Abstract

Association between elevated C-reactive protein (CRP) serum levels and subclinical atherosclerosis and cardiovascular (CV) events was described in rheumatoid arthritis (RA). CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 exert an influence on elevated CRP serum levels in non-rheumatic Caucasians. Consequently, we evaluated the potential role of these genes in the development of CV events and subclinical atherosclerosis in RA patients. Three tag CRP polymorphisms and HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 were genotyped in 2,313 Spanish patients by TaqMan. Subclinical atherosclerosis was determined in 1,298 of them by carotid ultrasonography (by assessment of carotid intima-media thickness-cIMT-and presence/absence of carotid plaques). CRP serum levels at diagnosis and at the time of carotid ultrasonography were measured in 1,662 and 1,193 patients, respectively, by immunoturbidimetry. Interestingly, a relationship between CRP and CRP serum levels at diagnosis and at the time of the carotid ultrasonography was disclosed. However, no statistically significant differences were found when CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 were evaluated according to the presence/absence of CV events, carotid plaques and cIMT after adjustment. Our results do not confirm an association between these genes and CV disease in RA.

Introduction

Rheumatoid arthritis (RA) is a chronic disease related to an increased risk of cardiovascular (CV) mortality and high prevalence of subclinical atherosclerosis1. Besides traditional CV risk factors2 and inflammation3, a genetic component appears to be crucial in these processes2,4,5,6.

C-reactive protein (CRP) is currently the most widely used biomarker of inflammation7. The production of this protein occurs almost exclusively in the liver8. Several studies have suggested that elevated serum concentrations of CRP are related to the development of several processes associated with atherosclerosis such as coronary heart disease9 and stroke10. Accordingly, a relationship between chronic inflammation determined by CRP serum levels and the development of both subclinical atherosclerosis11 and CV events2 has been found in RA patients.

Genetic variation is a major determinant of CRP levels. In this sense, a meta-analysis has identified several loci associated with elevated CRP serum levels in non-rheumatic Caucasian individuals12. CRP gene was found to be the most significant signal related to increased CRP serum levels12. Other polymorphisms also exert an influence on the elevated level of serum CRP in non-rheumatic Caucasians12. It is the case for common genetic variants that play a role in the immune system (NLRP3 [NACHT, LRR and PYD domains-containing protein 3] rs12239046 or IL1F10 [interleukin-1 family, member 10] rs6734238) or in the susceptibility to develop metabolic syndrome (HNF1A [hepatic nuclear factor 1-α] rs1183910, LEPR [leptin receptor] rs4420065, GCKR [glucokinase regulator] rs1260326 and HNF4A [hepatocyte nuclear factor 4-α] rs1800961)12. A relationship between genetic variants that reside in regions without an apparent role in chronic inflammation (PPP1R3B [protein phosphatase 1, regulatory-inhibitor- subunit 3B] rs9987289, SALL1 [sal-like 1] rs10521222 and ASCL1 [achaete-scute complex homolog 1] rs10745954) and increased CRP serum levels was also disclosed in non-rheumatic Caucasian individuals12.

Taking together all this information, the aim of the present study was to evaluate the potential influence of CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1, polymorphisms related to elevated CRP serum levels in non-rheumatic Caucasians, on the development of CV events and subclinical atherosclerosis in RA patients. For this purpose, we took advantage of data from a large series of RA patients assessed for CV disease.

Patients and Methodology

Subjects and Study Protocol

2,313 unrelated patients from Spain were enrolled in our work. Peripheral blood was obtained from subjects recruited from Hospital Universitario Lucus Augusti (Lugo), Marqués de Valdecilla (Santander), Bellvitge (Barcelona), San Cecilio (Granada), Canarias (Tenerife), Doctor Peset (Valencia), General de Ciudad Real (Ciudad Real) and Clínico San Carlos, La Paz, La Princesa, Gregorio Marañón and 12 de Octubre (Madrid).

