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CSF and blood levels of Neurofilaments, T-Tau, P-Tau, and Abeta-42 in amyotrophic lateral sclerosis: a systematic review and meta-analysis

Journal of Translational Medicine volume 22, Article number: 953 (2024) Cite this article

Abstract

Recent literature suggests that markers of neuroaxonal damage, such as neurofilaments and tau protein, might serve as potential biomarkers for ALS. We conducted this systematic review and meta-analysis study to compare cerebrospinal fluid (CSF) and blood levels of total tau (t-tau), phosphorylated tau (p-tau), amyloid beta peptide 42 (Abeta-42), and neurofilaments in ALS patients and controls. A systematic search of Cochrane Library, PubMed, Embase, and ISI Web of Science was conducted on March 18, 2022, and updated on January 26, 2023. Observational studies that compared the concentrations of neurofilament light chain (NfL), neurofilament heavy chain (NFH), t-tau, p-tau, or Abeta-42 in CSF or peripheral blood of ALS patients and controls were included. Data from relevant studies were independently extracted and screened for quality using a standard tool, by at least two authors. Meta-analysis was conducted when a minimum of 3 studies reported the same biomarker within the same biofluid. A total of 100 studies were eligible for at least one meta-analysis. CSF and blood levels of NfL (standardized mean difference (SMD) [95% CI]; CSF: 1.46 [1.25–1.68]; blood: 1.35 [1.09–1.60]) and NFH (CSF: 1.32 [1.13–1.50], blood: 0.90 [0.58–1.22]) were significantly higher in ALS patients compared with controls. The pooled differences between ALS patients and controls were not significant for CSF t-tau, blood t-tau, and CSF Abeta-42, but CSF p-tau was lower in ALS patients (-0.27 [-0.47- -0.07]). Significantly decreased p-tau/t-tau ratios were found in ALS patients compared with controls (-0.84 [-1.16- -0.53]). Heterogeneity was considerable in most of our meta-analyses. CSF and blood neurofilament levels, as well as the CSF p-tau/t-tau ratio, might be potential candidates for improving ALS diagnosis. Further research is warranted to better understand the underlying mechanisms and the clinical implications of these biomarker alterations.

Introduction

Amyotrophic Lateral Sclerosis (ALS), the most common form of adult-onset motor neuron disease (MND), is a devastating incurable neurodegenerative disease. It affects motor neurons in the brain and spinal cord, causing progressive painless muscle weakness, and death usually occurs due to respiratory failure [1]. Early and accurate diagnosis is crucial for optimizing patient care and developing potential therapeutic interventions. Due to the absence of gold standard diagnostic criteria, clinicians are left with obtaining an integrative approach based on clinical presentation, physical examination, and electromyographic studies (EMG) [2,3,4]. However, heterogenic clinical manifestations and shared presentation with ALS mimicking disorders (ALSmd) make the diagnosis further challenging [5].

The use of reliable biomarkers can help clinicians and researchers make timely and accurate diagnosis, better understand its etiology, develop potential therapeutic interventions, and provide prognostic information. Additionally, biomarkers can serve as surrogate endpoints in clinical trials, enabling a more efficient assessment of treatment efficacy. To date, several studies have demonstrated that neuroaxonal damage biomarkers, such as neurofilaments and tau protein, may reflect the underlying massive neurodegeneration in symptomatic ALS patients [6,7,8,9,10]. Neurofilaments are neuronal-specific structural proteins that determine axonal caliber and are involved in axonal transport. Neurofilaments are composed of three different subunits: neurofilament light chain (NfL), neurofilament medium chain (NFM), and neurofilament heavy chain (NFH). In the context of ALS, NfL has gained significant attention as a potential biomarker for disease diagnosis and prognosis [11]. Neuronal damage in the central or peripheral nervous system (CNS, PNS) prompts axons to release NfL into cerebrospinal fluid (CSF) and blood [11, 12]. Elevated levels of NfL and NFH have been detected in ALS patients, and previous studies report that higher levels are associated with faster disease progression and poorer prognosis [6, 7, 13]. Phosphorylation of NFH slows axonal transport and interaction with other cytoskeletal proteins, which may contribute to ALS progression [11, 14].

Tau, a phosphoprotein belonging to the family of microtubule-associated proteins (MAPs), is responsible for axonal transport, axon outgrowth, and maintenance of cell shape [15, 16]. Tau can be phosphorylated by specific kinases at threonine 181 (pTau), leading to its detachment from tubulin, with microtubule instability and disintegration [16]. Total tau (t-tau) and p-tau, along with amyloid beta peptide 42 (Abeta-42) are well-known biomarkers for Alzheimer’s disease (AD) [17]. There has been a rising debate over the use of these proteins as diagnostic ALS biomarkers [18,19,20,21].

