Right coronary artery spectral Doppler coronary flow velocity signal in baseline (A) and hyperemic (B) conditions

<p><b>Copyright information:</b></p><p>Taken from "Echocardiographic and hemodynamic determinants of right coronary artery flow reserve and phasic flow pattern in advanced non-ischemic cardiomyopathy"</p><p>http://www.cardiovascularultrasound.com/content/5/1/31</p><p>Cardiovascular Ultrasound 2007;5():31-31.</p><p>Published online 26 Sep 2007</p><p>PMCID:PMC2137923.</p><p></p> S = systolic, D = diastolic, portions of phasic coronary flow. APV = time-averaged peak coronary flow velocity. DSVR = diastolic/systolic flow velocity ratio

Baseline spectral Doppler coronary flow velocity signal in right coronary artery (A) and left anterior descending coronary artery (B)

<p><b>Copyright information:</b></p><p>Taken from "Echocardiographic and hemodynamic determinants of right coronary artery flow reserve and phasic flow pattern in advanced non-ischemic cardiomyopathy"</p><p>http://www.cardiovascularultrasound.com/content/5/1/31</p><p>Cardiovascular Ultrasound 2007;5():31-31.</p><p>Published online 26 Sep 2007</p><p>PMCID:PMC2137923.</p><p></p> S = systolic, D = diastolic, portions of phasic coronary flow. APV = time-averaged peak coronary flow velocity. DSVR = diastolic/systolic flow velocity ratio

Box-plot representing the RCA vs LAD comparison respecting the coronary flow reserve, showing no significant difference

<p><b>Copyright information:</b></p><p>Taken from "Echocardiographic and hemodynamic determinants of right coronary artery flow reserve and phasic flow pattern in advanced non-ischemic cardiomyopathy"</p><p>http://www.cardiovascularultrasound.com/content/5/1/31</p><p>Cardiovascular Ultrasound 2007;5():31-31.</p><p>Published online 26 Sep 2007</p><p>PMCID:PMC2137923.</p><p></p> LAD – left anterior descending coronary artery; N – number of patients; RCA – right coronary artery

Box-plot representing the RCA phasic coronary flow pattern (D/S) according the RV ejection fraction, showing no difference between RV non-dysfunctional vs

<p><b>Copyright information:</b></p><p>Taken from "Echocardiographic and hemodynamic determinants of right coronary artery flow reserve and phasic flow pattern in advanced non-ischemic cardiomyopathy"</p><p>http://www.cardiovascularultrasound.com/content/5/1/31</p><p>Cardiovascular Ultrasound 2007;5():31-31.</p><p>Published online 26 Sep 2007</p><p>PMCID:PMC2137923.</p><p></p> dysfunctional subgroups. APV – time-averaged peak coronary flow velocity; D/S – diastolic/systolic APV ratio; N – number of patients; RCA – right coronary artery; RV EF – right ventricular ejection fraction

Genomic positions that associated to traits (unadjusted P-value <10⁻⁶, intergenic positions not shown).

<p>Genomic positions that associated to traits (unadjusted P-value <10⁻⁶, intergenic positions not shown).</p

Population stratification of Brazilian Chagas cohort along with Hapmap populations.

<p>Each point on the plot represents an individual; each population is coded in a different color. The populations are: ASW: African ancestry in Southwest USA; CEU: Utah residents with Northern and Western European ancestry from the CEPH collection; CHB: Han Chinese in Beijing, China; CHD: Chinese in Metropolitan Denver, Colorado; GIH: Gujarati Indians in Houston, Texas; JPT: Japanese in Tokyo, Japan; LWK: Luhya in Webuye, Kenya; MEX: Mexican ancestry in Los Angeles, California; MKK: Maasai in Kinyawa, Kenya; TSI: Toscans in Italy; YRI: Yoruba in Ibadan, Nigeria.A) Dimension 1 vs. Dimension 2; B) Dimension 2 vs Dimension 3.</p

Genome Wide Association Study (GWAS) of Chagas Cardiomyopathy in <i>Trypanosoma cruzi</i> Seropositive Subjects