For experiments involving humans and the use of human blood samples, all the methods were carried out in accordance with the approved guidelines and regulations, according to the Declaration of Helsinki. All experimental protocols were approved by the Ethics Committees of clinical research of Galicia for Hospital Lucus Augusti in Lugo, of Cantabria for Hospital Marqués de Valdecilla in Santander, of Cataluña for Hospital de Bellvitge in Barcelona, of Andalucía for Hospital San Cecilio in Granada, of Canarias for Hospital de Canarias in Tenerife, of Comunidad Valenciana for Hospital Doctor Peset in Valencia, of Castilla-La Mancha for Hospital General de Ciudad Real in Ciudad Real and of Madrid for Hospital Clínico San Carlos, La Paz, La Princesa, Gregorio Marañón and 12 de Octubre in Madrid. Informed consent was obtained from all subjects.

Patients fulfilled the 2010 classification criteria for RA13. RA patients were evaluated for CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 polymorphisms. In addition, subclinical atherosclerosis was determined in 1,298 of the RA patients recruited in the study using a carotid ultrasound (US) technique (by evaluation of carotid intima-media thickness -cIMT- and presence/absence of carotid plaques). Also, CRP serum levels at the time of RA diagnosis and at the time of carotid US study were measured in a subgroup of 1,662 and 1,193 patients, respectively, by immunoturbidimetry.

Data on epidemiological and demographical features of the patients recruited in the present work are displayed in Table 1. Traditional CV risk factors and CV events were defined previously2,14.

Table 1: Data on epidemiological and demographical features of the 2,313 patients with rheumatoid arthritis from Spain recruited in this work.

Selection of polymorphisms and genotyping

Since CRP has been identified as the most relevant signal related to elevated CRP serum levels in non-rheumatic Caucasians12, we performed a tagging of this gene with the aim of covering all its variability. Consequently, we genotyped 3 polymorphisms: CRP rs1417938, CRP rs1800947 and CRP rs1205.

Additionally, we tested 9 genetic variants (HNF1A rs1183910, LEPR rs4420065, GCKR rs1260326, NLRP3 rs12239046, IL1F10 rs6734238, PPP1R3B rs9987289, ASCL1 rs10745954, HNF4A rs1800961 and SALL1 rs10521222) previously described as relevant polymorphisms related to increased CRP serum levels in non-rheumatic Caucasians12.

Genotyping was performed by TaqMan predesigned assays in a 7900 HT Real-Time polymerase chain reaction system (Applied Biosystems, Foster City, CA, USA).

US evaluation

Measurement of the cIMT values and presence/absence of carotid plaques were evaluated in 1,298 cases. Patients from Santander, Granada, Tenerife, Valencia, Ciudad Real and Madrid were evaluated by a commercially scanner, Mylab 70, Esaote (Genoa-Italy) as previously described15. Patients from Lugo were measured by high-resolution B-mode ultrasound, Hewlett Packard SONOS 5500 as previously reported16. cIMT was measured at the far wall of the right and left common carotid arteries over the proximal 15 mm-long segment. cIMT was determined as the average of three measurements in each common carotid artery. Plaque criteria in the accessible extracranial carotid tree (common carotid artery, bulb and internal carotid artery) were focal protrusion in the lumen at least cIMT >1.5 mm, protrusion at least 50% greater than the surrounding cIMT, or arterial lumen encroaching >0.5 mm17. The carotid plaques were counted in each territory and defined as no plaque, unilateral plaque or bilateral plaques17. Agreement between these two US methods was previously reported18. Experts with a high reproducibility and an excellent inter-observer reliability in the evaluation of subclinical atherosclerosis in patients with RA performed the studies.

Evaluation of CRP serum levels

CRP serum levels at the time of RA diagnosis and at the time of the carotid US study were measured in a subgroup of 1,662 and 1,193 patients, respectively, by an automated immunoturbidimetric assay using the ADVIA Chemistry system (Siemens Healthcare Diagnostics Inc.). Serum samples of RA patients containing CRP form an immune complex with the assay reagent and antibodies against CRP that precipitates, increasing the turbidity of the sample. When light is passed through the reaction solution, some light is absorbed by the precipitates, which is measured at 596/694 nm. The level of CRP is determined by comparison with a calibrator of known concentration.

Statistical analysis

Genotyping data were checked for deviation from Hardy-Weinberg equilibrium (HWE) using http://ihg.gsf.de/cgi-bin/hw/hwa1.pl. Power for the study was calculated using “CaTS-Power Calculator for Two Stage Association Studies” (http://www.sph.umich.edu/csg/abecasis/CaTS/). Haplotypes were constructed using Haploview v4.2 software.

