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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Aging Neurosci.</journal-id>
<journal-title>Frontiers in Aging Neuroscience</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Aging Neurosci.</abbrev-journal-title>
<issn pub-type="epub">1663-4365</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnagi.2024.1380237</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Aging Neuroscience</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Biofluid biomarkers for Alzheimer&#x2019;s disease</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes"><name><surname>Wang</surname> <given-names>Sensen</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2646187/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes"><name><surname>Xie</surname> <given-names>Sitan</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
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</contrib>
<contrib contrib-type="author"><name><surname>Zheng</surname> <given-names>Qinpin</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author"><name><surname>Zhang</surname> <given-names>Zhihui</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Wang</surname> <given-names>Tian</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1438281/overview"/>
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<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
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<contrib contrib-type="author" corresp="yes"><name><surname>Zhang</surname> <given-names>Guirong</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
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</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Shandong Yinfeng Academy of Life Science</institution>, <addr-line>Jinan, Shandong</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation, Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University</institution>, <addr-line>Yantai, Shandong</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0002">
<p>Edited by: Urszula Wojda, Polish Academy of Sciences, Poland</p>
</fn>
<fn fn-type="edited-by" id="fn0003">
<p>Reviewed by: Enrica Caterina Pietronigro, University of Verona, Italy</p>
<p>Aashutosh Shetti, Northwestern University, United States</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Tian Wang, <email>bluewt2000@163.com</email>; Guirong Zhang, <email>guirong_zhang@126.com</email></corresp>
<fn fn-type="equal" id="fn0001">
<p><sup>&#x2020;</sup>These authors share first authorship</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>10</day>
<month>04</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>16</volume>
<elocation-id>1380237</elocation-id>
<history>
<date date-type="received">
<day>01</day>
<month>02</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>03</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2024 Wang, Xie, Zheng, Zhang, Wang and Zhang.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Wang, Xie, Zheng, Zhang, Wang and Zhang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Alzheimer&#x2019;s disease (AD) is a multifactorial neurodegenerative disease, with a complex pathogenesis and an irreversible course. Therefore, the early diagnosis of AD is particularly important for the intervention, prevention, and treatment of the disease. Based on the different pathophysiological mechanisms of AD, the research progress of biofluid biomarkers are classified and reviewed. In the end, the challenges and perspectives of future research are proposed.</p>
</abstract>
<kwd-group>
<kwd>Alzheimer&#x2019;s disease</kwd>
<kwd>diagnosis</kwd>
<kwd>biofluid</kwd>
<kwd>biomarkers</kwd>
<kwd>neurodegenerative diseases</kwd>
</kwd-group>
<counts>
<fig-count count="1"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="236"/>
<page-count count="16"/>
<word-count count="16560"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Alzheimer's Disease and Related Dementias</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1"><label>1</label>
<title>Introduction</title>
<p>Alzheimer&#x2019;s disease (AD) is the most common type of dementia, which accounts for 60&#x2009;~&#x2009;80% of all cases (<xref ref-type="bibr" rid="ref58">Gauthier et al., 2022</xref>). According to the &#x201C;World Alzheimer&#x2019; Report in 2019,&#x201D; there were about 55 million dementia patients in the world, and this number was expected to reach 152 million by 2055 (<xref ref-type="bibr" rid="ref2">Alzheimer&#x2019;s Disease International, 2019</xref>). In 2019, the global societal cost of dementia was around 1.3 trillion US dollars, of which 50% was from the economic value of unpaid care. The 2017 World Health Assembly (WHA) recognized dementia as a public health priority (<xref ref-type="bibr" rid="ref219">World Health Organization, 2017</xref>). Nowadays, dementia has become one of the biggest public health challenges in the world.</p>
<p>AD can be divided into early-onset AD (EOAD) and late-onset AD (LOAD) at the age boundary of 60 or 65. It could also be classified into familial AD (FAD) and sporadic AD (SAD) based on the family history (<xref ref-type="bibr" rid="ref222">Xie et al., 2022</xref>). LOAD is mainly SAD, accounting for around 95% of all cases. EOAD is relatively rare, which accounts for less than 5% of AD (<xref ref-type="bibr" rid="ref2">Alzheimer&#x2019;s Disease International, 2019</xref>). <xref ref-type="bibr" rid="ref90">Jia et al. (2022)</xref> reported a 19-year-old AD patient with the memory impairment occurring at the age of 17, which was the youngest probable AD case in the world.</p>
<p>The amyloid plaques and the neurofibrillary tangles (NFT) are the two main pathological characteristics of AD (<xref ref-type="bibr" rid="ref16">Blennow et al., 2006</xref>; <xref ref-type="bibr" rid="ref93">Kang et al., 2022</xref>; <xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>). The amyloid plaques are formed by deposition of extracellular &#x03B2;-amyloid protein (A&#x03B2;), and the NFT is induced by intracellular tau hyperphosphorylation. The etiology of AD is still unclear. However, it is generally believed that AD is induced by multiple factors, e.g., genetics, biology, environment, and social psychology (<xref ref-type="bibr" rid="ref202">Vermunt et al., 2019</xref>; <xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). The potential mechanism of A&#x03B2;-induced neurodegeneration is always the research focus. Human soluble A&#x03B2; dimers and trimers induce progressive loss of hippocampal synapses. When exposes to picomolar level of soluble A&#x03B2; oligomers, pyramidal neurons in rat brain slice significantly reduce the density of dendritic spines and the number of electrophysiologically active synapses (<xref ref-type="bibr" rid="ref170">Shankar et al., 2007</xref>). A&#x03B2; could directly incorporate into neuronal membranes of hypothalamic neurons, and participate in the formation of calcium-permeable pores, leading to an increase in intracellular calcium concentration of GT1-7 cells. Therefore, the disruption of calcium homeostasis by &#x201C;A&#x03B2;-channels&#x201D; is recognized as the molecular basis for A&#x03B2; neurotoxicity. Previous studies indicated that the lipid composition of cell membrane played an important role in the formation of this channel (<xref ref-type="bibr" rid="ref98">Kawahara and Kuroda, 2000</xref>). Normally, tau proteins bind to microtubules for maintaining the stability of cytoskeleton. The hyperphosphorylated tau aggregates to form paired helical filaments, which have fewer binding sites and unable to attach to microtubules, thus forming NFT (<xref ref-type="bibr" rid="ref116">Liu et al., 2019</xref>). NFT disintegrates the microtubule network of nerve cells, resulting in the inhibition of cell biochemical communication, the destruction of the cytoskeleton, and ultimately the production of neurotoxicity (<xref ref-type="bibr" rid="ref178">Srivastava et al., 2021</xref>). Research data showed that A&#x03B2; induced the spread of tau pathology in an unknown way leading to neuronal death (<xref ref-type="bibr" rid="ref118">Long and Holtzman, 2019</xref>; <xref ref-type="bibr" rid="ref96">Karran and De Strooper, 2022</xref>). Once A&#x03B2; accumulation exceeding a specific threshold, the spread of tau pathology was significantly accelerated (<xref ref-type="bibr" rid="ref96">Karran and De Strooper, 2022</xref>). However, the hypothesis that the interaction between A&#x03B2; and tau leads to cytopathology is still required further investigation.</p>
<p>Since the conceptual framework of preclinical AD was officially proposed by the National Institute of Aging and the Alzheimer&#x2019;s Association (NIA-AA) in 2011, accumulating data suggested that cognitive decline occurred continuously and progressively over a long period (<xref ref-type="bibr" rid="ref82">Jack et al., 2018</xref>). For example, the whole course of AD for a 70-year-old person could take approximately 15&#x2013;25&#x2009;years, including ~10-year asymptomatic stage (preclinical stage), 4-year mild cognitive impairment, and 6-year for ultimately developing into dementia (<xref ref-type="bibr" rid="ref166">Scheltens et al., 2021</xref>). Therefore, the measurement of AD biomarker should be a continuous process that begins before symptom appearance (<xref ref-type="bibr" rid="ref53">Fleisher et al., 2015</xref>; <xref ref-type="bibr" rid="ref82">Jack et al., 2018</xref>).</p>
<p>Cerebrospinal fluid (CSF) directly reflects pathological changes in brain. Core CSF biomarkers of AD include A&#x03B2;<sub>42</sub>, total tau protein (T-tau) and P-tau. A&#x03B2;<sub>42</sub> reflects cortical amyloid deposition. T-tau indicates the density of neurodegeneration, and P-tau links to the pathological changes in NFT. The increased concentration of CSF T-tau and P-tau was found in AD patients (<xref ref-type="bibr" rid="ref158">Reitz and Mayeux, 2014</xref>), and their diagnostic accuracy was around 85&#x2013;90% (<xref ref-type="bibr" rid="ref204">Visser et al., 2009</xref>). However, the CSF or imaging analysis of AD biomarkers is either invasive or expensive (e.g., 10,000 RMB/per time for positron emission tomography (PET), 1,500 RMB/per time for magnetic resonance imaging (MRI), 300 RMB/per time for computed tomography (CT), 1,000&#x2013;3,000 RMB/per time for CSF examination), or both (<xref ref-type="bibr" rid="ref192">Teunissen et al., 2022</xref>).</p>
