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A Scoping Review on Body Fluid Biomarkers for Prognosis and Disease Activity in Patients with Multiple Sclerosis. J Pers Med 2022; 12:jpm12091430. [PMID: 36143216 PMCID: PMC9501898 DOI: 10.3390/jpm12091430] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 08/22/2022] [Accepted: 08/27/2022] [Indexed: 11/30/2022] Open
Abstract
Multiple sclerosis (MS) is a complex demyelinating disease of the central nervous system, presenting with different clinical forms, including clinically isolated syndrome (CIS), which is a first clinical episode suggestive of demyelination. Several molecules have been proposed as prognostic biomarkers in MS. We aimed to perform a scoping review of the potential use of prognostic biomarkers in MS clinical practice. We searched MEDLINE up to 25 November 2021 for review articles assessing body fluid biomarkers for prognostic purposes, including any type of biomarkers, cell types and tissues. Original articles were obtained to confirm and detail the data reported by the review authors. We evaluated the reliability of the biomarkers based on the sample size used by various studies. Fifty-two review articles were included. We identified 110 molecules proposed as prognostic biomarkers. Only six studies had an adequate sample size to explore the risk of conversion from CIS to MS. These confirm the role of oligoclonal bands, immunoglobulin free light chain and chitinase CHI3L1 in CSF and of serum vitamin D in the prediction of conversion from CIS to clinically definite MS. Other prognostic markers are not yet explored in adequately powered samples. Serum and CSF levels of neurofilaments represent a promising biomarker.
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Bergström S, Öijerstedt L, Remnestål J, Olofsson J, Ullgren A, Seelaar H, van Swieten JC, Synofzik M, Sanchez-Valle R, Moreno F, Finger E, Masellis M, Tartaglia C, Vandenberghe R, Laforce R, Galimberti D, Borroni B, Butler CR, Gerhard A, Ducharme S, Rohrer JD, Månberg A, Graff C, Nilsson P. A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study. Mol Neurodegener 2021; 16:79. [PMID: 34838088 PMCID: PMC8626910 DOI: 10.1186/s13024-021-00499-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 11/01/2021] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND A detailed understanding of the pathological processes involved in genetic frontotemporal dementia is critical in order to provide the patients with an optimal future treatment. Protein levels in CSF have the potential to reflect different pathophysiological processes in the brain. We aimed to identify and evaluate panels of CSF proteins with potential to separate symptomatic individuals from individuals without clinical symptoms (unaffected), as well as presymptomatic individuals from mutation non-carriers. METHODS A multiplexed antibody-based suspension bead array was used to analyse levels of 111 proteins in CSF samples from 221 individuals from families with genetic frontotemporal dementia. The data was explored using LASSO and Random forest. RESULTS When comparing affected individuals with unaffected individuals, 14 proteins were identified as potentially important for the separation. Among these, four were identified as most important, namely neurofilament medium polypeptide (NEFM), neuronal pentraxin 2 (NPTX2), neurosecretory protein VGF (VGF) and aquaporin 4 (AQP4). The combined profile of these four proteins successfully separated the two groups, with higher levels of NEFM and AQP4 and lower levels of NPTX2 in affected compared to unaffected individuals. VGF contributed to the models, but the levels were not significantly lower in affected individuals. Next, when comparing presymptomatic GRN and C9orf72 mutation carriers in proximity to symptom onset with mutation non-carriers, six proteins were identified with a potential to contribute to a separation, including progranulin (GRN). CONCLUSION In conclusion, we have identified several proteins with the combined potential to separate affected individuals from unaffected individuals, as well as proteins with potential to contribute to the separation between presymptomatic individuals and mutation non-carriers. Further studies are needed to continue the investigation of these proteins and their potential association to the pathophysiological mechanisms in genetic FTD.
