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De Bartolo MI, Belvisi D, Mancinelli R, Costanzo M, Caturano C, Leodori G, Berardelli A, Fabbrini G, Vivacqua G. A systematic review of salivary biomarkers in Parkinson's disease. Neural Regen Res 2024; 19:2613-2625. [PMID: 38595280 PMCID: PMC11168506 DOI: 10.4103/nrr.nrr-d-23-01677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 12/25/2023] [Accepted: 01/25/2024] [Indexed: 04/11/2024] Open
Abstract
The search for reliable and easily accessible biomarkers in Parkinson's disease is receiving a growing emphasis, to detect neurodegeneration from the prodromal phase and to enforce disease-modifying therapies. Despite the need for non-invasively accessible biomarkers, the majority of the studies have pointed to cerebrospinal fluid or peripheral biopsies biomarkers, which require invasive collection procedures. Saliva represents an easily accessible biofluid and an incredibly wide source of molecular biomarkers. In the present study, after presenting the morphological and biological bases for looking at saliva in the search of biomarkers for Parkinson's disease, we systematically reviewed the results achieved so far in the saliva of different cohorts of Parkinson's disease patients. A comprehensive literature search on PubMed and SCOPUS led to the discovery of 289 articles. After screening and exclusion, 34 relevant articles were derived for systematic review. Alpha-synuclein, the histopathological hallmark of Parkinson's disease, has been the most investigated Parkinson's disease biomarker in saliva, with oligomeric alpha-synuclein consistently found increased in Parkinson's disease patients in comparison to healthy controls, while conflicting results have been reported regarding the levels of total alpha-synuclein and phosphorylated alpha-synuclein, and few studies described an increased oligomeric alpha-synuclein/total alpha-synuclein ratio in Parkinson's disease. Beyond alpha-synuclein, other biomarkers targeting different molecular pathways have been explored in the saliva of Parkinson's disease patients: total tau, phosphorylated tau, amyloid-β1-42 (pathological protein aggregation biomarkers); DJ-1, heme-oxygenase-1, metabolites (altered energy homeostasis biomarkers); MAPLC-3beta (aberrant proteostasis biomarker); cortisol, tumor necrosis factor-alpha (inflammation biomarkers); DNA methylation, miRNA (DNA/RNA defects biomarkers); acetylcholinesterase activity (synaptic and neuronal network dysfunction biomarkers); Raman spectra, proteome, and caffeine. Despite a few studies investigating biomarkers targeting molecular pathways different from alpha-synuclein in Parkinson's disease, these results should be replicated and observed in studies on larger cohorts, considering the potential role of these biomarkers in determining the molecular variance among Parkinson's disease subtypes. Although the need for standardization in sample collection and processing, salivary-based biomarkers studies have reported encouraging results, calling for large-scale longitudinal studies and multicentric assessments, given the great molecular potentials and the non-invasive accessibility of saliva.
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Affiliation(s)
| | - Daniele Belvisi
- IRCCS Neuromed, Pozzilli, Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Romina Mancinelli
- Department of Anatomical, Histological, Forensic Medicine and Orthopedics Sciences, Sapienza University of Rome, Rome, Italy
| | | | - Claudia Caturano
- Department of Experimental Morphology and Microscopy -Integrated Research Center (PRAAB) -Campus Biomedico University of Rome, Rome, Italy
| | - Giorgio Leodori
- IRCCS Neuromed, Pozzilli, Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Alfredo Berardelli
- IRCCS Neuromed, Pozzilli, Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Giovanni Fabbrini
- IRCCS Neuromed, Pozzilli, Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Giorgio Vivacqua
- Department of Experimental Morphology and Microscopy -Integrated Research Center (PRAAB) -Campus Biomedico University of Rome, Rome, Italy
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2
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Gabbert C, Blöbaum L, Lüth T, König IR, Caliebe A, Sendel S, Laabs BH, Klein C, Trinh J. The combined effect of lifestyle factors and polygenic scores on age at onset in Parkinson's disease. Sci Rep 2024; 14:14670. [PMID: 38918550 PMCID: PMC11199580 DOI: 10.1038/s41598-024-65640-x] [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: 02/08/2024] [Accepted: 06/21/2024] [Indexed: 06/27/2024] Open
Abstract
The objective of this study was to investigate the association between a Parkinson's disease (PD)-specific polygenic score (PGS) and protective lifestyle factors on age at onset (AAO) in PD. We included data from 4367 patients with idiopathic PD, 159 patients with GBA1-PD, and 3090 healthy controls of European ancestry from AMP-PD, PPMI, and Fox Insight cohorts. The association between PGS and lifestyle factors on AAO was assessed with linear and Cox proportional hazards models. The PGS showed a negative association with AAO (β = - 1.07, p = 6 × 10-7) in patients with idiopathic PD. The use of one, two, or three of the protective lifestyle factors showed a reduction in the hazard ratio by 21% (p = 0.0001), 44% (p < 2 × 10-16), and 55% (p < 2 × 10-16), compared to no use. An additive effect of aspirin (β = 7.62, p = 9 × 10-7) and PGS (β = - 1.58, p = 0.0149) was found for AAO without an interaction (p = 0.9993) in the linear regressions, and similar effects were seen for tobacco. In contrast, no association between aspirin intake and AAO was found in GBA1-PD (p > 0.05). In our cohort, coffee, tobacco, aspirin, and PGS are independent predictors of PD AAO. Additionally, lifestyle factors seem to have a greater influence on AAO than common genetic risk variants with aspirin presenting the largest effect.
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Affiliation(s)
- Carolin Gabbert
- Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany
| | - Leonie Blöbaum
- Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany
| | - Theresa Lüth
- Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany
| | - Inke R König
- Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck, Germany
| | - Amke Caliebe
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Sebastian Sendel
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Björn-Hergen Laabs
- Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany
| | - Joanne Trinh
- Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany.
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3
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Hu R, Wang R, Yuan J, Lin Z, Hutchins E, Landin B, Liao Z, Liu G, Scherzer CR, Dong X. Transcriptional pathobiology and multi-omics predictors for Parkinson's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.18.599639. [PMID: 38948706 PMCID: PMC11212969 DOI: 10.1101/2024.06.18.599639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Early diagnosis and biomarker discovery to bolster the therapeutic pipeline for Parkinson's disease (PD) are urgently needed. In this study, we leverage the large-scale whole-blood total RNA-seq dataset from the Accelerating Medicine Partnership in Parkinson's Disease (AMP PD) program to identify PD-associated RNAs, including both known genes and novel circular RNAs (circRNA) and enhancer RNAs (eRNAs). There were 1,111 significant marker RNAs, including 491 genes, 599 eRNAs, and 21 circRNAs, that were first discovered in the PPMI cohort (FDR < 0.05) and confirmed in the PDBP/BioFIND cohorts (nominal p < 0.05). Functional enrichment analysis showed that the PD-associated genes are involved in neutrophil activation and degranulation, as well as the TNF-alpha signaling pathway. We further compare the PD-associated genes in blood with those in post-mortem brain dopamine neurons in our BRAINcode cohort. 44 genes show significant changes with the same direction in both PD brain neurons and PD blood, including neuroinflammation-associated genes IKBIP, CXCR2, and NFKBIB. Finally, we built a novel multi-omics machine learning model to predict PD diagnosis with high performance (AUC = 0.89), which was superior to previous studies and might aid the decision-making for PD diagnosis in clinical practice. In summary, this study delineates a wide spectrum of the known and novel RNAs linked to PD and are detectable in circulating blood cells in a harmonized, large-scale dataset. It provides a generally useful computational framework for further biomarker development and early disease prediction.
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Affiliation(s)
- Ruifeng Hu
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Precision Neurology Program, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Genomics and Bioinformatics Hub, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Ruoxuan Wang
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Precision Neurology Program, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Genomics and Bioinformatics Hub, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Jie Yuan
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Precision Neurology Program, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Genomics and Bioinformatics Hub, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Zechuan Lin
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Precision Neurology Program, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Elizabeth Hutchins
- Neurogenomics Division, Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | | | - Zhixiang Liao
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Precision Neurology Program, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ganqiang Liu
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Shenzhen Key Laboratory of Systems Medicine in Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Clemens R. Scherzer
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Precision Neurology Program, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Xianjun Dong
- APDA Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Precision Neurology Program, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Genomics and Bioinformatics Hub, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
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Pan W, Su C, Maasch JRMA, Chen K, Henchcliffe C, Wang F. Learning Phenotypic Associations for Parkinson's Disease with Longitudinal Clinical Records. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE PROCEEDINGS. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE 2024; 2024:374-383. [PMID: 38827071 PMCID: PMC11141836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Parkinson's disease (PD) is associated with multiple clinical motor and non-motor manifestations. Understanding of PD etiologies has been informed by a growing number of genetic mutations and various fluid-based and brain imaging biomarkers. However, the mechanisms underlying its varied phenotypic features remain elusive. The present work introduces a data-driven approach for generating phenotypic association graphs for PD cohorts. Data collected by the Parkinson's Progression Markers Initiative (PPMI), the Parkinson's Disease Biomarkers Program (PDBP), and the Fox Investigation for New Discovery of Biomarkers (BioFIND) were analyzed by this approach to identify heterogeneous and longitudinal phenotypic associations that may provide insight into the pathology of this complex disease. Findings based on the phenotypic association graphs could improve understanding of longitudinal PD pathologies and how these relate to patient symptomology.
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Affiliation(s)
- Weishen Pan
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Chang Su
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | | | - Kun Chen
- Department of Statistics, University of Connecticut, Storrs, CT, USA
| | - Claire Henchcliffe
- Department of Neurology, University of California, Irvine, Irvine, CA, USA
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
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Durmaz Celik N, Ozben S, Ozben T. Unveiling Parkinson's disease through biomarker research: current insights and future prospects. Crit Rev Clin Lab Sci 2024:1-17. [PMID: 38529882 DOI: 10.1080/10408363.2024.2331471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 03/13/2024] [Indexed: 03/27/2024]
Abstract
Parkinson's disease (PD) is a neurodegenerative condition marked by the gradual depletion of dopaminergic neurons in the substantia nigra. Despite substantial strides in comprehending potential causative mechanisms, the validation of biomarkers with unequivocal evidence for routine clinical application remains elusive. Consequently, the diagnosis heavily relies on patients' clinical assessments and medical backgrounds. The imperative need for diagnostic and prognostic biomarkers arises due to the prevailing limitations of treatments, which predominantly address symptoms without modifying the disease course. This comprehensive review aims to elucidate the existing landscape of diagnostic and prognostic biomarkers for PD, drawing insights from contemporary literature.
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Affiliation(s)
- Nazlı Durmaz Celik
- Department of Neurology, Eskisehir Osmangazi University Faculty of Medicine, Eskisehir, Turkey
| | - Serkan Ozben
- Department of Neurology, University of Health Sciences, Antalya Training and Research Hospital, Antalya, Turkey
| | - Tomris Ozben
- Department of Medical Biochemistry, Medical Faculty, Akdeniz University, Antalya, Turkey
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6
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Paslawski W, Svenningsson P. Elevated ApoE, ApoJ and lipoprotein-bound α-synuclein levels in cerebrospinal fluid from Parkinson's disease patients - Validation in the BioFIND cohort. Parkinsonism Relat Disord 2023; 116:105765. [PMID: 37479568 PMCID: PMC11140586 DOI: 10.1016/j.parkreldis.2023.105765] [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: 03/17/2023] [Revised: 06/12/2023] [Accepted: 07/11/2023] [Indexed: 07/23/2023]
Abstract
BACKGROUND The progressive accumulation, aggregation, and spread of α-synuclein (aSN) are common hallmarks of Parkinson's disease (PD) pathology. The genotype of apolipoprotein E (ApoE) influences PD progression. Recently we found that aSN co-localize with apolipoproteins on lipoprotein vesicles. We reported an increased level of ApoE, ApoJ and lipoprotein-bound aSN in CSF from early PD patients compared to matched controls. We also found reduced plasma ApoAI in PD patients. OBJECTIVE In this study, we used the same approach on the BioFIND cohort to validate our previous results and extended the studies to examine correlations with ApoE genotype, demographic variables, clinical symptoms and other biochemical findings reported in the BioFIND cohort. METHODS For the assessment, we used Western-Blot (WB) technique for apolipoproteins measurements in CSF and plasma from PD patients and healthy controls. Further, for measurement of aSN bound to lipoproteins, we combined immunodepletion with the enzyme-linked immunosorbent assay (ELISA). RESULTS Levels of ApoE, ApoJ and lipoprotein bound aSN were significantly increased in CSF from PD patients compared to controls. We also observed decreased levels of ApoAI and ApoJ in plasma from PD patients compared to controls. CONCLUSIONS Concluding, the present data validated our previous findings. Altered lipoproteins appear to be important in early PD pathology and may be involved in mechanisms underlying aSN cell-to-cell transfer in the nervous system and be developed in algorithms for early diagnosis of PD.
