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Liu M, Wang Z, Shang H. Multiple system atrophy: an update and emerging directions of biomarkers and clinical trials. J Neurol 2024; 271:2324-2344. [PMID: 38483626 PMCID: PMC11055738 DOI: 10.1007/s00415-024-12269-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 02/17/2024] [Accepted: 02/19/2024] [Indexed: 04/28/2024]
Abstract
Multiple system atrophy is a rare, debilitating, adult-onset neurodegenerative disorder that manifests clinically as a diverse combination of parkinsonism, cerebellar ataxia, and autonomic dysfunction. It is pathologically characterized by oligodendroglial cytoplasmic inclusions containing abnormally aggregated α-synuclein. According to the updated Movement Disorder Society diagnostic criteria for multiple system atrophy, the diagnosis of clinically established multiple system atrophy requires the manifestation of autonomic dysfunction in combination with poorly levo-dopa responsive parkinsonism and/or cerebellar syndrome. Although symptomatic management of multiple system atrophy can substantially improve quality of life, therapeutic benefits are often limited, ephemeral, and they fail to modify the disease progression and eradicate underlying causes. Consequently, effective breakthrough treatments that target the causes of disease are needed. Numerous preclinical and clinical studies are currently focusing on a set of hallmarks of neurodegenerative diseases to slow or halt the progression of multiple system atrophy: pathological protein aggregation, synaptic dysfunction, aberrant proteostasis, neuronal inflammation, and neuronal cell death. Meanwhile, specific biomarkers and measurements with higher specificity and sensitivity are being developed for the diagnosis of multiple system atrophy, particularly for early detection of the disease. More intriguingly, a growing number of new disease-modifying candidates, which can be used to design multi-targeted, personalized treatment in patients, are being investigated, notwithstanding the failure of most previous attempts.
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Affiliation(s)
- Min Liu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Disease Center, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Zhiyao Wang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Disease Center, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Disease Center, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China.
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Ou R, Liu K, Lin J, Yang T, Xiao Y, Wei Q, Hou Y, Li C, Zhang L, Jiang Z, Zhao B, Chen X, Song W, Wu Y, Shang H. Relationship between plasma NFL and disease progression in Parkinson's disease: a prospective cohort study. J Neurol 2024; 271:1837-1843. [PMID: 38063869 DOI: 10.1007/s00415-023-12117-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/14/2023] [Accepted: 11/14/2023] [Indexed: 03/28/2024]
Abstract
OBJECTIVE We aimed to examine the longitudinal change of plasma neurofilament light chain (NFL) level and explore its diagnostic and prognostic implications in Parkinson's disease (PD). METHODS A total of 184 patients with early PD who completed 5-year annually repeated clinical assessments were included. Plasma NFL at baseline, 1 year, and 2 year were examined, which were quantified using the ultrasensitive Simoa technology. At baseline, blood from 86 sex- and age-matched healthy controls (HC) were obtained for comparison. RESULTS Plasma NFL in PD patients at baseline was significantly higher than those in HC (P = 0.046), and significantly increased after 2 years (P = 0.046). Receiver operating characteristic curve indicated that a plasma NFL cut-off value of 10.79 pg/mL resulted in 39.7% sensitivity and 84.0% specificity, with an area under the curve of 0.635, to distinguish PD from HC (P < 0.001). Linear mixed-effect models indicated that baseline plasma NFL (> 9.24 pg/mL) correlated with a greater increase in the Unified Parkinson's Disease Rating Scale III (estimate = 0.651, P = 0.001) and Hoehn & Yahr stage (estimate = 0.072, P < 0.001), and also correlated with a greater decrease in the Montreal Cognitive Assessment (estimate = - 0.387, P < 0.001) during follow-up visits. CONCLUSIONS Plasma NFL exhibits a tendency to increase with disease progression, and elevated baseline plasma NFL can serve as a predictor for accelerated motor deterioration and cognitive decline in PD. However, plasma NFL does not have high accuracy to distinguish individuals with early-stage PD from HC.
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Affiliation(s)
- Ruwei Ou
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Kuncheng Liu
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Junyu Lin
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Tianmi Yang
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Yi Xiao
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Qianqian Wei
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Yanbing Hou
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Chunyu Li
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Lingyu Zhang
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Zheng Jiang
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Bi Zhao
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Xueping Chen
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Wei Song
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Ying Wu
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Huifang Shang
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China.
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Stephen CD, Vangel M, Gupta AS, MacMore JP, Schmahmann JD. Rates of change of pons and middle cerebellar peduncle diameters are diagnostic of multiple system atrophy of the cerebellar type. Brain Commun 2024; 6:fcae019. [PMID: 38410617 PMCID: PMC10896291 DOI: 10.1093/braincomms/fcae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 12/01/2023] [Accepted: 02/19/2024] [Indexed: 02/28/2024] Open
Abstract
Definitive diagnosis of multiple system atrophy of the cerebellar type (MSA-C) is challenging. We hypothesized that rates of change of pons and middle cerebellar peduncle diameters on MRI would be unique to MSA-C and serve as diagnostic biomarkers. We defined the normative data for anterior-posterior pons and transverse middle cerebellar peduncle diameters on brain MRI in healthy controls, performed diameter-volume correlations and measured intra- and inter-rater reliability. We studied an Exploratory cohort (2002-2014) of 88 MSA-C and 78 other cerebellar ataxia patients, and a Validation cohort (2015-2021) of 49 MSA-C, 13 multiple system atrophy of the parkinsonian type (MSA-P), 99 other cerebellar ataxia patients and 314 non-ataxia patients. We measured anterior-posterior pons and middle cerebellar peduncle diameters on baseline and subsequent MRIs, and correlated results with Brief Ataxia Rating Scale scores. We assessed midbrain:pons and middle cerebellar peduncle:pons ratios over time. The normative anterior-posterior pons diameter was 23.6 ± 1.6 mm, and middle cerebellar peduncle diameter 16.4 ± 1.4 mm. Pons diameter correlated with volume, r = 0.94, P < 0.0001. The anterior-posterior pons and middle cerebellar peduncle measures were smaller at first scan in MSA-C compared to all other ataxias; anterior-posterior pons diameter: Exploratory, 19.3 ± 2.6 mm versus 20.7 ± 2.6 mm, Validation, 19.9 ± 2.1 mm versus 21.1 ± 2.1 mm; middle cerebellar peduncle transverse diameter, Exploratory, 12.0 ± 2.6 mm versus 14.3 ±2.1 mm, Validation, 13.6 ± 2.1 mm versus 15.1 ± 1.8 mm, all P < 0.001. The anterior-posterior pons and middle cerebellar peduncle rates of change were faster in MSA-C than in all other ataxias; anterior-posterior pons diameter rates of change: Exploratory, -0.87 ± 0.04 mm/year versus -0.09 ± 0.02 mm/year, Validation, -0.89 ± 0.48 mm/year versus -0.10 ± 0.21 mm/year; middle cerebellar peduncle transverse diameter rates of change: Exploratory, -0.84 ± 0.05 mm/year versus -0.08 ± 0.02 mm/year, Validation, -0.94 ± 0.64 mm/year versus -0.11 ± 0.27 mm/year, all values P < 0.0001. Anterior-posterior pons and middle cerebellar peduncle diameters were indistinguishable between Possible, Probable and Definite MSA-C. The rate of anterior-posterior pons atrophy was linear, correlating with ataxia severity. Using a lower threshold anterior-posterior pons diameter decrease of -0.4 mm/year to balance sensitivity and specificity, area under the curve analysis discriminating MSA-C from other ataxias was 0.94, yielding sensitivity 0.92 and specificity 0.87. For the middle cerebellar peduncle, with threshold decline -0.5 mm/year, area under the curve was 0.90 yielding sensitivity 0.85 and specificity 0.79. The midbrain:pons ratio increased progressively in MSA-C, whereas the middle cerebellar peduncle:pons ratio was almost unchanged. Anterior-posterior pons and middle cerebellar peduncle diameters were smaller in MSA-C than in MSA-P, P < 0.001. We conclude from this 20-year longitudinal clinical and imaging study that anterior-posterior pons and middle cerebellar peduncle diameters are phenotypic imaging biomarkers of MSA-C. In the correct clinical context, an anterior-posterior pons and transverse middle cerebellar peduncle diameter decline of ∼0.8 mm/year is sufficient for and diagnostic of MSA-C.
