SciELO - Scientific Electronic Library Online

vol.105 issue5Efficacy of Patient Selection for Diagnostic Coronary Angiography in Suspected Coronary Artery DiseaseHigh-fat Diet Promotes Cardiac Remodeling in an Experimental Model of Obesity author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand



  • text in Portuguese
  • text new page (beta)
  • English (pdf) | Portuguese (pdf)
  • Article in xml format
  • How to cite this article
  • SciELO Analytics
  • Curriculum ScienTI
  • Automatic translation


Related links


Arquivos Brasileiros de Cardiologia

Print version ISSN 0066-782XOn-line version ISSN 1678-4170

Arq. Bras. Cardiol. vol.105 no.5 São Paulo Nov. 2015  Epub Aug 25, 2015 

Original Articles

Assessment of Galectin-3 Polymorphism in Subjects with Chronic Chagas Disease

Gabriela da Silva Cruz1 

Ana Luiza Dias Angelo1 

Ticiana Ferreira Larocca1  2  3 

Carolina Thé Macedo1  2  3 

Márcia Noya-Rabelo2 

Luís Claudio Lemos Correia2 

Jorge Andion Torreão2 

Bruno Solano de Freitas Souza1  3 

Ricardo Ribeiro dos Santos1  3 

Milena Botelho Pereira Soares1  3 

1Centro de Biotecnologia e Terapia Celular – Hospital São Rafael, Salvador, BA - Brazil

2Departamento de Cardiologia - Hospital São Rafael, Salvador, BA - Brazil

3Centro de Pesquisas Gonçalo Moniz - FIOCRUZ, Salvador, BA - Brazil



Galectin-3, a β-galactoside binding lectin, has been described as a mediator of cardiac fibrosis in experimental studies and as a risk factor associated with cardiovascular events in subjects with heart failure. Previous studies have evaluated the genetic susceptibility to Chagas disease in humans, including the polymorphisms of cytokine genes, demonstrating correlations between the genetic polymorphism and cardiomyopathy development in the chronic phase. However, the relationship between the galectin-3 single nucleotide polymorphism (SNP) and phenotypic variations in Chagas disease has not been evaluated.


The present study aimed to determine whether genetic polymorphisms of galectin-3 may predispose to the development of cardiac forms of Chagas disease.


Fifty-five subjects with Chagas disease were enrolled in this observational study. Real-time polymerase chain reaction (PCR) was used for genotyping the variants rs4644 and rs4652 of the galectin-3 gene.


For the SNP rs4644, the relative risk for the cardiac form was not associated with the genotypes AA (OR = 0.79, p = 0.759), AC (OR = 4.38, p = 0.058), or CC (OR = 0.39, p = 0.127). Similarly, for the SNP rs4652, no association was found between the genotypes AA (OR = 0.64, p = 0.571), AC (OR = 2.85, p = 0.105), or CC (OR = 0.49, p = 0.227) and the cardiac form of the disease.


Our results showed no association between the different genotypes for both SNPs of the galectin-3 gene and the cardiac form of Chagas disease. (Arq Bras Cardiol. 2015; [online].ahead print, PP.0-0)

Keywords: Chagas Disease; Galectin 3; Heart Failure; Polymorphism, Genetic; Chagas Cardiomyopathy



A galectina-3, uma lectina de ligação à β-galactosidase, foi descrita como um mediador de fibrose cardíaca em estudos experimentais e um fator de risco associado com eventos cardiovasculares em indivíduos com insuficiência cardíaca. Estudos prévios avaliaram a susceptibilidade genética para doença de Chagas em humanos, incluindo polimorfismos dos genes de citocinas, demonstrando correlações entre o polimorfismo genético e o desenvolvimento de cardiomiopatia na fase crônica. No entanto, a relação entre polimorfismos de nucleotídeo único (single nucleotide polymorphism, SNP) e variações fenotípicas na doença de Chagas ainda não foi avaliada.


O presente estudo teve como objetivo determinar se os polimorfismos genéticos da galectina-3 podem predispor ao desenvolvimento de formas cardíacas da doença de Chagas.


Cinquenta e cinco indivíduos com doença de Chagas foram incluídos neste estudo observacional. A genotipagem das variantes rs4644 e rs4652 do gene da galectina-3 foi realizada por PCR (reação em cadeia de polimerase).


