Detection of age-related changes in networks of B cells by multivariate time-series analysis

Immunosenescence concerns the gradual deterioration of the immune system due to aging. Recent advances in cellular phenotyping have enabled key improvements in this context during the last decades. In this work we present a novel extensions and integration of data-driven models for describing age-related changes in the network of relationships among cell quantities of eight peripheral B lymphocyte subpopulations. Our dataset contains about six thousands samples of patients having an age between one day and ninety-six years, where for each patient, cell quantities of eight peripheral B lymphocyte subpopulations were mea- sured. By correlation-based multiple time series segmentation we gener- ate four sets of age-related networks depending on the number of age segments. We first analyze a partition in 30 very short segments, then segmentations in 5, 3 and 2 segments. Moving from a fine to a large grain segmentation, different aspects of the dataset are highlighted and analyzed.