The relationship between allele/haplotype frequencies and the presence/absence of CV events was tested using Cox regression adjusting for gender, follow-up time, age at RA diagnosis and traditional CV risk factors as confounder factors. Results were expressed as hazard ratios (HR) with 95% confidence interval (CI).

Differences in the allele/haplotype frequencies according to the presence/absence of carotid plaques were calculated by χ2 or Fisher tests when necessary (expected values below 5). Strength of associations was estimated using odds ratios (OR) and 95% CI. Results were adjusted for gender, follow-up time, age at the time of US evaluation and traditional CV risk factors as confounder factors by logistic regression.

Association between allele/haplotype frequencies and data on cIMT was evaluated by unpaired t test. Results were adjusted for gender, follow-up time, age at the time of US evaluation and traditional CV risk factors as confounder factors by analysis of covariance (ANCOVA).

Results on CRP serum levels were expressed as mean ± standard deviation (SD). The relationship between allele/haplotype frequencies and CRP serum levels at RA diagnosis and at the time of the carotid US study was evaluated by unpaired t test.

The statistical software used to perform all the statistical analyses was STATA 12/SE (Stata Corp., College Station, TX, USA).

Results

CRP rs1417938, CRP rs1800947, CRP rs1205, HNF1A rs1183910, LEPR rs4420065, GCKR rs1260326, NLRP3 rs12239046, IL1F10 rs6734238, PPP1R3B rs9987289, ASCL1 rs10745954, HNF4A rs1800961 and SALL1 rs10521222 genotype distribution were in HWE (p > 0.05). The genotyping success was greater than 99% in all the cases.

The study had >90% of power to detect genotypic OR = 1.3 for CRP rs1417938, CRP rs1205 and HNF1A rs1183910, LEPR rs4420065, GCKR rs1260326, NLRP3 rs12239046, IL1F10 rs6734238, ASCL1 rs10745954, and ≥90% to detect OR ≥ 1.4 for CRP rs1800947 and PPP1R3B rs9987289 and HNF4A rs1800961 and SALL1 rs10521222.

Influence of CRP polymorphisms on CV events or subclinical atherosclerosis in patients with RA

We assessed the potential influence of CRP polymorphisms (rs1417938, rs1800947 and rs1205) on the risk of CV events or subclinical atherosclerosis in RA patients.

The linkage disequilibrium (LD) pattern of these 3 CRP polymorphisms obtained by HapMap Project phase I, II and III and Haploview (v.4.2) software and measured by r2 coefficient is displayed in Supplementary Fig. online.

After adjustment for potential confounder factors, no statistically significant differences were found when each CRP polymorphism was assessed independently and according to the presence/absence of CV events, carotid plaques and cIMT values (Table 2). Similarly, after adjustment for potential confounder factors, no statistically significant differences were detected when CRP polymorphisms were tested together conforming haplotypes and according to the presence/absence of CV events, carotid plaques and cIMT values (Table 3).

Table 2: Association between CRP polymorphisms according to the presence/absence of CV events or subclinical atherosclerosis in RA patients.
Table 3: Results of CRP haplotype analysis according to the presence/absence of CV events or subclinical atherosclerosis in RA patients.

Influence of HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 polymorphisms on CV events or subclinical atherosclerosis in patients with RA

In addition, we evaluated the potential relationship between HNF1A rs1183910, LEPR rs4420065, GCKR rs1260326, NLRP3 rs12239046, IL1F10 rs6734238, PPP1R3B rs9987289, ASCL1 rs10745954, HNF4A rs1800961 and SALL1 rs10521222 polymorphisms and CV events or subclinical atherosclerosis in RA patients (Table 4). Accordingly, no significant differences were obtained when RA patients were stratified according to the presence/absence of CV events after adjustment for potential confounder factors (Table 4). It was also the case when RA patients were stratified according to the presence/absence of carotid plaques and the evaluation of cIMT after adjustment for potential confounder factors (Table 4).

Table 4: Association between HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A, SALL1 according to the presence/absence of CV events or subclinical atherosclerosis in RA patients.

