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Proteomics Studies of Subjects with Alzheimer’s Disease and Chronic Pain
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Chemistry.
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Description
Abstract [en]

Alzheimer’s disease (AD) is a neurodegenerative disease and the major cause of dementia, affecting more than 50 million people worldwide. Chronic pain is long-lasting, persistent pain that affects more than 1.5 billion of the world population. Overlapping and heterogenous symptoms of AD and chronic pain conditions complicate their diagnosis, emphasizing the need for more specific biomarkers to improve the diagnosis and understand the disease mechanisms.

To characterize disease pathology of AD, we measured the protein changes in the temporal neocortex region of the brain of AD subjects using mass spectrometry (MS). We found proteins involved in exo-endocytic and extracellular vesicle functions displaying altered levels in the AD brain, potentially resulting in neuronal dysfunction and cell death in AD.

To detect novel biomarkers for AD, we used MS to analyze cerebrospinal fluid (CSF) of AD patients and found decreased levels of eight proteins compared to controls, potentially indicating abnormal activity of complement system in AD.

By integrating new proteomics markers with absolute levels of Aβ42, total tau (t-tau) and p-tau in CSF, we improved the prediction accuracy from 83% to 92% of early diagnosis of AD. We found increased levels of chitinase-3-like protein 1 (CH3L1) and decreased levels of neurosecretory protein VGF (VGF) in AD compared to controls.

By exploring the CSF proteome of neuropathic pain patients before and after successful spinal cord stimulation (SCS) treatment, we found altered levels of twelve proteins, involved in neuroprotection, synaptic plasticity, nociceptive signaling and immune regulation.

To detect biomarkers for diagnosing a chronic pain state known as fibromyalgia (FM), we analyzed the CSF of FM patients using MS. We found altered levels of four proteins, representing novel biomarkers for diagnosing FM. These proteins are involved in inflammatory mechanisms, energy metabolism and neuropeptide signaling.

Finally, to facilitate fast and robust large-scale omics data handling, we developed an e-infrastructure. We demonstrated that the e-infrastructure provides high scalability, flexibility and it can be applied in virtually any fields including proteomics. This thesis demonstrates that proteomics is a promising approach for gaining deeper insight into mechanisms of nervous system disorders and find biomarkers for diagnosis of such diseases.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. , 82 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1385
Keyword [en]
Bioinformatics, microservices, biomarkers, Alzheimer's disease, chronic pain, fibromyalgia, neuropathic pain, spinal cord stimulation, cloud computing, proteomics, metabolomics, software, workflows, data analysis, mass spectrometry
National Category
Geriatrics Neurology Neurosciences
Research subject
Bioinformatics; Neurology; Geriatrics
Identifiers
URN: urn:nbn:se:uu:diva-331748ISBN: 978-91-513-0111-2 (print)OAI: oai:DiVA.org:uu-331748DiVA: diva2:1150065
Public defence
2017-12-05, Rosénsalen, Akademiska sjukhuset, Ing 95/96, nbv, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2017-11-14 Created: 2017-10-17 Last updated: 2017-11-14
List of papers
1. Increased levels of extracellular microvesicle markers and decreased levels of endocytic/exocytic proteins in the Alzheimer’s disease brain
Open this publication in new window or tab >>Increased levels of extracellular microvesicle markers and decreased levels of endocytic/exocytic proteins in the Alzheimer’s disease brain
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2016 (English)In: Journal of Alzheimer's Disease, ISSN 1387-2877, E-ISSN 1875-8908, Vol. 54, no 4, 71 p.1671-1686 p.Article in journal (Refereed) Published
Abstract [en]

Background: Alzheimer's disease (AD) is a chronic neurodegenerative disorder accounting for more than 50% of all dementia cases. AD neuropathology is characterized by the formation of extracellular plaques and intracellular neurofibrillary tangles consisting of aggregated amyloid-beta and tau, respectively. The disease mechanism has only been partially elucidated and is believed to also involve many other proteins.