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Affiliation(s)
- Wojciech Paslawski
- Laboratory of Translational Neuropharmacology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Per Svenningsson
- Laboratory of Translational Neuropharmacology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
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7
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Paslawski W, Khosousi S, Hertz E, Markaki I, Boxer A, Svenningsson P. Large-scale proximity extension assay reveals CSF midkine and DOPA decarboxylase as supportive diagnostic biomarkers for Parkinson's disease. Transl Neurodegener 2023; 12:42. [PMID: 37667404 PMCID: PMC10476347 DOI: 10.1186/s40035-023-00374-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 08/17/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND There is a need for biomarkers to support an accurate diagnosis of Parkinson's disease (PD). Cerebrospinal fluid (CSF) has been a successful biofluid for finding neurodegenerative biomarkers, and modern highly sensitive multiplexing methods offer the possibility to perform discovery studies. Using a large-scale multiplex proximity extension assay (PEA) approach, we aimed to discover novel diagnostic protein biomarkers allowing accurate discrimination of PD from both controls and atypical Parkinsonian disorders (APD). METHODS CSF from patients with PD, corticobasal syndrome (CBS), progressive supranuclear palsy (PSP), multiple system atrophy and controls, were analysed with Olink PEA panels. Three cohorts were used in this study, comprising 192, 88 and 36 cases, respectively. All samples were run on the Cardiovascular II, Oncology II and Metabolism PEA panels. RESULTS Our analysis revealed that 26 and 39 proteins were differentially expressed in the CSF of test and validation PD cohorts, respectively, compared to controls. Among them, 6 proteins were changed in both cohorts. Midkine (MK) was increased in PD with the strongest effect size and results were validated with ELISA. Another most increased protein in PD, DOPA decarboxylase (DDC), which catalyses the decarboxylation of DOPA (L-3,4-dihydroxyphenylalanine) to dopamine, was strongly correlated with dopaminergic treatment. Moreover, Kallikrein 10 was specifically changed in APD compared with both PD and controls, but unchanged between PD and controls. Wnt inhibitory factor 1 was consistently downregulated in CBS and PSP patients in two independent cohorts. CONCLUSIONS Using the large-scale PEA approach, we have identified potential novel PD diagnostic biomarkers, most notably MK and DDC, in the CSF of PD patients.
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Affiliation(s)
- Wojciech Paslawski
- Laboratory of Translational Neuropharmacology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Shervin Khosousi
- Laboratory of Translational Neuropharmacology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ellen Hertz
- Laboratory of Translational Neuropharmacology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ioanna Markaki
- Laboratory of Translational Neuropharmacology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Adam Boxer
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Per Svenningsson
- Laboratory of Translational Neuropharmacology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
- Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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8
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Leonard HL, Murtadha R, Martinez-Carrasco A, Jama A, Müller-Nedebock AC, Gil-Martinez AL, Illarionova A, Moore A, Bustos BI, Jadhav B, Huxford B, Storm C, Towns C, Vitale D, Chetty D, Yu E, Grenn FP, Salazar G, Rateau G, Iwaki H, Elsayed I, Foote IF, Jansen van Rensburg Z, Kim JJ, Yuan J, Lake J, Brolin K, Senkevich K, Wu L, Tan MMX, Periñán MT, Makarious MB, Ta M, Pillay NS, Betancor OL, Reyes-Pérez PR, Alvarez Jerez P, Saini P, Al-Ouran R, Sivakumar R, Real R, Reynolds RH, Hu R, Abrahams S, Rao SC, Antar T, Leal TP, Iankova V, Scotton WJ, Song Y, Singleton A, Nalls MA, Dey S, Bandres-Ciga S, Blauwendraat C, Noyce AJ. The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data. NPJ Parkinsons Dis 2023; 9:33. [PMID: 36871034 PMCID: PMC9984758 DOI: 10.1038/s41531-023-00472-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 02/13/2023] [Indexed: 03/06/2023] Open
Abstract
Open science and collaboration are necessary to facilitate the advancement of Parkinson's disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD.
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Affiliation(s)
- Hampton L Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA. .,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA. .,Data Tecnica International LLC, Washington, DC, USA. .,German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
| | - Ruqaya Murtadha
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Alejandro Martinez-Carrasco
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Alina Jama
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Amica Corda Müller-Nedebock
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Ana-Luisa Gil-Martinez
- Department of Neurodegenerative Disease, University College London, London, UK.,Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, UK
| | | | - Anni Moore
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Bernabe I Bustos
- The Ken & Ruth Davee Department of Neurology and Simpson Querrey Center of Neurogenetics, Feinberg Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Bharati Jadhav
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, New York, NY, 10029, USA
| | - Brook Huxford
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Catherine Storm
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Clodagh Towns
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Dan Vitale
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Data Tecnica International LLC, Washington, DC, USA
| | - Devina Chetty
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Eric Yu
- Department of Human Genetics, McGill University, Montreal, QC, Canada.,The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada
| | - Francis P Grenn
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Gabriela Salazar
- INNCOSYS, Col. Morelos Second Section, 50120, Toluca de Lerdo, México
| | - Geoffrey Rateau
- Institut du Cerveau - Institute of Brain and Spine (ICM), Hôpital Pitié, 47 Bd de l'Hôpital, 75013, Paris, France
| | - Hirotaka Iwaki
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Data Tecnica International LLC, Washington, DC, USA
| | - Inas Elsayed
- Faculty of pharmacy, University of Gezira, Wad Medani, P.O. Box 20, Sudan.,International Parkinson Disease Genomics Consortium (IPDGC)-Africa, University of Gezira, Wad Medani, P.O. Box 20, Sudan
| | - Isabelle Francesca Foote
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, New York, NY, 10029, USA.,Unit for Psychological Medicine, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Zuné Jansen van Rensburg
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jonggeol Jeff Kim
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, New York, NY, 10029, USA
| | - Jie Yuan
- Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Julie Lake
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Kajsa Brolin
- Translational Neurogenetics Unit, Wallenberg Neuroscience Center, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - Konstantin Senkevich
- Department of Human Genetics, McGill University, Montreal, QC, Canada.,Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
| | - Lesley Wu
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Manuela M X Tan
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK.,Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - María Teresa Periñán
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain.,CIBERNED, Madrid, Spain
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Michael Ta
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Nikita Simone Pillay
- South African National Bioinformatics Institute (SANBI), South African Medical Research Council Bioinformatics Unit, University of the Western Cape, Bellville, South Africa
| | - Oswaldo Lorenzo Betancor
- Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA.,Department of Neurology, University of Washington School of Medicine, Seattle, WA, USA
| | - Paula R Reyes-Pérez
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de, México, Juriquilla, México
| | - Pilar Alvarez Jerez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Prabhjyot Saini
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Rami Al-Ouran
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, 77030, USA
| | | | - Raquel Real
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Regina H Reynolds
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa.,Department of Neurodegenerative Disease, University College London, London, UK
| | - Ruifneg Hu
- Center for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Shameemah Abrahams
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Shilpa C Rao
- Department of Genomic Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, 44195, USA.,Department of Molecular Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Tarek Antar
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Thiago Peixoto Leal
- Department of Genomic Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, 44195, USA
| | - Vassilena Iankova
- Department of Neurology With Friedrich Baur Institut, University Hospital of Ludwig-Maximilians-Universität München, Munich, Germany
| | - William J Scotton
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Yeajin Song
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Andrew Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Data Tecnica International LLC, Washington, DC, USA
| | - Sumit Dey
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, New York, NY, 10029, USA
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.,Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Alastair J Noyce
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, New York, NY, 10029, USA
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9
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LeWitt PA, Li J, Wu KH, Lu M. Diagnostic metabolomic profiling of Parkinson's disease biospecimens. Neurobiol Dis 2023; 177:105962. [PMID: 36563791 DOI: 10.1016/j.nbd.2022.105962] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 12/02/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Reliable and sensitive biomarkers are needed for enhancing and predicting Parkinson's disease (PD) diagnosis. OBJECTIVE To investigate comprehensive metabolomic profiling of biochemicals in CSF and serum for determining diagnostic biomarkers of PD. METHODS Fifty subjects, symptomatic with PD for ≥5 years, were matched to 50 healthy controls (HCs). We used ultrahigh-performance liquid chromatography linked to tandem mass spectrometry (UHPLC-MS/MS) for measuring relative concentrations of ≤1.5 kDalton biochemicals. A reference library created from authentic standards facilitated chemical identifications. Analytes underwent univariate analysis for PD association, with false discovery rate-adjusted p-value (≤0.05) determinations. Multivariate analysis (for identifying a panel of biochemicals discriminating PD from HCs) used several biostatistical methods, including logistic LASSO regression. RESULTS Comparing PD and HCs, strong differentiation was achieved from CSF but not serum specimens. With univariate analysis, 21 CSF compounds exhibited significant differential concentrations. Logistic LASSO regression led to selection of 23 biochemicals (11 shared with those determined by the univariate analysis). The selected compounds, as a group, distinguished PD from HCs, with Area-Under-the-Receiver-Operating-Characteristic (ROC) curve of 0.897. With optimal cutoff, logistic LASSO achieved 100% sensitivity and 96% specificity (and positive and negative predictive values of 96% and 100%). Ten-fold cross-validation gave 84% sensitivity and 82% specificity (and 82% positive and 84% negative predictive values). From the logistic LASSO-chosen regression model, 2 polyamine metabolites (N-acetylcadaverine and N-acetylputrescine) were chosen and had the highest fold-changes in comparing PD to HCs. Another chosen biochemical, acisoga (N-(3-acetamidopropyl)pyrrolidine-2-one), also is a polyamine metabolism derivative. CONCLUSIONS UHPLC-MS/MS assays provided a metabolomic signature highly predictive of PD. These findings provide further evidence for involvement of polyamine pathways in the neurodegeneration of PD.
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Affiliation(s)
- Peter A LeWitt
- Departments of Neurology, Henry Ford Hospital, West Bloomfield, MI, USA; Wayne State University School of Medicine, West Bloomfield, MI, USA.
| | - Jia Li
- The Department of Public Health Science, Henry Ford Health System, Detroit, MI, USA
| | - Kuan-Han Wu
- The Department of Public Health Science, Henry Ford Health System, Detroit, MI, USA
| | - Mei Lu
- The Department of Public Health Science, Henry Ford Health System, Detroit, MI, USA
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10
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Fernández-Espejo E, Rodríguez de Fonseca F, Gavito AL, Córdoba-Fernández A, Chacón J, Martín de Pablos Á. Myeloperoxidase and Advanced Oxidation Protein Products in the Cerebrospinal Fluid in Women and Men with Parkinson's Disease. Antioxidants (Basel) 2022; 11:antiox11061088. [PMID: 35739985 PMCID: PMC9219636 DOI: 10.3390/antiox11061088] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 05/24/2022] [Accepted: 05/27/2022] [Indexed: 11/30/2022] Open
Abstract
Background: Myeloperoxidase (MPO) and advanced oxidation protein products, or AOPP (a type of MPO-derived chlorinated adducts), have been implicated in Parkinson´s disease (PD). Human MPO also show sex-based differences in PD. The objective was to study the relationship of MPO and AOPP in the cerebrospinal fluid (CSF) with motor features of idiopathic PD in male and female patients. Methods: MPO concentration and activity and AOPP content were measured in the CSF and serum in 34 patients and 30 controls. CSF leukocytes and the integrity of the blood-brain barrier were evaluated. Correlations of MPO and AOPP with clinical variables were examined. Results: The blood-brain barrier was intact and CSF leukocyte count was normal in all patients. CSF MPO concentration and activity were similar in the cohort of patients and controls, but CSF MPO content was significantly higher in male patients than in PD women (p = 0.0084). CSF MPO concentration correlated with disease duration in male and female patients (p < 0.01). CSF MPO concentration was significantly higher in men with disease duration ≥12 years versus the remainder of the male subjects (p < 0.01). Changes in CSF MPO in women were not significant. Serum MPO concentration and activity were significantly higher in all PD patients relative to controls (p < 0.0001). CSF MPO was not correlated with serum MPO. Serum AOPP were detected in all patients, but CSF AOPP was undetectable in 53% of patients. AOPP were not quantifiable in controls. Conclusions: CSF MPO is not a good biomarker for PD because mean CSF MPO concentration and activity are not different between the cohort of patients and controls. CSF MPO concentration positively correlated with disease duration in men and women, but CSF MPO is significantly enhanced only in male patients with disease duration longer than 12 years. It can be hypothesized that the MPO-related immune response in early-stage PD might be weak in all patients, but then the MPO-related immune response is progressively enhanced in men, not women. Since the blood-brain barrier is intact, and CSF MPO is not correlated with serum MPO, CSF myeloperoxidase would reflect MPO content in brain cells, not blood-derived cells. Finally, serum AOPP was detected in all patients, but not controls, which is consistent with the occurrence of chlorinative stress in blood serum in PD. The study of CSF AOPP as biomarker could not be assessed because the ELISA assay was hampered by its detection limit in the CSF.