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Affiliation(s)
- Christopher D Stephen
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Mark Vangel
- Biostatistics Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02129, USA
| | - Anoopum S Gupta
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Jason P MacMore
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Jeremy D Schmahmann
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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Singer W, Schmeichel AM, Sletten DM, Gehrking TL, Gehrking JA, Trejo-Lopez J, Suarez MD, Anderson JK, Bass PH, Lesnick TG, Low PA. Neurofilament light chain in spinal fluid and plasma in multiple system atrophy: a prospective, longitudinal biomarker study. Clin Auton Res 2023; 33:635-645. [PMID: 37603107 PMCID: PMC10840936 DOI: 10.1007/s10286-023-00974-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 08/10/2023] [Indexed: 08/22/2023]
Abstract
PURPOSE There is a critical need for reliable diagnostic biomarkers as well as surrogate markers of disease progression in multiple system atrophy (MSA). Neurofilament light chain (NfL) has been reported to potentially meet those needs. We therefore sought to explore the value of NfL in plasma (NfL-p) in contrast to cerebrospinal fluid (NfL-c) as a diagnostic marker of MSA, and to assess NfL-p and NfL-c as markers of clinical disease progression. METHODS Well-characterized patients with early MSA (n = 32), Parkinson's disease (PD; n = 21), and matched controls (CON; n = 15) were enrolled in a prospective, longitudinal study of synucleinopathies with serial annual evaluations. NfL was measured using a high-sensitivity immunoassay, and findings were assessed by disease category and relationship with clinical measures of disease progression. RESULTS Measurements of NfL-c were highly reproducible across immunoassay platforms (Pearson, r = 0.99), while correlation between NfL-c and -p was only moderate (r = 0.66). NfL was significantly higher in MSA compared with CON and PD; the separation was essentially perfect for NfL-c, but there was overlap, particularly with PD, for NfL-p. While clinical measures of disease severity progressively increased over time, NfL-c and -p remained at stable elevated levels within subjects across serial measurements. Neither change in NfL nor baseline NfL were significantly associated with changes in clinical markers of disease severity. CONCLUSIONS These findings confirm NfL-c as a faithful diagnostic marker of MSA, while NfL-p showed less robust diagnostic value. The significant NfL elevation in MSA was found to be remarkably stable over time and was not predictive of clinical disease progression.
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Affiliation(s)
- Wolfgang Singer
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Ann M Schmeichel
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - David M Sletten
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Tonette L Gehrking
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jade A Gehrking
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jorge Trejo-Lopez
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Mariana D Suarez
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jennifer K Anderson
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Pamela H Bass
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Phillip A Low
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
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Zhang L, Hou Y, Li C, Wei Q, Ou R, Liu K, Lin J, Yang T, Xiao Y, Jiang Q, Zhao B, Shang H. Longitudinal evolution of sleep disturbances in early multiple system atrophy: a 2-year prospective cohort study. BMC Med 2023; 21:454. [PMID: 37993943 PMCID: PMC10664599 DOI: 10.1186/s12916-023-03176-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 11/14/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND The progression of sleep disturbances remains unclear in patients with early multiple system atrophy (MSA). We aimed to explore the frequency, severity, and coexistence of 2-year longitudinal changes of sleep disturbances including REM sleep behavior disorder (RBD), excessive daytime sleepiness (EDS), and Parkinson's disease-related sleep problems (PD-SP) in early MSA. METHODS MSA patients with a disease duration < 3 years were enrolled to complete a 2-year follow-up visit. Sleep disturbances including RBD, EDS, and PD-SP were assessed using the RBD Screening Questionnaire, Epworth sleepiness scale, and PD sleep scale-2, respectively. RESULTS A total of 220 patients with MSA enrolled in the study and 90 patients completed the 2-year follow-up visit. The score of all three sleep disturbances significantly increased over the 2-year follow-up in MSA and MSA with the predominant parkinsonism group (all p < 0.05). The frequency of PD-SP (from 14.5 to 26.7%) and EDS (from 17.7 to 37.8%) was progressively increased (all p < 0.05) except for RBD (from 51.8 to 65.6%, p = 0.152) over the 2-year follow-up in MSA. The frequency of coexistence of two or three sleep disturbances also increased over time. The most common sleep disturbance was RBD, followed by EDS and PD-SP over the 2-year follow-up. CONCLUSIONS The present study demonstrated that the frequency of different types of sleep disturbances progressively increased except for RBD and the coexistence of two or three sleep disturbances became more common over time in early MSA. Our study suggested that the assessment and management of sleep disturbances should begin early in MSA.
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Affiliation(s)
- Lingyu Zhang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
- Health Management Center, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Yanbing Hou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Chunyu Li
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Qianqian Wei
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Ruwei Ou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Kuncheng Liu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Junyu Lin
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Tianmi Yang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yi Xiao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Qirui Jiang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Bi Zhao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
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Lin J, Ou R, Li C, Hou Y, Zhang L, Wei Q, Pang D, Liu K, Jiang Q, Yang T, Xiao Y, Zhao B, Chen X, Song W, Yang J, Wu Y, Shang H. Plasma glial fibrillary acidic protein as a biomarker of disease progression in Parkinson's disease: a prospective cohort study. BMC Med 2023; 21:420. [PMID: 37932720 PMCID: PMC10626747 DOI: 10.1186/s12916-023-03120-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/19/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND Reactive astrogliosis has been demonstrated to have a role in Parkinson's disease (PD); however, astrocyte-specific plasma glial fibrillary acidic protein (GFAP)'s correlation with PD progression remains unknown. We aimed to determine whether plasma GFAP can monitor and predict PD progression. METHODS A total of 184 patients with PD and 95 healthy controls (HCs) were included in this prospective cohort study and followed-up for 5 years. Plasma GFAP, amyloid-beta (Aβ), p-tau181, and neurofilament light chain (NfL) were measured at baseline and at 1- and 2-year follow-ups. Motor and non-motor symptoms, activities of daily living, global cognitive function, executive function, and disease stage were evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS) part III, UPDRS-I, UPDRS-II, Montreal Cognitive Assessment (MoCA), Frontal Assessment Battery (FAB), and Hoehn and Yahr (H&Y) scales at each visit, respectively. RESULTS Plasma GFAP levels were higher in patients with PD (mean [SD]: 69.80 [36.18], pg/mL) compared to HCs (mean [SD]: 57.89 [23.54], pg/mL). Higher levels of GFAP were observed in female and older PD patients. The adjusted linear mixed-effects models showed that plasma GFAP levels were significantly associated with UPDRS-I scores (β: 0.006, 95% CI [0.001-0.011], p = 0.027). Higher baseline plasma GFAP correlated with faster increase in UPDRS-I (β: 0.237, 95% CI [0.055-0.419], p = 0.011) and UPDRS-III (β: 0.676, 95% CI [0.023-1.330], p = 0.043) scores and H&Y stage (β: 0.098, 95% CI [0.047-0.149], p < 0.001) and faster decrease in MoCA (β: - 0.501, 95% CI [- 0.768 to - 0.234], p < 0.001) and FAB scores (β: - 0.358, 95% CI [- 0.587 to - 0.129], p = 0.002). Higher baseline plasma GFAP predicted a more rapid progression to postural instability (hazard ratio: 1.009, 95% CI [1.001-1.017], p = 0.033). CONCLUSIONS Plasma GFAP might be a potential biomarker for monitoring and predicting disease progression in PD.
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Affiliation(s)
- Junyu Lin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Ruwei Ou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Chunyu Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yanbing Hou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Lingyu Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Qianqian Wei
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Dejiang Pang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Kuncheng Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Qirui Jiang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Tianmi Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yi Xiao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Bi Zhao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Xueping Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Wei Song
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Jing Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Ying Wu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Huifang Shang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
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Chiu C, Cheng W, Lin Y, Lin T, Chang H, Chang Y, Lee C, Chang H, Liu C. A pilot study: handgrip as a predictor in the disease progression of SCA3. Orphanet J Rare Dis 2023; 18:317. [PMID: 37817286 PMCID: PMC10565987 DOI: 10.1186/s13023-023-02948-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/05/2023] [Indexed: 10/12/2023] Open
Abstract
BACKGROUND Spinocerebellar ataxia type 3 (SCA3) is an inherited, autosomal, and rare neurodegenerative disease. Serum/plasma biomarkers or functional magnetic resonance imaging used to assess progression, except for neurological examinations, is either inconvenient or expensive. Handgrip strength (HGS) may be considered as a biomarker to predict the progress of SCA3 and align with the alteration of plasma neurofilament light chain (NfL) and Scale for the Assessment and Rating of Ataxia (SARA). METHODS Patients with SCA3 and healthy subjects were recruited from Changhua Christian Hospital. SARA, body mass index (BMI), and NfL were obtained for both groups. HGS was measured using a Jamar Plus + hand dynamometer. RESULTS This study recruited 31 patients and 36 controls. HGS in the SCA3 group revealed a profound decrease (P < 0.001) compared with normal subjects. HGS also had a negative correlation with SARA (r = - 0.548, P = 0.001), NfL (r = - 0.359, P = 0.048), and a positive correlation with BMI (r = 0.680, P < 0.001). Moreover, HGS/BMI ratio correlated with SARA (r = - 0.441, P = 0.013). Controlling for gender and age, HGS still correlated with the above clinical items. The initial hypothesis was also proved in SCA3 84Q transgenic mice, showing grip strength weakness compared to normal mice. CONCLUSIONS HGS can be an alternative tool to assess the clinical severity of SCA3. Further research is needed to investigate the underlying mechanisms.
