Blood and cerebrospinal fluid differences between Parkinson's disease and related diseases

preprint OA: closed
Full text JSON View at publisher

Abstract

Abstract Accurately diagnosing Parkinson’s disease (PD) in its early stages is difficult due to its symptoms overlapping with those of various disorders, including atypical Parkinsonian syndromes, dementia with Lewy bodies (DLB), and even essential tremor. This complicates the diagnostic process for PD, which traditionally heavily relies on symptomatic assessment and treatment response. Recent advances have identified several biomarkers in the blood and cerebrospinal fluid (CSF), including α-synuclein, lysosomal enzymes, fatty acid-binding proteins, and neurofilament light chain, that may potentially be used to diagnosed PD. However, not all can effectively distinguish PD from related disorders or identify its subtypes. This review advocates for a paradigm shift towards biomarker-based diagnosis to effectively distinguish between PD and similar conditions and to categorize PD into its subtypes. These biomarkers may reflect the differences that exist among different diseases and provide an effective way to accurately understand their mechanisms. This review focused on blood and CSF biomarkers of PD that may have differential diagnostic value and the related molecular measurement methods with high diagnostic performance due to emerging technologies.
Full text 126,911 characters · extracted from preprint-html · click to expand
Blood and cerebrospinal fluid differences between Parkinson's disease and related diseases | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Blood and cerebrospinal fluid differences between Parkinson's disease and related diseases Jie Ma, Zhijian Tang, Yaqi Wu, Jun Zhang, Zitao Wu, Lulu Huang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4973615/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Dec, 2024 Read the published version in Cellular and Molecular Neurobiology → Version 1 posted 13 You are reading this latest preprint version Abstract Accurately diagnosing Parkinson’s disease (PD) in its early stages is difficult due to its symptoms overlapping with those of various disorders, including atypical Parkinsonian syndromes, dementia with Lewy bodies (DLB), and even essential tremor. This complicates the diagnostic process for PD, which traditionally heavily relies on symptomatic assessment and treatment response. Recent advances have identified several biomarkers in the blood and cerebrospinal fluid (CSF), including α-synuclein, lysosomal enzymes, fatty acid-binding proteins, and neurofilament light chain, that may potentially be used to diagnosed PD. However, not all can effectively distinguish PD from related disorders or identify its subtypes. This review advocates for a paradigm shift towards biomarker-based diagnosis to effectively distinguish between PD and similar conditions and to categorize PD into its subtypes. These biomarkers may reflect the differences that exist among different diseases and provide an effective way to accurately understand their mechanisms. This review focused on blood and CSF biomarkers of PD that may have differential diagnostic value and the related molecular measurement methods with high diagnostic performance due to emerging technologies. Parkinson’s disease Atypical Parkinsonian disorders Dementia and movement disorders Differential diagnosis Biomarkers Figures Figure 1 Figure 2 Introduction Atypical Parkinson’s syndrome (APS) includes progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), multiple system atrophy (MSA), and vascular parkinsonism (VP). During the early stages of APS, the individual conditions are difficult to distinguish from Parkinson's disease (PD) and are often misdiagnosed as PD (Jabbari et al. 2020 ; Holm et al. 2023 ). PD dementia (PDD) is a manifestation of PD during its middle and late stages. Distinguishing PDD from dementia with Lewy bodies (DLB) is challenging and may result in indiscriminate clinical pathology studies or clinical trials (Hirschberg et al. 2023 ). DLB and PDD are collectively referred to as Lewy body disease or synucleinopathy (Harris 2023 ). Additionally, the motor symptoms of PD should also be differentiated from essential tremor (ET) (Yu et al. 2023 ; Yoo et al. 2023 ). Through an extensive literature search, we found that several blood and cerebrospinal fluid (CSF) biomarkers significantly differ between PD and other related diseases (Fig. 1). These molecules may be defined as differential diagnostic biomarkers of PD (Quadalti et al. 2021 ). While these biomarkers have significant statistical differences in the study of groups, the traits of discrimination may need to be demonstrated in many ways. The differential diagnostic biomarkers of PD may be used as reference for clinical pathological studies and clinical trials, because differentiating these diseases is the first step for such studies (Dutta et al., 2021 ). Figure 1 Flow diagram of the different types of PD’s differential diagnostic biomarkers. DDC: DOPA decarboxylase; GFAP: glial fibrillary acidic protein; NfL: neurofilament light chain protein; 8-OHdG: 8-hydroxy-2'–deoxyguanosine; Hcy: homocysteine; TC: total cholesterol; TG: triglycerides; HDL: high-density lipoprotein cholesterol; Apo A1: apolipoprotein A1. Search Strategy and Selection Criteria Through literature review, we first identified diseases that require differentiation from PD as well as the different PD subtypes (see search query). Next, we screened for diagnostic biomarkers using the search statements (“Parkinson’s disease” OR “PD”) AND (“biomarker”) on PubMed and Web of Science. We obtained PD-related biomarkers (see search query) and selected review articles to obtain a comprehensive biomarkers selection. Based on the biomarkers identified, we used the search formulas (“Parkinson's Disease” OR PD) AND ((“Atypical Parkinson's syndrome” OR APS OR “Atypical parkinsonism disorder” OR APD) OR (“progressive supranuclear palsy” OR PSP) OR (“corticobasal syndrome” OR CBS) OR (“multiple system atrophy” OR MSA) OR (“vascular parkinsonism” OR VP) OR (“dementia with Lewy bodies” OR DLB) OR (“essential tremor” OR ET)) AND ((“α-Synuclein” OR “α-Syn”) OR (“DOPA Decarboxylase” OR “DDC”) OR (“Amyloid beta” OR “Aβ”) OR “tau protein” OR “Exosomes” OR (“Neurofilament Light Protein” OR “NfL”) OR “MicroRNAs” OR “FABP3”) to retrieve targeted literature while selecting studies that were appropriate to meet our research objectives. A similar search strategy was used to screen biomarkers for distinguishing PD subtypes. After screening abstracts, 91 articles were identified for further in-depth reading. Midkine (MK) and Kallikrein 10 were two molecules not obtained in the initial search, and no study further elaborated their roles in different PD subtypes. Ultimately, 72 articles were included in this review. PD and APS 2.1. α-Synuclein (α-syn) and its variants α-syn is detectable in both CSF and plasma and is the most widely researched biomarker of PD (Tsao et al., 2022 ; Estaun-Panzano et al. 2023 ; Tofaris 2022 ). Phosphorylation of the Ser129 site results in phosphorylated α-syn (PS-129), while pro-aggregating forms of α-syn, such as oligomeric α-syn (o-α-syn), are also found in CSF and blood (Ma et al. 2023; Constantinides et al. 2021 ; Zubelzu et al. 2022 ; Chen et al. 2022 ; Chen et al. 2022 ). Meanwhile, the pathogenic β-sheet seed is the pathological conformation of α-syn and can be detected in serum (Okuzumi et al. 2023 ). Several studies and meta-analyses have confirmed that when compared to the control group, the total α-syn (t-α-syn) levels in the CSF are consistently lower in PD, MSA, PSP, CBS, and VP groups, with no significant differences among them (Zubelzu et al. 2022 ; Constantinides et al. 2017 ; Førland et al. 2020 ; Koníčková et al. 2023 ; Aerts et al. 2012 ). Therefore, t-α-syn levels cannot differentiate between PD and APS. Notably, levels of o-α-syn in PD and other Parkinsonian syndromes reportedly do not differ significantly but are elevated compared to that of the control group (Eusebi et al. 2017 ). Utilizing a Bead-based Luminex assay (with a sensitivity of 9 pg/mL), researchers measured the concentration of pS129 in the CSF of patients with PD, MSA, and PSP, revealing differences among them. To differentiate between the different diseases, receiver operating characteristic analysis following the discovery phase indicated that pS-129/t-α-syn was superior to pS-129 alone, with a specificity of ≥ 80%. The sensitivity among the three different Parkinsonian disease groups were as follows: PD vs MSA, 40%; PD vs PSP, 72%; and MSA vs. PSP, 63% (Wang et al. 2012 ). Aggregates of α-syn, including propagative α-syn seeds, showed high diagnostic performance in differentiating between PD and MSA (Siderowf et al. 2023 ; Painous et al. 2024 ; Parnetti et al. 2019 ; Goolla et al. 2023 ; Shahnawaz et al. 2020 ) Amplified seeds maintain disease-specific properties, allowing for the differentiation of samples from individuals with PD and MSA (Painous et al. 2024 ) Okuzumi et al. ( 2023 ) suggested that the rate of negative results of IP/RT-QuIC in patients with MSA was significantly higher than that in patients with PD. Additionally, their study also examined the distinctive morphological features of seeds in various diseases. The fibril morphology of products derived from IP/RT-QuIC of serum α-syn seeds in patients with synucleinopathies could differentiate PD, DLB, and MSA, allowing for further research in this area. A study found that the intensity of the signal in MSA was greater than that in PD when aggregation was performed in a specific buffered solution, indicating that α-syn seed aggregation from various diseases require different conditions for optimal detection (Martinez-Valbuena et al. 2022 ). These results suggest that our follow-up study can focus on the structural diversity and disease specificity of α-syn seeds. 2.2 DOPA decarboxylase (DDC) A primary pathological feature of PD is the degeneration of dopaminergic neurons in the substantia nigra (Stoker and Greenland 2018 ). DDC is a diagnostic marker of dopaminergic dysfunction and can be detected in CS (Painous et al. 2024 ). Several studies have attempted to reveal the differences in DDC between PD and APS (Paslawski et al. 2023 ; Pereira et al. 2023 ). CSF levels of DDC may potentially be useful in differentiating among degenerative Parkinsonisms (PD vs. APS) (Paslawski et al. 2023 ). 2.2 MK MK is predominantly expressed during midgestation in embryogenesis, but its presence in normal adult brains is minimal. However, MK may recently play a role in various adult brain pathologies (Neumaier et al. 2023 ). MK has demonstrated significant diagnostic potential as its levels were notably higher in patients with PD compared to those with APS (Paslawski et al. 2023 ). 2.3 Kallikrein 10 Kallikreins, which is a subgroup of serine proteases, play various physiological roles. Recent research has emphasized their involvement in carcinogenesis, highlighting several kallikreins as promising candidates for novel biomarkers in cancer and other diseases. This supports the potential utility of kallikreins in clinical diagnostics and therapeutic targeting (Wikipedia, nd). Kallikrein 10 has exhibited specific changes in APS compared to PD and controls; unfortunately, these changes were not elaborated (Paslawski et al. 2023 ). 2.4 Classic Alzheimer’s disease (AD) biomarkers Amyloid-beta-Aβ42, tau protein-τT, and phosphorylated tau protein-τP-181 are classical biomarkers of AD (Sung et al. 2023 ). Notably, their significance in Parkinson’s syndrome has been re-recognized. When compared to patients with PD, τT/Aβ42 ratio was increased in patients with MSA (Constantinides et al. 2021 ; Constantinides et al. 2017 ). An elevated τT/Aβ42 ratio effectively differentiated MSA from PD, with an optimal cut-off value of 0.344 that yielded a sensitivity of 0.71 and specificity of 0.93 (Constantinides et al. 2017 ). 2.5 Exosomes Exosomes from peripheral blood and CSF nerve cells have been used to distinguish PD and MSA (Taha and Bogoniewski 2024 ; Taha 2023 ; Yan et al. 2024 ). Dutta et al.’s ( 2021 ) study confirmed that α-syn concentrations in exosomes were markedly lower in the control group and significantly higher in the MSA group compared to the PD group. They created a ratio using α-syn concentrations of putative oligodendroglial exosomes and putative neuronal exosomes with good sensitivity in distinguishing PD and MSA. By incorporating this ratio along with the α-syn and total exosome concentrations, a multinomial logistic model successfully distinguished PD from MSA, with an area under the curve (AUC) of 0.902, sensitivity of 89.8%, and specificity of 86.0% after application to an independent validation cohort. Meloni et al. ( 2023 ) investigated neural-derived extracellular vesicles (NDEVs) isolated from the blood. Analysis of NDEVs revealed a significant increase in o-α-syn levels in PD compared to APS (CBD and PSP). Additionally, levels of Tau aggregates in NDEVs were significantly elevated in APS compared to PD (p < 0.0001). Receiver operating characteristic analysis showed that the concentration of NDEVs of both oligomeric o-α-syn and Tau aggregates exhibited an “excellent” power of classification that effectively distinguished PD from APS. For o-α-syn, the AUC was 0.817 (95% confidence interval (CI): 0.732–0.885; p < 0.0001), sensitivity of 78.6%, and specificity of 77.5%. For Tau aggregates, the AUC was 0.856 (95% CI: 0.776–0.915; p < 0.0001), sensitivity of 90.0%, and specificity of 75.7%. Taha et al. ( 2023 ) was the first to measure pS129-α-syn levels in neuronal extracellular vesicles (nEVs) and oligodendroglial extracellular vesicles (oEVs). They reported that nEV pS129-α-syn concentrations were highest in healthy controls (HC) followed by PD and MSA, but the differences were not statistically significant. Conversely, oEV concentrations of pS129-α-syn were also highest in HC followed by PD and MSA and was significantly higher in both disease groups. Additionally, their study revealed that the oEV/nEV pS129-α-syn ratio increased in the order of HC < PD < MSA. Furthermore, they also measured total tau, pT181-tau (tau phosphorylated at Thr181) in nEVs and oEVs, and/or serum neurofilament light protein (NfL) levels. Due to the detection sensitivity, pT181-tau was detected in very few samples. Other results were similar to experiments involving plasma or CSF. 2.6 NfL NfL in CSF (cNfL) and plasma (pNfL) is a marker for neuronal damage that may potentially be used to distinguish between clinically similar conditions, such as frontotemporal dementia from AD and PD from APS (Quadalti et al. 2021 ). Among Parkinsonian syndromes, the mean cNfL levels were higher in MSA, PSP, and CBS when compared with PD (Wikipedia, nd; Bridel et al. 2019 ). Suffering from both PD and MSA 3.1 MicroRNAs MicroRNAs, which are small non-coding RNAs with 20–22 nucleotides, play a critical role in several mechanisms underlying the pathogenesis of various neurodegenerative diseases, including PD. (Guévremont et al. 2023 ) More importantly, they can be detected in the serum. (van Wamelen et al. 2020 ) miR-30c and miR-148b are specific to individuals with PD, whereas miR-24, miR-223, and miR-324-3p are present in patients with both PD and MSA when compared with healthy individuals (Villar-Menéndez et al. 2014 ). PDD and Other Dementia and Movement Disorders 4.1 Fatty acid-binding protein 3, heart type (FABP3) FABP3 is a small cytosolic protein that plays a role in lipid transport (Chiasserini et al. 2017 ). In the brain, FABP3 plays a regulatory role in the lipid composition of the membrane, suggesting a potential involvement in synapse formation and in the activity of cholinergic and glutamatergic neurons (Parnetti et al. 2019 ). Elevated FABP3 levels have been detected in the serum of individuals diagnosed with DLB and PDD (Kawahata et al. 2023 ). Additionally, FABP3 levels were higher in patients with DLB than in those with PDD. This suggests the potential of FABP3 as a distinctive biomarker for DLB (Kawahata and Fukunaga 2023 ). Similar to DLB, FABP3 levels were higher in patients with AD than in those with PD and other neurological disorders (p < 0.001). Notably, a combination of p-tau, FABP3, and α-syn successfully differentiated patients with AD from those with PDD, yielding an AUC of 0.96 (Chiasserini et al. 2017 ). 