<p>Based on the characteristics of accessibility, sampling technology, repeatability and cost-effectiveness, blood biomarkers have more advantages than CSF and imaging analysis (<xref ref-type="bibr" rid="ref19">Blennow and Zetterberg, 2018</xref>). However, the detection of AD biomarkers in blood is much more complex than in CSF (<xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). First, there is a blood&#x2013;brain barrier (BBB) in the human body. The capillary endothelium in BBB lacks pores (<xref ref-type="bibr" rid="ref199">Ueno et al., 2016</xref>), and therefore ions and polar molecules could only cross the BBB in the presence of some transport proteins (<xref ref-type="bibr" rid="ref66">Haas, 2018</xref>). However, the transporters that are responsible for transporting tau through BBB have not yet been identified (<xref ref-type="bibr" rid="ref199">Ueno et al., 2016</xref>). When the axon is damaged, proteins are released from the extracellular space of the brain and only a small fraction could enter the bloodstream. These brain proteins are cleaved, modified, and degraded before or after passing through BBB (<xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). Second, the blood-cerebrospinal fluid barrier (BCB) is another important barrier. BCB is porous, so small peptides and hydrophilic molecules could pass through it. Due to the death of neuronal cells and intracellular high concentration, tau is firstly released to CSF (<xref ref-type="bibr" rid="ref191">Tarasoff-Conway et al., 2015</xref>), and then enters the blood through the barrier (<xref ref-type="bibr" rid="ref66">Haas, 2018</xref>). Because of the existence of BBB and BCB, there is a difference on the concentration between CSF and blood biomarkers. Third, plasma contains multiple background proteins. Some of them are at high levels. Therefore, the analytical techniques of blood samples should have a high sensitivity and specificity in order to detect a small quantity of biomarkers in the complex backgrounds (<xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>).</p>
<p>In this review, the traditional and emerging AD biomarkers are summarized and categorized according to main AD pathologies such as amyloidosis, NFT, neurodegeneration, synaptic dysfunction, neuroinflammation, and BBB breakdown (<xref ref-type="fig" rid="fig1">Figure 1</xref>). The physiological function and the biofluid level of these markers are described. In addition, the research of some biomarkers on the other neurodegenerative diseases are also reviewed in this article.</p>
<fig position="float" id="fig1"><label>Figure 1</label>
<caption>
<p>Classification of AD biofluid biomarkers described in this review based on different pathophysiological mechanisms. The inner ring indicates different potential mechanisms. The outer ring lists the biomarkers. Biomarkers with different colors present the corresponding research in different biological matrices. Black, CSF and blood; Blue, CSF; Red, blood. A&#x03B2;<sub>42</sub>, &#x03B2;-amyloid 42; A&#x03B2;<sub>40</sub>, &#x03B2;-amyloid 40; BACE1, &#x03B2;-secretase enzyme; BIN1, Bridging integrator 1; NfL, Neurofilament Light Chain; NFT, Neurofibrillary tangles; VILIP-1, Visinin-like Protein 1; SNAP-25, Synaptosome-associated protein 25; NPTX-2, Neuronal pentraxin 2; GAP-43, Growth-associated protein 43; NG, Neurogranin; TREM2, Triggering receptor 2; sTREM2, Soluble Triggering receptor 2; GFAP, Glial fibrillary acidic protein; NRG-1, Neuregulin-1; YKL-40, Human cartilage glycoprotein-39; TRAIL, TNF-related apoptosis-inducing ligand; PDGFR&#x03B2;, Platelet-derived growth factor receptor-&#x03B2;; BBB, Blood&#x2013;brain barrier.</p>
</caption>
<graphic xlink:href="fnagi-16-1380237-g001.tif"/>
</fig>
</sec>
<sec id="sec2"><label>2</label>
<title>Biomarkers of amyloidosis</title>
<sec id="sec3"><label>2.1</label>
<title>A&#x03B2;<sub>42</sub></title>
<p>A&#x03B2;<sub>40</sub> and A&#x03B2;<sub>42</sub> are the most common subtypes in human. Due to the expanded C-terminal, A&#x03B2;<sub>42</sub> is highly hydrophobic and easier to aggregate than A&#x03B2;<sub>40</sub> (<xref ref-type="bibr" rid="ref118">Long and Holtzman, 2019</xref>). The level of CSF A&#x03B2;<sub>42</sub> in preclinical stage, mild cognitive impairment (MCI), and AD with dementia symptoms was lower than those in control groups (<xref ref-type="bibr" rid="ref12">Bateman et al., 2012</xref>). It could decrease to around 50% of the healthy individuals (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="bibr" rid="ref143">Olsson et al., 2016</xref>). A neuropathological examination showed that a decrease in CSF A&#x03B2;<sub>42</sub> was associated with an increase in brain amyloid plaques (<xref ref-type="bibr" rid="ref181">Strozyk et al., 2003</xref>). Elderly persons with a decrease of CSF A&#x03B2;<sub>42</sub> were also A&#x03B2;-PET positive, and vice versa (<xref ref-type="bibr" rid="ref51">Fagan et al., 2006</xref>). The studies indicated that a reduction in CSF A&#x03B2;<sub>42</sub> preceded the formation of plaques (<xref ref-type="bibr" rid="ref148">Palmqvist et al., 2016</xref>; <xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). Thus, CSF A&#x03B2;<sub>42</sub> is considered as a robust biomarker of early AD diagnosis. A decrease in CSF A&#x03B2;<sub>42</sub>, coupled with an increase in T-tau and P-tau could help to identify the symptomatic AD (<xref ref-type="bibr" rid="ref17">Blennow and Hampel, 2003</xref>). Low level of CSF A&#x03B2;<sub>42</sub>, rather than high level of T-tau, could predict cognitive decline (<xref ref-type="bibr" rid="ref180">Stomrud et al., 2007</xref>). In addition, a significant decrease in CSF A&#x03B2;<sub>42</sub> was observed in Creutzfeldt-Jakob disease (CJD), multiple system atrophy (MSA), and amyotrophic lateral sclerosis (ALS) (<xref ref-type="bibr" rid="ref78">Holmberg et al., 2003</xref>), which indicated that CSF A&#x03B2;<sub>42</sub> could be influenced by other factors besides plaque formation (<xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>).</p>
<table-wrap position="float" id="tab1"><label>Table 1</label>
<caption>
<p>Summarized information of AD amyloidosis biofluid biomarkers presented in this review.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Pathophysiological mechanism</th>
<th align="left" valign="top">Biomarker</th>
<th align="left" valign="top">Biological matrices</th>
<th align="left" valign="top">Trend</th>
<th align="left" valign="top">Purpose</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="12">Amyloidosis</td>
<td align="left" valign="middle" rowspan="2">A&#x03B2;<sub>42</sub></td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">Decrease (<xref ref-type="bibr" rid="ref143">Olsson et al., 2016</xref>)</td>
<td align="left" valign="middle">Diagnosis (<xref ref-type="bibr" rid="ref82">Jack et al., 2018</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood</td>
<td align="left" valign="middle">Controversial (<xref ref-type="bibr" rid="ref130">Mayeux et al., 2003</xref>; <xref ref-type="bibr" rid="ref138">Nakamura et al., 2018</xref>)</td>
<td align="left" valign="middle">Research (<xref ref-type="bibr" rid="ref209">Wang J. et al., 2018</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">A&#x03B2;<sub>40</sub></td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">No significant change (<xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>; <xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood</td>
<td align="left" valign="middle">Decrease (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub></td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">Decrease (<xref ref-type="bibr" rid="ref168">Schindler et al., 2019</xref>)</td>
<td align="left" valign="middle">Diagnosis (<xref ref-type="bibr" rid="ref82">Jack et al., 2018</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood</td>
<td align="left" valign="middle">Decrease (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>)</td>
<td align="left" valign="middle">Research (<xref ref-type="bibr" rid="ref168">Schindler et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">T-tau/A&#x03B2;<sub>42</sub></td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle" rowspan="2">Increase (<xref ref-type="bibr" rid="ref94">Kaplow et al., 2020</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref94">Kaplow et al., 2020</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">P-tau181/A&#x03B2;<sub>42</sub></td>
<td align="left" valign="middle">CSF</td>
</tr>
<tr>
<td align="left" valign="middle">APP669-711/A&#x03B2;<sub>42</sub></td>
<td align="left" valign="middle">Blood</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref138">Nakamura et al., 2018</xref>)</td>
<td align="left" valign="middle">Research (<xref ref-type="bibr" rid="ref138">Nakamura et al., 2018</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">BACE1</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle" rowspan="2">Increase (<xref ref-type="bibr" rid="ref32">Cervellati et al., 2020</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref47">Decourt and Sabbagh, 2011</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood</td>
</tr>
<tr>
<td align="left" valign="middle">BIN1</td>
<td align="left" valign="middle">Blood</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref186">Sun et al., 2013</xref>)</td>
<td align="left" valign="middle">Research (<xref ref-type="bibr" rid="ref186">Sun et al., 2013</xref>)</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Plasma A&#x03B2; analysis is one of the most widely applied peripheral biomarker tests of AD (<xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>). Plasma and CSF A&#x03B2;<sub>42</sub> had a weak positive correlation, while plasma A&#x03B2;<sub>42</sub> levels and brain A&#x03B2; deposition had a negative correlation (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>). The research results regarding the relationship between plasma A&#x03B2;<sub>42</sub> and cognitive impairment were not consistent. Some studies showed decreased plasma A&#x03B2;<sub>42</sub> in MCI and AD (<xref ref-type="bibr" rid="ref138">Nakamura et al., 2018</xref>), while others reported increased A&#x03B2;<sub>42</sub> level and following decreased trend before or at the beginning of cognitive decline (<xref ref-type="bibr" rid="ref130">Mayeux et al., 2003</xref>). The inconsistent results are probably caused by differences in sample inclusion and exclusion criteria, as well as the analytical methods (<xref ref-type="bibr" rid="ref209">Wang J. et al., 2018</xref>). Elevated levels of plasma A&#x03B2;<sub>42</sub> and A&#x03B2;<sub>40</sub> were also associated with other diseases, such as hypertension, diabetes and ischemic heart disease, indicating significant differences in metabolic process of amyloid proteins between blood and brain (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>). Despite these differences, all studies confirmed the changes of blood amyloid proteins at the early stages of AD. In the future, the association between AD pathology and blood amyloid protein is required further exploration to promote its clinical application.</p>
