Proteomic studies of potential cerebrospinal fluid protein markers for Alzheimer's disease

Puchades, Maja; Hansson, Sara; Nilsson, Carol L.; Andreasen, Niels; Blennow, Kaj; Davidsson, Pia

doi:10.1016/j.molbrainres.2003.08.005

Cited by 279 publications

(214 citation statements)

References 26 publications

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“…Prior proteomic investigations utilizing 2-DE and MALDI-TOF-MS have identified individual proteins present in the CSF of specific diseases, such as Alzheimer's disease, Parkinson's disease, CJD, chronic pain, and primary CNS neoplasms [15,26,[27][28][29]. However, direct comparisons of CSF protein alterations across CNS disease states have not been adequately undertaken, raising legitimate questions regarding the specificity of these CSF markers [30].…”

Section: Discussionmentioning

confidence: 99%

Proteomic analysis of cerebrospinal fluid discriminates malignant and nonmalignant disease of the central nervous system and identifies specific protein markers

et al. 2006

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CNS diseases are often accompanied by changes in the protein composition of cerebrospinal fluid (CSF). SELDI-TOF-MS provides an approach for identifying specific protein markers of disease in biological fluids. We compared the CSF proteomes from patients with neoplastic and reactive/inflammatory CNS diseases to identify potential biomarkers. SELDI-TOF-MS was performed on CSF derived from lumbar puncture of 32 patients, including 10 with CNS malignancies, 12 with inflammatory or reactive conditions, and 10 with unknown CNS disease. Using the SAX-2 (strong anionic exchange) chip, we uncovered three conserved protein peak ranges within each disease category. For neoplastic diseases, we identified conserved peaks at 7.5-8.0 kDa (9/10 samples), 15.1-15.9 kDa (8/10 samples), and 30.0-32.0 kDa (5/10 samples). In reactive/inflammatory diseases, conserved peaks were found at 6.7-7.1 kDa (10/12 samples), 11.5-11.9 kDa (12/12 samples), and 13.3-13.7 kDa (9/12 samples). A protein from the 30.0 to 32.0 kDa peak range found in neoplastic CSF was identified by MALDI analysis as carbonic anhydrase, a protein overexpressed in many malignancies including high-grade gliomas. Similarly, cystatin C was identified in the 13.3-13.7 kDa peak range in non-neoplastic CSF and was most prominent in inflammatory conditions. Our approach provides a rational basis for identifying biomarkers that could be used for detection, diagnosis, and monitoring of CNS diseases.

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Section: Discussionmentioning

confidence: 99%

Proteomic analysis of cerebrospinal fluid discriminates malignant and nonmalignant disease of the central nervous system and identifies specific protein markers

et al. 2006

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“…Cathepsin D, cystatins B and C, serine inhibitor, fibrinogen gamma, and ubiquitin-activating enzyme E1 were found to be enriched in amyloid plaques [71]. The levels of calpain 2 increased in the brain [106] and of alpha antitrypsin in the CSF of patients with AD, whereas the levels of kininogen decreased [101]. In a mouse model of AD, calpain 12 was nitrated [129].…”

Section: Protein Metabolismmentioning

confidence: 98%

“…The energy metabolism proteins, dynein, phosphofructokinase, and vacuolar ATPase subunit H were found to be highly expressed in amyloid plaques [71]. In the CSF of patients with AD, decreased levels for alpha-1 beta glycoprotein [101] and in the CSF of patients with CJD, decreased expression for carbonic anhydrase and prostaglandin D2 synthase were observed [116]. In mouse models with dysfunctional ubiquitin C-terminal hydrolase L-1 [94] and ApoE-knockout [108], increased oxidation was found for creatine kinase BB, GFAP, dihydropyrimidinase-related protein (DRP2), disulfide isomerase, phosphoglycerate mutase 1, and peroxiredoxin.…”

Section: Energy Metabolism Proteinsmentioning

confidence: 99%

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Proteomics‐driven progress in neurodegeneration research