4.2 Tau Despite being a hallmark of AD, Tau proteins are also found in the brains of patients with PD and DLB (Shim et al. 2022 ). A study aimed at distinguishing AD, DLB, and PD revealed that t-tau levels were higher in the DLB group than in the control and PD groups, but the differences were not statistically significant. Meanwhile, the t-tau/t-α-syn ratio had a better performance than standalone markers. For AD vs. DLB, the AUC increased from 0.66 for t-tau alone (70% sensitivity and 68% specificity) to 0.74 for the t-tau/t-α-syn ratio (55% sensitivity and 95% specificity) (Førland et al. 2020 ). 4.3 C-reactive protein (CRP) CRP concentrations in the CSF are higher in patients with PD and PDD than in patients with PD without dementia and HCs (Lindqvist et al. 2013 ). However, distinguishing between patients with PD without dementia and HCs based on CRP levels was not feasible. 4.4 Plasma homocysteine (Hcy) In one study, Hcy levels were measured in patients with (PDD) and without dementia (PDwoD) as well as in HCs. Results showed that individuals with PDD demonstrated higher Hcy levels than PDwoD and HCs (Song et al. 2013 ). 4.5 Glial fibrillary acidic protein (GFAP) A study revealed that plasma GFAP levels in patients with PDD were higher than those in HCs, patients with PD with mild cognitive impairment (PD-MCI), and patients with PD with normal cognition (Bartl et al. 2023 ). PD and ET 5.1 α-syn in erythrocytes While pathological α-syn aggregations primarily localize in the central nervous system, peripheral α-syn concentrations, particularly in erythrocytes, are higher than in those in the CSF (Barbour et al. 2008 ) α-syn in erythrocytes are reportedly excellent biomarkers for diagnosing PD (Yu et al. 2023 , Yu et al. 2022 ). Total α-syn levels in erythrocytes are higher in patients with ET than in those with PD. Moreover, the proportion of aggregated α-syn levels to t-α-syn levels in erythrocytes is markedly lower in patients with ET than in those with PD and HCs. Receiver operating characteristic curve analysis showed that the ratios of aggregated α-syn to monomeric α-syn concentrations performed well in distinguishing patients with ET from those with PD and HCs, with an AUC of 0.892, sensitivity of 86.67%, and specificity of 97.96% for patients with ET vs. HCs. For ET vs. PD, the AUC was 0.817, with a sensitivity of 80.00% and specificity of 81.25% (Yu et al. 2023 ). 5.2 NfL Some studies have compared serum NfL levels in PD and ET. (Hansson et al. 2017 ) Huang et al. ( 2022 ) reported that serum NfL concentrations in patients with PD (16.6 ± 3.5 pg/mL) were significantly higher than that in patients with ET (12.2 ± 2.4 pg/mL) and HCs (11.8 ± 2.4 pg/mL) (both p < 0.01, effect sizes = 1.47 and 1.60, respectively). When the cut-off was set at 13.65 pg/mL, the sensitivity and specificity of distinguishing between PD and ET were 76.7% and 84.1% respectively, with an AUC of 0.854. Figure 2 Concentrations of NfL in PD were considerably different from those in APS PDD and ET, with NfL concentrations higher in APS and PDD than in PD and the opposite in APS (vascular parkinsonism is not included). This may suggest a different pathogenesis of its disease at the molecular level. NfL: Neurofilament light protein, PD: Parkinson’s diaseae, APS: Atypical parkinson’s syndrome, PSP: progressive supranuclear palsy, CBS: corticobasal syndrome, MSA: multiple system atrophy, PDD: Parkinson's disease dementia, ET: Essential tremor. PD and its Subtypes 6.1 Early-onset PD (EOPD) and late-onset PD (LOPD) An analysis of plasma microRNA levels in patients with EOPD, patients with LOPD, and HCs revealed a statistically significant difference between patients with PD and HCs. Upregulation of miR-29b-3p and downregulation of miR-297 and miR-4462 in EOPD may be associated with EOPD alone (Arshad et al. 2017 ). 6.2 Tremor-dominant (TD) PD vs. non-tremor-dominant (NTD) PD PPD can be classified into TD PD and NTD PD. Individuals with NTD PD have lower levels of serum uric acid (UA) and a significantly lower serum UA/creatinine (Cr) ratio (UA/Cr) than those with TD PD (van Wamelen et al. 2020 ). 6.3 PD versus PD-MCI Individuals with PD-MCI have higher mean levels of total cholesterol (TC), triglycerides (TG), and apolipoprotein A1 (apo A1) than subgroups with normal cognition. Therefore, TC, TG, and apo A1 may serve as valuable biomarkers for PD-MCI (Deng et al. 2022 ). Conversely, serum levels of high-density lipoprotein cholesterol were elevated in patients with PD (Dong et al. 2021 ; Li et al. 2020 ). 6.4 PD with hallucinations Levels of 8-OHdG are reportedly higher in PD with hallucinations, while no such elevation was observed in cases associated with dementia or other clinical features (Hirayama et al. 2018 ; Faria et al. 2019 ). 6.5 PD with rapid eye movement sleep behavior disorder (RBD) Plasma GFAP levels were notably elevated in patients with PD exhibiting RBD compared to those without RBD (Teng et al. 2023 ). Emerging Technologies The importance of novel technologies in identifying biomarkers has been emphasized as these advancements provided increased discriminatory capabilities (Parnetti et al. 2019 ). Highly accurate methods are changing previously known but non-significant findings. The measurement techniques, represented by α-syn seed amplification (SAA) that includes real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA), have shown high specificity (almost 100%) and sensitivity (> 90%) (Shahnawaz et al. 2017 ; Fairfoul et al. 2016 ). SAA has been employed to identify misfolded α-syn aggregates in the CSF and peripheral tissues (Ma et al. 2023). RT-QuIC and PMCA can distinguish PD from other NDDs according to variations in α-syn aggregates. The reliability in detection and the adaptability of RT-QuIC across different tissues and biological fluids have allowed this technique to become the benchmark when investigating the aggregation of α-syn in humans (Goolla et al. 2023 ). The HANdai Amyloid Burst Inducer technique has been suggested as a viable alternative to the PMCA and RT-QuIC for assessing pro-aggregating proteins in biofluids due to its faster assay speed than PMCA and RT-QuIC (Umemoto et al. 2014 ). It is currently being studied as a technique for measuring pro-aggregating forms of α-syn. Combining these technologies, scientists have developed several types of SAA, including immunoprecipitation-based RT-QuIC (IP/RT-QuIC), which enables the detection of pathogenic α-syn seeds in the serum of individuals with synucleinopathy (Okuzumi et al. 2023 ). Moreover, researchers found that different sources of α-syn seeds have different optimal signal display conditions, making it possible to develop specific SAAs for a single disease such as MSA (Martinez-Valbuena et al. 2022 ). Based on the total α-synuclein assay, a modified Luminex assay, namely the Bead-based Luminex assays, was developed. Its sensitivity is approximately 9 pg/mL, providing a highly precise method for measuring pS129 (Wang et al. 2012 ). Detection systems supported by the Simoa Bead technology can accurately quantify low-concentration proteins and peptides at the level of fM with excellent reproducibility. Kawahata, Sekimori, Oizumi, Takeda, and Fukunaga (Kawahata et al. 2023 ) used this technique to quantify FABP levels. Currently, Meso Scale Discovery electrochemiluminescence technology has been gradually used to detect molecular markers of neurodegenerative diseases and has shown a higher sensitivity (Zhao et al. 2020 ) Novel ELISA assays have been developed by Majbour et al. ( 2016 ). Their method expanded the detection limit of α-syn to 50 pg/mL, which is 20-fold lower than that detected in human CSF. Meanwhile, the detection limits of pS129 and recombinant o-α-syn were expanded to 20 pg/mL and 10 pg/mL, respectively. To exceed these limits, technologies, such as novel photochemical, electrochemical, and crystal biosensors should be utilized (Jabbari et al. 2020 ). From the perspective of technological evolution, the development of targeted detection methods is an inevitable requirement for the differential diagnosis of PD. Conclusions This review focused on the blood and CSF markers in PD as they are easily acquired, non-invasive, and in proximity to the brain in contrast to brain tissue biopsy or urine tests (Parnetti et al. 2019 ). Thus, facilitating the integration of clinical and scientific research for these biomarkers is essential. The differences between t-α-syn, o-α-syn, pS-129, aggregates of α-syn, Kallikrein 10, τT/Aβ42 ratio, α-syn concentrations in exosomes, NDEV concentrations of both o-α-syn and Tau aggregates, the oEV/nEV pS129-α-syn ratio, and cNfL levels between PD and APS have been revealed. Future diagnostic studies on PD should focus on the differentially expressed molecules in this disease. miR-30c, miR-148b, miR-24, miR-223, and miR-324-3p exhibit specificity in identifying patient with PD with MSA. FABP3, the t-tau/t-a-syn ratio, total α-syn levels in erythrocytes, and serum NfL concentrations may distinguish PDD from other dementias and movement disorders. Total α-syn levels in erythrocytes and serum NfL levels have distinctly different concentrations in ET compared to PD. CRP, Hcy, GFAP, microRNA, serum UA, TC, TG, A1, and 8-OHdG levels may also be potentially used to support the differentiation between the different PD subtypes (Supplementary Table 1). Currently, diagnosing PD primarily depends on clinical symptoms, and the relationship between symptoms and prognosis has been partially established (Armstrong and Okun 2020 ). However, the differences between biomarkers among different neurodegenerative diseases should make us consider the occurrence and development of this disease at a more specific level. Differential diagnostic biomarkers of PD in the blood and CSF represent its unique onset and evolution, which should further research on its etiology and pathogenesis (Kelly et al. 2023 ). Clinical pathological studies and clinical trials should accurately classify study participants (Lin et al. 2020 ). The emergence of biomarkers makes it feasible to accurately identify patients and allows for a more reliable reference for distinguishing PD from other diseases (Tolosa et al. 2021 ). This is a practical significance of PD’s differential diagnostic biomarkers. Several biomarkers in PD and related diseases have obvious differences, but only a few have excellent performance by relying on high-precision testing methods. The combination of multiple biomarkers or clinical signs can increase the ability to discriminate between diseases (Quadalti et al. 2021 ; Dutta et al. 2021 ; Meloni et al. 2023 ; Taha et al. 2023 ; Kawahata et al. 2023 ). Developing a combined detection method based on multiple biomarkers may not be an urgent need for PD, which is an incurable disease; however, if patients can be accurately classified at disease onset, improving the efficiency of future scientific research and follow-up research in a large population will be beneficial. Declarations Acknowledgments: The manuscript has been carefully reviewed by an experienced editor whose first language is English and who specializes in editing papers written by scientists whose native language is not English. Funding : The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests: Author LH was employed by ICON Plc. The remaining authors have no relevant financial or nonfinancial interests to disclose.. Author Contributions: Study design was performed by YW and writing of the original draft and visualization was performed by JM. Data collection was performed by ZT, YqW, JZ, ZW and LH. Data acquisition and critical revision of the manuscript was performed by SL. Project administration was carried out by YW. Data Availability Statement: No new data were created. Ethics Approval: Not applicable. Consent to Participate: Not applicable. Consent to Publish : All authors have read and approved the final version of the manuscript. References Aerts MB, Esselink RA, Abdo WF, Bloem BR, Verbeek MM (2012) CSF α-synuclein does not differentiate between parkinsonian disorders. Neurobiol Aging 33:430.e1-430.e3. https://doi.org/10.1016/j.neurobiolaging.2010.12.001 Armstrong MJ, Okun MS (2020) Diagnosis and treatment of Parkinson disease: a review. JAMA 323:548-560. https://doi.org/10.1001/jama.2019.22360 Arshad AR, Sulaiman SA, Saperi AA, Jamal R, Mohamed Ibrahim N, Abdul Murad