Para o SNP rs4644, não houve associação entre o risco relativo para a forma cardíaca e os genótipos AA (OR = 0,79, p = 0,759), AC (OR = 4,38, p = 0,058), ou CC (OR = 0,39, p = 0,127). Similarmente, para o SNP rs4652, não foi encontrada associação entre os genótipos AA (OR = 0,64, p = 0,571), AC (OR = 2,85, p = 0,105), ou CC (OR = 0,49, p = 0,227) e a forma cardíaca da doença.


Nossos resultados não mostraram associação entre os diferentes genótipos para ambos SNPs do gene da galectina-3 e a forma cardíaca da doença de Chagas. (Arq Bras Cardiol. 2015; [online].ahead print, PP.0-0)

Palavras-chave: Doença de Chagas; Galectina 3; Insuficiência Cardíaca; Polimorfismo Genético; Cardiomiopatia Chagásica


Chagas disease (CD), caused by the intracellular parasite Trypanosoma cruzi, is a major public health problem in Latin America and affects millions of people worldwide1. About 30% of the patients develop chronic cardiomyopathy, which is the most severe form of CD and associated with worse prognosis in heart failure2. Since there is no effective treatment in this stage of the disease, it is crucial to identify biomarkers that might be used in the early detection of cardiac disease and prognostic stratification.

Previous studies have evaluated the genetic susceptibility to CD in humans. Polymorphisms of molecules involved in host damage, induced by the parasite, such as IL-4, IL-6, IL-10, IL-12, TNF-α, and IFN-γ have been determined in subjects with the disease, demonstrating the association between genetic polymorphism and the development of cardiomyopathy in the chronic phase of CD3-8.

Recently, our group has demonstrated that the galectin-3 gene is overexpressed in the heart of animals chronically infected with Trypanosoma cruzi9,10. Galectin-3 is a member of the galectin family that binds β-galactosides and is produced by activated macrophages and fibroblasts11. It has been shown to be a mediator of cardiac fibrosis in experimental studies11,12 and to be related to cardiovascular events and heart failure severity13,14.

Previous studies have shown that genetic variants at two galectin-3 gene single nucleotide polymorphism (SNP) sites (rs4644 and rs4652, corresponding to LGALS3 +191 A>C and LGALS3 +292 A>C, respectively) are able to change the protein levels15. Galectin-3 plays an important role in inflammation and fibrosis process, and the relationship between the SNPs in the galectin-3 gene and the phenotypic variations in CD have not been evaluated. We hypothesized that galectin-3 SNPs can influence the development of cardiac forms of Chagas disease. Therefore, the present study aimed to evaluate the correlation of genetic polymorphisms of galectin-3 with severity of the cardiac form of Chagas disease.


Study population

A retrospective observational study was performed between January 2011 and December 2013. A convenience sample of 55 subjects attending the CD outpatient clinic at Hospital São Rafael was studied.

Inclusion criteria were: CD diagnosis confirmed microbiologically by two serological tests (indirect hemagglutination and indirect immunofluorescence), and age from 18 to 70 years. Exclusion criteria were: previous myocardial infarction or history of coronary artery disease, primary valve disease, dialysis treatment for end-stage renal disease, active liver disease, hematologic, neoplastic or bone diseases, and contraindications to magnetic resonance imaging (MRI).

The study complied with the Declaration of Helsinki and was approved by the Ethics Committee. All subjects signed a written informed consent before their inclusion in the study. All subjects underwent a structured medical history and physical examination, blood analysis, 12-lead Electrocardiography (ECG), chest X-Ray, 24-h Holter monitoring, conventional Doppler echocardiogram, and cardiac magnetic resonance.

Genotyping of galectin-3 gene SNPs

Samples of genomic DNA were obtained from peripheral blood mononuclear cells. DNA extraction was performed using the commercial kit QIAamp DNA Blood Mini Kit (Qiagen GmbH, Hilden, Germany), according to the manufacturer’s recommendations. The samples were stored in a freezer at -20°C. Genotyping of the SNPs rs4644 and rs4652 of the galectin-3 gene was performed by real-time polymerase chain reaction (PCR) using TaqMan® (Life Technologies, Carlsbad, USA), and the SNPs were amplified using the TaqMan® Universal PCR protocol (Life Technologies). Genotypes of each SNP were determined using the Sequence Detection System software version 1.3.1 (Life Technologies). The probes and primers for the selected SNPs were supplied by the same company.

Doppler echocardiogram

Standard transthoracic echocardiographic examination was performed using the Vivid 7 digital ultrasound system (GE Vingmed Ultrasound AS, Horten, Norway). Three cardiac cycles were stored in cineloop format for offline analysis. Left ventricle (LV) and left atrial dimensions were measured according to the American Society of Echocardiography’s recommendations16. The LV ejection fraction (LVEF) was measured using the biplane Simpson’s method.

