Plasma NfL, clinical subtypes and motor progression in Parkinson's disease

Padovani, Alessandro; Imarisio, Alberto; Conforti, F. L.; Scalvini, Andrea; Masciocchi, Stefano; Nocivelli, Sara; Turrone, Rosanna; Gipponi, Stefano; Cottini, Elisabetta; Borroni, Barbara; Rizzetti, Maria Cristina; Pizzi, Marina; Bonanni, Laura; Sturchio, Andrea; Espay, Alberto J.; Zetterberg, Henrik; Ashton, Nicholas J.; Hye, Abdul; Padovani, Alessandro

doi:10.1016/j.parkreldis.2021.04.016

Cited by 29 publications

(23 citation statements)

References 47 publications

(65 reference statements)

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“…On the other, a recent work proposed Cys-C as a mediator of neurodegeneration, able to induct microglial activation and consequent neurotoxic factors' release in rat dopaminergic cell cultures [17]. The present study added an important piece to this complex picture, revealing a strong correlation between plasma levels of Cys-C and NfL, a highly reliable biomarker of neuronal damage [8,27,47]. This association is of particular relevance because constitutes the first evidence of a direct link between neurodegeneration and Cys-C, independently from peripheral inflammation.…”

Section: Discussionsupporting

confidence: 55%

“…Findings showed that PD patients with higher Cys-C levels exhibited faster motor progression over a 2-year follow-up, as measured by MDS-UPDRS-III changes, after adjusting for age, sex, disease duration, and peripheral inflammation. In addition, the present work provides the first evidence of a significant correlation between plasma levels of Cys-C and NfL, a well-known marker of axonal damage in neurodegenerative diseases [7, 8, 27, 28].…”

Section: Discussionmentioning

confidence: 92%

“…A comprehensive, standardized cognitive and behavioral assessment was applied, including Mini-Mental State Examination (MMSE) and ten tests covering five cognitive domains as previously described [25]. All patients included in the analyses underwent a complete motor and cognitive assessment follow-up at 2 years as previously described [8].…”

Section: Methodsmentioning

confidence: 99%

“…Parkinson's disease (PD) represents a neurodegenerative condition characterized by an heterogeneous clinical presentation and prognosis [1][2][3][4]. Recently, faster PD progression have been associated with increased level of CSF and blood neurofilament light chain (NfL) as proxy of neuronal damage [5][6][7][8][9]. Still, the biological factors underpinning the wide clinical heterogeneity and individual vulnerability to neurodegeneration are theme of debate.…”

Section: Introductionmentioning

confidence: 99%

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Plasma Cystatin C Correlates with Plasma NfL Levels and Predicts Disease Progression in Parkinson’s Disease

et al. 2021

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Introduction: Previous studies reported increased plasma levels of Cystatin C (Cys-C) in Parkinson’s disease (PD) and claimed for a possible association with disease severity and progression. The aim of this study was to evaluate plasma Cys-C in PD and healthy controls (HC) and test its association with markers of peripheral inflammation, neurodegeneration and clinical progression in a longitudinal study. Methods: Plasma Cys-C, high-sensitive C-reactive protein (hsCRP), interleukin 6 (IL-6) and Neurofilament Light Chain (NfL) were assessed at the baseline in 71 consecutive non-demented PD and 69 HC. PD patients underwent an extensive motor and cognitive assessment at baseline and after 2 years of follow-up. The association of Cys-C with disease severity was evaluated in a multilinear model adjusted for the effect of age, sex, disease duration and peripheral inflammation. Results: Cys-C levels appeared to be higher in PD compared to controls and correlated with the plasma neuronal marker NfL (r = 0.204, p = 0.046). In longitudinal analyses, PD patients with higher Cys-C levels exhibited faster motor progression at two years of follow-up independently from the peripheral inflammatory profile. Conclusions: Cys-C was associated with higher NfL levels and a remarkably faster motor progression in PD independently from peripheral inflammation. Further studies are needed in order to understand the mechanisms underpinning the association of Cys-C with higher neuronal damage markers in neurodegenerative diseases.

