Cautions on utilizing plasma GFAP level as a biomarker for reactive astrocytes in neurodegenerative diseases

IF 14.9 1区 医学 Q1 NEUROSCIENCES
Wongu Youn, Mijin Yun, C. Justin Lee, Michael Schöll
{"title":"Cautions on utilizing plasma GFAP level as a biomarker for reactive astrocytes in neurodegenerative diseases","authors":"Wongu Youn, Mijin Yun, C. Justin Lee, Michael Schöll","doi":"10.1186/s13024-025-00846-9","DOIUrl":null,"url":null,"abstract":"<p>In the recent decade, there has been a surge of efforts to develop scalable, specific and cost-effective biomarkers in blood to diagnose neurodegenerative diseases and prognose their progress even before overt symptoms manifest. Among an array of brain-associated proteins, glial fibrillary acidic protein (GFAP) has emerged as a compelling biomarker candidate, often in conjunction with other biomarkers. GFAP levels in bodily fluid, especially blood and cerebrospinal fluid (CSF), have underscored associations with disease progression by robust support in a substantial body of reports encompassing cohorts afflicted with a spectrum of brain and spinal cord disorders, including progressive neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease, multiple sclerosis and Lewy body dementia. Notably, GFAP in CSF is known to reflect astrogliosis in alignment with other astrogliosis marker levels such as S100β, chitinase-3-like protein 1 (CHI3L1, also known as YKL40 in humans and BMP39 in mice), aquaporin 4, evidence in tissue by immunohistochemistry staining, and uptake of certain PET radiotracers targeting reactive astrocytes, i.e., <sup>11</sup>C-deuterium-L-deprenyl (<sup>11</sup>C-DED), <sup>11</sup>C-BU99008, <sup>11</sup>C-SMBT-1 or <sup>11</sup> C-acetate [1]. On the other hand, GFAP levels in blood seem to demonstrate more precise diagnostic performance than CSF GFAP level in an AD context. Patient case studies employing MRI and PET have underscored correlations between disease progression and GFAP levels in bodily fluids, with plasma GFAP yielding greater significance [2]. Furthermore, recent cohort studies suggest that the effect of amyloid-β (Aβ) on tau pathology may be modulated by astrocytic reactivity, which was suggested to be indicated by increased plasma GFAP levels [3]. The recent inclusion of interchangeable use of plasma and CSF GFAP as a marker of inflammation (category ‘I’) in the Alzheimer’s Association Workgroup criteria for diagnosis and staging of Alzheimer’s disease showcases its suggested diagnostic potential [4]. We argue, however, that there are several concerns regarding the use of blood GFAP as a direct biomarker for astrocyte reactivity. Research has identified discrepancies between astrocyte reactivity examined by <sup>11</sup>C-deuterium-L-deprenyl (<sup>11</sup>C-DED) PET imaging and plasma GFAP levels in AD patients [5], with more significant changes observed in blood GFAP levels than in cerebrospinal fluid (CSF) GFAP levels [6]. In this perspective, we argue that astrocytic reactivity cannot be represented solely from blood GFAP level, and more direct methods for examining astrocyte reactivity such as PET imaging must be followed. Our argument is based on two primary concerns: the ambiguous origin of plasma GFAP and inconsistencies between blood GFAP level increases and other biomarkers.</p><p>First, the origin of blood GFAP remains unclear, with uncertainty about whether plasma GFAP derives from CSF or specifically from (reactive) astrocytes. Identified in multiple sclerosis brain tissue in 1969, GFAP quickly became a key astrocyte marker and has since been widely used for selectively targeting astrocyte expression in mice via the GFAP promoter [7]. During both pathological and physiological states, the well-established process of reactive astrogliosis leads to morphological and functional changes in astrocytes, accompanied by increased GFAP expression. Consequently, elevated GFAP levels in CSF and blood have traditionally been attributed to upregulated production by reactive astrocytes. While GFAP release into the bloodstream is well-documented in acute brain injuries with transient blood-brain barrier disruptions, the mechanisms behind increased blood GFAP levels in neurodegenerative disease progression—especially when blood-brain barrier integrity is maintained—remain elusive.</p><p>Recent studies further question this assumption, revealing a negative correlation between plasma GFAP levels and astrocytic reactivity in both autosomal dominant and sporadic AD cases, challenging earlier assumptions [5]. Also, a recent preprint reported a negative correlation between brain and plasma GFAP concentration in a 5xFAD transgenic mouse model [8]. Notably, in AD, glial activation appears to precede increases in both CSF and plasma GFAP levels, suggesting that elevated plasma GFAP may not solely originate from GFAP-upregulated reactive astrocytes [1]. During the pre-symptomatic phase, modest increases in CSF and plasma GFAP are observed even 10 years before symptoms manifest [8], with more significant elevations arising only in symptomatic stages. Additionally, plasma GFAP levels tend to increase before CSF GFAP, with differences in the magnitude of these increases [6]. In contrast, increased serum GFAP levels have shown correlations with immunohistochemistry-based astrocytic reactivity and post-mortem brain atrophy in dementia patient cohort study [9]. This temporal and spatial discrepancy calls into question the direct association of blood GFAP with astrocytic reactivity.</p><p>The discrepancy between CSF and plasma GFAP levels is not the only point of doubt; GFAP expression in various body cells also raises questions about the true origin of blood GFAP. Although GFAP is widely regarded as an astrocyte-specific protein, its roles remain poorly understood, partly due to its variable expression across different brain cell types and astrocytic subpopulations. Even within the human brain, additional GFAP-expressing cells, such as developing neural progenitor cells and ependymal cells, are present, requiring supplementary markers like calcium-binding protein B (S100β), excitatory amino acid transporter 1 (EAAT1 or GLAST), glutamine synthetase (GS), and aldehyde dehydrogenase 1 family member L1 (ALDH1L1) for accurate astrocyte identification. Beyond the central nervous system, GFAP expression is also found in non-myelinating Schwann cells in the peripheral nervous system (PNS), Müller glia in retina, enteric glial cells in the enteric nervous system (ENS), renal tubular cells, Leydig and Sertoli cells in the testis, and various cell types in the liver, skin, bone, and placenta under normal conditions [7].</p><p>Notably, these non-brain GFAP-expressing cells in pathological conditions also upregulate GFAP, complicating attempts to pinpoint the origin of blood GFAP. For instance, GFAP is overexpressed in the intestines of patients with inflammatory bowel disease; Parkinson’s disease has been associated with elevated GFAP expression and phosphorylation in enteric glia; hepatic stellate cells show GFAP overexpression near areas of hepatic fibrosis; and GFAP has been detected in the bloodstream following complex thoracic aortic surgery [10]. Despite these observations, no direct evidence yet demonstrates that blood GFAP originates from reactive astrocytes in the brain.</p><p>Second, inconsistencies are documented for the association between plasma GFAP levels and other glial biomarkers, whereas CSF GFAP levels are strongly correlated with these markers. Glial biomarkers extend beyond GFAP alone, with different markers of reactive astrocytes, such as CHI3L1 and S100B, as well as soluble triggering receptor expressed on myeloid cells 2 (sTREM2), which is secreted by microglia. While CSF GFAP levels correlate with these glial biomarkers, contradictory reports exist regarding the correlation between plasma GFAP levels and measures of astrogliosis as investigated with different PET tracers or at autopsy. Plasma GFAP levels were thus positively correlated with <sup>18</sup>F-SMBT-1 uptake in sporadic AD patients compared to control groups [11], but showed no correlation or were even negatively correlated with <sup>11</sup>C-DED [5] or GFAP levels in brain tissue [8], suggesting that mechanisms beyond reactive astrocytes or CSF release may contribute to elevated blood GFAP levels [6]. Moreover, in a cohort study on multiple sclerosis (MS), serum GFAP levels failed to predict disease activity and progression, whereas CSF GFAP levels were significant predictors despite a correlation existing between CSF and serum GFAP levels and other glial/neuroinflammation markers [12].