C-reactive protein distribution and correlation with traditional cardiovascular risk factors in the Italian population

European Journal of Internal Medicine 24 (2013) 161–166

Contents lists available at SciVerse ScienceDirect

European Journal of Internal Medicine journal homepage: www.elsevier.com/locate/ejim

Original article

C-reactive protein distribution and correlation with traditional cardiovascular risk factors in the Italian population Manuela Casula a, Elena Tragni a,⁎, Antonella Zambon b, Alessandro Filippi c, Ovidio Brignoli c, Claudio Cricelli c, Andrea Poli a, d, Alberico L. Catapano a, e and for the CHECK group 1 a

Epidemiology and Preventive Pharmacology Centre (SEFAP), Department of Pharmacological Sciences, University of Milan, Via Balzaretti 9, 20133 Milano, Italy Unit of Biostatistics and Epidemiology, Department of Statistics, University of Milan-Bicocca, Milan, Italy c Italian Society of General Medicine (SIMG), Via del Pignoncino 9-11, 50142 Firenze, Italy d Nutrition Foundation of Italy, Viale Tunisia 38, 20124 Milano, Italy e IRCCS MultiMedica, via Milanese 300, 20099 Sesto San Giovanni (MI), Italy b

a r t i c l e

i n f o

Article history: Received 16 May 2012 Received in revised form 4 September 2012 Accepted 13 September 2012 Available online 4 October 2012 Keywords: C-reactive protein Epidemiology Italian population Multivariate analysis Cardiovascular risk factors Adiposity

a b s t r a c t Background: C-reactive protein (CRP) increases during an inflammatory response; its plasma levels are believed to be an independent predictor of future atherosclerotic disease. We report the distribution of plasma levels of CRP and its possible relationship with other cardiovascular risk factors in an Italian cohort. Methods: CRP was assessed in frozen plasma samples of 1949 participants in the CHECK study (2001–2005), which collected clinical and biochemical data from randomly selected subjects (40–79 years) in the setting of Italian general practice. Results: Median CRP (interquartile range) was higher in women (1.42 [0.58–2.86] vs 1.28 [0.58–2.50]; p =.163), in people aged ≥65 years (1.74 [0.89–3.34] vs 1.11 [0.52–2.45]; p b .001), in patients with obesity (2.37 [1.27– 4.15] vs 1.16 [0.52–2.41]; p b .001), metabolic syndrome (2.12 [1.16–3.72] vs 1.10 [0.50–2.38]; p b .001), or higher cardiovascular risk (2.03 [1.01–3.42] vs 1.19 [0.53–2.50]; pb .001). Stepwise regression analysis showed significant associations (R2 =.264) of circulating logeCRP with body mass index, fibrinogen, apoB, age, gender, smoking habits, physical inactivity, creatinine levels, and systolic blood pressure. Conclusion: This study provides epidemiological data of CRP in the Italian population and reinforces the existing evidences about the close correlation between CRP and markers of inflammation and adiposity. © 2012 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

1. Introduction C-reactive protein (CRP), an acute-phase reactant produced mainly in the liver, belongs to the pentraxin family of proteins [1]. Its plasma concentration can increase rapidly in response to a wide range of inflammatory stimuli. In the past decades, as the role of inflammation in cardiovascular disease emerged [2], interest turned to C-reactive protein as a possible risk marker or risk factor for cardiovascular disease. CRP is increased in patients admitted for acute myocardial infarction [3]. Large epidemiological studies have established a role for CRP in the prediction of coronary heart disease (CHD) events [4–6]. In the absence of inflammation, CRP levels of b 1 μg/mL confer a lower risk for CHD, while levels above

⁎ Corresponding author. Tel.: +39 02 5031 8259; fax: +39 02 5031 8292. 1 As presented in Appendix A.

3 μg/mL increase the risk of CHD [7]. Interventions known to reduce CHD risk (i.e., smoking cessation, losing weight, exercise) also decrease serum CRP levels. Several medications, including aspirin, clopidogrel, and, in particular, statins, are also known to reduce serum CRP levels [8–10]. Although CRP has multiple pro-inflammatory and pro-atherogenic properties [11], recent studies have not supported a causal role for it in atherogenesis. A meta-analysis of 54 long-term prospective studies suggests continuous association of CRP with risk of coronary heart disease, ischemic heart disease, and vascular mortality independent of conventional risk factors [12]. More recent evidence, however, suggests that CRP is just “an innocent bystander” and that elevated levels of CRP are not causally associated with cardiovascular disease (CVD) [13]. Administration of large amounts of human CRP to animals, in fact, produces no adverse inflammatory effects [14]. Mendelian randomization studies, additionally, demonstrate that genetic polymorphisms associated with elevated CRP expression (and hence plasma levels) are not associated

0953-6205/$ – see front matter © 2012 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ejim.2012.09.010