In the present systematic review and meta-analysis, we aimed to quantify the differences in the CSF and blood concentrations of t-tau, p-tau, Abeta-42, and neurofilaments in patients with ALS compared to controls. This study will serve as the base stone to our successive discussion on the applicability of the investigated biomarkers in expedited ALS diagnosis.

Method

Study selection

This systematic review and meta-analysis was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statements [22]. The protocol of this systematic review and meta-analysis was registered on the PROSPERO website under the registration number of CRD42017078127 and is available in a separate publication [23]. We included the articles that met the following criteria: (1) observational studies with adult human subjects quantifying biomarkers of interest in the CSF or peripheral blood of ALS patients versus controls, (2) use of validated diagnostic criteria for ALS diagnosis [2, 24], (3) use of quantitative methods to determine biomarkers concentrations, and (4) A minimum of 10 patients in each study group. We excluded case reports, case studies, letters, reviews, and animal or in vitro studies. Studies that lacked a non-ALS control group and were limited to patients with comorbid conditions were excluded to avoid the possible effect of the concurrent disease on the biomarker levels (e.g., studies only including ALS with frontotemporal dementia (FTD)). In the studies reporting both ALS and ALS-FTD patients, we tried to extract the data for ALS patients without FTD, when possible. However, in the undividable situations, we only included studies whose samples had 50% or less ALS-FTD of the total ALS group population.

Search strategy

We systematically searched the Cochrane Library, PubMed, Embase, and ISI Web of Science to find related papers published since 1980. We applied no language restrictions. The detailed search terms and keywords for each biomarker is provided in Appendix 1. A preliminary search was conducted on March 18, 2022, followed by an update on January 26, 2023. A manual review of the reference and citation (based on what appeared on the article’s google scholar profile) lists of eligible papers and relevant reviews was conducted to identify additional studies. We also searched the grey literature and conference papers in accordance with the Cochrane Handbook for Systematic Reviews of Interventions [25].

Two independent authors assessed the titles and abstracts of all retrieved articles against eligibility criteria. When it was not possible to make a judgment regarding the eligibility of an article based on its abstract or title, at least two authors evaluated its full text. Disagreements were resolved by discussion or consultation with a third author. We checked for overlaps in the study site, recruitment period, and first/corresponding authors to avoid duplicate publication bias. If two or more studies with similar recruitment periods or first/corresponding authors were conducted at the same facility, the largest sample size was chosen.

Data extraction

Two authors independently extracted the following information from each included article: bibliographic details (first author’s name, study title, journal, year of publication, and country), demographics and clinical information (number of patients and controls, type of ALS and controls, study design, age, gender, specimen, ALSFRS-R, and duration of disease), measurements, including assay technique (enzyme-linked immunoassay (ELISA), single molecule array (SIMOA), chemiluminescence enzyme immunoassay, electrochemiluminescence), value type, and biomarker levels, and also the STROBE-ME checklist [26]. To better compare biomarker levels between ALS patients and control subjects, all non-ALS controls (Con) were further categorized into neurologically healthy controls (HCs), non-neurodegenerative controls (NNCs), and neurodegenerative controls (NCs). HCs consisted of individuals with no known neurological disorders. NNCs included patients with non-neurodegenerative neurological conditions such as headache, idiopathic intracranial hypertension, and inflammatory polyneuropathies. NCs comprised patients with neurodegenerative disorders other than ALS, including Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia. Additionally, some studies included patients with ALS mimic disorders (ALSmd), such as multifocal motor neuropathy and cervical myelopathy, and other motor neuron diseases (MNDs) like primary lateral sclerosis and progressive muscular atrophy. The specific composition of each control subgroup varied among the included studies, and not all studies used all subgroups. ALS gene carriers were excluded from the Con group, and presymptomatic ALS patients were excluded from the ALS group. As a supplementary analysis, we also compared the level of biomarkers between ALS patients and patients with ALSmd, other MNDs, frontotemporal lobar degeneration (FTLD), and AD.

In case possible, means and standard deviation (SD) of biomarker concentrations were extracted. According to the Cochrane Handbook, alternative summary statistics were transformed into means and SDs using formulas proposed by Wan and colleagues [27], or approximated using WebPlotDigitizer Software (version 4.5) when data were presented graphically.

Any inconsistencies found among the extracted data were resolved by discussion. The corresponding authors of the eligible studies were contacted if additional data were required.

Quality assessment

The revised version of Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was utilized to assess the quality of included studies [28]. The quality assessment using QUADAS-2 was independently performed by AB, AA, and ZS. Any disagreements were resolved through discussion or, when necessary, through consultation with EA, who served as the third author for judgement.

Statistical analysis

Data were meta-analyzed when at least 3 studies were included. The pooled standardized mean difference (SMD) and 95% confidence interval (CI) were calculated using the mean and SD of extracted biomarker concentrations, applying Hedges g to correct for small sample size bias. When there was significant heterogeneity, a random-effects meta-analysis model with DerSimonian and Laird approach was used. Otherwise, we applied the fixed-effects meta-analysis model using the inverse-variance method.