Fountoulakis

Κοσσίδα

2006

Electrophoresis

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Proteomics-driven progress in neurodegeneration researchProteomics technologies have been widely used in the investigation of neurodegenerative and psychiatric disorders, and in particular in the detection of differences between healthy individuals and patients suffering from such diseases. Thus, brain and cerebrospinal fluid (CSF) samples from patients with Alzheimer's disease, Down syndrome, Pick's disease, Parkinson's disease, schizophrenia, and other disorders as well as brain and CSF from animals serving as models of neurological disorders have been analyzed by proteomics. 2-DE followed by MALDI-TOF-MS has been mainly applied as this proteomics approach provides the possibility of convenient quantification of protein levels and detection of post-translational modifications. About 330 unique proteins with deranged levels and modifications have been detected by proteomics approaches to be related to neurodegeneration and psychiatric disorders. They are mainly involved in metabolism pathways, cytoskeleton formation, signal transduction, guidance, detoxification, transport, and conformational changes. In this article, we provide a summary of the major contributions of proteomics technologies in the study of neurodegenerative and psychiatric diseases, in particular, in the detection of changes in protein levels and modifications related to these disorders. IntroductionNeurodegeneration is a major hallmark of a series of genetic and acquired disorders of the central nervous system (CNS), like Alzheimer's disease (AD), Down syndrome (DS), Pick's disease, Creutzfeldt-Jakob disease (CJD), and Parkinson's disease, which result in severe cognitive and motor deficits. A common characteristic of these diseases is that they are multifactorial.Their molecular basis is unknown and individual biomarkers are not reliable. Genomics and proteomics approaches have been applied to obtain a better understanding of neurodegeneration and psychiatric disorders. Genomics has been used to map and identify genes that are mutated in a wide variety of such disorders, like presenilins in AD. Next to genomics, which only provides a partial view of the biological problem, proteomics is widely used in clinical diagnosis as well and many changes in protein levels associated with specific diseases have been identified [1,2].Proteomics is a technology-driven science that studies the proteins of the various biological systems, their structures, interactions, post-translational modifications, and in particular the changes in their levels and modifications, which are the result of specific diseases or are induced by external factors.

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“…Indeed, many increasingly more powerful yet complementary proteomics technologies have been leveled at CSF biomarker discovery in the past decade, including: variations of 2D gel electrophoresis [2,20,[22][23][24][25][26][27][28][29][30]; SELDI-TOF-MS [31][32][33][34]; offline LC -MALDI-TOF [35]; and LC-MS/MS with either isotopecoded affinity tags (ICAT) [36], Tandem Mass Tags [37] or iTRAQ (isobaric tag for relative and absolute quantification) [38,39]. These techniques have all been used successfully to identify candidate biomarkers because they provide accurate relative quantitative information between or among samples.…”

Section: Introductionmentioning

confidence: 99%

P1–206: Quantitative label‐free proteomics for discovery of biomarkers in cerebrospinal fluid: Assessment of technical and inter‐individual variation

Perrin

Payton

Malone

et al. 2013

Alzheimer's & Dementia

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Background: Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF) is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance) among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF) and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) for CSF biomarker discovery by (1) identifying reparable sources of technical variability, (2) assessing subject variance and residual technical variability for numerous CSF proteins, and (3) testing its ability to segregate samples on the basis of desired biomarker characteristics.

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Proteomic studies of potential cerebrospinal fluid protein markers for Alzheimer's disease

Cited by 279 publications

References 26 publications

Proteomic analysis of cerebrospinal fluid discriminates malignant and nonmalignant disease of the central nervous system and identifies specific protein markers

Proteomic analysis of cerebrospinal fluid discriminates malignant and nonmalignant disease of the central nervous system and identifies specific protein markers

Proteomics‐driven progress in neurodegeneration research

P1–206: Quantitative label‐free proteomics for discovery of biomarkers in cerebrospinal fluid: Assessment of technical and inter‐individual variation

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