Minoretti, 23848 Oggiono, LC, Italy. 6 CMRR,
Memory Resources and Research Center, Montpellier University of Excellence
i-site, 34295 Montpellier, France. 7 Department of Drug and Health Sciences,
University of Catania, 95125 Catania, Italy. 8 Department for Life Quality Studies,
Alma Mater Studiorum, University of Bologna, 40126 Bologna, Italy. 9 Depart‑
ment of Physiology and Pharmacology, Sapienza University, 00185 Rome, Italy.
10Physical Activity and Health Research Group (PaHerg), Research Instituteof the Hospital, 12 de Octubre (‘imas12’), 28041 Madrid, Spain. 11 Depart‑
ment of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy.
12
Luxembourg Centre for Systems Biomedicine, University of Luxembourg,
4367 Esch‑Belval, Luxembourg.
Received: 29 May 2024 Accepted: 28 June 2024

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