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Idiopathic RBD (iRBD) indicates an earlyα-synucleinopathy, with approximately 90% of individualsdeveloping clinically manifest Parkinson’s disease (PD),dementia with Lewy Bodies (DLB), or multiple systematrophy (MSA) within 15 years of iRBD diagnosis [,]. A broad definition of a biomarker is an indicator of nor-mal biological processes, pathogenic processes, or responsesto an exposure or intervention [].They could be helpful notonly for diagnosis but also for therapeutic management andmonitoring of iRBD progression []. Serum biomarkers areminimally invasive, clinically accessible tools with grow-ing potential to predict phenoconversion [,]. Research Received: 3 September 2025 / Revised: 19 April 2026 / Accepted: 24 April 2026 © The Author(s) 2026 Danielle Mesquita Torres Manoel Alves Sobreira-Neto 1 Postgraduate Program in Translational Medicine,Universidade Federal do Ceará, Fortaleza, Brazil 2 Department of Physiology and Pharmacology,Neuropsychopharmacology Laboratory, Drug Research andDevelopment Center, Faculty of Medicine, UniversidadeFederal do Ceará, Fortaleza, CE, Brazil 3 Faculty of Medicine, Division of Neurology, UniversidadeFederal do Ceará, Fortaleza, CE, Brazil 4 Universidade de Brasília, Brasília, DF, Brazil 5 Clinical Medicine Departament, Faculty of Medicine ofFederal, University of Ceará, Rua Prof. Costa Mendes, 1408– 4º. Andar, Fortaleza CEP: 60.430-140, Brazil 6 Department of Translational Medicine, Federal University ofCeará, Rua Coronel Nunes de Melo, n 1000,Fortaleza CEP 60.430-275, Brazil # Abstract # Background Idiopathic REM sleep behavior disorder (iRBD) indicates an early α-synucleinopathy, offering a window forearly detection and intervention. # Objective Explore a serum-based biomarker panel, comprising NfL, GFAP, t-tau, and UCH-L1, in patients with iRBD, andcompare to individuals with synucleinopathy and healthy controls. # Method This is a cross-sectional, observational study. Serum biomarkers were measured using the single molecule array technique.Clinical evaluation included standardized assessments of sleep, cognitive function, motor symptoms, and psychiatric features. # Results GFAP levels were significantly higher in the iRBD group than in the control and synucleinopathy groups. SerumNfL levels yielded conflicting results. T-tau and UCHL-1 protein levels were lower in the iRBD and synucleinopathy groupscompared to the control group. # Conclusion Our findings suggest that serum levels of NfL, GFAP, t-tau, and UCH-L1 may serve as potential biomarkers iniRBD, primarily GFAP levels. Keywords REM sleep behavior disorder · Synucleinopathies · Neurodegeneration · Biomarker Exploratory serum biomarker profiling in idiopathic REM sleepbehavior disorder: evidence of early neurodegenerativesignatures: a pilot study Danielle Mesquita Torres1,6 · Fábio Henrique Queiroz Pereira1 · Marylane da Silva Viana2 ·Mariana Michilles Santos Ramos3 · Elisa Gabriela Barros Cunha3 · Leonardo José Rodrigues de Araújo Melo3 ·Emmanuelle Silva Tavares Sobreira3 · Francisca Charliane Almino Lopes1 · Annyta Fernandes Frota2 ·Michelle Verde Ramos Soares2 · Ricardo Titze- de- Almeida4 · Pedro Braga-Neto3 · Danielle S. Macedo2 ·Manoel Alves Sobreira-Neto3,5 Sleep and Breathing (2026) 30:158 [ ![http://crossmark.crossref.org/dialog/?doi=10.1007/s11325-026-03698-9&domain=pdf&date_stamp=2026-5-9]() ](http://crossmark.crossref.org/dialog/?doi=10.1007/s11325-026-03698-9&domain=pdf&date_stamp=2026-5-9) ![Springer Logo]() ### Page 2 is currently underway to assess the biomarker potentialof miRNAs obtained from peripheral blood samples [,]. Research on plasma biomarkers has also analyzed thepotential of neurofilament (Nfl), glial fibrillary acid protein(GFAP), ubiquitin C-terminal hydrolase L1 (UCH-L1), andTotal tau (t-tau), neurodegeneration markers, as biomarkersin PD, using the single-molecule array (SIMOA) platform[]. However, its