New approach to determine the healthy immune variations by combining clustering methods

• Published in: Scientific reports Vol. 11; no. 1; pp. 8917 - 10
• Main Authors: Liefferinckx, Claire, De Grève, Zacharie, Toubeau, Jean-François, Perée, Hélène, Quertinmont, Eric, Tafciu, Vjola, Minsart, Charlotte, Rahmouni, Souad, Georges, Michel, Vallée, François, Franchimont, Denis
• Format: Journal Article Web Resource
• Language: English
• Published: London Nature Publishing Group UK 26.04.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/114/2404; Algorithms; Blood; Clustering; Cortisol; Cytomegalovirus; Datasets; Disease; Environmental factors; Epstein-Barr virus; Gastroenterology; Hormones; Human health sciences; Humanities and Social Sciences; Immune system; Immunologie & maladie infectieuse; Immunology & infectious disease; Inflammatory diseases; multidisciplinary; Principal components analysis; Proteins; Science; Science (multidisciplinary); Sciences de la santé humaine; Testosterone; Variability; Variation
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-88272-x

Immune-mediated inflammatory diseases are characterized by variability in disease presentation and severity but studying it is a challenging task. Defining the limits of a healthy immune system is therefore a prior step to capture variability in disease conditions. The goal of this study is to characterize the global immune cell composition along with their influencing factors. Blood samples were collected from 2 independent cohorts of respectively 389 (exploratory) and 208 (replication) healthy subjects. Twelve immune cells were measured in blood together with biological parameters. Three complementary clustering approaches were used to evaluate if variability related to the immune cells could be characterized as clusters or as a continuum. Large coefficients of variation confirmed the inter-individual variability of immune cells. Considering all subset variations in an overall analysis, it appeared that the immune makeup was organized as a continuum through the two cohorts. Some intrinsic and environmental factors affected the inter-individual variability of cells but without unveiling separable groups with similar features. This study provides a framework based on complementary clustering approach for analyzing inter-individual variability of immune cells. Our analyses support the absence of clusters in our two healthy cohorts. Also, our study reports some influence of age, gender, BMI, cortisol, season and CMV infection on immune variability.