# Chlamydia pneumoniae-Mediated Inflammation in Atherosclerosis: A Meta-Analysis

Authors: Simone Filardo; Marisa Di Pietro; Alessio Farcomeni; Giovanna Schiavoni; Rosa Sessa
Journal: Mediators of Inflammation
 (2015)

---

## Abstract

Several studies have attempted to relate theC. pneumoniae-mediated inflammatory state with atherosclerotic cardiovascular diseases, providing inconsistent results. Therefore, we performed a meta-analysis to clarify whether C. pneumoniae may contribute to the pathogenesis of atherosclerosis by enhancing inflammation. 12 case-control, 6 cross-sectional, and 7 prospective studies with a total of 10,176 patients have been included in this meta-analysis. Odds Ratio (OR) with a 95% confidence interval was used to assess the seroprevalence of C. pneumoniae and differences between levels of inflammatory markers were assessed by standard mean differences. Publication bias was performed to ensure the statistical power. hsCRP, fibrinogen, interleukin- (IL-) 6, TNF-α, and IFN-γ showed a significant increase in patients with atherosclerosis compared to healthy controls (P
<
0.05), along with a higher seroprevalence of C. pneumoniae (OR of 3.11, 95% CI: 2.88–3.36, P
<
0.001). More interestingly, hsCRP, IL-6, and fibrinogen levels were significantly higher in C. pneumoniae IgA seropositive compared to seronegative atherosclerotic patients (P
<
0.0001). In conclusion, the present meta-analysis suggests that C. pneumoniae infection may contribute to atherosclerotic cardiovascular diseases by enhancing the inflammatory state, and, in particular, seropositivity to C. pneumoniae IgA, together with hsCRP, fibrinogen, and IL-6, may be predictive of atherosclerotic cardiovascular risk.


---

## Body

## 1. Introduction

Atherosclerosis, a chronic inflammatory disease of multifactorial aetiology, typically begins with endothelial dysfunction followed by low density lipoprotein (LDL) infiltration of the arterial intima, mononuclear cell recruitment into vascular wall, and the differentiation of macrophages in foam cells [1, 2]. Macrophages and foam cells, within the evolving atherosclerotic lesion, secrete various proinflammatory cytokines, such as interleukin- (IL-) 6, interferon- (IFN-) γ, tumor necrosis factor- (TNF-) α, and chemokines, including intercellular adhesion molecule- (ICAM-) 1 and vascular cell adhesion molecule- (VCAM-) 1. In response to proinflammatory cytokines, endothelial cells express high levels of leukocyte adhesion molecules on their surface, leading to further mononuclear cell recruitment and, hence, to a chronic inflammatory state [3, 4]. As a result, the formation, progression, and destabilisation of atherosclerotic plaque occur, leading to cardiovascular diseases, a major public health problem in developed countries, accounting for one-third of all deaths worldwide [5].In the last decades, several infectious agents have been related to the pathogenesis of atherosclerotic cardiovascular diseases, and current opinion is that the most implicated pathogen isChlamydia pneumoniae, an obligate intracellular microorganism, known as being responsible for respiratory tract infections [6, 7].The association betweenC. pneumoniae and atherosclerotic cardiovascular diseases has been well documented by seroepidemiological studies [8–12], direct detection of microorganism within atherosclerotic plaque [13–17], and in vivo studies showing an atherosclerotic lesion exacerbation followingC. pneumoniae inoculation of hyperlipidemic animal models [18–23].C. pneumoniae is presumed to play a role in atherosclerotic cardiovascular diseases for its ability to systematically disseminate from the lung through peripheral blood mononuclear cells and to localise in extrapulmonary tissues, such as the vascular wall [24–28]. Once being inside the vascular tissue,C. pneumoniae has been shown to act directly on the cells involved in atherosclerotic process, contributing to endothelial dysfunction, foam cell formation, vascular smooth muscle cell (VSMC) proliferation and migration, and platelet aggregation [29–33]. Indeed,C. pneumoniae is able to multiply within macrophages, platelets, endothelial cells, and VSMCs and to induce the elicitation of proinflammatory cytokines, such as IL-6, IFN-γ, and TNF-α, and adhesion molecules, such as ICAM-1 and VCAM-1, as well as reactive oxygen species, thus contributing to the chronic inflammatory state responsible for the initiation, progression, and destabilisation of atherosclerotic plaque [34–40].Specifically,C. pneumoniae persistent form seems to be responsible for chronic infection and, hence, for the inflammatory process underlying atherosclerosis, since it is able to endure for a long time inside host cells [41, 42].In addition to the direct effect on vascular cells, previously described,C. pneumoniae has also shown to contribute to the systemic inflammation involved in the pathogenesis of atherosclerotic cardiovascular diseases, as evidenced by high levels of IL-6 and high sensitivity c-reactive protein (hsCRP) [7, 43].Given the central role of inflammation in the atherosclerotic process and the inflammatory effects ofC. pneumoniae, several studies have attempted to relate theC. pneumoniae-mediated inflammatory state with atherosclerotic cardiovascular diseases, providing inconsistent results.We performed, therefore, a meta-analysis to clarify whetherC. pneumoniae may contribute to the pathogenesis of atherosclerotic cardiovascular diseases by the means of enhanced inflammatory state.