162

M. Casula et al. / European Journal of Internal Medicine 24 (2013) 161–166

with higher rates of ischemic or cerebrovascular events [15–17]. Anand and Yusuf recently analyzed the collective evidence of causal association between CRP and CVD and suggested CRP as a marker of CVD rather than a causal factor [18]. In this study, we aimed to describe the distribution of CRP in a large Italian cohort of adult subjects and to explore their associations with several cardiovascular risk factors. 2. Methods 2.1. Study design and population CHECK is an ongoing observational study [19], started in 2001, jointly coordinated by the Epidemiology and Preventive Pharmacology Centre (SEFAP) of the University of Milan and the Italian Society of General Medicine (SIMG). In brief, 425 general practitioners, distributed across the country, extracted 16 subjects between 40 and 79 years of age from their patients' database. This extraction was based on a software-assisted random-number selection generated by the coordinating center, to ensure that the sample was representative of the Italian population in the selected age range. Enrolled subjects were clinically evaluated by their physician and underwent blood sampling for routine biochemical analyses. 2.2. Laboratory analysis Blood samples were obtained between 8 and 10 am, from the antecubital vein, in sitting position, after 12 h of fasting and alcohol abstinence. They were collected in EDTA or monoiodine-acetate (only for glucose assessment) coated tubes and shipped by courier at 4 °C temperature to the central laboratory (Fleming SpA, in Brescia, Italy) within 24 h, where the biochemical variables were determined. The biochemical evaluation was performed following the criteria of the World Health Organization Lipid Reference Laboratories. 1 mL aliquots of plasma (4–5 for each sample) were frozen at −80 °C for further biochemical evaluation. In this post-hoc analysis, aliquots for 2370 subjects randomly sampled were thawed for the determination of levels of C-reactive protein high sensitivity (hs-CRP), quantitatively measured by turbidimetric test, and creatinine. Creatinine clearance was calculated using the MDRD formula [20]. 2.3. Definitions Information about smoking habit, physical activity, alcohol use, and chronic drug treatments were collected directly from the patient during the examination. Smoking habit was defined as any use (current or former) of cigarettes. Self-reported leisure-time physical activity was classified as present or non-present. The use of alcohol was evaluated by adding the consumption of red and/or white wine, beer and liquors. Obesity was defined as body mass index (BMI) ≥30 kg/m 2. Metabolic syndrome (MetS) was defined when 3 of 5 of the listed characteristics were present: 1. abdominal obesity, with BMI as surrogate of waist circumference, men ≥28 kg/m 2, women ≥ 25 kg/m 2 (as demonstrated in a correlation analysis in 1000 subjects in the same cohort, p b .001); 2. triglycerides ≥ 150 mg/dL; 3. HDL cholesterol, men b40 mg/dL, women b50 mg/dL; 4. blood pressure (BP) ≥130/ 85 mm Hg; 5. fasting glucose ≥ 110 mg/dL. Hypercholesterolemia was defined as plasma levels of total cholesterol ≥200 mg/dL or LDL cholesterol ≥130 mg/dL or pharmacological treatment with statins and/or ezetimibe. Hypertriglyceridemia was defined as plasma levels of triglycerides ≥170 mg/dL or pharmacological treatment with fibrates or omega-3. Hypertension was defined as either recorded diagnosis by physician, or systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg, or currently taking medication to lower high BP [21]. Type 2 diabetes mellitus was defined as either recorded diagnosis

by physician or fasting blood glucose levels ≥126 mg/dL or currently taking antidiabetic drugs (oral hypoglycaemics medication and/or insulin). Subjects with a history of cardiovascular events (angina pectoris, myocardial infarction, coronary artery bypass graft or coronary angioplasty, stroke, transient ischemic attacks, claudicatio) were considered in secondary prevention. The global cardiovascular risk (CVD risk % in 10 years) was evaluated using the CUORE algorithm [22], developed from epidemiological data obtained in Italy. This function can be applied to men and women ages 35–69 years who have no history of previous coronary or cerebrovascular events, so we estimated CUORE risk score in the sub-sample of subjects aged up to 69 years. 2.4. Statistical analysis Continuous variables are presented as mean values [±standard deviation, SD], while qualitative variables are presented as frequencies. Hs-CRP levels show a non-normal distribution and are described as median (interquartile range, IQR) and comparisons across groups were performed by using non-parametric tests. Pearson correlation coefficient was estimated to test the associations of CRP (log-transformed dependent variable) with other traditional risk factors of CVD (continuous variables). Stepwise regression analysis between circulating logeCRP and several covariates (gender, age, educational level, smoke, physical activity, alcohol, systolic blood pressure, diastolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, glucose, apoB, fibrinogen, creatinine, BMI, secondary prevention, and familiar history of CVD) was performed. Variables are entered or removed one at a time. A variable is eligible for entry if it is an independent variable not currently in the model with rkk≥t (tolerance .0001). At each step, all eligible variables are considered for removal if the corresponding p-value was >.1 and for entry if p-value was b .05. If the inequality does not hold, no variable is removed or entered. The data were analyzed by using the software IBM SPSS (Statistical Package for Social Sciences) Version 19.0. 3. Results Complete risk factor data and CRP levels were available from 1949 individuals, randomly selected from the general CHECK sample. 989 (50.7%) of the study subjects were males. Mean age of the study group was 57.6 years (standard deviation 10.5). Median CRP (IQR) was 1.30 (0.57–2.65) mg/L, higher in women (1.42 [0.58–2.86] vs 1.28 [0.58–2.50]; p = .163; Table 1). CRP levels increased with age (from 0.92 [0.40–2.08] in people aged 40– 49 years to 1.92 [0.99–3.40] in people aged 70–79 years; p b .001). 20.6% (23.5% W vs 18.7% M) of the study population had elevated CRP values (≥ 3 mg/L). CRP levels were significantly higher in sedentary subjects, patients with obesity, metabolic syndrome, hypertriglyceridemia, hypertension, or diabetes. CRP levels were also significantly higher in individuals in secondary prevention or with CUORE risk score ≥20% (Table 1). Metabolic syndrome and all its individual components were associated with high CRP levels and there was a gradual increase in the levels of CRP with increasing numbers of MetS components, from a median (IQR) of 0.64 (0.34–1.46) mg/L for subjects with no MetS determinants to 2.76 (1.41–4.95) mg/L for subjects with all five determinants (p b .001). Median CRP levels also increased with each increasing calculated CUORE 10-year cardiovascular risk class, from 1.01 (0.45–2.20) mg/ L for CUORE b 5% to 2.04 (0.99–3.46) mg/L for CUORE ≥ 20% (p b .001). In univariate regression analysis (Table 2), age, systolic and diastolic blood pressure, triglycerides, apoB, fibrinogen, plasma glucose,