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Affiliation(s)
- Emilio Fernández-Espejo
- Reial Acadèmia de Medicina de Catalunya, 08001 Barcelona, Spain
- Laboratorio de Medicina Regenerativa, Hospital Regional Universitario, 29010 Málaga, Spain;
- Correspondence: (E.F.-E.); (F.R.d.F.); Tel.: +34-95-4184712 (E.F.-E.); +34-95-2614012 (F.R.d.F.)
| | - Fernando Rodríguez de Fonseca
- Laboratorio de Medicina Regenerativa, Hospital Regional Universitario, 29010 Málaga, Spain;
- Unidad de Gestión Clínica de Salud Mental, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Regional Universitario, 29010 Málaga, Spain
- Correspondence: (E.F.-E.); (F.R.d.F.); Tel.: +34-95-4184712 (E.F.-E.); +34-95-2614012 (F.R.d.F.)
| | - Ana Luisa Gavito
- Laboratorio de Medicina Regenerativa, Hospital Regional Universitario, 29010 Málaga, Spain;
- Unidad de Gestión Clínica de Salud Mental, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Regional Universitario, 29010 Málaga, Spain
| | | | - José Chacón
- Servicio de Neurología, Hospital Quirónsalud Infanta Luisa, 41010 Sevilla, Spain;
| | - Ángel Martín de Pablos
- Departamento de Cirugía, Universidad de Sevilla, 41009 Sevilla, Spain;
- Unidad de Anestesiología y Reanimación, Servicio de Cirugía, Hospital Macarena, 41009 Sevilla, Spain
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11
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Fernández-Espejo E, Gavito AL, Suárez J, Tolosa E, Vilas D, Aldecoa I, Berenguer J, Córdoba-Fernández A, Damas-Hermoso F, Rodríguez de Fonseca F. Salivary ATP13A2 is a potential marker of therapy-induced motor complications and is expressed by inclusions in submandibulary glands in Parkinson ́s disease. Clin Park Relat Disord 2022; 7:100163. [PMID: 36081833 PMCID: PMC9445999 DOI: 10.1016/j.prdoa.2022.100163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 08/01/2022] [Accepted: 08/19/2022] [Indexed: 11/25/2022] Open
Abstract
Patients with motor complications, not the remainder of the patients, show quantifiable levels of salivary ATP13A2. Patients with motor complications present high salivary ATP13A2 concentration relative to controls. Salivary ATP13A2 content in patients with motor complications positively correlates with levodopa equivalent daily dose and MDS-UPDRS. The submandibulary gland in PD patients contains ATP13A2-expressing rounded inclusions of 10–20 µm in diameter. This is the first description of ATP13A2-expressing inclusions outside the nervous system in PD patients.
Background ATP13A2 holds promise as biomarker for Parkinsońs disease (PD). No study has examined how salivary ATP13A2 is related to motor features in idiopathic PD. Methods Salivary ATP13A2 concentration was evaluated with ELISA, and statistical correlations of ATP13A2 level with PD parameters were examined. The dose intensity of the dopaminergic medication regimen was expressed as levodopa equivalent daily dose (LEDD). ATP13A2 expression on histological sections of submandibular glands was evaluated using immunohistochemistry. Results Salivary ATP13A2 was undetectable in many subjects (28 % of patients, 43.7 % of controls). However, all the patients with motor complications (n = 28) showed quantifiable levels of ATP13A2, that positively correlated with MDS-UPDRS (total, parts III and IV), and LEDD (p < 0.05). Dyskinetic patients showed the highest LEDD values (p < 0.05). The histological study revealed: a) ATP13A2 staining was very intense in duct cells and vascular endothelium, and b) two patterns of ATP13A2-positive deposits are observed: rounded inclusions of 10–20 µm in diameter located in the interlobular tissue of the patients, and amorphous aggregates inside duct lumen in controls and patients. Conclusions The sensitivity of the ELISA assay was a major limitation for quantifying ATP13A2. However, salivary ATP13A2 was detected in all patients with motor complications, where a direct relationship among ATP13A2 concentration, levodopa equivalent daily dose, and MDS-UPDRS was found. Therefore, salivary ATP13A2 might be a reliable index of therapy-induced motor complications. ATP13A2 was expressed by rounded inclusions in the submandibulary gland of patients. This is the first description of ATP13A2-positive inclusions outside the nervous system.
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Santos-Lobato BL, Gardinassi LG, Bortolanza M, Peti APF, Pimentel ÂV, Faccioli LH, Del-Bel EA, Tumas V. Metabolic Profile in Plasma AND CSF of LEVODOPA-induced Dyskinesia in Parkinson's Disease: Focus on Neuroinflammation. Mol Neurobiol 2021; 59:1140-1150. [PMID: 34855116 DOI: 10.1007/s12035-021-02625-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 10/27/2021] [Indexed: 12/17/2022]
Abstract
The existence of few biomarkers and the lack of a better understanding of the pathophysiology of levodopa-induced dyskinesia (LID) in Parkinson's disease (PD) require new approaches, as the metabolomic analysis, for discoveries. We aimed to identify a metabolic profile associated with LID in patients with PD in an original cohort and to confirm the results in an external cohort (BioFIND). In the original cohort, plasma and CSF were collected from 20 healthy controls, 23 patients with PD without LID, and 24 patients with PD with LID. LC-MS/MS and metabolomics data analysis were used to perform untargeted metabolomics. Untargeted metabolomics data from the BioFIND cohort were analyzed. We identified a metabolic profile associated with LID in PD, composed of multiple metabolic pathways. In particular, the dysregulation of the glycosphingolipid metabolic pathway was more related to LID and was strongly associated with the severity of dyskinetic movements. Furthermore, bile acid biosynthesis metabolites simultaneously found in plasma and CSF have distinguished patients with LID from other participants. Data from the BioFIND cohort confirmed dysregulation in plasma metabolites from the bile acid biosynthesis pathway. There is a distinct metabolic profile associated with LID in PD, both in plasma and CSF, which may be associated with the dysregulation of lipid metabolism and neuroinflammation.
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Affiliation(s)
- Bruno L Santos-Lobato
- Department of Neurosciences and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, São Paulo, CEP: 14049-900, Brazil.,Laboratório de Neuropatologia Experimental, Federal University of Pará, Belém, PA, Brazil
| | - Luiz Gustavo Gardinassi
- Department of Biosciences and Technology, Institute of Tropical Pathology and Public Health, Federal University of Goiás, Goiânia, GO, Brazil
| | - Mariza Bortolanza
- Department of Basic and Oral Biology, Faculty of Odontology of Ribeirão Preto, University of São Paulo, Av do Café, S/N, Ribeirão Preto, São Paulo, CEP: 14049-900, Brazil
| | - Ana Paula Ferranti Peti
- Department of Clinical Analysis, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Ângela V Pimentel
- Department of Neurosciences and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, São Paulo, CEP: 14049-900, Brazil
| | - Lúcia Helena Faccioli
- Department of Clinical Analysis, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Elaine A Del-Bel
- Department of Basic and Oral Biology, Faculty of Odontology of Ribeirão Preto, University of São Paulo, Av do Café, S/N, Ribeirão Preto, São Paulo, CEP: 14049-900, Brazil.
| | - Vitor Tumas
- Department of Neurosciences and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, São Paulo, CEP: 14049-900, Brazil.
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13
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Albillos SM, Montero O, Calvo S, Solano-Vila B, Trejo JM, Cubo E. Plasma acyl-carnitines, bilirubin, tyramine and tetrahydro-21-deoxycortisol in Parkinson's disease and essential tremor. A case control biomarker study. Parkinsonism Relat Disord 2021; 91:167-172. [PMID: 34649109 DOI: 10.1016/j.parkreldis.2021.09.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 09/12/2021] [Accepted: 09/18/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND AND PURPOSE Given the overlapping clinical manifestations and pathology, the differentiation between essential tremor (ET) and Parkinson's disease (PD) is difficult. Our aims were to examine the plasma metabolomics profiling and their association with motor and non-motor symptoms (NMS) in patients with PD, and to determine differences between de novo PD compared to moderate-advanced PD vs. controls and patients with ET. METHODS Plasma samples were collected from 137 subjects including 35 age matched controls, 29 NOVO-PD, 35 PD and 38 ET patients. PD severity, motor and NMS including cognitive function were assessed using the UPDRS, NMS and PD cognitive rating scales, respectively. Metabolomics analysis was performed by UPLC-ESI-QToF-MS followed by unsupervised multivariate statistics. The area under the curve of the biomarkers according to distribution of their concentrations and the diagnosis of PD (NOVO-PD, advanced PD) vs ET and healthy controls was used as a measurement of diagnostic ability. RESULTS Several acyl-carnitines, bilirubin, tyramine and tetrahydro-21-deoxycortisol (THS) presented good predictive accuracy (AUC higher than 0.8) for differentiating de novo PD and advanced PD from controls and ET, suggesting an alteration in the lipid oxidation pathway. In multivariate regression analysis, metabolite levels were not significantly associated with motor and NMS severity in PD. CONCLUSIONS Diverse acyl-carnitines, bilirubin, tyramine and some adrenal gland derived metabolites are suggested as potential biomarkers able to distinguish between PD from controls and ET.
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Affiliation(s)
- Silvia M Albillos
- University of Burgos, Area of Biochemistry and Molecular Biology, Spain
| | - Olimpio Montero
- Institute of Biology and Molecular Genetics (IBGM), Spanish National Research Council (CSIC), Valladolid, Spain
| | - Sara Calvo
- University Hospital of Burgos, Research Unit, Spain
| | | | - José M Trejo
- University Hospital of Burgos, Department of Neurology, Spain
| | - Esther Cubo
- University Hospital of Burgos, Department of Neurology, Spain.
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14
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Comprehensive subtyping of Parkinson's disease patients with similarity fusion: a case study with BioFIND data. NPJ PARKINSONS DISEASE 2021; 7:83. [PMID: 34535682 PMCID: PMC8448859 DOI: 10.1038/s41531-021-00228-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 08/30/2021] [Indexed: 12/28/2022]
Abstract
Parkinson’s disease (PD) is a complex neurodegenerative disorder with diverse clinical manifestations. To better understand this disease, research has been done to categorize, or subtype, patients, using an array of criteria derived from clinical assessments and biospecimen analyses. In this study, using data from the BioFIND cohort, we aimed at identifying subtypes of moderate-to-advanced PD via comprehensively considering motor and non-motor manifestations. A total of 103 patients were included for analysis. Through the use of a patient-wise similarity matrix fusion technique and hierarchical agglomerative clustering analysis, three unique subtypes emerged from the clustering results. Subtype I, comprised of 60 patients (~58.3%), was characterized by mild symptoms, both motor and non-motor. Subtype II, comprised of 20 (~19.4%) patients, was characterized by an intermediate severity, with a high tremor score and mild non-motor symptoms. Subtype III, comprised of 23 (~22.3%) patients, was characterized by more severe motor and non-motor symptoms. These subtypes show statistically significant differences when looking at motor (on and off medication) clinical features and non-motor clinical features, while there was no clear difference in demographics, biomarker levels, and genetic risk scores.
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15
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Fernández-Espejo E, Rodríguez de Fonseca F, Suárez J, Tolosa E, Vilas D, Aldecoa I, Berenguer J, Damas-Hermoso F. Native α-Synuclein, 3-Nitrotyrosine Proteins, and Patterns of Nitro-α-Synuclein-Immunoreactive Inclusions in Saliva and Submandibulary Gland in Parkinson's Disease. Antioxidants (Basel) 2021; 10:antiox10050715. [PMID: 34062880 PMCID: PMC8147273 DOI: 10.3390/antiox10050715] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 04/19/2021] [Accepted: 04/28/2021] [Indexed: 11/16/2022] Open
Abstract
Background. Salivary α-synuclein (aSyn) and its nitrated form, or 3-nitrotyrosine-α-synuclein (3-NT-αSyn), hold promise as biomarkers for idiopathic Parkinson's disease (IPD). Nitrative stress that is characterized by an excess of 3-nitrotyrosine proteins (3-NT-proteins) has been proposed as a pathogenic mechanism in IPD. The objective is to study the pathological role of native αSyn, 3-NT-αSyn, and 3-NT-proteins in the saliva and submandibulary glands of patients with IPD. Methods. The salivary and serum αSyn and 3-NT-proteins concentration is evaluated with ELISA in patients and controls. Correlations of αSyn and 3-NT-proteins content with clinical features of the disease are examined. Immunohistochemical 3-NT-αSyn expression in submandibulary gland sections is analyzed. Results. (a) Salivary concentration and saliva/serum ratios of native αSyn and 3-NT-proteins are similar in patients and controls; (b) salivary αSyn and 3-NT-proteins do not correlate with any clinical feature; and (c) three patterns of 3-NT-αSyn-positive inclusions are observed on histological sections: rounded "Lewy-type" aggregates of 10-25 µm in diameter, coarse deposits with varied morphology, and spheroid inclusions or bodies of 3-5 µm in diameter. "Lewy-type" and coarse inclusions are observed in the interlobular connective tissue of the gland, and small-sized bodies are located within the cytoplasm of duct cells. "Lewy-type" inclusions are only observed in patients, and the remaining patterns of inclusions are observed in both the patients and controls. Conclusions. The patients' saliva presents a similar concentration of native αSyn and 3-nitrotyrosine-proteins than that of the controls, and no correlations with clinical features are found. These findings preclude the utility of native αSyn in the saliva as a biomarker, and they indicate the absence of nitrative stress in the saliva and serum of patients. As regards nitrated αSyn, "Lewy-type" inclusions expressing 3-NT-αSyn are observed in the patients, not the controls-a novel finding that suggests that a biopsy of the submandibulary gland, if proven safe, could be a useful technique for diagnosing IPD. Finally, to our knowledge, this is also the first description of 3-NT-αSyn-immunoreactive intracytoplasmic bodies in cells that are located outside the nervous system. These intracytoplasmic bodies are present in duct cells of submandibulary gland sections from all subjects regardless of their pathology, and they can represent an aging or involutional change. Further immunostaining studies with different antibodies and larger samples are needed to validate the data.
