Fig 1.
(A) Blood sample collection. (B) Isolation of peripheral blood mononuclear cells. (C) Flow cytometry analysis and isolation of monocytes. (D) Gene expression analysis using Fluidigm—a multiplex qPCR. This image was generated using BioRender.com.
Fig 2.
FACS gating strategy for isolated PBMCs, followed by sorting and analysis of the three monocyte subtypes.
Single cells negative for Draq7 were considered viable. Cells negative for (A) T-cell marker CD3 and B-cell marker CD19 were excluded. (B) NK-cells were defined as CD56+CD91-. The CD91 positive cells were gated further and (C) sub-fractioned as classical (CD14+/CD16-), intermediate (CD14+/CD16+), and non-classical (CD14-/CD16+) monocytes.
Fig 3.
Age-related correlation of PBMCs percentages.
(A) Shows the decrease (r = -0.44, P = 0.003) of B-cell, and (B) an increase (r = 0.31, P = 0.043) of NK-cell percentage within viable PBMCs. Each dot represents an individual donor, orange for males and blue for females. The black line shows linear regression, and the grey area is the 95% confidence interval.
Fig 4.
Age-related correlation of PBMCs percentages in comparison between males and females.
Only cells/groups with significant p-values are shown. Additional data are presented in S1 Fig 5 in S1 File. (A) Shows the increased (rf = 0.54, P = 0.025) proportion of female NK-cells and (B) decreased B-cells within viable PBMCs of female (rf = -0.56, P = 0.016) and male (rm = -0.49, P = 0.013) donors. Each circle represents an individual volunteer, orange for males and blue for females. The lines show the linear regression for each biological sex, and the grey area is the 95% confidence interval.
Fig 5.
Age-dependent expression of ANXA1 gene in monocytes and their subtypes.
ANXA1 expression in all monocytes (r = 0.38, P = 0.012) (A), classical (r = 0.28, P = 0.067) (B), intermediate (r = 0.33, P = 0.026) (C), and nonclassical (r = 0.43, P = 0.004) (D) monocytes. Each circle represents an individual donor, orange for males and blue for females. The black line shows linear regression, and the grey area is the 95% confidence interval.
Table 1.
Differentially expressed genes associated with age.
Fig 6.
Heatmap of the relationship between age and gene expression in the different monocyte subtypes, separated by biological sex.
The strength of the association of gene expression with age is represented by the Pearson correlation coefficient (r), ranging from -1, a perfect, negative correlation (blue); 0, no correlation; and 1, a perfect, positive correlation (red) of gene expression relative to ACTβ expression with increasing age. Genes are grouped by their most prevalent inflammatory function. Modulators have been linked to both pro- and anti-inflammatory functions. Female correlations are framed in blue (N = 18), and male correlations are in orange (N = 26). Significant genes, defined by a p-value below 0.05, are marked with an asterisk (*).
Table 2.
Age-dependent changes in neuroinflammation-related gene expression in males and females.