Influence of CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 polymorphisms on CRP serum levels in patients with RA

Furthermore, we determined the potential influence of CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 on CRP serum levels at RA diagnosis and also at the time of the carotid US study. In this regard, the mean ± SD of CRP serum levels at RA diagnosis in patients carrying the minor CRP rs1417938A allele was 12.66 ± 25.32 mg/l versus 9.80 ± 19.39 mg/l in those carrying the major CRP rs1417938T allele (p = 0.0002) (Supplementary Table S1). Additionally, the mean ± SD of CRP serum levels at the time of the carotid US study in patients carrying the minor CRP rs1417938A allele was 7.15 ± 19.16 mg/l versus 5.64 ± 14.56 mg/l in those carrying the major CRP rs1417938T allele (p = 0.029) (Supplementary Table S1). Moreover, the mean ± SD of CRP serum levels at the time of the carotid US study in patients carrying the minor CRP rs1205T allele was 5.02 ± 12.81 mg/l versus 6.71 ± 17.70 mg/l in those carrying the major CRP rs1205C allele (p = 0.018) (Supplementary Table S1). Consistent with these results, the mean ± SD of CRP serum levels at RA diagnosis in patients carrying the ACC haplotype (which harbors the minor CRP rs1417938A allele) was 14.08 ± 28.28 mg/l versus 10.23 ± 19.90 mg/l in those patients carrying the TCC haplotype, the most common haplotype found in our series (p = 0.0002) (Supplementary Table S2). Also, the mean ± SD of CRP serum levels at the time of the carotid US study in patients carrying the TCT haplotype (which harbors the minor CRP rs1205T allele) was 4.34 ± 7.75 mg/l versus 6.14 ± 16.46 mg/l in those patients carrying the TCC haplotype (p = 0.023) (Supplementary Table S2). However, no association between HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 and both CRP serum levels at RA diagnosis and at the time of the carotid US study was disclosed (Supplementary Table S3).

Discussion

Several studies have suggested that CRP has direct effects on the vessel wall promoting atherosclerosis19. Among them, CRP seems to stimulate the production of cellular adhesion molecules by vascular endothelial cells, facilitate the adhesion and migration of monocytes through the vessel wall, mediate the uptake of low-density lipoprotein cholesterol by macrophages and cause complement activation19.

An association between high-grade, chronic CRP elevation and subclinical atherosclerosis in patients with RA has been reported11. Additionally, a higher risk of CV events in patients with RA with chronic inflammation expressed by persistently increased CRP serum levels has been found2.

Since CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 have been described as significant signals associated with elevated CRP serum levels in non-rheumatic Caucasians12, we set up a large-scale study to determine the potential influence of these 10 genetic variants on the development of atherosclerotic disease in patients with RA. Interestingly, our results disclosed a relationship between CRP gene and CRP serum levels at RA diagnosis and at the time of the carotid US study. However, we could not find an association between the elevated CRP serum level-related variants in non-rheumatic Caucasians and the presence of subclinical atherosclerosis or CV events in RA patients.The lack of evidence for the association between these polymorphisms and atherosclerosis in RA patients does not exclude the implication of CRP in the pathogenesis of this disease. This protein is produced as a part of an intricate acute phase response where several inflammatory factors, closely interrelated, are involved. Although we could not find an association of IL6 gene polymorphisms with CV disease20, it is possible that complex interactions between elevated CRP serum level-related genes in non-rheumatic Caucasians and other genes implicated in the inflammation cascade may lead to up-regulation of CRP, promoting the progression of accelerated atherosclerosis in RA patients.

In summary, the results obtained in the present study do not confirm association between CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A and SALL1 and CV disease in patients with RA.

Additional Information

How to cite this article: López-Mejías, R. et al. Influence of elevated-CRP level-related polymorphisms in non-rheumatic Caucasians on the risk of subclinical atherosclerosis and cardiovascular disease in rheumatoid arthritis. Sci. Rep. 6, 31979; doi: 10.1038/srep31979 (2016).

References

  1. 1.

    , , , & Endothelial dysfunction, carotid intima-media thickness, and accelerated atherosclerosis in rheumatoid arthritis. Semin Arthritis Rheum. 38, 67–70 (2008).