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Affiliation(s)
- Emilio Fernández-Espejo
- Reial Acadèmia de Medicina de Catalunya, 08001 Barcelona, Spain
- Red Andaluza de Investigación Clínica y Traslacional en Neurología (Neuro-RECA), Laboratorio de Medicina Regenerativa, Hospital Regional Universitario, 29010 Málaga, Spain
- Correspondence: (E.F.-E.); (F.R.d.F.); Tel.: +34-954-184-712 (E.F.-E.); +34-952-614-012 (F.R.d.F.)
| | - Fernando Rodríguez de Fonseca
- Unidad de Gestión Clínica de Salud Mental, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Regional Universitario, 29010 Málaga, Spain
- Correspondence: (E.F.-E.); (F.R.d.F.); Tel.: +34-954-184-712 (E.F.-E.); +34-952-614-012 (F.R.d.F.)
| | - Juan Suárez
- Departamento de Anatomía Humana, Medicina Legal e Historia de la Ciencia, IBIMA, Universidad de Málaga, 29071 Málaga, Spain;
| | - Eduardo Tolosa
- Unidad de Parkinson y movimientos anormales, Servicio de Neurología, Hospital Clínic, 08036 Barcelona, Spain;
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, 08036 Barcelona, Spain
| | - Dolores Vilas
- Servicio de Neurología, Hospital Universitari Germans Trias i Pujol, 08916 Badalona, Spain;
| | - Iban Aldecoa
- Centro de Diagnóstico Biomédico, Departamento de Patología, Hospital Clinic de Barcelona, Universitat de Barcelona, 08036 Barcelona, Spain;
- Banco de Tejidos Neurológicos del Biobanco, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Joan Berenguer
- Servicio de Radiología, Hospital Clínic, 08036 Barcelona, Spain;
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Fernández-Espejo E, Rodriguez de Fonseca F, Suárez J, Martín de Pablos Á. Cerebrospinal fluid lactoperoxidase level is enhanced in idiopathic Parkinson's disease, and correlates with levodopa equivalent daily dose. Brain Res 2021; 1761:147411. [PMID: 33676939 DOI: 10.1016/j.brainres.2021.147411] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 02/22/2021] [Accepted: 03/01/2021] [Indexed: 01/08/2023]
Abstract
Lactoperoxidase (LPO) is proposed to play a role in the pathogenesis of Parkinson's disease (PD). This enzyme has been reported to be enhanced in the cerebrospinal fluid (CSF) in parkinsonian patients. The objective was to look at the relationship of LPO in the CSF and serum with clinical features of idiopathic PD. LPO concentration was analyzed through ELISA techniques. Correlation of CSF or serum LPO and MDS-UPDRS, dopaminergic medication, and other clinical parameters was examined. The findings revealed that LPO concentration in the CSF, not serum, was found to be elevated in patients with PD relative to controls (p < 0.001). CSF LPO concentration negatively correlated with MDS-UPDRS part-IV score (p < .0001), a rating scale that allows evaluating motor complications. CSF LPO level inversely correlated with the dose intensity of the dopaminergic medication regimen, as evaluated with levodopa equivalent dose or LED (mg/day; p < .0001). LED value positively correlated with MDS-UPDRS part-IV score (p < .0001). To sum up, the findings indicate that CSF LPO is found to be elevated in the CSF of PD patients, and this enzyme holds promise as potential biomarker for diagnosis of PD. Increasing the dose intensity of the dopaminergic medication regimen attenuates the elevation in LPO levels in the CSF, and it facilitates the development of motor complications in patients. The pathophysiological mechanisms that seem to be responsible for LPO increase would include dopamine deficiency, oxidative stress, and less likely, microbial infection.
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Affiliation(s)
- Emilio Fernández-Espejo
- Reial Acadèmia de Medicina de Catalunya, 08010 Barcelona, Spain; Red Andaluza de Investigación Clínica y Traslacional en Neurología (Neuro-RECA), Laboratorio de Medicina Regenerativa, Hospital Regional Universitario, 29010 Málaga, Spain.
| | - Fernando Rodriguez de Fonseca
- Unidad de Gestión Clínica de Salud Mental, Hospital Regional Universitario, Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain; Red Andaluza de Investigación Clínica y Traslacional en Neurología (Neuro-RECA), Laboratorio de Medicina Regenerativa, Hospital Regional Universitario, 29010 Málaga, Spain
| | - Juan Suárez
- Unidad de Gestión Clínica de Neurociencias, Hospital Regional Universitario, Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain; Red Andaluza de Investigación Clínica y Traslacional en Neurología (Neuro-RECA), Laboratorio de Medicina Regenerativa, Hospital Regional Universitario, 29010 Málaga, Spain
| | - Ángel Martín de Pablos
- Departamento de Anestesiología, Servicio de Cirugía, Hospital Universitario Macarena, 41009 Sevilla, Spain
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17
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Kakar RS, Pastor JV, Moe OW, Ambrosio F, Castaldi D, Sanders LH. Peripheral Klotho and Parkinson's Disease. Mov Disord 2021; 36:1274-1276. [PMID: 33629770 DOI: 10.1002/mds.28530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 01/25/2021] [Indexed: 11/06/2022] Open
Affiliation(s)
- Rumit S Kakar
- Old Dominion University Norfolk, Norfolk, Virginia, USA
| | - Johanne V Pastor
- University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Orson W Moe
- University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | | | | | - Laurie H Sanders
- Department of Neurology, Duke University Medical Center, Durham, North Carolina, USA
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18
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Orrù CD, Ma TC, Hughson AG, Groveman BR, Srivastava A, Galasko D, Angers R, Downey P, Crawford K, Hutten SJ, Kang UJ, Caughey B. A rapid α-synuclein seed assay of Parkinson's disease CSF panel shows high diagnostic accuracy. Ann Clin Transl Neurol 2021; 8:374-384. [PMID: 33373501 PMCID: PMC7886040 DOI: 10.1002/acn3.51280] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 11/18/2020] [Accepted: 12/02/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Assays that specifically measure α-synuclein seeding activity in biological fluids could revolutionize the diagnosis of Parkinson's disease. Recent improvements in α-synuclein real-time quaking-induced conversion assays of cerebrospinal fluid have dramatically reduced reaction times from 5-13 days down to 1-2 days. OBJECTIVE To test our improved assay against a panel of cerebrospinal fluid specimens from patients with Parkinson's disease and healthy controls from the MJ Fox Foundation/NINDS BioFIND collection. METHODS Specimens collected from healthy controls and patients with clinically typical moderate-to-advanced Parkinson's disease were tested without prior knowledge of disease status. Correlative analyses between assay parameters and clinical measures were performed by an independent investigator. RESULTS BioFIND samples gave positive signals in 105/108 (97%) Parkinson's disease cases versus 11/85 (13%) healthy controls. Receiver operating characteristic analyses of diagnosis of cases versus healthy controls gave areas under the curve of 95%. Beyond binary positive/negative determinations, only weak correlations were observed between various assay response parameters and Parkinson's disease clinical measures or other cerebrospinal fluid analytes. Of note, REM sleep behavioral disorder questionnaire scores correlated with the reaction times needed to reach 50% maximum fluorescence. Maximum fluorescence was inversely correlated with Unified Parkinson's Disease Rating Scale motor scores, which was driven by the patients without REM sleep behavioral disorder. CONCLUSIONS Our improved α-synuclein seed amplification assay dramatically reduces the time needed to diagnose Parkinson's disease while maintaining the high-performance standards associated with previous α-synuclein seed assays, supporting the clinical utility of this assay for Parkinson's disease diagnosis.
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Affiliation(s)
- Christina D. Orrù
- Laboratory of Persistent Viral DiseasesRocky Mountain LaboratoriesNational Institute of Allergy and Infectious DiseasesNIHHamiltonMontana
| | - Thong C. Ma
- Department of NeurologyNew York University Grossman School of MedicineNew YorkNew York
| | - Andrew G. Hughson
- Laboratory of Persistent Viral DiseasesRocky Mountain LaboratoriesNational Institute of Allergy and Infectious DiseasesNIHHamiltonMontana
| | - Bradley R. Groveman
- Laboratory of Persistent Viral DiseasesRocky Mountain LaboratoriesNational Institute of Allergy and Infectious DiseasesNIHHamiltonMontana
| | - Ankit Srivastava
- Laboratory of Persistent Viral DiseasesRocky Mountain LaboratoriesNational Institute of Allergy and Infectious DiseasesNIHHamiltonMontana
| | - Douglas Galasko
- Department of NeurosciencesUniversity of California‐San DiegoLa JollaCalifornia
| | | | | | - Karen Crawford
- Laboratory of Neuro ImagingMark and Mary Stevens Neuroimaging and Informatics InstituteKeck School of Medicine of USCUniversity of Southern CaliforniaLos AngelesCalifornia
| | | | - Un Jung Kang
- Department of NeurologyNew York University Grossman School of MedicineNew YorkNew York
| | - Byron Caughey
- Laboratory of Persistent Viral DiseasesRocky Mountain LaboratoriesNational Institute of Allergy and Infectious DiseasesNIHHamiltonMontana
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19
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Tropea TF, Amari N, Han N, Rick J, Suh E, Akhtar RS, Dahodwala N, Deik A, Gonzalez-Alegre P, Hurtig H, Siderowf A, Spindler M, Stern M, Thenganatt MA, Weintraub D, Willis AW, Van Deerlin V, Chen-Plotkin A. Whole Clinic Research Enrollment in Parkinson's Disease: The Molecular Integration in Neurological Diagnosis (MIND) Study. JOURNAL OF PARKINSON'S DISEASE 2021; 11:757-765. [PMID: 33492247 PMCID: PMC8058284 DOI: 10.3233/jpd-202406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
BACKGROUND Observational studies in Parkinson's disease (PD) have focused on relatively small numbers of research participants who are studied extensively. The Molecular Integration in Neurological Diagnosis Initiative at the University of Pennsylvania aims to characterize molecular and clinical features of PD in every patient in a large academic center. OBJECTIVE To determine the feasibility and interest in a global-capture biomarker research protocol. Additionally, to describe the clinical characteristics and GBA and LRRK2 variant carrier status among participants. METHODS All patients at UPenn with a clinical diagnosis of PD were eligible. Informed consent included options for access to the medical record, future recontact, and use of biosamples for additional studies. A blood sample and a completed questionnaire were obtained from participants. Targeted genotyping for four GBA and eight LRRK2 variants was performed, with plasma and DNA banked for future research. RESULTS Between September 2018 and December 2019, 704 PD patients were approached for enrollment; 652 (92.6%) enrolled, 28 (3.97%) declined, and 24 (3.41%) did not meet eligibility criteria. Median age was 69 (IQR 63_75) years, disease duration was 5.41 (IQR 2.49_9.95) years, and 11.10%of the cohort was non-white. Disease risk-associated variants in GBA were identified in 39 participants (5.98%) and in LRRK2 in 16 participants (2.45%). CONCLUSIONS We report the clinical and genetic characteristics of PD patients in an all-comers, global capture protocol from an academic center. Patient interest in participation and yield for identification of GBA and LRRK2 mutation carriers is high, demonstrating feasibility of PD clinic-wide molecular characterization.