</p><p>Delving into more practical considerations, quantifying GFAP levels in blood is challenging for conventional ELISA methods, which has led to the adoption of ultrasensitive techniques such as SIMOA. However, the inconsistencies in GFAP levels across studies indicate a lack of standardized criteria for its use as a biomarker, which might be due to limitations in antibody-based methods, including the aggregation-related hook effect and the presence of multiple GFAP isoforms and post-translational modifications [13]. To advance GFAP as a more reliable biomarker, standardized quantification methods, sample handling protocols including antibody information, and comprehensive studies on GFAP isoforms are essential to clarify the origins of GFAP release and improve its analytical accuracy.</p><p>Despite the numerous limitations and unresolved issues surrounding blood GFAP level elevations, these levels remain broadly accepted as biomarkers reflecting neurodegenerative disease stages, not only specific to AD but also early amyloidosis, dementia or faster cognitive decline [4]. Alongside other markers such as phosphorylated tau, amyloid beta 42/40, and neurofilament light chain protein (NfL), blood GFAP is believed to enhance our understanding of disease progression. However, for GFAP to be recognized as a reliable biomarker, a rigorous examination of its origins and causal links to pathophysiological conditions is essential, grounded in concrete biological evidence rather than correlations alone.</p><p>To truly determine GFAP’s value, we must undertake a comprehensive investigation that includes mapping GFAP expression across all relevant tissues, selectively marking or targeting GFAP in specific cell types, for example, along with PET imaging targeting particular cells, and closely examining the conditions that trigger GFAP release from astrocytes and reactive astrocytes. One way of observing GFAP release might be possible by analyzing astrocyte-derived exosomes through astrocyte-specific markers. These biological analyses must be backed by global, longitudinal cohort studies with rigorously standardized measurement methods, along with the support of imaging probes for reactive astrocytes. Only with such a thorough and meticulous approach can we move beyond superficial associations and harness GFAP as a precise, reliable biomarker for astrocyte reactiveness in neurodegenerative diseases.</p><p>Not applicable. The study contains publicly available data from published studies.</p><ol data-track-component=\"outbound reference\" data-track-context=\"references section\"><li data-counter=\"1.\"><p>Nam M-H, Na H, Lee CJ, Yun M. A key mediator and imaging target in Alzheimer’s disease: unlocking the role of reactive astrogliosis through MAOB. Nuc Med Mol Imaging. 2024;58:177–84.</p><p>Article Google Scholar </p></li><li data-counter=\"2.\"><p>Shen X-N, Huang S-Y, Cui M, Zhao Q-H, Guo Y, Huang Y-Y, Zhang W, Ma Y-H, Chen S-D, Zhang Y-R, et al. Plasma glial fibrillary acidic protein in the alzheimer disease continuum: relationship to other biomarkers, differential diagnosis, and prediction of clinical progression. Clin Chem. 2023;69(4):411–21.</p><p>Article CAS PubMed Google Scholar </p></li><li data-counter=\"3.\"><p>Bellaver B, Povala G, Ferreira PCL, João PF-S, Leffa DT, Lussier FZ, Benedet AL, Ashton NJ, Triana-Baltzer G, Kolb HC, et al. Astrocytic reactivity influences amyloid-β effects on Tau pathology in preclinical Alzheimer’s disease. Nat Med. 2023;29:1774–81.</p><p>Article Google Scholar </p></li><li data-counter=\"4.\"><p>Jack CR Jr, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, Hansson O, Ho C, Jagust W, McDade E, et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s association workgroup. Alzheimers Dement. 2024;20(8):5143–69.</p><p>Article PubMed PubMed Central Google Scholar </p></li><li data-counter=\"5.\"><p>Chiotis K, Johansson C, Rodriguez-Vieitez E, Ashton NJ, Blennow K, Zetterberg H, Graff C, Nordberg A. Tracking reactive astrogliosis in autosomal dominant and sporadic Alzheimer’s disease with multi-modal PET and plasma GFAP. Mol Neurodegener. 2023;18:60.</p><p>Article CAS PubMed PubMed Central Google Scholar </p></li><li data-counter=\"6.\"><p>Benedet AL, Milà-Alomà M, Vrillon A, Ashton NJ, Pascoal TA, Lussier F, Karikari TK, Hourregue C, Cognat Emmanuel, Dumurgier J, et al. Differences between plasma and cerebrospinal fluid glial fibrillary acidic protein levels across the alzheimer disease continuum. JAMA Neurol. 2021;78(12):1471–83.</p><p>Article PubMed Google Scholar </p></li><li data-counter=\"7.\"><p>Messing A, Brenner M. GFAP at 50. ASN Neuro. 2020;0:1–23.</p><p>Google Scholar </p></li><li data-counter=\"8.\"><p>Varma VR, An Y, Kac PR, Bilgel M, Moghekar A, Loeffler T, Amschl D, Troncoso J, Blennow K, Zetterberg H, et al. Longitudinal progression of blood biomarkers reveals a key role of astrocyte reactivity in preclinical Alzheimer’s disease. MedRxiv. 2024. https://doi.org/10.1101/2024.01.25.24301779.</p><p>Article PubMed PubMed Central Google Scholar </p></li><li data-counter=\"9.\"><p>Peretti DE, Boccalini C, Ribaldi F, Scheffler M, Marizzoni M, Ashton NJ, Zetterberg H, Blennow K, Frisoni GB, Garibotto V. Association of glial fibrillary acid protein, Alzheimer’s disease pathology and cognitive decline. Brain. 2024;147:4094–104.</p><p>Article PubMed PubMed Central Google Scholar </p></li><li data-counter=\"10.\"><p>Grundmann D, Loris E, Maas-Omlor S, Huang W, Scheller A, Kirchhoff F, Schäfer K-H. Enteric Glia: S100, GFAP, and beyond. Anat Rec. 2019;302:1333–44.</p><p>Article CAS Google Scholar </p></li><li data-counter=\"11.\"><p>Chatterjee P, Doré V, Pedrini S, Krishnadas N, Thota R, Bourgeat P, Ikonomovic MD, Rainey-Smith SR, Burnham SC, Fowler C, et al. Plasma glial fibrillary acidic protein is associated with 18F-SMBT-1 PET: two putative astrocyte reactivity biomarkers for Alzheimer’s disease. J Alzheimers Dis. 2023;92(2):615–28.</p><p>Article CAS PubMed PubMed Central Google Scholar </p></li><li data-counter=\"12.\"><p>Cross AH, Gelfand JM, Thebault S, Bennett JL, von Büdingen HC, Cameron B, Carruthers R, Edwards K, Fallis R, Gerstein R, et al. Emerging cerebrospinal fluid biomarkers of disease activity and progression in multiple sclerosis. JAMA Neurol. 2024;81(4):373–83.</p><p>Article PubMed PubMed Central Google Scholar </p></li><li data-counter=\"13.\"><p>Gogishvili D, Honey MIJ, Verberk IMW, Vermunt L, Hol EM, Teunissen CE, Abeln S. The GFAP proteoform puzzle: how to advance GFAP as a fluid biomarker in neurological diseases. J Neurochem. 2025;169(1):e16226.</p><p>Article CAS PubMed Google Scholar </p></li></ol><p>Download references<svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-download-medium\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></p><p>We thank Dr. Joo Min Park for kind guidance.</p><p>Open access funding provided by University of Gothenburg.</p><p>This study was supported by a Brain Pool Program (RS-2023-00263612) from the National Research Foundation of Korea and the Center for Cognition and Sociality (IBS-R001-D2) under the Institute for Basic Science (IBS), Republic of Korea.</p><h3>Authors and Affiliations</h3><ol><li><p>Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea</p><p>Wongu Youn &amp; C. Justin Lee</p></li><li><p>Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea</p><p>Mijin Yun</p></li><li><p>Department of Psychiatry and Neurochemistry and the Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, 41345, Sweden</p><p>Michael Schöll</p></li><li><p>Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, WC1E, UK</p><p>Michael Schöll</p></li><li><p>Department of Neuropsychiatry, Sahlgrenska University Hospital, Mölndal, 43141, Sweden</p><p>Michael Schöll</p></li></ol><span>Authors</span><ol><li><span>Wongu Youn</span>View author publications<p><span>You can also search for this author in</span><span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Mijin Yun</span>View author publications<p><span>You can also search for this author in</span><span>PubMed<span> </span>Google Scholar</span></p></li><li><span>C. Justin Lee</span>View author publications<p><span>You can also search for this author in</span><span>PubMed<span> </span>Google Scholar</span></p></li><li><span>Michael Schöll</span>View author publications<p><span>You can also search for this author in</span><span>PubMed<span> </span>Google Scholar</span></p></li></ol><h3>Contributions</h3><p>W.Y., M.Y., C.J.L. and M.S. wrote the manuscript. All authors read and approved the final manuscript.</p><h3>Corresponding authors</h3><p>Correspondence to Mijin Yun, C. Justin Lee or Michael Schöll.</p><h3>Ethics approval and consent to participate</h3>\n<p>Not applicable. The study does not involve human subjects. No ethical approval and consent are required.</p>\n<h3>Consent for publication</h3>\n<p>Not applicable.</p>\n<h3>Competing interests</h3>\n<p>The authors declare no competing financial interests in this manuscript.</p><h3>Publisher’s note</h3><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p><p><b>Open Access</b> 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 the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other 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 this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.