Heterogeneity assessment was carried out using Q statistic tests and the I2 index, which were interpreted based on the Cochrane Handbook [25]. We considered statistical heterogeneity insignificant if the associated I2 index was below 40%. We also conducted subgroup analyses to identify the possible sources of heterogeneity, based on the type of controls and assay technique.

Funnel plots and Egger’s test were used to evaluate the effect of unpublished studies or publication bias when at least five papers were eligible for analysis. Leave-one-out sensitivity analysis was conducted to identify studies that might have a disproportionate influence on the pooled effect size by removing each individual observation from the meta-analysis one at a time. All meta-analyses were conducted by R software version 4.2.3, R Foundation for Statistical Computing, using the meta and metafor packages. A two-tailed p-value < 0.05 was considered statistically significant.

Results

Study identification

From the 1204 unique records identified as a result of the literature search, 173 articles were read in full text to assess their eligibility and 95 met the inclusion criteria. Five additional papers were identified by searching through reference lists. Finally, a total number of 100 studies were included in our meta-analysis (Fig. 1). Further details regarding the inclusion of selected studies in the meta-analysis are provided in Appendix 2. An overview of the quality assessment results is provided in Appendix 3. The main features of the included studies are shown in eTable 1.

Fig. 1
figure 1

PRISMA flowchart of selected papers. Abeta-42, amyloid beta peptide 42; NFH, neurofilament heavy chain; NfL, neurofilament light chain; PRISMA, preferred reporting items for systematic reviews and meta-analyses; p-tau, phosphorylated tau; t-tau, total tau

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Findings

NfL levels across groups

Forty studies, comprising 3158 ALS patients and 4579 control subjects, reported the level of NfL in CSF. The meta-analysis results demonstrated higher CSF NfL concentrations among ALS patients than Con (SMD = 1.46 [95% CI: 1.25, 1.68], Fig. 2A). Similarly, higher levels of CSF NfL were found in patients with ALS compared to HCs (SMD = 1.62 [95% CI: 1.44, 1.80], Fig. 2B), NNCs (SMD = 1.22 [95% CI: 0.94, 1.49], Fig. 2C), and NCs (SMD = 1.29 [95% CI: 0.94, 1.64], Fig. 2D). Increased CSF NfL levels were also found compared with patients with ALSmd (SMD = 1.539, 95% CI = 1.307–1.770), other MNDs (SMD = 1.083, 95% CI = 0.664–1.501), FTLD (SMD = 0.828, 95% CI = 0.605–1.052), and AD (SMD = 1.374, 95% CI = 0.886–1.863) (eFigure 1 A-D).

Fig. 2
figure 2

Meta-analysis of CSF and Blood NfL levels in ALS patients compared with Con (A & E), HCs (B & F), NNCs (C & G), and NCs (D & H). ALS, amyotrophic lateral sclerosis; CI, confidence interval; Con, all non-ALS controls; CSF, cerebrospinal fluid; ECL, electrochemiluminescence; ELISA, enzyme-linked immunoassay; HCs, healthy controls; NCs, neurodegenerative controls; NfL, neurofilament light chain; NNCs, non-neurodegenerative controls; SIMOA, single molecule array; SMD, standardized mean difference

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Blood levels of NfL were measured in 29 studies involving 2863 ALS patients and 3080 control subjects. Increased levels of blood NfL were found in ALS patients compared with Con (SMD = 1.35, 95% CI = 1.09–1.60), HCs (SMD = 1.50, 95% CI = 1.30–1.70), NNCs (SMD = 0.78, 95% CI = 0.32–1.24), and NCs (SMD = 1.35, 95% CI = 1.06–1.65) (Fig. 2E-H). Likewise, the level of blood NfL was higher among ALS patients compared with patients with ALSmd (SMD = 1.226, 95% CI = 1.070–1.383), other MNDs (SMD = 1.118, 95% CI = 0.595–1.641), FTLD (SMD = 1.211, 95% CI = 0.813–1.610), and AD (SMD = 1.288, 95% CI = 0.972–1.603) (eFigure 1E-H).

Subgroup analyses were also conducted based on the specific NfL assay method, showing maintenance of significant effect sizes comparing ALS patients with Con (Fig. 2A and E) and HCs (Fig. 2B and F). Funnel plot asymmetry was found in CSF NfL meta-analyses of ALS vs. Con and ALS vs. NNCs (eFigure 2), and meta-analyses of blood NfL in ALS vs. HCs (eFigure 3), indicative of potential publication bias. Sensitivity analyses are shown in eFigure 4. Shi 2022 [29] (ALS vs. Con and ALS vs. NNCs) and Olsson 2019 [30] (ALS vs. NCs) were potentially influential studies in meta-analyses of CSF NfL. In meta-analyses of blood NfL, Wilke 2016 [31] was found to be an influential study in the meta-analysis of ALS vs. HCs.

