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研究生：	陳怡瑄
論文名稱：	發展個人化腦脊髓液蛋白體定量策略 Development of personalized quantitative strategies for cerebrospinal fluid proteomics
指導教授：	陳玉如
學位類別：	碩士 Master
系所名稱：	化學系 Department of Chemistry
論文出版年：	2011
畢業學年度：	99
語文別：	英文
論文頁數：	119
中文關鍵詞：	腦脊髓液、蛋白質體學
英文關鍵詞：	CSF, proteomics
論文種類：	學術論文
相關次數：	點閱：163 下載：4
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上一筆

腦脊髓液為臨床上與中樞神經系統關係最密切的體液樣本，分析期成份能提供關於神經系統疾病與損傷的病理機制某些獨特的訊息。但是,腦脊髓液裡蛋白質的濃度差異過大、低濃度、高含量蛋白質的干擾, 都侷限了低含量的生物標靶蛋白之開發。為了要作更有效的個人化腦脊髓液的分析，我們結合以奈米探針為基礎的去高含量蛋白技術及同位素標記法(iTRAQ)或免標定定量法(Label-free quantitation) 開發一個具高靈敏性及高再現性的個人化腦脊髓液蛋白體分析方法。在腦脊髓液分析結果顯示，帶有albumin抗體的奈米粒子與其他市售去除高含量蛋白的試劑相比,奈米粒子可以更有效的達到去除腦脊髓液裡的高含量蛋白，並鑑定到1.4倍的蛋白質。在結合同位素標定定量法及免標定定量法的部分，兩種定量策略都提供相近的準確度(同位素標定法的平均值為0.03，免標定定量法為-0.066, log2 尺標)以及誤差範圍(同位素標定法標準偏差為0.27，免標定定量法為0.3, log2尺標)。
在論文的第二部分中，我們將這兩種定量策略應用在分析體顯性腦動脈血管病變合併皮質下腦梗塞及腦白質病變(CADASIL)病患與年齡相對應的正常人，及經過兩次手術治療的脊椎損傷病患，以了解蛋白質在腦脊髓液裡的表現量。在CADASIL 病患中，我們定量了311個蛋白質，並且有39個蛋白質在60%以上的病患中皆有異常表現量。在這些變異蛋白質中, Amyloid precursor protein, Apolipoprotein E, Angiotensinogen, Alpha-1-acid glycoprotein 1, and Alpha-1-acid glycoprotein 2 都曾被直接或間接地報導與CADASIL的致病基因，NOTCH3基因有關。更進一步的，我們也利用西方點墨法驗證Amyloid precursor protein在病人的腦脊髓液中Amyloid precursor protein的含量是下降的。
在脊椎損傷的部分，從7對脊椎損傷病患的脊髓液中，我們找到了233個蛋白質且其中221 可被定量。目前分析結果得到在7組脊椎損傷病患中，因經過FGF 治療方式所導致的不同表現量蛋白比例為19-45%。31個蛋白質在4個以上的經過二次手術的脊椎損傷病患中皆有異常表現量。在此結果中找到四種蛋白質Apolipoproteins, Tresferrin, Tubulin, Zinc finger proteins 曾被報導與脊椎損傷有關。
在此篇論文中，我們提出的腦脊髓液定量分析平台能有效地尋找針對CADASIL 疾病診斷及追蹤脊椎損傷治療效果的標靶蛋白質。

Cerebrospinal fluid (CSF) is an important specimen to accurately reflect pathological processes and provides an ideal window for insights into mechanisms and detection of biochemical changes, such as protein biomarker associated with neurodegenerative disorders and spinal cord injury. However, the wide dynamic range, low protein concentration, and presence of high abundant albumin in CSF pose challenges for comprehensive proteome identification. To facilitate the identification of disease biomarker candidates, we integrated nanoprobe-based albumin depletion technology with iTRAQ or label-free quantitation for quantitative analysis of personalized CSF proteome. The anti-albumin immobilized magnetic nanoparticles (anti-albumin@MNPs) showed 1.4-fold increase in the number of protein identification than commercially available kits to deplete the high abundant albumin in CSF. Combining with iTRAQ or Label-free quantitation, the two platforms provide similar accuracy (mean = 0.003 and -0.066 for iTRAQ and label-free quantitation, respectively in log2 scale) and reproducibility (standard deviation = 0.27 and 0.3 for iTRAQ and label-free quantitation, respectively in log2 scale)
In the second part of thesis, we applied these two strategies to analyze the expression levels of CSF proteome for two diseases: (1) patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) in comparison with age-matched controls and (2) patients with spinal cord injury (SCI) after first and second FGF treatments. A total of 311 proteins were quantified and 39 proteins showed differential expression in more than 60% of CADASIL patients. Among them, amyloid precursor protein, Apolipoprotein E, angiotensinogen, Alpha-1-acid glycoprotein 1, and Alpha-1-acid glycoprotein 2 have been reported to be related to NOTCH3, the disease-causive mutant gene in CADASIL. Further validation using western blot analysis confirmed the down-regulation of amyloid precursor protein in CSF samples from CADASIL patients.