NA (2017) MicroRNAs and target genes as biomarkers for the diagnosis of early onset of Parkinson disease. Front Mol Neurosci 10:352. https://doi.org/10.3389/fnmol.2017.00352 Barbour R, Kling K, Anderson JP, Banducci K, Cole T, Diep L, Fox M, Goldstein JM, Soriano F, Seubert P, Chilcote TJ (2008) Red blood cells are the major source of alpha-synuclein in blood. Neurodegener Dis 5:55-59. https://doi.org/10.1159/000112832 Bartl M, Dakna M, Schade S, Otte B, Wicke T, Lang E, Starke M, Ebentheuer J, Weber S, Toischer K, Schnelle M, Sixel-Döring F, Trenkwalder C, Mollenhauer B (2023) Blood markers of inflammation, neurodegeneration, and cardiovascular risk in early Parkinson’s disease. Mov Disord 38:68-81. https://doi.org/10.1002/mds.29257 Bridel C, van Wieringen WN, Zetterberg H, Tijms BM, Teunissen CE, and the NFL Group, Alvarez-Cermeño JC, Andreasson U, Axelsson M, Bäckström DC, Bartos A, Bjerke M, Blennow K, Boxer A, Brundin L, Burman J, Christensen T, Fialová L, Forsgren L, Frederiksen JL, Gisslén M, Gray E, Gunnarsson M, Hall S, Hansson O, Herbert MK, Jakobsson J, Jessen-Krut J, Janelidze S, Johannsson G, Jonsson M, Kappos L, Khademi M, Khalil M, Kuhle J, Landén M, Leinonen V, Logroscino G, Lu CH, Lycke J, Magdalinou NK, Malaspina A, Mattsson N, Meeter LH, Mehta SR, Modvig S, Olsson T, Paterson RW, Pérez-Santiago J, Piehl F, Pijnenburg YAL, Pyykkö OT, Ragnarsson O, Rojas JC, Romme Christensen J, Sandberg L, Scherling CS, Schott JM, Sellebjerg FT, Simone IL, Skillbäck T, Stilund M, Sundström P, Svenningsson A, Tortelli R, Tortorella C, Trentini A, Troiano M, Turner MR, van Swieten JC, Vågberg M, Verbeek MM, Villar LM, Visser PJ, Wallin A, Weiss A, Wikkelsø C, Wild EJ (2019) Diagnostic value of cerebrospinal fluid neurofilament light protein in neurology: a systematic review and meta-analysis. JAMA Neurol 76:1035-1048. https://doi.org/10.1001/jamaneurol.2019.1534 Chen R, Gu X, Wang X (2022) α-synuclein in Parkinson’s disease and advances in detection. Clin Chim Acta 529:76-86. https://doi.org/10.1016/j.cca.2022.02.006 Chen WR, Chen JC, Chang SY, Chao CT, Wu YR, Chen CM, Chou C (2022) Phosphorylated α-synuclein in diluted human serum as a biomarker for Parkinson’s disease. Biomed J 45:914-922. https://doi.org/10.1016/j.bj.2021.12.010 Chiasserini D, Biscetti L, Eusebi P, Salvadori N, Frattini G, Simoni S, De Roeck N, Tambasco N, Stoops E, Vanderstichele H, Engelborghs S, Mollenhauer B, Calabresi P, Parnetti L (2017) Differential role of CSF fatty acid binding protein 3, α-synuclein, and Alzheimer’s disease core biomarkers in Lewy body disorders and Alzheimer’s dementia. Alzheimers Res Ther 9:52. https://doi.org/10.1186/s13195-017-0276-4 Constantinides VC, Majbour NK, Paraskevas GP, Abdi I, Safieh-Garabedian B, Stefanis L, El-Agnaf OM, Kapaki E (2021) Cerebrospinal fluid alpha-synuclein species in cognitive and movements disorders. Brain Sci 11:119. https://doi.org/10.3390/brainsci11010119 Constantinides VC, Paraskevas GP, Emmanouilidou E, Petropoulou O, Bougea A, Vekrellis K, Evdokimidis I, Stamboulis E, Kapaki E (2017) CSF biomarkers beta-amyloid, tau proteins and a-synuclein in the differential diagnosis of Parkinson-plus syndromes. J Neurol Sci 382:91-95. https://doi.org/10.1016/j.jns.2017.09.039 Deng X, Saffari SE, Ng SYE, Chia N, Tan JY, Choi X, Heng DL, Xu Z, Tay KY, Au WL, Liu N, Ng A, Tan EK, Tan LCS (2022) Blood lipid biomarkers in early Parkinson’s disease and Parkinson’s disease with mild cognitive impairment. J Parkinsons Dis 12:1937-1943. https://doi.org/10.3233/JPD-213135 Dong MX, Wei YD, Hu L (2021) The disturbance of lipid metabolism is correlated with neuropsychiatric symptoms in patients with Parkinson’s disease. Chem Phys Lipids 239:105112. https://doi.org/10.1016/j.chemphyslip.2021.105112 Dutta S, Hornung S, Kruayatidee A, Maina KN, Del Rosario I, Paul KC, Wong DY, Duarte Folle A, Markovic D, Palma JA, Serrano GE, Adler CH, Perlman SL, Poon WW, Kang UJ, Alcalay RN, Sklerov M, Gylys KH, Kaufmann H, Fogel BL, Bronstein JM, Ritz B, Bitan G (2021) α-synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson’s disease from multiple system atrophy. Acta Neuropathol 142:495-511. https://doi.org/10.1007/s00401-021-02324-0 Dutta, S.; Hornung, S.; Kruayatidee, A.; Maina, K.N.; Del Rosario, I.; Paul, K.C.; Wong, D.Y.; Duarte Folle, A.; Markovic, D.; Palma, J.A.; Serrano, G.E.; Adler, C.H.; Perlman, S.L.; Poon, W.W.; Kang, U.J.; Alcalay, R.N.; Sklerov, M.; Gylys, K.H.; Kaufmann, H.; Fogel, B.L.; Bronstein, J.M.; Ritz, B.; Bitan, G (2021) α-synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson’s disease from multiple system atrophy. Acta Neuropathol 142:495-511. https://doi.org/10.1007/s00401-021-02324-0 Estaun-Panzano J, Arotcarena ML, Bezard E (2023) Monitoring α-synuclein aggregation. Neurobiol Dis 176:105966. https://doi.org/10.1016/j.nbd.2022.105966 Eusebi P, Giannandrea D, Biscetti L, Abraha I, Chiasserini D, Orso M, Calabresi P, Parnetti L (2017) Diagnostic utility of cerebrospinal fluid α-synuclein in Parkinson’s disease: a systematic review and meta-analysis. Mov Disord 32:1389-1400. https://doi.org/10.1002/mds.27110 Fairfoul G, McGuire LI, Pal S, Ironside JW, Neumann J, Christie S, Joachim C, Esiri M, Evetts SG, Rolinski M, Baig F, Ruffmann C, Wade-Martins R, Hu MTM, Parkkinen L, Green AJE (2016) Alpha-synuclein RT-QuIC in the CSF of patients with alpha-synucleinopathies. Ann Clin Transl Neurol 3:812-818. https://doi.org/10.1002/acn3.338 Faria AM, Peixoto EBMI, Adamo CB, Flacker A, Longo E, Mazon T (2019) Controlling parameters and characteristics of electrochemical biosensors for enhanced detection of 8-hydroxy-2′-deoxyguanosine. Sci Rep 9:7411. https://doi.org/10.1038/s41598-019-43680-y Førland MG, Tysnes OB, Aarsland D, Maple-Grødem J, Pedersen KF, Alves G, Lange J (2020) The value of cerebrospinal fluid α-synuclein and the tau/α-synuclein ratio for diagnosis of neurodegenerative disorders with Lewy pathology. Eur J Neurol 27:43-50. https://doi.org/10.1111/ene.14032 Goolla M, Cheshire WP, Ross OA, Kondru N (2023) Diagnosing multiple system atrophy: current clinical guidance and emerging molecular biomarkers. Front Neurol 14:1210220. https://doi.org/10.3389/fneur.2023.1210220 Guévremont D, Roy J, Cutfield NJ, Williams JM (2023) MicroRNAs in Parkinson’s disease: a systematic review and diagnostic accuracy meta-analysis. Sci Rep 13:16272. https://doi.org/10.1038/s41598-023-43096-9 Hansson O, Janelidze S, Hall S, Magdalinou N, Lees AJ, Andreasson U, Norgren N, Linder J, Forsgren L, Constantinescu R, Zetterberg H, Blennow K, Swedish BioFINDER study (2017) Blood-based NfL: A biomarker for differential diagnosis of parkinsonian disorder. Neurology 88:930-937. https://doi.org/10.1212/WNL.0000000000003680 Harris E (2023) Identifying lewy body disease before symptoms. JAMA 330:686. https://doi.org/10.1001/jama.2023.13621 Hirayama M, Ito M, Minato T, Yoritaka A, LeBaron TW, Ohno K (2018) Inhalation of hydrogen gas elevates urinary 8-hydroxy-2′-deoxyguanine in Parkinson’s disease. Med Gas Res 8:144-149. https://doi.org/10.4103/2045-9912.248264 Hirschberg Y, Valle-Tamayo N, Dols-Icardo O, Engelborghs S, Buelens B, Vandenbroucke RE, Vermeiren Y, Boonen K, Mertens I (2023) Proteomic comparison between non-purified cerebrospinal fluid and cerebrospinal fluid-derived extracellular vesicles from patients with Alzheimer’s, Parkinson’s and Lewy body dementia. J Extracell Vesicles 12:e12383. https://doi.org/10.1002/jev2.12383 Holm H, Gundersen V, Dietrichs E (2023) Vascular parkinsonism. Tidsskr Nor Laegeforen 143. https://doi.org/10.4045/tidsskr.22.0539 Huang Y, Huang C, Zhang Q, Shen T, Sun J (2022) Serum NFL discriminates Parkinson disease from essential tremor and reflect motor and cognition severity. BMC Neurol 22:39. https://doi.org/10.1186/s12883-022-02558-9 Jabbari E, Holland N, Chelban V, Jones PS, Lamb R, Rawlinson C, Guo T, Costantini AA, Tan MMX, Heslegrave AJ, Roncaroli F, Klein JC, Ansorge O, Allinson KSJ, Jaunmuktane Z, Holton JL, Revesz T, Warner TT, Lees AJ, Zetterberg H, Russell LL, Bocchetta M, Rohrer JD, Williams NM, Grosset DG, Burn DJ, Pavese N, Gerhard A, Kobylecki C, Leigh PN, Church A, Hu MTM, Woodside J, Houlden H, Rowe JB, Morris HR (2020) Diagnosis across the spectrum of progressive supranuclear palsy and corticobasal syndrome. JAMA Neurol 77:377-387. https://doi.org/10.1001/jamaneurol.2019.4347 Kawahata I, Fukunaga K (2023) Pathogenic impact of fatty acid-binding proteins in Parkinson’s disease-potential biomarkers and therapeutic targets. Int J Mol Sci 24:17037. https://doi.org/10.3390/ijms242317037 Kawahata I, Sekimori T, Oizumi H, Takeda A, Fukunaga K (2023) Using fatty acid-binding proteins as potential biomarkers to discriminate between Parkinson’s disease and dementia with Lewy bodies: exploration of a novel technique. Int J Mol Sci 24:13267. https://doi.org/10.3390/ijms241713267 Kelly J, Moyeed R, Carroll C, Luo S, Li X (2023) Blood biomarker-based classification study for neurodegenerative diseases. Sci Rep 13:17191. https://doi.org/10.1038/s41598-023-43956-4 Koníčková D, Menšíková K, Klíčová K, Chudáčková M, Kaiserová M, Přikrylová H, Otruba P, Nevrlý M, Hluštík P, Hényková E, Kaleta M, Friedecký D, Matěj R, Strnad M, Novák O, Plíhalová L, Rosales R, Colosimo C, Kaňovský P (2023) Cerebrospinal fluid and blood serum biomarkers in neurodegenerative proteinopathies: a prospective, open, cross-correlation study. J Neurochem 167:168-182. https://doi.org/10.1111/jnc.15944 Li J, Gu C, Zhu M, Li D, Chen L, Zhu X (2020) Correlations between blood lipid, serum cystatin C, and homocysteine levels in patients with Parkinson’s disease. Psychogeriatrics 20:180-188. https://doi.org/10.1111/psyg.12483 Lin CH, Chiu SI, Chen TF, Jang JR, Chiu MJ (2020) Classifications of neurodegenerative disorders using a multiplex blood biomarkers-based machine learning model. Int J Mol Sci 21:6914. https://doi.org/10.3390/ijms21186914 Lindqvist D, Hall S, Surova Y, Nielsen HM, Janelidze S, Brundin L, Hansson O (2013) Cerebrospinal fluid inflammatory markers in Parkinson’s disease—associations with depression, fatigue, and cognitive impairment. Brain Behav Immun 33:183-189. https://doi.org/10.1016/j.bbi.2013.07.007 Ma Z-L, Wang Z-L, Zhang F-Y, Liu H-X, Mao L-H, Yuan L (2024) Biomarkers of Parkinson’s disease: from basic research to clinical practice. Aging Dis 15:1813-1830. https://doi.org/10.14336/AD.2023.1005 Majbour NK, Vaikath NN, van Dijk KD, Ardah MT, Varghese S, Vesterager LB, Montezinho LP, Poole S, Safieh-Garabedian B, Tokuda T, Teunissen CE, Berendse HW, van de Berg WDJ, El-Agnaf OMA (2016) Oligomeric and phosphorylated alpha-synuclein as potential CSF biomarkers for Parkinson’s disease. Mol Neurodegener 11:7. https://doi.org/10.1186/s13024-016-0072-9 Martinez-Valbuena I, Visanji NP, Kim A, Lau HHC, So RWL, Alshimemeri S, Gao A, Seidman MA, Luquin MR, Watts JC, Lang AE, Kovacs GG (2022) Alpha-synuclein seeding shows a wide heterogeneity in multiple system atrophy. Transl Neurodegener 11:7. https://doi.org/10.1186/s40035-022-00283-4 Meloni M, Agliardi C, Guerini FR, Zanzottera M, Bolognesi E, Picciolini S, Marano M, Magliozzi A, Di Fonzo A, Arighi A, Fenoglio C, Franco G, Arienti F, Saibene FL, Navarro J, Clerici M (2023) Oligomeric α-synuclein and tau aggregates in NDEVs differentiate Parkinson’s disease from atypical parkinsonisms. Neurobiol Dis 176:105947. https://doi.org/10.1016/j.nbd.2022.105947 Neumaier EE, Rothhammer V, Linnerbauer M (2023) The role of midkine in health and disease. Front Immunol 14:1310094. https://doi.org/10.3389/fimmu.2023.1310094 Okuzumi A, Hatano T, Matsumoto G, Nojiri S, Ueno SI, Imamichi-Tatano Y, Kimura H, Kakuta S, Kondo A, Fukuhara T, Li Y, Funayama M, Saiki S, Taniguchi D, Tsunemi T, McIntyre D, Gérardy JJ, Mittelbronn M, Kruger R, Uchiyama Y, Nukina N, Hattori N (2023) Propagative α-synuclein seeds as serum biomarkers for synucleinopathies. Nat Med 29:1448-1455. https://doi.org/10.1038/s41591-023-02358-9 Painous C, Fernández M, Pérez J, de Mena L, Cámara A, Compta Y (2024) Fluid and tissue biomarkers in Parkinson’s disease: immunodetection or seed amplification? Central or peripheral? Parkinsonism Relat Disord 121:105968. https://doi.org/10.1016/j.parkreldis.2023.105968 Parnetti L, Gaetani L, Eusebi P, Paciotti S, Hansson O, El-Agnaf O, Mollenhauer B, Blennow K, Calabresi P (2019) CSF and blood biomarkers for Parkinson’s disease. Lancet Neurol 18:573-586. https://doi.org/10.1016/S1474-4422(19)30024-9 Paslawski W, Khosousi S, Hertz E, Markaki I, Boxer A, Svenningsson P (2023) Large-scale proximity extension assay reveals CSF midkine and DOPA decarboxylase as supportive diagnostic biomarkers for Parkinson’s disease. Transl Neurodegener 12:42. https://doi.org/10.1186/s40035-023-00374-w Pereira JB, Kumar A, Hall S, Palmqvist S, Stomrud E, Bali D, Parchi P, Mattsson-Carlgren N, Janelidze S, Hansson O (2023) DOPA decarboxylase is an emerging biomarker for Parkinsonian disorders including preclinical lewy body disease. Nat Aging 3:1201-1209. https://doi.org/10.1038/s43587-023-00478-y Quadalti C, Calandra-Buonaura G, Baiardi S, Mastrangelo A, Rossi M, Zenesini C, Giannini G, Candelise N, Sambati L, Polischi B, Plazzi G, Capellari S, Cortelli P, Parchi P (2021) Neurofilament light chain and alpha-synuclein RT-QuIC as differential diagnostic biomarkers in parkinsonisms and related syndromes. NPJ Parkinsons Dis 7:93. https://doi.org/10.1038/s41531-021-00232-4 Shahnawaz M, Mukherjee A, Pritzkow S, Mendez N, Rabadia P, Liu X, Hu B, Schmeichel A, Singer W, Wu G, Tsai AL, Shirani H, Nilsson KPR, Low PA, Soto C (2020) Discriminating α-synuclein strains in Parkinson’s disease and multiple system atrophy. Nature 578:273-277. https://doi.org/10.1038/s41586-020-1984-7 Shahnawaz M, Tokuda T, Waragai M, Mendez N, Ishii R, Trenkwalder C, Mollenhauer B, Soto C (2017) Development of a biochemical diagnosis of Parkinson disease by detection of alpha-synuclein misfolded aggregates in cerebrospinal fluid. JAMA Neurol 74:163-172. https://doi.org/10.1001/jamaneurol.2016.4547 Shim KH, Kang MJ, Youn YC, An SSA, Kim S (2022) Alpha-synuclein: a pathological factor with Abeta and tau and biomarker in Alzheimer’s disease. Alzheimers Res Ther 14:201. https://doi.org/10.1186/s13195-022-01150-0 Siderowf A, Concha-Marambio L, Lafontant DE, Farris CM, Ma Y, Urenia PA, Nguyen H, Alcalay RN, Chahine LM, Foroud T, Galasko D, Kieburtz K, Merchant K, Mollenhauer B, Poston KL, Seibyl J, Simuni T, Tanner CM, Weintraub