</p>\n<p>Reprints and permissions</p><img alt=\"Check for updates. Verify currency and authenticity via CrossMark\" height=\"81\" loading=\"lazy\" src=\"data:image/svg+xml;base64,<svg height="81" width="57" xmlns="http://www.w3.org/2000/svg"><g fill="none" fill-rule="evenodd"><path d="m17.35 35.45 21.3-14.2v-17.03h-21.3" fill="#989898"/><path d="m38.65 35.45-21.3-14.2v-17.03h21.3" fill="#747474"/><path d="m28 .5c-12.98 0-23.5 10.52-23.5 23.5s10.52 23.5 23.5 23.5 23.5-10.52 23.5-23.5c0-6.23-2.48-12.21-6.88-16.62-4.41-4.4-10.39-6.88-16.62-6.88zm0 41.25c-9.8 0-17.75-7.95-17.75-17.75s7.95-17.75 17.75-17.75 17.75 7.95 17.75 17.75c0 4.71-1.87 9.22-5.2 12.55s-7.84 5.2-12.55 5.2z" fill="#535353"/><path d="m41 36c-5.81 6.23-15.23 7.45-22.43 2.9-7.21-4.55-10.16-13.57-7.03-21.5l-4.92-3.11c-4.95 10.7-1.19 23.42 8.78 29.71 9.97 6.3 23.07 4.22 30.6-4.86z" fill="#9c9c9c"/><path d="m.2 58.45c0-.75.11-1.42.33-2.01s.52-1.09.91-1.5c.38-.41.83-.73 1.34-.94.51-.22 1.06-.32 1.65-.32.56 0 1.06.11 1.51.35.44.23.81.5 1.1.81l-.91 1.01c-.24-.24-.49-.42-.75-.56-.27-.13-.58-.2-.93-.2-.39 0-.73.08-1.05.23-.31.16-.58.37-.81.66-.23.28-.41.63-.53 1.04-.13.41-.19.88-.19 1.39 0 1.04.23 1.86.68 2.46.45.59 1.06.88 1.84.88.41 0 .77-.07 1.07-.23s.59-.39.85-.68l.91 1c-.38.43-.8.76-1.28.99-.47.22-1 .34-1.58.34-.59 0-1.13-.1-1.64-.31-.5-.2-.94-.51-1.31-.91-.38-.4-.67-.9-.88-1.48-.22-.59-.33-1.26-.33-2.02zm8.4-5.33h1.61v2.54l-.05 1.33c.29-.27.61-.51.96-.72s.76-.31 1.24-.31c.73 0 1.27.23 1.61.71.33.47.5 1.14.5 2.02v4.31h-1.61v-4.1c0-.57-.08-.97-.25-1.21-.17-.23-.45-.35-.83-.35-.3 0-.56.08-.79.22-.23.15-.49.36-.78.64v4.8h-1.61zm7.37 6.45c0-.56.09-1.06.26-1.51.18-.45.42-.83.71-1.14.29-.3.63-.54 1.01-.71.39-.17.78-.25 1.18-.25.47 0 .88.08 1.23.24.36.16.65.38.89.67s.42.63.54 1.03c.12.41.18.84.18 1.32 0 .32-.02.57-.07.76h-4.36c.07.62.29 1.1.65 1.44.36.33.82.5 1.38.5.29 0 .57-.04.83-.13s.51-.21.76-.37l.55 1.01c-.33.21-.69.39-1.09.53-.41.14-.83.21-1.26.21-.48 0-.92-.08-1.34-.25-.41-.16-.76-.4-1.07-.7-.31-.31-.55-.69-.72-1.13-.18-.44-.26-.95-.26-1.52zm4.6-.62c0-.55-.11-.98-.34-1.28-.23-.31-.58-.47-1.06-.47-.41 0-.77.15-1.07.45-.31.29-.5.73-.58 1.3zm2.5.62c0-.57.09-1.08.28-1.53.18-.44.43-.82.75-1.13s.69-.54 1.1-.71c.42-.16.85-.24 1.31-.24.45 0 .84.08 1.17.23s.61.34.85.57l-.77 1.02c-.19-.16-.38-.28-.56-.37-.19-.09-.39-.14-.61-.14-.56 0-1.01.21-1.35.63-.35.41-.52.97-.52 1.67 0 .69.17 1.24.51 1.66.34.41.78.62 1.32.62.28 0 .54-.06.78-.17.24-.12.45-.26.64-.42l.67 1.03c-.33.29-.69.51-1.08.65-.39.15-.78.23-1.18.23-.46 0-.9-.08-1.31-.24-.4-.16-.75-.39-1.05-.7s-.53-.69-.7-1.13c-.17-.45-.25-.96-.25-1.53zm6.91-6.45h1.58v6.17h.05l2.54-3.16h1.77l-2.35 2.8 2.59 4.07h-1.75l-1.77-2.98-1.08 1.23v1.75h-1.58zm13.69 1.27c-.25-.11-.5-.17-.75-.17-.58 0-.87.39-.87 1.16v.75h1.34v1.27h-1.34v5.6h-1.61v-5.6h-.92v-1.2l.92-.07v-.72c0-.35.04-.68.13-.98.08-.31.21-.57.4-.79s.42-.39.71-.51c.28-.12.63-.18 1.04-.18.24 0 .48.02.69.07.22.05.41.1.57.17zm.48 5.18c0-.57.09-1.08.27-1.53.17-.44.41-.82.72-1.13.3-.31.65-.54 1.04-.71.39-.16.8-.24 1.23-.24s.84.08 1.24.24c.4.17.74.4 1.04.71s.54.69.72 1.13c.19.45.28.96.28 1.53s-.09 1.08-.28 1.53c-.18.44-.42.82-.72 1.13s-.64.54-1.04.7-.81.24-1.24.24-.84-.08-1.23-.24-.74-.39-1.04-.7c-.31-.31-.55-.69-.72-1.13-.18-.45-.27-.96-.27-1.53zm1.65 0c0 .69.14 1.24.43 1.66.28.41.68.62 1.18.62.51 0 .9-.21 1.19-.62.29-.42.44-.97.44-1.66 0-.7-.15-1.26-.44-1.67-.29-.42-.68-.63-1.19-.63-.5 0-.9.21-1.18.63-.29.41-.43.97-.43 1.67zm6.48-3.44h1.33l.12 1.21h.05c.24-.44.54-.79.88-1.02.35-.24.7-.36 1.07-.36.32 0 .59.05.78.14l-.28 1.4-.33-.09c-.11-.01-.23-.02-.38-.02-.27 0-.56.1-.86.31s-.55.58-.77 1.1v4.2h-1.61zm-47.87 15h1.61v4.1c0 .57.08.97.25 1.2.17.24.44.35.81.35.3 0 .57-.07.8-.22.22-.15.47-.39.73-.73v-4.7h1.61v6.87h-1.32l-.12-1.01h-.04c-.3.36-.63.64-.98.86-.35.21-.76.32-1.24.32-.73 0-1.27-.24-1.61-.71-.33-.47-.5-1.14-.5-2.02zm9.46 7.43v2.16h-1.61v-9.59h1.33l.12.72h.05c.29-.24.61-.45.97-.63.35-.17.72-.26 1.1-.26.43 0 .81.08 1.15.24.33.17.61.4.84.71.24.31.41.68.53 1.11.13.42.19.91.19 1.44 0 .59-.09 1.11-.25 1.57-.16.47-.38.85-.65 1.16-.27.32-.58.56-.94.73-.35.16-.72.25-1.1.25-.3 0-.6-.07-.9-.2s-.59-.31-.87-.56zm0-2.3c.26.22.5.37.73.45.24.09.46.13.66.13.46 0 .84-.2 1.15-.6.31-.39.46-.98.46-1.77 0-.69-.12-1.22-.35-1.61-.23-.38-.61-.57-1.13-.57-.49 0-.99.26-1.52.77zm5.87-1.69c0-.56.08-1.06.25-1.51.16-.45.37-.83.65-1.14.27-.3.58-.54.93-.71s.71-.25 1.08-.25c.39 0 .73.07 1 .2.27.14.54.32.81.55l-.06-1.1v-2.49h1.61v9.88h-1.33l-.11-.74h-.06c-.25.25-.54.46-.88.64-.33.18-.69.27-1.06.27-.87 0-1.56-.32-2.07-.95s-.76-1.51-.76-2.65zm1.67-.01c0 .74.13 1.31.4 1.7.26.38.65.58 1.15.58.51 0 .99-.26 1.44-.77v-3.21c-.24-.21-.48-.36-.7-.45-.23-.08-.46-.12-.7-.12-.45 0-.82.19-1.13.59-.31.39-.46.95-.46 1.68zm6.35 1.59c0-.73.32-1.3.97-1.71.64-.4 1.67-.68 3.08-.84 0-.17-.02-.34-.07-.51-.05-.16-.12-.3-.22-.43s-.22-.22-.38-.3c-.15-.06-.34-.1-.58-.1-.34 0-.68.07-1 .2s-.63.29-.93.47l-.59-1.08c.39-.24.81-.45 1.28-.63.47-.17.99-.26 1.54-.26.86 0 1.51.25 1.93.76s.63 1.25.63 2.21v4.07h-1.32l-.12-.76h-.05c-.3.27-.63.48-.98.66s-.73.27-1.14.27c-.61 0-1.1-.19-1.48-.56-.38-.36-.57-.85-.57-1.46zm1.57-.12c0 .3.09.53.27.67.19.14.42.21.71.21.28 0 .54-.07.77-.2s.48-.31.73-.56v-1.54c-.47.06-.86.13-1.18.23-.31.09-.57.19-.76.31s-.33.25-.41.4c-.09.15-.13.31-.13.48zm6.29-3.63h-.98v-1.2l1.06-.07.2-1.88h1.34v1.88h1.75v1.27h-1.75v3.28c0 .8.32 1.2.97 1.2.12 0 .24-.01.37-.04.12-.03.24-.07.34-.11l.28 1.19c-.19.06-.4.12-.64.17-.23.05-.49.08-.76.08-.4 0-.74-.06-1.02-.18-.27-.13-.49-.3-.67-.52-.17-.21-.3-.48-.37-.78-.08-.3-.12-.64-.12-1.01zm4.36 2.17c0-.56.09-1.06.27-1.51s.41-.83.71-1.14c.29-.3.63-.54 1.01-.71.39-.17.78-.25 1.18-.25.47 0 .88.08 1.23.24.36.16.65.38.89.67s.42.63.54 1.03c.12.41.18.84.18 1.32 0 .32-.02.57-.07.76h-4.37c.08.62.29 1.1.65 1.44.36.33.82.5 1.38.5.3 0 .58-.04.84-.13.25-.09.51-.21.76-.37l.54 1.01c-.32.21-.69.39-1.09.53s-.82.21-1.26.21c-.47 0-.92-.08-1.33-.25-.41-.16-.77-.4-1.08-.7-.3-.31-.54-.69-.72-1.13-.17-.44-.26-.95-.26-1.52zm4.61-.62c0-.55-.11-.98-.34-1.28-.23-.31-.58-.47-1.06-.47-.41 0-.77.15-1.08.45-.31.29-.5.73-.57 1.3zm3.01 2.23c.31.24.61.43.92.57.3.13.63.2.98.2.38 0 .65-.08.83-.23s.27-.35.27-.6c0-.14-.05-.26-.13-.37-.08-.1-.2-.2-.34-.28-.14-.09-.29-.16-.47-.23l-.53-.22c-.23-.09-.46-.18-.69-.3-.23-.11-.44-.24-.62-.4s-.33-.35-.45-.55c-.12-.21-.18-.46-.18-.75 0-.61.23-1.1.68-1.49.44-.38 1.06-.57 1.83-.57.48 0 .91.08 1.29.25s.71.36.99.57l-.74.98c-.24-.17-.49-.32-.73-.42-.25-.11-.51-.16-.78-.16-.35 0-.6.07-.76.21-.17.15-.25.33-.25.54 0 .14.04.26.12.36s.18.18.31.26c.14.07.29.14.46.21l.54.19c.23.09.47.18.7.29s.44.24.64.4c.19.16.34.35.46.58.11.23.17.5.17.82 0 .3-.06.58-.17.83-.12.26-.29.48-.51.68-.23.19-.51.34-.84.45-.34.11-.72.17-1.15.17-.48 0-.95-.09-1.41-.27-.46-.19-.86-.41-1.2-.68z" fill="#535353"/></g></svg>\" width=\"57\"/><h3>Cite this article</h3><p>Youn, W., Yun, M., Lee, C.J. <i>et al.</i> Cautions on utilizing plasma GFAP level as a biomarker for reactive astrocytes in neurodegenerative diseases. <i>Mol Neurodegeneration</i> <b>20</b>, 54 (2025). https://doi.org/10.1186/s13024-025-00846-9</p><p>Download citation<svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-download-medium\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></p><ul data-test=\"publication-history\"><li><p>Received<span>: </span><span><time datetime=\"2025-02-25\">25 February 2025</time></span></p></li><li><p>Accepted<span>: </span><span><time datetime=\"2025-04-17\">17 April 2025</time></span></p></li><li><p>Published<span>: </span><span><time datetime=\"2025-05-09\">09 May 2025</time></span></p></li><li><p>DOI</abbr><span>: </span><span>https://doi.org/10.1186/s13024-025-00846-9</span></p></li></ul><h3>Share this article</h3><p>Anyone you share the following link with will be able to read this content:</p><button data-track=\"click\" data-track-action=\"get shareable link\" data-track-external=\"\" data-track-label=\"button\" type=\"button\">Get shareable link</button><p>Sorry, a shareable link is not currently available for this article.</p><p data-track=\"click\" data-track-action=\"select share url\" data-track-label=\"button\"></p><button data-track=\"click\" data-track-action=\"copy share url\" data-track-external=\"\" data-track-label=\"button\" type=\"button\">Copy to clipboard</button><p> Provided by the Springer Nature SharedIt content-sharing initiative </p><h3>Keywords</h3><ul><li><span>Biomarker</span></li><li><span>Glial fibrillary acidic protein</span></li><li><span>Neurodegenerative disease</span></li><li><span>Reactive astrocyte</span></li></ul>","PeriodicalId":18800,"journal":{"name":"Molecular Neurodegeneration","volume":"49 1","pages":""},"PeriodicalIF":14.9000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Neurodegeneration","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13024-025-00846-9","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