  2. 2.

    et al. HLA-DRB1 and persistent chronic inflammation contribute to cardiovascular events and cardiovascular mortality in patients with rheumatoid arthritis. Arthritis Rheum. 57, 125–132 (2007).

  3. 3.

    , , , & Influence of nonclassical cardiovascular risk factors on the accuracy of predicting subclinical atherosclerosis in rheumatoid arthritis. J Rheumatol. 34, 943–951 (2007).

  4. 4.

    et al. Vitamin D receptor GATG haplotype association with atherosclerotic disease in patients with rheumatoid arthritis. Atherosclerosis. 245, 139–142 (2016).

  5. 5.

    et al. Protective Role of the Interleukin 33 rs3939286 Gene Polymorphism in the Development of Subclinical Atherosclerosis in Rheumatoid Arthritis Patients. PLoS One. 10, e0143153 (2015).

  6. 6.

    et al. NFKB1-94ATTG ins/del polymorphism (rs28362491) is associated with cardiovascular disease in patients with rheumatoid arthritis. Atherosclerosis. 224, 426–429 (2012).

  7. 7.

    et al. Genetic Loci associated with C-reactive protein levels and risk of coronary heart disease. JAMA. 302, 37–48 (2009).

  8. 8.

    & Cytokines in atherosclerosis: pathogenic and regulatory pathways. Physiol Rev. 86, 515–581 (2006).

  9. 9.

    et al. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med. 350, 1387–1397 (2004).

  10. 10.

    , , , & Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men. N Engl J Med. 336, 973–979 (1997).

  11. 11.

    et al. High-grade C-reactive protein elevation correlates with accelerated atherogenesis in patients with rheumatoid arthritis. J Rheumatol. 32, 1219–1223 (2005).

  12. 12.

    et al. Meta-analysis of genome-wide association studies in >80 000 subjects identifies multiple loci for C-reactive protein levels. Circulation. 123, 731–738 (2011).

  13. 13.

    et al. Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum. 62, 2569–2581 (2010).

  14. 14.

    , , & Carotid intima-media thickness predicts the development of cardiovascular events in patients with rheumatoid arthritis. Semin Arthritis Rheum. 38, 366–371 (2009).

  15. 15.

    et al. Carotid ultrasound is useful for the cardiovascular risk stratification of patients with rheumatoid arthritis: results of a population-based study. Ann Rheum Dis. 73, 722–727 (2014).

  16. 16.

    , , , & Effect of anti-tumor necrosis factor alpha therapy on the progression of subclinical atherosclerosis in severe rheumatoid arthritis. Arthritis Rheum. 55, 150–153 (2006).

  17. 17.

    et al. Mannheim carotid intima-media thickness consensus (2004–2006). An update on behalf of the Advisory Board of the 3rd and 4th Watching the Risk Symposium, 13th and 15th European Stroke Conferences, Mannheim, Germany, 2004, and Brussels, Belgium, 2006. Cerebrovasc Dis. 23, 75–80 (2007).

  18. 18.

    et al. Multi-examiner reliability of automated radio frequency-based ultrasound measurements of common carotid intima-media thickness in rheumatoid arthritis. Rheumatology (Oxford). 50, 1860–1864 (2011).

  19. 19.

    et al. Baseline levels of C-reactive protein and prediction of death from cardiovascular disease in patients with inflammatory polyarthritis: a ten-year followup study of a primary care-based inception cohort. Arthritis Rheum. 52, 2293–2299 (2005).

  20. 20.

    et al. Lack of association between IL6 single nucleotide polymorphisms and cardiovascular disease in Spanish patients with rheumatoid arthritis. Atherosclerosis. 219, 655–658 (2011).

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Acknowledgements

We want to thank Patricia Fuentevilla Rodríguez, Virginia Portilla González and Jesús González-Vela. The present work was financed by European Union FEDER funds and “Fondo de Investigación Sanitaria” (grants PI12/00060 and PI15/00525) and RETICS Programs RD12/0009 from “Instituto Carlos III de Salud” (Health Ministry, Spain) and in part by grants from the European IMI BTCure Program. RL-M and BU are financed by RETICS (RD12/0009/0013). FG is supported by a Sara Borrell postdoctoral fellowship (CD15/00095).