## 2. Materials and Methods

### 2.1. Search Strategy

We performed a systematic search of all articles in journals indexed on the electronic databases PubMed and Scopus up to December 2014. The search terms used were “chlamydia pneumoniae” or “chlamydophila pneumoniae,” “inflammatory markers” or “inflammation,” “atherosclerosis,” and “cardiovascular disease.” The reference lists of reviews and retrieved articles were hand-searched simultaneously. When more than one of the same patient population was included in several publications, only the most recent or complete study was included in this meta-analysis.


### 2.2. Inclusion and Exclusion Criteria

The inclusion criteria in this meta-analysis were as follows: (i) studies comparing atherosclerotic patients with healthy subjects (control group) in relation to the seropositivity toC. pneumoniae IgG or IgA, (ii) studies comparing atherosclerotic patients in relation to the seropositivity toC. pneumoniae IgG or IgA, and (iii) studies analysing the levels of inflammatory markers.Case reports, reviews, letters, and studies which did not present their results in a correct and/or explicit manner, animal studies, and studies where the control groups were made up of patients with other chronic inflammatory disorders were excluded from our meta-analysis. We did not define any minimum number of patients to include a study in our meta-analysis.


### 2.3. Data Extraction

Information was carefully extracted from all eligible publications independently by two authors according to the inclusion and exclusion criteria listed above. Disagreement was resolved by discussion between the two authors. The following data were collected from each study: first author’s surname, year of publication, study design, type of cases, type of controls, total numbers of cases and controls, prevalence of traditional risk factors for CVD (obesity, diabetes, smoking, dyslipidemia, and hypertension), the prevalence ofC. pneumoniae antibodies (IgA or IgG), determined by microimmunofluorescence or ELISA, and the levels of inflammatory markers (CRP, IL-6, fibrinogen, IFN-γ, TNF-α, ICAM-1, and VCAM-1).Only inflammatory markers analysed by at least two studies were included in our meta-analysis.


### 2.4. Statistical Analysis

Differences between groups were assessed by means of differences in averages and standard deviations of the difference, as markers assessed were all continuous. Standard errors were computed after a normal approximation. Pooled effects were computed by means of a meta-analysis. The meta-analysis conducted was strictly under heterogeneity among studies, by means of a hierarchical Bayesian model. Effect sizes were assumed to be normally distributed. Each study effect was assumed to arise from a Gaussian centered on a study-specific effect and the extracted standard error, inflated by 25% to obtain a conservative statement. The study-specific effect was assumed to be Gaussian, centered on an unknown pooled effect, which is the main object of interest. An informative prior was used for the variance of the pooled effect, as an inverse Gamma centered on an estimator obtained with a moment-based approach (inflated by 25% to obtain a conservative statement). We also estimated posterior probabilities of no difference (P). P of less than 0.05 was considered as statistically significant. Potential publication bias was estimated using Egger’s linear regression test and funnel plots. Sensitivity analyses were assessed by deleting each study; in all cases, pooled estimates were very stable.All data were collected using Microsoft Office Excel 2007; statistical analyses were performed using R software.


