Cardiovascular Research

Cardiovascular Research 2003 60(1):141-146; doi:10.1016/S0008-6363(03)00362-6
© 2003 by European Society of Cardiology

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Copyright © 2003, European Society of Cardiology

Enhanced expression of inflammatory cytokines and activation markers in T-cells from patients with chronic heart failure

Arne Yndestad^a,*, Are M Holm^a,b, Fredrik Müller^a, Svein Simonsen^c, Stig S Frøland^a,b, Lars Gullestad^d and Pål Aukrust^a,b

^aResearch Institute for Internal Medicine, Rikshospitalet, University of Oslo, N-0027 Oslo, Norway
^bSection of Clinical Immunology and Infectious Diseases, Rikshospitalet, University of Oslo, N-0027 Oslo, Norway
^cDepartment of Cardiology, Rikshospitalet, University of Oslo, Oslo, Norway
^dMedical Department, Bærum Hospital, Sandvika, Norway

*Corresponding author. Tel.: +47-23-073-629; fax: +47-23-073-630. Email address: arne.yndestad{at}klinmed.uio.no

Received 12 November 2002; accepted 2 January 2003

	Abstract

Top Abstract 1. Introduction 2. Methods 3. Results 4. Discussion References

 
Objective: Increasing evidence supports a role for inflammation in chronic heart failure (CHF). However, the source and the mechanism for this immune activation are unknown. To address this issue we investigated the gene expression of cytokines and the surface expression of activity markers in T-cells and monocytes from CHF patients and healthy controls. Methods: Gene expression of cytokines was analysed by real-time RT-PCR and activation markers by flow cytometry in 14 CHF patients and nine healthy controls. Surface expression of activation markers for T-cells and monocytes were analysed by flow cytometry. Results: T-cells from CHF patients showed enhanced gene expression of chemokines, ligands in the tumor necrosis factor superfamily, as well as the inflammatory cytokines interferon- and interleukin-18 with similar pattern in ischemic (n = 5) and idiopathic cardiomyopathy (n = 9). In contrast, no differences in cytokine gene expression were found comparing monocytes from CHF patients and controls. Moreover, T-cells from CHF patients had enhanced surface expression of the activation markers CD69 and CD25, while there was no upregulation of the monocyte activation marker CD32 in these patients. Conclusion: T-cells may be a part of the inflammatory response during CHF independent of the etiology of the disorder. Intervention preventing unwanted T-cell activation could represent a new target in the treatment of CHF.

KEYWORDS Heart failure; Immunology; Cytokines; Leukocytes; Gene expression

	1. Introduction

Top Abstract 1. Introduction 2. Methods 3. Results 4. Discussion References

 
While inflammation is believed to contribute to the progression of chronic heart failure (CHF) [1], the source as well as the mechanisms for the observed immune activation remains to be determined. Peripheral blood mononuclear cells (PBMC) have been suggested as a potential source for increased systemic cytokine production in CHF, but the results are somewhat conflicting [2–4]. Moreover, the relative contribution to this immune activation of the various cellular subsets within the PBMC population, such as T-cells and monocytes, has not been clarified. Such knowledge will not only identify cellular sources for the persistent inflammation in CHF, but could also indirectly provide information on the potential mechanisms leading to systemic immune activation in this disorder. For example, endotoxins have been suggested to trigger immune activation in CHF, and such a mechanism would most probably primarily induce monocyte activation [5]. To further elucidate these issues we examined the mRNA levels of several cytokines and the surface expression of activity markers in T-cells and monocytes from CHF patients and controls.

	2. Methods

Top Abstract 1. Introduction 2. Methods 3. Results 4. Discussion References

 
2.1. Patients
The study population consisted of 14 patients with stable CHF for >4 months classified in New York Heart Association functional class II–IV (Table 1). All patients were on optimal medical treatment with no changes in medication during the last 3 months. None of the patients had significant concomitant disease such as infections, malignancies or connective tissue disease. The etiology of CHF was classified as coronary artery disease (CAD, n = 5) or idiopathic dilated cardiomyopathy (IDCM, n = 9) on the basis of disease history and coronary angiographic examination. For comparison, blood samples were also collected from nine sex- and age-matched healthy blood donors. Signed informed consent was obtained from each individual. The investigation conforms to the principles outlined in the Declaration of Helsinki (Cardiovascular Research 1997;35:2–3).

View this table: [in this window] [in a new window]   Table 1

 
2.2. Isolation of cells
PBMC were obtained from heparinized blood by Isopaque-Ficoll (Lymphoprep, Nycomed, Oslo, Norway) gradient centrifugation. Further separation of monocytes (CD14-labeled magnetic beads; MACS, Miltenyi Biotec, Bergisch Gladbach, Germany) and CD3⁺ T-cells (negative selection by monodisperse immunomagnetic beads; Dynal, Oslo, Norway) was performed as described elsewhere [6,7]. After isolation, the cells were immediately stored in liquid nitrogen. The selected T-cells consisted of >90% CD3⁺ cells and the isolated monocytes of >95% CD14⁺ cells (flow cytometry).

