A Combinatorial Approach in Discrimination of Alcohol Use Disorders: Inclusion of Differentially Expressed Plasma Proteins.


Boşgelmez I. I. , Güvendik G., Dilbaz N., Saraçbaşı T., Esen M.

Acta Medica, cilt.47, ss.99-108, 2016 (Hakemli Üniversite Dergisi)

  • Cilt numarası: 47 Konu: 3
  • Basım Tarihi: 2016
  • Dergi Adı: Acta Medica
  • Sayfa Sayıları: ss.99-108

Özet

Alcohol use disorders are associated with a variety of medical, social, and economical problems worldwide. The diagnosis relies mainly on questionnaires, physical examination, clinical history, and biochemical markers. Alcohol or its metabolites may be responsible for changes in stability, structure and expression of proteins; therefore, proteomics may provide unique opportunities in the identification of novel biomarkers. The aim of this study was to compare the protein expression profile in plasma samples obtained from alcohol use disorder patients (n=30) with those of social drinkers (n=15) and nondrinkers (n=15) using two-dimensional gel electrophoresis, combined with mass spectrometric analysis to identify spots of interest and search for a potential combination of these proteins with some biochemical tests including carbohydrate deficient transferrin, total sialic acid, mean corpuscular volume, gamma-glutamyl transferase, alkaline phosphatase, lactate dehydrogenase, aspartate aminotransferase, alanine aminotransferase, and AST/ALT ratio. Discriminant analysis revealed that the combined use of all differentially expressed spots and biochemical tests revealed a sensitivity and specificity of 100%, while the combination of stepwise-selected 4 spots (identified as coagulation factor II, complement factor B, apolipoprotein E, latent human C1-inhibitor) and 5 known-markers (CDT, SA, MCV, GGT, AST/ALT) could classify 27 out of 30 alcohol use disorder patients correctly. This study shows that combining conventional markers with the spots of interest may be a strategy to increase sensitivity, since the conventional marker combination already has a specificity of 100%. Therefore, this combinatorial approach may be of use for classification studies; however further studies in larger samples are needed to test findings of this research.