</sec>
<sec id="sec4"><label>2.2</label>
<title>A&#x03B2;<sub>40</sub></title>
<p>A&#x03B2;<sub>40</sub> is the most abundant protein fragment hydrolyzed from APP. The concentration of CSF A&#x03B2;<sub>40</sub> had no significant difference during the development of AD (<xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). Similar to A&#x03B2;<sub>42</sub>, there was a weak positive correlation between plasma and CSF A&#x03B2;<sub>40</sub> (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>). Although A&#x03B2;<sub>40</sub> does not have the same strong cytotoxicity as A&#x03B2;<sub>42</sub>, A&#x03B2;<sub>40</sub> aggregates could be detected in cerebral amyloid vasculopathy (<xref ref-type="bibr" rid="ref4">Attems et al., 2011</xref>). The decreased plasma concentration of A&#x03B2;<sub>40</sub> was observed in AD patients compared with controls (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>). Biochemical and molecular simulation showed that A&#x03B2;<sub>40</sub> inhibited the aggregation of A&#x03B2;<sub>42</sub> (<xref ref-type="bibr" rid="ref84">Jan et al., 2008</xref>).</p>
</sec>
<sec id="sec5"><label>2.3</label>
<title>A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub></title>
<p>The impact of total A&#x03B2; variation could be neutralized through normalization of A&#x03B2;<sub>42</sub> by A&#x03B2;<sub>40</sub> (<xref ref-type="bibr" rid="ref109">Lewczuk et al., 2004</xref>). Several studies showed that CSF A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> could better diagnose, differentiate, and monitor AD than CSF A&#x03B2;<sub>42</sub> (<xref ref-type="bibr" rid="ref75">Hansson et al., 2019</xref>). CSF A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> and A&#x03B2;-PET positive had a good correlation (<xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). Compared to negative A&#x03B2;-PET population, the CSF A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> level of positive A&#x03B2;-PET individuals decreased (<xref ref-type="bibr" rid="ref168">Schindler et al., 2019</xref>). PD and dementia with Lewy body (DLB) had higher level of CSF A&#x03B2;<sub>40</sub>. Therefore, A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> could help to distinguish AD from these diseases (<xref ref-type="bibr" rid="ref141">Nutu et al., 2013</xref>; <xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>). The combined application of CSF A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> and other CSF biomarkers, e.g., T-tau or P-tau, gave a better prediction of AD (<xref ref-type="bibr" rid="ref8">Baldeiras et al., 2018</xref>) and the conversion from MCI to AD (<xref ref-type="bibr" rid="ref8">Baldeiras et al., 2018</xref>; <xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>). Thus, CSF A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> is proposed as a promising biomarker for preclinical AD diagnosis (<xref ref-type="bibr" rid="ref75">Hansson et al., 2019</xref>; <xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>).</p>
<p>In a 719-person cohort study, the plasma concentration of A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> significantly decreased in MCI and AD patients (<xref ref-type="bibr" rid="ref87">Janelidze et al., 2016b</xref>). <xref ref-type="bibr" rid="ref145">Ovod et al. (2017)</xref> reported that plasma A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> was decreased in patients with cerebral amyloidosis. Cognitive decline and the risk of AD progression were associated with low plasma A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> levels (<xref ref-type="bibr" rid="ref201">Verberk et al., 2020</xref>). Plasma A&#x03B2;<sub>42</sub> alone was not an accurate biomarker for AD brain pathology, while A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> could give a better prediction (<xref ref-type="bibr" rid="ref145">Ovod et al., 2017</xref>; <xref ref-type="bibr" rid="ref168">Schindler et al., 2019</xref>). Moreover, plasma A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> was associated with A&#x03B2;-PET (<xref ref-type="bibr" rid="ref168">Schindler et al., 2019</xref>). Cognitively normal individuals with declined A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> were observed within A&#x03B2;-PET-negative groups, indicating the early stage of AD before plaque formation (<xref ref-type="bibr" rid="ref168">Schindler et al., 2019</xref>). A mathematical simulation study suggested that the risk of positive A&#x03B2;-PET for the above population was 15 times higher than those with normal plasma A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> in the next 6&#x2009;years (<xref ref-type="bibr" rid="ref168">Schindler et al., 2019</xref>). Additionally, plasma A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>40</sub> and A&#x03B2;<sub>42</sub>/A&#x03B2;<sub>38</sub> had higher accuracy than A&#x03B2;<sub>42</sub> in distinguishing AD from DLB, PD, or subcortical vascular dementia (VaD) (<xref ref-type="bibr" rid="ref88">Janelidze et al., 2016c</xref>).</p>
</sec>
<sec id="sec6"><label>2.4</label>
<title>Other A&#x03B2; ratios</title>
<p>Elevated CSF T-tau/A&#x03B2;<sub>42</sub> or P-tau181/A&#x03B2;<sub>42</sub> indicated an obvious AD brain pathology (<xref ref-type="bibr" rid="ref94">Kaplow et al., 2020</xref>). CSF A&#x03B2;<sub>42</sub>/P-tau181 showed high accuracy in predicting the progression from MCI to AD (<xref ref-type="bibr" rid="ref27">Buchhave et al., 2012</xref>; <xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>). A study based on mass spectrometry suggested that the plasma levels of APP669-711/A&#x03B2;<sub>42</sub> and A&#x03B2;<sub>40</sub>/A&#x03B2;<sub>42</sub> in A&#x03B2;-PET-positive individuals were higher than those with negative A&#x03B2;-PET scan (<xref ref-type="bibr" rid="ref138">Nakamura et al., 2018</xref>). These two ratios were associated with the levels of CSF A&#x03B2;<sub>42</sub> (<xref ref-type="bibr" rid="ref92">Kaneko et al., 2014</xref>; <xref ref-type="bibr" rid="ref138">Nakamura et al., 2018</xref>), and they could be used to predict the brain A&#x03B2; burden (<xref ref-type="bibr" rid="ref138">Nakamura et al., 2018</xref>).</p>
</sec>
<sec id="sec7"><label>2.5</label>
<title>BACE1</title>
<p>BACE1, also known as &#x03B2;-secretase or &#x03B2;-site APP-lyase 1, is encoded by <italic>BACE1</italic> gene, which is primarily expressed in neurons of brain and responsible for A&#x03B2; production (<xref ref-type="bibr" rid="ref200">Vassar et al., 1999</xref>). It was reported that the increase of <italic>BACE1</italic> gene expression or the abnormal function of &#x03B2;-secretase was one of the earliest processes in AD (<xref ref-type="bibr" rid="ref224">Yang et al., 2003</xref>). Knocking out <italic>BACE1</italic> in mice resulted in a significant decrease in A&#x03B2; and CTF&#x03B2; concentration (a 99-amino acid fragment starting with the N-terminal aspartic acid residue of A&#x03B2;) in the brain (<xref ref-type="bibr" rid="ref131">McConlogue et al., 2007</xref>). In the SAD brain, the expression of BACE1 significantly increased (<xref ref-type="bibr" rid="ref224">Yang et al., 2003</xref>). The CSF level of BACE1 protein of AD patients were significantly elevated (<xref ref-type="bibr" rid="ref32">Cervellati et al., 2020</xref>). The activity of CSF BACE1 was higher in the individuals with the conversion from MCI to AD than those without (<xref ref-type="bibr" rid="ref226">Zetterberg et al., 2008</xref>). A recent research (<xref ref-type="bibr" rid="ref73">Hampel et al., 2021</xref>) and two large-scale cohort studies (<xref ref-type="bibr" rid="ref236">Zuliani et al., 2020</xref>) presented similar trend of CSF BACE1 in peripheral blood, with a 30% increase in serum of AD compared to the control group. In <italic>APP/PS-1</italic> transgenic mice, abnormal BACE1 expression in the retina predated behavioral defects. Therefore, BACE1 could be used as a sensitive biomarker for the early diagnosis of AD (<xref ref-type="bibr" rid="ref47">Decourt and Sabbagh, 2011</xref>; <xref ref-type="bibr" rid="ref66">Haas, 2018</xref>). However, the application of CSF BACE1 as a clinical AD biomarker is limited by its inter-subject variability and technical difference of assay in the lab (<xref ref-type="bibr" rid="ref72">Hampel et al., 2020</xref>). The research focus is mainly on the <italic>BACE1</italic> gene rather than the level of BACE1 protein in the other neurodegenerative diseases such as PD (<xref ref-type="bibr" rid="ref110">Li et al., 2020</xref>).</p>
</sec>
<sec id="sec8"><label>2.6</label>
<title>BIN1</title>
<p>Bridging integrator 1 (BIN1) is a member of amphiphysin proteins family. It is associated with the cytoskeleton and cell membrane. BIN1 plays an important role in the nervous system (<xref ref-type="bibr" rid="ref185">Sudwarts et al., 2022</xref>). BIN1 is widely expressed in mice and human brain (<xref ref-type="bibr" rid="ref133">Miyagawa et al., 2016</xref>). It participates in the regulation of endocytose (<xref ref-type="bibr" rid="ref213">Wechsler-Reya et al., 1998</xref>), and it is important in intracellular vesicles sorting (<xref ref-type="bibr" rid="ref151">Pant et al., 2009</xref>). Previous study showed that BIN1 affected the AD molecular pathobiology through the regulation membrane trafficking of AD-related proteins (<xref ref-type="bibr" rid="ref133">Miyagawa et al., 2016</xref>). BIN1 dependent pathophysiological process is possibly associated with tau pathology through various mechanisms (<xref ref-type="bibr" rid="ref195">Thomas et al., 2019</xref>). However, there is no further evidence to clarify whether this effect is regulated through the modulation of tau phosphorylation (<xref ref-type="bibr" rid="ref195">Thomas et al., 2019</xref>), the influence of BIN1-tau interactions (<xref ref-type="bibr" rid="ref122">Malki et al., 2017</xref>; <xref ref-type="bibr" rid="ref162">Sartori et al., 2019</xref>), or directly facilitating the propagation of pathogenic tau (<xref ref-type="bibr" rid="ref42">Crotti et al., 2019</xref>). Genome-wide association studies demonstrated that <italic>BIN1</italic> was a genetic risk factor of LOAD (<xref ref-type="bibr" rid="ref190">Tan et al., 2013</xref>). The depletion of <italic>BIN1</italic> enhanced the level of cellular BACE1 by impairing endosomal trafficking and decreased BACE1 lysosomal degradation, leading to the overproduction of A&#x03B2; (<xref ref-type="bibr" rid="ref133">Miyagawa et al., 2016</xref>). A cohort study including 112 AD and 200 control subjects showed significantly elevated levels of BIN1 mRNA and protein in the plasma of ADs. However, this trend is required further investigation in the larger-scale cohort (<xref ref-type="bibr" rid="ref186">Sun et al., 2013</xref>).</p>