## 2.1. Search Strategy

We performed a systematic search of all articles in journals indexed on the electronic databases PubMed and Scopus up to December 2014. The search terms used were “chlamydia pneumoniae” or “chlamydophila pneumoniae,” “inflammatory markers” or “inflammation,” “atherosclerosis,” and “cardiovascular disease.” The reference lists of reviews and retrieved articles were hand-searched simultaneously. When more than one of the same patient population was included in several publications, only the most recent or complete study was included in this meta-analysis.


## 2.2. Inclusion and Exclusion Criteria

The inclusion criteria in this meta-analysis were as follows: (i) studies comparing atherosclerotic patients with healthy subjects (control group) in relation to the seropositivity toC. pneumoniae IgG or IgA, (ii) studies comparing atherosclerotic patients in relation to the seropositivity toC. pneumoniae IgG or IgA, and (iii) studies analysing the levels of inflammatory markers.Case reports, reviews, letters, and studies which did not present their results in a correct and/or explicit manner, animal studies, and studies where the control groups were made up of patients with other chronic inflammatory disorders were excluded from our meta-analysis. We did not define any minimum number of patients to include a study in our meta-analysis.


## 2.3. Data Extraction

Information was carefully extracted from all eligible publications independently by two authors according to the inclusion and exclusion criteria listed above. Disagreement was resolved by discussion between the two authors. The following data were collected from each study: first author’s surname, year of publication, study design, type of cases, type of controls, total numbers of cases and controls, prevalence of traditional risk factors for CVD (obesity, diabetes, smoking, dyslipidemia, and hypertension), the prevalence ofC. pneumoniae antibodies (IgA or IgG), determined by microimmunofluorescence or ELISA, and the levels of inflammatory markers (CRP, IL-6, fibrinogen, IFN-γ, TNF-α, ICAM-1, and VCAM-1).Only inflammatory markers analysed by at least two studies were included in our meta-analysis.


## 2.4. Statistical Analysis

Differences between groups were assessed by means of differences in averages and standard deviations of the difference, as markers assessed were all continuous. Standard errors were computed after a normal approximation. Pooled effects were computed by means of a meta-analysis. The meta-analysis conducted was strictly under heterogeneity among studies, by means of a hierarchical Bayesian model. Effect sizes were assumed to be normally distributed. Each study effect was assumed to arise from a Gaussian centered on a study-specific effect and the extracted standard error, inflated by 25% to obtain a conservative statement. The study-specific effect was assumed to be Gaussian, centered on an unknown pooled effect, which is the main object of interest. An informative prior was used for the variance of the pooled effect, as an inverse Gamma centered on an estimator obtained with a moment-based approach (inflated by 25% to obtain a conservative statement). We also estimated posterior probabilities of no difference (P). P of less than 0.05 was considered as statistically significant. Potential publication bias was estimated using Egger’s linear regression test and funnel plots. Sensitivity analyses were assessed by deleting each study; in all cases, pooled estimates were very stable.All data were collected using Microsoft Office Excel 2007; statistical analyses were performed using R software.