applicability in assessing phenoconver-sion in patients with iRBD remains undetermined. The present study aimed to explore a serum-based bio-marker panel, comprising Nfl, GFAP, t-tau, and UCH-L1, inpatients with iRBD and to compare these profiles with thoseobserved in individuals with established synucleinopathyand healthy controls. This multi-analyte approach may offeradditional pathophysiological insight and discriminatorypower, potentially enhancing early risk stratification in theprodromal phase of synucleinopathies. Methods Participants were recruited from the community and fromthe Sleep and Parkinson’s disease outpatient clinics at theUniversity Hospital of the Federal University of Ceará (HU-UFC). PD diagnosis followed the Movement Disorder Soci-ety clinical diagnostic criteria []. The diagnosis of RBDwas established in accordance with the International Clas-sification of Sleep Disorders, Third Edition (ICSD-3) andthe American Academy of Sleep Medicine (AASM) poly-somnographic criteria [,]. Patients who were usingantidepressants had their medications discontinued to assesscausality, establishing the diagnosis of antidepressant-related RBD. A healthy control group was recruited fromthe community, matched for age and sex, and included unre-lated individuals with no family history linking them to thepatients. RSWA (REM sleep without atonia) quantificationduring v-PSG (video polysomnography) was performedaccording to the cut-offs established by the SINBAR groupstudy []. Clinical evaluation was performed using the followingscales: Pittsburgh Sleep Quality Index (PSQI), EpworthSleep Scale (ESS), Stop Bang score, Beck’s DepressionInventory (BDI), Beck Anxiety Inventory (BAI), Mini-Mental Status Examination (MMSE), Montreal CognitiveAssessment (MoCA), and Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS-III). After, the participants underwent blood collection andv-PSG. Serum biomarkers were measured by Simoa tech-nique on the Simoa SR-X Analyzer (Quanterix, Lexington,MA) as established previously []. The lower limits ofquantification (LLOQ) for each biomarker were as follows:0.276 pg/mL for GFAP, 0.136 pg/mL for NfL, 4.03 pg/mLfor UCH-L1, and 0.0298 pg/mL for t-tau. The Nfl valueswere adjusted for age and body mass index (BMI) using theswiss national reference database and web application [].V-PSG was performed using a digital polygraph in accor-dance with AASM guidelines. This study was approved by the Ethics Committee ofHU-UFC, protocol number (CAAE 74817423.8.10015045).The study was approved according to the principles of theDeclaration of Helsinki. The normality of the data distribution was assessed usingthe Kolmogorov–Smirnov test. Because most variables didnot follow a normal distribution, nonparametric tests wereinitially used. Correlations among variables were evalu-ated using Spearman’s correlation. Data were processedand analyzed using Microsoft Excel and R software version4.1. Given the nature of the data and the presence of groupswith small and unequal sample sizes, particularly the iRBDgroup (n = 4), the robustness of the inferences was ensuredby applying the simple Bootstrap method with 1000 resam-ples, using bias-corrected and accelerated confidence inter-vals (BCa) at the 95% level. One-way ANOVA and post hocanalysis were also conducted. The datasets analyzed dur-ing the current study are available from the correspondingauthor on reasonable request. Results A total of 31 participants were included in our study, dividedinto four groups (control, iRBD, antidepressant-relatedRBD, and PD). 11 patients were enrolled in the controlgroup. 