</sec>
</sec>
<sec id="sec9"><label>3</label>
<title>Biomarkers of NFT formation</title>
<sec id="sec10"><label>3.1</label>
<title>P-tau</title>
<p>AD-related NFT are composed of P-tau (<xref ref-type="bibr" rid="ref64">Grundke-Iqbal et al., 1986</xref>). CSF P-tau was elevated at the preclinical stage of AD (<xref ref-type="bibr" rid="ref163">Sato et al., 2018</xref>), and it continued to rise during the early clinical stage (<xref ref-type="bibr" rid="ref146">Palmqvist et al., 2019</xref>). Higher CSF T-tau and P-tau indicated faster disease progression (<xref ref-type="bibr" rid="ref207">Wallin et al., 2010</xref>). The elevated CSF T-tau reflected CNS degeneration, while increased P-tau was specific to AD (<xref ref-type="bibr" rid="ref17">Blennow and Hampel, 2003</xref>; <xref ref-type="bibr" rid="ref176">Skillb&#x00E4;ck et al., 2014</xref>). Therefore, P-tau could help to distinguish AD from other neurodegenerative diseases (<xref ref-type="bibr" rid="ref71">Hampel et al., 2004</xref>). The correlation between CSF P-tau and A&#x03B2; was stronger than that between CSF P-tau and tau-PET (<xref ref-type="bibr" rid="ref107">La Joie et al., 2018</xref>). This is probably because A&#x03B2; pathology is the reason for the increased CSF P-tau, while tau-PET measures NFT (<xref ref-type="bibr" rid="ref163">Sato et al., 2018</xref>; <xref ref-type="bibr" rid="ref177">Smirnov et al., 2022</xref>).</p>
<p>Several CSF P-tau proteins were reported to increase at the preclinical stage of AD. Both P-tau181 and P-tau217 began to increase at the early stage of AD, which were around 20&#x2009;years before the detection of tau aggregation in the brain (<xref ref-type="bibr" rid="ref10">Barth&#x00E9;lemy et al., 2020b</xref>). Compared to the control groups, the CSF P-tau217 increased by 5 times in AD patients, while P-tau181 only increased by 1.3 times (<xref ref-type="bibr" rid="ref11">Barth&#x00E9;lemy et al., 2019</xref>). CSF or plasma P-tau217 could identify patients with A&#x03B2;-PET positive but tau-PET negative, which indicated the changes of CSF P-tau before the detection of tau aggregates (<xref ref-type="bibr" rid="ref9">Barth&#x00E9;lemy et al., 2020a</xref>; <xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). CSF P-tau205 increased in the advanced AD, and it was related to the increase of T-tau and brain atrophy (<xref ref-type="bibr" rid="ref10">Barth&#x00E9;lemy et al., 2020b</xref>). Studies reported that P-tau231 was the earliest increasing biomarker in AD (<xref ref-type="bibr" rid="ref3">Ashton et al., 2021</xref>; <xref ref-type="bibr" rid="ref177">Smirnov et al., 2022</xref>). There are few studies about comparison of different CSF P-tau biomarkers. One study showed that the levels of CSF P-tau181, P-tau199 and P-tau231 were strongly associated with each other (<xref ref-type="bibr" rid="ref71">Hampel et al., 2004</xref>). By combining the application of two or more biomarkers, higher diagnostic accuracy could be obtained (<xref ref-type="bibr" rid="ref76">Hansson et al., 2006</xref>). The fragments of the microtubule binding region (MTBR) where tau was much easier to aggregate (<xref ref-type="bibr" rid="ref15">Blennow et al., 2020</xref>) were more reliable indicators for tau aggregation (<xref ref-type="bibr" rid="ref173">Simr&#x00E9;n et al., 2023</xref>). A mass spectrometry study investigating the role of MTBR showed that CSF MTBR-tau, such as MTBR-tau243, MTBR-tau299 or MTBR-tau354, was a promising biomarker for monitoring target participation in the clinical trials (<xref ref-type="bibr" rid="ref79">Horie et al., 2021</xref>).</p>
<p>Plasma P-tau was suggested to be the most promising analyte as a screening tool in clinical application. The increase of plasma P-tau was closely related to amyloid plaques and tau tangles (<xref ref-type="bibr" rid="ref126">Mattsson-Carlgren et al., 2021</xref>). The validity of plasma P-tau as AD biomarker has been verified in neuropathologically confirmed cases (<xref ref-type="bibr" rid="ref108">Lantero Rodriguez et al., 2020</xref>; <xref ref-type="bibr" rid="ref147">Palmqvist et al., 2020</xref>), which was not affected by common co-pathologies (such as TDP-43 or &#x03B1;-synuclein pathology) (<xref ref-type="bibr" rid="ref177">Smirnov et al., 2022</xref>). Studies proved that plasma P-tau could predict the progression from cognitively unimpaired individuals to MCI and eventually to AD (<xref ref-type="bibr" rid="ref86">Janelidze et al., 2020</xref>). Plasma P-tau had excellent accuracy in distinguishing AD from non-AD tau proteinosis (e.g., progressive supranuclear paralysis or cortical basal degeneration) or non-AD neurodegenerative diseases [e.g., DLB or frontotemporal dementia (FTD)] (<xref ref-type="bibr" rid="ref147">Palmqvist et al., 2020</xref>; <xref ref-type="bibr" rid="ref3">Ashton et al., 2021</xref>; <xref ref-type="bibr" rid="ref193">Thijssen et al., 2021</xref>). Several P-tau proteins such as P-tau181, P-tau217 and P-tau231 have been proposed as AD blood biomarkers (<xref ref-type="bibr" rid="ref147">Palmqvist et al., 2020</xref>; <xref ref-type="bibr" rid="ref3">Ashton et al., 2021</xref>; <xref ref-type="bibr" rid="ref177">Smirnov et al., 2022</xref>). With the progression of the disease, plasma P-tau181 increased steadily (<xref ref-type="bibr" rid="ref183">Su&#x00E1;rez-Calvet et al., 2020</xref>; <xref ref-type="bibr" rid="ref194">Thijssen et al., 2020</xref>), and it could accurately distinguish AD from non-AD neurodegenerative diseases (<xref ref-type="bibr" rid="ref86">Janelidze et al., 2020</xref>). Plasma P-tau 217 was at a high level before detection of tau pathology by PET.</p>
<p>The concentrations of P-tau181, T-tau and A&#x03B2;<sub>42</sub> in exosomes of AD were associated with the corresponding CSF biomarkers. They were significantly higher than those in MCI and healthy controls (<xref ref-type="bibr" rid="ref89">Jia et al., 2019</xref>). Compared to the control groups, P-tau, A&#x03B2;<sub>42</sub> and phosphorylated insulin receptor substrate 1 (IRS-1) of neuronal derived extracellular vesicles (NDEVs) in ADs showed high accuracy in predicting and distinguishing AD (<xref ref-type="bibr" rid="ref95">Kapogiannis et al., 2019</xref>).</p>
</sec>
</sec>
<sec id="sec11"><label>4</label>
<title>Biomarkers of neurodegeneration</title>
<p>In 2018, NIA-AA guideline proposed neurodegeneration as the third biomarker of AD (<xref ref-type="table" rid="tab2">Table 2</xref>; <xref ref-type="bibr" rid="ref82">Jack et al., 2018</xref>). Although neurodegeneration alone was not enough as a diagnostic marker, its change rate could accurately predict the progression of the disease (<xref ref-type="bibr" rid="ref56">Frisoni et al., 2010</xref>).</p>
<table-wrap position="float" id="tab2"><label>Table 2</label>
<caption>
<p>Summarized information of AD neurodegeneration biofluid biomarkers presented in this review.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Pathophysiological mechanism</th>
<th align="left" valign="top">Biomarker</th>
<th align="left" valign="top">Biological matrices</th>
<th align="left" valign="top">Trend</th>
<th align="left" valign="top">Purpose</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="6">Neurodegeneration</td>
<td align="left" valign="middle" rowspan="2">T-tau</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref172">Shui et al., 2018</xref>)</td>
<td align="left" valign="middle">Diagnosis (<xref ref-type="bibr" rid="ref82">Jack et al., 2018</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref35">Chen et al., 2019</xref>)</td>
<td align="left" valign="middle">Research (<xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">NfL</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref228">Zetterberg et al., 2016</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref124">Mattsson et al., 2017</xref>; <xref ref-type="bibr" rid="ref23">Bridel et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref124">Mattsson et al., 2017</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">VILIP-1</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle" rowspan="2">Increase (<xref ref-type="bibr" rid="ref21">Braunewell, 2012</xref>; <xref ref-type="bibr" rid="ref68">Halbgebauer et al., 2022b</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref137">Mroczko et al., 2015</xref>; <xref ref-type="bibr" rid="ref68">Halbgebauer et al., 2022b</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood</td>
</tr>
</tbody>
</table>
</table-wrap>
<sec id="sec12"><label>4.1</label>
<title>T-tau</title>
<p>In AD patients, the level of CSF T-tau increased (<xref ref-type="bibr" rid="ref172">Shui et al., 2018</xref>). Similar to CSF P-tau181, CSF T-tau began to increase after the formation of amyloid plaques (<xref ref-type="bibr" rid="ref167">Schindler, 2022</xref>). This happened 10&#x2009;~&#x2009;15&#x2009;years earlier before NFT (<xref ref-type="bibr" rid="ref12">Bateman et al., 2012</xref>; <xref ref-type="bibr" rid="ref53">Fleisher et al., 2015</xref>). Therefore, CSF T-tau and P-tau181 probably reflected neuron dysfunction caused by A&#x03B2; plaques, rather than tau tangles. The level of CSF T-tau also increased in other diseases, such as stroke, acute neuronal injury, and CJD (<xref ref-type="bibr" rid="ref176">Skillb&#x00E4;ck et al., 2014</xref>). It increased within a few days after acute brain injury, and continued to elevate for several weeks until it finally fell back to the normal range (<xref ref-type="bibr" rid="ref227">Zetterberg et al., 2006</xref>). Previous studies reported that the highest level of CSF T-tau was observed in the most serious neurodegenerative diseases. For example, CSF T-tau level in CJD patients was 10 to 20 times higher than that in AD (<xref ref-type="bibr" rid="ref176">Skillb&#x00E4;ck et al., 2014</xref>).</p>