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Affiliation(s)
- Chungmin Chiu
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan
- Department of Chinese Medicine, Changhua Christian Hospital, Changhua, Taiwan
| | - Wenling Cheng
- Vascular and Genomic Center, Institute of ATP, Changhua Christian Hospital, Changhua, Taiwan
| | - Yongshiou Lin
- Vascular and Genomic Center, Institute of ATP, Changhua Christian Hospital, Changhua, Taiwan
| | - Tatsung Lin
- Vascular and Genomic Center, Institute of ATP, Changhua Christian Hospital, Changhua, Taiwan
| | - Huiju Chang
- Center of Regenerative Medicine and Tissue Repair, Institute of ATP, Changhua Christian Hospital, Changhua, Taiwan
| | - Yujun Chang
- Big Data Center, Changhua Christian Hospital, Changhua, Taiwan
| | - Chiaju Lee
- Department of Neurology, Changhua Christian Hospital, 7F., No.235, Syuguang Rd., Changhua, 500, Taiwan
| | - Henhong Chang
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan.
- Department of Chinese Medicine, China Medical University Hospital, No.91, Xueshi Rd., North District, Taichung, 404, Taiwan.
- Chinese Medicine Research Center, China Medical University, Taichung, Taiwan.
| | - Chinsan Liu
- Vascular and Genomic Center, Institute of ATP, Changhua Christian Hospital, Changhua, Taiwan.
- Department of Neurology, Changhua Christian Hospital, 7F., No.235, Syuguang Rd., Changhua, 500, Taiwan.
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan.
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8
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Goolla M, Cheshire WP, Ross OA, Kondru N. Diagnosing multiple system atrophy: current clinical guidance and emerging molecular biomarkers. Front Neurol 2023; 14:1210220. [PMID: 37840912 PMCID: PMC10570409 DOI: 10.3389/fneur.2023.1210220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 09/18/2023] [Indexed: 10/17/2023] Open
Abstract
Multiple system atrophy (MSA) is a rare and progressive neurodegenerative disorder characterized by motor and autonomic dysfunction. Accurate and early diagnosis of MSA is challenging due to its clinical similarity with other neurodegenerative disorders, such as Parkinson's disease and atypical parkinsonian disorders. Currently, MSA diagnosis is based on clinical criteria drawing from the patient's symptoms, lack of response to levodopa therapy, neuroimaging studies, and exclusion of other diseases. However, these methods have limitations in sensitivity and specificity. Recent advances in molecular biomarker research, such as α-synuclein protein amplification assays (RT-QuIC) and other biomarkers in cerebrospinal fluid and blood, have shown promise in improving the diagnosis of MSA. Additionally, these biomarkers could also serve as targets for developing disease-modifying therapies and monitoring treatment response. In this review, we provide an overview of the clinical syndrome of MSA and discuss the current diagnostic criteria, limitations of current diagnostic methods, and emerging molecular biomarkers that offer hope for improving the accuracy and early detection of MSA.
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Affiliation(s)
- Meghana Goolla
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, United States
- Department of Surgery, University of Illinois, Chicago, IL, United States
| | | | - Owen A. Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, United States
- Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL, United States
- Department of Biology, University of North Florida, Jacksonville, FL, United States
| | - Naveen Kondru
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, United States
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9
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Peng L, Wan L, Liu M, Long Z, Chen D, Yuan X, Tang Z, Fu Y, Zhu S, Lei L, Wang C, Peng H, Shi Y, He L, Yuan H, Wan N, Hou X, Xia K, Li J, Chen C, Qiu R, Tang B, Chen Z, Jiang H. Diagnostic and prognostic performance of plasma neurofilament light chain in multiple system atrophy: a cross-sectional and longitudinal study. J Neurol 2023; 270:4248-4261. [PMID: 37184660 DOI: 10.1007/s00415-023-11741-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/22/2023] [Accepted: 04/24/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND The longitudinal dynamics of neurofilament light chain (NfL) in multiple system atrophy (MSA) were incompletely illuminated. This study aimed to explore whether the plasma NfL (pNfL) could serve as a potential biomarker of clinical diagnosis and disease progression for MSA. METHODS We quantified pNfL concentrations in both a large cross-sectional cohort with 214 MSA individuals, 65 PD individuals, and 211 healthy controls (HC), and a longitudinal cohort of 84 MSA patients. Propensity score matching (PSM) was used to balance the age between the three groups. The pNfL levels between groups were compared using Kruskal-Wallis test. Linear mixed models were performed to explore the disease progression-associated factors in longitudinal MSA cohort. Random forest model as a complement to linear models was employed to quantify the importance of predictors. RESULTS Before and after matching the age by PSM, the pNfL levels could reliably differentiate MSA from HC and PD groups, but only had mild potential to distinguish PD from HC. By combining linear and nonlinear models, we demonstrated that pNfL levels at baseline, rather than the change rate of pNfL, displayed potential prognostic value for progression of MSA. The combination of baseline pNfL levels and other modifiers, such as subtypes, Hoehn-Yahr stage at baseline, was first shown to improve the diagnosis accuracy. CONCLUSIONS Our study contributed to a better understanding of longitudinal dynamics of pNfL in MSA, and validated the values of pNfL as a non-invasive sensitive biomarker for the diagnosis and progression. The combination of pNfL and other factors is recommended for better monitoring and prediction of MSA progression.
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Affiliation(s)
- Linliu Peng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Linlin Wan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, Hunan, China
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National International Collaborative Research Center for Medical Metabolomics, Central South University, Changsha, 410008, Hunan, China
| | - Mingjie Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Department of Neurology, the Affiliated Nanhua Hospital, University of South China, Hengyang, 421002, Hunan, China
| | - Zhe Long
- Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China
| | - Daji Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Xinrong Yuan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Zhichao Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - You Fu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Sudan Zhu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Lijing Lei
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Chunrong Wang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Huirong Peng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Yuting Shi
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Lang He
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Hongyu Yuan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Na Wan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Xuan Hou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Kun Xia
- Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, 410008, Hunan, China
- Hunan Key Laboratory of Medical Genetics, Central South University, Changsha, 410008, Hunan, China
| | - Jinchen Li
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Chao Chen
- Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, 410008, Hunan, China
- Hunan Key Laboratory of Medical Genetics, Central South University, Changsha, 410008, Hunan, China
| | - Rong Qiu
- School of Computer Science and Engineering, Central South University, Changsha, 410083, Hunan, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
| | - Zhao Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China.
| | - Hong Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- Department of Neurology, The Third Xiangya Hospital of Central South University, Changsha, 410013, Hunan, China.
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China.
- National International Collaborative Research Center for Medical Metabolomics, Central South University, Changsha, 410008, Hunan, China.
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10
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Wan L, Zhu S, Chen Z, Qiu R, Tang B, Jiang H. Multidimensional biomarkers for multiple system atrophy: an update and future directions. Transl Neurodegener 2023; 12:38. [PMID: 37501056 PMCID: PMC10375766 DOI: 10.1186/s40035-023-00370-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 07/11/2023] [Indexed: 07/29/2023] Open
Abstract
Multiple system atrophy (MSA) is a fatal progressive neurodegenerative disease. Biomarkers are urgently required for MSA to improve the diagnostic and prognostic accuracy in clinic and facilitate the development and monitoring of disease-modifying therapies. In recent years, significant research efforts have been made in exploring multidimensional biomarkers for MSA. However, currently few biomarkers are available in clinic. In this review, we systematically summarize the latest advances in multidimensional biomarkers for MSA, including biomarkers in fluids, tissues and gut microbiota as well as imaging biomarkers. Future directions for exploration of novel biomarkers and promotion of implementation in clinic are also discussed.
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Affiliation(s)
- Linlin Wan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National International Collaborative Research Center for Medical Metabolomics, Central South University, Changsha, 410008, China
| | - Sudan Zhu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Zhao Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, 410008, China
| | - Rong Qiu
- School of Computer Science and Engineering, Central South University, Changsha, 410083, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, 410008, China
| | - Hong Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, 410013, China.