In the recent decade, there has been a surge of efforts to develop scalable, specific and cost-effective biomarkers in blood to diagnose neurodegenerative diseases and prognose their progress even before overt symptoms manifest. Among an array of brain-associated proteins, glial fibrillary acidic protein (GFAP) has emerged as a compelling biomarker candidate, often in conjunction with other biomarkers. GFAP levels in bodily fluid, especially blood and cerebrospinal fluid (CSF), have underscored associations with disease progression by robust support in a substantial body of reports encompassing cohorts afflicted with a spectrum of brain and spinal cord disorders, including progressive neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease, multiple sclerosis and Lewy body dementia. Notably, GFAP in CSF is known to reflect astrogliosis in alignment with other astrogliosis marker levels such as S100β, chitinase-3-like protein 1 (CHI3L1, also known as YKL40 in humans and BMP39 in mice), aquaporin 4, evidence in tissue by immunohistochemistry staining, and uptake of certain PET radiotracers targeting reactive astrocytes, i.e., 11C-deuterium-L-deprenyl (11C-DED), 11C-BU99008, 11C-SMBT-1 or 11 C-acetate [1]. On the other hand, GFAP levels in blood seem to demonstrate more precise diagnostic performance than CSF GFAP level in an AD context. Patient case studies employing MRI and PET have underscored correlations between disease progression and GFAP levels in bodily fluids, with plasma GFAP yielding greater significance [2]. Furthermore, recent cohort studies suggest that the effect of amyloid-β (Aβ) on tau pathology may be modulated by astrocytic reactivity, which was suggested to be indicated by increased plasma GFAP levels [3]. The recent inclusion of interchangeable use of plasma and CSF GFAP as a marker of inflammation (category ‘I’) in the Alzheimer’s Association Workgroup criteria for diagnosis and staging of Alzheimer’s disease showcases its suggested diagnostic potential [4]. We argue, however, that there are several concerns regarding the use of blood GFAP as a direct biomarker for astrocyte reactivity. Research has identified discrepancies between astrocyte reactivity examined by 11C-deuterium-L-deprenyl (11C-DED) PET imaging and plasma GFAP levels in AD patients [5], with more significant changes observed in blood GFAP levels than in cerebrospinal fluid (CSF) GFAP levels [6]. In this perspective, we argue that astrocytic reactivity cannot be represented solely from blood GFAP level, and more direct methods for examining astrocyte reactivity such as PET imaging must be followed. Our argument is based on two primary concerns: the ambiguous origin of plasma GFAP and inconsistencies between blood GFAP level increases and other biomarkers.