<p>A two-year longitudinal study involving 152 people showed that plasma T-tau and T-tau/A&#x03B2;<sub>42</sub> could predict the deposition of abnormally folded proteins in the brain (<xref ref-type="bibr" rid="ref188">Sutphen et al., 2018</xref>). There was a correlation between high plasma T-tau and AD (<xref ref-type="bibr" rid="ref35">Chen et al., 2019</xref>). Although the plasma T-tau concentration in MCI or AD increased, the research data showed that the range of plasma T-tau in AD overlapped with that in normal population. This hinders the application of plasma T-tau as a diagnostic biomarker (<xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>).</p>
</sec>
<sec id="sec13"><label>4.2</label>
<title>Neurofilament light chain (NfL)</title>
<p>Neurofilament plays an important role in maintaining the neuronal integrity and regulating the transport of intracellular components (<xref ref-type="bibr" rid="ref117">Liu et al., 2004</xref>; <xref ref-type="bibr" rid="ref206">Wagner et al., 2007</xref>; <xref ref-type="bibr" rid="ref223">Yan et al., 2007</xref>; <xref ref-type="bibr" rid="ref26">Bruno et al., 2012</xref>). Because of the imbalance of tau kinase and phosphatase activity, abnormal hyperphosphorylation of neurofilaments occurred leading to the loss of their stability and axonal injury in the white matter and brain (<xref ref-type="bibr" rid="ref63">Gong et al., 2000</xref>). Axonal injury released neurofilament proteins into interstitial fluid, and they could be detected in CSF (<xref ref-type="bibr" rid="ref26">Bruno et al., 2012</xref>). The concentration of NfL in CSF rose at the early clinical stages of AD, correlating with cognitive decline and the changes of brain structure (<xref ref-type="bibr" rid="ref228">Zetterberg et al., 2016</xref>). A longitudinal study involving 389 subjects showed the elevated CSF NfL level in ADs than healthy controls (<xref ref-type="bibr" rid="ref125">Mattsson et al., 2016</xref>). The lack of correlation between increased CSF NfL and A&#x03B2; pathology indicated that NfL was not specific to AD. Higher concentration of CSF NfL indicated the existence of axonal injury (<xref ref-type="bibr" rid="ref23">Bridel et al., 2019</xref>). Although CSF NfL was not a specific biomarker for a disease, it could help clinicians to investigate whether cognitively impaired patients had neurological causes (<xref ref-type="bibr" rid="ref167">Schindler, 2022</xref>). Studies showed that combined application of NfL with other biomarkers could greatly improve the accuracy of dementia diagnosis (<xref ref-type="bibr" rid="ref45">de Jong et al., 2007</xref>; <xref ref-type="bibr" rid="ref125">Mattsson et al., 2016</xref>). For example, the combination of CSF A&#x03B2;<sub>42</sub> and P-tau181 with CSF NfL improved the diagnosis accuracy of early AD and FTD (<xref ref-type="bibr" rid="ref45">de Jong et al., 2007</xref>).</p>
<p>Blood NfL was closely related to CSF NfL (<xref ref-type="bibr" rid="ref74">Hansson et al., 2017</xref>), and it has become an easy-to-obtain biomarker for reflecting the intensity of neuronal damage and neurodegeneration (<xref ref-type="bibr" rid="ref173">Simr&#x00E9;n et al., 2023</xref>). Some studies proposed that blood NfL was an effective tool for the early diagnosis of AD (<xref ref-type="bibr" rid="ref54">Fortea et al., 2018</xref>). Elevated plasma NfL concentrations were observed in SAD (<xref ref-type="bibr" rid="ref3">Ashton et al., 2021</xref>). Compared to the healthy controls, the plasma NfL level of AD increased by nearly 150% (<xref ref-type="bibr" rid="ref124">Mattsson et al., 2017</xref>). The increased NFL was related to the cognitive decline, brain atrophy and low metabolism (<xref ref-type="bibr" rid="ref124">Mattsson et al., 2017</xref>). Weston et al. pointed out that serum NfL increased in asymptomatic FAD, and it was associated with the stage and severity of the disease (<xref ref-type="bibr" rid="ref215">Weston et al., 2017</xref>). Due to the concomitant pathologies of axons and peripheral axons, big difference in plasma NfL levels among healthy elderly population limited its specificity (<xref ref-type="bibr" rid="ref173">Simr&#x00E9;n et al., 2023</xref>). Nevertheless, the plasma NfL was more specific in autosomal dominant AD (ADAD) and Down syndrome because of the younger onset age of these disease process (<xref ref-type="bibr" rid="ref173">Simr&#x00E9;n et al., 2023</xref>).</p>
</sec>
<sec id="sec14"><label>4.3</label>
<title>VILIP-1</title>
<p>Visinin-like Protein 1 (VILIP-1) is a new biomarker for reflecting the pathological changes of AD. It is a calcium-binding protein of neuronal calcium sensor (NCS), which plays an important role in neuronal signaling cascades (<xref ref-type="bibr" rid="ref28">Burgoyne and Weiss, 2001</xref>). In AD and other neurodegenerative diseases, neurons showed abnormal Ca<sup>2+</sup> homeostasis, which resulted in the aberrant regulation of Ca<sup>2+</sup> ion channels and reduction of Ca<sup>2+</sup> buffering capacity (<xref ref-type="bibr" rid="ref123">Marambaud et al., 2009</xref>). VILIP-1 participated in calcium-mediated neuronal injury through regulation of Ca<sup>2+</sup> ions. The expression of VILIP-1 was closely related to A&#x03B2; plaque and NFT in ADs (<xref ref-type="bibr" rid="ref22">Braunewell et al., 2001</xref>; <xref ref-type="bibr" rid="ref21">Braunewell, 2012</xref>). CSF VILIP-1 could predict the change rate of global and focal brain atrophy which was similar as T-tau and P-tau181 (<xref ref-type="bibr" rid="ref119">Luo et al., 2013</xref>). The CSF VILIP-1 level of <italic>ApoE &#x03B5;4</italic> carriers was significantly increased, and it was positively correlated with tau and P-tau levels (<xref ref-type="bibr" rid="ref212">Wang et al., 2020</xref>). A meta-analysis indicated enhanced levels of CSF VILIP-1 in AD compared to the control group. In addition, the CSF VILIP-1 level was higher in MCI patients who progressed to AD than stable MCIs (<xref ref-type="bibr" rid="ref128">Mavroudis I. A. et al., 2021</xref>). Similarly, several longitudinal studies pointed out that the concentration of VILIP-1 and/or VILIP-1/A&#x03B2;<sub>42</sub> in CSF could be applied to diagnose diseases at an early stage, and predicted the future cognitive impairment of normal individuals (<xref ref-type="bibr" rid="ref119">Luo et al., 2013</xref>). For example, the VILIP-1/A&#x03B2;<sub>42</sub> and VILIP-1 in the CSF could help to differentiate AD from CJD (<xref ref-type="bibr" rid="ref68">Halbgebauer et al., 2022b</xref>). No significant difference of VILIP-1 was observed between AD and DLB (<xref ref-type="bibr" rid="ref128">Mavroudis I. A. et al., 2021</xref>). Serum VILIP-1 could not discriminate AD from PD, ALS, and behavioral variant frontotemporal dementia (bvFTD) (<xref ref-type="bibr" rid="ref68">Halbgebauer et al., 2022b</xref>). It was reported that serum VILIP-1 was correlated with acute ischemic stroke (<xref ref-type="bibr" rid="ref179">Stejskal et al., 2011</xref>; <xref ref-type="bibr" rid="ref113">Liu D. et al., 2020</xref>) and the neuronal injury caused by epileptic seizures (<xref ref-type="bibr" rid="ref189">Tan et al., 2020</xref>). To date, there is no convincing data supporting the correlation between plasma VILIP-1 and AD or other neurodegenerative diseases.</p>
</sec>
</sec>
<sec id="sec15"><label>5</label>
<title>Biomarkers of synaptic dysfunction</title>
<p>Synaptic dysfunction is closely correlated with the loss of synaptic integrity and neuropathological changes in the brain, which is another important pathophysiological mechanism of cognitive decline in AD. Synaptic dysfunction is largely driven by A&#x03B2; and tau pathology, and/or by the indirect consequence of neuroinflammatory response (<xref ref-type="bibr" rid="ref83">Jackson et al., 2019</xref>). Therefore, synaptic alterations are considered as an early pathological event of AD (<xref ref-type="bibr" rid="ref165">Scheff et al., 2007</xref>). Biomarkers indicating synaptic integrity and plasticity are helpful for early diagnosis and prognosis monitoring of AD (<xref ref-type="table" rid="tab3">Table 3</xref>; <xref ref-type="bibr" rid="ref123">Marambaud et al., 2009</xref>).</p>
<table-wrap position="float" id="tab3"><label>Table 3</label>
<caption>
<p>Summarized information of AD synaptic dysfunction biofluid biomarkers presented in this review.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Pathophysiological mechanism</th>
<th align="left" valign="top">Biomarker</th>
<th align="left" valign="top">Biological matrices</th>
<th align="left" valign="top">Trend</th>
<th align="left" valign="top">Purpose</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="7">Synaptic dysfunction</td>
<td align="left" valign="middle" rowspan="2">SNAP-25</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref142">&#x00D6;hrfelt et al., 2016</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref142">&#x00D6;hrfelt et al., 2016</xref>; <xref ref-type="bibr" rid="ref1">Agliardi et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood NDEs</td>
<td align="left" valign="middle">Decrease (<xref ref-type="bibr" rid="ref1">Agliardi et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">GAP-43</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref161">Sandelius et al., 2019</xref>)</td>
<td align="left" valign="middle">Research (<xref ref-type="bibr" rid="ref161">Sandelius et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">NPTX-2</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle" rowspan="2">Decrease (<xref ref-type="bibr" rid="ref61">Goetzl et al., 2018</xref>; <xref ref-type="bibr" rid="ref140">Nilsson et al., 2021</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref61">Goetzl et al., 2018</xref>; <xref ref-type="bibr" rid="ref140">Nilsson et al., 2021</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood NDEs</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">NG</td>
<td align="left" valign="middle">CSF</td>
<td align="left" valign="middle">Increase (<xref ref-type="bibr" rid="ref156">Portelius et al., 2018</xref>)</td>
<td align="left" valign="middle" rowspan="2">Research (<xref ref-type="bibr" rid="ref115">Liu W. et al., 2020</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Blood exosome</td>
<td align="left" valign="middle">Decrease (<xref ref-type="bibr" rid="ref115">Liu W. et al., 2020</xref>)</td>
</tr>
</tbody>
</table>
</table-wrap>
<sec id="sec16"><label>5.1</label>
<title>Presynaptic protein</title>