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, 410008, China.
- National International Collaborative Research Center for Medical Metabolomics, Central South University, Changsha, 410008, China.
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11
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Zhang L, Hou Y, Wei Q, Ou R, Liu K, Lin J, Yang T, Xiao Y, Zhao B, Shang H. Diagnostic utility of movement disorder society criteria for multiple system atrophy. Front Aging Neurosci 2023; 15:1200563. [PMID: 37396656 PMCID: PMC10310919 DOI: 10.3389/fnagi.2023.1200563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 05/26/2023] [Indexed: 07/04/2023] Open
Abstract
Background The 2008 criteria for the diagnosis of multiple system atrophy (MSA) has been widely used for more than 10 years, but the sensitivity is low, particularly for patients in the early stage. Recently, a new MSA diagnostic criteria was developed. Objective The objective of the study was to assess and compare the diagnostic utility of the new movement disorder society (MDS) MSA criteria with the 2008 MSA criteria. Methods This study included patients diagnosed with MSA between January 2016 and October 2021. All patients underwent regular face-to-face or telephonic follow-ups every year until October 2022. A total of 587 patients (309 males and 278 females) were retrospectively reviewed to compare the diagnostic accuracy of the MDS MSA criteria to that of the 2008 MSA criteria (determined by the proportion of patients categorized as established or probable MSA). Autopsy is the gold standard diagnosis of MSA, which is not available in clinical practice. Thus, we applied the 2008 MSA criteria at the last review as the reference standard. Results The sensitivity of the MDS MSA criteria (93.2%, 95% CI = 90.5-95.2%) was significantly higher than that of the 2008 MSA criteria (83.5%, 95% CI = 79.8-86.6%) (P < 0.001). Additionally, the sensitivity of the MDS MSA criteria was maintained robustly across different subgroups, defined by diagnostic subtype, disease duration, and the type of symptom[s] at onset. Importantly, the specificities were not significantly different between the MDS MSA criteria and the 2008 MSA criteria (P > 0.05). Conclusion The present study demonstrated that the MDS MSA criteria exhibited good diagnostic utility for MSA. The new MDS MSA criteria should be considered as a useful diagnostic tool for clinical practice and future therapeutic trials.
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12
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Zhang X, Ma L, Liang D, Song B, Chen J, Huang Y, Xu L, Zhao P, Wu W, Zhang N, Xue R. Neurofilament Light Protein Predicts Disease Progression in Idiopathic REM Sleep Behavior Disorder. JOURNAL OF PARKINSON'S DISEASE 2023:JPD223519. [PMID: 37182898 DOI: 10.3233/jpd-223519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND Idiopathic rapid eye movement sleep behavior disorder (iRBD) is increasingly recognized as a manifestation preceding the α-synucleinopathies like Parkinson's disease (PD). Neurofilament light chain (NfL) have been reported to be higher in synucleinopathies as a sign of neurodegeneration. OBJECTIVE To evaluate whether plasma NfL is valuable in reflecting cognitive and motor status in iRBD and PD with a premorbid history of RBD (PDRBD), and predicting disease progression in iRBD. METHODS Thirty-one patients with iRBD, 30 with PDRBD, and 18 healthy controls were included in the cross-sectional and prospective study. Another cohort from the Parkinson's Progression Markers Initiative (PPMI) dataset was enrolled for verification analysis. All patients received evaluations of cognitive, motor, and autonomic function by a battery of clinical tests at baseline and follow-up. Blood NfL was measured by the Quanterix Simoa HD-1. RESULTS In our cohort, 26 patients with iRBD completed the follow-up evaluations, among whom eight (30.8%) patients displayed phenoconversion. Baseline plasma NfL cutoff value of 22.93 pg/mL performed best in distinguishing the iRBD converters from non-converters (sensitivity: 75.0%, specificity: 83.3%, area under the curve: 0.84). Cognitive and motor function were significantly correlated with NfL levels in PDRBD (correlation coefficients: -0.379, 0.399; respectively). Higher baseline NfL levels in iRBD were significantly associated with higher risks for cognitive, motor, autonomic function progression, and phenoconversion at follow-up (hazard ratios: 1.069, 1.065, 1.170, 1.065; respectively). The findings were supported by the PPMI dataset. CONCLUSION Plasma NfL is valuable in reflecting disease severity of PDRBD and predicting disease progression and phenoconversion in iRBD.
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Affiliation(s)
- Xuan Zhang
- Department of Neurology, Tianjin Medical University General Hospital Airport Site, Tianjin, China
| | - Li Ma
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Danqi Liang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Bingxin Song
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Jingshan Chen
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Yaqin Huang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Lin Xu
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Peng Zhao
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Wei Wu
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Nan Zhang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Rong Xue
- Department of Neurology, Tianjin Medical University General Hospital Airport Site, Tianjin, China
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
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13
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Guo Y, Shen XN, Huang SY, Chen SF, Wang HF, Zhang W, Zhang YR, Cheng W, Cui M, Dong Q, Yu JT. Head-to-head comparison of 6 plasma biomarkers in early multiple system atrophy. NPJ Parkinsons Dis 2023; 9:40. [PMID: 36922526 PMCID: PMC10017699 DOI: 10.1038/s41531-023-00481-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
There is a dire need for reliable biomarkers to solidify an early and accurate diagnosis of multiple system atrophy (MSA). We sought to compare the ability of emerging plasma markers in distinguishing MSA from its mimics and healthy controls in early disease stages, and to evaluate their performance in detecting disease severity and brain atrophy. Plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), phosphorylated tau181, amyloid-β (Aβ)42, and Aβ40 were measured using ultrasensitive Simoa in early-stage patients with MSA (n = 73), spinocerebellar ataxia (SCA, n = 29), Parkinson's disease (PD, n = 28), and healthy controls (n = 100). We observed that elevated NfL outperformed other biomarkers in distinguishing MSA and its subtypes (AUC = 0.9) versus controls. Intriguingly, when separating MSA from its mimics, increased GFAP (AUC = 0.717) in MSA-C and decreased Aβ40 (AUC = 0.807) in MSA-P best discriminated from SCA and PD respectively. Plasma levels were comparable between MSA-C and MSA-P and the differentiation by plasma index alone was poor. Combining plasma markers noticeably improved the discriminatory efficacy. Of note, among MSA patients, higher GFAP and NfL were correlated with the atrophy of brain regions vulnerable to MSA (e.g., cerebellum, pons, or putamen). They could also aggravate the severity of MSA, and this association was partially mediated by cerebral volumes. In contrast, no obvious associations of phosphorylated tau and Aβ with disease severity were observed. Collectively, plasma biomarkers, especially in combination, are useful to facilitate the discriminatory work-up of MSA at early stages. Moreover, NfL and GFAP may be promising biomarkers to monitor the disease severity of MSA.