First, the origin of blood GFAP remains unclear, with uncertainty about whether plasma GFAP derives from CSF or specifically from (reactive) astrocytes. Identified in multiple sclerosis brain tissue in 1969, GFAP quickly became a key astrocyte marker and has since been widely used for selectively targeting astrocyte expression in mice via the GFAP promoter [7]. During both pathological and physiological states, the well-established process of reactive astrogliosis leads to morphological and functional changes in astrocytes, accompanied by increased GFAP expression. Consequently, elevated GFAP levels in CSF and blood have traditionally been attributed to upregulated production by reactive astrocytes. While GFAP release into the bloodstream is well-documented in acute brain injuries with transient blood-brain barrier disruptions, the mechanisms behind increased blood GFAP levels in neurodegenerative disease progression—especially when blood-brain barrier integrity is maintained—remain elusive.

Recent studies further question this assumption, revealing a negative correlation between plasma GFAP levels and astrocytic reactivity in both autosomal dominant and sporadic AD cases, challenging earlier assumptions [5]. Also, a recent preprint reported a negative correlation between brain and plasma GFAP concentration in a 5xFAD transgenic mouse model [8]. Notably, in AD, glial activation appears to precede increases in both CSF and plasma GFAP levels, suggesting that elevated plasma GFAP may not solely originate from GFAP-upregulated reactive astrocytes [1]. During the pre-symptomatic phase, modest increases in CSF and plasma GFAP are observed even 10 years before symptoms manifest [8], with more significant elevations arising only in symptomatic stages. Additionally, plasma GFAP levels tend to increase before CSF GFAP, with differences in the magnitude of these increases [6]. In contrast, increased serum GFAP levels have shown correlations with immunohistochemistry-based astrocytic reactivity and post-mortem brain atrophy in dementia patient cohort study [9]. This temporal and spatial discrepancy calls into question the direct association of blood GFAP with astrocytic reactivity.

The discrepancy between CSF and plasma GFAP levels is not the only point of doubt; GFAP expression in various body cells also raises questions about the true origin of blood GFAP. Although GFAP is widely regarded as an astrocyte-specific protein, its roles remain poorly understood, partly due to its variable expression across different brain cell types and astrocytic subpopulations. Even within the human brain, additional GFAP-expressing cells, such as developing neural progenitor cells and ependymal cells, are present, requiring supplementary markers like calcium-binding protein B (S100β), excitatory amino acid transporter 1 (EAAT1 or GLAST), glutamine synthetase (GS), and aldehyde dehydrogenase 1 family member L1 (ALDH1L1) for accurate astrocyte identification. Beyond the central nervous system, GFAP expression is also found in non-myelinating Schwann cells in the peripheral nervous system (PNS), Müller glia in retina, enteric glial cells in the enteric nervous system (ENS), renal tubular cells, Leydig and Sertoli cells in the testis, and various cell types in the liver, skin, bone, and placenta under normal conditions [7].

Notably, these non-brain GFAP-expressing cells in pathological conditions also upregulate GFAP, complicating attempts to pinpoint the origin of blood GFAP. For instance, GFAP is overexpressed in the intestines of patients with inflammatory bowel disease; Parkinson’s disease has been associated with elevated GFAP expression and phosphorylation in enteric glia; hepatic stellate cells show GFAP overexpression near areas of hepatic fibrosis; and GFAP has been detected in the bloodstream following complex thoracic aortic surgery [10]. Despite these observations, no direct evidence yet demonstrates that blood GFAP originates from reactive astrocytes in the brain.

