METHOD OF IMMUNOSIGNATURE IN DIFFERENTIAL DIAGNOSIS OF AUTISM SPECTRUM DISORDERS. A PILOT STUDY

A large and diverse repertoire of antibodies encodes the history of past immunological experience, creating a global network of the body’s regulation system. In this article, we propose to use a peptide microarray (“immunosignature”) for evaluating global individual antibody patterns and bioinformatic data analysis for differential diagnosis of autism spectrum disorders. The peptide microarray consists of 124 000 antigen mimetics with random sequences covalently bound to the surface of the glass slide. A drop of plasma is tested for the presence of antibodies of distinct specificity, by measuring their binding to each antigen mimetic in the microarray detectable by fluorescent staining with secondary IgG antibodies, and this reaction is registered by laser activation assay. For bioinformatic analysis, we used the files of digitalized fluorescence intensity data, which presented the reactivity of plasma antibodies bound to antigen mimetics. Data processing was carried out by packages of the Bioconductor project for the R software environment to perform statistical evaluation. At the stage of primary data processing, the quantile normalization was used in order to equalize the distributions of antibodies’ reactivity. The sample data and other necessary information were combined into the discrete ExpessionSet container files. To compare the control and experimental groups, the Welch’s one-way ANOVA (for unequal variances) was used. The obtained estimates of the mean value differences and statistical significance of P levels were used further for constructing a volcano diagram, in order of ranking and selecting the most promising antibody reactivity parameters.
For differential diagnosis of autism, and evaluation of diagnostic significance of the immunosignature method, a heatmap was constructed. The standardized values of the logarithms of antibody reactivity, and the results of the hierarchical cluster analysis performed by the Ward method using Pearson correlation, as a measure of similarity were used in constructing the heatmap. As a result of the bioinformatiс analysis of the data, 73 antibodies were selected whose reactivity had statistically significant differences in groups of children with autism and normally developing children. These antibodies were used for differential diagnosis, the value of which was determined in the heatmap construction. It was found that the group of children with autism spectrum disorders by the antibody reactivity exhibits marked heterogeneity, and consists of at least two subgroups. In addition, 60 antibodies in children with autism showed predominantly medium and low reactivity, i.e. these antibodies had a weak binding power with antigenic mimetics, and only 13 antibodies showed high reactivity. In general, diagnostic specificity of the autism spectrum disorders using immunosignature approach was 96.0% (95% CI 82.8 to 99.6%), sensitivity was 78.3% (95% CI 64.9 to 88.2%), and diagnostic efficiency was 82.7%. Our pilot study allows us to propose a method of immunosignature for differential diagnosis of autism and, possibly, to expand our understanding of autism spectrum disorders.

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