NFH levels across groups

NFH levels in CSF and blood have been reported in 33 (ALS: 2615 patients, Con: 2526 subjects) and 14 (ALS: 1241 patients, Con: 888 participants) publications, respectively. Both CSF and blood levels of NFH were significantly higher among ALS patients than in Con and different subgroups of Con (Fig. 3, eFigure 5, and eFigure 6).

Fig. 3
figure 3

Meta-analysis of CSF and Blood NFH levels in ALS patients compared with Con (A & E), HCs (B & F), NNCs (C), and NCs (D & G). ALS, amyotrophic lateral sclerosis; CI, confidence interval; Con, all non-ALS controls; CSF, cerebrospinal fluid; ECL, electrochemiluminescence; ELISA, enzyme-linked immunoassay; HCs, healthy controls; NCs, neurodegenerative controls; NFH, neurofilament heavy chain; NNCs, non-neurodegenerative controls; SIMOA, single molecule array; SMD, standardized mean difference

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Results of subgroup analyses pointed to the persistence of effect sizes when ALS patients were compared with Con (Fig. 3A and E) and HCs (Fig. 3B), according to the specific NFH assay method. Funnel plots of CSF NFH meta-analysis in ALS versus Con and ALS versus NNCs (eFigure 7) and blood NFH meta-analysis in ALS vs. Con (eFigure 8) showed asymmetry. In meta-analyses of CSF NFH, Shi 2022 [29] (ALS vs. Con and ALS vs. NNCs), and in meta-analyses of blood NFH McCombe 2015 [32] (ALS vs. HCs), Benatar 2020 [33] (ALS vs. NCs), and De Schaepdryver 2018 [13] (ALS vs. NCs) were potentially influential publications (eFigure 9).

Abeta-42 levels across groups

A total of fifteen studies compared the CSF Abeta-42 concentration between 575 ALS patients and 2409 controls. The pooled difference of CSF Abeta-42 in the ALS group compared with Con, HCs, and NNCs did not reach significance (Fig. 4). However, the meta-analysis showed significant higher levels of CSF Abeta-42 in patients with ALS compared with NCs (Fig. 4D). The level of CSF Abeta-42 was significantly higher among ALS patients compared with patients with AD (SMD = 1.943, 95% CI = 0.722–3.165), but was similar to FTLD patients (SMD = 0.158, 95% CI=-0.417-0.732) (eFigure 10).

Fig. 4
figure 4

Meta-analysis of CSF Abeta-42 levels in ALS patients compared with Con (A), HCs (B), NNCs (C), and NCs (D). Abeta-42, amyloid beta peptide 42; ALS, amyotrophic lateral sclerosis; CI, confidence interval; Con, all non-ALS controls; CSF, cerebrospinal fluid; ELISA, enzyme-linked immunoassay; HCs, healthy controls; NCs, neurodegenerative controls; NNCs, non-neurodegenerative controls; SMD, standardized mean difference

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The results remained nonsignificant when ALS patients were compared with Con (Fig. 4A), according to the method used for CSF Abeta-42 assay. No funnel plot asymmetry was found (eFigure 11). Sensitivity analyses revealed that Sjögren 2002 [34] (ALS vs. HCs), Ye 2020 [35] and Delaby 2020 [36] (ALS vs. NNCs), and Cousins 2022 [19] (ALS vs. NCs) might be influential studies (eFigure 12).

t-tau levels across groups

CSF t-tau was measured in 29 studies, including 1760 ALS patients and 3573 control subjects (Fig. 5A-D). When ALS patients were compared with all controls (Con), the pooled difference was not significant (Fig. 5A). However, the level of CSF t-tau was significantly increased among ALS patients compared with HCs (Fig. 5B), NNCs (Fig. 5C), and ALSmd patients (SMD = 0.445, 95% CI = 0.167–0.724, eFigure 13 A) and was significantly decreased in comparison with NCs (Fig. 5D) and patients with AD (SMD=-1.314, 95% CI=-1.634 – -0.994, eFigure 13D). Meta-analysis of CSF t-tau in ALS patients compared with patients with other MNDs (SMD = 0.123, 95% CI=-0.396–0.642, eFigure 13 C) and FTLD (SMD=-0.082, 95%CI=-0.478–0.315, eFigure 13D) did not point to a significant pooled difference.