For the CSF analysis for patients with SCI, 233 proteins were identified and 221 proteins were quantified in 7 paired SCI samples from patients after first and second FGF treatments. The preliminary analysis revealed that the FGF treatment induced differential expression of 19%-45% of quantified proteins for the 7 paired SCI patients. Among these proteins, 31 proteins showed common differential expression in more than 4 of SCI patients before and after operation. Four proteins, including Apolipoproteins, tresferrin, tubulin, Zinc finger proteins, had been reported to relate to spinal cord injury.
Our method demonstrated the potential on the identification of potential biomarker for CADASIL disease and the treatment efficiency of SCI.

Table of Contents
謝誌 ............................................................................................................................................ 1
中文摘要 .................................................................................................................................... 2
Abstract ..................................................................................................................................... 4
List of Figure ............................................................................................................................. 6
List of Tables ............................................................................................................................. 8
Table of Contents ...................................................................................................................... 9
Abbreviations .......................................................................................................................... 12
Chapter 1 Introduction .......................................................................................................... 14
1 Significance of Cerebrospinal Fluid (CSF) ............................................................. 14
3 Analytical Methods and Recent Advancements in CSF proteomics ....................... 15
3.1 Previous Literatures on CSF Proteomics ...................................................... 15
3.1.1 Two-dimensional Polyacrylamide Gel Electrophoresis (2D-PAGE) ........... 15
3.1.2 Peptide Fractionation .................................................................................... 16
3.2 Depletion of High Abundant Proteins in CSF .............................................. 17
3.2.1 Immunoaffinity-based Depletion ............................................................... 17
3.2.2 Affinity-based Depletion .............................................................................. 18
3.3 Quantitation Methods for CSF Proteomics .................................................. 19
3.3.1 iTRAQ Labeling ........................................................................................ 19
3.3.2 Label-free Quantitation................................................................................. 20
4 Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and
Leucoencephalopathy (CADASIL) .................................................................................. 22
5 Spinal Cord Injury (SCI) ......................................................................................... 23
6 Objective of this study .......................................................................................... 24
Chapter 2 Materials and Method .......................................................................................... 25
1 Materials .................................................................................................................. 25
1.1 Chemical ....................................................................................................... 25
2 Patient Preparation ................................................................................................... 26
3 Protein Depletion. .................................................................................................... 27
3.1 Depletion by Commercial Kits ..................................................................... 27
3.2 Depletion by Anti-albumin@MNPs ............................................................. 27
4 Protein Digestion ..................................................................................................... 28
4.1 Gel-assisted Digestion .................................................................................. 28
5 Protein and Peptide Assays ...................................................................................... 28
5.1 Coomassie (Bradford) Protein Assay Kit ..................................................... 28
5.2 BCATM Protein Assay Kit ............................................................................. 29
6 iTRAQ Labeling ...................................................................................................... 29
7 Strong Cation Exchange Chromatography (SCX)................................................... 29