## 3. Results

### 3.1. Study Characteristics

25 studies concerning the association ofC. pneumoniae and atherosclerosis through inflammation met the inclusion criteria and comprised 12 case-control, 6 cross-sectional, and 7 prospective studies [44–68]. Overall, a total of 3633 cases and 2781 controls for the case-control analysis, 1593 seropositive and 915 seronegative patients for theC. pneumoniae IgG seropositive-seronegative analysis, and 528 seropositive and 726 seronegative patients for theC. pneumoniae IgA seropositive-seronegative analysis were considered. One publication had apparently overlapping cases with a second study, so that we extracted only the most relevant data from both studies. Table 1 presents the main characteristics of the included studies for the case-control analysis, whereas Table 2 presents the main characteristics of the included studies for the seropositive to seronegative analysis according toC. pneumoniae IgG and IgA. Controls were mainly healthy population and matched for age and sex.Table 1
Characteristics of the studies included in the case-control analysis.
First author
Year
Country
Cases
Number of cases
Number of controls
Study design
Serology assay
Mundkur [68]
2012
India
CAD
433
433
Prospective
ELISA
Haider [67]
2011
India
CAD
63
40
Cross-sectional
ELISA
Jha [65]
2009
India
CAD
192
192
Case-control
ELISA
Jafarzadeh [64]
2008
Iran
IHD
62
31
Case-control
ELISA
Videm [63]
2007
Norway
CAD
131
103
Case-control
ELISA
Corrado [59]
2006
Italy
A
456
212
Prospective
ELISA
Kaperonis [61]
2006
Greece
PAD
51
30
Cross-sectional
ELISA
Romano Carratelli [62]
2006
Italy
CAD
60
20
Case-control
MIF
Adiloglu [57]
2005
Turkey
A
88
91
Case-control
ELISA
Lanza [55]
2004
Italy
SA, cardiac SX
104
60
Case-control
MIF
Linares-Palomino [56]
2004
Spain
PAD
64
50
Case-control
MIF
Biasucci [51]
2003
Italy
UA, MI
259
100
Prospective
MIF
Georges [53]
2003
Germany
SA, UA
991
333
Case-control
MIF
Bloemenkamp [49]
2002
Netherlands
PAD
228
643
Case-control
ELISA
Gattone [46]
2001
Italy
MI
120
120
Case-control
MIF
Anderson [44]
1998
USA
CAD, MI
331
323
Case-control
MIF
CAD, coronary artery disease; IHD, ischemic heart disease; A, atherosclerosis; PAD, peripheral artery disease; SA, stable angina; SX, syndrome X; UA, unstable angina; MI, myocardial infarction.Table 2
Characteristics of the studies included in theC. pneumoniae IgG and IgA analysis.
First author
Year
Country
Cases
Number of cases
Number of controls
Study design
Serology assay
IgG
Nazmi [66]
2010
USA
CAD
697
288
Cross-sectional
MIF
Jitsuiki [60]
2006
Japan
A
136
123
Cross-sectional
ELISA
Adiloglu [57]
2005
Turkey
A
227
17
Case-control
ELISA
Zairis [54]
2003
Greece
SA, UA
182
214
Prospective
MIF
Altman [48]
2002
Argentina
CAD
107
52
Case-control
MIF
Schumacher [50]
2002
Norway
CAD
119
74
Cross-sectional
ELISA
Sander [47]
2001
Germany
TIA, IS
125
147
Prospective
MIF
IgA
Jha [65]
2009
India
CAD
155
37
Case-control
ELISA
Jitsuiki [60]
2006
Japan
A
92
167
Cross-sectional
ELISA
Schumacher [58]
2005
Norway
CAD
63
130
Cross-sectional
MIF
Gabriel [52]
2003
Sweden
CAD
38
15
Prospective
MIF
Zairis [54]
2003
Greece
SA, UA
87
214
Prospective
MIF
Toss [45]
1998
Sweden
UA
93
163
Prospective
MIF
CAD, coronary artery disease; A, atherosclerosis; SA, stable angina; UA, unstable angina; TIA, transient ischemic attack; IS, ischemic stroke.


