Background
Hypertension is a major source of cardiovascular morbidity and mortality in the United States [
1,
2]. Major risk factors for hypertension include dietary sodium, physical inactivity, alcohol intake, and obesity [
1]. While effective dietary and drug therapies exist to treat elevated blood pressure, our understanding of the biology and causes of hypertension remains incomplete.
Human and animal studies suggest that both the innate and adaptive immune system may be related to hypertension [
3‐
7] although samples sizes have been limited. This link between immune cells and hypertension may help explain previous associations seen between immune cells and atherosclerosis. In a previous cross-sectional publication from the Multi-Ethnic Study of Atherosclerosis (MESA) Exam 4 (2005–2007), fresh samples were assayed for lymphocyte subsets. Investigators found that naive and memory CD4
+ T cells, and T helper type 1 (Th1) cells, analyzed as proportions of CD4
+ cells, were associated with subclinical atherosclerosis [
8,
9]. These fresh lymphocytes were from a subset of participants, at a later exam, and fewer white-cell subsets were measured in this prior study.
To investigate the links between immune cell subsets and cardiovascular disease (CVD), we used cryopreserved peripheral blood mononuclear cells (PBMC) to phenotype a range of immune cells by flow cytometry in the MESA cohort [
10]. We leveraged the availability of this data for a secondary analysis of the relationships between 30 immune cell subsets and repeated SBP measures measured over 10-years. Based on prior findings [
3‐
7] that some immune cell subsets were associated with blood pressure (primarily in mouse models), we hypothesized a priori that higher proportions of Th1, gamma delta (γδ) T cells, and Th17 cells would be associated with higher systolic blood pressure, and that higher proportions of regulatory T cells would be associated with lower systolic blood pressure [
3,
7,
11,
12]. We included the other 26 immune cell subsets measured in MESA as secondary hypotheses, to understand broadly the relationship between the immune system and systolic blood pressure.
Results
The case-cohort study sample included 1195 MESA participants, with a mean (SD) age of 64 (± 10) years, and 53% of whom were male. The mean (SD) baseline systolic blood pressure was 130.0 mmHG (21.7 mmHg) at the Exam 1 baseline visit (Table
1). The average blood pressure at baseline and the subsequent follow-up exams can be seen in Fig.
1, and it does not show a statistically significant trend with time over study follow-up.
Table 1
Characteristics of MESA subjects (n = 1087) with measures for γδ T cells, as a representative of a typical population in the study*
Age (years, SD) | 63.9 | 10.1 |
Male (n, %) | 578 | 53% |
Race/ethnicity (n, %) | | |
White | 413 | 38% |
Chinese | 135 | 12% |
Black | 314 | 29% |
Hispanic | 227 | 21% |
Diabetes (n, %) | 184 | 17% |
Smoker (n, %) | 144 | 13% |
Alcohol user (n, %) | 557 | 64% |
Statin user (n, %) | 191 | 18% |
Calcium Channel Blocker user (n, %) | 159 | 15% |
Diuretic user (n, %) | 173 | 16% |
Beta Blocker user (n, %) | 110 | 10% |
Vasodilator user (n, %) | 67 | 6% |
ACE User (n, %) | 171 | 16% |
College education (n, %) | 378 | 35% |
Intentional Exercise (met-min/week, SD) | 1527 | 2293 |
IL-6 (pg/mL, SD) | 1.64 | 1.24 |
CMV antibody titer (EU/mL, SD) | 240 | 266 |
Systolic blood pressure (mmHG, SD) | 130.0 | 21.7 |
Diastolic blood pressure (mmHG, SD) | 72.7 | 10.4 |
Total cholesterol (mg/dL, SD) | 193.9 | 35.8 |
HDL Cholesterol (mg/dL, SD) | 49.4 | 14.4 |
Body Mass Index (kg/m2, SD) | 28.3 | 5.4 |
The proportions of immune cell subsets and the number of participants contributing data to each are presented in Table
2. For example, γδ T cells averaged 6.6% of the total CD3
+ cells measured. The numbers of participants with data on any particular immune cell phenotype ranged from 770 to 1113.