Objective: This study intended to perform a proteomic profiling of post mortem AD brains and compare it with control brains as well as brains from other neurological diseases to gain insight into the disease pathology.

Methods: Here we used label-free shotgun mass spectrometry to analyze temporal neocortex samples from AD, other neurological disorders, and non-demented controls, in order to identify additional proteins that are altered in AD. The mass spectrometry results were verified by antibody suspension bead arrays.

Results: We found 50 proteins with altered levels between AD and control brains. The majority of these proteins were found at lower levels in AD. Pathway analyses revealed that several of the decreased proteins play a role in exocytic and endocytic pathways, whereas several of the increased proteins are related to extracellular vesicles. Using antibody-based analysis, we verified the mass spectrometry results for five representative proteins from this group of proteins (CD9, HSP72, PI42A, TALDO, and VAMP2) and GFAP, a marker for neuroinflammation.

Conclusions: Several proteins involved in exo-endocytic pathways and extracellular vesicle functions display altered levels in the AD brain. We hypothesize that such changes may result in disturbed cellular clearance and a perturbed cell-to-cell communication that may contribute to neuronal dysfunction and cell death in AD.

Publisher
71 p.
Keyword
Brain, Proteomics, Mass spectrometry, Alzheimer's disease
National Category
Analytical Chemistry Geriatrics Neurosciences
Research subject
Chemistry with specialization in Analytical Chemistry
Identifiers
urn:nbn:se:uu:diva-277617 (URN)10.3233/JAD-160271 (DOI)000386749900034 ()27636840 (PubMedID)
Funder
VINNOVALars Hierta Memorial FoundationSwedish Research Council, P29797-1; 621-2011-4423Knut and Alice Wallenberg FoundationStiftelsen Gamla Tjänarinnor
Available from: 2016-02-22 Created: 2016-02-22 Last updated: 2017-10-17Bibliographically approved
2. Analysis of the Cerebrospinal Fluid Proteome in Alzheimer's Disease
Open this publication in new window or tab >>Analysis of the Cerebrospinal Fluid Proteome in Alzheimer's Disease
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2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 3, e0150672Article in journal (Refereed) Published
Abstract [en]

Alzheimer's disease is a neurodegenerative disorder accounting for more than 50% of cases of dementia. Diagnosis of Alzheimer's disease relies on cognitive tests and analysis of amyloid beta, protein tau, and hyperphosphorylated tau in cerebrospinal fluid. Although these markers provide relatively high sensitivity and specificity for early disease detection, they are not suitable for monitor of disease progression. In the present study, we used label-free shotgun mass spectrometry to analyse the cerebrospinal fluid proteome of Alzheimer's disease patients and non-demented controls to identify potential biomarkers for Alzheimer's disease. We processed the data using five programs (DecyderMS, Maxquant, OpenMS, PEAKS, and Sieve) and compared their results by means of reproducibility and peptide identification, including three different normalization methods. After depletion of high abundant proteins we found that Alzheimer's disease patients had lower fraction of low-abundance proteins in cerebrospinal fluid compared to healthy controls (p<0.05). Consequently, global normalization was found to be less accurate compared to using spiked-in chicken ovalbumin for normalization. In addition, we determined that Sieve and OpenMS resulted in the highest reproducibility and PEAKS was the programs with the highest identification performance. Finally, we successfully verified significantly lower levels (p<0.05) of eight proteins (A2GL, APOM, C1QB, C1QC, C1S, FBLN3, PTPRZ, and SEZ6) in Alzheimer's disease compared to controls using an antibody-based detection method. These proteins are involved in different biological roles spanning from cell adhesion and migration, to regulation of the synapse and the immune system.