M. Casula et al. / European Journal of Internal Medicine 24 (2013) 161–166

4. Discussion

Table 1 CRP levels by presence of risk factors. Risk factors

Gender Age Smoke Physical inactivity Alcohol intake Obesity Hypertension Diabetes mellitus Hypercholesterolemia Hypertriglyceridemia Secondary prevention Metabolic syndrome CUORE risk score

N

M F b65 years ≥65 years No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes b20% ≥20%

Hs-CRP (mg/L)

989 960 1367 582 1525 422 441 1474 1047 868 1620 323 945 977 1679 236 765 1157 1510 392 1794 155 1495 434 1421 53

Median (IQR)

p

1.28 1.42 1.11 1.74 1.30 1.35 1.00 1.45 1.28 1.39 1.16 2.37 0.98 1.67 1.24 2.07 1.25 1.39 1.21 1.69 1.30 1.45 1.10 2.12 1.19 2.03

.163

(0.58–2.50) (0.58–2.86) (0.52–2.45) (0.89–3.34) (0.58–2.68) (0.59–2.60) (0.45–2.16) (0.63–2.86) (0.54–2.61) (0.63–2.72) (0.52–2.41) (1.27–4.15) (0.44–2.20) (0.82–3.18) (0.54–2.52) (0.98–3.54) (0.53–2.55) (0.61–2.74) (0.53–2.49) (0.91–3.46) (0.56–2.62) (0.87–3.10) (0.50–2.38) (1.16–3.72) (0.53–2.50) (1.01–3.42)

.000 .528 .000 .123 .000 .000 .000 .021 .000 .017 .000 .000

creatinine, and body mass index were all significantly positively correlated with logeCRP levels. The Pearson correlation coefficients varied in the range of .347 for body mass index (p b .001) to .066 for creatinine (p = .001). HDL cholesterol was significantly negatively correlate with logeCRP (linear regression coefficient -0.154, p b .001). To overcome the multicollinearity problem between LDL cholesterol and apoB, we used an apoB residual model, in which the apoB residuals obtained by regressing LDL cholesterol on apoB were included as independent variable. In multiple stepwise regression analysis (Table 2), BMI, fibrinogen, residuals of apoB, age, gender, smoke, physical inactivity, creatinine, and systolic blood pressure were selected as significant explanatory variables accounting for logeCRP. Table 2 Parameter estimates from univariate and stepwise linear multivariate regression model (R2 = .264). Variables

Body mass index Fibrinogen Apoba Age Gender Smoke Physical inactivity Creatinine Systolic blood pressure HDL-cholesterol Educational level Glucose LDL-cholesterol Secondary prevention Alcohol Familiar history of CVD Diastolic blood pressure Triglycerides a

163

Univariate analysis

Multivariate analysis

Beta

p

Beta

p

.347 .292 .244 .248 .019 .015 .132 .057 .214 -.150 -.186 .168 .067 .049 .035 .018 .122 .228

.000 .000 .000 .000 .216 .264 .000 .009 .000 .000 .000 .000 .003 .022 .075 .228 .000 .000

.261 .228 .207 .133 .096 .060 .049 .056 .048

.000 .000 .000 .000 .000 .006 .022 .025 .042

– –

apoB residuals were obtained by regressing LDL cholesterol on apoB.

