Multivariate reconstruction of lymphocyte profiles in a two-dimensional graphical model as a tool for the investigation of lymphocyte subset distribution in health and disease.

Advanced multivariate data-analytical techniques are proposed to concisely represent and evaluate complex lymphocyte profiles (i.e., compound lymphocyte subset distributions) of individual subjects in easily interpretable, two-dimensional, graphical correlation biplots. The lymphocyte profile of each subject is represented by its location in the model, and the score of a subject for a particular lymphocyte subset is inferred from the perpendicular projection on a rotated axis that coincides with this lymphocyte subset. Simultaneously, the model yields information about the correlation between the lymphocyte subsets. Furthermore, individuals with aberrant lymphocyte profiles can be easily identified. In case studies of 80 healthy donors and of 40 patients with multiple myeloma, 10 patients with monoclonal gammopathy of undetermined significance, and 50 age- and sex-matched healthy donors, reconstruction of the two-dimensional lymphocyte profiles from 27 flow-cytometric characterized lymphocyte subsets succeeded in representing 43% and 51% of the total information (variability) contained within the 80 x 27 (= 2,160) and 100 x 27 (= 2,700) flow cytometry measurements, respectively. It is concluded from the present studies that the correlation biplot represents a unique and powerful tool to concisely describe, represent, and analyze complex lymphocyte profiles of individual subjects and the heterogeneity in lymphocyte profiles among these subjects.