National Category
Neurology Geriatrics
Identifiers
urn:nbn:se:uu:diva-283774 (URN)10.1371/journal.pone.0150672 (DOI)000371990100049 ()26950848 (PubMedID)
Funder
Knut and Alice Wallenberg FoundationMarianne and Marcus Wallenberg FoundationThe Swedish Brain FoundationSwedish Research Council FormasSwedish Research Council, P29797-1Swedish Research Council, 621-2011-4423
Available from: 2016-04-14 Created: 2016-04-14 Last updated: 2017-10-17Bibliographically approved
3. Chitinase-3-like protein 1 (CH3L1) and Neurosecretory protein VGF (VGF) as two novel CSF biomarker candidates for improved diagnostics in Alzheimer’s disease
Open this publication in new window or tab >>Chitinase-3-like protein 1 (CH3L1) and Neurosecretory protein VGF (VGF) as two novel CSF biomarker candidates for improved diagnostics in Alzheimer’s disease
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder characterized by amyloid-β (Aβ) plaque deposition and accumulation of intracellular neurofibrillary tangles. This pathology is mirrored in the cerebrospinal fluid (CSF), where decreased Aβ42 together with increased total (t-tau) and phospho-tau (p-tau) today is used as a diagnostic marker. Although these biomarkers have a fairly good sensitivity and specificity, additional biomarkers are needed to further improve the accuracy for early disease detection and to monitor disease development. In this study, we used mass spectrometry-based shotgun proteomics to investigate the CSF proteome of patients with AD and mild cognitive impairment (MCI) as well as of non-demented controls. By combining the diagnostic markers (Aβ42, total t-tau, and p-tau) with a selection of proteomics biomarkers, the accuracy of predicting MCI to AD conversion increased from 83% to 92% with a specificity of 1.0 and sensitivity of 0.86. Among these markers, the levels of protein chitinase-3-like protein 1 (CH3L1) were significantly higher in AD and MCI converters compared to controls. In addition to Aβ42, t-tau, and p-tau the protein CH3L1 contributed mostly to the prediction accuracy. We also found statistically significant lower CSF levels of the neurosecretory protein VGF (VGF) in AD compared to controls. Taken together, our findings suggest that incorporating new CSF biomarkers can further enhance early diagnosis of AD.

Keyword
Alzheimer's disease, cerebrospinal fluid, biomarker, diagnostics, neurodegenerative disorder, dementia
National Category
Geriatrics Neurosciences
Research subject
Geriatrics; Medical Science; Neurology
Identifiers
urn:nbn:se:uu:diva-331711 (URN)
Available from: 2017-10-17 Created: 2017-10-17 Last updated: 2017-10-25
4. Spinal Cord Stimulation Alters Protein Levels in the Cerebrospinal Fluid of Neuropathic Pain Patients: A Proteomic Mass Spectrometric Analysis
Open this publication in new window or tab >>Spinal Cord Stimulation Alters Protein Levels in the Cerebrospinal Fluid of Neuropathic Pain Patients: A Proteomic Mass Spectrometric Analysis
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2016 (English)In: Neuromodulation (Malden, Mass.), ISSN 1094-7159, E-ISSN 1525-1403, Vol. 19, no 6, 549-562 p.Article in journal (Refereed) Published
Abstract [en]