In our cohort of Italian adults (40–79 years of age), the median CRP concentration was 1.30 mg/L. CRP levels increased with age, were higher in women than in men, in hypertensive or diabetic subjects, and were lower in physically active people. CRP levels also considerably increased with BMI. Our data are consistent with results from other observational studies [12,23,24], although we had, on average, lower median CRP levels. We observed significant linear positive correlation of CRP levels with body mass index, blood pressure, plasma glucose, apoB, and triglycerides and a decrease with HDL cholesterol. There was also a linear increase in CRP levels with increase in number of MetS determinants or with increasing cardiovascular risk score, estimated using the Italian CUORE algorithm. Several data showed a strong link between overweight/adiposity and CRP [25–27]. In our analysis, the most important correlate of CRP was adiposity (BMI was the first variable in the model): these results are consistent with the established relevance of adipose tissue as a source of proinflammatory cytokines and CRP [28,29]. Although we could not determine whether visceral adiposity directly elevates CRP levels, visceral fat has been described as an important determinant of a low-level chronic inflammatory state as reflected by a high level of CRP in a healthy adult population [30]. Consistently with other previous observations [23,31], we found a strong correlation between fibrinogen and CRP concentration. This is not surprising: fibrinogen is one of the acute-phase proteins, which implies that its concentration can increase in all inflammatory conditions. The regression analysis also showed the close correlation between CRP and apoB, net of LDL cholesterol. This can be explained by the fact that apoB is a marker of the presence of small dense LDL particles, more atherogenic than large, buoyant LDL particles [32,33]. As small dense LDL have been correlated with the traditional indices of adiposity [34], our hypothesis is supported by a stronger correlation between CRP and apoB (Beta= .224) in obese subjects (BMI ≥30 kg/m 2). Inflammation is thought to play a major role in the pathophysiological mechanisms of CVD and minor elevations in CRP levels are considered to be a strong, independent predictor of cardiovascular events [35]. In our study CRP levels were significantly elevated in individuals with multiple risk factors of CVD in comparison to individuals with no risk factors. This association underscores the relationship that well-established risk factors contribute to the inflammatory process. However, a causal relationship can not be established because of the cross-sectional nature of present study. A number of novel biomarkers, as for example renin, fibrinogen, or homocysteine, have been proposed to identify people at an increased risk for future cardiovascular events independently from the presence of established risk factors; plausible links to clinical CVD development have been reported for some of these biomarkers [36]. However, the strength of the dose response relationship of these novel risk factors with cardiovascular events and their role in risk stratification and risk prediction need to be established more accurately [36,37]. Some authors have hypothesized that CRP plasma levels may represent a specific target for intervention, especially in secondary prevention. This approach is based, as an example, on the results from predetermined analyses of the Pravastatin or Atorvastatin Evaluation and Infection Therapy (PROVE-IT) of the A-to-Z trials data [38] and the JUPITER trial data [39]. These data showed that patients who have reached both LDL cholesterol levels b 2.0 mmol/L (less than 80 mg/dL) and hs-CRP levels b 2.0 mg/L had the lowest CVD event rate. Advocating for the widespread use of hs-CRP for CV prediction is premature without randomized controlled trials that include subjects with both low and high hs-CRP levels and without a careful assessment of cost effectiveness. Until such trials are conducted, we advocate that the use of hs-CRP be limited to intermediate-risk

164

M. Casula et al. / European Journal of Internal Medicine 24 (2013) 161–166

individuals, to better stratify their total CV risk, as currently recommended by the AHA/CDC [40] and EAS/ESC guidelines [41]. Preliminary data applying this approach to our sample show that 45.6% of those at intermediate (CUORE score between 10 and 20%) cardiovascular risk (corresponding to 3.7% of the total sample) had hs-CRP > 2.0 mg/L, thus requiring a careful clinical assessment even if the CV algorithm does not indicate a higher risk. Moreover, although, as already explained, we can not rely on causal relationships between CRP and cardiovascular events, this variable may support the definition of therapy and the assessment of its effectiveness. This study has some limitations. Foremost, its cross-sectional nature confines our analysis to observational data; therefore, no conclusion can be drawn on a possible cause-effect relationship. Furthermore, our observation is limited to a sample aged between 40 and 79 years, so our data may not apply to younger or older population. The lack of disease-specific selection criteria could have led to the inclusion of subjects with acute or chronic inflammatory conditions (situations characterized by increased levels of CRP). However, this is unlikely, given the absence of CRP levels above 10 mg/L in our sample and the requirement for the patient to be at the GP office for the visit and the blood sampling planned in the study protocol. 5. Conclusion To our knowledge, this is the first study from the Italian population showing epidemiological data and association of CRP levels with other traditional risk factors of CVD in adult subjects. Our results reinforce the existing evidences about the close correlation between CRP and markers of inflammation and adiposity and suggest that in intermediate risk people CRP might be used to better stratify risk as it recapitulates several conditions (e.g. adiposity, body mass index, inflammation) that contribute to cardiovascular risk but are not usually accounted for in the risk calculation algorithms. Learning points • In our cohort of Italian adults, CRP levels increased with age, were higher in women than in men, in hypertensive or diabetic subjects, and were lower in physically active people. CRP levels also considerably increased with body mass index. The multivariate regression analysis showed significant linear positive correlation of CRP levels with body mass index, blood pressure, plasma glucose, apoB, and triglycerides and a decrease with HDL cholesterol. • This is the first study from the Italian population showing epidemiological data and association of CRP levels with other traditional risk factors of CVD in adult subjects. Our results reinforce the existing evidences about the close correlation between CRP and markers of inflammation and adiposity. • CRP assessment may help to stratify cardiovascular disease risk and to identify people at an increased risk for future cardiovascular events independently from the presence of established risk factors.

