Figure 1

Intra- and inter-subject variation of immune cells at baseline. (A) Representative flow cytometry plots of the gating procedure for immune cells population characteristics. Fresh unstimulated leucocytes from each of the sixteen subjects were stained with specific antibodies. Plots show a side-scatter (SSC) versus CD3+ marker to gate human myeloid (I) and T lymphocytes (IV). Human CD66+ granulocytes and CD14+ cells were gated in the myeloid gate II and III, respectively. After gating on CD3+ T lymphocytes in gate IV, CD4+ and CD8+ T cells were separated based on the expression of single membrane markers. (B) Unsupervised clustering (tSNE) visualization of temporal immune cells phenotypic signatures among subjects. Two-dimensional tSNE (x, y) plots based on immune cells flow cytometry markers at baseline of 16 subjects and reconstitution of cell frequency and phenotypic similarity for CD66+ (beige), CD14+ (red), CD4+ (light blue), CD8+ (dark blue). Data are representative of three independent experiments for each subject, each in duplicate. (C) Global tSNE visualization of immune cells phenotypes at baseline. Downsampling function of multiple inter-subject measurements was applied before data concatenation. The resulting FCS file was analyzed on FlowJo tSNE module to reconstitute a single two-dimensional plot gathering the phenotypic similitudes of immune cells from among subjects (n = 16). (D) Variation in CD4+, CD8+, CD3+, CD66+ and CD14+ cell subpopulation frequencies at baseline. The relative contribution of inter- versus intra-subject variability to the total observed variation in the immune parameters was measured by calculating the range of subject-to-subject differences. An Analysis of Variance Model (ANOVA) was fitted to assess what fraction of the observed frequency variance (expressed as sum-of-squares) is due to differences among subjects (inter-subject variability, white boxes) or temporal changes around the baseline within subjects (intra-subject variability, gray boxes). p ≤ 0.05. *P < 0.05; **P < 0.001; **P < 0.0001 by one-way ANOVA with Tukey’s multiple-comparison test (n = 16). ns, not significant.