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Affiliation(s)
- Thomas F. Tropea
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Noor Amari
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Noah Han
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jacqueline Rick
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - EunRan Suh
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rizwan S. Akhtar
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nabila Dahodwala
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andres Deik
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pedro Gonzalez-Alegre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Howard Hurtig
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew Siderowf
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Meredith Spindler
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Stern
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mary Ann Thenganatt
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Weintraub
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Parkinson’s Disease Research, Education and Clinical Centers (PADRECC), Philadelphia Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Allison W. Willis
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vivianna Van Deerlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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20
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Prevalence and Relationship of Rest Tremor and Action Tremor in Parkinson's Disease. Tremor Other Hyperkinet Mov (N Y) 2020; 10:58. [PMID: 33384882 PMCID: PMC7757606 DOI: 10.5334/tohm.552] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Background: Despite the significance of tremor in Parkinson’s disease (PD) diagnosis, classification, and patient’s quality of life, there is a relative lack of data on prevalence and relationship of different tremor types in PD. Methods: The presence of rest tremor (RT) and action tremor (AT; defined as combination of both postural and kinetic tremor) was determined and RT severity was defined using the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) at baseline in the Progression Marker Initiative (PPMI, n = 423), the Fox Investigation for New Discovery of Biomarkers (BioFIND, n = 118) and the Parkinson’s Disease Biomarkers Program (PDBP, n = 873) cohorts. Results: Across baseline data of all three cohorts, RT prevalence (58.2%) was higher than AT prevalence (39.0%). Patients with RT had significantly higher (Chi-square test, p < 0.05) prevalence of AT compared to patients without RT in the PPMI (40.0% versus 30.1%), BioFIND (48.0% versus 40.0%) and PDBP (49.9% versus 21.0%) cohorts. Furthermore, patients with AT had significantly (Student t-test, p < 0.05) higher RT severity that those without AT in PPMI (5.7 ± 5.4 versus 3.9 ± 3.3), BioFIND, 6.4 ± 6.3 versus 3.8 ± 4.4) and PDBP (6.4 ± 6.6 versus 3.7 ± 4.4) cohorts. In the BioFIND cohort, the prevalence of all types of tremor and their combinations significantly decreased from the off-state to on-state. Discussion: The RT is the most frequent tremor type and present in more than half of the PD patients. However, AT is also present in nearly one-third of the PD patients. Our results also indicate that RT and AT may have cross-interactions in PD, and that dopaminergic treatment influences both RT and AT.
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21
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Su C, Tong J, Wang F. Mining genetic and transcriptomic data using machine learning approaches in Parkinson's disease. NPJ PARKINSONS DISEASE 2020; 6:24. [PMID: 32964109 PMCID: PMC7481248 DOI: 10.1038/s41531-020-00127-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Accepted: 08/13/2020] [Indexed: 01/08/2023]
Abstract
High-throughput techniques have generated abundant genetic and transcriptomic data of Parkinson’s disease (PD) patients but data analysis approaches such as traditional statistical methods have not provided much in the way of insightful integrated analysis or interpretation of the data. As an advanced computational approach, machine learning, which enables people to identify complex patterns and insight from data, has consequently been harnessed to analyze and interpret large, highly complex genetic and transcriptomic data toward a better understanding of PD. In particular, machine learning models have been developed to integrate patient genotype data alone or combined with demographic, clinical, neuroimaging, and other information, for PD outcome study. They have also been used to identify biomarkers of PD based on transcriptomic data, e.g., gene expression profiles from microarrays. This study overviews the relevant literature on using machine learning models for genetic and transcriptomic data analysis in PD, points out remaining challenges, and suggests future directions accordingly. Undoubtedly, the use of machine learning is amplifying PD genetic and transcriptomic achievements for accelerating the study of PD. Existing studies have demonstrated the great potential of machine learning in discovering hidden patterns within genetic or transcriptomic information and thus revealing clues underpinning pathology and pathogenesis. Moving forward, by addressing the remaining challenges, machine learning may advance our ability to precisely diagnose, prognose, and treat PD.
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Affiliation(s)
- Chang Su
- Department of Population Health Sciences, Weill Cornell Medical College, Cornell University, New York, NY USA
| | - Jie Tong
- Department of Mechanical and Aerospace Engineering, New York University, New York, NY USA
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medical College, Cornell University, New York, NY USA
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22
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Candelise N, Baiardi S, Franceschini A, Rossi M, Parchi P. Towards an improved early diagnosis of neurodegenerative diseases: the emerging role of in vitro conversion assays for protein amyloids. Acta Neuropathol Commun 2020; 8:117. [PMID: 32711575 PMCID: PMC7382043 DOI: 10.1186/s40478-020-00990-x] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 07/06/2020] [Indexed: 12/20/2022] Open
Abstract
Tissue accumulation of abnormal aggregates of amyloidogenic proteins such as prion protein, α-synuclein, and tau represents the hallmark of most common neurodegenerative disorders and precedes the onset of symptoms by years. As a consequence, the sensitive and specific detection of abnormal forms of these proteins in patients' accessible tissues or fluids as biomarkers may have a significant impact on the clinical diagnosis of these disorders. By exploiting seeded polymerization propagation mechanisms to obtain cell-free reactions that allow highly amplified detection of these amyloid proteins, novel emerging in vitro techniques, such as the real-time quaking-induced conversion assay (RT-QuIC) have paved the way towards this important goal. Given its high accuracy in identifying misfolded forms of prion protein from Creutzfeldt-Jakob disease (CJD) CSF, RT-QuIC has already been included in the diagnostic criteria for the clinical diagnosis of sporadic CJD, the most common human prion disease. By showing that this assay may also accurately discriminate between Lewy body disorders and other forms of parkinsonisms or dementias, more recent studies strongly suggested that CSF RT-QuIC can also be successfully applied to synucleinopathies. Finally, preliminary encouraging data also suggested that CSF RT-QuIC might also work for tau protein, and accurately distinguish between 3R- and 4R tauopathies, including Pick's disease, progressive supranuclear palsy, and corticobasal degeneration. Here we will review the state of the art of cell-free aggregation assays, their current diagnostic value and putative limitations, and the future perspectives for their expanded use in clinical practice.
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Affiliation(s)
- Niccolò Candelise
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Simone Baiardi
- IRCCS, Istituto delle Scienze Neurologiche di Bologna, Ospedale Bellaria, Via Altura 1/8, 40139 Bologna, Italy
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Alessia Franceschini
- IRCCS, Istituto delle Scienze Neurologiche di Bologna, Ospedale Bellaria, Via Altura 1/8, 40139 Bologna, Italy
| | - Marcello Rossi
- IRCCS, Istituto delle Scienze Neurologiche di Bologna, Ospedale Bellaria, Via Altura 1/8, 40139 Bologna, Italy
| | - Piero Parchi
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
- IRCCS, Istituto delle Scienze Neurologiche di Bologna, Ospedale Bellaria, Via Altura 1/8, 40139 Bologna, Italy
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23
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van Steenoven I, Koel-Simmelink MJA, Vergouw LJM, Tijms BM, Piersma SR, Pham TV, Bridel C, Ferri GL, Cocco C, Noli B, Worley PF, Xiao MF, Xu D, Oeckl P, Otto M, van der Flier WM, de Jong FJ, Jimenez CR, Lemstra AW, Teunissen CE. Identification of novel cerebrospinal fluid biomarker candidates for dementia with Lewy bodies: a proteomic approach. Mol Neurodegener 2020; 15:36. [PMID: 32552841 PMCID: PMC7301448 DOI: 10.1186/s13024-020-00388-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Accepted: 06/08/2020] [Indexed: 12/15/2022] Open
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.
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Affiliation(s)
- Inger van Steenoven
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HV Amsterdam, The Netherlands
| | - Marleen J. A. Koel-Simmelink
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Leonie J. M. Vergouw
- Alzheimer Center Erasmus MC, Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HV Amsterdam, The Netherlands
| | - Sander R. Piersma
- OncoProteomics Laboratory, Department of Medical Oncology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Thang V. Pham
- OncoProteomics Laboratory, Department of Medical Oncology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Claire Bridel
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Gian-Luca Ferri
- NEF-laboratory, Department of Biomedical Sciences, University of Cagliari, Monserrato, Italy
| | - Cristina Cocco
- NEF-laboratory, Department of Biomedical Sciences, University of Cagliari, Monserrato, Italy
| | - Barbara Noli
- NEF-laboratory, Department of Biomedical Sciences, University of Cagliari, Monserrato, Italy
| | - Paul F. Worley
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Mei-Fang Xiao
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Desheng Xu
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Patrick Oeckl
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Markus Otto
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HV Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frank Jan de Jong
- Alzheimer Center Erasmus MC, Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Connie R. Jimenez
- OncoProteomics Laboratory, Department of Medical Oncology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Afina W. Lemstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HV Amsterdam, The Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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24
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Chaudhuri KR, Jenner P, Antonini A. Dyskinesia Matters: But Not as Much as It Used to. Mov Disord 2020; 35:900-901. [PMID: 32415717 DOI: 10.1002/mds.28047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 03/03/2020] [Indexed: 11/07/2022] Open
Affiliation(s)
- K Ray Chaudhuri
- King's College London, Department of Neurosciences, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom
- Parkinson's Foundation Centre of Excellence, King's College Hospital, London, United Kingdom
| | - Peter Jenner
- Neurodegenerative Diseases Research Group, School of Cancer and Pharmaceutical Sciences, Faculty of Life Science and Medicine, King's College London, London, United Kingdom
| | - Angelo Antonini
- Department of Neuroscience, University of Padova, Padova, Italy
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25
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Rotunno MS, Lane M, Zhang W, Wolf P, Oliva P, Viel C, Wills AM, Alcalay RN, Scherzer CR, Shihabuddin LS, Zhang K, Sardi SP. Cerebrospinal fluid proteomics implicates the granin family in Parkinson's disease. Sci Rep 2020; 10:2479. [PMID: 32051502 PMCID: PMC7015906 DOI: 10.1038/s41598-020-59414-4] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 01/24/2020] [Indexed: 12/25/2022] Open
Abstract
Parkinson's disease, the most common age-related movement disorder, is a progressive neurodegenerative disease with unclear etiology. Better understanding of the underlying disease mechanism(s) is an urgent need for the development of disease-modifying therapeutics. Limited studies have been performed in large patient cohorts to identify protein alterations in cerebrospinal fluid (CSF), a proximal site to pathology. We set out to identify disease-relevant protein changes in CSF to gain insights into the etiology of Parkinson's disease and potentially assist in disease biomarker identification. In this study, we used liquid chromatography-tandem mass spectrometry in data-independent acquisition (DIA) mode to identify Parkinson's-relevant biomarkers in cerebrospinal fluid. We quantified 341 protein groups in two independent cohorts (n = 196) and a longitudinal cohort (n = 105 samples, representing 40 patients) consisting of Parkinson's disease and healthy control samples from three different sources. A first cohort of 53 Parkinson's disease and 72 control samples was analyzed, identifying 53 proteins with significant changes (p < 0.05) in Parkinson's disease relative to healthy control. We established a biomarker signature and multiple protein ratios that differentiate Parkinson's disease from healthy controls and validated these results in an independent cohort. The second cohort included 28 Parkinson's disease and 43 control samples. Independent analysis of these samples identified 41 proteins with significant changes. Evaluation of the overlapping changes between the two cohorts identified 13 proteins with consistent and significant changes (p < 0.05). Importantly, we found the extended granin family proteins as reduced in disease, suggesting a potential common mechanism for the biological reduction in monoamine neurotransmission in Parkinson's patients. Our study identifies several novel protein changes in Parkinson's disease cerebrospinal fluid that may be exploited for understanding etiology of disease and for biomarker development.
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Affiliation(s)
- Melissa S Rotunno
- Rare and Neurologic Diseases Therapeutic Area, Sanofi, Inc., Framingham, MA, 01701, USA.,Biomarkers and Bioanalytics, Translational Sciences, Sanofi, Inc., Framingham, MA, 01701, USA
| | - Monica Lane
- Biomarkers and Bioanalytics, Translational Sciences, Sanofi, Inc., Framingham, MA, 01701, USA
| | - Wenfei Zhang
- Translational Medicine, Sanofi, Inc., Framingham, MA, 01701, USA
| | - Pavlina Wolf
- Biomarkers and Bioanalytics, Translational Sciences, Sanofi, Inc., Framingham, MA, 01701, USA.,Editas Medicine, Cambridge, MA, 02141, USA
| | - Petra Oliva
- Biomarkers and Bioanalytics, Translational Sciences, Sanofi, Inc., Framingham, MA, 01701, USA.,ARCHIMED Life Sciences GmbH, Leberstraße 20/2, 1110, Vienna, Austria
| | - Catherine Viel
- Rare and Neurologic Diseases Therapeutic Area, Sanofi, Inc., Framingham, MA, 01701, USA
| | - Anne-Marie Wills
- Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Roy N Alcalay
- Department of Neurology, Columbia University, New York, NY, 10032-3784, USA
| | - Clemens R Scherzer
- Precision Neurology Program, Harvard Medical School, Brigham & Women's Hospital, Boston, MA, 02115, USA.,Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA.,APDA Center for Advance Parkinson Research, Harvard Medical School, Brigham & Women's Hospital, Boston, MA, 02115, USA
| | - Lamya S Shihabuddin
- Rare and Neurologic Diseases Therapeutic Area, Sanofi, Inc., Framingham, MA, 01701, USA
| | - Kate Zhang
- Biomarkers and Bioanalytics, Translational Sciences, Sanofi, Inc., Framingham, MA, 01701, USA.,Editas Medicine, Cambridge, MA, 02141, USA
| | - S Pablo Sardi
- Rare and Neurologic Diseases Therapeutic Area, Sanofi, Inc., Framingham, MA, 01701, USA.