D, Videnovic A, Choi SH, Kurth R, Caspell-Garcia C, Coffey CS, Frasier M, Oliveira LMA, Hutten SJ, Sherer T, Marek K, Soto C, Parkinson's Progression Markers Initiative (2023) Assessment of heterogeneity among participants in the Parkinson’s Progression Markers Initiative cohort using α-synuclein seed amplification: a cross-sectional study. Lancet Neurol 22:407-417. https://doi.org/10.1016/S1474-4422(23)00109-6 Song IU, Kim JS, Park IS, Kim YD, Cho HJ, Chung SW, Lee KS (2013) Clinical significance of homocysteine (hcy) on dementia in Parkinson’s disease (PD). Arch Gerontol Geriatr 57:288-291. https://doi.org/10.1016/j.archger.2013.04.015 Stoker TB, Greenland JC (2018) Parkinson’s disease: pathogenesis and clinical aspects. Codon Publications, Brisbane (AU) Sung YJ, Yang C, Norton J, Johnson M, Fagan A, Bateman RJ, Perrin RJ, Morris JC, Farlow MR, Chhatwal JP, Schofield PR, Chui H, Wang F, Novotny B, Eteleeb A, Karch C, Schindler SE, Rhinn H, Johnson ECB, Oh HSH, Rutledge JE, Dammer EB, Seyfried NT, Wyss-Coray T, Harari O, Cruchaga C (2023) Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer’s disease. Sci Transl Med 15:eabq5923. https://doi.org/10.1126/scitranslmed.abq5923 Taha HB (2023) Rethinking the reliability and accuracy of biomarkers in CNS-originating EVs for Parkinson’s disease and multiple system atrophy. Front Neurol 14:1192115. https://doi.org/10.3389/fneur.2023.1192115 Taha HB, Bogoniewski A (2024) Analysis of biomarkers in speculative CNS-enriched extracellular vesicles for parkinsonian disorders: a comprehensive systematic review and diagnostic meta-analysis. J Neurol 271:1680-1706. https://doi.org/10.1007/s00415-023-12093-3 Taha HB, Hornung S, Dutta S, Fenwick L, Lahgui O, Howe K, Elabed N, Del Rosario I, Wong DY, Duarte Folle A, Markovic D, Palma JA, Kang UJ, Alcalay RN, Sklerov M, Kaufmann H, Fogel BL, Bronstein JM, Ritz B, Bitan G (2023) Toward a biomarker panel measured in CNS-originating extracellular vesicles for improved differential diagnosis of Parkinson’s disease and multiple system atrophy. Transl Neurodegener 12:14. https://doi.org/10.1186/s40035-023-00346-0 Teng X, Mao S, Wu H, Shao Q, Zu J, Zhang W, Zhou S, Zhang T, Zhu J, Cui G, Xu C (2023) The relationship between serum neurofilament light chain and glial fibrillary acidic protein with the REM sleep behavior disorder subtype of Parkinson’s disease. J Neurochem 165:268-276. https://doi.org/10.1111/jnc.15780 Tofaris GK (2022) Initiation and progression of α-synuclein pathology in Parkinson’s disease. Cell Mol Life Sci 79:210. https://doi.org/10.1007/s00018-022-04240-2 Tolosa E, Garrido A, Scholz SW, Poewe W (2021) Challenges in the diagnosis of Parkinson’s disease. Lancet Neurol 20:385-397. https://doi.org/10.1016/S1474-4422(21)00030-2 Tsao H-H, Huang C-G, Wu Y-R (2022) Detection and assessment of alpha-synuclein in Parkinson disease. Neurochem Int 158:105358. https://doi.org/10.1016/j.neuint.2022.105358 Umemoto A, Yagi H, So M, Goto Y (2014) High-throughput analysis of ultrasonication-forced amyloid fibrillation reveals the mechanism underlying the large fluctuation in the lag time. J Biol Chem 289:27290-27299. https://doi.org/10.1074/jbc.M114.569814 van Wamelen DJ, Taddei RN, Calvano A, Titova N, Leta V, Shtuchniy I, Jenner P, Martinez-Martin P, Katunina E, Chaudhuri KR (2020) Serum uric acid levels and non-motor symptoms in Parkinson’s disease. J Parkinsons Dis 10:1003-1010. https://doi.org/10.3233/JPD-201988 Villar-Menéndez I, Porta S, Buira SP, Pereira-Veiga T, Díaz-Sánchez S, Albasanz JL, Ferrer I, Martín M, Barrachina M (2014) Increased striatal adenosine A2a receptor levels is an early event in Parkinson’s disease-related pathology and it is potentially regulated by miR-34b. Neurobiol Dis 69:206-214. https://doi.org/10.1016/j.nbd.2014.05.030 Wang Y, Shi M, Chung KA, Zabetian CP, Leverenz JB, Berg D, Srulijes K, Trojanowski JQ, Lee VMY, Siderowf AD, Hurtig H, Litvan I, Schiess MC, Peskind ER, Masuda M, Hasegawa M, Lin X, Pan C, Galasko D, Goldstein DS, Jensen PH, Yang H, Cain KC, Zhang J (2012) Phosphorylated α-synuclein in Parkinson’s disease. Sci Transl Med 4:121ra20. https://doi.org/10.1126/scitranslmed.3002566 Wikipedia KLK10. Wikipedia. Wikipedia. Retrieved from https://en.wikipedia.org/wiki/KLK10 Yan S, Jiang C, Janzen A, Barber TR, Seger A, Sommerauer M, Davis JJ, Marek K, Hu MT, Oertel WH, Tofaris GK (2024) Neuronally derived extracellular vesicle α-synuclein as a serum biomarker for individuals at risk of developing Parkinson disease. JAMA Neurol 81:59-68. https://doi.org/10.1001/jamaneurol.2023.4398 Yoo SW, Ha S, Lyoo CH, Kim Y, Yoo JY, Kim JS (2023) Exploring the link between essential tremor and Parkinson’s disease. NPJ Parkinsons Dis 9:134. https://doi.org/10.1038/s41531-023-00577-y Yu Z, Liu G, Li Y, Arkin E, Zheng Y, Feng T (2022) Erythrocytic alpha-synuclein species for Parkinson’s disease diagnosis and the correlations with clinical characteristics. Front Aging Neurosci 14:827493. https://doi.org/10.3389/fnagi.2022.827493 Yu Z, Liu G, Zheng Y, Huang G, Feng T (2023) Erythrocytic alpha-synuclein as potential biomarker for the differentiation between essential tremor and Parkinson’s disease. Front Neurol 14:1173074. https://doi.org/10.3389/fneur.2023.1173074 Zhao A, Li Y, Niu M, Li G, Luo N, Zhou L, Kang W, Liu J (2020) SNCA hypomethylation in rapid eye movement sleep behavior disorder is a potential biomarker for Parkinson’s disease. J Parkinsons Dis 10:1023-1031. https://doi.org/10.3233/JPD-201912 Zubelzu M, Morera-Herreras T, Irastorza G, Gómez-Esteban JC, Murueta-Goyena A (2022) Plasma and serum alpha-synuclein as a biomarker in Parkinson’s disease: a meta-analysis. Parkinsonism Relat Disord 99:107-115. https://doi.org/10.1016/j.parkreldis.2022.06.001 Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstract.tif SupplementaryTable.docx Cite Share Download PDF Status: Published Journal Publication published 27 Dec, 2024 Read the published version in Cellular and Molecular Neurobiology → Version 1 posted Editorial decision: Revision requested 11 Oct, 2024 Reviews received at journal 10 Oct, 2024 Reviews received at journal 10 Oct, 2024 Reviewers agreed at journal 06 Oct, 2024 Reviewers agreed at journal 01 Oct, 2024 Reviewers agreed at journal 04 Sep, 2024 Reviews received at journal 01 Sep, 2024 Reviewers agreed at journal 01 Sep, 2024 Reviewers agreed at journal 30 Aug, 2024 Reviewers invited by journal 30 Aug, 2024 Editor assigned by journal 29 Aug, 2024 Submission checks completed at journal 28 Aug, 2024 First submitted to journal 25 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4973615","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":355084909,"identity":"49e17dda-21cc-45ab-864d-6be194bc1b1f","order_by":0,"name":"Jie Ma","email":"","orcid":"","institution":"Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Ma","suffix":""},{"id":355084910,"identity":"ea38a381-2806-4778-bc3a-c6ea50466f87","order_by":1,"name":"Zhijian Tang","email":"","orcid":"","institution":"Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhijian","middleName":"","lastName":"Tang","suffix":""},{"id":355084911,"identity":"08116315-dffe-4aaf-a480-572384d095a2","order_by":2,"name":"Yaqi Wu","email":"","orcid":"","institution":"Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yaqi","middleName":"","lastName":"Wu","suffix":""},{"id":355084912,"identity":"953b7045-0adf-4ee1-9bcd-17027f52dcec","order_by":3,"name":"Jun Zhang","email":"","orcid":"","institution":"Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Zhang","suffix":""},{"id":355084913,"identity":"1b6287b6-dafa-40dd-94b1-974b5a63c7d0","order_by":4,"name":"Zitao Wu","email":"","orcid":"","institution":"University of Illinois Urbana-Champaign","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zitao","middleName":"","lastName":"Wu","suffix":""},{"id":355084916,"identity":"411e7450-0423-4092-9ec2-514fc02f7b81","order_by":5,"name":"Lulu Huang","email":"","orcid":"","institution":"Department of ICON Pharma Development Solutions (IPD), ICON Public limited company (ICON Plc)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lulu","middleName":"","lastName":"Huang","suffix":""},{"id":355084918,"identity":"3d18ef46-1f62-4de6-ac0e-7f6f1559e1c8","order_by":6,"name":"Shengwen Liu","email":"","orcid":"","institution":"Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shengwen","middleName":"","lastName":"Liu","suffix":""},{"id":355084920,"identity":"304c6641-7c54-4df7-8809-073a7ac95835","order_by":7,"name":"Yu Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYBACfmbG9g8MPBL1jO3Nx6BiCfi1SIJUHuCxSWDuOZYG5BsQ1mJwBqjyAENaAvuMHDPitDDcyDF7/EHmcB7vjJxvj3n+/GHgZ88xYPi5A7cOxhk55gYHeA4XS/a83W7M22bAINnzxoCx9wxuLcwSOQYSQC2MG9tzt0nzNhgwGNzIMWBmbMOthQ2mZf+BnGfSPH8MGOwJaeHhOZYG1JKW2NiRwybNwwa0RYKAFgn25sMGZ3hsjBl7jplJzm0z5pE486zgYC8eLfaHGRsfVPZIyAGj8pnEmz9ycvztyRsf/MSjBQwYe5BcCiIOENAABD8IKxkFo2AUjIIRDADIxFP5VkWOjgAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-08-25 16:42:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4973615/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4973615/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10571-024-01523-z","type":"published","date":"2024-12-27T15:57:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":65464624,"identity":"13670006-6b27-44b7-8732-36650a43c263","added_by":"auto","created_at":"2024-09-27 19:11:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4493,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the different types of PD’s differential diagnostic biomarkers. DDC: DOPA decarboxylase; GFAP: glial fibrillary acidic protein; NfL: neurofilament light chain protein; 8-OHdG: 8-hydroxy-2'–deoxyguanosine; Hcy: homocysteine; TC: total cholesterol; TG: triglycerides; HDL: high-density lipoprotein cholesterol; Apo A1: apolipoprotein A1.\u003c/p\u003e","description":"","filename":"fig.png","url":"https://assets-eu.researchsquare.com/files/rs-4973615/v1/88542813a58592e5f63ed310.png"},{"id":65464626,"identity":"e2cd8f19-1fa2-4762-8a6d-bf6609335b95","added_by":"auto","created_at":"2024-09-27 19:11:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":362927,"visible":true,"origin":"","legend":"\u003cp\u003eConcentrations of NfL in PD were considerably different from those in APS PDD and ET, with NfL concentrations higher in APS and PDD than in PD and the opposite in APS (vascular parkinsonism is not included). This may suggest a different pathogenesis of its disease at the molecular level. NfL: Neurofilament light protein, PD: Parkinson’s diaseae, APS: Atypical parkinson’s syndrome, PSP: progressive supranuclear palsy, CBS: corticobasal syndrome, MSA: multiple system atrophy, PDD: Parkinson's disease dementia, ET: Essential tremor.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4973615/v1/a6a17023dda85847b736e8cd.png"},{"id":72640813,"identity":"3d9a4cbe-1ff4-4f72-9e12-76ee790db744","added_by":"auto","created_at":"2024-12-30 16:09:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":928234,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4973615/v1/49e29044-0593-4993-946a-dc9d070c1833.pdf"},{"id":65464628,"identity":"c20a7571-bfcc-4b55-a937-0d66c6c9c345","added_by":"auto","created_at":"2024-09-27 19:11:18","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20713980,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.tif","url":"https://assets-eu.researchsquare.com/files/rs-4973615/v1/5cf3b9f07c12f9cf62bc0109.tif"},{"id":65464627,"identity":"25585887-ae90-441d-bca9-8a381a0e34cb","added_by":"auto","created_at":"2024-09-27 19:11:18","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":35211,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-4973615/v1/338cdb8bfecb205e1b01f30a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Blood and cerebrospinal fluid differences between Parkinson's disease and related diseases","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAtypical Parkinson\u0026rsquo;s syndrome (APS) includes progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), multiple system atrophy (MSA), and vascular parkinsonism (VP). During the early stages of APS, the individual conditions are difficult to distinguish from Parkinson's disease (PD) and are often misdiagnosed as PD (Jabbari et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Holm et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). PD dementia (PDD) is a manifestation of PD during its middle and late stages. Distinguishing PDD from dementia with Lewy bodies (DLB) is challenging and may result in indiscriminate clinical pathology studies or clinical trials (Hirschberg et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). DLB and PDD are collectively referred to as Lewy body disease or synucleinopathy (Harris \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, the motor symptoms of PD should also be differentiated from essential tremor (ET) (Yu et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yoo et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThrough an extensive literature search, we found that several blood and cerebrospinal fluid (CSF) biomarkers significantly differ between PD and other related diseases (Fig.\u0026nbsp;1). These molecules may be defined as differential diagnostic biomarkers of PD (Quadalti et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While these biomarkers have significant statistical differences in the study of groups, the traits of discrimination may need to be demonstrated in many ways. The differential diagnostic biomarkers of PD may be used as reference for clinical pathological studies and clinical trials, because differentiating these diseases is the first step for such studies (Dutta et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;1\u003c/b\u003e Flow diagram of the different types of PD\u0026rsquo;s differential diagnostic biomarkers. DDC: DOPA decarboxylase; GFAP: glial fibrillary acidic protein; NfL: neurofilament light chain protein; 8-OHdG: 8-hydroxy-2'\u0026ndash;deoxyguanosine; Hcy: homocysteine; TC: total cholesterol; TG: triglycerides; HDL: high-density lipoprotein cholesterol; Apo A1: apolipoprotein A1.