Human monocyte transcriptional profiling identifies IL-18 receptor accessory protein and lactoferrin as novel immune targets in hypertension

Abstract

Background and purpose: Monocytes play a critical role in hypertension. The purpose of our study was to use an unbiased approach to determine whether hypertensive individuals on conventional therapy exhibit an altered monocyte gene expression profile and to perform validation studies of selected genes to identify novel therapeutic targets for hypertension.

Experimental approach: Next generation RNA sequencing identified differentially expressed genes in a small discovery cohort of normotensive and hypertensive individuals. Several of these genes were further investigated for association with hypertension in multiple validation cohorts using qRT-PCR, regression analysis, phenome-wide association study and case-control analysis of a missense polymorphism.

Key results: We identified 60 genes that were significantly differentially expressed in hypertensive monocytes, many of which are related to IL-1β. Uni- and multivariate regression analyses of the expression of these genes with mean arterial pressure (MAP) revealed four genes that significantly correlated with MAP in normotensive and/or hypertensive individuals. Of these, lactoferrin (LTF), peptidoglycan recognition protein 1 and IL-18 receptor accessory protein (IL18RAP) remained significantly elevated in peripheral monocytes of hypertensive individuals in a separate validation cohort. Interestingly, IL18RAP expression associated with MAP in a cohort of African Americans. Furthermore, homozygosity for a missense single nucleotide polymorphism in LTF that decreases antimicrobial function and increases protein levels (rs1126478) was over-represented in patients with hypertension relative to controls (odds ratio 1.16).

Conclusions and implications: These data demonstrate that monocytes exhibit enhanced pro-inflammatory gene expression in hypertensive individuals and identify IL18RAP and LTF as potential novel mediators of human hypertension.

Linked articles: This article is part of a themed section on Immune Targets in Hypertension. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.12/issuetoc.

Figure 1

(A) Hierarchical clustering of normalized RPKM for those genes that were identified as significantly differentially expressed using RNASeq. Intensity of red or green is used to show fold increase or decrease respectively. Columns represent individual samples, and each row represents one gene. (B) PCA of the 60 significant genes. Three components were sufficient to describe 80.6% of the variability among samples (48.8, 20.2 and 11.6% on the X, Y and Z axes respectively). (C) Functional network generated from upstream regulator analysis using IPA software. The three central proteins were predicted to be activated using IPA (P values = 1.5 × 10‐11 to 1.5 × 10‐9, Z scores = 2.9 to 3.9). Peripheral genes are overlaid with RNASeq expression values. Red or green colour represents up‐ or down‐regulation respectively. Intensity of the colour represents the degree of change. Orange lines with arrows indicate that directionality of the downstream gene is consistent with predicted activation of the upstream regulator. Yellow lines indicate inconsistent results between gene expression and IPA's knowledge base for that particular interaction. Grey lines indicate that directionality cannot be resolved. Gene abbreviations are defined in Supporting Information Table S3.

Figure 2

Univariate regressions of MAP and the expression (log₍₁₀₎RPKMs) of those genes that significantly correlated with MAP in multivariate regression analyses: (A) LTF, (B) PGLYRP1, (C) GZMH and (D) IL18RAP. Data are from control normotensive subjects (C, n = 5) and from hypertensive subjects (HTN, n = 7). Pearson correlation coefficients ( r ), when significant (P < 0.05), are given for controls, hypertensive subjects and all subjects analysed together (All, n = 12).

Figure 3

Relative RT‐PCR quantification (normalized to GAPDH) of (A) LTF, (B) PGLYRP1, (C) GZMH and (D) IL18RAP in a validation cohort of normotensive (n = 6) and hypertensive (n = 9) patients. Data are plotted as mean ± SEM. ^* P < 0.05, significantly different as indicated; Student's t‐test or Mann–Whitney test.

Figure 4

Correlation between MAP and IL18RAP expression (A) and between eGFR and IL18RAP expression (B) in hypertensive individuals (n = 76). Pearson correlation coefficients ( r ) are shown when significant (P < 0.05).

Figure 5

PheWAS Manhattan plot for the LTF SNP rs1126478 showing association between this SNP and 1416 different phenotypes. Disease groups on the x‐axis are shown in different colours, and the y‐axis reflects the P value for each phenotype. Purple and orange horizontal lines represent P value of 0.05 and Bonferroni corrected P value of 3.5 × 10⁻⁵ respectively.