8 Desalting and Concentration ................................................................................... 30
9 LC-MS/MS Analysis ............................................................................................... 30
10 Data Conversion and Protein Identification .......................................................... 31
10.1 Label-free Quantitation by IDEAL-Q ........................................................ 32
10.2 iTRAQ Quantitation by Multi-Q ................................................................ 32
11 Western Blot Analysis ............................................................................................ 33
12 Protein Annotations and Network Analysis ........................................................... 33
CHAPTER 3 RESULTS ......................................................................................................... 35
1 Depletion of High Abundant Albumin in CSF ........................................................ 35
1.1 Depletion by Commercial Kits ..................................................................... 36
1.2 Nanoprobe-based Affinity Depletion .................................................................... 37
1.3 Identification of CSF Proteins with or without Albumin Depletion ............. 38
2 Evaluation of Reproducibility and Accuracy of Label-free Quantitation of CSF after
Sequential Depletion of Albumin by Anti-albumin@MNP ............................................. 38
3 Evaluation of Accuracy of iTRAQ Quantitation after Sequential Depletion of
Albumin by Anti-albumin@MNP .................................................................................... 39
4 Comparison of Quantitation Performance between Label-free and iTRAQ Labeling
Strategies .......................................................................................................................... 40
5 Quantitative Analysis of Personalized CSF Proteomics in Patients with CADASIL
in comparison with Age-matched Controls ...................................................................... 40
5.1 Structural and Functional Annotation of Quantified Proteins ...................... 41
5.2 Western Blot Analysis of Amyloid A4 protein ............................................. 42
5.3 Network Mapping of Differentially Expressed Proteins .............................. 43
6 Quantitative Analysis of Spinal Cord Injury ........................................................... 43
Chapter 4 Discussion .............................................................................................................. 45
1 An Efficient Platform for Personalized CSF Quantitative Proteomics ................... 45
2 Discovery of biomarker for CADASIL diagnosis ................................................... 47
3 Discovery of CSF Marker for Monitoring the FGF treatment ................................ 49
Chapter 5 Conclusion ............................................................................................................. 51
Reference .................................................................................................................................52
                                

1. Schutzer, S. E., Liu, T., Natelson, B. H., Angel, T. E., Schepmoes, A. A., Purvine, S. O., Hixson, K. K., Lipton, M. S., Camp, D. G., Coyle, P. K., Smith, R. D. & Bergquist, J. (2010). Establishing the proteome of normal human cerebrospinal fluid. PLoS One 5, e10980.
2. Huhmer, A. F., Biringer, R. G., Amato, H., Fonteh, A. N. & Harrington, M. G. (2006). Protein analysis in human cerebrospinal fluid: Physiological aspects, current progress and future challenges. Dis Markers 22, 3-26.
3. Hu, S., Loo, J. A. & Wong, D. T. (2006). Human body fluid proteome analysis. Proteomics 6, 6326-53.
4. Roche, S., Gabelle, A. & Lehmann, S. (2008). Clinical proteomics of the cerebrospinal fluid: Towards the discovery of new biomarkers. Proteomics Clin Appl 2, 428-36.
5. Chen, X. Q., Walker, A. K., Strahler, J. R., Simon, E. S., Tomanicek-Volk, S. L., Nelson, B. B., Hurley, M. C., Ernst, S. A., Williams, J. A. & Andrews, P. C. (2006). Organellar proteomics: analysis of pancreatic zymogen granule membranes. Mol. Cell. Proteomics 5, 306-312.
6. Bai, S., Liu, S., Guo, X., Qin, Z., Wang, B., Li, X., Qin, Y. & Liu, Y. H. (2009). Proteome analysis of biomarkers in the cerebrospinal fluid of neuromyelitis optica patients. Mol Vis 15, 1638-48.
7. Xiao, F., Chen, D., Lu, Y., Xiao, Z., Guan, L. F., Yuan, J., Wang, L., Xi, Z. Q. & Wang, X. F. (2009). Proteomic analysis of cerebrospinal fluid from patients with idiopathic temporal lobe epilepsy. Brain Res 1255, 180-9.
8. Gorg, A., Obermaier, C., Boguth, G., Harder, A., Scheibe, B., Wildgruber, R. & Weiss, W. (2000). The current state of two-dimensional electrophoresis with immobilized pH gradients. Electrophoresis 21, 1037-53.
9. Heller, M., Michel, P. E., Morier, P., Crettaz, D., Wenz, C., Tissot, J. D., Reymond, F. & Rossier, J. S. (2005). Two-stage Off-Gel isoelectric focusing: protein followed by peptide fractionation and application to proteome analysis of human plasma. Electrophoresis 26, 1174-88.
