New analysis workflow for MALDI imaging mass spectrometry: application to the discovery and identification of potential markers of childhood absence epilepsy

J Proteome Res. 2012 Nov 2;11(11):5453-63. doi: 10.1021/pr3006974. Epub 2012 Oct 12.

Abstract

Childhood absence epilepsy is a prototypic form of generalized nonconvulsive epilepsy characterized by short impairments of consciousness concomitant with synchronous and bilateral spike-and-wave discharges in the electroencephalogram. For scientists in this field, the BS/Orl and BR/Orl mouse lines, derived from a genetic selection, constitute an original mouse model "in mirror" of absence epilepsy. The potential of MALDI imaging mass spectrometry (IMS) for the discovery of potential biomarkers is increasingly recognized. Interestingly, statistical analysis tools specifically adapted to IMS data sets and methods for the identification of detected proteins play an essential role. In this study, a new cross-classification comparative design using a combined discrete wavelet transformation-support vector machine classification was developed to discriminate spectra of brain sections of BS/Orl and BR/Orl mice. Nineteen m/z ratios were thus highlighted as potential markers with very high recognition rates (87-99%). Seven of these potential markers were identified using a top-down approach, in particular a fragment of Synapsin-I. This protein is yet suspected to be involved in epilepsy. Immunohistochemistry and Western Blot experiments confirmed the differential expression of Synapsin-I observed by IMS, thus tending to validate our approach. Functional assays are being performed to confirm the involvement of Synapsin-I in the mechanisms underlying childhood absence epilepsy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biomarkers / metabolism*
  • Blotting, Western
  • Child
  • Epilepsy, Absence / metabolism*
  • Humans
  • Immunohistochemistry
  • Mice
  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Substances

  • Biomarkers