Second, inconsistencies are documented for the association between plasma GFAP levels and other glial biomarkers, whereas CSF GFAP levels are strongly correlated with these markers. Glial biomarkers extend beyond GFAP alone, with different markers of reactive astrocytes, such as CHI3L1 and S100B, as well as soluble triggering receptor expressed on myeloid cells 2 (sTREM2), which is secreted by microglia. While CSF GFAP levels correlate with these glial biomarkers, contradictory reports exist regarding the correlation between plasma GFAP levels and measures of astrogliosis as investigated with different PET tracers or at autopsy. Plasma GFAP levels were thus positively correlated with 18F-SMBT-1 uptake in sporadic AD patients compared to control groups [11], but showed no correlation or were even negatively correlated with 11C-DED [5] or GFAP levels in brain tissue [8], suggesting that mechanisms beyond reactive astrocytes or CSF release may contribute to elevated blood GFAP levels [6]. Moreover, in a cohort study on multiple sclerosis (MS), serum GFAP levels failed to predict disease activity and progression, whereas CSF GFAP levels were significant predictors despite a correlation existing between CSF and serum GFAP levels and other glial/neuroinflammation markers [12].

Delving into more practical considerations, quantifying GFAP levels in blood is challenging for conventional ELISA methods, which has led to the adoption of ultrasensitive techniques such as SIMOA. However, the inconsistencies in GFAP levels across studies indicate a lack of standardized criteria for its use as a biomarker, which might be due to limitations in antibody-based methods, including the aggregation-related hook effect and the presence of multiple GFAP isoforms and post-translational modifications [13]. To advance GFAP as a more reliable biomarker, standardized quantification methods, sample handling protocols including antibody information, and comprehensive studies on GFAP isoforms are essential to clarify the origins of GFAP release and improve its analytical accuracy.

Despite the numerous limitations and unresolved issues surrounding blood GFAP level elevations, these levels remain broadly accepted as biomarkers reflecting neurodegenerative disease stages, not only specific to AD but also early amyloidosis, dementia or faster cognitive decline [4]. Alongside other markers such as phosphorylated tau, amyloid beta 42/40, and neurofilament light chain protein (NfL), blood GFAP is believed to enhance our understanding of disease progression. However, for GFAP to be recognized as a reliable biomarker, a rigorous examination of its origins and causal links to pathophysiological conditions is essential, grounded in concrete biological evidence rather than correlations alone.

To truly determine GFAP’s value, we must undertake a comprehensive investigation that includes mapping GFAP expression across all relevant tissues, selectively marking or targeting GFAP in specific cell types, for example, along with PET imaging targeting particular cells, and closely examining the conditions that trigger GFAP release from astrocytes and reactive astrocytes. One way of observing GFAP release might be possible by analyzing astrocyte-derived exosomes through astrocyte-specific markers. These biological analyses must be backed by global, longitudinal cohort studies with rigorously standardized measurement methods, along with the support of imaging probes for reactive astrocytes. Only with such a thorough and meticulous approach can we move beyond superficial associations and harness GFAP as a precise, reliable biomarker for astrocyte reactiveness in neurodegenerative diseases.

Not applicable. The study contains publicly available data from published studies.

  1. Nam M-H, Na H, Lee CJ, Yun M. A key mediator and imaging target in Alzheimer’s disease: unlocking the role of reactive astrogliosis through MAOB. Nuc Med Mol Imaging. 2024;58:177–84.

    Article Google Scholar

  2. Shen X-N, Huang S-Y, Cui M, Zhao Q-H, Guo Y, Huang Y-Y, Zhang W, Ma Y-H, Chen S-D, Zhang Y-R, et al. Plasma glial fibrillary acidic protein in the alzheimer disease continuum: relationship to other biomarkers, differential diagnosis, and prediction of clinical progression. Clin Chem. 2023;69(4):411–21.

    Article CAS PubMed Google Scholar

  3. Bellaver B, Povala G, Ferreira PCL, João PF-S, Leffa DT, Lussier FZ, Benedet AL, Ashton NJ, Triana-Baltzer G, Kolb HC, et al. Astrocytic reactivity influences amyloid-β effects on Tau pathology in preclinical Alzheimer’s disease. Nat Med. 2023;29:1774–81.

    Article Google Scholar

  4. Jack CR Jr, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, Hansson O, Ho C, Jagust W, McDade E, et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s association workgroup. Alzheimers Dement. 2024;20(8):5143–69.

    Article PubMed PubMed Central Google Scholar

  5. Chiotis K, Johansson C, Rodriguez-Vieitez E, Ashton NJ, Blennow K, Zetterberg H, Graff C, Nordberg A. Tracking reactive astrogliosis in autosomal dominant and sporadic Alzheimer’s disease with multi-modal PET and plasma GFAP. Mol Neurodegener. 2023;18:60.

    Article CAS PubMed PubMed Central Google Scholar

  6. Benedet AL, Milà-Alomà M, Vrillon A, Ashton NJ, Pascoal TA, Lussier F, Karikari TK, Hourregue C, Cognat Emmanuel, Dumurgier J, et al. Differences between plasma and cerebrospinal fluid glial fibrillary acidic protein levels across the alzheimer disease continuum. JAMA Neurol. 2021;78(12):1471–83.

    Article PubMed Google Scholar

  7. Messing A, Brenner M. GFAP at 50. ASN Neuro. 2020;0:1–23.

    Google Scholar

  8. Varma VR, An Y, Kac PR, Bilgel M, Moghekar A, Loeffler T, Amschl D, Troncoso J, Blennow K, Zetterberg H, et al. Longitudinal progression of blood biomarkers reveals a key role of astrocyte reactivity in preclinical Alzheimer’s disease. MedRxiv. 2024. https://doi.org/10.1101/2024.01.25.24301779.

    Article PubMed PubMed Central Google Scholar

  9. Peretti DE, Boccalini C, Ribaldi F, Scheffler M, Marizzoni M, Ashton NJ, Zetterberg H, Blennow K, Frisoni GB, Garibotto V. Association of glial fibrillary acid protein, Alzheimer’s disease pathology and cognitive decline. Brain. 2024;147:4094–104.

    Article PubMed PubMed Central Google Scholar

  10. Grundmann D, Loris E, Maas-Omlor S, Huang W, Scheller A, Kirchhoff F, Schäfer K-H. Enteric Glia: S100, GFAP, and beyond. Anat Rec. 2019;302:1333–44.

    Article CAS Google Scholar

  11. Chatterjee P, Doré V, Pedrini S, Krishnadas N, Thota R, Bourgeat P, Ikonomovic MD, Rainey-Smith SR, Burnham SC, Fowler C, et al. Plasma glial fibrillary acidic protein is associated with 18F-SMBT-1 PET: two putative astrocyte reactivity biomarkers for Alzheimer’s disease. J Alzheimers Dis. 2023;92(2):615–28.

    Article CAS PubMed PubMed Central Google Scholar

  12. Cross AH, Gelfand JM, Thebault S, Bennett JL, von Büdingen HC, Cameron B, Carruthers R, Edwards K, Fallis R, Gerstein R, et al. Emerging cerebrospinal fluid biomarkers of disease activity and progression in multiple sclerosis. JAMA Neurol. 2024;81(4):373–83.