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Affiliation(s)
- Yu Guo
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Xue-Ning Shen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Shu-Yi Huang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Shu-Fen Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Hui-Fu Wang
- The Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Wei Zhang
- The Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Wei Cheng
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.,The Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.,Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Zhejiang, China
| | - Mei Cui
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
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14
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Oender D, Faber J, Wilke C, Schaprian T, Lakghomi A, Mengel D, Schöls L, Traschütz A, Fleszar Z, Dufke C, Vielhaber S, Machts J, Giordano I, Grobe-Einsler M, Klopstock T, Stendel C, Boesch S, Nachbauer W, Timmann-Braun D, Thieme AG, Kamm C, Dudesek A, Tallaksen C, Wedding I, Filla A, Schmid M, Synofzik M, Klockgether T. Evolution of Clinical Outcome Measures and Biomarkers in Sporadic Adult-Onset Degenerative Ataxia. Mov Disord 2023; 38:654-664. [PMID: 36695111 DOI: 10.1002/mds.29324] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/11/2022] [Accepted: 12/22/2022] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Sporadic adult-onset ataxias without known genetic or acquired cause are subdivided into multiple system atrophy of cerebellar type (MSA-C) and sporadic adult-onset ataxia of unknown etiology (SAOA). OBJECTIVES To study the differential evolution of both conditions including plasma neurofilament light chain (NfL) levels and magnetic resonance imaging (MRI) markers. METHODS SPORTAX is a prospective registry of sporadic ataxia patients with an onset >40 years. Scale for the Assessment and Rating of Ataxia was the primary outcome measure. In subgroups, blood samples were taken and MRIs performed. Plasma NfL was measured via a single molecule assay. Regional brain volumes were automatically measured. To assess signal changes, we defined the pons and middle cerebellar peduncle abnormality score (PMAS). Using mixed-effects models, we analyzed changes on a time scale starting with ataxia onset. RESULTS Of 404 patients without genetic diagnosis, 130 met criteria of probable MSA-C at baseline and 26 during follow-up suggesting clinical conversion to MSA-C. The remaining 248 were classified as SAOA. At baseline, NfL, cerebellar white matter (CWM) and pons volume, and PMAS separated MSA-C from SAOA. NfL decreased in MSA-C and did not change in SAOA. CWM and pons volume decreased faster, whereas PMAS increased faster in MSA-C. In MSA-C, pons volume had highest sensitivity to change, and PMAS was a predictor of faster progression. Fulfillment of possible MSA criteria, NfL and PMAS were risk factors, CWM and pons volume protective factors for conversion to MSA-C. CONCLUSIONS This study provides detailed information on differential evolution and prognostic relevance of biomarkers in MSA-C and SAOA. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Demet Oender
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Jennifer Faber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Carlo Wilke
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Tamara Schaprian
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Asadeh Lakghomi
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - David Mengel
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Ludger Schöls
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Andreas Traschütz
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Zofia Fleszar
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Claudia Dufke
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Stefan Vielhaber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Judith Machts
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Ilaria Giordano
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegeneration and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Marcus Grobe-Einsler
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Thomas Klopstock
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, Friedrich-Baur-Institute, Ludwig-Maximilians-University, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Claudia Stendel
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, Friedrich-Baur-Institute, Ludwig-Maximilians-University, Munich, Germany
| | - Sylvia Boesch
- Department of Neurology and Center for Rare Movement Disorders, Medical University Innsbruck, Austria
| | - Wolfgang Nachbauer
- Department of Neurology and Center for Rare Movement Disorders, Medical University Innsbruck, Austria
| | - Dagmar Timmann-Braun
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Andreas Gustafsson Thieme
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Christoph Kamm
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Neurology, University of Rostock, Germany
| | - Ales Dudesek
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Neurology, University of Rostock, Germany
| | | | - Iselin Wedding
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alessandro Filla
- Department of Neurosciences Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Thomas Klockgether
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
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15
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Zhang L, Hou Y, Gu X, Cao B, Wei Q, Ou R, Liu K, Lin J, Yang T, Xiao Y, Zhao B, Shang H. Prediction of early-wheelchair dependence in multiple system atrophy based on machine learning algorithm: A prospective cohort study. Clin Park Relat Disord 2023; 8:100183. [PMID: 36714501 PMCID: PMC9881368 DOI: 10.1016/j.prdoa.2023.100183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/02/2023] [Accepted: 01/14/2023] [Indexed: 01/20/2023] Open
Abstract
Objective The predictive factors for wheelchair dependence in patients with multiple system atrophy (MSA) are unclear. We aimed to explore the predictive factors for early-wheelchair dependence in patients with MSA focusing on clinical features and blood biomarkers. Methods This is a prospective cohort study. This study included patients diagnosed with MSA between January 2014 and December 2019. At the deadline of October 2021, patients met the diagnosis of probable MSA were included in the analysis. Random forest (RF) was used to establish a predictive model for early-wheelchair dependence. Accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the model. Results Altogether, 100 patients with MSA including 49 with wheelchair dependence and 51 without wheelchair dependence were enrolled in the RF model. Baseline plasma neurofilament light chain (NFL) levels were higher in patients with wheelchair dependence than in those without (P = 0.037). According to the Gini index, the five major predictive factors were disease duration, age of onset, Unified MSA Rating Scale (UMSARS)-II score, NFL, and UMSARS-I score, followed by C-reactive protein (CRP) levels, neutrophil-to-lymphocyte ratio (NLR), UMSARS-IV score, symptom onset, orthostatic hypotension, sex, urinary incontinence, and diagnosis subtype. The sensitivity, specificity, accuracy, and AUC of the RF model were 70.82 %, 74.55 %, 72.29 %, and 0.72, respectively. Conclusion Besides clinical features, baseline features including NFL, CRP, and NLR were potential predictive biomarkers of early-wheelchair dependence in MSA. These findings provide new insights into the trials regarding early intervention in MSA.
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Key Words
- AUC, area under the receiver operating characteristic curve
- CRP, C-reactive protein
- Cohort study
- MSA, multiple system atrophy
- MSA-C, multiple system atrophy with predominate cerebellar ataxia
- MSA-P, multiple system atrophy with predominate parkinsonism
- Multiple system atrophy
- NFL, neurofilament light chain
- NLR, neutrophil-to-lymphocyte ratio
- OH, orthostatic hypotension
- RF, random forest
- SCA, spinocerebellar ataxia
- TNF, tumor necrosis factor
- UMSARS, unified multiple system atrophy rating scale
- Wheelchair dependence
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Huifang Shang
- Corresponding author at: Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
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16
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Watanabe H, Shima S, Mizutani Y, Ueda A, Ito M. Multiple System Atrophy: Advances in Diagnosis and Therapy. J Mov Disord 2023; 16:13-21. [PMID: 36537066 PMCID: PMC9978260 DOI: 10.14802/jmd.22082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 08/28/2022] [Indexed: 12/24/2022] Open
Abstract
This review summarizes improvements in understanding the pathophysiology and early clinical symptoms of multiple system atrophy (MSA) and advancements in diagnostic methods and disease-modifying therapies for the condition. In 2022, the Movement Disorder Society proposed new diagnostic criteria to develop disease-modifying therapies and promote clinical trials of MSA since the second consensus was proposed in 2008. Regarding pathogenesis, cutting-edge findings have accumulated on the interactions of α-synuclein, neuroinflammation, and oligodendroglia with neurons. In neuroimaging, introducing artificial intelligence, machine learning, and deep learning has notably improved diagnostic accuracy and individual analyses. Advancements in treatment have also been achieved, including immunotherapy therapy against α-synuclein and serotonin-targeted and mesenchymal stem cell therapies, which are thought to affect several aspects of the disease, including neuroinflammation. The accelerated progress in clarifying the pathogenesis of MSA over the past few years and the development of diagnostic techniques for detecting early-stage MSA are expected to facilitate the development of disease-modifying therapies for one of the most intractable neurodegenerative diseases.
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Affiliation(s)
- Hirohisa Watanabe
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan,Corresponding author: Hirohisa Watanabe, MD, PhD Department of Neurology, Fujita Health University, School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake 470-1192, Japan / Tel: +81- 562-93-9295 / Fax: +81-562-93-1856 / E-mail:
| | - Sayuri Shima
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Yasuaki Mizutani
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Akihiro Ueda
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan,Department of Neurology, Fujita Health University Okazaki Medical Center, Okazaki, Japan
| | - Mizuki Ito
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan,Department of Neurology, Fujita Health University Bantane Hospital, Nagoya, Japan
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17
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Stefanova N. A Mouse Model of Multiple System Atrophy: Bench to Bedside. Neurotherapeutics 2023; 20:117-126. [PMID: 35995919 PMCID: PMC10119356 DOI: 10.1007/s13311-022-01287-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/05/2022] [Indexed: 10/15/2022] Open
Abstract
Multiple system atrophy (MSA) is a rare neurodegenerative disorder with unclear etiology, currently difficult and delayed diagnosis, and rapid progression, leading to disability and lethality within 6 to 9 years after symptom onset. The neuropathology of MSA classifies the disease in the group of a-synucleinopathies together with Parkinson's disease and other Lewy body disorders, but features specific oligodendroglial inclusions, which are pathognomonic for MSA. MSA has no efficient therapy to date. Development of experimental models is crucial to elucidate the disease mechanisms in progression and to provide a tool for preclinical screening of putative therapies for MSA. In vitro and in vivo models, based on selective neurotoxicity, a-synuclein oligodendroglial overexpression, and strain-specific propagation of a-synuclein fibrils, have been developed, reflecting various facets of MSA pathology. Over the years, the continuous exchange from bench to bedside and backward has been crucial for the advancing of MSA modelling, elucidating MSA pathogenic pathways, and understanding the existing translational gap to successful clinical trials in MSA. The review discusses specifically advantages and limitations of the PLP-a-syn mouse model of MSA, which recapitulates motor and non-motor features of the human disease with underlying striatonigral degeneration, degeneration of autonomic centers, and sensitized olivopontocerebellar system, strikingly mirroring human MSA pathology.