2.3. Real-time quantitative RT-PCR
Total RNA for real-time quantitative RT-PCR was isolated from frozen T-cells and monocytes using RNeasy Minikit (Qiagen, Hilden, Germany), subjected to DNase I treatment (RQI DNase; Promega, Madison, WI, USA) and stored at –80°C. Primers and TaqMan probes were designed using the Primer Express software version 1.5 (Applied Biosystems, Foster City, CA, USA) (Table 2). Quantification of mRNA was performed using the ABI Prism 7700 (Applied Biosystems) [3]. SyBr Green assays (Table 2) were performed using 2 x SyBr Green Universal Master Mix (Applied Biosystems) and 300 nM sense and anti-sense primers. The specificity of the SyBr Green assays was assessed by melting point analysis and gel electrophoresis. Gene expression of the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Applied Biosystems) was used for normalisation.

View this table: [in this window] [in a new window]   Table 2 Characteristics of the real-time PCR assays used in the study

 
2.4. Flow cytometry
PBMC for flow cytometry analyses were cryopreserved and stored in liquid nitrogen as previously described [8]. Four-coloured immunofluorescent phenotyping using phycoerythrin-conjugated anti-CD32, anti-CD69, anti-HLA-DR or isotype-matched control antibody in combination with fluorescein isothiocyanate-conjugated anti-CD14 and anti-CD3, peridinin chlorophyll protein-conjugated anti-CD4 and allophycocyanin-conjugated anti-CD3, anti CD25 and anti-CD8 (all antibodies from PharMingen, San Diego, CA, USA) were performed by a FACSCalibur flow cytometer and CellQuest software (Becton Dickinson Immunocytometry Systems, San Jose, CA, USA). List mode files were collected for 20 000 cells from each sample.

2.5. Statistical analyses
When comparing differences between groups the Mann–Whitney U-test was used. Data are given as mean±S.E.M. if not otherwise stated. Probability values are two-sided and taken as statistically significant at <0.05.

	3. Results

Top Abstract 1. Introduction 2. Methods 3. Results 4. Discussion References

 
3.1. Differential gene expression in T-cells and monocytes
Comparing CHF patients and controls, we found that T-cells from CHF patients showed significantly enhanced gene expression of the tumor necrosis factor (TNF) superfamily ligands TNF (1.8-fold) and Fas ligand (L) (5.5-fold) and the inflammatory cytokines interferon (IFN) and interleukin (IL)-18 (2.9-fold). T-cells from CHF patients had also increased gene expression of the chemokines macrophage inflammatory protein (MIP)-1 (7.4-fold) and growth related oncogene (GRO) (3.0-fold), although the difference for GRO did not reach statistical significance (P = 0.18) (Fig. 1). Also, the gene expression of the anti-inflammatory cytokine IL-10 was significantly increased in T-cells from CHF patients comparing healthy controls (2.3-fold) (Fig. 1).

View larger version (40K): [in this window] [in a new window] [Download PowerPoint slide]   Fig. 1 Gene expression, quantified by real-time quantitative RT-PCR and related to glyceraldehyde-3-phosphate dehydrogenase (GAPDH), of tumor necrosis factor (TNF) (A), FasL (B), macrophage inflammatory protein (MIP)-1 (C), growth-related oncogene (GRO) (D), interferon (IFN)- (E), interleukin (IL)-18 (F), IL-10 (G) and IL-6 (H) in CD3+ T-cells and CD14+ monocytes from healthy blood donors (n = 9) and CHF patients (n = 14). Values are expressed as mean±S.E.M. *P<0.05 and **P<0.01 vs. controls. n.d., not determined.

 
In contrast to this enhanced expression of inflammatory genes in T-cells, monocytes from CHF patients showed no upregulation of these genes (Fig. 1). In fact, we found a tendency for downregulation of IL-18 in monocytes from CHF patients (32% reduction, P = 0.08) (Fig. 1). As for IL-6 in T-cells and IFN in monocytes the gene expression was too weak to yield reliable quantitative results. Apart from moderately lower IL-18 mRNA levels in monocytes from CHF patients with CAD (n = 5) comparing those with IDCM (n = 9), there were no significant differences in mRNA levels according to CHF etiology in either T-cells or monocytes (Table 3). Moreover, while all patients received ACE-inhibitors and diuretics, β-blockers, HMG-CoA reductase inhibitors and aldosterone inhibitors were not used by the whole study population (Table 1), but importantly, there were no tendencies for differences in gene expression with regard to the patients’ medication.