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Affiliation(s)
- Sofia Bergström
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
- Swedish FTD Initiative, Stockholm, Sweden
| | - Linn Öijerstedt
- Swedish FTD Initiative, Stockholm, Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Unit of Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
| | - Julia Remnestål
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
- Swedish FTD Initiative, Stockholm, Sweden
| | - Jennie Olofsson
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
- Swedish FTD Initiative, Stockholm, Sweden
| | - Abbe Ullgren
- Swedish FTD Initiative, Stockholm, Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Unit of Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
| | - Harro Seelaar
- Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands
| | | | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Raquel Sanchez-Valle
- Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d’Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Fermin Moreno
- Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa Spain
- Neuroscience Area, Biodonostia Health Research Institute, San Sebastian, Gipuzkoa Spain
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario Canada
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de Médecine, Université Laval, QC, Canada
| | - Daniela Galimberti
- Fondazione IRCCS Ospedale Policlinico, Milan, Italy
- University of Milan, Centro Dino Ferrari, Milan, Italy
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Chris R. Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Departments of Geriatric Medicine and Nuclear Medicine, University of Duisburg- Essen, Duisburg, Germany
| | - Simon Ducharme
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Québec Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec Canada
| | - Jonathan D. Rohrer
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK
| | - Anna Månberg
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
- Swedish FTD Initiative, Stockholm, Sweden
| | - Caroline Graff
- Swedish FTD Initiative, Stockholm, Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Unit of Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
| | - Peter Nilsson
- Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
- Swedish FTD Initiative, Stockholm, Sweden
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3
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Bergström S, Remnestål J, Yousef J, Olofsson J, Markaki I, Carvalho S, Corvol JC, Kultima K, Kilander L, Löwenmark M, Ingelsson M, Blennow K, Zetterberg H, Nellgård B, Brosseron F, Heneka MT, Bosch B, Sanchez-Valle R, Månberg A, Svenningsson P, Nilsson P. Multi-cohort profiling reveals elevated CSF levels of brain-enriched proteins in Alzheimer's disease. Ann Clin Transl Neurol 2021; 8:1456-1470. [PMID: 34129723 PMCID: PMC8283172 DOI: 10.1002/acn3.51402] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/30/2021] [Accepted: 05/12/2021] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE Decreased amyloid beta (Aβ) 42 together with increased tau and phospho-tau in cerebrospinal fluid (CSF) is indicative of Alzheimer's disease (AD). However, the molecular pathophysiology underlying the slowly progressive cognitive decline observed in AD is not fully understood and it is not known what other CSF biomarkers may be altered in early disease stages. METHODS We utilized an antibody-based suspension bead array to analyze levels of 216 proteins in CSF from AD patients, patients with mild cognitive impairment (MCI), and controls from two independent cohorts collected within the AETIONOMY consortium. Two additional cohorts from Sweden were used for biological verification. RESULTS Six proteins, amphiphysin (AMPH), aquaporin 4 (AQP4), cAMP-regulated phosphoprotein 21 (ARPP21), growth-associated protein 43 (GAP43), neurofilament medium polypeptide (NEFM), and synuclein beta (SNCB) were found at increased levels in CSF from AD patients compared with controls. Next, we used CSF levels of Aβ42 and tau for the stratification of the MCI patients and observed increased levels of AMPH, AQP4, ARPP21, GAP43, and SNCB in the MCI subgroups with abnormal tau levels compared with controls. Further characterization revealed strong to moderate correlations between these five proteins and tau concentrations. INTERPRETATION In conclusion, we report six extensively replicated candidate biomarkers with the potential to reflect disease development. Continued evaluation of these proteins will determine to what extent they can aid in the discrimination of MCI patients with and without an underlying AD etiology, and if they have the potential to contribute to a better understanding of the AD continuum.