\u003c/p\u003e"},{"header":"Search Strategy and Selection Criteria","content":"\u003cp\u003eThrough literature review, we first identified diseases that require differentiation from PD as well as the different PD subtypes (see search query). Next, we screened for diagnostic biomarkers using the search statements (\u0026ldquo;Parkinson\u0026rsquo;s disease\u0026rdquo; OR \u0026ldquo;PD\u0026rdquo;) AND (\u0026ldquo;biomarker\u0026rdquo;) on PubMed and Web of Science. We obtained PD-related biomarkers (see search query) and selected review articles to obtain a comprehensive biomarkers selection. Based on the biomarkers identified, we used the search formulas (\u0026ldquo;Parkinson's Disease\u0026rdquo; OR PD) AND ((\u0026ldquo;Atypical Parkinson's syndrome\u0026rdquo; OR APS OR \u0026ldquo;Atypical parkinsonism disorder\u0026rdquo; OR APD) OR (\u0026ldquo;progressive supranuclear palsy\u0026rdquo; OR PSP) OR (\u0026ldquo;corticobasal syndrome\u0026rdquo; OR CBS) OR (\u0026ldquo;multiple system atrophy\u0026rdquo; OR MSA) OR (\u0026ldquo;vascular parkinsonism\u0026rdquo; OR VP) OR (\u0026ldquo;dementia with Lewy bodies\u0026rdquo; OR DLB) OR (\u0026ldquo;essential tremor\u0026rdquo; OR ET)) AND ((\u0026ldquo;α-Synuclein\u0026rdquo; OR \u0026ldquo;α-Syn\u0026rdquo;) OR (\u0026ldquo;DOPA Decarboxylase\u0026rdquo; OR \u0026ldquo;DDC\u0026rdquo;) OR (\u0026ldquo;Amyloid beta\u0026rdquo; OR \u0026ldquo;Aβ\u0026rdquo;) OR \u0026ldquo;tau protein\u0026rdquo; OR \u0026ldquo;Exosomes\u0026rdquo; OR (\u0026ldquo;Neurofilament Light Protein\u0026rdquo; OR \u0026ldquo;NfL\u0026rdquo;) OR \u0026ldquo;MicroRNAs\u0026rdquo; OR \u0026ldquo;FABP3\u0026rdquo;) to retrieve targeted literature while selecting studies that were appropriate to meet our research objectives. A similar search strategy was used to screen biomarkers for distinguishing PD subtypes. After screening abstracts, 91 articles were identified for further in-depth reading. Midkine (MK) and Kallikrein 10 were two molecules not obtained in the initial search, and no study further elaborated their roles in different PD subtypes. Ultimately, 72 articles were included in this review.\u003c/p\u003e"},{"header":"PD and APS","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.1. α-Synuclein (α-syn) and its variants\u003c/h2\u003e \u003cp\u003eα-syn is detectable in both CSF and plasma and is the most widely researched biomarker of PD (Tsao et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Estaun-Panzano et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tofaris \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Phosphorylation of the Ser129 site results in phosphorylated α-syn (PS-129), while pro-aggregating forms of α-syn, such as oligomeric α-syn (o-α-syn), are also found in CSF and blood (Ma et al. 2023; Constantinides et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zubelzu et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Meanwhile, the pathogenic β-sheet seed is the pathological conformation of α-syn and can be detected in serum (Okuzumi et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral studies and meta-analyses have confirmed that when compared to the control group, the total α-syn (t-α-syn) levels in the CSF are consistently lower in PD, MSA, PSP, CBS, and VP groups, with no significant differences among them (Zubelzu et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Constantinides et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; F\u0026oslash;rland et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kon\u0026iacute;čkov\u0026aacute; et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Aerts et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Therefore, t-α-syn levels cannot differentiate between PD and APS.\u003c/p\u003e \u003cp\u003eNotably, levels of o-α-syn in PD and other Parkinsonian syndromes reportedly do not differ significantly but are elevated compared to that of the control group (Eusebi et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUtilizing a Bead-based Luminex assay (with a sensitivity of 9 pg/mL), researchers measured the concentration of pS129 in the CSF of patients with PD, MSA, and PSP, revealing differences among them. To differentiate between the different diseases, receiver operating characteristic analysis following the discovery phase indicated that pS-129/t-α-syn was superior to pS-129 alone, with a specificity of \u0026ge;\u0026thinsp;80%. The sensitivity among the three different Parkinsonian disease groups were as follows: PD vs MSA, 40%; PD vs PSP, 72%; and MSA vs. PSP, 63% (Wang et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAggregates of α-syn, including propagative α-syn seeds, showed high diagnostic performance in differentiating between PD and MSA (Siderowf et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Painous et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Parnetti et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Goolla et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shahnawaz et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) Amplified seeds maintain disease-specific properties, allowing for the differentiation of samples from individuals with PD and MSA (Painous et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) Okuzumi et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) suggested that the rate of negative results of IP/RT-QuIC in patients with MSA was significantly higher than that in patients with PD. Additionally, their study also examined the distinctive morphological features of seeds in various diseases. The fibril morphology of products derived from IP/RT-QuIC of serum α-syn seeds in patients with synucleinopathies could differentiate PD, DLB, and MSA, allowing for further research in this area. A study found that the intensity of the signal in MSA was greater than that in PD when aggregation was performed in a specific buffered solution, indicating that α-syn seed aggregation from various diseases require different conditions for optimal detection (Martinez-Valbuena et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These results suggest that our follow-up study can focus on the structural diversity and disease specificity of α-syn seeds.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.2 DOPA decarboxylase (DDC)\u003c/h2\u003e \u003cp\u003eA primary pathological feature of PD is the degeneration of dopaminergic neurons in the substantia nigra (Stoker and Greenland \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). DDC is a diagnostic marker of dopaminergic dysfunction and can be detected in CS (Painous et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral studies have attempted to reveal the differences in DDC between PD and APS (Paslawski et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pereira et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). CSF levels of DDC may potentially be useful in differentiating among degenerative Parkinsonisms (PD vs. APS) (Paslawski et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2 MK\u003c/h2\u003e \u003cp\u003eMK is predominantly expressed during midgestation in embryogenesis, but its presence in normal adult brains is minimal. However, MK may recently play a role in various adult brain pathologies (Neumaier et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMK has demonstrated significant diagnostic potential as its levels were notably higher in patients with PD compared to those with APS (Paslawski et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Kallikrein 10\u003c/h2\u003e \u003cp\u003eKallikreins, which is a subgroup of serine proteases, play various physiological roles. Recent research has emphasized their involvement in carcinogenesis, highlighting several kallikreins as promising candidates for novel biomarkers in cancer and other diseases. This supports the potential utility of kallikreins in clinical diagnostics and therapeutic targeting (Wikipedia, nd).\u003c/p\u003e \u003cp\u003eKallikrein 10 has exhibited specific changes in APS compared to PD and controls; unfortunately, these changes were not elaborated (Paslawski et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Classic Alzheimer\u0026rsquo;s disease (AD) biomarkers\u003c/h2\u003e \u003cp\u003eAmyloid-beta-Aβ42, tau protein-τT, and phosphorylated tau protein-τP-181 are classical biomarkers of AD (Sung et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Notably, their significance in Parkinson\u0026rsquo;s syndrome has been re-recognized.\u003c/p\u003e \u003cp\u003eWhen compared to patients with PD, τT/Aβ42 ratio was increased in patients with MSA (Constantinides et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Constantinides et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). An elevated τT/Aβ42 ratio effectively differentiated MSA from PD, with an optimal cut-off value of 0.344 that yielded a sensitivity of 0.71 and specificity of 0.93 (Constantinides et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Exosomes\u003c/h2\u003e \u003cp\u003eExosomes from peripheral blood and CSF nerve cells have been used to distinguish PD and MSA (Taha and Bogoniewski \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Taha \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yan et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDutta et al.\u0026rsquo;s (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) study confirmed that α-syn concentrations in exosomes were markedly lower in the control group and significantly higher in the MSA group compared to the PD group. They created a ratio using α-syn concentrations of putative oligodendroglial exosomes and putative neuronal exosomes with good sensitivity in distinguishing PD and MSA. By incorporating this ratio along with the α-syn and total exosome concentrations, a multinomial logistic model successfully distinguished PD from MSA, with an area under the curve (AUC) of 0.902, sensitivity of 89.8%, and specificity of 86.0% after application to an independent validation cohort.\u003c/p\u003e \u003cp\u003eMeloni et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) investigated neural-derived extracellular vesicles (NDEVs) isolated from the blood. Analysis of NDEVs revealed a significant increase in o-α-syn levels in PD compared to APS (CBD and PSP). Additionally, levels of Tau aggregates in NDEVs were significantly elevated in APS compared to PD (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Receiver operating characteristic analysis showed that the concentration of NDEVs of both oligomeric o-α-syn and Tau aggregates exhibited an \u0026ldquo;excellent\u0026rdquo; power of classification that effectively distinguished PD from APS. For o-α-syn, the AUC was 0.817 (95% confidence interval (CI): 0.732\u0026ndash;0.885; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), sensitivity of 78.6%, and specificity of 77.5%. For Tau aggregates, the AUC was 0.856 (95% CI: 0.776\u0026ndash;0.915; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), sensitivity of 90.0%, and specificity of 75.7%.\u003c/p\u003e \u003cp\u003eTaha et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) was the first to measure pS129-α-syn levels in neuronal extracellular vesicles (nEVs) and oligodendroglial extracellular vesicles (oEVs). They reported that nEV pS129-α-syn concentrations were highest in healthy controls (HC) followed by PD and MSA, but the differences were not statistically significant. Conversely, oEV concentrations of pS129-α-syn were also highest in HC followed by PD and MSA and was significantly higher in both disease groups. Additionally, their study revealed that the oEV/nEV pS129-α-syn ratio increased in the order of HC\u0026thinsp;\u0026lt;\u0026thinsp;PD\u0026thinsp;\u0026lt;\u0026thinsp;MSA. Furthermore, they also measured total tau, pT181-tau (tau phosphorylated at Thr181) in nEVs and oEVs, and/or serum neurofilament light protein (NfL) levels. Due to the detection sensitivity, pT181-tau was detected in very few samples. Other results were similar to experiments involving plasma or CSF.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.6 NfL\u003c/h2\u003e \u003cp\u003eNfL in CSF (cNfL) and plasma (pNfL) is a marker for neuronal damage that may potentially be used to distinguish between clinically similar conditions, such as frontotemporal dementia from AD and PD from APS (Quadalti et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong Parkinsonian syndromes, the mean cNfL levels were higher in MSA, PSP, and CBS when compared with PD (Wikipedia, nd; Bridel et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Suffering from both PD and MSA","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 MicroRNAs\u003c/h2\u003e \u003cp\u003eMicroRNAs, which are small non-coding RNAs with 20\u0026ndash;22 nucleotides, play a critical role in several mechanisms underlying the pathogenesis of various neurodegenerative diseases, including PD. (Gu\u0026eacute;vremont et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) More importantly, they can be detected in the serum. (van Wamelen et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003cp\u003emiR-30c and miR-148b are specific to individuals with PD, whereas miR-24, miR-223, and miR-324-3p are present in patients with both PD and MSA when compared with healthy individuals (Villar-Men\u0026eacute;ndez et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"PDD and Other Dementia and Movement Disorders","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Fatty acid-binding protein 3, heart type (FABP3)\u003c/h2\u003e \u003cp\u003eFABP3 is a small cytosolic protein that plays a role in lipid transport (Chiasserini et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In the brain, FABP3 plays a regulatory role in the lipid composition of the membrane, suggesting a potential involvement in synapse formation and in the activity of cholinergic and glutamatergic neurons (Parnetti et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eElevated FABP3 levels have been detected in the serum of individuals diagnosed with DLB and PDD (Kawahata et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, FABP3 levels were higher in patients with DLB than in those with PDD. This suggests the potential of FABP3 as a distinctive biomarker for DLB (Kawahata and Fukunaga \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilar to DLB, FABP3 levels were higher in patients with AD than in those with PD and other neurological disorders (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, a combination of p-tau, FABP3, and α-syn successfully differentiated patients with AD from those with PDD, yielding an AUC of 0.96 (Chiasserini et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Tau\u003c/h2\u003e \u003cp\u003eDespite being a hallmark of AD, Tau proteins are also found in the brains of patients with PD and DLB (Shim et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA study aimed at distinguishing AD, DLB, and PD revealed that t-tau levels were higher in the DLB group than in the control and PD groups, but the differences were not statistically significant. Meanwhile, the t-tau/t-α-syn ratio had a better performance than standalone markers. For AD vs. DLB, the AUC increased from 0.66 for t-tau alone (70% sensitivity and 68% specificity) to 0.74 for the t-tau/t-α-syn ratio (55% sensitivity and 95% specificity) (F\u0026oslash;rland et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3 C-reactive protein (CRP)\u003c/h2\u003e \u003cp\u003eCRP concentrations in the CSF are higher in patients with PD and PDD than in patients with PD without dementia and HCs (Lindqvist et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, distinguishing between patients with PD without dementia and HCs based on CRP levels was not feasible.