Conflict of interests No conflict of interest regarding the material discussed in the manuscript. Acknowledgments The CHECK study was supported in part by an unconditioned educational grant from AstraZeneca SpA. Thanks to Maria Grazia Lanfranco and Elena Loggia for their assistance in completing our survey.

Appendix A. The CHECK Study Group (bold type for coordinators) Aalders Maria Anna Abbate Giuseppe Agati Riccardo Alano Raffaele Alba Mauro Alemagna Silvia Alunni Massimo Alvaro Antonio Amato Fabio Ammendola Erminia Amodeo Vincenzo Amoretti Giovanni Andrani Alberto Antiga Ivo Appolonia Giorgio Aramini Enrico Arisi Marco Emilio Artebani Adriano Atzei Massimiliano Azzolini Micheline Bachetti Francesco Bagagli Franco Baldicchi Lorella Banzi Roberta Barba Ettore Maria Barbato Pasquale Claudio Caregnato Massimo Cariola Gianni Carlino Saverio Carminati Luisa Angela Carnelli Feliciano Carnesalli Franco Caruso Ciro Casale Ezio Casini Marcella Cassanelli Marco Castiello Maria Luisa Castriotta Antonio Catalano Domenico Cataldi Maria Elvira Ceccarini Agostino Celebrano Mario Celora Amedeo Cerracchio Alessandro Cesaro Andrea Cesaro Federico Chiriatti Alberto Cipriani Rosa Collura Giuseppe Colombo Valter Coluccia Salvatore Conte Sergio Corda Andrea Costa Roberto Cottani Antonio Crivellenti Giuseppe D'Ambrosio Gaetano D'Angelo Massimo Dalla Rosa Rosanna Damico Giansanto De Andreis Bessone Pier Luigi Grimaldi Emanuela Grosso Marco Guarnera Lucia Guerra Antonio Guillaro Bruno Gussoni Barbara Rita Ianiro Gabriella Ilardi Salvatore Imbalzano Pasquale Inguscio Cherubino Invernizzi Giovanni Iocca Tommaso Kos Egidia

Barral Gino Battaggia Alessandro Battigelli Doriano Baudi Marina Bellumori Giovanni Beltrami Giuseppe Benincasa Anna Maria Berardi Mario Berlengiero Claudio Bernardelli Stefano Bernardi Giuseppe Bertelle Evandro Bettini Gianluca Bevacqua Giuseppe Bevilacqua Stefano Bianconi Giuseppe Biggioggero Giovanni Bini Vincenzo Bocchino Giancarlo Boccone Nicolfranco Boito Giancarlo Bollo Alberto Maria Boncompagni Salvatore Bond Giuseppe Bonesi Maria Grazia Bono Gianfranco

Boscaro Federica Bossi Paolo Bozza Giulio Bracone Enrico Brandodoro Lucio Brasesco Pierclaudio Breviario Adele Brizzi Antonio Brugnetta Maurizio Bruno Giuseppe Buemi Giuseppe Bufano Carmine Bugli Tiziano Burigo Daniela Buzzatti Agostino Caccamo Orazio Antonio Cadamosti Danilo Cagliesi Francesco Caleffa Manuela Cammisa Nicolo' Campo Franceso Campobello Margherita Caputo Stanislao Caraccio Nicola Cardi Silvio Cardinale Fulvio

De Benedictis Antonio De Conto Umberto De Mola Cosimo De Rosa Antonio

Frascati Angelo Frignani Patrizia Fronteddu Pier Francesco Gadaleta Caldarola Gennaro Gallicchio Nicola Gallina Franco Gallo Silvano Gambino Fortunato Gambuzza Guglielmo

De Tommasi Roberto Del Nero Barbara Della Briotta Ivana Dell'Orco Mario Domenico Dell'Orco Mario Lucio Raffaele Di Candia Giuseppe Di Carlo Vittorio Di Febo Enrico Di Feo Antonio Di Fraia Giovanni Di Fulvio Aristide Di Nardo Dionisio Dolmetta Franco Donzelli Luigi Dughiero Fausto Durando Andrea Ercolino Luigi Fabbri Stelania Fabrizio Nicola Falchi Raffaello Fariello Ciro Fascendini Emilvio Fasulo Serenella Federici Laura Ferioli Paolo Ferrari Vincenzo Fidelbo Melchiorre Filetti Giuseppe Filippini Giovanni Fogher Michele Franchini Carlo Andrea