Cardiac magnetic resonance imaging

Cardiac magnetic resonance imaging was performed using a Sigma HDx 1.5-T system (General Electric; Fairfield, CT, USA). For assessment of the LV function, electrocardiography-gated, breath-hold long-axis, short-axis, and four-chamber views were acquired in the same location in different sequences. Acquisition parameters used for the dynamic sequence included a repetition time (RT) of 3.5 ms, an echo time (ET) of 1.5 ms, flip angle of 60°, a receiver bandwidth of 125 kHz, a 35 x 35 cm field of view (FOV), a matrix of 256x148, a temporal resolution (TR) of 35 ms, and a slice thickness of 8.0 mm without gap. Delayed enhancement images were acquired every heartbeat, 10 to 20 min after the administration of a gadolinium-based contrast (0.1 mmol/kg) using RT of 7.1 ms, ET of 3.1 ms, flip angle of 20°, first cardiac phase, views per segment 16/32, matrix size of 256 x 192, slice thickness of 8.0 mm, gap between slices of 2 mm, field of view 32 to 38 cm, inversion time 150 to 300 ms, receiver bandwidth of 31.25 kHz, number of excitations of 2. The myocardial delayed enhancement (MDE) technique was used to investigate myocardial fibrosis, which was estimated by a quantitative visual method.

Statistical analysis

Categorical data were expressed as numbers (percentages, 95% confidence interval), and continuous data were expressed as mean ± SD or median (interquartile range). The genotype distribution of the SNPs rs4644 and rs4652 (AA, AC and CC) in subjects with indeterminate form of CD was compared with that in subjects with the cardiac form of CD using the Chi-square test or the Fisher’s exact test. The percentage of myocardial fibrosis was compared between the groups with the 3 different genotypes Kruskal-Wallis test. Mann-Whitney test was used to assess differences in the median of myocardial fibrosis between subjects with and without the SNPs. The association between the cardiac form of CD and each of the genotypes (AA, AC and CC) was estimated by Odds Ratio (OR) and 95% confidence interval (CI). Cases with missing data were dropped from the analysis. Analyses were performed using SPSS version 20.0 (IBM), and p < 0.05 (two-tailed) was considered statistically significant.


Clinical and imaging characteristics

The study comprised 55 subjects, 42% were men, with mean age of 58 ± 9 years. The prevalence of hypertension, diabetes, hypercholesterolemia and smoking were 71, 14, 42 and 27% respectively. Regarding the clinical forms, the subjects were distributed as follows: 16 (29%) with the indeterminate form (subjects with no evidence of cardiac involvement or heart failure), 16 (29%) with the cardiac form without ventricular dysfunction and 23 (42%) with the cardiac form with ventricular dysfunction. Seventeen subjects were in NYHA (New York Heart Association) functional class III-IV (31%). The mean LVEF, measured using the biplane Simpson’s method, was 54 ± 15%, and the median percentage of myocardial fibrosis was 9.4% (2.2-17.3). Clinical and demographic characteristics of the subjects are described in Table 1.

Table 1 Subjects' clinical and demographic characteristics 

  Subjects (n = 55)
Male gender 23 (41.8)
Age (years) 58 ± 9
Indeterminate form 16 (29)
Cardiac form without ventricular dysfunction 16 (29)
Cardiac form with ventricular dysfunction 23 (42)
NYHA III ou IV 17 (30.9)
Hypertension 39 (70.9)
Diabetes 8 (14.5)
Current smoking 15 (27.3)
Hypercholesterolemia 23 (41.8)
RBBB 27 (49.1)
Hemoglobin (g/dl) 14.0 ± 0.97
Creatinin (mg/dl) 0.87 ± 0.16
LVEF (%) 53.7 ± 15.4
LVESV (ml) 79.1 ± 65.4
LVEDV (ml) 177.3 ± 80.6
LVmass (g) 172.8 ± 57.3
Myocardial fibrosis (%) 9.4 (2.2-17.3)*

Data are expressed as number (percentage) for categorical variables, and as mean ± SD or median (interquartile interval) for continuous variables; NYHA: New York Heart Association CMR: RBBB: Right bundle-branch block; LVEF: Left ventricular ejection fraction; LVESV: Left ventricular end-systolic volume; LVEDV: Left ventricular end-diastolic volume; LV: Left ventricular mass.