View this table: [in this window] [in a new window]   Table 3 Gene expression of cytokines in T-cells and monocytes from patients with idiopathic and ischemic cardiomyopathy

 
3.2. T-cell and monocyte activation as assessed by flow cytometry
To further examine the role of T-cells and monocytes in the systemic inflammatory response during CHF, we analyzed the surface expression of activation markers on these cells by flow cytometry. Notably, while the percentage of T-cells as well as the proportion of CD4⁺ and CD8⁺ T-cells were similar in PBMC from CHF patients and controls, the percentage of T-cells expressing the early activation marker CD69 was significantly increased in CHF patients as compared to controls (2.1±0.44 versus 1.0±0.11%, P<0.02; Fig. 2). Similarly, while 4.3±0.37% of T-cells in CHF patients expressed CD25, this activation marker was found on the surface of only 3.0±0.50% of T-cells in healthy controls (P<0.05; Fig. 2). A similar pattern with enhanced CD69 and CD25 expression in CHF was found in both CD4⁺ and CD8⁺ T-cells. As for the percentage of T-cells expressing the late activation marker HLA-DR there was no difference between CHF patients and controls (2.6±0.41 versus 3.3±0.91%, respectively; Fig. 2). Thus, although we lack cytokine protein data, these findings suggest T-cell activation in CHF as assessed by both mRNA and protein (i.e. flow cytometry) analyses. In contrast to these signs of T-cell activation, there was no difference in the expression of the activation marker CD32 on monocytes comparing CHF patients and controls. Thus, all monocytes from both patients and controls expressed CD32, and the mean fluorescence intensity of CD32 did not differ between these groups (659±30.8 versus 702±112.6, CHF patients and controls, respectively). However, PBMC from CHF patients contained a higher percentage of monocytes than PBMC from healthy controls (18±2.3 versus 12±1.4%, P<0.05).

View larger version (42K): [in this window] [in a new window] [Download PowerPoint slide]   Fig. 2 Flow cytometry analysis of the activation markers CD69, CD25 and HLA-DR in CHF patients compared to healthy controls. Analysis was performed gating on CD3+ cells, and dead cells were excluded by forward/side scatter gating. Figures indicate percentages of CD69+, CD25+ or HLA-DR+ cells, respectively, and are representative of samples from nine CHF patients and nine healthy controls.

 

	4. Discussion

Top Abstract 1. Introduction 2. Methods 3. Results 4. Discussion References

 
While most previous studies have focused on PBMC and monocytes, the present study shows that circulating T-cells are markedly activated in CHF as assessed by both enhanced mRNA levels of several inflammatory cytokines as well as by increased surface expression of activation markers. Somewhat surprisingly, no such activation was found in monocytes from the same patients. Notably, although relatively few CHF patients were studied, these signs of T-cell activation seem to be independent of the etiology of heart failure. Our findings suggest that T-cells may represent an important cellular source for the systemic inflammation and immune activation in CHF, possibly playing a pathogenic role in this disorder.

Both antigen-dependent and independent pathways may promote T-cell activation in CHF. Thus, this activation could be part of an autoimmune response against self-antigens such as β-adrenergic receptors within the myocardium [9]. Moreover, increased myocardial expression and release to the circulation of heat shock proteins may also elicit a systemic T-cell activation in these patients [10]. Furthermore, the chemokine RANTES that is upregulated in CHF [11], may directly activate T-cells in an antigen independent manner [12]. Finally, as part of the innate immune response, tissue injury and myocardial stress can itself activate antigen presenting cells residing in the myocardium, with further activation of T-cells [13]. In fact, recent studies in ischemia reperfusion models have suggested an important role for T-cells in the early inflammatory response after tissue injury [14]. Furthermore, several cytokines released from activated T-cells, such as IFN and IL-18, both found upregulated in CHF patients in the present study, can trigger a cascade of antigen-non-specific responses mediated by the innate immune system [15]. Thus, the T-cell activation in CHF may represent a link between innate and adaptive immune responses leading to an inappropriate and persistent immune activation in these patients.

Translocation of endotoxins from the oedematous bowel has been suggested to trigger a systemic immune activation during CHF [5]. Such a mechanism would be suspected to primarily provoke monocyte activation, but maybe surprisingly, although we found that CHF patients were characterized by a relative monocytosis, monocytes from these patients had no signs of increased activation or cytokine gene expression. While this finding may argue against the endotoxin hypothesis, it could also reflect a LPS-mediated desensitisation of monocytes in CHF patients [16,17].

Whatever the mechanisms, the T-cell activation in CHF could contribute to myocardial dysfunction in this disorder. Thus, infiltrating T-cells expressing FasL and TNF may promote cardiomyocyte apoptosis within the failing myocardium [18]. Moreover, we found that T-cells in CHF showed enhanced expression of MIP-1 and GRO and notably, we have recently demonstrated that their corresponding receptors are expressed in cardiomyocytes, suggesting a potential for inflammatory interaction involving T-cell mediated mechanisms within the failing myocardium [19]. A role for T-cells in the promotion of myocardial failure is also supported by studies in animal models demonstrating T-cell activation during cardiac injury and importantly, these T-cells have been found to retain a memory response against cardiomyocytes recognizing and killing these cells [20].

In the present study we, to the best of our knowledge, for the first time report that the systemic inflammatory response in CHF patients as assessed by enhanced expression of inflammatory cytokines in PBMC, reflects T-cell and not monocyte activation. Intervention that prevents this unwanted T-cell activation could represent a new target in the treatment of this disorder.

	Acknowledgements

 
We thank Cecilia Guevara, Elin Kjekshus, Bodil Lunden and Rita Skårdal for excellent technical assistance.

	Notes

 
Time for primary review 22 days.

	References

Top Abstract 1. Introduction 2. Methods 3. Results 4. Discussion References

 

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