    Article PubMed PubMed Central Google Scholar

  13. Gogishvili D, Honey MIJ, Verberk IMW, Vermunt L, Hol EM, Teunissen CE, Abeln S. The GFAP proteoform puzzle: how to advance GFAP as a fluid biomarker in neurological diseases. J Neurochem. 2025;169(1):e16226.

    Article CAS PubMed Google Scholar

Download references

We thank Dr. Joo Min Park for kind guidance.

Open access funding provided by University of Gothenburg.

This study was supported by a Brain Pool Program (RS-2023-00263612) from the National Research Foundation of Korea and the Center for Cognition and Sociality (IBS-R001-D2) under the Institute for Basic Science (IBS), Republic of Korea.

Authors and Affiliations

  1. Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea

    Wongu Youn & C. Justin Lee

  2. Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea

    Mijin Yun

  3. Department of Psychiatry and Neurochemistry and the Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, 41345, Sweden

    Michael Schöll

  4. Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, WC1E, UK

    Michael Schöll

  5. Department of Neuropsychiatry, Sahlgrenska University Hospital, Mölndal, 43141, Sweden

    Michael Schöll

Authors
  1. Wongu YounView author publications

    You can also search for this author inPubMed Google Scholar

  2. Mijin YunView author publications

    You can also search for this author inPubMed Google Scholar

  3. C. Justin LeeView author publications

    You can also search for this author inPubMed Google Scholar

  4. Michael SchöllView author publications

    You can also search for this author inPubMed Google Scholar

Contributions

W.Y., M.Y., C.J.L. and M.S. wrote the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Mijin Yun, C. Justin Lee or Michael Schöll.

Ethics approval and consent to participate

Not applicable. The study does not involve human subjects. No ethical approval and consent are required.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing financial interests in this manuscript.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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 the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other 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 this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