*n = 40 (delayed enhancement cardiac magnetic resonance).

Genotyping of LGALS3 SNPs

The SNPs genotype distribution is described in Table 2. There was no significant association between LGALS3genotypes (AA, AC, CC) of the SNPs rs4644 and rs4652 and the presence of the cardiac form of CD. For the SNP rs4644, the relative risk of the cardiac form was not associated with the genotype AA (OR = 0.79, 95%CI = 0.17 to 3.63, p = 0.759), AC (OR = 4.38, 95%CI = 0.87 to 22.02, p = 0.058), or CC (OR = 0.39, 95%CI = 0.11 to 1.33, p = 0.127). Similarly, for the SNP rs4652, the genotypes AA (OR = 0.64, 95%CI = 0.13 to 3.06, p = 0.571), AC (OR = 2.85, 95%CI = 0.78 to 10.40, p = 0.105), and CC (OR = 0.49, 95%CI = 0.15 to 1.58, p = 0.227) were not associated with the cardiac form of CD.

Table 2 Genotype and allele frequency of LGALS3 + 191 and LGALS3+292 in 16 subjects with the indeterminate form and 39 subjects with the cardiac form of Chagas disease 

LGALS3 polymorphism Indeterminate form (n=16) Cardiac form (n = 39) OR (95% CI) p value
LGALS3 +191        
AA 3 (19, 7-43) 6 (15, 7-30) 0.79 (0.17-3.63) 0.759
AC 2 (12, 4-36) 15 (38, 25-54) 4.38 (0.87-22.02) 0.058
CC 11 (69, 44-86) 18 (46, 32-61) 0.39 (0.11-1.33) 0.127
LGALS3 +292        
AA 3 (19, 7-43) 5 (13, 6-27) 0.64 (0.13-3.06) 0.571
AC 4 (25, 10-50) 19 (49, 34-64) 2.85 (0.78-10.40) 0.105
CC 9 (56, 33-77) 15 (38, 25-54) 0.49 (0.15-1.58) 0.227

Data are expressed as number (percentage, 95% confidence interval).

The SNP rs4644 genotype frequencies were not statistically different between the subjects with the indeterminate form and with the cardiac form of CD. (AA [19% vs 15%, p = 0.710], AC [12% vs 38%, p = 0.106] and CC [69% vs 46%, p = 0.149]) (Figure 1). In subjects with the indeterminate form, the most frequent genotype was the CC genotype, with a significantly higher prevalence than the genotypes AA and AC (p = 0.011 and p = 0.003, respectively). In subjects with the cardiac form, two genotypes were found to be more prevalent, AC and CC, as compared with the AA genotype (p = 0.04 and p = 0.006, respectively), with no difference between the prevalence of AC and CC (p = 0.647).

Figure 1 Prevalence of the genotypes AA, AC and CC of the LGALS3 rs4644 in the indeterminate form and cardiac form of Chagas disease. The p-values using two-sided Fisher’s exact test were p = 0.710, p = 0.106 and p = 0.149, respectively. * p = 0.04, compared to AA genotype; ** p = 0.006, compared to AA genotype AA; *** p = 0.011, compared to AA genotype, and p = 0.003, compared to AC genotype 

Similar results were observed for the SNP rs4652 genotype distribution between the groups (Figure 2). In subjects with the indeterminate form and subjects with the cardiac form of CD, respectively, the prevalence of the AA genotype was 19% vs 13% (p = 0.678), the prevalence of AC was 25% vs 49% (p = 0.138), and the prevalence of CC was 56% vs 38% (p = 0.249). In subjects with the indeterminate form, there was no significant difference between the three genotypes (AA vs CC, p = 0.066; AA vs AC, p = 1.00; and AC vs AA, p = 0.149). Similarly to the SNP rs4644, in subjects with the cardiac form, genotypes AC and CC were more prevalent, as compared with genotype AA (p = 0.001 and p = 0.018, respectively), with no difference between the prevalence of AC and CC (p = 0.494).

Figure 2 Prevalence of the genotypes AA, AC and CC of the LGALS3 rs4652 in the indeterminate form and cardiac form of Chagas disease. The p-values using twosided Fisher’s exact test were p = 0. 678, p = 0.138 and p = 0.249, respectively; * p = 0.018, compared to the AA genotype; ** p = 0.001, compared to the AA genotype 

Myocardial fibrosis

There was no statistically significant difference in the median percentage of myocardial fibrosis between subjects with and without the presence of any of the SNPs rs4644 and rs4652 genotypes (Table 3).