### 3.2. Meta-Analysis Results

The meta-analysis was performed on 16 studies (case-controls analysis, Table1) comparing atherosclerotic patients with healthy controls in relation to the seropositivity toC. pneumoniae and levels of inflammatory markers (hsCRP, IL-6, fibrinogen, TNF-α, IFN-γ, ICAM-1, and VCAM-1) [44, 46, 49, 51, 53, 55–57, 59, 61–65, 67, 68].C. pneumoniae seroprevalence was 59.2% (95% CI: 57.8–60.7) in cases and 31.2% (95% CI: 30.0–32.5) in controls, with an OR of 3.11 (95% CI: 2.88–3.36, P
<
0.001). Concerning the inflammatory markers, hsCRP, IL-6, fibrinogen, TNF-α, and IFN-γ showed a significant increase in patients with atherosclerosis compared to health controls (P
<
0.05), whereas the adhesion molecules ICAM-1 and VCAM-1 did not show any significant difference (P
>
0.05) (Table 3, Figure 1).Table 3
Summary of SMDs and 95% CI of inflammatory marker levels in case-control analysis.
hsCRP (mg/L)
IL-6 (ng/mL)
Fibrinogen (mg/dL)
TNF-α (pg/mL)
IFN-γ (pg/mL)
ICAM-1 (ng/mL)
VCAM-1 (ng/mL)
SMD
6.360
7.861
5.627
9.467
4.320
0.001
3.722
95% CI
5.76–6.96
7.40–8.32
0.65–10.60
6.45–12.49
2.32–6.32
−0.25–0.25
−1.46–8.90
P value
<0.0001
<0.0001
0.00895
<0.0001
<0.0001
0.49628
0.06611
SMD, standard mean difference; CI, confidence interval.Figure 1
Forest plot of standardized mean differences (SMDs) of individual studies and pooled SMDs for hsCRP (a), IL-6 (b), and fibrinogen (c) in patients with atherosclerotic cardiovascular diseases and healthy controls.
(a)
(b)
(c)In addition, the meta-analysis was also performed on studies comparing atherosclerotic patients seropositive toC. pneumoniae IgG or IgA with seronegative patients. Specifically, 7 studies comparing atherosclerotic patients seropositive toC. pneumoniae IgG with seronegative patients (C. pneumoniae IgG analysis, Table 2) [47, 48, 50, 54, 57, 60, 66] and 6 studies comparing atherosclerotic patients seropositive toC. pneumoniae IgA with seronegative patients (C. pneumoniae IgA analysis, Table 2) [45, 52, 54, 58, 60, 65], both according to levels of inflammatory markers (hsCRP, IL-6, fibrinogen, and IFN-γ), were evaluated.For theC. pneumoniae IgG analysis, hsCRP, IL-6, and fibrinogen levels were significantly higher in seropositive compared to seronegative patients (P
<
0.0001) (Figure 2).Figure 2
Forest plot of standardized mean differences (SMDs) of individual studies and pooled SMDs for hsCRP (a), IL-6 (b), and fibrinogen (c) inC. pneumoniae IgG seropositive and seronegative patients with atherosclerotic cardiovascular diseases.
(a)
(b)
(c)For theC. pneumoniae IgA analysis, hsCRP, IL-6, and fibrinogen were markedly increased in seropositive patients (P
<
0.01), whereas IFN-γ did not show any significant difference between seropositive and seronegative patients (P
>
0.05) (Figure 3).Figure 3
Forest plot of standardized mean differences (SMDs) of individual studies and pooled SMDs for hsCRP (a), IL-6 (b), and fibrinogen (c) inC. pneumoniae IgA seropositive and seronegative patients with atherosclerotic cardiovascular diseases.
(a)
(b)
(c)Results are independent of the main confounding factors as the meta-analysis was computed under heterogeneity. We also have verified that they could not form a relationship with mean age and study proportions of males, patients with diabetes, hypertension, obesity, smoking, dyslipidemia, and risk factors for CVDs.


### 3.3. Publication Bias

Funnel plots and Egger’s test were performed to assess publication bias. Publication bias was detected only for meta-analysis of fibrinogen with IgA (P
=
0.012). In particular no publication bias was detected for hsCRP for IgA (P
=
0.200), IgG (P
=
0.890), and case-control data (P
=
0.122).


