Variation in dietary salt intake induces coordinated dynamics of monocyte subsets and monocyte-platelet aggregates in humans: implications in end organ inflammation

Abstract

Background: Monocyte activation and tissue infiltration are quantitatively associated with high-salt intake induced target organ inflammation. We hypothesized that high-salt challenge would induce the expansion of CD14++CD16+ monocytes, one of the three monocyte subsets with a pro-inflammatory phenotype, that is associated with target organ inflammation in humans.

Methodology/principal findings: A dietary intervention study was performed in 20 healthy volunteers, starting with a 3-day usual diet and followed with a 7-day high-salt diet (≥15 g NaCl/day), and a 7-day low-salt diet (≤5 g NaCl/day). The amounts of three monocyte subsets ("classical" CD14++CD16-, "intermediate" CD14++CD16+ and "non-classical" CD14+CD16++) and their associations with monocyte-platelet aggregates (MPAs) were measured by flow cytometry. Blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) was used to evaluate renal hypoxia. Switching to a high-salt diet resulted in CD14++ monocyte activation and a rapid expansion of CD14++CD16+ subset and MPAs, with a reciprocal decrease in the percentages of CD14++CD16- and CD14+CD16++ subsets. In vitro study using purified CD14++ monocytes revealed that elevation in extracellular [Na(+)] could lead to CD14++CD16+ expansion via a ROS dependent manner. In addition, high-salt intake was associated with progressive hypoxia in the renal medulla (increased R2* signal) and enhanced urinary monocyte chemoattractant protein-1 (MCP-1) excretion, indicating a temporal and spatial correlation between CD14++CD16+ subset and renal inflammation. The above changes could be completely reversed by a low-salt diet, whereas blood pressure levels remained unchanged during dietary intervention.

Conclusions/significance: The present work demonstrates that short-term increases in dietary salt intake could induce the expansion of CD14++CD16+ monocytes, as well as an elevation of MPAs, which might be the underlying cellular basis of high-salt induced end organ inflammation and potential thromboembolic risk. In addition, this process seems largely unrelated to changes in blood pressure levels. This finding provides novel links between dietary salt intake, innate immunity and end organ inflammation.

Figure 1. Research protocol.

Figure 2. Gating strategies for monocyte subset and MPA analysis.

Figures A to D show the verification analysis (backgating). Figure A shows the FSC/SSC plot for white blood cells after red blood cell lysis. Figure B shows the gating of CD86+ cells. Figure C and D shows the backgating for plot B. The CD86+ population was backgated into the FSC/SSC plot; all events fall within the traditional “monocyte gate”. Figures E to J show the detailed gating strategies for monocyte subsets and their associations with MPAs. Mon1 indicates CD14++CD16− monocytes; Mon2 indicates CD14++CD16+ monocytes; Mon3 indicates CD14+CD16++ monocytes; MPA indicates monocyte-platelet aggregates.

Figure 3. Representative flow cytometry analysis of monocyte subsets and MPAs from one participant and related statistical comparisons.

Mon1 indicates CD14++CD16− monocytes; Mon2 indicates CD14++CD16+ monocytes; Mon3 indicates CD14+CD16++ monocytes. The box and whisker plots: the boxes extend from the 25^th to the 75^th percentile, with a line at the median. The whiskers extend above and below the box to show the 5^th–95^th percentiles of values. “D3” to “D17” labeled in the x-axis indicates “day 3″ to “day 17″. *P<0.05, **P<0.01, ***P<0.001 (one way repeated measures ANOVA or Friedman test, n = 20).

Figure 4. CD14++CD16+ monocyte linear correlation analysis.

A, shows the correlation between CD14++CD16+ counts and CD14++CD16+ MPA counts on day 4. B and C, show the correlation of net changes (day 4 minus day 3) between CD14++CD16+ percentages/counts and 24 h urinary sodium. Mon2 indicates CD14++CD16+ monocytes; MPA indicates monocyte-platelet aggregates.

Figure 5. Pro-inflammatory activation of purified CD14++ monocytes during dietary intervention.

Figures A to B show the purity analysis of CD14-magnetic-bead isolated human circulating monocytes. A, shows the percentage of CD14++ cells after CD14 bead purification. B, shows a CD14 versus CD16 color plot using cells after CD14 bead purification. Note that monocyte purified by this method are CD14++ monocytes (i.e., CD14++CD16− and CD14++CD16+, according to gating strategies described in Figure 2 ). Figures C and D show intracellular ROS production in magnetic beads purified CD14++ monocytes by 2′, 7′-dichlorofluorescein (DCF) flow cytometry analysis (n = 6, one way repeated measures ANOVA).Figure E shows the related gene expression in magnetic-bead-purified CD14++ monocytes (n = 16, one way repeated measures ANOVA). “D3” to “D17” labeled in the x-axis indicates “day 3″ to “day 17″. *P<0.05, **P<0.01, ***P<0.001. NF-κB indicates nuclear factor kappa B; MCP-1 indicates monocyte chemoattractant protein-1; RANTES indicates Regulated on Activation, Normal T Cell Expressed and Secreted (or CC chemokine ligand 5, CCL5); TGF-β indicates transforming growth factor β; Arg1 indicates arginase 1; MFI indicates median fluorescence intensity.

Figure 6. ROS dependent shift towards CD16 positivity in purified human CD14++ monocytes induced by increased extracellular [Na⁺] (25 mM).

Figure A shows CD14++ monocyte intracellular [Na⁺] detected by CoroNa Green. B shows intracellular ROS production measured by 2′, 7′-dichlorofluorescein (DCF) flow cytometry in CD14++ monocytes. C shows monocyte subset phenotyping using CD16 and CD14 after CD14++ monocytes were incubated for 2 hours (the upper panel) and 6 hours (the lower panel). N-acetylcysteine (NAC, 2 mM) was used as ROS scavenger. All results are derived from 3 independent tests. MFI indicates median fluorescence intensity; Mon2 indicates CD14++CD16+ monocytes. *P<0.05.

Figure 7. Renal blood oxygen level dependent-magnetic resonance imaging (BOLD-MRI) during dietary intervention.

Figures A to E show the representative changes of BOLD-MRI images from one participant during dietary intervention on day 3, day 4, day 10, day 11 and day 17, respectively. Figures F and G show R2*signal changes in renal cortex and medulla, respectively. Statistical comparisons are derived from 11 subjects by one way repeated measures ANOVA. *P<0.05, **P<0.01, ***P<0.001. “D3” to “D17” labeled in the x-axis indicates “day 3″ to “day 17″.

Figure 8. Urinary and serum markers for oxidative stress and renal inflammation.

Figure A shows urinary 8-OHdG corrected for urinary creatinine excretion (n = 20, one way repeated ANOVA). Figure B shows 24-h excretion of urinary MCP-1/CCL2 (10 male subjects, one way repeated ANOVA). Figure C shows the dynamic changes of serum MCP-1/CCL2 levels during dietary intervention. No obvious across-time difference was observed in serum MCP-1 levels (one-way repeated measures ANOVA, 10 male subjects). The box and whisker plots: the boxes extend from the 25^th to the 75^th percentile, with a line at the median. The whiskers extend above and below the box to show the 5^th–95^th percentiles of values. D3 to D17 in x-axis label indicates day 3 to day 17. *P<0.05, **P<0.01, ***P<0.001. 8-OHdG indicates 8-Hydroxy-2-deoxyguanosine; MCP-1 indicates monocyte chemoattractant protein-1.