10. Horth, P., Miller, C. A., Preckel, T. & Wenz, C. (2006). Efficient fractionation and improved protein identification by peptide OFFGEL electrophoresis. Mol Cell Proteomics 5, 1968-74.
11. Michel, P. E., Reymond, F., Arnaud, I. L., Josserand, J., Girault, H. H. & Rossier, J. S. (2003). Protein fractionation in a multicompartment device using Off-Gel isoelectric focusing. Electrophoresis 24, 3-11.
12. Elschenbroich, S., Ignatchenko, V., Sharma, P., Schmitt-Ulms, G., Gramolini, A. O. & Kislinger, T. (2009). Peptide separations by on-line MudPIT compared to isoelectric focusing in an off-gel format: application to a membrane-enriched fraction from C2C12 mouse skeletal muscle cells. J Proteome Res 8, 4860-9.
13. Waller, L. N., Shores, K. & Knapp, D. R. (2008). Shotgun proteomic analysis of cerebrospinal fluid using off-gel electrophoresis as the first-dimension separation. J Proteome Res 7, 4577-84.
14. Shores, K. S. & Knapp, D. R. (2007). Assessment approach for evaluating high abundance protein depletion methods for cerebrospinal fluid (CSF) proteomic analysis. J Proteome Res 6, 3739-51.
15. Wenner, B. R., Lovell, M. A. & Lynn, B. C. (2004). Proteomic analysis of human ventricular cerebrospinal fluid from neurologically normal, elderly subjects using two-dimensional LC-MS/MS. J Proteome Res 3, 97-103.
16. Hu, Y., Malone, J. P., Fagan, A. M., Townsend, R. R. & Holtzman, D. M. (2005). Comparative proteomic analysis of intra- and interindividual variation in human cerebrospinal fluid. Mol Cell Proteomics 4, 2000-9.
17. Ogata, Y., Charlesworth, M. C. & Muddiman, D. C. (2005). Evaluation of protein depletion methods for the analysis of total-, phospho- and glycoproteins in lumbar cerebrospinal fluid. J Proteome Res 4, 837-45.
18. Burgess, J. A., Lescuyer, P., Hainard, A., Burkhard, P. R., Turck, N., Michel, P., Rossier, J. S., Reymond, F., Hochstrasser, D. F. & Sanchez, J. C. (2006). Identification of brain cell death associated proteins in human post-mortem cerebrospinal fluid. J Proteome Res 5, 1674-81.
19. Sjodin, M. O., Bergquist, J. & Wetterhall, M. (2010). Mining ventricular cerebrospinal fluid from patients with traumatic brain injury using hexapeptide ligand libraries to search for trauma biomarkers. J Chromatogr B Analyt Technol Biomed Life Sci 878, 2003-12.
20. Ross, P. L., Huang, Y. L. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., Purkayastha, S., Juhasz, P., Martin, S., Bartlet-Jones, M., He, F., Jacobson, A. & Pappin, D. J. (2004). Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics 3, 1154-1169.
21. Wetterhall, M., Zuberovic, A., Hanrieder, J. & Bergquist, J. (2010). Assessment of the partitioning capacity of high abundant proteins in human cerebrospinal fluid using affinity and immunoaffinity subtraction spin columns. J Chromatogr B Analyt Technol Biomed Life Sci 878, 1519-30.
22. Ow, S. Y., Cardona, T., Taton, A., Magnuson, A., Lindblad, P., Stensjo, K. & Wright, P. C. (2008). Quantitative shotgun proteomics of enriched heterocysts from Nostoc sp. PCC 7120 using 8-plex isobaric peptide tags. J. Proteome Res. 7, 1615-1628.
23. Wang, W., Zhou, H., Lin, H., Roy, S., Shaler, T. A., Hill, L. R., Norton, S., Kumar, P., Anderle, M. & Becker, C. H. (2003). Quantification of proteins and metabolites by mass spectrometry without isotopic labeling or spiked standards. Anal Chem 75, 4818-26.