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Section: Discussionsupporting

confidence: 55%

Section: Discussionmentioning

confidence: 92%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Plasma Cystatin C Correlates with Plasma NfL Levels and Predicts Disease Progression in Parkinson’s Disease

et al. 2021

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“…As blood NFLs have a diagnostic accuracy similar to CSF NFLs, they may be a valid clinical tool in differential diagnosis between PD and APD [ 54 ]. Increased NFL levels were observed in patients with PD in connection with severe and long-term disease, in the context of the presence of dementia [ 55 ]. Although NFL in CSF and blood can differentiate between PD and APD, they cannot be used as a tool to differentiate between APD with synuclein depositions (MSA), and APD related to the depositions of pathologically changed protein tau (tauopathies) as progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD).…”

Section: Parkinson’s Disease and Dementia With Lewy Bodies (Pd And Dlb)mentioning

confidence: 99%

Biomarkers of Neurodegenerative Diseases: Biology, Taxonomy, Clinical Relevance, and Current Research Status

et al. 2022

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The understanding of neurodegenerative diseases, traditionally considered to be well-defined entities with distinguishable clinical phenotypes, has undergone a major shift over the last 20 years. The diagnosis of neurodegenerative diseases primarily requires functional brain imaging techniques or invasive tests such as lumbar puncture to assess cerebrospinal fluid. A new biological approach and research efforts, especially in vivo, have focused on biomarkers indicating underlying proteinopathy in cerebrospinal fluid and blood serum. However, due to the complexity and heterogeneity of neurodegenerative processes within the central nervous system and the large number of overlapping clinical diagnoses, identifying individual proteinopathies is relatively difficult and often not entirely accurate. For this reason, there is an urgent need to develop laboratory methods for identifying specific biomarkers, understand the molecular basis of neurodegenerative disorders and classify the quantifiable and readily available tools that can accelerate efforts to translate the knowledge into disease-modifying therapies that can improve and simplify the areas of differential diagnosis, as well as monitor the disease course with the aim of estimating the prognosis or evaluating the effects of treatment. The aim of this review is to summarize the current knowledge about clinically relevant biomarkers in different neurodegenerative diseases.

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A machine learning approach to predict quality of life changes in patients with Parkinson's Disease

Alexander

Nataraj

2023

Ann Clin Transl Neurol

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Objective: Parkinson disease (PD) is a progressive neurodegenerative disorder with an annual incidence of approximately 0.1%. While primarily considered a motor disorder, increasing emphasis is being placed on its non-motor features. Both manifestations of the disease affect quality of life (QoL), which is captured in part II of the Unified Parkinson's Disease Rating Scale (UPDRS-II). While useful in the management of patients, it remains challenging to predict how QoL will change over time in PD. The goal of this work is to explore the feasibility of a machine learning algorithm to predict QoL changes in PD patients. Methods: In this retrospective cohort study, patients with at least 12 months of follow-up were identified from the Parkinson's Progression Markers Initiative database (N = 630) and divided into two groups: those with and without clinically significant worsening in UPDRS-II (n = 404 and n = 226, respectively). We developed an artificial neural network using only UPDRS-II scores, to predict whether a patient would clinically worsen or not at 12 months from follow-up. Results: Using UPDRS-II at baseline, at 2 months, and at 4 months, the algorithm achieved 90% specificity and 56% sensitivity. Interpretation: A learning model has the potential to rule in patients who may exhibit clinically significant worsening in QoL at 12 months. These patients may require further testing and increased focus.

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Plasma NfL, clinical subtypes and motor progression in Parkinson's disease

Cited by 29 publications

References 47 publications

Plasma Cystatin C Correlates with Plasma NfL Levels and Predicts Disease Progression in Parkinson’s Disease

Plasma Cystatin C Correlates with Plasma NfL Levels and Predicts Disease Progression in Parkinson’s Disease

Biomarkers of Neurodegenerative Diseases: Biology, Taxonomy, Clinical Relevance, and Current Research Status

A machine learning approach to predict quality of life changes in patients with Parkinson's Disease

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