Table 3 Median percentage of myocardial fibrosis in subjects with and without galectin-3 SNPs by genotype 

  Without the SNP With the SNP p value
rs4644 AA 4.3 (0.0-14.4) 1.6 (0.0-4.7) 0.261
rs4644 AC 4.4 (0.0-9.8) 1.6 (0.0-19.2) 0.969
rs4644 CC 1.6 (0.0-15.0) 5.2 (0.2-18.5) 0.441
rs4652 AA 4.3 (0.0-14.0) 2.0 (0.3-10.6) 0.743
rs4652 AC 4.4 (0.0-10.0) 1.7 (0.0-15.1) 0.862
rs4652 CC 1.9 (0.0-14.1) 4.8 (0.0-10.0) 0.681

SNP: Single nucleotide polymorphism; Data are expressed as median (interquartile interval); p-values of Mann-Whitney U test.

The median percentage of myocardial fibrosis was not statistically different between the AA, AC and CC genotypes (p = 0.508), or between SNP rs4644 and SNP rs4652 (p = 0.903 (Figure 3).

Figure 3 Percentage of myocardial fibrosis in subjects with the AA, AC and CC genotypes of the LGALS3 rs4644 (A) and rs4652 (B), p = 0.508 and p = 0.903, respectively. 


This study evaluated the association between genetic variants of the LGALS3 gene, encoding for galectin-3, and disease severity in subjects with CD. Since galectin-3 has been previously found to be highly correlated with fibrosis, we also evaluated the association of the three genotypes of the SNPs rs4644 and rs4652 with myocardial fibrosis. We found no significant difference in the prevalence of any of the genotypes between the subjects with the indeterminate form and the cardiac form of the disease. Also, there was no difference in the median of myocardial fibrosis between subjects with the AA, AC and CC genotypes of the SNPs in question.

The genetic predisposition to galectin-3 polymorphism has been previously associated with rheumatoid arthritis, another inflammatory disease. Hu et al15 described an association between this rheumatic disease and the LGALS3 +292C allele. Although we have shown that the LGALS3 +191C and LGALS3 + 292C allele carriage was relatively high in subjects with the cardiac form of CD, the CC genotype, at least for the SNP rs4644, was relatively more frequent among subjects with the indeterminate form. Thus, we could not confirm the possible role of the presence of CC genotype or AA genotype for both SNPs as a protective or a risk factor for developing the cardiac form of CD. Similarly, no relationship between the genetic polymorphisms in the gene encoding galectin-3 and the median of myocardial fibrosis was observed.


Studies at the levels of genes and proteins contribute to the understanding of the role of genetic variants in the etiology of diseases, as well as to elucidate their potential as therapeutic targets, risk predictors and prognostic markers. Our findings did not lead to a significant conclusion on the role of galectin-3 polymorphism in the development of the cardiac form of CD. In addition, further studies with long-term follow up are necessary to evaluate whether other genetic variants play a role in inflammation and fibrosis in the indeterminate form of CD, to identify possible variants associated with disease progression in CD.

Sources of Funding

This study was funded by FAPESB.

Study Association

This study is not associated with any thesis or dissertation work.


The authors thank Dr. Kyan James Allahdadi, PhD, for carefully reviewing the manuscript.


World Health Organization. Chagas disease: control and elimination. Geneva; 2010. [ Links ]

Silva CP, Del Carlo CH, Oliveira Junior MT, Scipioni A, Strunz-Cassaro C, Ramirez JA, et al. Why do patients with chagasic cardiomyopathy have worse outcomes than those with non-chagasic cardiomyopathy? Arq Bras Cardiol. 2008;91(6):358-62. [ Links ]

Beraún Y, Nieto A, Collado MD, González A, Martín J. Polymorphisms at tumor necrosis factor (TNF) loci are not associated with Chagas' disease. Tissue Antigens. 1998;52(1):81-3. [ Links ]

Costa GC, da Costa Rocha MO, Moreira PR, Menezes CA, Silva MR, Gollob KJ, et al. Functional IL-10 gene polymorphism is associated with Chagas disease cardiomyopathy. J Infect Dis. 2009;199(3):451-4. [ Links ]

Drigo SA, Cunha-Neto E, Ianni B, Mady C, Faé KC, Buck P, et al. Lack of association of tumor necrosis factor-alpha polymorphisms with Chagas disease in Brazilian patients. Immunol Lett. 2007;108(1):109-11. [ Links ]

