Proteomics Studies of Subjects with Alzheimer’s Disease and Chronic Pain

• Main Author: Emami Khoonsari, Payam
• Format: Doctoral Thesis
• Language: English
• Published: Uppsala universitet, Klinisk kemi 2017
• Subjects: Bioinformatics; microservices; biomarkers; Alzheimer's disease; chronic pain; fibromyalgia; neuropathic pain; spinal cord stimulation; cloud computing; proteomics; metabolomics; software; workflows; data analysis; mass spectrometry; Geriatrics; Geriatrik; Neurology; Neurologi; Neurosciences; Neurovetenskaper
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-331748; http://nbn-resolving.de/urn:isbn:978-91-513-0111-2

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.