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Affiliation(s)
- Nadia Stefanova
- Laboratory for Translational Neurodegeneration Research, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
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18
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Chelban V, Nikram E, Perez-Soriano A, Wilke C, Foubert-Samier A, Vijiaratnam N, Guo T, Jabbari E, Olufodun S, Gonzalez M, Senkevich K, Laurens B, Péran P, Rascol O, Le Traon AP, Todd EG, Costantini AA, Alikhwan S, Tariq A, Ng BL, Muñoz E, Painous C, Compta Y, Junque C, Segura B, Zhelcheska K, Wellington H, Schöls L, Jaunmuktane Z, Kobylecki C, Church A, Hu MTM, Rowe JB, Leigh PN, Massey L, Burn DJ, Pavese N, Foltynie T, Pchelina S, Wood N, Heslegrave AJ, Zetterberg H, Bocchetta M, Rohrer JD, Marti MJ, Synofzik M, Morris HR, Meissner WG, Houlden H. Neurofilament light levels predict clinical progression and death in multiple system atrophy. Brain 2022; 145:4398-4408. [PMID: 35903017 PMCID: PMC9762941 DOI: 10.1093/brain/awac253] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/06/2022] [Accepted: 06/17/2022] [Indexed: 11/12/2022] Open
Abstract
Disease-modifying treatments are currently being trialled in multiple system atrophy. Approaches based solely on clinical measures are challenged by heterogeneity of phenotype and pathogenic complexity. Neurofilament light chain protein has been explored as a reliable biomarker in several neurodegenerative disorders but data on multiple system atrophy have been limited. Therefore, neurofilament light chain is not yet routinely used as an outcome measure in multiple system atrophy. We aimed to comprehensively investigate the role and dynamics of neurofilament light chain in multiple system atrophy combined with cross-sectional and longitudinal clinical and imaging scales and for subject trial selection. In this cohort study, we recruited cross-sectional and longitudinal cases in a multicentre European set-up. Plasma and CSF neurofilament light chain concentrations were measured at baseline from 212 multiple system atrophy cases, annually for a mean period of 2 years in 44 multiple system atrophy patients in conjunction with clinical, neuropsychological and MRI brain assessments. Baseline neurofilament light chain characteristics were compared between groups. Cox regression was used to assess survival; receiver operating characteristic analysis to assess the ability of neurofilament light chain to distinguish between multiple system atrophy patients and healthy controls. Multivariate linear mixed-effects models were used to analyse longitudinal neurofilament light chain changes and correlated with clinical and imaging parameters. Polynomial models were used to determine the differential trajectories of neurofilament light chain in multiple system atrophy. We estimated sample sizes for trials aiming to decrease neurofilament light chain levels. We show that in multiple system atrophy, baseline plasma neurofilament light chain levels were better predictors of clinical progression, survival and degree of brain atrophy than the neurofilament light chain rate of change. Comparative analysis of multiple system atrophy progression over the course of disease, using plasma neurofilament light chain and clinical rating scales, indicated that neurofilament light chain levels rise as the motor symptoms progress, followed by deceleration in advanced stages. Sample size prediction suggested that significantly lower trial participant numbers would be needed to demonstrate treatment effects when incorporating plasma neurofilament light chain values into multiple system atrophy clinical trials in comparison to clinical measures alone. In conclusion, neurofilament light chain correlates with clinical disease severity, progression and prognosis in multiple system atrophy. Combined with clinical and imaging analysis, neurofilament light chain can inform patient stratification and serve as a reliable biomarker of treatment response in future multiple system atrophy trials of putative disease-modifying agents.
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Affiliation(s)
- Viorica Chelban
- Correspondence to: Dr Viorica Chelban Department of Neuromuscular Diseases UCL Queen Square Institute of Neurology London WC1N 3BG, UK E-mail:
| | - Elham Nikram
- Peninsula Technology Assessment Group (PenTAG), University of Exeter, Exeter EX 2LU, UK
| | - Alexandra Perez-Soriano
- Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid 28029, Spain
| | - Carlo Wilke
- Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, 72074 Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), 72074 Tübingen, Germany
| | - Alexandra Foubert-Samier
- CRMR AMS, Service de Neurologie – Maladies Neurodégénératives, CHU de Bordeaux, F-33000 Bordeaux, France
- Université de Bordeaux, CNRS, IMN, UMR 5293, F-33000 Bordeaux, France
- Université de Bordeaux, INSERM, BPH, U1219, F-33000 Bordeaux, France
- Inserm, CIC 1401 Bordeaux, Clinical Epidemiology Unit, F-33000 Bordeaux, France
| | - Nirosen Vijiaratnam
- Department Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Tong Guo
- Department Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Edwin Jabbari
- Department Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Simisola Olufodun
- Department of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Mariel Gonzalez
- Department of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Konstantin Senkevich
- Neurogenomics and Precision Medicine (NAP-Med) Laboratory, The Neuro (Montreal Neurological Institute-Hospital), Montreal, QC H3A 2B4, Canada
- Department of Neurology & Neurosurgery, McGill University, Montreal, QC H3A 2B4, Canada
- Laboratory of Human Genetics, Petersburg Nuclear Physics Institute named by B.P. Konstantinov of National Research Centre 'Kurchatov Institute', Gatchina 188300, Russia
- Laboratory of Medical Genetics, Pavlov First Saint-Petersburg State Medical University, St. Petersburg 197022, Russia
| | - Brice Laurens
- CRMR AMS, Service de Neurologie – Maladies Neurodégénératives, CHU de Bordeaux, F-33000 Bordeaux, France
- Université de Bordeaux, CNRS, IMN, UMR 5293, F-33000 Bordeaux, France
| | - Patrice Péran
- ToNIC, Toulouse NeuroImaging Center, UMR 1214, Université de Toulouse, 31024 Toulouse, France
| | - Olivier Rascol
- CRMR AMS, CHU de Toulouse, 31300 Toulouse, France
- Clinical Investigation Center CIC 1436, NS-Park/F-CRIN Network and NeuroToul COEN Center; Inserm, University of Toulouse 3 and CHU of Toulouse, F-31000 Toulouse, France
- Departments of Neurosciences and Clinical Pharmacology, CHU Toulouse and University of Toulouse 3, F-31000 Toulouse, France
| | - Anne Pavy Le Traon
- CRMR AMS, CHU de Toulouse, 31300 Toulouse, France
- Institut des Maladies Métaboliques et Cardiovasculaires, Inserm U 1297, Toulouse University, F-31000 Toulouse, France
| | - Emily G Todd
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG London, UK
| | - Alyssa A Costantini
- Department Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Sondos Alikhwan
- Department of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Ambreen Tariq
- Department of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Bai Lin Ng
- Department of Economics, University College London, London WC1N 3BG, UK
| | - Esteban Muñoz
- Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid 28029, Spain
| | - Celia Painous
- Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid 28029, Spain
| | - Yaroslau Compta
- Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid 28029, Spain
| | - Carme Junque
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid 28029, Spain
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, 08035 Barcelona, Spain
| | - Barbara Segura
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid 28029, Spain
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, 08035 Barcelona, Spain
| | - Kristina Zhelcheska
- Department of Neuromuscular Diseases, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Henny Wellington
- Biomarkers Factory Laboratory, UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Ludger Schöls
- Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, 72074 Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), 72074 Tübingen, Germany
| | - Zane Jaunmuktane
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, WC1N 3BG London, UK
| | - Christopher Kobylecki
- Department of Neurology, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, Stott Lane, Salford M6 8HD, UK
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK
| | - Alistair Church
- Department of Neurology, Royal Gwent Hospital, Newport NP20 2UB, UK
| | - Michele T M Hu
- Division of Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - James B Rowe
- Department of Clinical Neurosciences, Cambridge University, Cambridge CB3 0SZ, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, CB3 0SZ Cambridge, UK
- Neurology Department, Cambridge University Hospitals NHS Trust, Cambridge CB2 0QQ, UK
| | - P Nigel Leigh
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton BN1 9PX, UK
| | - Luke Massey
- Neurology Department, University Hospitals Dorset, Poole BH15 2JB, UK
| | - David J Burn
- Faculty of Medical Sciences, Clinical Ageing Research Unit, Newcastle University, NE4 5PL Newcastle, UK
| | - Nicola Pavese
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, WC1N 3BG London, UK
| | - Tom Foltynie
- Department Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Sofya Pchelina
- Laboratory of Human Genetics, Petersburg Nuclear Physics Institute named by B.P. Konstantinov of National Research Centre 'Kurchatov Institute', Gatchina 188300, Russia
- Laboratory of Medical Genetics, Pavlov First Saint-Petersburg State Medical University, St. Petersburg 197022, Russia
| | - Nicholas Wood
- Department Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Amanda J Heslegrave
- Biomarkers Factory Laboratory, UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Henrik Zetterberg
- Biomarkers Factory Laboratory, UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, WC1N 3BG London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, 405 30 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 405 30 Mölndal, Sweden
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong 1512-1518, China
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG London, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG London, UK
| | - Maria J Marti
- Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
- Parkinson's Disease and Movement Disorders Unit, Neurology Department, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid 28029, Spain
| | - Matthis Synofzik
- Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, 72074 Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), 72074 Tübingen, Germany
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19
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Zhang L, Li R, Hou Y, Cao B, Wei Q, Ou R, Liu K, Lin J, Yang T, Xiao Y, Huang W, Shang H. Cystatin C predicts cognitive decline in multiple system atrophy: A 1-year prospective cohort study. Front Aging Neurosci 2022; 14:1069837. [PMID: 36518820 PMCID: PMC9742413 DOI: 10.3389/fnagi.2022.1069837] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 11/14/2022] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Accumulating evidence has suggested that cystatin C is associated with cognitive impairment in patients with neurodegenerative diseases. However, the association between cystatin C and cognitive decline in patients with multiple system atrophy (MSA) remains largely unknown. OBJECTIVES The objective was to determine whether cystatin C was independently associated with cognitive decline in patients with early-stage MSA. METHODS Patients with MSA underwent evaluation at baseline and the 1-year follow-up. Cognitive function was evaluated with Montreal cognitive assessment (MoCA). Changes in the MoCA score and the absolute MoCA score at the 1-year assessment were considered the main cognitive outcome. The cystatin C concentrations in patients with MSA and age, sex, and body mass index matched-healthy controls (HCs) were measured. A multiple linear regression model was used to test the association between cystatin C and cognitive decline. RESULTS A total of 117 patients with MSA and 416 HCs were enrolled in the study. The cystatin C levels were significantly higher in patients with MSA than in HCs (p < 0.001). Cystatin C levels were negatively correlated with MoCA score at baseline and at 1-year follow-up. Multiple linear regression model adjusted for potential confounders showed that baseline cystatin C levels were significantly associated with the MoCA score (p = 0.004) or change in the MoCA score (p = 0.008) at 1-year follow-up. CONCLUSION Our results suggested that cystatin C may serve as a potential biomarker of cognitive decline in patients with early-stage MSA.