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Plasma homocysteine (Hcy)\u003c/h2\u003e \u003cp\u003eIn one study, Hcy levels were measured in patients with (PDD) and without dementia (PDwoD) as well as in HCs. Results showed that individuals with PDD demonstrated higher Hcy levels than PDwoD and HCs (Song et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Glial fibrillary acidic protein (GFAP)\u003c/h2\u003e \u003cp\u003eA study revealed that plasma GFAP levels in patients with PDD were higher than those in HCs, patients with PD with mild cognitive impairment (PD-MCI), and patients with PD with normal cognition (Bartl et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"PD and ET","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.1 α-syn in erythrocytes\u003c/h2\u003e \u003cp\u003eWhile pathological α-syn aggregations primarily localize in the central nervous system, peripheral α-syn concentrations, particularly in erythrocytes, are higher than in those in the CSF (Barbour et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) α-syn in erythrocytes are reportedly excellent biomarkers for diagnosing PD (Yu et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Yu et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTotal α-syn levels in erythrocytes are higher in patients with ET than in those with PD. Moreover, the proportion of aggregated α-syn levels to t-α-syn levels in erythrocytes is markedly lower in patients with ET than in those with PD and HCs. Receiver operating characteristic curve analysis showed that the ratios of aggregated α-syn to monomeric α-syn concentrations performed well in distinguishing patients with ET from those with PD and HCs, with an AUC of 0.892, sensitivity of 86.67%, and specificity of 97.96% for patients with ET vs. HCs. For ET vs. PD, the AUC was 0.817, with a sensitivity of 80.00% and specificity of 81.25% (Yu et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e5.2 NfL\u003c/h2\u003e \u003cp\u003eSome studies have compared serum NfL levels in PD and ET. (Hansson et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) Huang et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported that serum NfL concentrations in patients with PD (16.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 pg/mL) were significantly higher than that in patients with ET (12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 pg/mL) and HCs (11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 pg/mL) (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, effect sizes\u0026thinsp;=\u0026thinsp;1.47 and 1.60, respectively). When the cut-off was set at 13.65 pg/mL, the sensitivity and specificity of distinguishing between PD and ET were 76.7% and 84.1% respectively, with an AUC of 0.854.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2\u003c/b\u003e Concentrations of NfL in PD were considerably different from those in APS PDD and ET, with NfL concentrations higher in APS and PDD than in PD and the opposite in APS (vascular parkinsonism is not included). This may suggest a different pathogenesis of its disease at the molecular level. NfL: Neurofilament light protein, PD: Parkinson\u0026rsquo;s diaseae, APS: Atypical parkinson\u0026rsquo;s syndrome, PSP: progressive supranuclear palsy, CBS: corticobasal syndrome, MSA: multiple system atrophy, PDD: Parkinson's disease dementia, ET: Essential tremor.\u003c/p\u003e \u003c/div\u003e"},{"header":" PD and its Subtypes","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Early-onset PD (EOPD) and late-onset PD (LOPD)\u003c/h2\u003e \u003cp\u003eAn analysis of plasma microRNA levels in patients with EOPD, patients with LOPD, and HCs revealed a statistically significant difference between patients with PD and HCs. Upregulation of miR-29b-3p and downregulation of miR-297 and miR-4462 in EOPD may be associated with EOPD alone (Arshad et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Tremor-dominant (TD) PD vs. non-tremor-dominant (NTD) PD\u003c/h2\u003e \u003cp\u003ePPD can be classified into TD PD and NTD PD. Individuals with NTD PD have lower levels of serum uric acid (UA) and a significantly lower serum UA/creatinine (Cr) ratio (UA/Cr) than those with TD PD (van Wamelen et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e6.3 PD versus PD-MCI\u003c/h2\u003e \u003cp\u003eIndividuals with PD-MCI have higher mean levels of total cholesterol (TC), triglycerides (TG), and apolipoprotein A1 (apo A1) than subgroups with normal cognition. Therefore, TC, TG, and apo A1 may serve as valuable biomarkers for PD-MCI (Deng et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Conversely, serum levels of high-density lipoprotein cholesterol were elevated in patients with PD (Dong et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e6.4 PD with hallucinations\u003c/h2\u003e \u003cp\u003eLevels of 8-OHdG are reportedly higher in PD with hallucinations, while no such elevation was observed in cases associated with dementia or other clinical features (Hirayama et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Faria et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e6.5 PD with rapid eye movement sleep behavior disorder (RBD)\u003c/h2\u003e \u003cp\u003ePlasma GFAP levels were notably elevated in patients with PD exhibiting RBD compared to those without RBD (Teng et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Emerging Technologies","content":"\u003cp\u003eThe importance of novel technologies in identifying biomarkers has been emphasized as these advancements provided increased discriminatory capabilities (Parnetti et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Highly accurate methods are changing previously known but non-significant findings.\u003c/p\u003e \u003cp\u003eThe measurement techniques, represented by α-syn seed amplification (SAA) that includes real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA), have shown high specificity (almost 100%) and sensitivity (\u0026gt;\u0026thinsp;90%) (Shahnawaz et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Fairfoul et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). SAA has been employed to identify misfolded α-syn aggregates in the CSF and peripheral tissues (Ma et al. 2023). RT-QuIC and PMCA can distinguish PD from other NDDs according to variations in α-syn aggregates. The reliability in detection and the adaptability of RT-QuIC across different tissues and biological fluids have allowed this technique to become the benchmark when investigating the aggregation of α-syn in humans (Goolla et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe HANdai Amyloid Burst Inducer technique has been suggested as a viable alternative to the PMCA and RT-QuIC for assessing pro-aggregating proteins in biofluids due to its faster assay speed than PMCA and RT-QuIC (Umemoto et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It is currently being studied as a technique for measuring pro-aggregating forms of α-syn.\u003c/p\u003e \u003cp\u003eCombining these technologies, scientists have developed several types of SAA, including immunoprecipitation-based RT-QuIC (IP/RT-QuIC), which enables the detection of pathogenic α-syn seeds in the serum of individuals with synucleinopathy (Okuzumi et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, researchers found that different sources of α-syn seeds have different optimal signal display conditions, making it possible to develop specific SAAs for a single disease such as MSA (Martinez-Valbuena et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the total α-synuclein assay, a modified Luminex assay, namely the Bead-based Luminex assays, was developed. Its sensitivity is approximately 9 pg/mL, providing a highly precise method for measuring pS129 (Wang et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Detection systems supported by the Simoa Bead technology can accurately quantify low-concentration proteins and peptides at the level of fM with excellent reproducibility. Kawahata, Sekimori, Oizumi, Takeda, and Fukunaga (Kawahata et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) used this technique to quantify FABP levels. Currently, Meso Scale Discovery electrochemiluminescence technology has been gradually used to detect molecular markers of neurodegenerative diseases and has shown a higher sensitivity (Zhao et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eNovel ELISA assays have been developed by Majbour et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Their method expanded the detection limit of α-syn to 50 pg/mL, which is 20-fold lower than that detected in human CSF. Meanwhile, the detection limits of pS129 and recombinant o-α-syn were expanded to 20 pg/mL and 10 pg/mL, respectively. To exceed these limits, technologies, such as novel photochemical, electrochemical, and crystal biosensors should be utilized (Jabbari et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom the perspective of technological evolution, the development of targeted detection methods is an inevitable requirement for the differential diagnosis of PD.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis review focused on the blood and CSF markers in PD as they are easily acquired, non-invasive, and in proximity to the brain in contrast to brain tissue biopsy or urine tests (Parnetti et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Thus, facilitating the integration of clinical and scientific research for these biomarkers is essential.\u003c/p\u003e \u003cp\u003eThe differences between t-α-syn, o-α-syn, pS-129, aggregates of α-syn, Kallikrein 10, τT/Aβ42 ratio, α-syn concentrations in exosomes, NDEV concentrations of both o-α-syn and Tau aggregates, the oEV/nEV pS129-α-syn ratio, and cNfL levels between PD and APS have been revealed. Future diagnostic studies on PD should focus on the differentially expressed molecules in this disease. miR-30c, miR-148b, miR-24, miR-223, and miR-324-3p exhibit specificity in identifying patient with PD with MSA. FABP3, the t-tau/t-a-syn ratio, total α-syn levels in erythrocytes, and serum NfL concentrations may distinguish PDD from other dementias and movement disorders. Total α-syn levels in erythrocytes and serum NfL levels have distinctly different concentrations in ET compared to PD. CRP, Hcy, GFAP, microRNA, serum UA, TC, TG, A1, and 8-OHdG levels may also be potentially used to support the differentiation between the different PD subtypes (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eCurrently, diagnosing PD primarily depends on clinical symptoms, and the relationship between symptoms and prognosis has been partially established (Armstrong and Okun \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the differences between biomarkers among different neurodegenerative diseases should make us consider the occurrence and development of this disease at a more specific level. Differential diagnostic biomarkers of PD in the blood and CSF represent its unique onset and evolution, which should further research on its etiology and pathogenesis (Kelly et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eClinical pathological studies and clinical trials should accurately classify study participants (Lin et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The emergence of biomarkers makes it feasible to accurately identify patients and allows for a more reliable reference for distinguishing PD from other diseases (Tolosa et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This is a practical significance of PD\u0026rsquo;s differential diagnostic biomarkers.\u003c/p\u003e \u003cp\u003eSeveral biomarkers in PD and related diseases have obvious differences, but only a few have excellent performance by relying on high-precision testing methods. The combination of multiple biomarkers or clinical signs can increase the ability to discriminate between diseases (Quadalti et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dutta et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Meloni et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Taha et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kawahata et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Developing a combined detection method based on multiple biomarkers may not be an urgent need for PD, which is an incurable disease; however, if patients can be accurately classified at disease onset, improving the efficiency of future scientific research and follow-up research in a large population will be beneficial.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The manuscript has been carefully reviewed by an experienced editor whose first language is English and who specializes in editing papers written by scientists whose native language is not English.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e:\u0026nbsp;The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e Author LH was employed by ICON Plc. The remaining authors have no relevant financial or nonfinancial interests to disclose..\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Study design was performed by YW and writing of the original draft and visualization was performed by JM. Data collection was performed by ZT, YqW, JZ, ZW and LH. Data acquisition and critical revision of the manuscript was performed by SL. Project administration was carried out by YW.