Garaffa Elio Garagiola Alberto Garofalo Remigio Garrone Alfonsino Gatta Luigi Gennari Massimo Gerace Antonio Geremia Maria Alessandra Germini Fabrizio Giacci Luciano Giannini Olivia Giordano Stefano Giovannelli Umberto Giuffré Giuseppe Giunti Giuliana Glaviano Bruno Gorletta Giovanni Grand Paola Grassini Giovanni Grasso Anna Maria Grasso Maria Filomena Grasso Giuseppe Greco Agostino Grifagni Marcello Grilli Piero Grimaldi Nicola

Mantovani Licia Marcenaro Alessandro Marchetti Anna Rosa Mariano Carlo Marino Antonino Mariuz Manuela Maroni Achille Martori Ampelio Masoch Gigliola Mattioli Mauro Mattioli Carlo Maurici Vincenzo Mauro Nicola

Moretti Marino Morgana Ignazio Morganti Mauro Mormile Annunziata Moro Roberto Mostacciolo Francesco Mourglia Danilo Murari Tiziana Muratore Alessandro Murgia Rosalba Naccari Massimo Napoli Luigi Nardacci Giuseppe

M. Casula et al. / European Journal of Internal Medicine 24 (2013) 161–166 Appendix A (continued)

Appendix A (continued) La Mattina Rosolino La Torre Angelo Lacava Cosimo Lalli Pasqualino Lamera Giorgio Lanza Gerardo Lardo Gerardo Laringe Matteo Lattanzio Giuseppe Le Foche Luca Leo Rosanna Leuzzi Giacomo Lipari Francesco Lipari Antonino Lippa Luciano Lo Conte Maurizio Lo Giudice Domenico Lonati Rossella Lorenzina Enrico Magi Lorenzo Magliozzo Francesco Mallamo Luciano Pasqualetto Salvatore Passamonti Marco Passaro Vincenzo Pederzani Fabio Pedrazzoli Giuliano Pelizzari Pier Carlo Pernici Pierrenato Pesaresi Carlo Pesce Gian Luigi Petrucci Mauro Petrucci Marco Petrulli Carmela Petti Stefano Piccinocchi Gaetano Picciotto Rinaldo Piccolo Francesco Pierobon Ivo Pilone Rita Piva Roberto Pizzillo Carlo Plebani Franco Polistina Stefano Pontari Antonino Poppi Maria Cristina Portanti Carla Prencipe Giovanni Prestifilippo Alessandro Procopio Antonio Profeta Gaetano Proietti Carlo Quattrocchi Pietro Raciti Teodoro Ragazzoni Anna Rattini Emanuela Reale Emanuela Tota Maria Fiorenza Tozzoli Alfonso Travaglini Rita Trois Paolo Trotta Gaetano Tuia Bruno Turbil Enrico Ughetti Claudio Urru Cesare Valente Fabio Valdevit Maria Valenti Marco Valle Lucia Valletta Domenico Valore Salvatore Varriale Antonio Varrica Gaetano Ventriglia Giuseppe Venturelli Antonio Vesco Giuseppe

165

Mazzardi Lidia Mazzarini Massimo Mazzi Wainer Mazzocchetti Alvaro Mazzoleni Francesco Mazzorana Michela Medagliani Giorgio Medea Gerardo Merlino Giovanni Merone Laura Metrucci Antonio Mezzano Silvio Micchi Alessio Micheli Pietro Severo Milazzo Vito Minafra Francesco Minetti Luca Mirandola Cipriano Monari Gianluigi Mongiello Claudio Montano Giovanni Montera Carmine Redaelli Dario Reggiani Claudio Ricotta Giuseppe Rigamonti Rodolfo Righini Velella Rinaldi Vanna Rista Pierangela Romano Salvatore Romei Federico Rossi Alberto Rossi Angelo Rossi Francesco Rossi Gianluca Rosso Lucia Rovazzani Massimo Rovelli Monica Rovescala Pietroclaudio Rubicini Giuseppe Rubini Stefano Russo Vincenzo Russo Carolina Sala Massimo Salurso Daniele Salvaderi Maria Dionice Salvato Alberto Salvetti Andrea Salvio Giuliano

Nebiacolombo Cristina Negri Fabrizio Nicolini Gianfranco Nigro Antonio Noia Emanuela Nuti Claudio Pietro Olivani Enrico Orlando Celestina Padovan Letizia Padula Maria Stella Pagan Maurizio Pannacci Valerio Pantalone Vincenzo Paolini Italo Papandrea Giampaolo Papini Giovanni Papulino Francesco Paradisi Enza Parisi Carmela Parretti Damiano Pasculli Domenico Pasinelli Pietro Carlo Schiavone Ciro Scola Vincenzo Scorpiniti Anna Scotto D'Antuono Antonio Scovotto Mari Antonietta Scuri Maurizio Giovanni Scuteri Antonio Sebastianelli Giuliano Sebben Maurizio Sforza Pasqualino Sfragara Ignazio Sicari Giuseppe Simonini Giorgio Soldani Miriam Soverina Patrizio Spagnolo Beatrice Sperandio Massimo Spezzano Alfredo Steri Lia Storni Paolo Strada Sonia Stramenga Carlo Tagliabue Paola Fausta Tarabini Legnoaura Tarallo Nicola Tei Alessandro Tei Gian Paolo