<div><p>Background</p><p>Familial aggregation of Chagas cardiac disease in <i>T. cruzi</i>–infected persons suggests that human genetic variation may be an important determinant of disease progression.</p><p>Objective</p><p>To perform a GWAS using a well-characterized cohort to detect single nucleotide polymorphisms (SNPs) and genes associated with cardiac outcomes.</p><p>Methods</p><p>A retrospective cohort study was developed by the NHLBI REDS-II program in Brazil. Samples were collected from 499 <i>T. cruzi</i> seropositive blood donors who had donated between1996 and 2002, and 101 patients with clinically diagnosed Chagas cardiomyopathy. In 2008–2010, all subjects underwent a complete medical examination. After genotype calling, quality control filtering with exclusion of 20 cases, and imputation of 1,000 genomes variants; association analysis was performed for 7 cardiac and parasite related traits, adjusting for population stratification.</p><p>Results</p><p>The cohort showed a wide range of African, European, and modest Native American admixture proportions, consistent with the recent history of Brazil. No SNPs were found to be highly (P<10⁻⁸) associated with cardiomyopathy. The two mostly highly associated SNPs for cardiomyopathy (rs4149018 and rs12582717; P-values <10⁻⁶) are located on Chromosome 12p12.2 in the SLCO1B1 gene, a solute carrier family member. We identified 44 additional genic SNPs associated with six traits at P-value <10^-6: Ejection Fraction, PR, QRS, QT intervals, antibody levels by EIA, and parasitemia by PCR.</p><p>Conclusion</p><p>This GWAS identified suggestive SNPs that may impact the risk of progression to cardiomyopathy. Although this Chagas cohort is the largest examined by GWAS to date, (580 subjects), moderate sample size may explain in part the limited number of significant SNP variants. Enlarging the current sample through expanded cohorts and meta-analyses, and targeted studies of candidate genes, will be required to confirm and extend the results reported here. Future studies should also include exposed seronegative controls to investigate genetic associations with susceptibility or resitance to <i>T. cruzi</i> infection and non-Chagas cardiomathy.</p></div

Table_2_Blood DNA methylation marks discriminate Chagas cardiomyopathy disease clinical forms.docx

Chagas disease is a parasitic disease from South America, affecting around 7 million people worldwide. Decades after the infection, 30% of people develop chronic forms, including Chronic Chagas Cardiomyopathy (CCC), for which no treatment exists. Two stages characterized this form: the moderate form, characterized by a heart ejection fraction (EF) ≥ 0.4, and the severe form, associated to an EF < 0.4. We propose two sets of DNA methylation biomarkers which can predict in blood CCC occurrence, and CCC stage. This analysis, based on machine learning algorithms, makes predictions with more than 95% accuracy in a test cohort. Beyond their predictive capacity, these CpGs are located near genes involved in the immune response, the nervous system, ion transport or ATP synthesis, pathways known to be deregulated in CCCs. Among these genes, some are also differentially expressed in heart tissues. Interestingly, the CpGs of interest are tagged to genes mainly involved in nervous and ionic processes. Given the close link between methylation and gene expression, these lists of CpGs promise to be not only good biomarkers, but also good indicators of key elements in the development of this pathology.</p

Table_1_Blood DNA methylation marks discriminate Chagas cardiomyopathy disease clinical forms.docx

Chagas disease is a parasitic disease from South America, affecting around 7 million people worldwide. Decades after the infection, 30% of people develop chronic forms, including Chronic Chagas Cardiomyopathy (CCC), for which no treatment exists. Two stages characterized this form: the moderate form, characterized by a heart ejection fraction (EF) ≥ 0.4, and the severe form, associated to an EF < 0.4. We propose two sets of DNA methylation biomarkers which can predict in blood CCC occurrence, and CCC stage. This analysis, based on machine learning algorithms, makes predictions with more than 95% accuracy in a test cohort. Beyond their predictive capacity, these CpGs are located near genes involved in the immune response, the nervous system, ion transport or ATP synthesis, pathways known to be deregulated in CCCs. Among these genes, some are also differentially expressed in heart tissues. Interestingly, the CpGs of interest are tagged to genes mainly involved in nervous and ionic processes. Given the close link between methylation and gene expression, these lists of CpGs promise to be not only good biomarkers, but also good indicators of key elements in the development of this pathology.</p

Table_3_Blood DNA methylation marks discriminate Chagas cardiomyopathy disease clinical forms.docx

Chagas disease is a parasitic disease from South America, affecting around 7 million people worldwide. Decades after the infection, 30% of people develop chronic forms, including Chronic Chagas Cardiomyopathy (CCC), for which no treatment exists. Two stages characterized this form: the moderate form, characterized by a heart ejection fraction (EF) ≥ 0.4, and the severe form, associated to an EF < 0.4. We propose two sets of DNA methylation biomarkers which can predict in blood CCC occurrence, and CCC stage. This analysis, based on machine learning algorithms, makes predictions with more than 95% accuracy in a test cohort. Beyond their predictive capacity, these CpGs are located near genes involved in the immune response, the nervous system, ion transport or ATP synthesis, pathways known to be deregulated in CCCs. Among these genes, some are also differentially expressed in heart tissues. Interestingly, the CpGs of interest are tagged to genes mainly involved in nervous and ionic processes. Given the close link between methylation and gene expression, these lists of CpGs promise to be not only good biomarkers, but also good indicators of key elements in the development of this pathology.</p