<p>Synaptosome-associated protein 25 (SNAP-25) exists in synaptic vesicles (<xref ref-type="bibr" rid="ref60">Geppert et al., 1994</xref>). CSF SNAP-25 is a key participant in synaptic degeneration (<xref ref-type="bibr" rid="ref230">Zhang et al., 2018</xref>). An increasing trend of CSF SNAP-25 was observed in the AD patients (<xref ref-type="bibr" rid="ref142">&#x00D6;hrfelt et al., 2016</xref>). The significantly reduced SNAP-25 in the cerebral cortex indicated the synaptic dysfunction (<xref ref-type="bibr" rid="ref44">Davidsson and Blennow, 1998</xref>). It was reported that CSF SNAP-25 could differentiate AD from PD, FTD and ALS, and high concentration of CSF SNAP-25 could be applied as a biomarker for both AD and CJD (<xref ref-type="bibr" rid="ref67">Halbgebauer et al., 2022a</xref>). CSF SNAP-25 level was correlated with <italic>APOE &#x03B5;4</italic> (<xref ref-type="bibr" rid="ref211">Wang S. et al., 2018</xref>). MCI patients carrying <italic>APOE &#x03B5;4</italic> showed higher CSF SNAP-25 than non-carriers (<xref ref-type="bibr" rid="ref211">Wang S. et al., 2018</xref>). There is few research on the correlation between blood SNAP-25 and AD. A study presented the reduced SNAP-25 in the neuron-derived exosomes (NDEs) isolated from serum, and it was associated with the cognition evaluated by Mini-Mental State Examination (MMSE) (<xref ref-type="bibr" rid="ref1">Agliardi et al., 2019</xref>).</p>
<p>The increase of growth-associated protein 43 (GAP-43) was considered as another biomarker reflecting AD-related synaptic dysfunction. CSF GAP-43 increased with the cognitive decline, and it was correlated with A&#x03B2; plaque and NFT in hippocampus, amygdala, and cortex (<xref ref-type="bibr" rid="ref161">Sandelius et al., 2019</xref>). CSF GAP-43 could predict the progression from MCI to AD, and this correlation was suspected to be related with <italic>APOE &#x03B5;4</italic> (<xref ref-type="bibr" rid="ref235">Zhu et al., 2023</xref>). Elevated level of CSF GAP-43 was specific to AD compared to the other neurodegenerative diseases, e.g., MCI, ALS, behavioral variant FTD (bvFTD), PD, DLB, primary progressive aphasia (PPA), progressive supranuclear palsy, corticobasal syndrome, and posterior cortical atrophy (PCA). Therefore, it was considered as a promise AD biomarker for the clinical research. However, another study reported a temporary increase of CSF GAP-43 after ischemic stroke (<xref ref-type="bibr" rid="ref160">Sandelius et al., 2018</xref>). A blood neuro-exosomal study presented that exosomal GAP-43 could predict MCI 5&#x2013;7&#x2009;years in advance (<xref ref-type="bibr" rid="ref91">Jia et al., 2021</xref>).</p>
<p>Neuronal pentraxin 2 (NPTX-2) is a protein correlated with the inhibitory circuit dysfunction. NPTX-2 showed different trends from the above biomarkers. The level of NPTX-2 in AD cerebral cortex and CSF decreased, and it had a strong correlation with cognitive ability and the volume of hippocampus (<xref ref-type="bibr" rid="ref221">Xiao et al., 2017</xref>; <xref ref-type="bibr" rid="ref140">Nilsson et al., 2021</xref>). Reduced CSF NPTX-2 level can predict early AD in adults with Down syndrome (<xref ref-type="bibr" rid="ref13">Belbin et al., 2020</xref>). A longitudinal CSF proteomics study found that the change rate of NPTX-2 concentration was significantly associated with cognitive decline. CSF NPTX-2 was suggested as a strong biomarker for accelerated cognitive decline (<xref ref-type="bibr" rid="ref111">Libiger et al., 2021</xref>). NPTX-2 regulates the complement activity and the loss of microglial synapses in the brain. Reduced NPTX-2 level may exacerbate complement-mediated neurodegeneration in FTD (<xref ref-type="bibr" rid="ref233">Zhou J. et al., 2023</xref>). Studies reported significantly reduced CSF NPTX-2 level in FTD (<xref ref-type="bibr" rid="ref43">Das et al., 2023</xref>) and DLB (<xref ref-type="bibr" rid="ref20">Boiten et al., 2020</xref>), indicating that CSF NPTX-2 was not a specific AD biomarker. NPTX-2/tau was closely related to the cognition of AD and MCI, and it had the best discrimination on AD (<xref ref-type="bibr" rid="ref57">Galasko et al., 2019</xref>). The correlation between serum NPTX-2 and AD still remains unclear. There was an independent correlation between the serum NPTX-2 and cognition of VaD patients (<xref ref-type="bibr" rid="ref171">Shao et al., 2020</xref>). Reduced NPTX-2 level was observed in the plasma NDEs of AD patients, but this change could not be detected 6&#x2013;11&#x2009;years before dementia (<xref ref-type="bibr" rid="ref61">Goetzl et al., 2018</xref>).</p>
<p>&#x03B1;-syn induced hyperphosphorylation and aggregation of tau protein (<xref ref-type="bibr" rid="ref48">Duka et al., 2006</xref>). There was a correlation between CSF &#x03B1;-syn and MMSE score (<xref ref-type="bibr" rid="ref103">Korff et al., 2013</xref>). Compared to the cognitively normal population, the level of CSF &#x03B1;-syn in AD increased (<xref ref-type="bibr" rid="ref69">Hall et al., 2012</xref>). CSF &#x03B1;-syn in AD was significantly higher than those in PD and other neurodegenerative diseases (<xref ref-type="bibr" rid="ref208">Wang et al., 2015</xref>). More research found that &#x03B1;-syn was a protein associated with familial PD, and it has identified as a major protein of the neuropathological hallmark for idiopathic PD (<xref ref-type="bibr" rid="ref52">Fayyad et al., 2019</xref>).</p>
</sec>
<sec id="sec17"><label>5.2</label>
<title>Postsynaptic protein</title>
<p>Neurogranin (NG) is the most well-studied postsynaptic protein. It is a protein composed of 78 amino acids, which is involved in synaptic dysfunction or neuronal injury (<xref ref-type="bibr" rid="ref159">Represa et al., 1990</xref>). NG participates in the induction of synaptic plasticity by accelerating the dissociation of calmodulin, e.g., long-term potentiation (LTP) and long-term depression (LTD) (<xref ref-type="bibr" rid="ref104">Kubota et al., 2007</xref>). High levels of CSF NG reflected the loss of brain neurogranin protein (<xref ref-type="bibr" rid="ref164">Saunders et al., 2023</xref>), and it was positively correlated with A&#x03B2; plaque and tau pathology (<xref ref-type="bibr" rid="ref154">Pereira et al., 2017</xref>; <xref ref-type="bibr" rid="ref156">Portelius et al., 2018</xref>). The content of CSF NG48-76 increased significantly indicating the neurodegenerative process in the brain (<xref ref-type="bibr" rid="ref106">Kvartsberg et al., 2015</xref>). CSF NG in MCI and AD was higher than cognitive normal population, and it could help to predict the progression from MCI to AD (<xref ref-type="bibr" rid="ref100">Kester et al., 2015</xref>). CSF NG can predict MCI 5&#x2013;7&#x2009;years in advance (<xref ref-type="bibr" rid="ref91">Jia et al., 2021</xref>), but it could not differentiate MCI from FTD or DLB (<xref ref-type="bibr" rid="ref129">Mavroudis et al., 2020</xref>). The specificity of CSF NG as a biomarker for AD diagnosis is controversial. Studies indicated that the elevation of CSF NG was highly specific to AD (<xref ref-type="bibr" rid="ref156">Portelius et al., 2018</xref>), while others presented opposite conclusion (<xref ref-type="bibr" rid="ref216">Willemse et al., 2021</xref>). Blood NG did not show a good trend. Plasma NG had no significant change or in a similar range between AD and healthy controls (<xref ref-type="bibr" rid="ref46">De Vos et al., 2015</xref>; <xref ref-type="bibr" rid="ref106">Kvartsberg et al., 2015</xref>). NG level in NDEVs of MCI and AD decreased, and it was correlated with the cognitive decline (<xref ref-type="bibr" rid="ref62">Goetzl et al., 2016</xref>; <xref ref-type="bibr" rid="ref217">Winston et al., 2016</xref>; <xref ref-type="bibr" rid="ref115">Liu W. et al., 2020</xref>). A meta-analysis reported decreased NG level in plasma exosomes, and plasma NG was closely correlated with the cognitive decline (<xref ref-type="bibr" rid="ref115">Liu W. et al., 2020</xref>). The interpretation of NDEVs biomarkers should be taken with caution because of their controversial origin (<xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>).</p>
</sec>
</sec>
<sec id="sec18"><label>6</label>
<title>Biomarkers of neuroinflammation</title>
<p>Neuropathologist Alois Alzheimer firstly observed lipid accumulation and fibrous structures in glial cells of dementia population&#x2019;s brain (<xref ref-type="bibr" rid="ref173">Simr&#x00E9;n et al., 2023</xref>). Glial cells in CNS include astrocytes and microglia, and they were reported to be involved in AD pathophysiology (<xref ref-type="table" rid="tab4">Table 4</xref>; <xref ref-type="bibr" rid="ref173">Simr&#x00E9;n et al., 2023</xref>).</p>
<table-wrap position="float" id="tab4"><label>Table 4</label>
<caption>
<p>Summarized information of AD neuroinflammation biofluid biomarkers presented in this review.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th>Pathophysiological mechanism</th>
<th align="left" valign="top">Biomarker</th>
<th align="left" valign="top">Biological matrices</th>
<th align="left" valign="top">Trend</th>
<th align="left" valign="top">Purpose</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="12">Neuroinflammation</td>
<td align="left" valign="top" rowspan="2">TREM2 &#x0026; sTREM2</td>
<td align="left" valign="top">CSF</td>
<td align="left" valign="top">Controversial (<xref ref-type="bibr" rid="ref120">Ma et al., 2020</xref>)</td>
<td align="left" valign="top" rowspan="2">Research (<xref ref-type="bibr" rid="ref80">Hu et al., 2014</xref>; <xref ref-type="bibr" rid="ref184">Su&#x00E1;rez-Calvet et al., 2016b</xref>)</td>
</tr>
<tr>
<td align="left" valign="top">Blood</td>
<td align="left" valign="top">Increase (<xref ref-type="bibr" rid="ref80">Hu et al., 2014</xref>)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">TAM receptor</td>
<td align="left" valign="top">CSF</td>
<td align="left" valign="top" rowspan="2">Increase (<xref ref-type="bibr" rid="ref24">Brosseron et al., 2022</xref>, <xref ref-type="bibr" rid="ref25">2023</xref>)</td>
<td align="left" valign="top" rowspan="2">Research (<xref ref-type="bibr" rid="ref24">Brosseron et al., 2022</xref>, <xref ref-type="bibr" rid="ref25">2023</xref>)</td>
</tr>
<tr>
<td align="left" valign="top">Blood</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">YKL-40</td>
<td align="left" valign="top">CSF</td>
<td align="left" valign="top">Increase (<xref ref-type="bibr" rid="ref85">Janelidze et al., 2016a</xref>)</td>
<td align="left" valign="top" rowspan="2">Research (<xref ref-type="bibr" rid="ref85">Janelidze et al., 2016a</xref>; <xref ref-type="bibr" rid="ref203">Villar-Piqu&#x00E9; et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left" valign="top">Blood</td>