Fig. 5
figure 5

Meta-analysis of CSF and blood t-tau levels in ALS patients compared with Con (A & E), HCs (B), NNCs (C & F), and NCs (D). ALS, amyotrophic lateral sclerosis; CI, confidence interval; CLEIA, chemiluminescence enzyme immunoassay; Con, all non-ALS controls; CSF, cerebrospinal fluid; ELISA, enzyme-linked immunoassay; HCs, healthy controls; NCs, neurodegenerative controls; NNCs, non-neurodegenerative controls; SIMOA, single molecule array; SMD, standardized mean difference; t-tau, total tau

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Four studies compared the level of blood t-tau between ALS patients (319 patients) and Con (439 participants). The meta-analysis results showed no significant difference between ALS patients and Con or NNCs, regarding the blood t-tau concentrations (Fig. 5E and F).

Subgroup analysis of ALS vs. Con based on the method used to assay CSF t-tau did not show significant subgroup differences (Fig. 5A). However, the pooled SMD of meta-analysis in studies that used CLEIA or SIMOA for CSF t-tau measurement was significant (Fig. 5A). No funnel plot asymmetry was found (eFigure 14). Sensitivity analyses of CSF t-tau yielded pooled estimates similar to the overall results, indicating that no single study significantly influenced the pool effect size or heterogeneity (eFigure 15). Kmezic 2022 [37] was a potentially influential observation in meta-analyses of blood t-tau.

p-tau levels across groups

A total of 23 studies reported the level of CSF p-tau among 1477 ALS patients and 3106 controls. Compared to all controls, ALS patients had decreased CSF p-tau levels (Fig. 6A). The pooled difference in CSF p-tau was not significant when ALS patients were compared with HCs (Fig. 6B) and NNCs (Fig. 6C). However, ALS patients had lower CSF p-tau levels than NCs (SMD = -0.64, 95% CI: -0.94 to -0.34, Fig. 6D). Furthermore, the level of CSF p-tau was significantly decreased in the ALS group in comparison with FTLD (SMD=-0.321, 95% CI=-0.611 – -0.031, eFigure 16 C) and AD (SMD=-1.372, 95% CI=-1.692 – -1.053, eFigure 16D) groups, but it was similar to ALSmd (SMD = 0.014, 95% CI=-0.246–0.273, eFigure 16 A) and other MNDs (SMD = 0.313, 95% CI=-0.233–0.858, eFigure 16B).

Fig. 6
figure 6

Meta-analysis of CSF p-tau levels in ALS patients compared with Con (A), HCs (B), NNCs (C), and NCs (D). ALS, amyotrophic lateral sclerosis; CI, confidence interval; Con, all non-ALS controls; CSF, cerebrospinal fluid; HCs, healthy controls; NCs, neurodegenerative controls; NNCs, non-neurodegenerative controls; p-tau, phosphorylated tau; SMD, standardized mean difference

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In none of the meta-analyses of CSF p-tau, funnel plot asymmetry was observed (eFigure 17). Cousins 2022 [19] (ALS vs. Con & ALS vs. NCs) and Gong 2022 [20] (ALS vs. NNCs) were potentially influential studies (eFigure 186).

p-tau/t-tau ratio across groups

The CSF p-tau/tau ratio was evaluated in nine studies involving 771 ALS patients and 589 controls. According to the results of plausible meta-analyses, the CSF p-tau/t-tau ratio was significantly decreased among ALS patients compared with Con (SMD=-0.84, 95% CI=-1.16 to -0.53, Fig. 7A), HCs (SMD=-0.92, 95% CI=-1.58 to -0.26, Fig. 7B), NNCs (SMD=-1.19, 95% CI=-1.83 to -0.55, Fig. 7C), and ALSmd (SMD=-0.930, 95% CI=-1.236 to -0.624, eFigure 19).

Fig. 7
figure 7

Meta-analysis of CSF p-tau/t-tau ratios in ALS patients compared with Con (A), HCs (B), and NNCs (C). ALS, amyotrophic lateral sclerosis; CI, confidence interval; Con, all non-ALS controls; CSF, cerebrospinal fluid; HCs, healthy controls; NNCs, non-neurodegenerative controls; p-tau, phosphorylated tau; SMD, standardized mean difference; t-tau, total tau

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No funnel plot asymmetry was found (eFigure 20). According to sensitivity analyses, Lanznaster 2020 [38] was a potential, influential observation (eFigure 21).

Discussion

In this systematic review and meta-analysis, we quantified the difference of neurofilaments, t-tau, p-tau, and Abeta-42 levels in ALS patients and different control populations. Our main findings are: (1) Consistent increase in CSF and blood levels of NfL and NFH in ALS patients compared to all control groups, (2) Significantly lower levels of CSF p-tau in ALS patients than Con and NCs, with no significant difference compared to other controls such as HCs and NNCs, (3) Significant decrease in CSF levels of p-tau/t-tau ratio in ALS patients compared to Con, HCs, and NNCs, (4) Significantly higher CSF levels of t-tau in ALS patients compared to HCs and NNCs, while it was lower in comparison to NCs, and was indifferent compared to Con (5) No significant difference was recorded in the blood levels of t-tau in ALS patients with Con and NNCs, (6) Lastly, CSF levels of Abeta-42 in ALS patients was significantly increased compared to NCs; however, it was not significantly different from Con and HCs. The schematic results of this study are provided in Fig. 8.