24. Cutillas, P. R., Geering, B., Waterfield, M. D. & Vanhaesebroeck, B. (2005). Quantification of gel-separated proteins and their phosphorylation sites by LC-MS using unlabeled internal standards: analysis of phosphoprotein dynamics in a B cell lymphoma cell line. Mol Cell Proteomics 4, 1038-51.
25. Locati, D., Morandi, S., Zanotti, M. & Arnoldi, A. (2006). Preliminary approaches for the development of a high-performance liquid chromatography/electrospray ionization tandem mass spectrometry method for the detection and label-free semi-quantitation of the main storage proteins of Lupinus albus in foods. Rapid Commun Mass Spectrom 20, 1305-16.
26. Andreev, V. P., Li, L., Cao, L., Gu, Y., Rejtar, T., Wu, S. L. & Karger, B. L. (2007). A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS. J Proteome Res 6, 2186-94.
27. Fraterman, S., Zeiger, U., Khurana, T. S., Rubinstein, N. A. & Wilm, M. (2007). Combination of peptide OFFGEL fractionation and label-free quantitation facilitated proteomics profiling of extraocular muscle. Proteomics 7, 3404-16.
28. Le Bihan, T., Goh, T., Stewart, II, Salter, A. M., Bukhman, Y. V., Dharsee, M., Ewing, R. & Wisniewski, J. R. (2006). Differential analysis of membrane proteins in mouse fore- and hindbrain using a label-free approach. J Proteome Res 5, 2701-10.
29. Bantscheff, M., Schirle, M., Sweetman, G., Rick, J. & Kuster, B. (2007). Quantitative mass spectrometry in proteomics: a critical review. Anal Bioanal Chem 389, 1017-31.
30. Tsou, C. C., Tsai, C. F., Tsui, Y. H., Sudhir, P. R., Wang, Y. T., Chen, Y. J., Chen, J. Y., Sung, T. Y. & Hsu, W. L. IDEAL-Q, an automated tool for label-free quantitation analysis using an efficient peptide alignment approach and spectral data validation. Mol Cell Proteomics 9, 131-44.
31. Mouton-Barbosa, E., Roux-Dalvai, F., Bouyssie, D., Berger, F., Schmidt, E., Righetti, P. G., Guerrier, L., Boschetti, E., Burlet-Schiltz, O., Monsarrat, B. & de Peredo, A. G. (2010). In-depth exploration of cerebrospinal fluid by combining peptide ligand library treatment and label-free protein quantification. Mol Cell Proteomics 9, 1006-21.
32. Tournier-Lasserve, E., Joutel, A., Melki, J., Weissenbach, J., Lathrop, G. M., Chabriat, H., Mas, J. L., Cabanis, E. A., Baudrimont, M., Maciazek, J. & et al. (1993). Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy maps to chromosome 19q12. Nat Genet 3, 256-9.
33. Chabriat, H., Vahedi, K., Iba-Zizen, M. T., Joutel, A., Nibbio, A., Nagy, T. G., Krebs, M. O., Julien, J., Dubois, B., Ducrocq, X. & et al. (1995). Clinical spectrum of CADASIL: a study of 7 families. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. Lancet 346, 934-9.
34. Joutel, A., Corpechot, C., Ducros, A., Vahedi, K., Chabriat, H., Mouton, P., Alamowitch, S., Domenga, V., Cecillion, M., Marechal, E., Maciazek, J., Vayssiere, C., Cruaud, C., Cabanis, E. A., Ruchoux, M. M., Weissenbach, J., Bach, J. F., Bousser, M. G. & Tournier-Lasserve, E. (1996). Notch3 mutations in CADASIL, a hereditary adult-onset condition causing stroke and dementia. Nature 383, 707-10.
35. Artavanis-Tsakonas, S., Matsuno, K. & Fortini, M. E. (1995). Notch signaling. Science 268, 225-32.
36. Joutel, A., Andreux, F., Gaulis, S., Domenga, V., Cecillon, M., Battail, N., Piga, N., Chapon, F., Godfrain, C. & Tournier-Lasserve, E. (2000). The ectodomain of the Notch3 receptor accumulates within the cerebrovasculature of CADASIL patients. J Clin Invest 105, 597-605.
