MISC

2004年4月

Identification of novel and downregulated biomarkers for alcoholism by surface enhanced laser desorption/ionization-mass spectrometry

PROTEOMICS
  • F Nomura
  • ,
  • T Tomonaga
  • ,
  • K Sogawa
  • ,
  • T Ohashi
  • ,
  • M Nezu
  • ,
  • M Sunaga
  • ,
  • N Kondo
  • ,
  • M Iyo
  • ,
  • H Shimada
  • ,
  • T Ochiai

4
4
開始ページ
1187
終了ページ
1194
記述言語
英語
掲載種別
DOI
10.1002/pmic.200300674
出版者・発行元
WILEY-V C H VERLAG GMBH

Since personal and verbal reporting of alcohol use is not necessarily accurate, objective markers to assess alcohol consumption are required. The currently available markers, however, are limited in sensitivity and specificity for screening of excessive alcohol drinkers. Therefore, searches for novel markers are warranted. Recently, surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) has been successfully used to detect disease-associated proteins in complex biological specimens. We used the ProteinChip SELDI technology to generate comparative protein profiles of the consecutive serum samples obtained during abstinence from a total of 16 chronic alcoholic patients hospitalized for a rehabilitation program. We recognized two peaks (5.9 and 7.8 kDa), both of which had been downregulated on admission, the expression level of which significantly increased after a one-week abstinence. These changes were also seen in nonresponders of gamma-glutamyltransferase. These two proteins were partially purified and subjected to amino acid sequencing. The 5.9 kDa protein was identified as a fragment of fibrinogen alphaE chain and the 7.8 kDa was a fragment of apoprotein A-II. These novel protein fragments may be promising biomarkers for excessive alcohol drinking.

リンク情報
DOI
https://doi.org/10.1002/pmic.200300674
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000220763900027&DestApp=WOS_CPL
ID情報
  • DOI : 10.1002/pmic.200300674
  • ISSN : 1615-9853
  • Web of Science ID : WOS:000220763900027

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