Fig. 8
figure 8

The schematic results of this study. Abeta-42, amyloid beta peptide 42; AD, Alzheimer’s disease; ALS, amyotrophic lateral sclerosis; ALSmd, ALS mimic disorders; Con, all non-ALS controls; CSF, cerebrospinal fluid; FTLD, frontotemporal lobar degeneration; HCs, healthy controls; MND, motor neuron disease; NCs, neurodegenerative controls; NFH, neurofilament heavy chain; NfL, neurofilament light chain; NNCs, non-neurodegenerative controls; p-tau, phosphorylated tau; t-tau, total tau

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The damaged motor neurons in the anterior horn of the spinal cord comprised of large axons, play a major role in the release of neurofilaments in the CSF. Increased blood levels of neurofilaments may result from either CSF drainage into the bloodstream or peripheral neurodegenerative processes. Thus, neurofilaments can be a specific marker indicative of neuroaxonal damage. Our findings strongly suggest consistent increase of CSF and blood-based NFL and NFH in ALS patients compared to all control groups, indicating their specificity to the disease. A large systematic review evaluated CSF NfL levels across different neurological disorders similarly showed increased CSF levels of NfL compared with HCs in most neurological conditions. Notably, their largest effect sizes were observed in human immunodeficiency virus (HIV)-infected individuals with cognitive impairment, FTD/ALS, ALS, and Huntington’s disease (HD) which further proves our current results [39]. In another study, Ashton et al. [40], evaluated plasma NfL levels in a multicenter study including 13 neurodegenerative disorders, Down syndrome, depression, and cognitively unimpaired controls. Similarly, the highest concentrations of plasma NfL were found in patients with ALS, FTD, and Down syndrome Alzheimer’s disease (DSAD) [40]. In addition, High AUCs (> 0.8) were found in distinguishing ALS from most neurodegenerative and non-neurodegenerative diagnoses [40].

Larger studies that compared the diagnostic performance of NfL and pNFH in CSF reported a relatively higher area under the curves (AUCs) and better specificity for the pNFH [41,42,43,44]. However, the potential utility of blood pNFH is complex. De Schaepdryver et al. [13], showed inferior performance of serum pNFH compared with CSF pNFH to discriminate patients with ALS from those with ALSmd and other controls. It is believed that the formation of aggregates in peripheral blood, known as the “hook effect”, hamper the utility of pNFH [45, 46]. In the current study, the pooled effect sizes for CSF NFH meta-analyses were larger than blood NFH meta-analyses (Fig. 3). Furthermore, there were not enough included studies to perform a meta-analysis of blood NFH to compare ALS with either NNCs, ALSmd, FTLD, or AD.

The complex relationship between neurofilament protein levels and disease duration in ALS needs further discussion. While our meta-analysis showed elevated levels of neurofilaments in ALS patients compared to controls, it’s considerable how these levels might change throughout the disease. Lu et al. [46] observed in their longitudinal study that plasma NFH levels increased during the early and middle stages of the disease but tended to stabilize or decrease slightly in later stages. This pattern might be connected to the progressive loss of motor neurons as the disease advances. Similarly, Benatar et al. [33] found that serum NfL levels were already elevated in asymptomatic ALS gene carriers and continued to rise as individuals progressed to symptomatic ALS, suggesting that neurofilament levels may be early biomarkers of disease onset. However, other studies have reported relatively stable neurofilament levels over time. Steinacker et al. [8] found that CSF levels of both NfL and pNFH remained relatively constant over follow-up periods. This variability could be due to factors such as different rates of disease progression among patients, variations in the site of disease onset, or the influence of genetic factors. These findings highlight the importance of considering disease duration and clinical features when interpreting neurofilament levels in ALS patients. While elevated levels can be a useful diagnostic marker, the absolute value might not always correlate directly with disease severity or progression.

Small to moderate SMDs were found in meta-analyses of Abeta-42, t-tau, and p-tau, comparing ALS patients with controls. Our results indicate that Abeta-42, t-tau, and p-tau may not be reliable biomarkers for ALS. CSF t-tau was the most extensively evaluated biomarker, examined in 29 studies with 1760 patients with ALS and 3573 controls. When ALS patients were compared with Con, a heterogeneous group of all non-ALS controls (and possibly a representative sample of general neurology patients) no significant difference in CSF tau levels was detected. ALS patients had slightly higher CSF t-tau levels than control groups which consisted mostly of individuals with non-neurodegenerative disorders, such as HCs, NNCs, and ALSmd. However, no significant pooled difference was found between patients with ALS and NNCs regarding blood t-tau levels. Decreased CSF t-tau levels were found in ALS patients compared with NCs, which might be mainly derived from the inclusion of AD patients. Studies that evaluated the level of CSF t-tau in ALS patients against AD patients unanimously reported significantly decreased levels in patients with ALS; however, SMDs compared with other MNDs and FTLD were not significant.

