利用質譜術研究阿茲海默症的標識化合物

Studies on Chemical Remarkers of Alzheimer’s Disease by Mass Spectrometry

王建智(Jian-Zhi Wang)

指導教授 ： 李慶國

臺北醫學大學/藥學院/生藥學研究所/碩士(2015年)

摘要

阿茲海默症是常見引起失智的形式，通常發生在大於65歲的老年人，影響全球超過3500萬人。目前阿茲海默症的機轉尚未完全明瞭，並且症狀是不可逆無法被治癒。然而目前臨床尚未有血中的生物標誌物幫助快速篩檢阿茲海默症，因此研究血液中的代謝物變化有助於尋找可能的生物標誌物來幫助做篩檢。本篇研究方式是利用高效液相層析串聯高解析質譜儀研究兩組(21件阿茲海默症以及26件健康對照組)血清的代謝物變化。當檢測完成之後再利用正交最小二偏差判別分析(OPLS-DA)來對於數據做統計分析。當數據利用OPLS-DA方法分析完後
我們可以得到Score-Plot以及S Plot兩種統計圖。從Score-Plot可以看到阿茲海默症組別與健康對照組有明顯分群。在S Plot的部分則可以看到在兩組間有差異的m/z，在正電部分中100.07、299.13、359.23、423.24、425.21、453.34、496.34、524.37、663.45、679.51、701.49、758.56、782.56差異性較大；負電m/z 158.91、179.07、279.23、281.25、284.26、284.97、303.23、327.23、
334.90、400.87、433.26、434.26、差異較大。其中正電某些離子可以推測是Phosphatidylcholine或LysoPhosphatidylcholine類，負離子某些可以推測是脂肪酸找到有差異的m/z後下一步將使用串聯質譜(MS/MS)來分析，擊碎有差異的離子得到其斷裂片，最後再利用母離子及子離子等資訊跟文獻以及資料庫做比對推測其可能為何種代謝物。而目前比對出的LysoPC類缺乏專一性，因此未來還需要嘗試其他方法來解出其他代謝物為何。

關鍵字

阿茲海默症；質譜

並列摘要

Alzheimer disease(AD) is the most common form of dementia. It often occurs in the population more than 65 years old and influenced about 35 million people worldwide. The mechanism of AD is still unclear, and its symptoms are irreversible and cannot be cured. Diagnosis focuses on classic biomarkers in the cerebrospinal fluid (CSF) such as amyloid levels and imaging techniques are used to identify plaque load. However, there are no fast and safe biological markers to detect AD in early stage. The aim of this metabolomic study was to use Ultra Performance Liquid Chromatography (UPLC) coupled with high resolution mass spectrometry to study the metabolome from normal and AD groups. Chemometrics for the analysis of serum from subjects with AD (n = 21) and healthy controls (n = 26) were undertaken. To analyze QTOF MS data was used with orthogonal partial least-squares discriminant analysis (OPLS-DA) to build a model differentiating control and AD. Data from score plot shows that it clearly divided into two groups. S plot was displayed the metabolites significantly differ between two groups. There are significant differences in positive mode m/z 100.07,299.13,359.23,423.24,425.21,453.34,496.34,524.37,663.45,679.51,701.49,
758.56,782.56 and negative mode m/z158.91,179.07,279.23,281.25,284.26,284.97
,303.23,327.23,334.90,400.87,433.26,434.26. 701.49,758.56,782.56 can predict as phosphatidylcholines in positive mode and 279.23 and 281.25 can predict as fatty acids in negative mode. Finally, we used MS/MS method to obtain the fragment of ions with significant differences. However, we only identified Lysophosphatidylcholines. So, we still have to find a way to identify those ions.

並列關鍵字

Alzheimer’s Disease；MS

參考文獻

1. Beckonert, O.; Keun, H. C.; Ebbels, T. M.; Bundy, J.; Holmes, E.; Lindon, J. C.; Nicholson, J. K., Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nature protocols 2007, 2 (11), 2692-703.

2. Vinayavekhin, N.; Homan, E. A.; Saghatelian, A., Exploring disease through metabolomics. ACS chemical biology 2010, 5 (1), 91-103.

3. 许国旺, 代谢组学：方法与应用. 科学出版社 2008

4. Sweedler, J. V., Metabolomics in Analytical Chemistry. Analytical chemistry 2012, 84 (14), 5833.

5. Williams, R.; Lenz, E. M.; Wilson, A. J.; Granger, J.; Wilson, I. D.; Major, H.; Stumpf, C.; Plumb, R., A multi-analytical platform approach to the metabonomic analysis of plasma from normal and Zucker (fa/fa) obese rats. Molecular bioSystems 2006, 2 (3-4), 174-83.