37. Joutel, A., Vahedi, K., Corpechot, C., Troesch, A., Chabriat, H., Vayssiere, C., Cruaud, C., Maciazek, J., Weissenbach, J., Bousser, M. G., Bach, J. F. & Tournier-Lasserve, E. (1997). Strong clustering and stereotyped nature of Notch3 mutations in CADASIL patients. Lancet 350, 1511-5.
38. Unlu, M., de Lange, R. P., de Silva, R., Kalaria, R. & St Clair, D. (2000). Detection of complement factor B in the cerebrospinal fluid of patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy disease using two-dimensional gel electrophoresis and mass spectrometry. Neurosci Lett 282, 149-52.
39. Formichi, P., Parnetti, L., Radi, E., Cevenini, G., Dotti, M. T. & Federico, A. (2008). CSF levels of beta-amyloid 1-42, tau and phosphorylated tau protein in CADASIL. Eur J Neurol 15, 1252-5.
40. Bresnahan, J. C., King, J. S., Martin, G. F. & Yashon, D. (1976). A neuroanatomical analysis of spinal cord injury in the rhesus monkey (Macaca mulatta). J Neurol Sci 28, 521-42.
41. Kang, S. K., So, H. H., Moon, Y. S. & Kim, C. H. (2006). Proteomic analysis of injured spinal cord tissue proteins using 2-DE and MALDI-TOF MS. Proteomics 6, 2797-812.
42. Tsai, M. C., Wei, C. P., Lee, D. Y., Tseng, Y. T., Tsai, M. D., Shih, Y. L., Lee, Y. H., Chang, S. F. & Leu, S. J. (2008). Inflammatory mediators of cerebrospinal fluid from patients with spinal cord injury. Surg Neurol 70 Suppl 1, S1:19-24; discussion S1:24.
43. Tsou, C. C., Tsai, C. F., Tsui, Y. H., Sudhir, P. R., Wang, Y. T., Chen, Y. J., Chen, J. Y., Sung, T. Y. & Hsu, W. L. (2010). IDEAL-Q, an automated tool for label-free quantitation analysis using an efficient peptide alignment approach and spectral data validation. Mol Cell Proteomics 9, 131-44.
44. Nikolsky, Y., Ekins, S., Nikolskaya, T. & Bugrim, A. (2005). A novel method for generation of signature networks as biomarkers from complex high throughput data. Toxicol Lett 158, 20-9.
45. Perez, J. M., Josephson, L. & Weissleder, R. (2004). Use of magnetic nanoparticles as nanosensors to probe for molecular interactions. Chembiochem 5, 261-4.
46. Buoso, E., Lanni, C., Schettini, G., Govoni, S. & Racchi, M. (2010). beta-Amyloid precursor protein metabolism: focus on the functions and degradation of its intracellular domain. Pharmacol Res 62, 308-17.
47. Chiasserini, D., Di Filippo, M., Candeliere, A., Susta, F., Orvietani, P. L., Calabresi, P., Binaglia, L. & Sarchielli, P. (2008). CSF proteome analysis in multiple sclerosis patients by two-dimensional electrophoresis. Eur J Neurol 15, 998-1001.
48. Sinha, A., Srivastava, N., Singh, S., Singh, A. K., Bhushan, S., Shukla, R. & Singh, M. P. (2009). Identification of differentially displayed proteins in cerebrospinal fluid of Parkinson's disease patients: a proteomic approach. Clin Chim Acta 400, 14-20.
49. Brettschneider, J., Lehmensiek, V., Mogel, H., Pfeifle, M., Dorst, J., Hendrich, C., Ludolph, A. C. & Tumani, H. (2010). Proteome analysis reveals candidate markers of disease progression in amyotrophic lateral sclerosis (ALS). Neurosci Lett 468, 23-7.
50. Amon, L. M., Law, W., Fitzgibbon, M. P., Gross, J. A., O'Briant, K., Peterson, A., Drescher, C., Martin, D. B. & McIntosh, M. (2010). Integrative proteomic analysis of serum and peritoneal fluids helps identify proteins that are up-regulated in serum of women with ovarian cancer. PLoS One 5, e11137.
51. Wang, Y. S., Cao, R., Jin, H., Huang, Y. P., Zhang, X. Y., Cong, Q., He, Y. F. & Xu, C. J. (2011). Altered protein expression in serum from endometrial hyperplasia and carcinoma patients. J Hematol Oncol 4, 15.