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Affiliation(s)
- Lingyu Zhang
- Health Management Center, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ruicen Li
- Health Management Center, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yanbing Hou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Bei Cao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Qianqian Wei
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ruwei Ou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Kuncheng Liu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Junyu Lin
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Tianmi Yang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Xiao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
| | - Wenxia Huang
- Health Management Center, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China
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20
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Longitudinal evolution of motor and non-motor symptoms in early-stage multiple system atrophy: a 2-year prospective cohort study. BMC Med 2022; 20:446. [PMID: 36397048 PMCID: PMC9670051 DOI: 10.1186/s12916-022-02645-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 10/31/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The progression of motor and non-motor symptoms (NMS) and the sensitivity of each item of the Unified Multiple System Atrophy Rating Scale (UMSARS) to change remain unclear in Chinese patients with early-stage multiple system atrophy (MSA). We investigated the evolution of motor symptoms and NMS in early-stage MSA and the sensitivity of each item included in the UMSARS to change over a 2-year follow-up. METHODS Motor symptoms and NMS were recorded at baseline and at 1- and 2-year follow-ups based on the UMSARS and the NMS scale. Generalized estimating equation models were used. The sensitivity of an item included in the UMSARS to change was assessed by calculating a standardized effect using the mean annual change divided by the standard deviation of the change. RESULTS We enrolled 246 consecutive patients with MSA and 97 MSA completed the 2-year follow-up. The mean total UMSARS score increased by 11.90 and 22.54 points at the 1- and 2-year follow-ups, respectively. UMSARS-I items associated with motor functions were more sensitive to change and those associated with autonomic dysfunction showed less sensitivity to change. Items 4 (tremor at rest), 5 (action tremor), and 3 (ocular motor dysfunction) of the UMSARS-II were less sensitive to change. The prevalence and severity of NMS significantly increased over the 2-year follow-up. CONCLUSIONS We observed significant progression in motor symptoms and NMS in patients with early-stage MSA. Our results provide useful information to support the revision of the UMSARS.
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Delaby C, Bousiges O, Bouvier D, Fillée C, Fourier A, Mondésert E, Nezry N, Omar S, Quadrio I, Rucheton B, Schraen-Maschke S, van Pesch V, Vicca S, Lehmann S, Bedel A. Neurofilaments contribution in clinic: state of the art. Front Aging Neurosci 2022; 14:1034684. [PMID: 36389064 PMCID: PMC9664201 DOI: 10.3389/fnagi.2022.1034684] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 10/10/2022] [Indexed: 07/26/2023] Open
Abstract
Neurological biomarkers are particularly valuable to clinicians as they can be used for diagnosis, prognosis, or response to treatment. This field of neurology has evolved considerably in recent years with the improvement of analytical methods, allowing the detection of biomarkers not only in cerebrospinal fluid (CSF) but also in less invasive fluids like blood. These advances greatly facilitate the repeated quantification of biomarkers, including at asymptomatic stages of the disease. Among the various informative biomarkers of neurological disorders, neurofilaments (NfL) have proven to be of particular interest in many contexts, such as neurodegenerative diseases, traumatic brain injury, multiple sclerosis, stroke, and cancer. Here we discuss these different pathologies and the potential value of NfL assay in the management of these patients, both for diagnosis and prognosis. We also describe the added value of NfL compared to other biomarkers currently used to monitor the diseases described in this review.
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Affiliation(s)
- Constance Delaby
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
- Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau—Biomedical Research Institute Sant Pau—Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Olivier Bousiges
- Laboratoire de biochimie et biologie moléculaire (LBBM)—Pôle de biologie Hôpital de Hautepierre—CHU de Strasbourg, CNRS, laboratoire ICube UMR 7357 et FMTS (Fédération de Médecine Translationnelle de Strasbourg), équipe IMIS, Strasbourg, France
| | - Damien Bouvier
- Service de Biochimie et Génétique Moléculaire, CHU de Clermont-Ferrand, Clermont-Ferrand, France
| | - Catherine Fillée
- Cliniques universitaires Saint-Luc UCLouvain, Service de Biochimie Médicale, Brussels, Belgium
| | - Anthony Fourier
- Biochimie et Biologie Moléculaire—LBMMS, Unité de diagnostic des pathologies dégénératives, Centre de Biologie et Pathologie Est, Groupement Hospitalier Est, Lyon, France
| | - Etienne Mondésert
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
| | - Nicolas Nezry
- Univ. Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, Lille, France
| | - Souheil Omar
- Laboratoire de biologie médicale de l’Institut de Neurologie de Tunis, Tunis, Tunisia
| | - Isabelle Quadrio
- Biochimie et Biologie Moléculaire—LBMMS, Unité de diagnostic des pathologies dégénératives, Centre de Biologie et Pathologie Est, Groupement Hospitalier Est, Lyon, France
| | - Benoit Rucheton
- Laboratoire de Biologie, Institut Bergonié, Bordeaux, France
| | - Susanna Schraen-Maschke
- Univ. Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, Lille, France
| | - Vincent van Pesch
- Cliniques universitaires Saint-Luc UCLouvain, Service de Neurologie, Brussels, Belgium
| | - Stéphanie Vicca
- Hôpital Necker-Enfants malades, Paris, Laboratoire de Biochimie générale, DMU BioPhyGen, AP-HP.Centre—Université de Paris, Paris, France
| | - Sylvain Lehmann
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
| | - Aurelie Bedel
- Service de Biochimie, CHU Pellegrin, Bordeaux, France
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22
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Laboratory prognostic factors for the long-term survival of multiple system atrophy. NPJ Parkinsons Dis 2022; 8:141. [PMID: 36302764 PMCID: PMC9613998 DOI: 10.1038/s41531-022-00413-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 10/12/2022] [Indexed: 11/24/2022] Open
Abstract
To elucidate the biomarkers related to survival in multiple system atrophy(MSA), we analyzed the predictability of retrospectively collected blood markers for survival in 650 probable MSA. High absolute neutrophil count, red-cell distribution width, C-reactive protein, erythrocyte sedimentation rate, and low hemoglobin, protein, albumin, and creatinine were correlated with higher mortality in MSA. Systemic alteration in inflammation and nutritional status in the early stage are associated with higher mortality in MSA.