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Reddy SP, Socal MP, Rieder CRDM, Schumacher-Schuh AF. Parkinson's disease-associated dyskinesia in countries with low access to levodopa-sparing regimens. Mov Disord 2019; 34:1929-1930. [PMID: 31845765 DOI: 10.1002/mds.27891] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 09/06/2019] [Accepted: 09/18/2019] [Indexed: 01/26/2023] Open
Affiliation(s)
- Sumanth P Reddy
- Department of Global Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Mariana P Socal
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | | | - Artur Francisco Schumacher-Schuh
- Departamento de Farmacologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.,Serviço de Neurologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
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27
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Abd Elhadi S, Grigoletto J, Poli M, Arosio P, Arkadir D, Sharon R. α-Synuclein in blood cells differentiates Parkinson's disease from healthy controls. Ann Clin Transl Neurol 2019; 6:2426-2436. [PMID: 31742923 PMCID: PMC6917335 DOI: 10.1002/acn3.50944] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 10/05/2019] [Accepted: 10/09/2019] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVE To determine whether blood cells expressed α-Syn can differentiate Parkinson's disease (PD) from healthy controls (HC). METHODS The concentrations of α-Syn were determined in samples of blood cell pellets using a quantitative Lipid-ELISA assay. In addition, the levels of total protein, hemoglobin, iron and H-ferritin were determined. The study includes samples from the Biofind cohort (n = 46 PD and 45 HC) and results were validated with an additional cohort (n = 35 PD and 28 HC). RESULTS A composite biomarker consisting of the concentrations of total α-Syn, proteinase-K resistant (PKres ) α-Syn and phospho-Serine 129 α-Syn (PSer 129), is designed based on the analysis of the discovery BioFIND cohort. This composite biomarker differentiates a PD subgroup, presenting motor symptoms without dementia from a HC group, with a convincing accuracy, represented by an AUC = 0.81 (95% CI, 0.71 to 0.92). Closely similar results were obtained for the validation cohort, that is, AUC = 0.81, (95% CI, 0.70 to 0.94). INTERPRETATION Our results demonstrate the potential usefulness of blood cells expressed α-Syn as a biomarker for PD.
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Affiliation(s)
- Suaad Abd Elhadi
- Department of Biochemistry and Molecular BiologyIMRICThe Hebrew University‐Hadassah Medical SchoolEin Kerem9112001JerusalemIsrael
| | - Jessica Grigoletto
- Department of Biochemistry and Molecular BiologyIMRICThe Hebrew University‐Hadassah Medical SchoolEin Kerem9112001JerusalemIsrael
| | - Maura Poli
- Laboratory of Molecular BiologyDepartment of Molecular and Translational MedicineUniversity of BresciaBresciaItaly
| | - Paolo Arosio
- Laboratory of Molecular BiologyDepartment of Molecular and Translational MedicineUniversity of BresciaBresciaItaly
| | - David Arkadir
- Department of NeurologyHadassah‐Hebrew University Medical CenterJerusalemIsrael
| | - Ronit Sharon
- Department of Biochemistry and Molecular BiologyIMRICThe Hebrew University‐Hadassah Medical SchoolEin Kerem9112001JerusalemIsrael
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28
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Biomarkers for Parkinson's Disease: How Good Are They? Neurosci Bull 2019; 36:183-194. [PMID: 31646434 DOI: 10.1007/s12264-019-00433-1] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 09/17/2019] [Indexed: 12/13/2022] Open
Abstract
Parkinson's disease (PD) is a complex neurodegenerative disorder with no cure in sight. Clinical challenges of the disease include the inability to make a definitive diagnosis at the early stages and difficulties in predicting the disease progression. The unmet demand to identify reliable biomarkers for early diagnosis and management of the disease course of PD has attracted a lot of attention. However, only a few reported candidate biomarkers have been tried in clinical practice at the present time. Studies on PD biomarkers have often overemphasized the discovery of novel identity, whereas efforts to further evaluate such candidates are rare. Therefore, we update the new development of biomarker discovery in PD and discuss the standard process in the evaluation and assessment of the diagnostic or prognostic value of the identified potential PD biomarkers in this review article. Recent developments in combined biomarkers and the current status of clinical trials of biomarkers as outcome measures are also discussed. We believe that the combination of different biomarkers might enhance the specificity and sensitivity over a single measure that might not be sufficient for such a multiplex disease.
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Zanfardino M, Franzese M, Pane K, Cavaliere C, Monti S, Esposito G, Salvatore M, Aiello M. Bringing radiomics into a multi-omics framework for a comprehensive genotype-phenotype characterization of oncological diseases. J Transl Med 2019; 17:337. [PMID: 31590671 PMCID: PMC6778975 DOI: 10.1186/s12967-019-2073-2] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 09/18/2019] [Indexed: 02/07/2023] Open
Abstract
Genomic and radiomic data integration, namely radiogenomics, can provide meaningful knowledge in cancer diagnosis, prognosis and treatment. Despite several data structures based on multi-layer architecture proposed to combine multi-omic biological information, none of these has been designed and assessed to include radiomic data as well. To meet this need, we propose to use the MultiAssayExperiment (MAE), an R package that provides data structures and methods for manipulating and integrating multi-assay experiments, as a suitable tool to manage radiogenomic experiment data. To this aim, we first examine the role of radiogenomics in cancer phenotype definition, then the current state of radiogenomics data integration in public repository and, finally, challenges and limitations of including radiomics in MAE, designing an extended framework and showing its application on a case study from the TCGA-TCIA archives. Radiomic and genomic data from 91 patients have been successfully integrated in a single MAE object, demonstrating the suitability of the MAE data structure as container of radiogenomic data.
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30
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Posavi M, Diaz-Ortiz M, Liu B, Swanson CR, Skrinak RT, Hernandez-Con P, Amado DA, Fullard M, Rick J, Siderowf A, Weintraub D, McCluskey L, Trojanowski JQ, Dewey RB, Huang X, Chen-Plotkin AS. Characterization of Parkinson's disease using blood-based biomarkers: A multicohort proteomic analysis. PLoS Med 2019; 16:e1002931. [PMID: 31603904 PMCID: PMC6788685 DOI: 10.1371/journal.pmed.1002931] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Accepted: 09/05/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Parkinson's disease (PD) is a progressive neurodegenerative disease affecting about 5 million people worldwide with no disease-modifying therapies. We sought blood-based biomarkers in order to provide molecular characterization of individuals with PD for diagnostic confirmation and prediction of progression. METHODS AND FINDINGS In 141 plasma samples (96 PD, 45 neurologically normal control [NC] individuals; 45.4% female, mean age 70.0 years) from a longitudinally followed Discovery Cohort based at the University of Pennsylvania (UPenn), we measured levels of 1,129 proteins using an aptamer-based platform. We modeled protein plasma concentration (log10 of relative fluorescence units [RFUs]) as the effect of treatment group (PD versus NC), age at plasma collection, sex, and the levodopa equivalent daily dose (LEDD), deriving first-pass candidate protein biomarkers based on p-value for PD versus NC. These candidate proteins were then ranked by Stability Selection. We confirmed findings from our Discovery Cohort in a Replication Cohort of 317 individuals (215 PD, 102 NC; 47.9% female, mean age 66.7 years) from the multisite, longitudinally followed National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) Cohort. Analytical approach in the Replication Cohort mirrored the approach in the Discovery Cohort: each protein plasma concentration (log10 of RFU) was modeled as the effect of group (PD versus NC), age at plasma collection, sex, clinical site, and batch. Of the top 10 proteins from the Discovery Cohort ranked by Stability Selection, four associations were replicated in the Replication Cohort. These blood-based biomarkers were bone sialoprotein (BSP, Discovery false discovery rate [FDR]-corrected p = 2.82 × 10-2, Replication FDR-corrected p = 1.03 × 10-4), osteomodulin (OMD, Discovery FDR-corrected p = 2.14 × 10-2, Replication FDR-corrected p = 9.14 × 10-5), aminoacylase-1 (ACY1, Discovery FDR-corrected p = 1.86 × 10-3, Replication FDR-corrected p = 2.18 × 10-2), and growth hormone receptor (GHR, Discovery FDR-corrected p = 3.49 × 10-4, Replication FDR-corrected p = 2.97 × 10-3). Measures of these proteins were not significantly affected by differences in sample handling, and they did not change comparing plasma samples from 10 PD participants sampled both on versus off dopaminergic medication. Plasma measures of OMD, ACY1, and GHR differed in PD versus NC but did not differ between individuals with amyotrophic lateral sclerosis (ALS, n = 59) versus NC. In the Discovery Cohort, individuals with baseline levels of GHR and ACY1 in the lowest tertile were more likely to progress to mild cognitive impairment (MCI) or dementia in Cox proportional hazards analyses adjusting for age, sex, and disease duration (hazard ratio [HR] 2.27 [95% CI 1.04-5.0, p = 0.04] for GHR, and HR 3.0 [95% CI 1.24-7.0, p = 0.014] for ACY1). GHR's association with cognitive decline was confirmed in the Replication Cohort (HR 3.6 [95% CI 1.20-11.1, p = 0.02]). The main limitations of this study were its reliance on the aptamer-based platform for protein measurement and limited follow-up time available for some cohorts. CONCLUSIONS In this study, we found that the blood-based biomarkers BSP, OMD, ACY1, and GHR robustly associated with PD across multiple clinical sites. Our findings suggest that biomarkers based on a peripheral blood sample may be developed for both disease characterization and prediction of future disease progression in PD.
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Affiliation(s)
- Marijan Posavi
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Maria Diaz-Ortiz
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Benjamine Liu
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Christine R Swanson
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- National Institute of Neurological Disease and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America
| | - R Tyler Skrinak
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Pilar Hernandez-Con
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Defne A Amado
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Michelle Fullard
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Jacqueline Rick
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Andrew Siderowf
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Daniel Weintraub
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Leo McCluskey
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Richard B Dewey
- Department of Neurology and Neurotherapeutics, Clinical Center for Movement Disorders at the University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Xuemei Huang
- Department of Neurology, Penn State College of Medicine, Hershey, Pennsylvania, United States of America
| | - Alice S Chen-Plotkin
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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31
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Luo L, Andrews H, Alcalay RN, Poyraz FC, Boehme AK, Goldman JG, Xie T, Tuite P, Henchcliffe C, Hogarth P, Amara AW, Frank S, Sutherland M, Kopil C, Naito A, Kang UJ. Motor phenotype classification in moderate to advanced PD in BioFIND study. Parkinsonism Relat Disord 2019; 65:178-183. [PMID: 31255537 DOI: 10.1016/j.parkreldis.2019.06.017] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 06/17/2019] [Accepted: 06/22/2019] [Indexed: 01/22/2023]
Abstract
BACKGROUND Three motor phenotypes have been described in PD: postural instability and gait difficulty (PIGD) dominant, tremor-dominant (TD), and indeterminate (IND) subtype. These phenotypes have been associated with different cognitive trajectories, motor outcomes, and biomarkers profiles. However, whether motor subtype classifications change with treatment and disease progression is not well established. METHODS To evaluate motor subtype ratio changes, we used the chi-square test for the off and on state motor subtypes for 115 PD participants in the BioFIND study and used repeated-measures analyses to evaluate longitudinal changes in 162 PD participants with five-year follow-up in the PPMI study. RESULTS PIGD and TD subtypes in moderate to advanced PD participants change with dopaminergic agents. For those who shifted subtypes, improvement in tremor accounted for the transition of 15 (25.4%) TD participants, while the lack of tremor improvement along with minimal changes in PIGD score resulted in changes for eight (19.0%) PIGD individuals. Analyses of PPMI data revealed that all three subgroups had a significant decrease in subtype ratio with disease progression and a significant decline in subtype ratio occurred only in the TD subgroup with dopaminergic agents. The impact of dopaminergic medication effect on subtype shift for each visit was also more notable with disease advancement. CONCLUSIONS Motor subtypes are not fixed but change with progression of the disease and with treatment. Improvement in tremor was the main contributor to motor phenotype transitions in the BioFIND cohort. A more stable classification system for subtypes based on underlying biological differences is desirable.
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Affiliation(s)
- Lan Luo
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - Howard Andrews
- Department of Biostatistics, Columbia University, New York, USA
| | - Roy N Alcalay
- Divison of Movement Disorders, Department of Neurology, Columbia University Medical Center, New York, USA
| | - Fernanda Carvalho Poyraz
- Divison of Movement Disorders, Department of Neurology, Columbia University Medical Center, New York, USA
| | - Amelia K Boehme
- Department of Neurology, College of Physicians and Surgeons, Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Jennifer G Goldman
- Parkinson Disease and Movement Disorders, Shirley Ryan AbilityLab, Chicago, IL, USA
| | - Tao Xie
- Parkinson Disease and Movement Disorder Program, Department of Neurology, University of Chicago, Chicago, IL, USA
| | - Paul Tuite
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | | | - Penelope Hogarth
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Amy W Amara
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Samuel Frank
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Margaret Sutherland
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Catherine Kopil
- The Michael J. Fox Foundation for Parkinson's Research, New York, USA
| | - Anna Naito
- The Michael J. Fox Foundation for Parkinson's Research, New York, USA
| | - Un Jung Kang
- Fresco Institute for Parkinson's and Movement Disorders, Department of Neurology, NYU Langone Health, New York, NY, USA.