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Affiliation(s)
- Sofia Bergström
- Division of Affinity Proteomics, Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Julia Remnestål
- Division of Affinity Proteomics, Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Jamil Yousef
- Division of Affinity Proteomics, Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Jennie Olofsson
- Division of Affinity Proteomics, Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Ioanna Markaki
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Stephanie Carvalho
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Assistance-Publique Hôpitaux de Paris, INSERM, CNRS, Hôpital Pitié-Salpêtrière, Department of Neurology, Centre d'Investigation Clinique Neurosciences, Paris, France
| | - Jean-Christophe Corvol
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Assistance-Publique Hôpitaux de Paris, INSERM, CNRS, Hôpital Pitié-Salpêtrière, Department of Neurology, Centre d'Investigation Clinique Neurosciences, Paris, France
| | - Kim Kultima
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
| | - Lena Kilander
- Department of Public Health and Caring Sciences, Geriatrics, Uppsala University, Uppsala, Sweden
| | - Malin Löwenmark
- Department of Public Health and Caring Sciences, Geriatrics, Uppsala University, Uppsala, Sweden
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Geriatrics, Uppsala University, Uppsala, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Bengt Nellgård
- Anesthesiology and Intensive Care Medicine, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Anesthesiology and Intensive Care Medicine, Institute of Clinical Sciences, The Sahlgrenska Academy, University of Gothenburg
| | - Frederic Brosseron
- Universitätsklinikum Bonn, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | | | - Beatriz Bosch
- Alzheimer's and other cognitive disorders Unit. Service of Neurology, Hospital Clínic de Barcelona, Institut d'Investigació Biomèdica August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - Raquel Sanchez-Valle
- Alzheimer's and other cognitive disorders Unit. Service of Neurology, Hospital Clínic de Barcelona, Institut d'Investigació Biomèdica August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - Anna Månberg
- Division of Affinity Proteomics, Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Per Svenningsson
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Peter Nilsson
- Division of Affinity Proteomics, Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden
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Naveed M, Tallat A, Butt A, Khalid M, Shehzadi M, Bashir N, Malik KKU, Tufail S, Nouroz F. Neuroproteomics in Paving the Pathway for Drug Abuse Research. CURR PROTEOMICS 2019. [DOI: 10.2174/1570164616666181127144621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Neuroproteomics, as a sub-discipline of proteomics, has enlightened the pathway for the
study of different complicated diseases and brain disorders. Since four decades, various analytical and
quantitative techniques have been used to cure problems related to brain and memory. Brain has a
complex structure with various cells and cell types, the expressing proteins and suppressing factors too.
Drug addiction is one of the main health concerns as it causes physiological changes in brain and affects
its different parts. Some of these drugs like cocaine, marijuana, nicotine and alcohol not only
affect memory and brain cells but also lead to expression and suppression of unwanted and beneficial
proteins respectively. A variety of techniques involving separation techniques, quantification techniques
and analytical techniques are used along with the combination of bioinformatics and magical
tools for analyzing different aspects of brain parts especially proteome of the brain cells. Moreover,
different animal models preferably those resembling human beings are routinely used in neuroproteomics
to study the effects of different drugs on the brain proteome. Different experiments have already
been performed by the researchers on drug abuse that helped massively in estimating not only the effects
of drug addiction on the brain of highly complex organisms (human beings) but also to propose
different therapeutics.
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Affiliation(s)
- Muhammad Naveed
- Department of Biotechnology, University of Central Punjab, Lahore, Pakistan
| | - Attha Tallat
- Department of Biotechnology, University of Gujrat, Sialkot Sub campus, Sialkot, Pakistan
| | - Ayesha Butt
- Department of Biotechnology, University of Gujrat, Sialkot Sub campus, Sialkot, Pakistan
| | - Maria Khalid
- Department of Biotechnology, University of Gujrat, Sialkot Sub campus, Sialkot, Pakistan
| | - Marium Shehzadi
- Department of Biotechnology, University of Gujrat, Sialkot Sub campus, Sialkot, Pakistan
| | - Nida Bashir
- Department of Biotechnology, University of Gujrat, Sialkot Sub campus, Sialkot, Pakistan
| | | | - Shafia Tufail
- Department of Biotechnology, University of Gujrat, Sialkot Sub campus, Sialkot, Pakistan
| | - Faisal Nouroz
- Department of Botany, Hazara University, Mansehra, Pakistan
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Chen Z, Dodig-Crnković T, Schwenk JM, Tao SC. Current applications of antibody microarrays. Clin Proteomics 2018; 15:7. [PMID: 29507545 PMCID: PMC5830343 DOI: 10.1186/s12014-018-9184-2] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 02/19/2018] [Indexed: 12/14/2022] Open
Abstract
The concept of antibody microarrays is one of the most versatile approaches within multiplexed immunoassay technologies. These types of arrays have increasingly become an attractive tool for the exploratory detection and study of protein abundance, function, pathways, and potential drug targets. Due to the properties of the antibody microarrays and their potential use in basic research and clinical analytics, various types of antibody microarrays have already been developed. In spite of the growing number of studies utilizing this technique, few reviews about antibody microarray technology have been presented to reflect the quality and future uses of the generated data. In this review, we provide a summary of the recent applications of antibody microarray techniques in basic biology and clinical studies, providing insights into the current trends and future of protein analysis.