Flórez O, Martín J, González CI. Interleukin 4, interleukin 4 receptor-a and interleukin 10 gene polymorphisms in Chagas disease. Parasite Immunol. 2011;33(9):506-11. [ Links ]

Torres OA, Calzada JE, Beraún Y, Morillo CA, González A, González CI, et al. Lack of association between IL-6-174G/C gene polymorphism and Chagas disease. Tissue Antigens. 2010;76(2):131-4. [ Links ]

Zafra G, Morillo C, Martín J, González A, González CI. Polymorphism in the 3' UTR of the IL12B gene is associated with Chagas' disease cardiomyopathy. Microbes Infect. 2007;9(9):1049-52. [ Links ]

Soares MB, Lima RS, Souza BS, Vasconcelos JF, Rocha LL, Dos Santos RR, et al. Reversion of gene expression alterations in hearts of mice with chronic chagasic cardiomyopathy after transplantation of bone marrow cells. Cell Cycle. 2011;10(9):1448-55. [ Links ]

Vasconcelos JF, Souza BS, Lins TF, Garcia LM, Kaneto CM, Sampaio GP, et al. Administration of granulocyte colony-stimulating factor induces immunomodulation, recruitment of T regulatory cells, reduction of myocarditis and decrease of parasite load in a mouse model of chronic Chagas disease cardiomyopathy. FASEB J. 2013;27(12):4691-702. [ Links ]

Sharma UC, Pokharel S, van Brakel TJ, van Berlo JH, Cleutjens JP, Schroen B, et al. Galectin-3 marks activated macrophages in failure-prone hypertrophied hearts and contributes to cardiac dysfunction. Circulation. 2004;110(19):3121-8. [ Links ]

Liu YH, D'Ambrosio M, Liao TD, Peng H, Rhaleb NE, Sharma U, et al. N-acetyl-seryl-aspartyl-lysyl-proline prevents cardiac remodeling and dysfunction induced by galectin-3, a mammalian adhesion/growth-regulatory lectin. Am J Physiol Heart Circ Physiol. 2009;296(2):H404-12. [ Links ]

Felker GM, Fiuzat M, Shaw LK, Clare R, Whellan DJ, Bettari L, et al. Galectin-3 in ambulatory patients with heart failure: results from the HF-ACTION study. Circ Heart Fail. 2012;5(1):72-8. [ Links ]

Fermann GJ, Lindsell CJ, Storrow AB, Hart K, Sperling M, Roll S, et al. Galectin 3 complements BNP in risk stratification in acute heart failure. Biomarkers. 2012;17(8):706-13. [ Links ]

Hu CY, Chang SK, Wu CS, Tsai WI, Hsu PN. Galectin-3 gene (LGALS3) +292C allele is a genetic predisposition factor for rheumatoid arthritis in Taiwan. Clin Rheumatol. 2011;30(9):1227-33. [ Links ]

Lang RM, Bierig M, Devereux RB, Flachskampf FA, Foster E, Pellikka PA, et al; Chamber Quantification Writing Group; American Society of Echocardiography's Guidelines and Standards Committee; European Association of Echocardiography. Recommendations for chamber quantification: a report from the American Society of Echocardiography's Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr. 2005;18(12):1440-63. [ Links ]

Received: May 21, 2015; Revised: June 01, 2015; Accepted: June 23, 2015

Mailing Address: Ticiana Ferreira Larocca, Av. São Rafael, 2152. Postal Code 41253-190. São Marcos, Salvador, BA - Brazil. Email:

Author contributions

Conception and design of the research: Cruz GS, Angelo ALD, Souza BSF, Santos RR, Soares MBP; Acquisition of data: Cruz GS, Angelo ALD, Larocca TF, Macedo CT, Noya- Rabelo M, Torreão JÁ; Analysis and interpretation of the data: Cruz GS, Angelo ALD, Larocca TF, Macedo CT, Noya- Rabelo M, Correia LCL, Torreão JA, Souza BSF, Soares MBP; Statistical analysis: Cruz GS, Angelo ALD, Larocca TF, Noya- Rabelo M, Correia LCL; Obtaining financing: Santos RR, Soares MBP; Writing of the manuscript: Cruz GS, Larocca TF, Souza BSF; Critical revision of the manuscript for intellectual content: Cruz GS, Angelo ALD, Larocca TF, Macedo CT, Noya- Rabelo M, Correia LCL, Souza BSF, Santos RR, Soares MBP.

Potential Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Creative Commons License This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.