<td align="left" valign="top">Increase (<xref ref-type="bibr" rid="ref41">Craig-Schapiro et al., 2010</xref>)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">GFAP</td>
<td align="left" valign="top">CSF</td>
<td align="left" valign="top">Increase (<xref ref-type="bibr" rid="ref14">Benedet et al., 2021</xref>)</td>
<td align="left" valign="top" rowspan="3">Research (<xref ref-type="bibr" rid="ref14">Benedet et al., 2021</xref>; <xref ref-type="bibr" rid="ref37">Cicognola et al., 2021</xref>; <xref ref-type="bibr" rid="ref97">Katsipis et al., 2021</xref>)</td>
</tr>
<tr>
<td align="left" valign="top">Blood</td>
<td align="left" valign="top">Increase (<xref ref-type="bibr" rid="ref14">Benedet et al., 2021</xref>)</td>
</tr>
<tr>
<td align="left" valign="top">Saliva</td>
<td align="left" valign="top">Decrease (<xref ref-type="bibr" rid="ref97">Katsipis et al., 2021</xref>)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">NRG-1</td>
<td align="left" valign="top">CSF</td>
<td align="left" valign="top" rowspan="2">Increase (<xref ref-type="bibr" rid="ref33">Chang et al., 2016</xref>; <xref ref-type="bibr" rid="ref136">Mouton-Liger et al., 2020</xref>)</td>
<td align="left" valign="top" rowspan="2">Research (<xref ref-type="bibr" rid="ref33">Chang et al., 2016</xref>; <xref ref-type="bibr" rid="ref136">Mouton-Liger et al., 2020</xref>)</td>
</tr>
<tr>
<td align="left" valign="top">Blood</td>
</tr>
<tr>
<td align="left" valign="top">TRAIL</td>
<td align="left" valign="top">Blood</td>
<td align="left" valign="top">Decrease (<xref ref-type="bibr" rid="ref220">Wu et al., 2015</xref>)</td>
<td align="left" valign="top">Research (<xref ref-type="bibr" rid="ref220">Wu et al., 2015</xref>)</td>
</tr>
</tbody>
</table>
</table-wrap>
<sec id="sec19"><label>6.1</label>
<title>TREM2 and sTREM2</title>
<p>Triggering receptor 2 (TREM2) is a cell surface receptor mainly expressed in CNS microglia, and it plays an important role in regulating energy metabolism and phenotypic transformation of microglia. TREM2 acts as a key regulator, allowing microglia to switch between steady state and activated state (disease-associated microglia) (<xref ref-type="bibr" rid="ref99">Keren-Shaul et al., 2017</xref>). Heterozygous loss-of-function variants in TREM2 were associated with the increasing AD risk (<xref ref-type="bibr" rid="ref65">Guerreiro et al., 2013</xref>), and another study presented that they also increased the risk of the other neurodegenerative diseases, such as FTD, PD, and ALS (<xref ref-type="bibr" rid="ref30">Carmona et al., 2018</xref>). Studies reported that TREM2 tripled the risk of AD (<xref ref-type="bibr" rid="ref65">Guerreiro et al., 2013</xref>), probably through its influence on tau pathology (<xref ref-type="bibr" rid="ref112">Lill et al., 2015</xref>) and A&#x03B2; clearance pathway (<xref ref-type="bibr" rid="ref102">Kleinberger et al., 2014</xref>). CSF TREM2 level was deranged at the early stage of AD, and it was closely related to neurodegenerative biomarkers such as T-tau and/or P-tau (<xref ref-type="bibr" rid="ref77">Heslegrave et al., 2016</xref>; <xref ref-type="bibr" rid="ref184">Su&#x00E1;rez-Calvet et al., 2016b</xref>). Compared to the healthy controls, the levels of TREM2 mRNA and protein in peripheral blood of AD were higher (<xref ref-type="bibr" rid="ref80">Hu et al., 2014</xref>). TREM2 level in MCI-AD patients was significantly higher than that in AD or healthy controls (<xref ref-type="bibr" rid="ref31">Casati et al., 2018</xref>).</p>
<p>After hydrolysis of the TREM2 protein, the soluble fragments of sTREM2 are produced outside the cell (<xref ref-type="bibr" rid="ref38">Colonna and Wang, 2016</xref>). Transgelin-2 (TG2) is expressed on neurons. The sTREM2-TG2 interaction mediates the crosstalk between neurons and microglia (<xref ref-type="bibr" rid="ref229">Zhang et al., 2023</xref>). The concentration of CSF sTREM2 in AD was higher than the healthy controls (<xref ref-type="bibr" rid="ref155">Piccio et al., 2016</xref>; <xref ref-type="bibr" rid="ref184">Su&#x00E1;rez-Calvet et al., 2016b</xref>). Before the appearance of expected symptoms and after the increasing of A&#x03B2; and T-tau, the level of CSF sTREM2 in ADAD mutation carriers was higher than non-carriers (<xref ref-type="bibr" rid="ref182">Su&#x00E1;rez-Calvet et al., 2016a</xref>). It was suggested that sTREM2 was potential to predict the progression from MCI to AD. The MCI patients with low CSF or high plasma sTREM2 levels had a higher risk of progression to AD. In addition, the concentration of CSF sTREM2 was closely correlated with sTREM2 in plasma (<xref ref-type="bibr" rid="ref231">Zhao et al., 2022</xref>). The dynamically changes of CSF sTREM2 was observed in preclinical AD. In the absence of neurodegeneration and tau deposition, A&#x03B2; pathology was correlated with the decreased CSF sTREM2. However, tau pathology and neurodegeneration are associated with the increased CSF sTREM2 (<xref ref-type="bibr" rid="ref120">Ma et al., 2020</xref>). A meta-analysis reported that CSF sTREM2 was significantly elevated in the entire continuum of AD compared to controls. However, an increasing trend of CSF sTREM2 was also observed in PD, multiple sclerosis (MS), FTD and DLB (<xref ref-type="bibr" rid="ref234">Zhou W. et al., 2023</xref>).</p>
</sec>
<sec id="sec20"><label>6.2</label>
<title>TAM receptor</title>
<p>TAM receptors are widely expressed in various types of cells and tissues in the immune, neurological, vascular, and reproductive systems (<xref ref-type="bibr" rid="ref232">Zhou S. et al., 2023</xref>). Axl and Mertk are expressed in microglia, but Tyro3 is not (<xref ref-type="bibr" rid="ref55">Fourgeaud et al., 2016</xref>). The TAM system is an important regulator for microglia to recognize and engulfment of amyloid plaques. Axl and Mertk proteins were correlated with AD (<xref ref-type="bibr" rid="ref81">Huang et al., 2021</xref>). Axl reduces inflammatory responses, while Mertk plays a role in the phagocytosis of aggregated proteins and cellular debris (<xref ref-type="bibr" rid="ref232">Zhou S. et al., 2023</xref>). Research reported that A&#x03B2; plaque-associated microglia exhibited hyperreactivity upon systemic inflammation and upregulated phagocytic genes in the transgenic AD mouse model, including <italic>Axl</italic> (<xref ref-type="bibr" rid="ref225">Yin et al., 2017</xref>). Microglial phagocytosis driven by TAM does not inhibit, but promotes the formation of amyloid plaques. Mertk is the major participan<underline>t</underline> in this process (<xref ref-type="bibr" rid="ref81">Huang et al., 2021</xref>). Phosphatidylserine (PtdSer) serves as the ligand decorating the plaques for TAM receptors. Mertk, expressed by activated microglia, recognized, and phagocytosed neurons exposed to PtdSer, thereby promoting tau-induced neuronal loss (<xref ref-type="bibr" rid="ref149">Pampuscenko et al., 2020</xref>; <xref ref-type="bibr" rid="ref232">Zhou S. et al., 2023</xref>). The increasing of soluble Axl level in CSF reflected the pathophysiology of AD and was positively correlated with P-tau181 (<xref ref-type="bibr" rid="ref24">Brosseron et al., 2022</xref>). However, extensive clinical data showed that CSF Axl was correlated with larger brain volume and slower cognitive decline, which indicated that Axl had a protective effect on related processes (<xref ref-type="bibr" rid="ref24">Brosseron et al., 2022</xref>). The serum Axl was significantly elevated in AD, and it was negatively correlated with cognition and structural imaging (<xref ref-type="bibr" rid="ref25">Brosseron et al., 2023</xref>). However, the specificity of Axl as an AD biomarker is still required further investigation.</p>
</sec>
<sec id="sec21"><label>6.3</label>
<title>YKL-40</title>
<p>Human cartilage glycoprotein-39 (YKL-40) is a biomarker of inflammation, as well as the activated astrocytes (<xref ref-type="bibr" rid="ref143">Olsson et al., 2016</xref>). It is primarily produced by astrocytes in the brain and it can predict the neurotoxicity induced by inflammation and other stress signals (<xref ref-type="bibr" rid="ref39">Connolly et al., 2023</xref>). The research focus on the role of YKL-40 in AD is limited. It was presented that YKL-40 may promote AD progression via altering amyloid burden and neuroinflammatory processes (<xref ref-type="bibr" rid="ref39">Connolly et al., 2023</xref>). Another study indicated a correlation between YKL-40 and tau pathology (<xref ref-type="bibr" rid="ref6">Baldacci et al., 2017a</xref>). YKL-40 showed good performance in distinguishing tau-positive patients from controls (<xref ref-type="bibr" rid="ref7">Baldacci et al., 2017b</xref>). A meta-analysis found that CSF YKL-40 could serve as a biomarker to predict the progression from MCI to AD, as well as for the prognosis of MCI. CSF YKL-40 was significantly elevated in AD, MCI, MCI-AD, and stable MCI compared to the controls, and it was higher in MCI-AD than in the stable MCI (<xref ref-type="bibr" rid="ref127">Mavroudis I. et al., 2021</xref>). The level of CSF YKL-40 increased in AD and FTD, and it was relatively low in DLB (<xref ref-type="bibr" rid="ref41">Craig-Schapiro et al., 2010</xref>; <xref ref-type="bibr" rid="ref85">Janelidze et al., 2016a</xref>). Another study showed that the level of CSF YKL-40 in AD increased compared to non-dementia control groups, DLB and PD (<xref ref-type="bibr" rid="ref214">Wennstr&#x00F6;m et al., 2015</xref>). The above results suggested that CSF YKL-40 could be used as a non-specific neuroinflammatory biomarker to distinguish AD from PD and DLB (<xref ref-type="bibr" rid="ref214">Wennstr&#x00F6;m et al., 2015</xref>). The application of plasma YKL-40 in diagnosis of AD is controversial. It was reported that higher plasma YKL-40 in Clinical Dementia Rating (CDR) 1 and 0.5 than CDR 0 (<xref ref-type="bibr" rid="ref41">Craig-Schapiro et al., 2010</xref>). Another study indicated the possibility of YKL-40 for predicting the progression from MCI to mild AD (<xref ref-type="bibr" rid="ref36">Choi et al., 2011</xref>). Some studies presented no statistical difference of plasma YKL-40 between AD and controls. However, the significantly increased plasma YKL-40 was observed in CJD and LBD (<xref ref-type="bibr" rid="ref41">Craig-Schapiro et al., 2010</xref>; <xref ref-type="bibr" rid="ref203">Villar-Piqu&#x00E9; et al., 2019</xref>).</p>
</sec>
<sec id="sec22"><label>6.4</label>
<title>GFAP</title>