Author information

Author notes

    • Raquel López-Mejías
    • , Fernanda Genre
    •  & Sara Remuzgo-Martínez

    These authors contributed equally to this work.

    • Javier Martín
    •  & Miguel A. González-Gay

    These authors jointly supervised this work.

Affiliations

  1. Epidemiology, Genetics and Atherosclerosis Research Group on Systemic Inflammatory Diseases, Division of Rheumatology, IDIVAL, Santander, Spain

    • Raquel López-Mejías
    • , Fernanda Genre
    • , Sara Remuzgo-Martínez
    • , Alfonso Corrales
    • , Trinitario Pina
    • , Ricardo Blanco
    • , Verónica Mijares
    • , Begoña Ubilla
    •  & Miguel A. González-Gay
  2. Cardiology Department, Hospital Lucus Augusti, Lugo, Spain

    • Carlos González-Juanatey
  3. Division of Rheumatology, Hospital Universitario Doctor Peset, Valencia, Spain

    • Montserrat Robustillo-Villarino
    •  & Juan J. Alegre-Sancho
  4. Department of Epidemiology and Computational Biology, School of Medicine, University of Cantabria, and CIBER Epidemiología y Salud Pública (CIBERESP), IDIVAL, Santander, Spain

    • Javier Llorca
  5. Division of Rheumatology, Hospital Universitario la Princesa, IIS-IPrincesa, Madrid, Spain

    • Esther Vicente
    • , Isidoro González-Álvaro
    •  & Santos Castañeda
  6. Rheumatology Department, Hospital Universitario Lucus Augusti, Lugo, Spain

    • José A. Miranda-Filloy
  7. Division of Rheumatology, Hospital Clínico San Cecilio, Granada, Spain

    • César Magro
    •  & Enrique Raya
  8. Rheumatology Division, Hospital Universitario de Canarias, Santa Cruz de Tenerife, Spain

    • Beatriz Tejera-Segura
    •  & Iván Ferraz-Amaro
  9. Rheumatology Department, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain

    • Marco A. Ramírez Huaranga
    •  & María D. Mínguez Sánchez
  10. Department of Rheumatology, Hospital Universitario Bellvitge, Barcelona, Spain

    • Carmen Gómez-Vaquero
  11. Department of Rheumatology, Hospital Universitario La Paz, Madrid, Spain

    • Alejandro Balsa
    •  & Dora Pascual-Salcedo
  12. Department of Rheumatology, Hospital General Universitario Gregorio Marañón, Madrid, Spain

    • Francisco J. López-Longo
  13. Department of Rheumatology, Hospital Universitario 12 de Octubre, Madrid, Spain

    • Patricia Carreira
  14. Department of Rheumatology, Hospital Clínico San Carlos, Madrid, Spain

    • Luis Rodríguez-Rodríguez
    •  & Benjamín Fernández-Gutiérrez
  15. Institute of Parasitology and Biomedicine López-Neyra, IPBLN-CSIC, Granada, Spain

    • Javier Martín
  16. School of Medicine, University of Cantabria, Santander, Spain

    • Miguel A. González-Gay
  17. Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

    • Miguel A. González-Gay

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Contributions

R.L.-M., F.G. and S.R.-M. genotyped, contributed to the conception of the work, performed the statistical analysis and helped to write the article. J.A.M.-F., B.T.-S., T.P., R.B., J.J.A.-S., E.R., V.M., B.U., M.D.M.S., C.G.-V., A.B., D.P.-S., F.J.L.-L., P.C., I.G.-A., B.F.-G. and S.C. were implicated in the acquisition of clinical characteristics and samples, participated in the statistical analysis and helped to write the article. C.G.-J., M.R.-V., A.C., E.V., C.M., M.A.R.H., L.R.R. and I.F.-A. carried out the assessment of carotid ultrasonography, were implicated in the acquisition of clinical characteristics and samples, participated in the statistical analysis and contributed to the writing of the article. J.L. performed the statistical analysis of the results and helped to write the article. J.M. and M.A.G.-G. contributed to the design of the work, acquisition of clinical data and samples and contributed to the writing of the article.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Miguel A. González-Gay.

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https://doi.org/10.1038/srep31979

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