Identification of novel cerebrospinal fluid biomarker candidates for dementia with Lewy bodies: a proteomic approach

Molecular Neurodegeneration

Inger van Steenoven¹  Betty M. Tijms¹  Wiesje M. van der Flier¹  Afina W. Lemstra¹  Leonie J. M. Vergouw²  Frank Jan de Jong²  Markus Otto³  Patrick Oeckl³  Gian-Luca Ferri⁴  Cristina Cocco⁴  Barbara Noli⁴  Charlotte E. Teunissen⁵  Marleen J. A. Koel-Simmelink⁵  Claire Bridel⁵  Sander R. Piersma⁶  Connie R. Jimenez⁶  Thang V. Pham⁶  Paul F. Worley⁷  Desheng Xu⁷  Mei-Fang Xiao⁷ 

[1] Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC;Alzheimer Center Erasmus MC, Department of Neurology, Erasmus Medical Center;Department of Neurology, Ulm University Hospital;NEF-laboratory, Department of Biomedical Sciences, University of Cagliari;Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC;OncoProteomics Laboratory, Department of Medical Oncology, Vrije Universiteit Amsterdam, Amsterdam UMC;Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine;

关键词: Biomarkers;    Cerebrospinal fluid;    Dementia with Lewy bodies;    Lewy body dementia;    Proteomics;   

DOI  :  10.1186/s13024-020-00388-2

来源: DOAJ

【 摘 要 】

Abstract Background Diagnosis of dementia with Lewy bodies (DLB) is challenging, largely due to a lack of diagnostic tools. Cerebrospinal fluid (CSF) biomarkers have been proven useful in Alzheimer’s disease (AD) diagnosis. Here, we aimed to identify novel CSF biomarkers for DLB using a high-throughput proteomic approach. Methods We applied liquid chromatography/tandem mass spectrometry with label-free quantification to identify biomarker candidates to individual CSF samples from a well-characterized cohort comprising patients with DLB (n = 20) and controls (n = 20). Validation was performed using (1) the identical proteomic workflow in an independent cohort (n = 30), (2) proteomic data from patients with related neurodegenerative diseases (n = 149) and (3) orthogonal techniques in an extended cohort consisting of DLB patients and controls (n = 76). Additionally, we utilized random forest analysis to identify the subset of candidate markers that best distinguished DLB from all other groups. Results In total, we identified 1995 proteins. In the discovery cohort, 69 proteins were differentially expressed in DLB compared to controls (p < 0.05). Independent cohort replication confirmed VGF, SCG2, NPTX2, NPTXR, PDYN and PCSK1N as candidate biomarkers for DLB. The downregulation of the candidate biomarkers was somewhat more pronounced in DLB in comparison with related neurodegenerative diseases. Using random forest analysis, we identified a panel of VGF, SCG2 and PDYN to best differentiate between DLB and other clinical groups (accuracy: 0.82 (95%CI: 0.75–0.89)). Moreover, we confirmed the decrease of VGF and NPTX2 in DLB by ELISA and SRM methods. Low CSF levels of all biomarker candidates, except PCSK1N, were associated with more pronounced cognitive decline (0.37 < r < 0.56, all p < 0.01). Conclusion We identified and validated six novel CSF biomarkers for DLB. These biomarkers, particularly when used as a panel, show promise to improve diagnostic accuracy and strengthen the importance of synaptic dysfunction in the pathophysiology of DLB.

【 授权许可】

Unknown