The level of CSF p-tau in ALS patients was slightly decreased compared with Con, but it was not significantly different from HCs, NNCs, ALSmd, and other MNDs. Nevertheless, CSF p-tau levels were significantly decreased in ALS patients compared with NCs, and patients with FTLD and AD. Like CSF t-tau, all studies that compared CSF p-tau levels between ALS and AD patients showed significantly reduced levels in ALS patients.

Despite the discrepancy in the current literature on the level of CSF t-tau and p-tau in our study population, almost all the studies, except for one study in the CSF p-tau/t-tau meta-analysis, reported significantly decreased ratios in ALS patients. Grossman et al. [47], found that lower p-tau/t-tau ratios were associated with reduced white matter fractional anisotropy (FA) in the corticospinal tract, prefrontal cortex, and midbrain in the magnetic resonance imaging (MRI) of ALS patients that are brain regions known to be affected in ALS [48]. Whether the decreased ratios are secondary to increased t-tau levels or to decreased p-tau levels is yet to be addressed. Among the studies that found significantly decreased p-tau/t-tau ratios, one study attributed the observation to the significant increase in t-tau levels and similar p-tau levels [7], while the other study observed a significant decrease in CSF p-tau levels and no difference in t-tau in [47], and the rest reported insignificant difference in CSF levels of t-tau and p-tau [49, 50]. Unfortunately, due to the small number of included studies, no meta-analysis was conducted to compare CSF p-tau/t-tau ratios between ALS patients and NCs, and patients with other MNDs, FTLD, and AD. However, current evidence suggests that CSF p-tau/t-tau ratios are decreased in ALS patients compared with patients with FTD and four-repeat (4R-) tauopathies [47, 51]. Further research is necessary to elucidate this altered ratio’s underlying mechanisms and clinical implications in ALS.

CSF Abeta-42 was the least altered biomarker in this study. The level of Abeta-42 in the CSF of ALS patients was not significantly different from that of HCs and NNCs. Only one study compared CSF Abeta-42 levels between ALS patients and patients with ALSmd, which reported a non-significant difference [9]. As with t-tau, the moderate SMD found for comparison between ALS and NCs may mainly be driven by the inclusion of AD patients, who have significantly decreased levels of Abeta-42. These findings indicate that Abeta-42 may not be directly involved in ALS pathogenesis and might not be a useful biomarker for ALS.

The diagnostic performances of neurofilaments and t-tau, p-tau, and Abeta-42 in ALS patients were directly compared in several studies [6,7,8, 52]. Falzone et al. [6], showed markedly better performance of serum NfL compared with serum t-tau in distinguishing ALS patients from HCs, NCs, and ALSmd. Abu-Rumeileh et al. [7], reported high AUCs for both CSF NfL and p-tau/t-tau ratio in differentiating ALS patients from HCs, but diagnostic performance of NfL was superior to p-tau/t-tau ratio in differentiating patients with ALS and ALSmd (AUC = 0.922 vs. 0.750, respectively). In a study conducted by Scarafino et al. [52], CSF NfL was the optimal biomarker in discrimination between ALS and ALSmd, smaller AUCs were found for CSF t-tau and CSF p-tau, and CSF p-tau/t-tau ratio was not efficient in discriminating ALS from ALSmd. Steinacker et al. [8], reported high AUCs for CSF NfL and pNFH when analyzing the MND group against all non-MND patients but found small AUCs for CSF t-tau and p-tau (AUC = 0.520 and 0519, respectively).

The findings of this study strongly advocate adding blood NfL and NFH to routine pre-diagnostic workups as minimally invasive tests. In cases with inconclusive results, CSF measurements of neurofilaments and p-tau/t-tau ratio may prove helpful. Several previous studies have shown that CSF and blood neurofilaments levels are predictors of future ALSFRSR decline and survival duration [7, 33, 46, 53, 54]. Furthermore, it seems that CSF/blood neurofilaments levels remain largely stable during the disease course [33, 42, 44, 46, 55, 56]. Hence, one-time CSF/blood NfL and NFH measurement might not only help ALS diagnosis but may also provide beneficial personalized prognostic information to patients with ALS. Neuromuscular centers are advised to validate their institutional standard operating procedures (SOPs) and reference intervals for candidate biomarkers as was recommended [57, 58].

The main strengths of our study include a comprehensive literature search and considering different types of control groups to better decipher the importance of these biomarkers. It is important to note that this meta-analysis has several limitations. Firstly, there was considerable heterogeneity among the included studies in terms of sample size, study population, study design, and measurement techniques. Secondly, the control groups varied across studies, which may have influenced the comparability of results. Thirdly, the majority of included studies focused on CSF biomarkers, with limited data available on blood biomarkers.