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Gupta DK, Fahn S, Tatsuoka C, Kang UJ. Hoehn and Yahr stage 3 and postural stability item in the movement disorder society-unified Parkinson's disease rating scale. Mov Disord 2019; 33:1188-1189. [PMID: 30153396 DOI: 10.1002/mds.27453] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 05/09/2018] [Accepted: 05/09/2018] [Indexed: 11/07/2022] Open
Affiliation(s)
- Deepak K Gupta
- Division of Movement Disorders, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Stanley Fahn
- Division of Movement Disorders, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Curtis Tatsuoka
- Department of Neurology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA
| | - Un Jung Kang
- Division of Movement Disorders, Department of Neurology, Columbia University Medical Center, New York, New York, USA
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Parnetti L, Gaetani L, Eusebi P, Paciotti S, Hansson O, El-Agnaf O, Mollenhauer B, Blennow K, Calabresi P. CSF and blood biomarkers for Parkinson's disease. Lancet Neurol 2019; 18:573-586. [PMID: 30981640 DOI: 10.1016/s1474-4422(19)30024-9] [Citation(s) in RCA: 334] [Impact Index Per Article: 66.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 12/21/2018] [Accepted: 01/15/2019] [Indexed: 01/09/2023]
Abstract
In the management of Parkinson's disease, reliable diagnostic and prognostic biomarkers are urgently needed. The diagnosis of Parkinson's disease mostly relies on clinical symptoms, which hampers the detection of the earliest phases of the disease-the time at which treatment with forthcoming disease-modifying drugs could have the greatest therapeutic effect. Reliable prognostic markers could help in predicting the response to treatments. Evidence suggests potential diagnostic and prognostic value of CSF and blood biomarkers closely reflecting the pathophysiology of Parkinson's disease, such as α-synuclein species, lysosomal enzymes, markers of amyloid and tau pathology, and neurofilament light chain. A combination of multiple CSF biomarkers has emerged as an accurate diagnostic and prognostic model. With respect to early diagnosis, the measurement of CSF α-synuclein aggregates is providing encouraging preliminary results. Blood α-synuclein species and neurofilament light chain are also under investigation because they would provide a non-invasive tool, both for early and differential diagnosis of Parkinson's disease versus atypical parkinsonian disorders, and for disease monitoring. In view of adopting CSF and blood biomarkers for improving Parkinson's disease diagnostic and prognostic accuracy, further validation in large independent cohorts is needed.
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Affiliation(s)
- Lucilla Parnetti
- Section of Neurology, Laboratory of Clinical Neurochemistry, Department of Medicine, University of Perugia, Perugia, Italy.
| | - Lorenzo Gaetani
- Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy
| | - Paolo Eusebi
- Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy
| | - Silvia Paciotti
- Section of Neurology, Laboratory of Clinical Neurochemistry, Department of Medicine, University of Perugia, Perugia, Italy; Section of Physiology and Biochemistry, Department of Experimental Medicine, University of Perugia, Perugia, Italy
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Omar El-Agnaf
- Neurological Disorders Research Center, Qatar Biomedical Research Institute, Hamad Bin Khalifa University, Education City, Doha, Qatar
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany; University Medical Center, Department of Neurology, Göttingen, Germany
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Paolo Calabresi
- Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy; IRCCS Fondazione Santa Lucia, Rome, Italy
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Kang UJ, Boehme AK, Fairfoul G, Shahnawaz M, Ma TC, Hutten SJ, Green A, Soto C. Comparative study of cerebrospinal fluid α-synuclein seeding aggregation assays for diagnosis of Parkinson's disease. Mov Disord 2019; 34:536-544. [PMID: 30840785 PMCID: PMC6519150 DOI: 10.1002/mds.27646] [Citation(s) in RCA: 130] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2018] [Revised: 01/18/2019] [Accepted: 01/28/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND PD diagnosis is based primarily on clinical criteria and can be inaccurate. Biological markers, such as α-synuclein aggregation, that reflect ongoing pathogenic processes may increase diagnosis accuracy and allow disease progression monitoring. Though α-synuclein aggregation assays have been published, reproducibility, standardization, and validation are key challenges for their development as clinical biomarkers. OBJECTIVE To cross-validate two α-synuclein seeding aggregation assays developed to detect pathogenic oligomeric α-synuclein species in CSF using samples from the same PD patients and healthy controls from the BioFIND cohort. METHODS CSF samples were tested by two independent laboratories in a blinded fashion. BioFIND features standardized biospecimen collection of clinically typical moderate PD patients and nondisease controls. α-synuclein aggregation was measured by protein misfolding cyclic amplification (Soto lab) and real-time quaking-induced conversion (Green lab). Results were analyzed by an independent statistician. RESULTS Measuring 105 PD and 79 healthy control CSF samples, these assays showed 92% concordance. The areas under the curve from receiver operating characteristic curve analysis for the diagnosis of PD versus healthy controls were 0.93 for protein misfolding cyclic amplification, 0.89 for real-time quaking-induced conversion, and 0.95 when considering only concordant assay results. Clinical characteristics of false-positive and -negative subjects were not different from true-negative and -positive subjects, respectively. CONCLUSIONS These α-synuclein seeding aggregation assays are reliable and reproducible for PD diagnosis. Assay parameters did not correlate with clinical parameters, including disease severity or duration. This assay is highly accurate for PD diagnosis and may impact clinical practice and clinical trials. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Un Jung Kang
- Department of NeurologyColumbia University Medical CenterNew YorkNew YorkUSA
| | - Amelia K. Boehme
- Department of NeurologyColumbia University Medical CenterNew YorkNew YorkUSA
| | - Graham Fairfoul
- The National CJD Research & Surveillance Unit, Western General HospitalUniversity of EdinburghEdinburghUnited Kingdom
| | - Mohammad Shahnawaz
- Mitchell Center for Alzheimer's Disease and Related Brain DisordersUniversity of Texas‐Houston Medical SchoolHoustonTexas
| | - Thong Chi Ma
- Department of NeurologyColumbia University Medical CenterNew YorkNew YorkUSA
| | | | - Alison Green
- The National CJD Research & Surveillance Unit, Western General HospitalUniversity of EdinburghEdinburghUnited Kingdom
| | - Claudio Soto
- Mitchell Center for Alzheimer's Disease and Related Brain DisordersUniversity of Texas‐Houston Medical SchoolHoustonTexas
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Cova I, Priori A. Diagnostic biomarkers for Parkinson's disease at a glance: where are we? J Neural Transm (Vienna) 2018; 125:1417-1432. [PMID: 30145631 PMCID: PMC6132920 DOI: 10.1007/s00702-018-1910-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Accepted: 07/24/2018] [Indexed: 12/19/2022]
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder whose aetiology remains unclear: degeneration involves several neurotransmission systems, resulting in a heterogeneous disease characterized by motor and non-motor symptoms. PD causes progressive disability that responds only to symptomatic therapies. Future advances include neuroprotective strategies for use in at-risk populations before the clinical onset of disease, hence the continuing need to identify reliable biomarkers that can facilitate the clinical diagnosis of PD. In this evaluative review, we summarize information on potential diagnostic biomarkers for use in the clinical and preclinical stages of PD.
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Affiliation(s)
- Ilaria Cova
- Neurology Unit, L. Sacco University Hospital, Milan, Italy
| | - Alberto Priori
- Department of Health Sciences, "Aldo Ravelli" Research Center for Neurotechnology and Experimental Brain Therapeutics, University of Milan and ASST Santi Paolo e Carlo, Milan, Italy.
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Chen-Plotkin AS, Albin R, Alcalay R, Babcock D, Bajaj V, Bowman D, Buko A, Cedarbaum J, Chelsky D, Cookson MR, Dawson TM, Dewey R, Foroud T, Frasier M, German D, Gwinn K, Huang X, Kopil C, Kremer T, Lasch S, Marek K, Marto JA, Merchant K, Mollenhauer B, Naito A, Potashkin J, Reimer A, Rosenthal LS, Saunders-Pullman R, Scherzer CR, Sherer T, Singleton A, Sutherland M, Thiele I, van der Brug M, Van Keuren-Jensen K, Vaillancourt D, Walt D, West A, Zhang J. Finding useful biomarkers for Parkinson's disease. Sci Transl Med 2018; 10:eaam6003. [PMID: 30111645 PMCID: PMC6097233 DOI: 10.1126/scitranslmed.aam6003] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 12/14/2017] [Indexed: 12/11/2022]
Abstract
The recent advent of an "ecosystem" of shared biofluid sample biorepositories and data sets will focus biomarker efforts in Parkinson's disease, boosting the therapeutic development pipeline and enabling translation with real-world impact.
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Affiliation(s)
- Alice S Chen-Plotkin
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Roger Albin
- Neurology Service and GRECC, VAAHS, Ann Arbor, MI 48105, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Roy Alcalay
- Department of Neurology, Columbia University Medical Center, New York, NY 10032, USA
| | - Debra Babcock
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
| | - Vikram Bajaj
- Verily/Google Life Sciences, South San Francisco, CA 94080, USA
| | - Dubois Bowman
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Alex Buko
- Human Metabolome Technology-America, Boston, MA 02134, USA
| | | | | | - Mark R Cookson
- Cell Biology and Gene Expression Section, Laboratory of Neurogenetics, National Institute of Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ted M Dawson
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Richard Dewey
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Mark Frasier
- The Michael J. Fox Foundation for Parkinson's Research, New York, NY 10163, USA
| | - Dwight German
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Katrina Gwinn
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
| | - Xuemei Huang
- Department of Neurology, Penn State University-Hershey Medical Center, Hershey, PA 17033, USA
| | - Catherine Kopil
- The Michael J. Fox Foundation for Parkinson's Research, New York, NY 10163, USA
| | - Thomas Kremer
- Pharmaceutical Research and Early Development, NORD Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland
| | - Shirley Lasch
- Institute for Neurodegenerative Disorders, New Haven, CT 06510, USA
| | - Ken Marek
- Institute for Neurodegenerative Disorders, New Haven, CT 06510, USA
| | - Jarrod A Marto
- Departments of Cancer Biology and Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
- Blais Proteomics Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA
| | | | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, 34128 Kassel, Germany
- University Medical Center, 37075 Goettingen, Germany
| | - Anna Naito
- The Michael J. Fox Foundation for Parkinson's Research, New York, NY 10163, USA
| | - Judith Potashkin
- Department of Cellular and Molecular Pharmacology, Chicago Medical School, Rosalind Franklin University of Medicine and Science, Chicago, IL 60064, USA
| | - Alyssa Reimer
- The Michael J. Fox Foundation for Parkinson's Research, New York, NY 10163, USA
| | - Liana S Rosenthal
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Rachel Saunders-Pullman
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY 10003, USA
| | - Clemens R Scherzer
- Center for Advanced Parkinson's Disease Research and Precision Neurology Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Todd Sherer
- The Michael J. Fox Foundation for Parkinson's Research, New York, NY 10163, USA
| | - Andrew Singleton
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD 20892, USA
| | - Margaret Sutherland
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
| | - Ines Thiele
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg, Luxembourg
| | | | | | - David Vaillancourt
- Department of Applied Physiology, Biomedical Engineering, and Neurology, University of Florida, Gainesville, FL 32611, USA
| | - David Walt
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA
| | - Andrew West
- Department of Neurology, University of Alabama, Birmingham, AL 35233, USA
| | - Jing Zhang
- Department of Pathology, University of Washington, Seattle, WA 98195, USA
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Kang UJ, Taylor P, Naito A, Goldman JG. Reply To: Detection of Alpha-Synuclein in Saliva: The Importance of Preanalytical Assessment. Mov Disord 2018; 33:1031. [DOI: 10.1002/mds.27424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 04/09/2018] [Indexed: 11/11/2022] Open
Affiliation(s)
- Un Jung Kang
- Division of Movement Disorders, Department of Neurology; Columbia University Medical Center; New York New York USA
| | | | - Anna Naito
- The Michael J. Fox Foundation for Parkinson's Research; New York New York USA
| | - Jennifer G. Goldman
- Section of Parkinson Disease and Movement Disorders, Department of Neurological Sciences; Rush University Medical Center; Chicago Illinois USA
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Sanjari Moghaddam H, Valitabar Z, Ashraf-Ganjouei A, Mojtahed Zadeh M, Ghazi Sherbaf F, Aarabi MH. Cerebrospinal Fluid C-Reactive Protein in Parkinson’s Disease: Associations with Motor and Non-motor Symptoms. Neuromolecular Med 2018; 20:376-385. [DOI: 10.1007/s12017-018-8499-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 06/11/2018] [Indexed: 11/24/2022]
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Trezzi JP, Hiller K, Mollenhauer B. The importance of an independent validation cohort for metabolomics biomarker studies. Mov Disord 2018; 33:856. [PMID: 29722455 DOI: 10.1002/mds.27374] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 02/13/2018] [Indexed: 11/10/2022] Open
Affiliation(s)
- Jean-Pierre Trezzi
- Integrated Biobank of Luxembourg, Dudelange, Luxembourg.,Luxembourg Center for Systems Biomedicine, avenue de l'Université, Esch-sur-Alzette, Luxembourg
| | - Karsten Hiller
