[Numerical analysis of western blot digitalized images. The case of HIV]

The present work explores the use of image digitalization of western blot (WB) aiming to extract more information about the humoral immune response of human immunodeficiency virus (HIV) infected individuals, and to analyze obtained data in a multivariate manner. The digitalization and analysis of WB images was performed on 115 sera. Images were analyzed either qualitatively: dendogram and principal component analysis (PCA) or quantitatively: PCA of the total bands, taking either the antigens, which belong to the virus, or only those which do not. Results show the feasibility of mechanical diagnosis of a large number of WB images. The dendogram and the qualitative PCA satisfactorily separated white images, images with less than four bands, and images with more complex patterns. Quantitative analysis, which keeps more information, separated the images of negative, undetermined and positive diagnosis quite precisely. It was also found that the positive images with complex patterns of antigen recognition correlate better with asymptomatic individuals. Image analysis also revealed various other bands in WB which do not seem to correspond to viral proteins and could represent autoantigens or crossed antigens between HIV and humans which may cause autoimmunity. Digital analysis of WB images is thus demonstrated to be of great usefulness in the diagnosis and of potential great interest in following the evolution and exploring the pathogenesis of AIDS.