ObjectivesElectrical neuromodulation by spinal cord stimulation (SCS) is a well-established method for treatment of neuropathic pain. However, the mechanism behind the pain relieving effect in patients remains largely unknown. In this study, we target the human cerebrospinal fluid (CSF) proteome, a little investigated aspect of SCS mechanism of action. MethodsTwo different proteomic mass spectrometry protocols were used to analyze the CSF of 14 SCS responsive neuropathic pain patients. Each patient acted as his or her own control and protein content was compared when the stimulator was turned off for 48 hours, and after the stimulator had been used as normal for three weeks. ResultsEighty-six proteins were statistically significantly altered in the CSF of neuropathic pain patients using SCS, when comparing the stimulator off condition to the stimulator on condition. The top 12 of the altered proteins are involved in neuroprotection (clusterin, gelsolin, mimecan, angiotensinogen, secretogranin-1, amyloid beta A4 protein), synaptic plasticity/learning/memory (gelsolin, apolipoprotein C1, apolipoprotein E, contactin-1, neural cell adhesion molecule L1-like protein), nociceptive signaling (neurosecretory protein VGF), and immune regulation (dickkopf-related protein 3). ConclusionPreviously unknown effects of SCS on levels of proteins involved in neuroprotection, nociceptive signaling, immune regulation, and synaptic plasticity are demonstrated. These findings, in the CSF of neuropathic pain patients, expand the picture of SCS effects on the neurochemical environment of the human spinal cord. An improved understanding of SCS mechanism may lead to new tracks of investigation and improved treatment strategies for neuropathic pain.

Keyword
Cerebrospinal fluid, mechanism of action, neuropathic pain, spinal cord stimulation
National Category
Neurology Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:uu:diva-304434 (URN)10.1111/ner.12473 (DOI)000382755300001 ()27513633 (PubMedID)
Funder
VINNOVASwedish Research Council
Available from: 2016-10-05 Created: 2016-10-05 Last updated: 2017-10-17Bibliographically approved
5. Systematic Analysis of the Cerebrospinal Fluid Proteome of Fibromyalgia patients
Open this publication in new window or tab >>Systematic Analysis of the Cerebrospinal Fluid Proteome of Fibromyalgia patients
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Fibromyalgia (FM) is a syndrome characterized by widespread muscular pain, fatigue and functional symptoms, which is known to be difficult to diagnose as the various symptoms overlap with many other conditions. Currently, there are no biomarkers for FM, and the diagnosis is made subjectively by the clinicians. We have performed shotgun proteomics on cerebrospinal fluid (CSF) from FM patients and non-pain controls to find potential biomarker candidates for this syndrome. Based on our multivariate and univariate analyses, we found that the relative differences in the CSF proteome between FM patients and controls were moderate. Four proteins, important to discriminate FM patients from non-pain controls, were found: Apolipoprotein C-III, Galectin-3-binding protein, Malate dehydrogenase cytoplasmic and the neuropeptide precursor protein ProSAAS. These proteins are involved in lipoprotein lipase (LPL) activity, inflammatory signaling, energy metabolism and neuropeptide signaling.

Keyword
cerebrospinal fluid, biomarker, chronic pain, fibromyalgia, inflammation, neuroinflammation, mass spectrometry
National Category
Health Sciences Neurosciences Clinical Laboratory Medicine Biomedical Laboratory Science/Technology
Research subject
Bioinformatics; Biology with specialization in Molecular Biology; Chemistry with specialization in Analytical Chemistry; Medical Science; Clinical Chemistry
Identifiers
urn:nbn:se:uu:diva-331615 (URN)
Available from: 2017-10-16 Created: 2017-10-16 Last updated: 2017-10-17
6. Interoperable and scalable metabolomics data analysis with microservices
Open this publication in new window or tab >>Interoperable and scalable metabolomics data analysis with microservices
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We here present a generic method based on microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed in parallel using the Kubernetes container orchestrator. The method was developed within the PhenoMeNal consortium to support flexible metabolomics data analysis and was designed as a virtual research environment which can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and established workflows can be re-used effortlessly by any novice user. We validate our method on two mass spectrometry studies, one nuclear magnetic resonance spectroscopy study and one fluxomics study, showing that the method scales dynamically with increasing availability of computational resources. We achieved a complete integration of the major software suites resulting in the first turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, multivariate statistics, and metabolite identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative data analysis.

Keyword
Bioinformatics, e-infrastructure, microservices, metabolomics, kubernetes, Docker, container
National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics
Identifiers
urn:nbn:se:uu:diva-331658 (URN)
Available from: 2017-10-16 Created: 2017-10-16 Last updated: 2017-10-17

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