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Affiliation(s)
- Ziqing Chen
- Key Laboratory of Systems Biomedicine, (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240 China
| | - Tea Dodig-Crnković
- Affinity Proteomics, SciLifeLab, KTH - Royal Institute of Technology, 171 65 Solna, Sweden
| | - Jochen M. Schwenk
- Affinity Proteomics, SciLifeLab, KTH - Royal Institute of Technology, 171 65 Solna, Sweden
| | - Sheng-ce Tao
- Key Laboratory of Systems Biomedicine, (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240 China
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Jiao Tong University, Shanghai, 200240 China
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6
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Hosp F, Mann M. A Primer on Concepts and Applications of Proteomics in Neuroscience. Neuron 2017; 96:558-571. [DOI: 10.1016/j.neuron.2017.09.025] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Revised: 08/29/2017] [Accepted: 09/14/2017] [Indexed: 02/06/2023]
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Häggmark-Månberg A, Zandian A, Forsström B, Khademi M, Lima Bomfim I, Hellström C, Arnheim-Dahlström L, Hallböök T, Darin N, Lundberg IE, Uhlén M, Partinen M, Schwenk JM, Olsson T, Nilsson P. Autoantibody targets in vaccine-associated narcolepsy. Autoimmunity 2016; 49:421-433. [PMID: 27206786 DOI: 10.1080/08916934.2016.1183655] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Narcolepsy is a chronic sleep disorder with a yet unknown cause, but the specific loss of hypocretin-producing neurons together with a strong human leukocyte antigen (HLA) association has led to the hypothesis that autoimmune mechanisms might be involved. Here, we describe an extensive effort to profile autoimmunity repertoires in serum with the aim to find disease-related autoantigens. Initially, 57 serum samples from vaccine-associated and sporadic narcolepsy patients and controls were screened for IgG reactivity towards 10 846 fragments of human proteins using planar microarrays. The discovered differential reactivities were verified on suspension bead arrays in the same sample collection followed by further investigation of 14 antigens in 176 independent samples, including 57 narcolepsy patients. Among these 14 antigens, methyltransferase-like 22 (METTL22) and 5'-nucleotidase cytosolic IA (NT5C1A) were recognized at a higher frequency in narcolepsy patients of both sample sets. Upon sequence analysis of the 14 proteins, polymerase family, member 3 (PARP3), acyl-CoA-binding domain containing 7 (ARID4B), glutaminase 2 (GLS2) and cyclin-dependent kinase-like 1 (CDKL1) were found to contain amino acid sequences with homology to proteins found in the H1N1 vaccine. These findings could become useful elements of further clinical assays that aim towards a better phenotypic understanding of narcolepsy and its triggers.
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Affiliation(s)
- Anna Häggmark-Månberg
- a Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden.,b KTH Center for Applied Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden
| | - Arash Zandian
- a Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden.,b KTH Center for Applied Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden
| | - Björn Forsström
- a Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden.,b KTH Center for Applied Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden
| | - Mohsen Khademi
- c Neuroimmunology Unit, Department of Clinical Neuroscience, Karolinska Institutet , Stockholm , Sweden
| | - Izaura Lima Bomfim
- c Neuroimmunology Unit, Department of Clinical Neuroscience, Karolinska Institutet , Stockholm , Sweden
| | - Cecilia Hellström
- a Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden.,b KTH Center for Applied Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden
| | - Lisen Arnheim-Dahlström
- d Department of Medical Epidemiology and Biostatistics , Karolinska Institutet , Stockholm , Sweden
| | - Tove Hallböök
- e Division of Pediatrics , Department of Clinical Sciences, Faculty of Medicine, Lund University , Lund , Sweden
| | - Niklas Darin
- e Division of Pediatrics , Department of Clinical Sciences, Faculty of Medicine, Lund University , Lund , Sweden
| | - Ingrid E Lundberg
- f Rheumatology Unit, Department of Medicine, Karolinska University Hospital, Solna, Karolinska Institutet , Stockholm , Sweden
| | - Mathias Uhlén
- a Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden.,b KTH Center for Applied Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden
| | - Markku Partinen
- g Helsinki Sleep Clinic, Vitalmed Research Centre , Helsinki , Finland , and.,h Department of Clinical Neurosciences , University of Helsinki , Helsinki , Finland
| | - Jochen M Schwenk
- a Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden.,b KTH Center for Applied Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden
| | - Tomas Olsson
- c Neuroimmunology Unit, Department of Clinical Neuroscience, Karolinska Institutet , Stockholm , Sweden
| | - Peter Nilsson
- a Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden.,b KTH Center for Applied Proteomics, SciLifeLab, School of Biotechnology, KTH-Royal Institute of Technology , Stockholm , Sweden
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