Table 2
Cellular phenotypes with their molecular description, parent population, number of samples evaluated, means and standard deviations
Primary hypotheses |
Th1 | CD4+ IFN-γ+ | CD4+ | 770 | 15.3 | 9.0 |
Th17 | CD4+ IL-17A+ | CD4+ | 770 | 2.1 | 1.4 |
Tregs | CD4+ CD25+ CD127− | CD4+ | 1113 | 6.2 | 3.8 |
γδ T cells | CD3+ γδ+ | CD3+ | 1087 | 6.6 | 6.1 |
Exploratory hypotheses |
T cells | CD3+ | % Lymphocytes | 1087 | 62.7 | 13.7 |
B cells | CD19+ | % Lymphocytes | 1087 | 11.3 | 7.4 |
NK cells | CD3− CD56+ CD16+ | % Lymphocytes | 1087 | 5.0 | 5.7 |
Classical monocytes | CD14++ CD16− | CD14 total | 922 | 74.4 | 10.2 |
Intermediate monocytes | CD14+ CD16+ | CD14 total | 922 | 18.1 | 7.1 |
Non-classical monocytes | CD14DimCD16+ | CD14 total | 922 | 7.4 | 7.5 |
T helper cells | CD4+ | % Lymphocytes | 1051 | 50.0 | 11.0 |
Th2 cells | CD4+ IL-4+ | CD4+ | 770 | 2.9 | 1.8 |
Naive CD4+ cells | CD4+ CD45RA+ | CD4+ | 1051 | 26.2 | 12.1 |
Memory CD4+ cells | CD4+ CD45RO+ | CD4+ | 1051 | 51.7 | 13.4 |
CD28-senescent CD4 cells | CD4+ CD28− | CD4+ | 1051 | 13.9 | 10.0 |
CD28-CD57+ senescent CD4 cells | CD4+ CD28− CD57+ | CD4+ | 1051 | 9.9 | 8.5 |
CD4+ TEMRA | CD4+ CD45RA+ CD28− CD57+ | CD4+ | 1051 | 5.6 | 5.3 |
Activated/mature CD4+ cells | CD4+ CD38+ | CD4+ | 1051 | 26.1 | 12.1 |
CD57+ CD4+ cells | CD4+ CD57+ | CD4+ | 1051 | 22.4 | 13.0 |
Cytotoxic T cells | CD8+ | % Lymphocytes | 1062 | 23.6 | 9.3 |
Tc1 | CD8+ IFN-γ+ | CD8+ | 770 | 41.8 | 17.9 |
Tc2 | CD8+ IL-4+ | CD8+ | 770 | 7.1 | 4.9 |
Tc17 | CD8+ IL-17A+ | CD8+ | 770 | 5.4 | 5.8 |
Naive CD8+ cells | CD8+ CD45RA+ | CD8+ | 1062 | 52.4 | 14.7 |
Memory CD8+ cells | CD8+ CD45RO+ | CD8+ | 1062 | 21.7 | 10.6 |
CD28-senescent CD8 cells | CD8+ CD28− | CD8+ | 1062 | 55.6 | 15.9 |
CD28− CD57+ senescent CD8 cells | CD8+ CD28− CD57+ | CD8+ | 1062 | 44.5 | 15.9 |
CD8+ TEMRA | CD8+ CD45RA+ CD28− CD57+ | CD8+ | 1062 | 32.8 | 14.3 |
Activated/mature CD8+ cells | CD8+ CD38+ | CD8+ | 1062 | 23.6 | 12.2 |
CD57+ CD8+ cells | CD8+ CD57+ | CD8+ | 1062 | 59.3 | 15.4 |
Of the four primary immune cell subsets that comprised our a priori hypotheses group (γδ T, Th1 (CD4
+IFN-γ
+), Th17 (CD4
+IL-17A
+), and Tregs (CD4
+CD25
+CD127
−)), only γδ T cells were significantly associated with systolic blood pressure (Table
3). A one standard deviation (1-SD) increment in the proportion of γδ T cells was associated with a 2.40 mmHg [95% confidence interval (CI) 1.34–3.42] higher level of systolic blood pressure. This association was significant after Bonferroni correction.