## 3.1. Study Characteristics

25 studies concerning the association ofC. pneumoniae and atherosclerosis through inflammation met the inclusion criteria and comprised 12 case-control, 6 cross-sectional, and 7 prospective studies [44–68]. Overall, a total of 3633 cases and 2781 controls for the case-control analysis, 1593 seropositive and 915 seronegative patients for theC. pneumoniae IgG seropositive-seronegative analysis, and 528 seropositive and 726 seronegative patients for theC. pneumoniae IgA seropositive-seronegative analysis were considered. One publication had apparently overlapping cases with a second study, so that we extracted only the most relevant data from both studies. Table 1 presents the main characteristics of the included studies for the case-control analysis, whereas Table 2 presents the main characteristics of the included studies for the seropositive to seronegative analysis according toC. pneumoniae IgG and IgA. Controls were mainly healthy population and matched for age and sex.Table 1
Characteristics of the studies included in the case-control analysis.
First author
Year
Country
Cases
Number of cases
Number of controls
Study design
Serology assay
Mundkur [68]
2012
India
CAD
433
433
Prospective
ELISA
Haider [67]
2011
India
CAD
63
40
Cross-sectional
ELISA
Jha [65]
2009
India
CAD
192
192
Case-control
ELISA
Jafarzadeh [64]
2008
Iran
IHD
62
31
Case-control
ELISA
Videm [63]
2007
Norway
CAD
131
103
Case-control
ELISA
Corrado [59]
2006
Italy
A
456
212
Prospective
ELISA
Kaperonis [61]
2006
Greece
PAD
51
30
Cross-sectional
ELISA
Romano Carratelli [62]
2006
Italy
CAD
60
20
Case-control
MIF
Adiloglu [57]
2005
Turkey
A
88
91
Case-control
ELISA
Lanza [55]
2004
Italy
SA, cardiac SX
104
60
Case-control
MIF
Linares-Palomino [56]
2004
Spain
PAD
64
50
Case-control
MIF
Biasucci [51]
2003
Italy
UA, MI
259
100
Prospective
MIF
Georges [53]
2003
Germany
SA, UA
991
333
Case-control
MIF
Bloemenkamp [49]
2002
Netherlands
PAD
228
643
Case-control
ELISA
Gattone [46]
2001
Italy
MI
120
120
Case-control
MIF
Anderson [44]
1998
USA
CAD, MI
331
323
Case-control
MIF
CAD, coronary artery disease; IHD, ischemic heart disease; A, atherosclerosis; PAD, peripheral artery disease; SA, stable angina; SX, syndrome X; UA, unstable angina; MI, myocardial infarction.Table 2
Characteristics of the studies included in theC. pneumoniae IgG and IgA analysis.
First author
Year
Country
Cases
Number of cases
Number of controls
Study design
Serology assay
IgG
Nazmi [66]
2010
USA
CAD
697
288
Cross-sectional
MIF
Jitsuiki [60]
2006
Japan
A
136
123
Cross-sectional
ELISA
Adiloglu [57]
2005
Turkey
A
227
17
Case-control
ELISA
Zairis [54]
2003
Greece
SA, UA
182
214
Prospective
MIF
Altman [48]
2002
Argentina
CAD
107
52
Case-control
MIF
Schumacher [50]
2002
Norway
CAD
119
74
Cross-sectional
ELISA
Sander [47]
2001
Germany
TIA, IS
125
147
Prospective
MIF
IgA
Jha [65]
2009
India
CAD
155
37
Case-control
ELISA
Jitsuiki [60]
2006
Japan
A
92
167
Cross-sectional
ELISA
Schumacher [58]
2005
Norway
CAD
63
130
Cross-sectional
MIF
Gabriel [52]
2003
Sweden
CAD
38
15
Prospective
MIF
Zairis [54]
2003
Greece
SA, UA
87
214
Prospective
MIF
Toss [45]
1998
Sweden
UA
93
163
Prospective
MIF
CAD, coronary artery disease; A, atherosclerosis; SA, stable angina; UA, unstable angina; TIA, transient ischemic attack; IS, ischemic stroke.