52. Ihalainen, S., Soliymani, R., Iivanainen, E., Mykkanen, K., Sainio, A., Poyhonen, M., Elenius, K., Jarvelainen, H., Viitanen, M., Kalimo, H. & Baumann, M. (2007). Proteome analysis of cultivated vascular smooth muscle cells from a CADASIL patient. Mol Med 13, 305-14.
53. Lobov, I. B., Cheung, E., Wudali, R., Cao, J., Halasz, G., Wei, Y., Economides, A., Lin, H. C., Papadopoulos, N., Yancopoulos, G. D. & Wiegand, S. J. (2011). The Dll4/Notch pathway controls postangiogenic blood vessel remodeling and regression by modulating vasoconstriction and blood flow. Blood 117, 6728-37.
54. Yasuhara, O., Kawamata, T., Aimi, Y., McGeer, E. G. & McGeer, P. L. (1994). Expression of chromogranin A in lesions in the central nervous system from patients with neurological diseases. Neurosci Lett 170, 13-6.
55. Hosaka, M., Watanabe, T., Sakai, Y., Uchiyama, Y. & Takeuchi, T. (2002). Identification of a chromogranin A domain that mediates binding to secretogranin III and targeting to secretory granules in pituitary cells and pancreatic beta-cells. Mol Biol Cell 13, 3388-99.
56. Davidsson, P., Westman-Brinkmalm, A., Nilsson, C. L., Lindbjer, M., Paulson, L., Andreasen, N., Sjogren, M. & Blennow, K. (2002). Proteome analysis of cerebrospinal fluid proteins in Alzheimer patients. Neuroreport 13, 611-5.
57. Gee, J. R. & Keller, J. N. (2005). Astrocytes: regulation of brain homeostasis via apolipoprotein E. Int J Biochem Cell Biol 37, 1145-50.
58. Liu, Q., Zerbinatti, C. V., Zhang, J., Hoe, H. S., Wang, B., Cole, S. L., Herz, J., Muglia, L. & Bu, G. (2007). Amyloid precursor protein regulates brain apolipoprotein E and cholesterol metabolism through lipoprotein receptor LRP1. Neuron 56, 66-78.
59. Grimm, M. O., Grimm, H. S., Patzold, A. J., Zinser, E. G., Halonen, R., Duering, M., Tschape, J. A., De Strooper, B., Muller, U., Shen, J. & Hartmann, T. (2005). Regulation of cholesterol and sphingomyelin metabolism by amyloid-beta and presenilin. Nat Cell Biol 7, 1118-23.
60. Breslow, D. K., Collins, S. R., Bodenmiller, B., Aebersold, R., Simons, K., Shevchenko, A., Ejsing, C. S. & Weissman, J. S. (2010). Orm family proteins mediate sphingolipid homeostasis. Nature 463, 1048-53.
61. Han, S., Lone, M. A., Schneiter, R. & Chang, A. (2010). Orm1 and Orm2 are conserved endoplasmic reticulum membrane proteins regulating lipid homeostasis and protein quality control. Proc Natl Acad Sci U S A 107, 5851-6.
62. Papassotiropoulos, A., Lewis, H. D., Bagli, M., Jessen, F., Ptok, U., Schulte, A., Shearman, M. S. & Heun, R. (2002). Cerebrospinal fluid levels of beta-amyloid(42) in patients with Alzheimer's disease are related to the exon 2 polymorphism of the cathepsin D gene. Neuroreport 13, 1291-4.
63. Eriksson, S., Janciauskiene, S. & Lannfelt, L. (1995). Alpha 1-antichymotrypsin regulates Alzheimer beta-amyloid peptide fibril formation. Proc Natl Acad Sci U S A 92, 2313-7.
64. Biroccio, A., Del Boccio, P., Panella, M., Bernardini, S., Di Ilio, C., Gambi, D., Stanzione, P., Sacchetta, P., Bernardi, G., Martorana, A., Federici, G., Stefani, A. & Urbani, A. (2006). Differential post-translational modifications of transthyretin in Alzheimer's disease: a study of the cerebral spinal fluid. Proteomics 6, 2305-13.

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