4 patients were diagnosed with iRBD, 14 with PD,and only 2 participants with antidepressant-related RBD(Table). These last ones, based on a small sample, wereremoved from the statistical analyses. The groups did notdiffer in terms of sex or age. Regarding the cognitive, mood disorder, and sleep qual-ity scales, we found a difference only between the iRBD andPD groups on the MMSE (p = 0.04). The PD group obtainedthe lowest score. The median UPDRS-III score in the PDgroup was significantly higher (p < 0.001) (Table). The analysis of biomarkers (GFAP, Nfl, t-tau, and UCH-L1) revealed statistically significant differences among thestudy groups in the initial analysis using Spearman’s cor-relation (Table; Fig.). For GFAP, one-way ANOVA indicated a significantgroup effect (p = 0.006). Multiple comparisons using theGames-Howell test revealed that GFAP levels were signifi-cantly higher in the iRBD group compared to the controlgroup (mean difference = 270.68; p = 0.037). The PD groupdid not show a statistically significant difference from thecontrol group for this marker (p = 0.467) (Table). ### Page 3 Regarding the Nfl, a significant overall variation wasobserved (p = 0.037), including adjusted values (Table).The post hoc test showed that the PD group had signifi-cantly higher levels than the control group (28.24 vs. 15.18;p = 0.030), whereas the iRBD group, although higher thanthe control group (25.03), did not reach statistical signifi-cance in this comparison (p = 0.107) (Table). The biomarkers t-tau and UCH-L1 showed the strongestassociations (p < 0.001 for both). The Control group showedsignificantly higher levels of t-tau (8.26 ± 0.60) and UCH-L1 (52.16 ± 5.46) than both pathological groups (p < 0.001in all comparisons with the control). No significant differ-ences were observed between the iRBD and PD groups forthese two biomarkers (p > 0.40) (Tables and). In our sample, we had 2 patients with antidepressant-related RBD. Their GFAP levels were 105.6 and 121.06pg/ml; Nfl levels were 5.42 and 7.49 pg/ml (z-scores 0.94and 0.95) ; t-tau levels were 4.25 and 0.26 pg/ml; UCH-L1 levels were 0.31 and 1.69 pg/ml. These levels are morelike those observed in the control group; however, given thelimited sample size, no further conclusions can be drawn. Discussion Our study showed that serum levels of GFAP, NfL, t-tau,and UCH-L1 are altered in patients with iRBD compared toan age- and sex-matched control group, with values resem-bling those observed in individuals with established PD. The cohort of Zhang et al. evaluated 26 patients withiRBD and found that the baseline plasma Nfl cutoff of 22.93pg/ml performed best in distinguishing iRBD convertersfrom non-converters []. In another cross-sectional study,Teng et al. identified higher levels of GFAP and Nfl in thePD group than in the control group. The cut-offs identi-fied in this previous study were 12.42 for Nfl and 110 forGFAP to identify patients with RBD []. In our study,GFAP levels were higher in the iRBD group than in bothPD and controls, even after post hoc analysis. This is likelyto reflect early astrocytic activation, which may decline inmore advanced PD due to predominant neuronal loss. Thesefindings contrast with Youssef et al., possibly due to differ-ences in disease stage among PD participants []. In thepost-hoc analysis, Nfl levels were statistically higher in thePD group. It remains controversial whether there is a directrelationship between UCH-L1, an essential component ofthe ubiquitin–proteasome system (UPS), and PD [,]. The study by Nabizadeh et al. evaluated cerebrospinalfluid (CSF) levels of alpha-synuclein (α-syn), beta-amyloid(Aβ1–42), t- tau and p-tau in patients with PD and com-pared them with healthy controls. These levels were higherin the control group. As with α-syn, reduced Aβ1–42 levelsin patients with PD can be explained by greater extracel-lular accumulation []. Consistent with these findings, thet-tau level in peripheral blood was also higher in our controlgroup than in the others. Another aspect to be considered in the cross-sectionalevaluation of biomarkers is the variation that occursthroughout disease progression. The study by Baek et al.analyzed biomarker levels in patients with PD over 3 years.At baseline, patients with PD