Additionally, we did not specifically examine the relationship between neurofilaments and cognitive impairment in ALS patients. Given that cognitive impairments are common in ALS patients, ranging from subtle alterations to more severe impairments, including frontotemporal dementia, and their possible impact on disease progression, this is an important area for future research. Lastly, our analysis did not explore the potential relationships between genetic mutations (such as FUS and C9orf72) and the levels of biomarkers, including t-tau, p-tau, Abeta-42, and neurofilaments. These genetic factors could influence ALS prognosis and may also affect biomarker levels. Future studies should aim to address these aspects to provide a more comprehensive understanding of biomarker dynamics in ALS.

Conclusion

In conclusion, this meta-analysis study is suggesting neurofilaments and p-tau/t-tau ratio as potential biomarkers for ALS. Our current findings alongside the available evidence confirm neurofilaments as the most reliable biomarkers for ALS. Both blood and CSF levels of NfL and NFH were consistently increased among ALS patients. T-tau, p-tau, and Abeta-42 per se were not dramatically altered in ALS patients and might not be valid biomarkers for ALS, based on our current knowledge. However, implementing a panel of biomarkers might be an effective approach for early diagnosis of ALS patients. Our findings strongly contribute to the growing body of knowledge surrounding ALS pathology and highlight the need for further research to better understand the underlying mechanisms and clinical implications of these biomarker alterations.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Abeta-42:

Amyloid beta peptide 42

AD:

Alzheimer’s disease

ALS:

Amyotrophic lateral sclerosis

ALSmd:

ALS mimic disorders

AUC:

Area under the curve

CI:

Confidence interval

CLEIA:

Chemiluminescence enzyme immunoassay

CNS:

Central nervous system

Con:

All non-ALS controls

CSF:

Cerebrospinal fluid

DSAD:

Down syndrome Alzheimer’s disease

ECL:

Electrochemiluminescence

ELISA:

Enzyme-linked immunoassay

FA:

Fractional anisotropy

FTD:

Frontotemporal dementia

FTLD:

Frontotemporal lobar degeneration

HCs:

Healthy controls

HD:

Huntington’s disease

HIV:

Human immunodeficiency virus

MAP:

Microtubule-associated protein

MND:

Motor neuron disease

MRI:

Magnetic resonance imaging

NCs:

Neurodegenerative controls

NFH:

Neurofilament heavy chain

NfL:

Neurofilament light chain

NFM:

Neurofilament medium chain

NNCs:

Non-neurodegenerative controls

PNS:

Peripheral nervous system

PRISMA:

Preferred reporting items for systematic reviews and meta-analyses

p-tau:

Phosphorylated tau

QUADAS:

Quality Assessment of Diagnostic Accuracy Studies

SD:

Standard deviation

SIMOA:

Single molecule array

SMD:

Standardized mean difference

SOP:

Standard operating procedures

t-tau:

Total tau

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Author notes

  1. Helia Mojtabavi, Atefeh Behkar, Arash Heidari and Atra Ajdari contributed equally to this work.

Authors and Affiliations

  1. Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran

    Elmira Agah, Seyed Vahid Mousavi & Abbas Tafakhori

  2. Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran

    Elmira Agah, Helia Mojtabavi, Atra Ajdari, Zoha Shaka & Nima Rezaei

  3. National Center for Adaptive Neurotechnologies (NCAN), Albany, NY, USA

    Helia Mojtabavi

  4. Occupational Sleep Research Center, Baharloo Hospital, Tehran University of Medical Sciences, Tehran, Iran

    Atefeh Behkar

  5. Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

    Arash Heidari

  6. Research Center for Immunodeficiencies (RCID), Children’s Medical Center Hospital, Tehran University of Medical Sciences, Tehran, Iran

    Arash Heidari

  7. Department of Radiology, Harborview Medical Center, University of Washington, Seattle, WA, USA

    Negar Firoozeh

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Contributions

All authors contributed to the review conception and design. EA, HM, AB, AH, AA, ZS, SVM and NF were involved in data collection. AB, AH, and ZS completed the quality assessment. EA performed data analysis and interpretation. All authors contributed to the drafting of the article, revision of the article and final approval of the version to be published.

Corresponding authors

Correspondence to Abbas Tafakhori or Nima Rezaei.

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Agah, E., Mojtabavi, H., Behkar, A. et al. CSF and blood levels of Neurofilaments, T-Tau, P-Tau, and Abeta-42 in amyotrophic lateral sclerosis: a systematic review and meta-analysis. J Transl Med 22, 953 (2024). https://doi.org/10.1186/s12967-024-05767-7

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Journal of Translational Medicine

ISSN: 1479-5876

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