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e No new data were created.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eEthics Approval:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eConsent to Participate:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003eAll authors have read and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAerts MB, Esselink RA, Abdo WF, Bloem BR, Verbeek MM (2012) CSF \u0026alpha;-synuclein does not differentiate between parkinsonian disorders. Neurobiol Aging 33:430.e1-430.e3. https://doi.org/10.1016/j.neurobiolaging.2010.12.001\u003c/li\u003e\n\u003cli\u003eArmstrong MJ, Okun MS (2020) Diagnosis and treatment of Parkinson disease: a review. JAMA 323:548-560. https://doi.org/10.1001/jama.2019.22360\u003c/li\u003e\n\u003cli\u003eArshad AR, Sulaiman SA, Saperi AA, Jamal R, Mohamed Ibrahim N, Abdul Murad NA (2017) MicroRNAs and target genes as biomarkers for the diagnosis of early onset of Parkinson disease. Front Mol Neurosci 10:352. https://doi.org/10.3389/fnmol.2017.00352\u003c/li\u003e\n\u003cli\u003eBarbour R, Kling K, Anderson JP, Banducci K, Cole T, Diep L, Fox M, Goldstein JM, Soriano F, Seubert P, Chilcote TJ (2008) Red blood cells are the major source of alpha-synuclein in blood. Neurodegener Dis 5:55-59. https://doi.org/10.1159/000112832\u003c/li\u003e\n\u003cli\u003eBartl M, Dakna M, Schade S, Otte B, Wicke T, Lang E, Starke M, Ebentheuer J, Weber S, Toischer K, Schnelle M, Sixel-D\u0026ouml;ring F, Trenkwalder C, Mollenhauer B (2023) Blood markers of inflammation, neurodegeneration, and cardiovascular risk in early Parkinson\u0026rsquo;s disease. Mov Disord 38:68-81. https://doi.org/10.1002/mds.29257\u003c/li\u003e\n\u003cli\u003eBridel C, van Wieringen WN, Zetterberg H, Tijms BM, Teunissen CE, and the NFL Group, Alvarez-Cerme\u0026ntilde;o JC, Andreasson U, Axelsson M, B\u0026auml;ckstr\u0026ouml;m DC, Bartos A, Bjerke M, Blennow K, Boxer A, Brundin L, Burman J, Christensen T, Fialov\u0026aacute; L, Forsgren L, Frederiksen JL, Gissl\u0026eacute;n M, Gray E, Gunnarsson M, Hall S, Hansson O, Herbert MK, Jakobsson J, Jessen-Krut J, Janelidze S, Johannsson G, Jonsson M, Kappos L, Khademi M, Khalil M, Kuhle J, Land\u0026eacute;n M, Leinonen V, Logroscino G, Lu CH, Lycke J, Magdalinou NK, Malaspina A, Mattsson N, Meeter LH, Mehta SR, Modvig S, Olsson T, Paterson RW, P\u0026eacute;rez-Santiago J, Piehl F, Pijnenburg YAL, Pyykk\u0026ouml; OT, Ragnarsson O, Rojas JC, Romme Christensen J, Sandberg L, Scherling CS, Schott JM, Sellebjerg FT, Simone IL, Skillb\u0026auml;ck T, Stilund M, Sundstr\u0026ouml;m P, Svenningsson A, Tortelli R, Tortorella C, Trentini A, Troiano M, Turner MR, van Swieten JC, V\u0026aring;gberg M, Verbeek MM, Villar LM, Visser PJ, Wallin A, Weiss A, Wikkels\u0026oslash; C, Wild EJ (2019) Diagnostic value of cerebrospinal fluid neurofilament light protein in neurology: a systematic review and meta-analysis. JAMA Neurol 76:1035-1048. https://doi.org/10.1001/jamaneurol.2019.1534\u003c/li\u003e\n\u003cli\u003eChen R, Gu X, Wang X (2022) \u0026alpha;-synuclein in Parkinson\u0026rsquo;s disease and advances in detection. Clin Chim Acta 529:76-86. https://doi.org/10.1016/j.cca.2022.02.006\u003c/li\u003e\n\u003cli\u003eChen WR, Chen JC, Chang SY, Chao CT, Wu YR, Chen CM, Chou C (2022) Phosphorylated \u0026alpha;-synuclein in diluted human serum as a biomarker for Parkinson\u0026rsquo;s disease. Biomed J 45:914-922. https://doi.org/10.1016/j.bj.2021.12.010\u003c/li\u003e\n\u003cli\u003eChiasserini D, Biscetti L, Eusebi P, Salvadori N, Frattini G, Simoni S, De Roeck N, Tambasco N, Stoops E, Vanderstichele H, Engelborghs S, Mollenhauer B, Calabresi P, Parnetti L (2017) Differential role of CSF fatty acid binding protein 3, \u0026alpha;-synuclein, and Alzheimer\u0026rsquo;s disease core biomarkers in Lewy body disorders and Alzheimer\u0026rsquo;s dementia. Alzheimers Res Ther 9:52. https://doi.org/10.1186/s13195-017-0276-4\u003c/li\u003e\n\u003cli\u003eConstantinides VC, Majbour NK, Paraskevas GP, Abdi I, Safieh-Garabedian B, Stefanis L, El-Agnaf OM, Kapaki E (2021) Cerebrospinal fluid alpha-synuclein species in cognitive and movements disorders. Brain Sci 11:119. https://doi.org/10.3390/brainsci11010119\u003c/li\u003e\n\u003cli\u003eConstantinides VC, Paraskevas GP, Emmanouilidou E, Petropoulou O, Bougea A, Vekrellis K, Evdokimidis I, Stamboulis E, Kapaki E (2017) CSF biomarkers beta-amyloid, tau proteins and a-synuclein in the differential diagnosis of Parkinson-plus syndromes. J Neurol Sci 382:91-95. https://doi.org/10.1016/j.jns.2017.09.039\u003c/li\u003e\n\u003cli\u003eDeng X, Saffari SE, Ng SYE, Chia N, Tan JY, Choi X, Heng DL, Xu Z, Tay KY, Au WL, Liu N, Ng A, Tan EK, Tan LCS (2022) Blood lipid biomarkers in early Parkinson\u0026rsquo;s disease and Parkinson\u0026rsquo;s disease with mild cognitive impairment. J Parkinsons Dis 12:1937-1943. https://doi.org/10.3233/JPD-213135\u003c/li\u003e\n\u003cli\u003eDong MX, Wei YD, Hu L (2021) The disturbance of lipid metabolism is correlated with neuropsychiatric symptoms in patients with Parkinson\u0026rsquo;s disease. Chem Phys Lipids 239:105112. https://doi.org/10.1016/j.chemphyslip.2021.105112\u003c/li\u003e\n\u003cli\u003eDutta S, Hornung S, Kruayatidee A, Maina KN, Del Rosario I, Paul KC, Wong DY, Duarte Folle A, Markovic D, Palma JA, Serrano GE, Adler CH, Perlman SL, Poon WW, Kang UJ, Alcalay RN, Sklerov M, Gylys KH, Kaufmann H, Fogel BL, Bronstein JM, Ritz B, Bitan G (2021) \u0026alpha;-synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson\u0026rsquo;s disease from multiple system atrophy. Acta Neuropathol 142:495-511. https://doi.org/10.1007/s00401-021-02324-0\u003c/li\u003e\n\u003cli\u003eDutta, S.; Hornung, S.; Kruayatidee, A.; Maina, K.N.; Del Rosario, I.; Paul, K.C.; Wong, D.Y.; Duarte Folle, A.; Markovic, D.; Palma, J.A.; Serrano, G.E.; Adler, C.H.; Perlman, S.L.; Poon, W.W.; Kang, U.J.; Alcalay, R.N.; Sklerov, M.; Gylys, K.H.; Kaufmann, H.; Fogel, B.L.; Bronstein, J.M.; Ritz, B.; Bitan, G (2021) \u0026alpha;-synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson\u0026rsquo;s disease from multiple system atrophy. Acta Neuropathol 142:495-511. https://doi.org/10.1007/s00401-021-02324-0\u003c/li\u003e\n\u003cli\u003eEstaun-Panzano J, Arotcarena ML, Bezard E (2023) Monitoring \u0026alpha;-synuclein aggregation. Neurobiol Dis 176:105966. https://doi.org/10.1016/j.nbd.2022.105966\u003c/li\u003e\n\u003cli\u003eEusebi P, Giannandrea D, Biscetti L, Abraha I, Chiasserini D, Orso M, Calabresi P, Parnetti L (2017) Diagnostic utility of cerebrospinal fluid \u0026alpha;-synuclein in Parkinson\u0026rsquo;s disease: a systematic review and meta-analysis. Mov Disord 32:1389-1400. https://doi.org/10.1002/mds.27110\u003c/li\u003e\n\u003cli\u003eFairfoul G, McGuire LI, Pal S, Ironside JW, Neumann J, Christie S, Joachim C, Esiri M, Evetts SG, Rolinski M, Baig F, Ruffmann C, Wade-Martins R, Hu MTM, Parkkinen L, Green AJE (2016) Alpha-synuclein RT-QuIC in the CSF of patients with alpha-synucleinopathies. Ann Clin Transl Neurol 3:812-818. https://doi.org/10.1002/acn3.338\u003c/li\u003e\n\u003cli\u003eFaria AM, Peixoto EBMI, Adamo CB, Flacker A, Longo E, Mazon T (2019) Controlling parameters and characteristics of electrochemical biosensors for enhanced detection of 8-hydroxy-2\u0026prime;-deoxyguanosine. Sci Rep 9:7411. https://doi.org/10.1038/s41598-019-43680-y\u003c/li\u003e\n\u003cli\u003eF\u0026oslash;rland MG, Tysnes OB, Aarsland D, Maple-Gr\u0026oslash;dem J, Pedersen KF, Alves G, Lange J (2020) The value of cerebrospinal fluid \u0026alpha;-synuclein and the tau/\u0026alpha;-synuclein ratio for diagnosis of neurodegenerative disorders with Lewy pathology. Eur J Neurol 27:43-50. https://doi.org/10.1111/ene.14032\u003c/li\u003e\n\u003cli\u003eGoolla M, Cheshire WP, Ross OA, Kondru N (2023) Diagnosing multiple system atrophy: current clinical guidance and emerging molecular biomarkers. Front Neurol 14:1210220. https://doi.org/10.3389/fneur.2023.1210220\u003c/li\u003e\n\u003cli\u003eGu\u0026eacute;vremont D, Roy J, Cutfield NJ, Williams JM (2023) MicroRNAs in Parkinson\u0026rsquo;s disease: a systematic review and diagnostic accuracy meta-analysis. Sci Rep 13:16272. https://doi.org/10.1038/s41598-023-43096-9\u003c/li\u003e\n\u003cli\u003eHansson O, Janelidze S, Hall S, Magdalinou N, Lees AJ, Andreasson U, Norgren N, Linder J, Forsgren L, Constantinescu R, Zetterberg H, Blennow K, Swedish BioFINDER study (2017) Blood-based NfL: A biomarker for differential diagnosis of parkinsonian disorder. Neurology 88:930-937. https://doi.org/10.1212/WNL.0000000000003680\u003c/li\u003e\n\u003cli\u003eHarris E (2023) Identifying lewy body disease before symptoms. JAMA 330:686. https://doi.org/10.1001/jama.2023.13621\u003c/li\u003e\n\u003cli\u003eHirayama M, Ito M, Minato T, Yoritaka A, LeBaron TW, Ohno K (2018) Inhalation of hydrogen gas elevates urinary 8-hydroxy-2\u0026prime;-deoxyguanine in Parkinson\u0026rsquo;s disease. Med Gas Res 8:144-149. https://doi.org/10.4103/2045-9912.248264\u003c/li\u003e\n\u003cli\u003eHirschberg Y, Valle-Tamayo N, Dols-Icardo O, Engelborghs S, Buelens B, Vandenbroucke RE, Vermeiren Y, Boonen K, Mertens I (2023) Proteomic comparison between non-purified cerebrospinal fluid and cerebrospinal fluid-derived extracellular vesicles from patients with Alzheimer\u0026rsquo;s, Parkinson\u0026rsquo;s and Lewy body dementia. J Extracell Vesicles 12:e12383. https://doi.org/10.1002/jev2.12383\u003c/li\u003e\n\u003cli\u003eHolm H, Gundersen V, Dietrichs E (2023) Vascular parkinsonism. Tidsskr Nor Laegeforen 143. https://doi.org/10.4045/tidsskr.22.0539\u003c/li\u003e\n\u003cli\u003eHuang Y, Huang C, Zhang Q, Shen T, Sun J (2022) Serum NFL discriminates Parkinson disease from essential tremor and reflect motor and cognition severity. BMC Neurol 22:39. https://doi.org/10.1186/s12883-022-02558-9\u003c/li\u003e\n\u003cli\u003eJabbari E, Holland N, Chelban V, Jones PS, Lamb R, Rawlinson C, Guo T, Costantini AA, Tan MMX, Heslegrave AJ, Roncaroli F, Klein JC, Ansorge O, Allinson KSJ, Jaunmuktane Z, Holton JL, Revesz T, Warner TT, Lees AJ, Zetterberg H, Russell LL, Bocchetta M, Rohrer JD, Williams NM, Grosset DG, Burn DJ, Pavese N, Gerhard A, Kobylecki C, Leigh PN, Church A, Hu MTM, Woodside J, Houlden H, Rowe JB, Morris HR (2020) Diagnosis across the spectrum of progressive supranuclear palsy and corticobasal syndrome. JAMA Neurol 77:377-387. https://doi.org/10.1001/jamaneurol.2019.4347\u003c/li\u003e\n\u003cli\u003eKawahata I, Fukunaga K (2023) Pathogenic impact of fatty acid-binding proteins in Parkinson\u0026rsquo;s disease-potential biomarkers and therapeutic targets. Int J Mol Sci 24:17037. https://doi.org/10.3390/ijms242317037\u003c/li\u003e\n\u003cli\u003eKawahata I, Sekimori T, Oizumi H, Takeda A, Fukunaga K (2023) Using fatty acid-binding proteins as potential biomarkers to discriminate between Parkinson\u0026rsquo;s disease and dementia with Lewy bodies: exploration of a novel technique. Int J Mol Sci 24:13267. https://doi.org/10.3390/ijms241713267\u003c/li\u003e\n\u003cli\u003eKelly J, Moyeed R, Carroll C, Luo S, Li X (2023) Blood biomarker-based classification study for neurodegenerative diseases. Sci Rep 13:17191. https://doi.org/10.1038/s41598-023-43956-4\u003c/li\u003e\n\u003cli\u003eKon\u0026iacute;čkov\u0026aacute; D, Men\u0026scaron;\u0026iacute;kov\u0026aacute; K, Kl\u0026iacute;čov\u0026aacute; K, Chud\u0026aacute;čkov\u0026aacute; M, Kaiserov\u0026aacute; M, Přikrylov\u0026aacute; H, Otruba P, Nevrl\u0026yacute; M, Hlu\u0026scaron;t\u0026iacute;k P, H\u0026eacute;nykov\u0026aacute; E, Kaleta M, Friedeck\u0026yacute; D, Matěj R, Strnad M, Nov\u0026aacute;k O, Pl\u0026iacute;halov\u0026aacute; L, Rosales R, Colosimo C, Kaňovsk\u0026yacute; P (2023) Cerebrospinal fluid and blood serum biomarkers in neurodegenerative proteinopathies: a prospective, open, cross-correlation study. J Neurochem 167:168-182. https://doi.org/10.1111/jnc.15944\u003c/li\u003e\n\u003cli\u003eLi J, Gu C, Zhu M, Li D, Chen L, Zhu X (2020) Correlations between blood lipid, serum cystatin C, and homocysteine levels in patients with Parkinson\u0026rsquo;s disease. Psychogeriatrics 20:180-188. https://doi.org/10.1111/psyg.12483\u003c/li\u003e\n\u003cli\u003eLin CH, Chiu SI, Chen TF, Jang JR, Chiu MJ (2020) Classifications of neurodegenerative disorders using a multiplex blood biomarkers-based machine learning model. Int J Mol Sci 21:6914. https://doi.org/10.3390/ijms21186914\u003c/li\u003e\n\u003cli\u003eLindqvist D, Hall S, Surova Y, Nielsen HM, Janelidze S, Brundin L, Hansson O (2013) Cerebrospinal fluid inflammatory markers in Parkinson\u0026rsquo;s disease\u0026mdash;associations with depression, fatigue, and cognitive impairment. Brain Behav Immun 33:183-189. https://doi.org/10.1016/j.bbi.2013.07.007\u003c/li\u003e\n\u003cli\u003eMa Z-L, Wang Z-L, Zhang F-Y, Liu H-X, Mao L-H, Yuan L (2024) Biomarkers of Parkinson\u0026rsquo;s disease: from basic research to clinical practice. Aging Dis 15:1813-1830. https://doi.org/10.14336/AD.2023.1005\u003c/li\u003e\n\u003cli\u003eMajbour NK, Vaikath NN, van Dijk KD, Ardah MT, Varghese S, Vesterager LB, Montezinho LP, Poole S, Safieh-Garabedian B, Tokuda T, Teunissen CE, Berendse HW, van de Berg WDJ, El-Agnaf OMA (2016) Oligomeric and phosphorylated alpha-synuclein as potential CSF biomarkers for Parkinson\u0026rsquo;s disease. Mol Neurodegener 11:7. https://doi.org/10.1186/s13024-016-0072-9\u003c/li\u003e\n\u003cli\u003eMartinez-Valbuena I, Visanji NP, Kim A, Lau HHC, So RWL, Alshimemeri S, Gao A, Seidman MA, Luquin MR, Watts JC, Lang AE, Kovacs GG (2022) Alpha-synuclein seeding shows a wide heterogeneity in multiple system atrophy. Transl Neurodegener 11:7. https://doi.org/10.1186/s40035-022-00283-4\u003c/li\u003e\n\u003cli\u003eMeloni M, Agliardi C, Guerini FR, Zanzottera M, Bolognesi E, Picciolini S, Marano M, Magliozzi A, Di Fonzo A, Arighi A, Fenoglio C, Franco G, Arienti F, Saibene FL, Navarro J, Clerici M (2023) Oligomeric \u0026alpha;-synuclein and tau aggregates in NDEVs differentiate Parkinson\u0026rsquo;s disease from atypical parkinsonisms. Neurobiol Dis 176:105947. https://doi.org/10.1016/j.nbd.2022.105947\u003c/li\u003e\n\u003cli\u003eNeumaier EE, Rothhammer V, Linnerbauer M (2023) The role of midkine in health and disease. Front Immunol 14:1310094. https://doi.org/10.3389/fimmu.2023.1310094\u003c/li\u003e\n\u003cli\u003eOkuzumi A, Hatano T, Matsumoto G, Nojiri S, Ueno SI, Imamichi-Tatano Y, Kimura H, Kakuta