showed lower CSF α-syn, Aβ,t-tau, and p-tau levels than controls. In all PD patients, CSFα-syn and Aβ decreased in a negative-exponential patternbefore the onset of motor symptoms, whereas CSF t-tau,p-tau, and serum NfL, increased []. This study has some limitations, including its cross-sectional design, the small sample size, particularly in theiRBD group, and the lack of CSF biomarker data. Periph-erally measured t-tau signals can be inflated by non-brain | Table 1 Comparison between socio-demographic data, standardizedscales scores and serum biomarkers levels of controls, iRBD and PDpatients (n = 29) | | - | | Control(n = 11) | iRBD(n = 4) | RBD + PD(n = 14) | p | | Age (years),mean ± SD | 64 ± 15 | 66 ± 3 | 67 ± 7 | 0.966 | | Male sex, n (%) | 5 (45%) | 3 (75%) | 6 (43%) | | PSQI,mean ± SD | N/A | 16 ± 7.8 | 14.8 ± 7.3 | 0.955 | | ESS, mean ± SD | N/A | 10.5 ± 1.7 | 12.5 ± 5 | 0.331 | | SBQ, mean ± SD | N/A | 3.25 ± 0.96 | 3.62 ± 0.77 | 0.494 | | MMSE,mean ± SD | N/A | 29 ± 0.8 | 24.1 ± 5 | 0.040* | | MoCA,mean ± SD | N/A | 24 ± 2 | 19 ± 8 | 0.460 | | BDI, mean ± SD | N/A | 8 ± 4 | 17 ± 15 | 0.364 | | BAI, mean ± SD | N/A | 19 ± 15 | 18 ± 15 | 0.692 | | GFAP,mean ± SD | 203 ± 111 | 474 ± 132 | 265 ± 147 | 0.019* | | NfL, mean ± SD | 15 ± 8 | 25 ± 7 | 28 ± 15 | 0.026* | | NfL z-scoremean ± SD | 0.35 ± 1.3 | 1.86 ± 0.47 | 1.76 ± 1.07 | 0.019* | | NfL percentilemean ± SD | 56 ± 35 | 96 ± 3 | 87 ± 22 | 0.020* | | T-tau,mean ± SD | 8.26 ± 1.97 | 0.79 ± 0.37 | 1.08 ± 0.47 | < 0.001* | | UCH-L1,mean ± SD | 52 ± 18 | 8 ± 7 | 9 ± 4 | < 0.001* | | UPDRS-III,mean ± SD | N/A | 0.25 ± 0.5 | 40.31 ± 21.6 | < 0.001* | | iRBD Idiopathic REM Sleep Behavior Disorder, PD Parkinson’s Dis-ease, SD Standard Deviation, PSQI Pittsburgh Sleep Quality Index,ESS Epworth Sleepiness Scale, SBQ STOP-Bang Questionnaire,MMSE Mini Mental State Examination, MoCA Montreal CognitiveAssessment, BDI Beck Depression Inventory, BAI Beck AnxietyInventory, GFAP Glial Fibrillary Acidic Protein, NfL Neurofilament,T-tau Tau Protein, UCH-L1 Ubiquitin C-terminal Hydrolase L1, N/ANot Available. (*P < 0.05). Units: GFAP ng/ml, Nfl pg/ml, Nfl z-scorepg/ml, Nfl precentile pg/ml, T-tau pg/ml, UCH-L1 pg/ml | | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | ### Page 4 signals. Circulating tau proteins may have extracerebralorigins, reducing the marker’s reliability. Nonetheless,the identification of distinct serum biomarker alterationsin both iRBD and Parkinson’s disease groups, comparedwith healthy controls, and the exploratory measurement of | Table 2 Descriptive profile and variability of biomarkers by group | | - | | Biomarker | Control(n = 11) | iRBD(n = 4) | PD(n = 14) | Valor-p(ANOVA) | | GFAP (ng/mL) | 203,19 ±33,42 | 473,87 ±65,97 | 264,89 ±39,27 | 0,006 | | NFL (pg/mL) | 15,18 ±2,51 | 25,03 ±3,26 | 28,24 ±3,99 | 0,037 | | NFL percentile | 56 ± 35 | 96 ± 3 | 87 ± 22 | 0,0162 | | T-tau (pg/mL) | 8,26 ± 0,60 | 0,79 ±0,19 | 1,08 ±0,13 | < 0,001 | | UCH-L1 (pg/mL) | 52,16 ±5,46 | 8,32 ±3,31 | 9,00 ±1,14 | < 0,001 | | Values are presented as Mean ± Standard Error of the Mean (SEM).p-value obtained via one-way ANOVA with validation by robust tests(Welch/Brown-Forsythe) | | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | Table 3 Post-hoc multiple comparisons (difference of means) | | - | | Pair comparison | GFAP (p) | NFL (p) | T-tau (p) | UCH-L1 (p) | | Control vs. iRBD | 0,037* | 0,107* | < 0,001 | < 0,001 | | Control vs. PD | 0,467* | 0,030* | < 0,001 | < 0,001 | | iRBD vs. PD | 0,085* | 0,810* | 0,432* | 0,980* | | *p-values were calculated using the Games-Howell test, which issuitable for groups with heterogeneous variances and unequal samplesizes | | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | ### Page 5 specific markers in this context, provides novel pathophysi-ological insights. Increasing the sample size in future stud-ies will be essential to validate these preliminary findings,improve