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Chitinase-3-like protein 1 (CH3L1) and Neurosecretory protein VGF (VGF) as two novel CSF biomarker candidates for improved diagnostics in Alzheimer’s disease
(Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.)
(Department of Chemistry-BMC, Analytical Chemistry, Uppsala University, Uppsala, Sweden.)
(Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.)
(Department of Chemistry-BMC, Analytical Chemistry, Uppsala University, Uppsala, Sweden.)
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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 [en]
Alzheimer's disease, cerebrospinal fluid, biomarker, diagnostics, neurodegenerative disorder, dementia
National Category
Geriatrics Neurosciences
Research subject
Geriatrics; Medical Science; Neurology
Identifiers
URN: urn:nbn:se:uu:diva-331711OAI: oai:DiVA.org:uu-331711DiVA: diva2:1149825
Available from: 2017-10-17 Created: 2017-10-17 Last updated: 2017-10-25
In thesis
1. Proteomics Studies of Subjects with Alzheimer’s Disease and Chronic Pain
Open this publication in new window or tab >>Proteomics Studies of Subjects with Alzheimer’s Disease and Chronic Pain
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
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
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:nbn:se:uu:diva-331748 (URN)978-91-513-0111-2 (ISBN)
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

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