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Abstract
Multiple system atrophy (MSA) is a rare neurodegenerative disease that is characterized by neuronal loss and gliosis in multiple areas of the central nervous system including striatonigral, olivopontocerebellar and central autonomic structures. Oligodendroglial cytoplasmic inclusions containing misfolded and aggregated α-synuclein are the histopathological hallmark of MSA. A firm clinical diagnosis requires the presence of autonomic dysfunction in combination with parkinsonism that responds poorly to levodopa and/or cerebellar ataxia. Clinical diagnostic accuracy is suboptimal in early disease because of phenotypic overlaps with Parkinson disease or other types of degenerative parkinsonism as well as with other cerebellar disorders. The symptomatic management of MSA requires a complex multimodal approach to compensate for autonomic failure, alleviate parkinsonism and cerebellar ataxia and associated disabilities. None of the available treatments significantly slows the aggressive course of MSA. Despite several failed trials in the past, a robust pipeline of putative disease-modifying agents, along with progress towards early diagnosis and the development of sensitive diagnostic and progression biomarkers for MSA, offer new hope for patients.
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Mak G, Menon S, Lu JQ. Neurofilaments in neurologic disorders and beyond. J Neurol Sci 2022; 441:120380. [PMID: 36027641 DOI: 10.1016/j.jns.2022.120380] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 08/07/2022] [Accepted: 08/10/2022] [Indexed: 11/17/2022]
Abstract
Many neurologic diseases can initially present as a diagnostic challenge and even when a diagnosis is made, monitoring of disease activity, progression and response to therapy may be limited with existing clinical and paraclinical assessments. As such, the identification of disease specific biomarkers provides a promising avenue by which diseases can be effectively diagnosed, monitored and used as a prognostic indicator for long-term outcomes. Neurofilaments are an integral component of the neuronal cytoskeleton, where assessment of neurofilaments in the blood, cerebrospinal fluid (CSF) and diseased tissue has been shown to have value in providing diagnostic clarity, monitoring disease activity, tracking progression and treatment efficacy, as well as lending prognostic insight into long-term outcomes. As such, this review attempts to provide a glimpse into the structure and function of neurofilaments, their role in various neurologic and non-neurologic disorders, including uncommon conditions with recent knowledge of neurofilament-related pathology, as well as their applicability in future clinical practice.
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Affiliation(s)
- Gloria Mak
- McMaster University, Department of Medicine, Hamilton, Ontario, Canada
| | - Suresh Menon
- McMaster University, Department of Medicine, Hamilton, Ontario, Canada
| | - Jian-Qiang Lu
- McMaster University, Department of Pathology and Molecular Medicine, Hamilton, Ontario, Canada.
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25
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Zhang P, Chen J, Cai T, He C, Li Y, Li X, Chen Z, Wang L, Zhang Y. Quantitative susceptibility mapping and blood neurofilament light chain differentiate between parkinsonian disorders. Front Aging Neurosci 2022; 14:909552. [PMID: 35992605 PMCID: PMC9389149 DOI: 10.3389/fnagi.2022.909552] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives We employed quantitative susceptibility mapping (QSM) to assess iron deposition in parkinsonian disorders and explored whether combining QSM values and neurofilament light (NfL) chain levels can improve the accuracy of distinguishing Parkinson’s disease (PD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Materials and methods Forty-seven patients with PD, 28 patients with MSA, 18 patients with PSP, and 28 healthy controls (HC) were enrolled, and QSM data were reconstructed. Susceptibility values in the bilateral globus pallidus (GP), putamen (PUT), caudate nucleus (CN), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN) were obtained. Plasma NfL levels of 47 PD, 18 MSA, and 14 PSP patients and 22 HC were measured by ultrasensitive Simoa technology. Results The highest diagnostic accuracy distinguishing MSA from PD patients was observed with increased susceptibility values in CN (AUC: 0.740). The susceptibility values in RN yielded the highest diagnostic performance for distinguishing PSP from PD patients (AUC: 0.829). Plasma NfL levels were significantly higher in the MSA and PSP groups than in PD and HC groups. Combining the susceptibility values in the RN and plasma NfL levels improved the diagnostic performance for PSP vs. PD (AUC: 0.904), whereas plasma NfL levels had higher diagnostic accuracy for MSA vs. PD (AUC: 0.877). Conclusion The exploratory study indicates different patterns of iron accumulation in deep gray matter nuclei in Parkinsonian disorders. Combining QSM values with NfL levels may be a promising biomarker for distinguishing PSP from PD, whereas plasma NfL may be a reliable biomarker for differentiating MSA from PD. QSM and NfL measures appeared to have low accuracy for separating PD from controls.
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Affiliation(s)
- Piao Zhang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Junling Chen
- Department of Neurology, Shantou Central Hospital, Shantou, China
| | - Tongtong Cai
- Department of Neurology, Shantou Central Hospital, Shantou, China
| | - Chentao He
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yan Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xiaohong Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhenzhen Chen
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Lijuan Wang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yuhu Zhang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- *Correspondence: Yuhu Zhang,
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Clinical correlations of cerebrospinal fluid biomarkers including neuron-glia 2 and neurofilament light chain in patients with multiple system atrophy. Parkinsonism Relat Disord 2022; 102:30-35. [DOI: 10.1016/j.parkreldis.2022.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/14/2022] [Accepted: 07/14/2022] [Indexed: 11/19/2022]
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Höllerhage M, Klietz M, Höglinger GU. Disease modification in Parkinsonism: obstacles and ways forward. J Neural Transm (Vienna) 2022; 129:1133-1153. [PMID: 35695938 PMCID: PMC9463344 DOI: 10.1007/s00702-022-02520-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/21/2022] [Indexed: 12/19/2022]
Abstract
To date, the diagnoses of Parkinson syndromes are based on clinical examination. Therefore, these specific diagnoses are made, when the neuropathological process is already advanced. However, disease modification or neuroprotection, is considered to be most effective before marked neurodegeneration has occurred. In recent years, early clinical or prodromal stages of Parkinson syndromes came into focus. Moreover, subtypes of distinct diseases will allow predictions of the individual course of the diseases more precisely. Thereby, patients will be enrolled into clinical trials with more specific disease entities and endpoints. Furthermore, novel fluid and imaging biomarkers that allow biochemical diagnoses are under development. These will lead to earlier diagnoses and earlier therapy in the future as consequence. Furthermore, therapeutic approaches will take the underlying neuropathological process of neurodegenerative Parkinson syndromes more specific into account. Specifically, future therapies will target the aggregation of aggregation-prone proteins such as alpha-synuclein and tau, the degradation of pathological aggregates, and the spreading of pathological protein aggregates throughout the brain. Many of these approaches are already in (pre)clinical development. In addition, anti-inflammatory approaches are in development. Furthermore, drug-repurposing is a feasible approach to shorten the developmental process of new drugs.
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Affiliation(s)
- M Höllerhage
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - M Klietz
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - G U Höglinger
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
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Chung SJ, Asgharnejad M, Bauer L, Benitez A, Boroojerdi B, Heidbrede T, Little A, Kim HJ. Switching from an oral dopamine receptor agonist to rotigotine transdermal patch: a review of clinical data with a focus on patient perspective. Expert Rev Neurother 2019; 17:737-749. [PMID: 28548894 DOI: 10.1080/14737175.2017.1336087] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Dopamine receptor agonists (DAs) are commonly used to treat Parkinson's disease (PD) and restless legs syndrome (RLS). In certain situations, switching from oral DAs to rotigotine transdermal patch may be beneficial for the patient (e.g., optimal symptom control/side effects/perioperative management, preference for once-daily/non-oral administration, RLS augmentation treatment). Areas covered: This narrative review summarizes available data on DA dose equivalency, dose conversions, switching schedules, safety, tolerability, efficacy and patient treatment preferences of switching from oral DAs to rotigotine (and vice versa) in patients with PD/RLS. The studies were identified in a PubMed search (up to 8 November 2016) using terms ('dopamine receptor agonist' OR 'rotigotine') AND 'switch'. Expert commentary: Randomized controlled studies often do not address the challenges clinicians face in practice, e.g., switching medications within the same class when dosing is not a one-to-one ratio. The authors describe three open-label studies in PD where oral DAs were successfully switched to rotigotine, and review three studies in RLS where oral DAs/levodopa were switched to rotigotine. Finally, the authors provide a suggested tool for switching from oral DAs to rotigotine, which includes dose conversion factors and switching schedules. The authors' view is that low-dose oral DAs (equivalent to ≤8 mg/24 h rotigotine) may be switched overnight.
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Affiliation(s)
- Sun Ju Chung
- a Department of Neurology, Asan Medical Center , University of Ulsan College of Medicine , Seoul , South Korea
| | | | - Lars Bauer
- c UCB Pharma , Monheim am Rhein , Germany
| | | | | | | | | | - Han Joon Kim
- f Seoul National University Hospital , Seoul , South Korea
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