Samani Fabio Sammarco Renato Santoiemma Luigi Santoro Michele Sassarini Graziano Savino Andrea Scaglione Matteo Scarano Libero Zito Alfonso Zollino Luciana Zovi Maria Carla Zunino Roberto

Testi Sergio Testolin Ennio Tibo Angela Titone Nicolò Tomasello Antonino Tondi Lidia Torti Giorgio Tommaso Toscano Emanuele

Vezzosi Angelo Viola Dario Viscusi Bruno Vita Salvatore Vitali Franco Vittozzi Dante Sergio Vivona Giacomo Volpe Augusto Volpone Damiano Antonio Voza Italo Zadra Alessandro Zaninetti Piero Zanini Riccardo Zennaro Walter Zingaro Angelo

References [1] Du Clos TW. Function of C-reactive protein. Ann Med 2000;32:274-8. [2] Ridker PM. Testing the inflammatory hypothesis of atherothrombosis: scientific rationale for the cardiovascular inflammation reduction trial (CIRT). J Thromb Haemost 2009;7:332-9. [3] de Beer FC, Hind CR, Fox KM, Allan RM, Maseri A, Pepys MB. Measurement of serum C-reactive protein concentration in myocardial ischaemia and infarction. Br Heart J 1982;47:239-43. [4] Folsom AR, Aleksic N, Catellier D, Juneja HS, Wu KK. C-reactive protein and incident coronary heart disease in the atherosclerosis risk in communities (ARIC) study. Am Heart J 2002;144:233-8. [5] Koenig W, Sund M, Frohlich M, Fischer HG, Lowel H, Doring A, et al. C-reactive protein, a sensitive marker of inflammation, predicts future risk of coronary heart disease in initially healthy middle-aged men: results from the MONICA (Monitoring Trends and Determinants in Cardiovascular Disease) Augsburg Cohort Study, 1984 to 1992. Circulation 1999;99:237-42. [6] Ridker PM, Buring JE, Shih J, Matias M, Hennekens CH. Prospective study of C-reactive protein and the risk of future cardiovascular events among apparently healthy women. Circulation 1998;98:731-3. [7] Calabro P, Willerson JT, Yeh ET. Inflammatory cytokines stimulated C-reactive protein production by human coronary artery smooth muscle cells. Circulation 2003;108:1930-2. [8] Gao XR, Adhikari CM, Peng LY, Guo XG, Zhai YS, He XY, et al. Efficacy of different doses of aspirin in decreasing blood levels of inflammatory markers in patients with cardiovascular metabolic syndrome. J Pharm Pharmacol 2009;61:1505-10. [9] Jialal I, Stein D, Balis D, Grundy SM, Adams-Huet B, Devaraj S. Effect of hydroxymethyl glutaryl coenzyme a reductase inhibitor therapy on high sensitive C-reactive protein levels. Circulation 2001;103:1933-5. [10] Woodward M, Lowe GD, Francis LM, Rumley A, Cobbe SM. A randomized comparison of the effects of aspirin and clopidogrel on thrombotic risk factors and C-reactive protein following myocardial infarction: the CADET trial. J Thromb Haemost 2004;2:1934-40. [11] Casas JP, Shah T, Cooper J, Hawe E, McMahon AD, Gaffney D, et al. Insight into the nature of the CRP-coronary event association using Mendelian randomization. Int J Epidemiol 2006;35:922-31. [12] Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, Collins R, et al. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis. Lancet 2010;375:132-40. [13] Nordestgaard BG, Zacho J. Lipids, atherosclerosis and CVD risk: is CRP an innocent bystander? Nutr Metab Cardiovasc Dis 2009;19:521-4. [14] Casas JP, Shah T, Hingorani AD, Danesh J, Pepys MB. C-reactive protein and coronary heart disease: a critical review. J Intern Med 2008;264:295-314. [15] Zacho J, Tybjaerg-Hansen A, Jensen JS, Grande P, Sillesen H, Nordestgaard BG. Genetically elevated C-reactive protein and ischemic vascular disease. N Engl J Med 2008;359:1897-908. [16] Marott SC, Nordestgaard BG, Zacho J, Friberg J, Jensen GB, Tybjaerg-Hansen A, et al. Does elevated C-reactive protein increase atrial fibrillation risk? A Mendelian randomization of 47,000 individuals from the general population. J Am Coll Cardiol 2010;56:789-95. [17] Pai JK, Mukamal KJ, Rexrode KM, Rimm EB. C-reactive protein (CRP) gene polymorphisms, CRP levels, and risk of incident coronary heart disease in two nested case–control studies. PLoS One 2008;3:e1395. [18] Anand SS, Yusuf S. C-reactive protein is a bystander of cardiovascular disease. Eur Heart J 2010;31:2092-6. [19] Brignoli O, Casula M, Catapano AL, Cricelli C, Favato G, Filippi A, et al. Risk Factors Distribution and Cardiovascular Disease Prevalence in a Representative Sample of Italian Population: The Check Study. Paper available at http://ssrn.com. Date posted: December 01, 2008; Last revised: March 30, 2010. [20] Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction

166

[21]

[22]

[23]

[24]

[25] [26] [27]

[28] [29] [30]

[31]

[32]

M. Casula et al. / European Journal of Internal Medicine 24 (2013) 161–166 equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999;130:461-70. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo Jr JL, et al. The seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure: the JNC 7 report. JAMA 2003;289: 2560-72. Palmieri L, Panico S, Vanuzzo D, Ferrario M, Pilotto L, Sega R, et al. Evaluation of the global cardiovascular absolute risk: the Progetto CUORE individual score. Ann Ist Super Sanita 2004;40:393-9. Arcari A, Zito F, Di Castelnuovo A, De Curtis A, Dirckx C, Arnout J, et al. C reactive protein and its determinants in healthy men and women from European regions at different risk of coronary disease: the IMMIDIET Project. J Thromb Haemost 2008;6:436-43. Imhof A, Frohlich M, Loewel H, Helbecque N, Woodward M, Amouyel P, et al. Distributions of C-reactive protein measured by high-sensitivity assays in apparently healthy men and women from different populations in Europe. Clin Chem 2003;49:669-72. Brooks GC, Blaha MJ, Blumenthal RS. Relation of C-reactive protein to abdominal adiposity. Am J Cardiol 2010;106:56-61. McDade TW, Rutherford JN, Adair L, Kuzawa C. Adiposity and pathogen exposure predict C-reactive protein in Filipino women. J Nutr 2008;138:2442-7. Moran LJ, Noakes M, Clifton PM, Wittert GA, Belobrajdic DP, Norman RJ. C-reactive protein before and after weight loss in overweight women with and without polycystic ovary syndrome. J Clin Endocrinol Metab 2007;92:2944-51. Tzotzas T, Evangelou P, Kiortsis DN. Obesity, weight loss and conditional cardiovascular risk factors. Obes Rev 2011;12:e282-. Park HS, Park JY, Yu R. Relationship of obesity and visceral adiposity with serum concentrations of CRP, TNF-alpha and IL-6. Diabetes Res Clin Pract 2005;69:29-35. Kim K, Valentine RJ, Shin Y, Gong K. Associations of visceral adiposity and exercise participation with C-reactive protein, insulin resistance, and endothelial dysfunction in Korean healthy adults. Metabolism 2008;57:1181-9. Arena R, Arrowood JA, Fei DY, Helm S, Kraft KA. The relationship between C-reactive protein and other cardiovascular risk factors in men and women. J Cardiopulm Rehabil 2006;26:323-7. Carmena R, Duriez P, Fruchart JC. Atherogenic lipoprotein particles in atherosclerosis. Circulation 2004;109:III2-7.

[33] Vekic J, Zeljkovic A, Jelic-Ivanovic Z, Spasojevic-Kalimanovska V, Bogavac-Stanojevic N, Memon L, et al. Small, dense LDL cholesterol and apolipoprotein B: relationship with serum lipids and LDL size. Atherosclerosis 2009;207:496-501. [34] Sattar N, Tan CE, Han TS, Forster L, Lean ME, Shepherd J, et al. Associations of indices of adiposity with atherogenic lipoprotein subfractions. Int J Obes Relat Metab Disord 1998;22:432-9. [35] Ridker PM, Morrow DA. C-reactive protein, inflammation, and coronary risk. Cardiol Clin 2003;21:315-25. [36] Wang TJ, Gona P, Larson MG, Tofler GH, Levy D, Newton-Cheh C, et al. Multiple biomarkers for the prediction of first major cardiovascular events and death. N Engl J Med 2006;355:2631-9. [37] Zethelius B, Berglund L, Sundstrom J, Ingelsson E, Basu S, Larsson A, et al. Use of multiple biomarkers to improve the prediction of death from cardiovascular causes. N Engl J Med 2008;358:2107-16. [38] Murphy SA, Cannon CP, Wiviott SD, de Lemos JA, Blazing MA, McCabe CH, et al. Effect of intensive lipid-lowering therapy on mortality after acute coronary syndrome (a patient-level analysis of the Aggrastat to Zocor and Pravastatin or Atorvastatin evaluation and infection therapy-thrombolysis in myocardial infarction 22 trials). Am J Cardiol 2007;100:1047-51. [39] Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto Jr AM, Kastelein JJ, et al. Reduction in C-reactive protein and LDL cholesterol and cardiovascular event rates after initiation of rosuvastatin: a prospective study of the JUPITER trial. Lancet 2009;373:1175-82. [40] Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon III RO, Criqui M, et al. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003;107:499-511. [41] Catapano AL, Reiner Z, De Backer G, Graham I, Taskinen MR, Wiklund O, et al. ESC/EAS guidelines for the management of dyslipidaemias. The task force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS). Atherosclerosis 2011;217:1–44.