<p>Glial fibrillary acidic protein (GFAP) is the main intermediate filament of the glial cytoskeleton (<xref ref-type="bibr" rid="ref152">Pekny and Nilsson, 2005</xref>). GFAP mediates insulin-like growth factor 1 signaling pathway that involved in AD pathology (<xref ref-type="bibr" rid="ref210">Wang et al., 2023</xref>). CSF GFAP increased with plaque deposition (<xref ref-type="bibr" rid="ref14">Benedet et al., 2021</xref>), and it could be used to predict the progression from MCI to AD (<xref ref-type="bibr" rid="ref37">Cicognola et al., 2021</xref>). In addition, studies found that CSF GFAP can effectively differentiate healthy population from preclinical ADs (<xref ref-type="bibr" rid="ref218">Wojda&#x0142;a et al., 2023</xref>). Plasma GFAP is considered as an early biomarker for A&#x03B2; pathology, but it is not related with tau pathology (<xref ref-type="bibr" rid="ref153">Pereira et al., 2021</xref>). Plasma GFAP was sensitive to AD pathology in LBD, especially to A&#x03B2; plaque accumulation (<xref ref-type="bibr" rid="ref40">Cousins et al., 2023</xref>). Studies showed that plasma GFAP level continued to increase as the disease progression (AD dementia&#x003E;MCI&#x2009;&#x003E;&#x2009;cognitively normal elderly with A&#x03B2; positive), but CSF GFAP did not reflect the consistent trend (<xref ref-type="bibr" rid="ref201">Verberk et al., 2020</xref>; <xref ref-type="bibr" rid="ref34">Chatterjee et al., 2021</xref>). The reason why plasma GFAP performs better than CSF GFAP as AD biomarker is still unclear. This is probably correlated with the direct release of GFAP into the blood by astrocytic end-feet, and/or different biological degradation between these two matrices (<xref ref-type="bibr" rid="ref174">Simr&#x00E9;n et al., 2022</xref>). Additionally, plasma GFAP can serve as a biomarker for adult AD in Down syndrome, and it could be applied in clinical practice and trials (<xref ref-type="bibr" rid="ref135">Montoliu-Gaya et al., 2023</xref>). Notably, significantly decreasing GFAP concentration was observed in saliva of MCI and AD compared to controls. Salivary GFAP is suggested as an excellent biomarker for distinguishing MCI or AD from the controls (<xref ref-type="bibr" rid="ref97">Katsipis et al., 2021</xref>).</p>
</sec>
<sec id="sec23"><label>6.5</label>
<title>NRG-1</title>
<p>Neuregulin (NRG) plays an important role in the development of nervous system (<xref ref-type="bibr" rid="ref50">Esper et al., 2006</xref>). NRG-1 is the first and best characterized NRG gene (<xref ref-type="bibr" rid="ref150">Pankonin et al., 2009</xref>). Soluble NRG (sNRG) was preferentially accumulated on the surface of white matter astrocytes (<xref ref-type="bibr" rid="ref150">Pankonin et al., 2009</xref>). NRG-1 signaling exerts neuroprotection through the activation of the phosphatidylinositol 3-kinase/Akt (PI3K/Akt) pathway to prevent the neurotoxicity induced by A&#x03B2;<sub>42</sub> (<xref ref-type="bibr" rid="ref5">Baik et al., 2016</xref>). Another study presented prevention of AD via blocking NRG-1 signaling on microglia (<xref ref-type="bibr" rid="ref114">Liu et al., 2023</xref>). Both the above studies are based on the animal models. Research found that ADs and MCI-ADs had higher CSF NRG-1 than controls and non-AD dementias, and the CSF NRG-1 was correlated with cognitive evolution (<xref ref-type="bibr" rid="ref136">Mouton-Liger et al., 2020</xref>). Plasma sNRG-1 level in AD increased and there was a significant correlation between plasma sNRG-1 and MMSE score. The lower MMSE score was correlated with the higher plasma sNRG-1 concentration (<xref ref-type="bibr" rid="ref33">Chang et al., 2016</xref>). In addition, plasma NRG-1 was found to be correlated with CSF GAP-43, SNAP-25, and NG (<xref ref-type="bibr" rid="ref205">Vrillon et al., 2022</xref>). Therefore, sNRG-1 was suggested as a sensitive plasma biomarker (<xref ref-type="bibr" rid="ref33">Chang et al., 2016</xref>).</p>
</sec>
<sec id="sec24"><label>6.6</label>
<title>TRAIL</title>
<p>Previous study presented the involvement of TNF-related apoptosis-inducing ligand (TRAIL) in A&#x03B2; induced neurotoxicity in a human neuronal cell line (<xref ref-type="bibr" rid="ref29">Cantarella et al., 2003</xref>). Blockade of the TRAIL-death receptor DR5 prevented A&#x03B2;-neurotoxicity (<xref ref-type="bibr" rid="ref198">Uberti et al., 2007</xref>). It was reported that the TRAIL was specifically expressed in the brains of ADs (<xref ref-type="bibr" rid="ref197">Uberti et al., 2004</xref>). The reduced plasma TRAIL level was observed in AD group compared to controls (<xref ref-type="bibr" rid="ref220">Wu et al., 2015</xref>), and it was significantly associated with its level in CSF (<xref ref-type="bibr" rid="ref220">Wu et al., 2015</xref>). No significant difference was observed in the serum TRAIL between ADs and controls. However, a negative correlation was indicated between serum TRAIL and MMSE scores of AD patients (<xref ref-type="bibr" rid="ref59">Genc et al., 2009</xref>).</p>
</sec>
</sec>
<sec id="sec25"><label>7</label>
<title>Biomarkers of BBB breakdown</title>
<p><italic>ApoE</italic> &#x03B5;4 could accelerate the breakdown of BBB and damage the pericapillary cells of the brain (<xref ref-type="bibr" rid="ref70">Halliday et al., 2016</xref>). High level of platelet-derived growth factor receptor-&#x03B2; (PDGFR-&#x03B2;) in CSF could predict the cognitive decline of <italic>ApoE</italic> &#x03B5;4 carriers (<xref ref-type="bibr" rid="ref134">Montagne et al., 2020</xref>). Brain capillary injury and BBB breakdown occurred in the hippocampus of patients with early cognitive impairment (<xref ref-type="bibr" rid="ref139">Nation et al., 2019</xref>). However, the BBB disruptions were not correlated with alterations in A&#x03B2; and/or tau levels (<xref ref-type="bibr" rid="ref139">Nation et al., 2019</xref>; <xref ref-type="bibr" rid="ref134">Montagne et al., 2020</xref>). BBB breakdown was proposed as an early biomarker for human cognitive impairment that was uncorrelated to A&#x03B2; and tau pathology (<xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>).</p>
<p>The ratio of CSF to serum albumin was applied as a standard method to measure BBB function (<xref ref-type="bibr" rid="ref196">Tibbling et al., 1977</xref>; <xref ref-type="bibr" rid="ref175">Skillb&#x00E4;ck et al., 2017</xref>; <xref ref-type="bibr" rid="ref132">Menendez-Gonzalez and Gasparovic, 2019</xref>). The mean value of this ratio was slightly higher in AD patients with vascular factors when compared to the healthy controls, but no significant difference was observed in AD group without vascular factors (<xref ref-type="bibr" rid="ref18">Blennow et al., 1990</xref>). It is suggested that the BBB damage in AD was associated with clinical vascular factors but not a result of the disease itself (<xref ref-type="bibr" rid="ref18">Blennow et al., 1990</xref>). This ratio might help to exclude some of the cerebrovascular diseases and indirectly assist the diagnosis of AD (<xref ref-type="bibr" rid="ref158">Reitz and Mayeux, 2014</xref>).</p>
</sec>
<sec id="sec26"><label>8</label>
<title>Outlook</title>
<p>The Ronald and Nancy Reagan Research Institute of the Alzheimer&#x2019;s Association, and the National Institute on Aging Working Group proposed that &#x201C;ideal&#x201D; biomarkers for AD diagnosis should meet the following criteria (<xref ref-type="bibr" rid="ref101">Khan and Alkon, 2015</xref>): (1) the basic characteristics of AD neuropathology could be detected; (2) the application of biomarkers should be validated in neuropathologically confirmed AD cases; (3) biomarkers could diagnose AD at the early stage with high sensitivity and specificity; and (4) the analysis should be repeatable, reliable, non-invasive, simple and cost-effective (<xref ref-type="bibr" rid="ref105">Kulichikhin et al., 2021</xref>). Several challenges still exist. First, the diagnosis of AD mainly depends on the clinical features. Some clinical features are overlapped between AD and non-AD dementia patients, resulting in a high rate of misdiagnosis at the early stage of AD, especially in non-specialist clinical centers (<xref ref-type="bibr" rid="ref49">Engelborghs et al., 2008</xref>). Second, other dementias, e.g., VaD and DLB, have the pathological characteristics of AD (<xref ref-type="bibr" rid="ref169">Schneider et al., 2009</xref>), which hinders the application of some AD biomarkers. Third, A&#x03B2; plaques and NFT are also presented in the elderly population without cognitive impairment (<xref ref-type="bibr" rid="ref157">Price and Morris, 1999</xref>). Fourth, the detection of most AD biomarkers has not been standardized. Most of the results are preliminary and retrospective, and lacking comparison between patients (<xref ref-type="bibr" rid="ref187">Sunderland et al., 2003</xref>; <xref ref-type="bibr" rid="ref121">Mahaman et al., 2022</xref>). Finally, more meta-analysis or the correlation analysis studies among different biomarkers are insufficient. Further investigation to rank and confirm their importance is required.</p>
<p>In the future, the research could focus on demonstrating the accuracy of AD biomarkers, especially for the blood-based biomarkers. The relationship between AD biomarkers and the pathogenesis of AD needs further exploration. Large-scale head-to-head studies are required to determine the most appropriate application scenario of biomarkers at different stages of AD, involving diagnosis, prediction, prognosis, and clinical trial design (<xref ref-type="bibr" rid="ref144">Ossenkoppele et al., 2019</xref>).</p>
</sec>
<sec sec-type="author-contributions" id="sec27">
<title>Author contributions</title>
<p>SW: Writing &#x2013; review &#x0026; editing, Writing &#x2013; original draft. SX: Writing &#x2013; review &#x0026; editing, Writing &#x2013; original draft. QZ: Writing &#x2013; original draft. ZZ: Writing &#x2013; original draft. TW: Writing &#x2013; review &#x0026; editing, Supervision, Conceptualization. GZ: Writing &#x2013; review &#x0026; editing, Supervision, Conceptualization.</p>
</sec>
</body>
<back>
<sec sec-type="funding-information" id="sec28">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by Shandong Yinfeng Academy of Life Science.</p>
</sec>
<ack>
<p>We thank the Shandong Yinfeng Academy of Life Science for financial support. Special thanks to Professor Guirong Zhang and Professor Tian Wang for their guidance in this work, as well as to Shandong Yinfeng Academy of Life Science and School of Pharmacy of Yantai University for their academic resources and support.</p>
</ack>
<sec sec-type="COI-statement" id="sec29">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="sec100" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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