Table 3
Associations between lymphocyte subsets (per 1-SD) and average systolic blood pressure level (mmHG) across 10 years of follow-up
Primary hypotheses (significance threshold p < 0.0125) |
Th1 | 1.19 | − 0.41 | 2.79 | 0.15 |
Th17 | − 0.06 | − 1.31 | 1.18 | 0.92 |
Tregs | 1.09 | 0.05 | 2.13 | 0.04 |
γδ T | 2.40 | 1.34 | 3.42 | < 0.0001 |
Exploratory hypotheses (significance threshold p < 0.0017) |
T cells | − 1.22 | − 2.34 | − 0.09 | 0.03 |
B cells | − 0.45 | − 1.6 | 0.7 | 0.44 |
NK cells | 1.88 | 0.82 | 2.94 | 0.0005 |
Classical monocytes | − 2.01 | − 3.24 | − 0.79 | 0.0013 |
Intermediate monocytes | 0.98 | − 0.31 | 2.28 | 0.14 |
Non-classical monocytes | 1.82 | 0.64 | 3.00 | 0.0025 |
CD4+ | − 0.15 | − 1.19 | 0.89 | 0.78 |
Th2 | − 0.14 | − 1.45 | 1.18 | 0.84 |
Naïve CD4+ | 0.18 | − 0.97 | 1.34 | 0.76 |
Memory CD4+ | 0.49 | − 0.68 | 1.65 | 0.41 |
CD4+ CD28− | − 0.19 | − 1.34 | 0.96 | 0.75 |
CD4+ CD28− CD57+ | − 0.04 | − 1.17 | 1.08 | 0.94 |
CD4+ TEMRA | 0.45 | − 0.53 | 1.43 | 0.37 |
CD4+ CD38+ | − 0.36 | − 1.51 | 0.80 | 0.54 |
CD4+ CD57+ | 0.05 | − 1.07 | 1.17 | 0.93 |
CD8+ | 0.11 | − 1.02 | 1.24 | 0.85 |
Tc1 | 1.24 | − 0.11 | 2.59 | 0.07 |
Tc2 | − 0.93 | − 2.21 | 0.34 | 0.15 |
Tc17 | 0.49 | − 0.90 | 1.88 | 0.49 |
Naïve CD8+ | 0.97 | − 0.15 | 2.09 | 0.09 |
Memory CD8+ | − 1.02 | − 2.13 | 0.09 | 0.07 |
CD8+ CD28− | 0.91 | − 0.28 | 2.09 | 0.13 |
CD8+ CD28− CD57+ | 0.69 | − 0.46 | 1.84 | 0.24 |
CD8+ TEMRA | 0.99 | − 0.13 | 2.12 | 0.08 |
CD8+ CD38+ | 0.53 | − 0.58 | 1.64 | 0.35 |
CD8+ CD57+ | 0.42 | − 0.67 | 1.52 | 0.45 |
After adjusting for multiple comparisons, three other immune cell subsets, included in our exploratory secondary analyses, were also associated with systolic blood pressure; two were significant using a Bonferroni criteria (natural killer cells and classical monocytes), while using FDR added one additional immune cell subset (non-classical monocytes). A 1-SD increment in the proportion of natural killer cells was associated with a 1.88 mmHG (95% CI 0.82–2.94) higher level of systolic blood pressure during follow-up. The two other immune cell subsets associated with systolic blood pressure were both monocytes. A 1-SD increase in classical monocytes (characterized as CD14
++CD16
−) was associated with a 2.01 mmHG (95% CI 0.79–3.24) lower level of systolic blood pressure. While barely missing the Bonferroni threshold, a 1-SD increment in non-classical monocytes (characterized as CD14
dimCD16
++) was associated with a 1.82 mmHG (95% CI 0.64–3.00) higher level of systolic blood pressure. In sensitivity analyses, using a false discovery rate approach [
19] instead of the Bonferroni approach (FDR cutoff for non-classical monocytes is 0.0068 versus an observed p-value of 0.0025), results for non-classical monocytes would also be considered statistically significant.
In further exploratory analyses, we looked for interaction of our main findings with sex, race, BMI, and age. The data, shown in the Additional file
2: Tables S2–S5, were null for all interactions, although some interactions had relatively large point estimates that were imprecise and could not exclude the null hypothesis. There was some limited evidence of effect modification for γδ T cells by the use of antihypertensive medications (
p = 0.0203) (Table
4). For all of the other cell types, there was no statistically significant evidence of effect measure modification on the linear scale.
Table 4
Stratification by anti-hypertensive medication use of the immune cell subsets with a statistically significant main effect to test for effect measure modification
Any antihypertensive medication use (median SBP 131 mmHG) n = 1852 repeated SBP measures |
CD3+ γδ+ | 5.10 | 3.03 | 7.17 | < .0001 |
CD3− CD56+ CD16+ | 2.25 | 1.06 | 3.45 | 0.0002 |
CD14++ CD16− | − 2.02 | − 3.61 | − 0.43 | 0.0127 |
CD14+ CD16+ | 1.16 | − 0.41 | 2.74 | 0.1475 |
CD14DimCD16++ | 1.52 | 0.019 | 3.30 | 0.0472 |
No antihypertensive medication use (median SBP 119.5 mmHG) n = 1928 repeated SBP measures |
CD3+ γδ+ | 1.33 | 0.22 | 2.45 | 0.0194 |
CD3− CD56+ CD16+ | 0.76 | − 0.67 | 2.19 | 0.2997 |
CD14++ CD16− | − 0.79 | − 2.22 | 0.63 | 0.2756 |
CD14+ CD16+ | − 0.38 | − 1.76 | 1.00 | 0.5912 |
CD14DimCD16++ | 1.56 | − 0.027 | 3.15 | 0.0540 |
Discussion
The main finding of this study is the association of γδ T cells, natural killer cells, and two monocyte populations with average systolic blood pressure during 10 years of measurement in a large multi-ethnic population. Three of these immune-cell subsets-γδ T cells, natural killer cells, and non-classical monocytes-are pro-inflammatory cells, which may suggest an association between innate immune cell-mediated inflammation and systolic blood pressure in a multi-ethnic cohort with no baseline cardiovascular disease.
