Fig. 5: Multivariate analyses confirm the establishment of a different immune response depending on age group.

A subset of samples with multiple measurements was selected for the multivariate analyses. It consists of 111 samples from 80 adults and 75 samples from 52 children. A, B Spearman correlations between all antibody measurements were calculated and depicted as a network for samples from adults (A) or children (B) participants. Each node corresponds to a variable, and edges between them represent positive correlations in red and negative correlations in blue. The thickness of the edge represents the correlation coefficient, with fine lines indicating a coefficient below 0.4. Only significant correlations after Bonferroni correction for multiple testing are shown. Nodes were grouped together when strongly correlating for children. Features are colour coded, with grey for donor information, blue for IgG, pink for IgM, green for IgA, orange for IgG avidity, purple for Fc-receptors and red for neutralisation (PRNT). C, D A principal component analysis with all numerical variables except age was performed and points for dimensions 3 and 4 are shown in (C) coloured by age group with children in red and adults in grey. 95% concentration ellipses are overlaid to indicate clustering patterns. A two-sided Analysis of Similarities test (ANOSIM) was used to assess if the two age groups were statistically different: p-value and R statistic are indicated. R ranges from -1 to 1, if around 0 the groups are similar, the closest to 1 the most the groups are separated. The contribution of each variable to each dimension of the PCA are shown in (D) with the size of the dots while the colour of the dots represents the loadings on each principal component. Only significant contributions are represented, where a contribution is considered significant if it exceeds 3.7%, corresponding to the expected value under a uniform distribution. E, F Supervised multiple factor analysis illustrating the distribution of samples colour-coded by sex, symptoms or age group (E). ANOSIM p-values and R statistic are indicated. The loadings of each variable are shown in (F) on the x-axis, with bars colour-coded to indicate their contribution to the principal component, non-significant contributions are in grey. Contributions are considered significant if they exceed 3%, corresponding to the expected value under a uniform distribution. Source data are provided as a Source Data file.