## 3.2. Meta-Analysis Results

The meta-analysis was performed on 16 studies (case-controls analysis, Table1) comparing atherosclerotic patients with healthy controls in relation to the seropositivity toC. pneumoniae and levels of inflammatory markers (hsCRP, IL-6, fibrinogen, TNF-α, IFN-γ, ICAM-1, and VCAM-1) [44, 46, 49, 51, 53, 55–57, 59, 61–65, 67, 68].C. pneumoniae seroprevalence was 59.2% (95% CI: 57.8–60.7) in cases and 31.2% (95% CI: 30.0–32.5) in controls, with an OR of 3.11 (95% CI: 2.88–3.36, P
<
0.001). Concerning the inflammatory markers, hsCRP, IL-6, fibrinogen, TNF-α, and IFN-γ showed a significant increase in patients with atherosclerosis compared to health controls (P
<
0.05), whereas the adhesion molecules ICAM-1 and VCAM-1 did not show any significant difference (P
>
0.05) (Table 3, Figure 1).Table 3
Summary of SMDs and 95% CI of inflammatory marker levels in case-control analysis.
hsCRP (mg/L)
IL-6 (ng/mL)
Fibrinogen (mg/dL)
TNF-α (pg/mL)
IFN-γ (pg/mL)
ICAM-1 (ng/mL)
VCAM-1 (ng/mL)
SMD
6.360
7.861
5.627
9.467
4.320
0.001
3.722
95% CI
5.76–6.96
7.40–8.32
0.65–10.60
6.45–12.49
2.32–6.32
−0.25–0.25
−1.46–8.90
P value
<0.0001
<0.0001
0.00895
<0.0001
<0.0001
0.49628
0.06611
SMD, standard mean difference; CI, confidence interval.Figure 1
Forest plot of standardized mean differences (SMDs) of individual studies and pooled SMDs for hsCRP (a), IL-6 (b), and fibrinogen (c) in patients with atherosclerotic cardiovascular diseases and healthy controls.
(a)
(b)
(c)In addition, the meta-analysis was also performed on studies comparing atherosclerotic patients seropositive toC. pneumoniae IgG or IgA with seronegative patients. Specifically, 7 studies comparing atherosclerotic patients seropositive toC. pneumoniae IgG with seronegative patients (C. pneumoniae IgG analysis, Table 2) [47, 48, 50, 54, 57, 60, 66] and 6 studies comparing atherosclerotic patients seropositive toC. pneumoniae IgA with seronegative patients (C. pneumoniae IgA analysis, Table 2) [45, 52, 54, 58, 60, 65], both according to levels of inflammatory markers (hsCRP, IL-6, fibrinogen, and IFN-γ), were evaluated.For theC. pneumoniae IgG analysis, hsCRP, IL-6, and fibrinogen levels were significantly higher in seropositive compared to seronegative patients (P
<
0.0001) (Figure 2).Figure 2
Forest plot of standardized mean differences (SMDs) of individual studies and pooled SMDs for hsCRP (a), IL-6 (b), and fibrinogen (c) inC. pneumoniae IgG seropositive and seronegative patients with atherosclerotic cardiovascular diseases.
(a)
(b)
(c)For theC. pneumoniae IgA analysis, hsCRP, IL-6, and fibrinogen were markedly increased in seropositive patients (P
<
0.01), whereas IFN-γ did not show any significant difference between seropositive and seronegative patients (P
>
0.05) (Figure 3).Figure 3
Forest plot of standardized mean differences (SMDs) of individual studies and pooled SMDs for hsCRP (a), IL-6 (b), and fibrinogen (c) inC. pneumoniae IgA seropositive and seronegative patients with atherosclerotic cardiovascular diseases.
(a)
(b)
(c)Results are independent of the main confounding factors as the meta-analysis was computed under heterogeneity. We also have verified that they could not form a relationship with mean age and study proportions of males, patients with diabetes, hypertension, obesity, smoking, dyslipidemia, and risk factors for CVDs.


## 3.3. Publication Bias

Funnel plots and Egger’s test were performed to assess publication bias. Publication bias was detected only for meta-analysis of fibrinogen with IgA (P
=
0.012). In particular no publication bias was detected for hsCRP for IgA (P
=
0.200), IgG (P
=
0.890), and case-control data (P
=
0.122).