S, Kondo A, Fukuhara T, Li Y, Funayama M, Saiki S, Taniguchi D, Tsunemi T, McIntyre D, G\u0026eacute;rardy JJ, Mittelbronn M, Kruger R, Uchiyama Y, Nukina N, Hattori N (2023) Propagative \u0026alpha;-synuclein seeds as serum biomarkers for synucleinopathies. Nat Med 29:1448-1455. https://doi.org/10.1038/s41591-023-02358-9\u003c/li\u003e\n\u003cli\u003ePainous C, Fern\u0026aacute;ndez M, P\u0026eacute;rez J, de Mena L, C\u0026aacute;mara A, Compta Y (2024) Fluid and tissue biomarkers in Parkinson\u0026rsquo;s disease: immunodetection or seed amplification? Central or peripheral? Parkinsonism Relat Disord 121:105968. https://doi.org/10.1016/j.parkreldis.2023.105968\u003c/li\u003e\n\u003cli\u003eParnetti L, Gaetani L, Eusebi P, Paciotti S, Hansson O, El-Agnaf O, Mollenhauer B, Blennow K, Calabresi P (2019) CSF and blood biomarkers for Parkinson\u0026rsquo;s disease. Lancet Neurol 18:573-586. https://doi.org/10.1016/S1474-4422(19)30024-9\u003c/li\u003e\n\u003cli\u003ePaslawski W, Khosousi S, Hertz E, Markaki I, Boxer A, Svenningsson P (2023) Large-scale proximity extension assay reveals CSF midkine and DOPA decarboxylase as supportive diagnostic biomarkers for Parkinson\u0026rsquo;s disease. Transl Neurodegener 12:42. https://doi.org/10.1186/s40035-023-00374-w\u003c/li\u003e\n\u003cli\u003ePereira JB, Kumar A, Hall S, Palmqvist S, Stomrud E, Bali D, Parchi P, Mattsson-Carlgren N, Janelidze S, Hansson O (2023) DOPA decarboxylase is an emerging biomarker for Parkinsonian disorders including preclinical lewy body disease. Nat Aging 3:1201-1209. https://doi.org/10.1038/s43587-023-00478-y\u003c/li\u003e\n\u003cli\u003eQuadalti C, Calandra-Buonaura G, Baiardi S, Mastrangelo A, Rossi M, Zenesini C, Giannini G, Candelise N, Sambati L, Polischi B, Plazzi G, Capellari S, Cortelli P, Parchi P (2021) Neurofilament light chain and alpha-synuclein RT-QuIC as differential diagnostic biomarkers in parkinsonisms and related syndromes. NPJ Parkinsons Dis 7:93. https://doi.org/10.1038/s41531-021-00232-4\u003c/li\u003e\n\u003cli\u003eShahnawaz M, Mukherjee A, Pritzkow S, Mendez N, Rabadia P, Liu X, Hu B, Schmeichel A, Singer W, Wu G, Tsai AL, Shirani H, Nilsson KPR, Low PA, Soto C (2020) Discriminating \u0026alpha;-synuclein strains in Parkinson\u0026rsquo;s disease and multiple system atrophy. Nature 578:273-277. https://doi.org/10.1038/s41586-020-1984-7\u003c/li\u003e\n\u003cli\u003eShahnawaz M, Tokuda T, Waragai M, Mendez N, Ishii R, Trenkwalder C, Mollenhauer B, Soto C (2017) Development of a biochemical diagnosis of Parkinson disease by detection of alpha-synuclein misfolded aggregates in cerebrospinal fluid. JAMA Neurol 74:163-172. https://doi.org/10.1001/jamaneurol.2016.4547\u003c/li\u003e\n\u003cli\u003eShim KH, Kang MJ, Youn YC, An SSA, Kim S (2022) Alpha-synuclein: a pathological factor with Abeta and tau and biomarker in Alzheimer\u0026rsquo;s disease. Alzheimers Res Ther 14:201. https://doi.org/10.1186/s13195-022-01150-0\u003c/li\u003e\n\u003cli\u003eSiderowf A, Concha-Marambio L, Lafontant DE, Farris CM, Ma Y, Urenia PA, Nguyen H, Alcalay RN, Chahine LM, Foroud T, Galasko D, Kieburtz K, Merchant K, Mollenhauer B, Poston KL, Seibyl J, Simuni T, Tanner CM, Weintraub D, Videnovic A, Choi SH, Kurth R, Caspell-Garcia C, Coffey CS, Frasier M, Oliveira LMA, Hutten SJ, Sherer T, Marek K, Soto C, Parkinson\u0026apos;s Progression Markers Initiative (2023) Assessment of heterogeneity among participants in the Parkinson\u0026rsquo;s Progression Markers Initiative cohort using \u0026alpha;-synuclein seed amplification: a cross-sectional study. Lancet Neurol 22:407-417. https://doi.org/10.1016/S1474-4422(23)00109-6\u003c/li\u003e\n\u003cli\u003eSong IU, Kim JS, Park IS, Kim YD, Cho HJ, Chung SW, Lee KS (2013) Clinical significance of homocysteine (hcy) on dementia in Parkinson\u0026rsquo;s disease (PD). Arch Gerontol Geriatr 57:288-291. https://doi.org/10.1016/j.archger.2013.04.015\u003c/li\u003e\n\u003cli\u003eStoker TB, Greenland JC (2018) Parkinson\u0026rsquo;s disease: pathogenesis and clinical aspects. Codon Publications, Brisbane (AU)\u003c/li\u003e\n\u003cli\u003eSung YJ, Yang C, Norton J, Johnson M, Fagan A, Bateman RJ, Perrin RJ, Morris JC, Farlow MR, Chhatwal JP, Schofield PR, Chui H, Wang F, Novotny B, Eteleeb A, Karch C, Schindler SE, Rhinn H, Johnson ECB, Oh HSH, Rutledge JE, Dammer EB, Seyfried NT, Wyss-Coray T, Harari O, Cruchaga C (2023) Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer\u0026rsquo;s disease. Sci Transl Med 15:eabq5923. https://doi.org/10.1126/scitranslmed.abq5923\u003c/li\u003e\n\u003cli\u003eTaha HB (2023) Rethinking the reliability and accuracy of biomarkers in CNS-originating EVs for Parkinson\u0026rsquo;s disease and multiple system atrophy. Front Neurol 14:1192115. https://doi.org/10.3389/fneur.2023.1192115\u003c/li\u003e\n\u003cli\u003eTaha HB, Bogoniewski A (2024) Analysis of biomarkers in speculative CNS-enriched extracellular vesicles for parkinsonian disorders: a comprehensive systematic review and diagnostic meta-analysis. J Neurol 271:1680-1706. https://doi.org/10.1007/s00415-023-12093-3\u003c/li\u003e\n\u003cli\u003eTaha HB, Hornung S, Dutta S, Fenwick L, Lahgui O, Howe K, Elabed N, Del Rosario I, Wong DY, Duarte Folle A, Markovic D, Palma JA, Kang UJ, Alcalay RN, Sklerov M, Kaufmann H, Fogel BL, Bronstein JM, Ritz B, Bitan G (2023) Toward a biomarker panel measured in CNS-originating extracellular vesicles for improved differential diagnosis of Parkinson\u0026rsquo;s disease and multiple system atrophy. Transl Neurodegener 12:14. https://doi.org/10.1186/s40035-023-00346-0\u003c/li\u003e\n\u003cli\u003eTeng X, Mao S, Wu H, Shao Q, Zu J, Zhang W, Zhou S, Zhang T, Zhu J, Cui G, Xu C (2023) The relationship between serum neurofilament light chain and glial fibrillary acidic protein with the REM sleep behavior disorder subtype of Parkinson\u0026rsquo;s disease. J Neurochem 165:268-276. https://doi.org/10.1111/jnc.15780\u003c/li\u003e\n\u003cli\u003eTofaris GK (2022) Initiation and progression of \u0026alpha;-synuclein pathology in Parkinson\u0026rsquo;s disease. Cell Mol Life Sci 79:210. https://doi.org/10.1007/s00018-022-04240-2\u003c/li\u003e\n\u003cli\u003eTolosa E, Garrido A, Scholz SW, Poewe W (2021) Challenges in the diagnosis of Parkinson\u0026rsquo;s disease. Lancet Neurol 20:385-397. https://doi.org/10.1016/S1474-4422(21)00030-2\u003c/li\u003e\n\u003cli\u003eTsao H-H, Huang C-G, Wu Y-R (2022) Detection and assessment of alpha-synuclein in Parkinson disease. Neurochem Int 158:105358. https://doi.org/10.1016/j.neuint.2022.105358\u003c/li\u003e\n\u003cli\u003eUmemoto A, Yagi H, So M, Goto Y (2014) High-throughput analysis of ultrasonication-forced amyloid fibrillation reveals the mechanism underlying the large fluctuation in the lag time. J Biol Chem 289:27290-27299. https://doi.org/10.1074/jbc.M114.569814\u003c/li\u003e\n\u003cli\u003evan Wamelen DJ, Taddei RN, Calvano A, Titova N, Leta V, Shtuchniy I, Jenner P, Martinez-Martin P, Katunina E, Chaudhuri KR (2020) Serum uric acid levels and non-motor symptoms in Parkinson\u0026rsquo;s disease. J Parkinsons Dis 10:1003-1010. https://doi.org/10.3233/JPD-201988\u003c/li\u003e\n\u003cli\u003eVillar-Men\u0026eacute;ndez I, Porta S, Buira SP, Pereira-Veiga T, D\u0026iacute;az-S\u0026aacute;nchez S, Albasanz JL, Ferrer I, Mart\u0026iacute;n M, Barrachina M (2014) Increased striatal adenosine A2a receptor levels is an early event in Parkinson\u0026rsquo;s disease-related pathology and it is potentially regulated by miR-34b. Neurobiol Dis 69:206-214. https://doi.org/10.1016/j.nbd.2014.05.030\u003c/li\u003e\n\u003cli\u003eWang Y, Shi M, Chung KA, Zabetian CP, Leverenz JB, Berg D, Srulijes K, Trojanowski JQ, Lee VMY, Siderowf AD, Hurtig H, Litvan I, Schiess MC, Peskind ER, Masuda M, Hasegawa M, Lin X, Pan C, Galasko D, Goldstein DS, Jensen PH, Yang H, Cain KC, Zhang J (2012) Phosphorylated \u0026alpha;-synuclein in Parkinson\u0026rsquo;s disease. Sci Transl Med 4:121ra20. https://doi.org/10.1126/scitranslmed.3002566\u003c/li\u003e\n\u003cli\u003eWikipedia KLK10. Wikipedia. Wikipedia. Retrieved from https://en.wikipedia.org/wiki/KLK10\u003c/li\u003e\n\u003cli\u003eYan S, Jiang C, Janzen A, Barber TR, Seger A, Sommerauer M, Davis JJ, Marek K, Hu MT, Oertel WH, Tofaris GK (2024) Neuronally derived extracellular vesicle \u0026alpha;-synuclein as a serum biomarker for individuals at risk of developing Parkinson disease. JAMA Neurol 81:59-68. https://doi.org/10.1001/jamaneurol.2023.4398\u003c/li\u003e\n\u003cli\u003eYoo SW, Ha S, Lyoo CH, Kim Y, Yoo JY, Kim JS (2023) Exploring the link between essential tremor and Parkinson\u0026rsquo;s disease. NPJ Parkinsons Dis 9:134. https://doi.org/10.1038/s41531-023-00577-y\u003c/li\u003e\n\u003cli\u003eYu Z, Liu G, Li Y, Arkin E, Zheng Y, Feng T (2022) Erythrocytic alpha-synuclein species for Parkinson\u0026rsquo;s disease diagnosis and the correlations with clinical characteristics. Front Aging Neurosci 14:827493. https://doi.org/10.3389/fnagi.2022.827493\u003c/li\u003e\n\u003cli\u003eYu Z, Liu G, Zheng Y, Huang G, Feng T (2023) Erythrocytic alpha-synuclein as potential biomarker for the differentiation between essential tremor and Parkinson\u0026rsquo;s disease. Front Neurol 14:1173074. https://doi.org/10.3389/fneur.2023.1173074\u003c/li\u003e\n\u003cli\u003eZhao A, Li Y, Niu M, Li G, Luo N, Zhou L, Kang W, Liu J (2020) SNCA hypomethylation in rapid eye movement sleep behavior disorder is a potential biomarker for Parkinson\u0026rsquo;s disease. J Parkinsons Dis 10:1023-1031. https://doi.org/10.3233/JPD-201912\u003c/li\u003e\n\u003cli\u003eZubelzu M, Morera-Herreras T, Irastorza G, G\u0026oacute;mez-Esteban JC, Murueta-Goyena A (2022) Plasma and serum alpha-synuclein as a biomarker in Parkinson\u0026rsquo;s disease: a meta-analysis. Parkinsonism Relat Disord 99:107-115. https://doi.org/10.1016/j.parkreldis.2022.06.001\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cellular-and-molecular-neurobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cemn","sideBox":"Learn more about [Cellular and Molecular Neurobiology](https://www.springer.com/journal/10571)","snPcode":"10571","submissionUrl":"https://submission.nature.com/new-submission/10571/3","title":"Cellular and Molecular Neurobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Parkinson’s disease, Atypical Parkinsonian disorders, Dementia and movement disorders, Differential diagnosis, Biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-4973615/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4973615/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccurately diagnosing Parkinson\u0026rsquo;s disease (PD) in its early stages is difficult due to its symptoms overlapping with those of various disorders, including atypical Parkinsonian syndromes, dementia with Lewy bodies (DLB), and even essential tremor. This complicates the diagnostic process for PD, which traditionally heavily relies on symptomatic assessment and treatment response. Recent advances have identified several biomarkers in the blood and cerebrospinal fluid (CSF), including α-synuclein, lysosomal enzymes, fatty acid-binding proteins, and neurofilament light chain, that may potentially be used to diagnosed PD. However, not all can effectively distinguish PD from related disorders or identify its subtypes. This review advocates for a paradigm shift towards biomarker-based diagnosis to effectively distinguish between PD and similar conditions and to categorize PD into its subtypes. These biomarkers may reflect the differences that exist among different diseases and provide an effective way to accurately understand their mechanisms. This review focused on blood and CSF biomarkers of PD that may have differential diagnostic value and the related molecular measurement methods with high diagnostic performance due to emerging technologies.\u003c/p\u003e","manuscriptTitle":"Blood and cerebrospinal fluid differences between Parkinson's disease and related diseases","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-27 19:11:13","doi":"10.21203/rs.3.rs-4973615/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-11T07:04:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-10T18:44:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-10T15:32:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196411119527748366033980296386538580932","date":"2024-10-06T10:02:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33240132770455574868215460587419032753","date":"2024-10-01T11:11:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302031255494849128232627541933987930820","date":"2024-09-04T08:09:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-01T10:24:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5151791759885170524518059179452375627","date":"2024-09-01T10:01:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92604880866305989099590595825098668602","date":"2024-08-30T09:51:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-30T07:25:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-29T21:35:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-29T03:47:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cellular and Molecular Neurobiology","date":"2024-08-25T16:41:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cellular-and-molecular-neurobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cemn","sideBox":"Learn more about [Cellular and Molecular Neurobiology](https://www.springer.com/journal/10571)","snPcode":"10571","submissionUrl":"https://submission.nature.com/new-submission/10571/3","title":"Cellular and Molecular Neurobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"62f76242-1cff-459c-9277-32e7a61bdc9b","owner":[],"postedDate":"September 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-30T16:05:03+00:00","versionOfRecord":{"articleIdentity":"rs-4973615","link":"https://doi.org/10.1007/s10571-024-01523-z","journal":{"identity":"cellular-and-molecular-neurobiology","isVorOnly":false,"title":"Cellular and Molecular Neurobiology"},"publishedOn":"2024-12-27 15:57:31","publishedOnDateReadable":"December 27th, 2024"},"versionCreatedAt":"2024-09-27 19:11:13","video":"","vorDoi":"10.1007/s10571-024-01523-z","vorDoiUrl":"https://doi.org/10.1007/s10571-024-01523-z","workflowStages":[]},"version":"v1","identity":"rs-4973615","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4973615","identity":"rs-4973615","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00