statistical power, and determine the clinical utilityof this biomarker panel for early identification and subtyp-ing of RBD. Conclusion Our study suggested that serum levels of NfL, GFAP, T-tau,and UCH-L1 may serve as potential biomarkers in iRBD,as their profiles closely resemble those observed in patientswith PD and differ significantly from those of healthy con-trols. The GFAP levels performed better in differentiatingthe iRBD group. These findings may be useful for prognosti-cating patients at higher risk of developing synucleinopathy. Acknowledgements This work was supported by the Brazilian NationalCouncil for Scientific and Technological Development (CNPq). Authors' contributions Danielle Mesquita Torres; Ethics committeeprocesses, organization of research processes, statistical analysis, dataand article writing. Fábio Henrique Queiroz Pereira; Data collection,scale application, article writing. Marylane da Silva Viana; Collection,storage and analysis of biological samples. Mariana Michilles SantosRamos; Data collection, application of clinical scales, polysomnogra-phy analysis. Elisa Gabriela Barros Cunha; Data collection, applicationof clinical scales, polysomnography analysis. Leonardo José Rodriguesde Araújo Melo; Documents and submission processes to the researchethics committee. Emmanuelle Silva Tavares Sobreira; Guidance oncognitive scales and neuropsychological assessment. Francisca Char-liane Almino Lopes; Application of cognitive scales and neuropsycho-logical tests. Annyta Fernandes Frota; Analysis of biological samples atSIMOA. Michelle Verde Ramos Soares; Analysis of biological samplesat SIMOA. Ricardo Titze-de-Almeida; Guidance on analysis, storageand data from biological samples. Pedro Braga-Neto; Guidance on cog-nitive scales and interpretation of biological sample analysis. DanielleS. Macedo; Guidance on analysis, tabulation and recording of biologi-cal samples. Manoel Alves Sobreira-Neto; General research supervi-sion and design of the original project. Guidance on all stages. Funding The Article Processing Charge (APC) for the publica-tion of this research was funded by the Coordenação de Aperfeiçoa-mento de Pessoal de Nível Superior - Brasil (CAPES) (ROR identi-fier: 00x0ma614). This work was supported by the Brazilian NationalCouncil for Scientific and Technological Development (CNPq). Data availability The datasets generated during and/or analysed dur-ing the current study are available from the corresponding author onreasonable request. Declarations Ethical approval All procedures performed in studies involving hu-man participants were in accordance with the ethical standards of theinstitutional and/or national research committee (Ethics Committee ofHU-UFC) and with the 1964 Helsinki declaration and its later amend-ments or comparable ethical standards. This study was approved bythe Ethics Committee of HU-UFC, under the protocol number (CAAE74817423.8.10015045). Informed consent was obtained from all indi-vidualparticipants included in the study. Conflict of interest All authors certify that they have no affiliationswith or involvement in any organization or entity with any financial in-terest (such as honoraria; educational grants; participation in speakers’bureaus; membership, employment, consultancies, stock ownership,or other equity interest; and expert testimony or patent-licensing ar-rangements), or non-financial interest (such as personal or professionalrelationships, affiliations, knowledge or beliefs) in the subject matteror materials discussed in this manuscript. Statement regarding the use of AI AI resources were used solely forlanguage improvement. Financial disclosures of all authors (for the preceding 12 months) Thiswork was supported by the Brazilian National Council for Scientif-ic and Technological Development (CNPq). All authors deny othersources of funding and conflict of interest. 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