One of our a priori hypotheses, the association between higher proportions of γδ T cells and higher systolic blood pressure replicates the association seen in Caillon et al. [
3] and further builds evidence that these cells are involved in the development of human hypertension. γδ T cells respond rapidly in the initiation phase of immune reactions and act as a “bridge” between the innate and adaptive systems [
20]. The current data are consistent with animal models of hypertension where γδ T cell receptor gene deletion or addition of inhibitory γδ T cell receptor antibodies blunted endothelial dysfunction and hypertension in an angiotensin II model of hypertension in mice [
3]. γδ T cells produce the cytokine IL-17 that has been implicated in hypertension [
6,
21‐
25]. When antibodies to IL-17 were administered in a mouse model of hypertension, hypertension was attenuated, renal and vascular cellular infiltration and proinflammatory proteins, such as TGF-β, were decreased [
12,
24]. In the current study, we did not see an association of the IL-17 producing Th17 cells with systolic blood pressure, indicating the results seen previously indicating a role for IL17 may have been due to IL-17 production by γδ T cells or other IL17-producing cells.
In our exploratory analysis, we discovered an association between increased proportions of natural killer cells and levels of systolic blood pressure. Like γδ T cells, NK cells play a critical role in viral infection [
20]. Natural killer cells are non-specific responders to bacterial or viral particles or infected cells and can produce IFN-γ and other cytokines that have been shown to be associated with hypertension [
6,
21‐
26]. IFN-γ knockout mice were protected from angiotensin II induced vascular and kidney dysfunction [
23]. In contrast, IFN-γ receptor knock out mice did not have the response to angiotensin II induced hypertension, although cardio-protective effects were noted [
27]. While the current study does not show an association with the IFN-g producing adaptive immune cells (Th1, Tc1), the association of NK cells, which are a major source of IFN-γ, supports the role of IFN-γ in hypertension in humans.
Monocytes are an important component of the innate immune system and previous studies have implicated monocytes in atherosclerosis [
28]. Monocytes have shown associations with blood pressure in several animal models [
7,
29,
30] and these cells are related to both tissue remodeling in the vasculature as well as vascular inflammation [
7]. Current anti-hypertensive medications (such as Angiotensin-converting enzyme inhibitors and Angiotensin II Receptor Blockers) can directly influence monocyte behavior, making it a plausible target for therapy [
7]. The associations with systolic blood pressure observed here, with a shift from classical to the more pro-inflammatory non-classical monocytes, suggest a potential for further refinement of possible drug targets as well as a better understanding of the origins of hypertension. Notably, this may be an especially attractive line of research as monocytes are also thought to be involved in organ damage due to hypertension [
7].
These data support other recent studies showing important links between the immune system and diseases, including both cardiovascular and kidney disease [
31‐
33]. This includes evidence that the neutrophil-to-lymphocyte ratio is a predictor of mortality and/or kidney dysfunction in older patients with hypertension [
31,
32], although neither of these studies looked at antihypertensive medications. This makes the possible effect modification of γδ T cells with anti-hypertensive medication use observed in the current study of potential interest for designing prospective future studies with adequate power linking the immune system and hypertension for prediction. Finally, there is a clear advantage in being able to sub-type immune cells, as cruder approaches to classifying immune cells do not show significant differences between hypertensive and non-hypertensive participants [
25].
The strengths of this study include the large sample size, the large panel of cell subsets evaluated and the long term, longitudinal measures of systolic blood pressure. The limitations include the observational nature of the data and technical issues with complex samples which resulted in some missing data. The use of cryopreserved PBMCs may result in different absolute levels of some of the subsets as compared with whole blood [
25], although relative levels should be preserved [
34]. Further, the immune cell distributions measured in this study from cryopreserved samples are similar to those previously measured in fresh whole blood obtained in MESA at Exam 4 (2005–2007) [
8,
9] among phenotypes measured in both studies. Furthermore, participants treated with different anti-hypertensive medications may alter underlying biological relationships between some immune cell subsets and systolic blood pressure. Due to the variety of medications used in this cohort, we were not powered to see these relationships. It is also unknown how interventions on the immune cells will translate into therapeutic results; additional intervention studies will be required to allow translation of these results [
35]. As a general correction for the direct effect of the medication, we added 10 mmHg to participants’ systolic blood pressure who were being treated [
15‐
18], and any approach to accounting for medication use can have some measurement error.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.