Abstract Image

Cite this article

Youn, W., Yun, M., Lee, C.J. et al. Cautions on utilizing plasma GFAP level as a biomarker for reactive astrocytes in neurodegenerative diseases. Mol Neurodegeneration 20, 54 (2025). https://doi.org/10.1186/s13024-025-00846-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13024-025-00846-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Biomarker
  • Glial fibrillary acidic protein
  • Neurodegenerative disease
  • Reactive astrocyte
血浆GFAP水平作为神经退行性疾病反应性星形细胞生物标志物的注意事项
这种时间和空间上的差异使人们对血液GFAP与星形细胞反应性的直接联系产生了疑问。脑脊液和血浆GFAP水平之间的差异并不是唯一的疑点;GFAP在各种体细胞中的表达也提出了关于血液GFAP真正起源的问题。尽管GFAP被广泛认为是星形细胞特异性蛋白,但其作用仍然知之甚少,部分原因是其在不同脑细胞类型和星形细胞亚群中的表达变化。即使在人脑中,也存在其他表达gfap的细胞,如发育中的神经祖细胞和室管膜细胞,需要钙结合蛋白B (S100β)、兴奋性氨基酸转运蛋白1 (EAAT1或GLAST)、谷氨酰胺合成酶(GS)和醛脱氢酶1家族成员L1 (ALDH1L1)等补充标记物来准确识别星形胶质细胞。除中枢神经系统外,正常情况下,GFAP在外周神经系统(PNS)的非髓鞘雪旺细胞、视网膜的神经胶质、肠神经系统(ENS)的肠胶质细胞、肾小管细胞、睾丸的Leydig和Sertoli细胞以及肝脏、皮肤、骨骼和胎盘的各种细胞类型中也有表达[7]。值得注意的是,在病理状态下,这些非脑GFAP表达细胞也上调GFAP,使查明血液GFAP起源的尝试复杂化。例如,GFAP在炎症性肠病患者的肠道中过度表达;帕金森病与肠胶质细胞GFAP表达和磷酸化升高有关;肝星状细胞在肝纤维化区附近显示GFAP过表达;在复杂胸主动脉手术后的血流中检测到GFAP。尽管有这些观察结果,还没有直接证据表明血液GFAP起源于大脑中的反应性星形胶质细胞。其次,血浆GFAP水平与其他神经胶质生物标志物之间的相关性不一致,而脑脊液GFAP水平与这些标志物密切相关。胶质生物标志物不仅仅局限于GFAP,还包括反应性星形胶质细胞的不同标志物,如CHI3L1和S100B,以及小胶质细胞分泌的髓样细胞2上表达的可溶性触发受体(sTREM2)。虽然脑脊液GFAP水平与这些胶质生物标志物相关,但通过不同的PET示踪剂或尸检研究,关于血浆GFAP水平与星形胶质细胞形成的相关性存在矛盾的报道。因此,与对照组相比,散发性AD患者血浆GFAP水平与18F-SMBT-1摄取[11]呈正相关,但与11C-DED[5]或脑组织GFAP水平[8]无相关性,甚至呈负相关,提示反应性星形胶质细胞或脑脊液释放之外的机制可能导致血液GFAP水平[6]升高。此外,在一项多发性硬化症(MS)的队列研究中,血清GFAP水平无法预测疾病的活动性和进展,而CSF GFAP水平是显著的预测因子,尽管CSF和血清GFAP水平与其他胶质/神经炎症标志物[12]存在相关性。深入到更实际的考虑,定量血液中GFAP水平对传统的ELISA方法来说是一个挑战,这导致了采用超灵敏技术,如SIMOA。然而,研究中GFAP水平的不一致性表明其作为生物标志物的使用缺乏标准化的标准,这可能是由于基于抗体的方法的局限性,包括聚集相关的钩效应和多种GFAP亚型和翻译后修饰[13]的存在。为了使GFAP成为更可靠的生物标志物,标准化的定量方法、包含抗体信息的样品处理方案以及对GFAP同种异构体的全面研究对于阐明GFAP释放的起源和提高其分析准确性至关重要。尽管血液GFAP水平升高有许多限制和未解决的问题,但这些水平仍然被广泛接受为反映神经退行性疾病阶段的生物标志物,不仅针对AD,还针对早期淀粉样变,痴呆或更快的认知能力下降bb0。与其他标志物如磷酸化的tau蛋白、β 42/40淀粉样蛋白和神经丝轻链蛋白(NfL)一起,血液GFAP被认为可以增强我们对疾病进展的理解。然而,要使GFAP被认为是一种可靠的生物标志物,对其起源及其与病理生理条件的因果关系进行严格的检查是必不可少的,要以具体的生物学证据为基础,而不仅仅是相关性。 为了真正确定GFAP的价值,我们必须进行全面的研究,包括绘制GFAP在所有相关组织中的表达图谱,选择性地标记或靶向特定细胞类型中的GFAP,例如,与针对特定细胞的PET成像一起,并密切检查触发星形胶质细胞和反应性星形胶质细胞释放GFAP的条件。观察GFAP释放的一种方法可能是通过星形胶质细胞特异性标记分析星形胶质细胞衍生的外泌体。这些生物学分析必须得到全球纵向队列研究的支持,这些研究采用严格标准化的测量方法,以及反应性星形胶质细胞成像探针的支持。只有通过这种彻底和细致的方法,我们才能超越表面的联系,利用GFAP作为神经退行性疾病中星形胶质细胞反应的精确、可靠的生物标志物。不适用。该研究包含来自已发表研究的公开数据。李俊华,李俊杰,尹明。阿尔茨海默病的一个关键介质和成像靶点:通过MAOB解锁反应性星形胶质细胞增生的作用。中华医学杂志,2009;38(5):397 - 397。[文章]学者沈晓宁,黄世勇,崔敏,赵启华,郭勇,黄永勇,张伟,马永华,陈绍东,张永荣,等。阿尔茨海默病连续体中的血浆胶质原纤维酸性蛋白:与其他生物标志物、鉴别诊断和临床进展预测的关系中国生物医学工程学报(英文版);2009;36(4):411 - 421。[文章]学者Bellaver B, Povala G, Ferreira PCL, jo<e:1> o PF-S, Leffa DT, Lussier FZ, Benedet AL, Ashton NJ, Triana-Baltzer G, Kolb HC,等。星形胶质细胞反应性影响淀粉样蛋白β对临床前阿尔茨海默病Tau病理的影响。中华医学杂志,2009;29:1774-81。[10]刘建军,刘建军,刘建军,刘建军,等。阿尔茨海默病诊断和分期的修订标准:阿尔茨海默病协会工作组。阿尔茨海默病。2024;20(8):5143-69。[j]学者Chiotis K, Johansson C, Rodriguez-Vieitez E, Ashton NJ, Blennow K, Zetterberg H, Graff C, Nordberg A.多模态PET和血浆GFAP追踪常染色体遗传和散发性阿尔茨海默病反应性星形胶质细胞增生。神经退行性疾病杂志。2023;18:60。文章学者Benedet AL, Milà-Alomà M, Vrillon A, Ashton NJ, Pascoal TA, Lussier F, Karikari TK, Hourregue C, Cognat Emmanuel, Dumurgier J,等。血浆和脑脊液胶质纤维酸性蛋白水平在阿尔茨海默病连续体中的差异中华神经科杂志,2011;38(12):1471 - 1483。文章发表于PubMed bbb学者Messing A, Brenner M. GFAP 50岁。神经网络学报,2020;0:1-23。[10]学者Varma VR, An Y, Kac PR, Bilgel M, Moghekar A, Loeffler T, Amschl D, Troncoso J, Blennow K, Zetterberg H,等。血液生物标志物的纵向进展揭示了星形胶质细胞反应性在临床前阿尔茨海默病中的关键作用。MedRxiv。2024. https://doi.org/10.1101/2024.01.25.24301779.Article PubMed PubMed Central bbb学者Peretti DE, Boccalini C, Ribaldi F, Scheffler M, Marizzoni M, Ashton NJ, Zetterberg H, Blennow K, Frisoni GB, Garibotto V.神经胶质原纤维酸蛋白与阿尔茨海默病病理和认知能力下降的关系。大脑。2024;147:4094 - 104。文章PubMed PubMed Central bbb学者Grundmann D, Loris E, Maas-Omlor S, Huang W, Scheller A, Kirchhoff F, Schäfer K-H。肠胶质细胞:S100, GFAP及以上。生物工程学报,2019;32(2):1333 - 44。[文章]学者Chatterjee P, dor<s:1> V, Pedrini S, Krishnadas N, Thota R, Bourgeat P, Ikonomovic MD, Rainey-Smith SR, Burnham SC, Fowler C等。血浆胶质原纤维酸性蛋白与18F-SMBT-1 PET相关:两种假定的阿尔茨海默病星形细胞反应性生物标志物中华老年痴呆症杂志,2009;32(2):391 - 391。文章CAS PubMed PubMed Central bbb学者Cross AH, Gelfand JM, Thebault S, Bennett JL, von bdingen HC, Cameron B, Carruthers R, Edwards K, Fallis R, Gerstein R,等。多发性硬化症新出现的脑脊液生物标志物的疾病活动和进展。中华神经科杂志,2014;31(4):373 - 383。学者Gogishvili D, Honey MIJ, Verberk IMW, vermont L, Hol EM, Teunissen CE, Abeln S. GFAP蛋白样之谜:如何推进GFAP作为神经系统疾病的液体生物标志物。中国生物医学工程学报,2009;32(1):391 - 391。我们感谢Joo Min Park博士的指导。由哥德堡大学提供的开放获取资金。本研究得到了韩国国家研究基金会和韩国基础科学研究所(IBS)认知与社会中心(IBS- r001 - d2)的人才库计划(RS-2023-00263612)的支持。 韩国国立大学基础科学研究所认知与社会性研究中心,大田34126C. Justin lee延世大学医学院核医学系,首尔,03722韩国;a . ijin yunn哥德堡大学精神病学和神经化学系,Wallenberg分子和转化医学中心,哥德堡,瑞典,41345;michael SchöllDementia伦敦大学学院皇后广场神经病学研究所研究中心,伦敦,WC1E, UKMichael SchöllDepartment Sahlgrenska大学医院神经精神病学研究中心,Mölndal;43141,瑞典michael SchöllAuthorsWongu youview作者出版物您也可以在pubmed谷歌ScholarMijin YunView作者出版物您也可以在pubmed谷歌ScholarC中搜索该作者。Justin LeeView作者出版物您也可以在pubmed谷歌ScholarMichael SchöllView作者出版物您也可以在pubmed谷歌scholarcontributions.y中搜索该作者。, m.y., C.J.L.和M.S.撰写了手稿。所有作者都阅读并批准了最终的手稿。通讯作者:Mijin Yun, C. Justin Lee或Michael Schöll。对参与者的伦理批准和同意不适用。这项研究不涉及人类受试者。不需要伦理批准和同意。发表同意不适用。竞争利益作者声明在本文中没有竞争的经济利益。出版方声明:对于已出版地图的管辖权要求和机构关系,普林格·自然保持中立。开放获取本文遵循知识共享署名4.0国际许可协议,该协议允许以任何媒介或格式使用、共享、改编、分发和复制,只要您适当地注明原作者和来源,提供知识共享许可协议的链接,并注明是否进行了更改。本文中的图像或其他第三方材料包含在文章的知识共享许可协议中,除非在材料的署名中另有说明。如果材料未包含在文章的知识共享许可中,并且您的预期用途不被法律法规允许或超过允许的用途,您将需要直接获得版权所有者的许可。要查看本许可的副本,请访问http://creativecommons.org/licenses/by/4.0/。知识共享公共领域免责条款(http://creativecommons.org/publicdomain/zero/1.0/)适用于本文中提供的数据,除非在数据的署名中另有说明。转载及授权:youn, W., Yun, M., Lee, C.J.等。血浆GFAP水平作为神经退行性疾病反应性星形细胞生物标志物的注意事项神经退行性病变,20,54(2025)。https://doi.org/10.1186/s13024-025-00846-9Download citation:收稿日期:2025年2月25日接受日期:2025年4月17日发布日期:2025年5月9日doi: https://doi.org/10.1186/s13024-025-00846-9Share本文任何您与之分享以下链接的人都可以阅读此内容:获取可共享链接对不起,本文目前没有可共享链接。【关键词】生物细胞细胞纤维酸性蛋白神经退行性疾病反应性星形胶质细胞
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Molecular Neurodegeneration
Molecular Neurodegeneration 医学-神经科学
CiteScore
23.00
自引率
4.60%
发文量
78
审稿时长
6-12 weeks
期刊介绍: Molecular Neurodegeneration, an open-access, peer-reviewed journal, comprehensively covers neurodegeneration research at the molecular and cellular levels. Neurodegenerative diseases, such as Alzheimer's, Parkinson's, Huntington's, and prion diseases, fall under its purview. These disorders, often linked to advanced aging and characterized by varying degrees of dementia, pose a significant public health concern with the growing aging population. Recent strides in understanding the molecular and cellular mechanisms of these neurodegenerative disorders offer valuable insights into their pathogenesis.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信