## 4. Discussion

Atherosclerosis, precursor to cardiovascular diseases, is recognised as a chronic inflammatory disease of large arteries, involving cytokines, such as IFN-γ and TNF-α, adhesion molecules, such as ICAM-1 and VCAM-1, and several plasma inflammatory markers, such as hsCRP, IL-6, and fibrinogen [2, 3]. The latter have been demonstrated to better correlate with the chronic inflammation underlying atherosclerotic cardiovascular diseases; in fact, IL-6, a proinflammatory cytokine that plays a role in the instability of a vulnerable plaque, and hsCRP, an acute-phase protein, appear to be strong independent predictors of cardiovascular events [3]. Lastly, fibrinogen, a substrate leading to the generation of thrombin, the end point of the hemostatic process, is involved in the early formation and growth of the atherosclerotic plaque [69].As previously described,C. pneumoniae has been suggested to contribute to the chronic inflammation underlying the atherosclerotic process, as evidenced by elevated levels of circulating inflammatory markers in atherosclerotic patients. Gattone et al., in 2001, have suggested, for the first time, the association ofC. pneumoniae seropositivity and high hsCRP levels, with increased risk of myocardial infarction [46]. Since then, other studies [47, 49, 50, 52, 57, 61, 64, 67] have supported the relationship betweenC. pneumoniae infection and atherogenesis through systemic inflammation. On the other hand, some studies have failed to demonstrate such association [44, 48, 55, 68], thus making it difficult to draw conclusions.To the best of our knowledge, our study is the first meta-analysis to evaluate whetherC. pneumoniae may contribute to the pathogenesis of atherosclerotic cardiovascular diseases by the means of enhanced inflammation, assessed by levels of inflammatory markers.The first result of our meta-analysis showed a significant increase in hsCRP, fibrinogen, IL-6, TNF-α, and IFN-γ in atherosclerotic patients compared to healthy controls. These data, together with the higher seroprevalence ofC. pneumoniae in atherosclerotic patients compared to healthy controls (P
<
0.001), suggest thatC. pneumoniae infection may contribute to the chronic inflammation underlying the development and progression of atherosclerosis, even though it is not possible to establish a causal relationship.Consequently, in order to better define the contribution ofC. pneumoniae on the inflammation underlying atherosclerosis, we performed a further analysis on studies comparing the levels of inflammatory markers in atherosclerotic patients seropositive toC. pneumoniae IgG or IgA with seronegative patients.The more relevant data is thatC. pneumoniae IgA seropositivity was overall more strongly related to the inflammatory state than IgG seropositivity. Indeed, our results showed an increase of inflammatory marker levels, such as hsCRP, fibrinogen, and IL-6, in IgA seropositive patients. Specifically, the standard mean differences of hsCRP, fibrinogen, and IL-6 were, respectively, 7.17, 7.79, and 1.37 times higher in the IgA compared to the IgG analysis, thus showing that seropositivity toC. pneumoniae IgA might better correlate to a chronic inflammatory state in patients with atherosclerosis. This is not particularly surprising sinceC. pneumoniae IgA is considered a marker of chronic infection, known to be involved in chronic disorders.The main strength of our meta-analysis is the statistical robustness of our data, since the results were not affected by exclusion of any specific study from the pooled analysis.However, our meta-analysis has potential limitations. First, since multiple infectious agents, labeled as infectious burden, rather than any single pathogen, have been shown to contribute to the pathogenesis of atherosclerosis, the inflammatory effect ofC. pneumoniae might be overestimated. Of note, in all the studies included in our meta-analysis, data regarding other infectious agents were missing or incomplete and, hence, we were not able to quantify their influence on chronic inflammation. Second, potential bias might be introduced in that not all the included studies reported data concerning the confounding factors. Lastly, two different diagnostic tests, along with different cutoffs, were used for detectingC. pneumoniae seropositivity in the included studies and, hence, may partly account for further bias.


## 5. Conclusions

In conclusion, despite some limitations, our study suggests thatC. pneumoniae infection may contribute to atherosclerotic cardiovascular diseases by enhancing the inflammatory state, as demonstrated by increased levels of systemic inflammatory markers. Furthermore, seropositivity toC. pneumoniae IgA, together with hsCRP, fibrinogen, and IL-6, may be predictive of atherosclerotic cardiovascular risk.In the future, large scale, prospective, and well-designed studies should be needed to deepen our knowledge concerning the causative role ofC. pneumoniae in inflammation in atherosclerotic cardiovascular diseases.



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*Source: 378658-2015-08-09.xml*