- Braunschweig Integrated Centre for Systems Biology (BRICS), Technische Universität Braunschweig, Germany.,Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Brit Mollenhauer
- Paracelsus-Elena Klinik, Kassel and University Medical Center, Goettingen, Germany
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40
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Calabresi P, Standaert DG, Chiasserini D, Parnetti L. Biomarkers in Parkinson's disease: From pathophysiology to early diagnosis. Mov Disord 2018; 31:769-70. [PMID: 27245116 DOI: 10.1002/mds.26683] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 05/03/2016] [Indexed: 12/16/2022] Open
Affiliation(s)
- Paolo Calabresi
- Clinica Neurologica, Università degli Studi di Perugia, Ospedale S. Maria della Misericordia, Perugia, Italy.,IRCCS Fondazione Santa Lucia, Rome, Italy
| | - David G Standaert
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Davide Chiasserini
- Clinica Neurologica, Università degli Studi di Perugia, Ospedale S. Maria della Misericordia, Perugia, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università degli Studi di Perugia, Ospedale S. Maria della Misericordia, Perugia, Italy
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41
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Goldman JG, Andrews H, Amara A, Naito A, Alcalay RN, Shaw LM, Taylor P, Xie T, Tuite P, Henchcliffe C, Hogarth P, Frank S, Saint‐Hilaire M, Frasier M, Arnedo V, Reimer AN, Sutherland M, Swanson‐Fischer C, Gwinn K, Kang UJ. Cerebrospinal fluid, plasma, and saliva in the BioFIND study: Relationships among biomarkers and Parkinson's disease Features. Mov Disord 2017; 33:282-288. [PMID: 29205509 PMCID: PMC5836918 DOI: 10.1002/mds.27232] [Citation(s) in RCA: 99] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Revised: 10/08/2017] [Accepted: 10/16/2017] [Indexed: 01/05/2023] Open
Abstract
OBJECTIVE Examine relationships among neurodegenerative biomarkers and PD motor and nonmotor symptoms. BACKGROUND CSF alpha-synuclein is decreased in PD versus healthy controls, but whether plasma and saliva alpha-synuclein differentiate these groups is controversial. Correlations of alpha-synuclein among biofluids (CSF, plasma, saliva) or biomarkers (eg, beta-amyloid, tau [total, phosphorylated]) are not fully understood. The relationships of these biomarkers with PD clinical features remain unclear. METHODS BioFIND, a cross-sectional, observational study, examines clinical and biomarker characteristics in moderate-advanced PD and matched healthy controls. We compared alpha-synuclein concentrations across diagnosis, biofluids, and CSF biomarkers. Correlations of CSF biomarkers and MDS-UPDRS, motor phenotype, MoCA, and rapid eye movement sleep behavior disorder questionnaire scores in PD were examined. RESULTS CSF alpha-synuclein was lower in PD versus controls (P = .01), controlling for age, gender, and education. Plasma and saliva alpha-synuclein did not differ between PD and controls, and alpha-synuclein did not significantly correlate among biofluids. CSF beta-amyloid1-42 was lower in PD versus controls (P < .01), and correlated weakly with MoCA recall scores (r = 0.23, P = .02). CSF alpha-synuclein was lower in the postural instability/gait difficulty phenotype than other motor phenotypes (P < .01). No CSF biomarkers predicted or correlated with total motor or rapid eye movement sleep behavior disorder scores. CSF alpha-synuclein correlated with beta-amyloid1-42 , total-tau, and phosphorylated-tau (r = 0.41, 0.81, 0.43, respectively; Ps < .001). CONCLUSION Lower CSF alpha-synuclein is associated with diagnosis and motor phenotype in moderate-advanced PD. Plasma and saliva alpha-synuclein neither correlate with CSF alpha-synuclein, nor distinguish PD from controls. CSF beta-amyloid1-42 remains a potential biomarker for cognitive impairment in PD. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jennifer G. Goldman
- Section of Parkinson Disease and Movement Disorders, Department of Neurological SciencesRush University Medical CenterChicagoIllinoisUSA
| | - Howard Andrews
- Division of Movement Disorders, Department of NeurologyColumbia University Medical CenterNew YorkNew YorkUSA
| | - Amy Amara
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Anna Naito
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - Roy N. Alcalay
- Division of Movement Disorders, Department of NeurologyColumbia University Medical CenterNew YorkNew YorkUSA
| | - Leslie M. Shaw
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease ResearchUniversity of Pennsylvania School of MedicinePhiladelphiaPAUSA
| | | | - Tao Xie
- Parkinson Disease and Movement Disorder Program, Department of NeurologyUniversity of ChicagoChicagoIllinoisUSA
| | - Paul Tuite
- Department of NeurologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | - Penelope Hogarth
- Department of Molecular and Medical GeneticsOregon Health & Science UniversityPortlandOregonUSA
| | - Samuel Frank
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
| | | | - Mark Frasier
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - Vanessa Arnedo
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - Alyssa N. Reimer
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - Margaret Sutherland
- National Institute of Neurological Disorders and StrokeNational Institutes of HealthBethesdaMarylandUSA
| | - Christine Swanson‐Fischer
- National Institute of Neurological Disorders and StrokeNational Institutes of HealthBethesdaMarylandUSA
| | - Katrina Gwinn
- National Institute of Neurological Disorders and StrokeNational Institutes of HealthBethesdaMarylandUSA
| | | | - Un Jung Kang
- Division of Movement Disorders, Department of NeurologyColumbia University Medical CenterNew YorkNew YorkUSA
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42
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Chahine LM, Stern MB. Parkinson's Disease Biomarkers: Where Are We and Where Do We Go Next? Mov Disord Clin Pract 2017; 4:796-805. [PMID: 30363472 DOI: 10.1002/mdc3.12545] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Revised: 08/09/2017] [Accepted: 08/23/2017] [Indexed: 12/16/2022] Open
Abstract
Background Objective measures of Parkinson's disease (PD) are needed for purposes of diagnosis and prognostication, as well as identification of those at risk of PD. In this qualitative review, we provide an overview of the current state of the field of PD biomarker development, delineate challenges, and discuss how the field is evolving. Methods A search of PubMed was conducted for articles pertaining to objective biomarkers for PD. Articles were selected based on relevance and methodology; where available, meta-analyses, systematic reviews, and comprehensive qualitative review articles were preferentially referenced. Results There are several potential sources of objective PD biomarkers including biofluids, peripheral tissue, imaging, genetics, and technology based objective motor testing. Approaches to biomarker identification include the candidate biomarker approach and unbiased discovery methods, each of which has advantages and disadvantages. Several emerging techniques hold promise in each of these areas. Advances in technology and bioinformatics, and the increasing availability of biobanks, are expected to facilitate future PD biomarker development. Conclusions The field of objective biomarkers for PD has made great progress but much remains to be done in translating putative biomarkers into tools useful in the clinic and for research. Multimodal biomarker platforms have the potential to capitalize on the utility and strengths of individual biomarkers. Rigorous methodology and standards for replication of findings will be key to meaningful progress in the field.
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Affiliation(s)
- Lana M Chahine
- Department of Neurology Parkinson's Disease and Movement Disorders Center Perelman School of Medicine University of Pennsylvania Philadelphia PA
| | - Matthew B Stern
- Department of Neurology Parkinson's Disease and Movement Disorders Center Perelman School of Medicine University of Pennsylvania Philadelphia PA
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43
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Parnetti L, Paciotti S, Eusebi P, Dardis A, Zampieri S, Chiasserini D, Tasegian A, Tambasco N, Bembi B, Calabresi P, Beccari T. Cerebrospinal fluid β-glucocerebrosidase activity is reduced in parkinson's disease patients. Mov Disord 2017; 32:1423-1431. [PMID: 28843015 DOI: 10.1002/mds.27136] [Citation(s) in RCA: 107] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 06/20/2017] [Accepted: 06/26/2017] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Reduced β-glucocerebrosidase activity was observed in postmortem brains of both GBA1 mutation carrier and noncarrier Parkinson's disease patients, suggesting that lower β-glucocerebrosidase activity is a key feature in the pathogenesis of PD. The objectives of this study were to confirm whether there is reduced β-glucocerebrosidase activity in the CSF of GBA1 mutation carrier and noncarrier PD patients and verify if other lysosomal enzymes show altered activity in the CSF. METHODS CSF β-glucocerebrosidase, cathepsin D, and β-hexosaminidase activities were measured in 79 PD and 61 healthy controls from the BioFIND cohort. The whole GBA1 gene was sequenced. RESULTS Enzyme activities were normalized according to CSF protein content (specific activity). β-glucocerebrosidase specific activity was significantly decreased in PD versus controls (-28%, P < 0.001). GBA1 mutations were found in 10 of 79 PD patients (12.7%) and 3 of 61 controls (4.9%). GBA1 mutation carrier PD patients showed significantly lower β-glucocerebrosidase specific activity versus noncarriers. β-glucocerebrosidase specific activity was also decreased in noncarrier PD patients versus controls (-25%, P < 0.001). Cathepsin D specific activity was lower in PD versus controls (-21%, P < 0.001). β-Hexosaminidase showed a similar trend. β-Glucocerebrosidase specific activity fairly discriminated PD from controls (area under the curve, 0.72; sensitivity, 0.67; specificity, 0.77). A combination of β-glucocerebrosidase, cathepsin D, and β-hexosaminidase improved diagnostic accuracy (area under the curve, 0.77; sensitivity, 0.71; specificity, 0.85). Lower β-glucocerebrosidase and β-hexosaminidase specific activities were associated with worse cognitive performance. CONCLUSIONS CSF β-glucocerebrosidase activity is reduced in PD patients independent of their GBA1 mutation carrier status. Cathepsin D and β-hexosaminidase were also decreased. The possible link between altered CSF lysosomal enzyme activities and cognitive decline deserves further investigation. © 2017 International Parkinson and Movement Disorder Society.
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Affiliation(s)
| | - Silvia Paciotti
- Department of Pharmaceutical Sciences, University of Perugia, Perugia, Italy
| | - Paolo Eusebi
- Neurology Clinic, University of Perugia, Perugia, Italy
| | - Andrea Dardis
- Regional Coordinating Centre for Rare Diseases, University Hospital Santa Maria della Misericordia, Udine, Italy
| | - Stefania Zampieri
- Regional Coordinating Centre for Rare Diseases, University Hospital Santa Maria della Misericordia, Udine, Italy
| | | | - Anna Tasegian
- Department of Pharmaceutical Sciences, University of Perugia, Perugia, Italy
| | | | - Bruno Bembi
- Regional Coordinating Centre for Rare Diseases, University Hospital Santa Maria della Misericordia, Udine, Italy
| | | | - Tommaso Beccari
- Department of Pharmaceutical Sciences, University of Perugia, Perugia, Italy
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Gwinn K, David KK, Swanson-Fischer C, Albin R, Hillaire-Clarke CS, Sieber BA, Lungu C, Bowman FD, Alcalay RN, Babcock D, Dawson TM, Dewey RB, Foroud T, German D, Huang X, Petyuk V, Potashkin JA, Saunders-Pullman R, Sutherland M, Walt DR, West AB, Zhang J, Chen-Plotkin A, Scherzer CR, Vaillancourt DE, Rosenthal LS. Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program. Biomark Med 2017; 11:451-473. [PMID: 28644039 PMCID: PMC5619098 DOI: 10.2217/bmm-2016-0370] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 04/11/2017] [Indexed: 11/21/2022] Open
Abstract
Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.
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Affiliation(s)
- Katrina Gwinn
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Karen K David
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Christine Swanson-Fischer
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Roger Albin
- Neurology Service & GRECC, VAAAHS, UM Udall Center, University of Michigan, Ann Arbor, MI, USA
| | | | - Beth-Anne Sieber
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Codrin Lungu
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD, USA
| | - F DuBois Bowman
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Roy N Alcalay
- Department of Neurology, Columbia University, New York, NY, USA
| | - Debra Babcock
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Ted M Dawson
- Neuroregeneration & Stem Cell Programs, Institute for Cell Engineering, Solomon H Snyder Department of Neuroscience, Pharmacology & Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Richard B Dewey
- Department of Neurology & Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Tatiana Foroud
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Dwight German
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xuemei Huang
- Department of Neurology, Penn State Hershey Medical Center, Hershey, PA, USA
| | - Vlad Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Judith A Potashkin
- Department of Cellular & Molecular Pharmacology, Rosalind Franklin University of Medicine & Science, North Chicago, IL, USA
| | - Rachel Saunders-Pullman
- Department of Neurology, Mount Sinai Beth Israel & Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Margaret Sutherland
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD, USA
| | - David R Walt
- Department of Chemistry, Tufts University, Medford, MA, USA
| | - Andrew B West
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jing Zhang
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Alice Chen-Plotkin
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Clemens R Scherzer
- Department of Neurology, Harvard Medical School, Brigham & Women's Hospital, Cambridge, MA, USA
| | - David E Vaillancourt
- Departments of Applied Physiology & Kinesiology, University of Florida, Gainesville, FL, USA
| | - Liana S Rosenthal
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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