Talks
Presenting Author Academic/Professional Position
Veronica O'Brien, Medical Student
Academic Level (Author 1)
Medical Student
Academic Level (Author 2)
Faculty
Discipline/Specialty (Author 2)
Human Genetics
Academic Level (Author 3)
Faculty
Discipline/Specialty (Author 3)
Human Genetics
Academic Level (Author 4)
Faculty
Discipline/Specialty (Author 4)
Human Genetics
Academic Level (Author 5)
Faculty
Discipline/Specialty (Author 5)
Human Genetics
Discipline Track
Translational Science
Abstract Type
Research/Clinical
Abstract
Background: Cardiovascular disease (CVD) is the leading cause of death worldwide, and the Hispanic population has a significantly higher risk of developing CVD. In this study, we measured plasma cytokine levels, lipidomic data, and cardiac magnetic resonance imaging (CMRI) in individuals from the San Antonio Family Heart Study (SAFHS). Statistical analysis was implemented to determine the heritability, the correlation between cytokine expression and cardiac phenotype and lipid and cardiac phenotype.
Methods: We analyzed frozen plasma samples from 254 participants using the MILLIPLEX Human Cytokine/Chemokine/Growth Factor Panel A Magnetic Bead Panel. The panel included GM-CSF, IFNg, IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17a, and TNFa. Out of the 254 plasma samples, 234 participants had CMRI performed. Lipidomic analysis of 799 lipid species was performed for each participant. Statistical analyses using Sequential Oligogenic Linkage Analysis Routines (SOLAR) were used to compare quantified cardiac phenotypes from CMRI and lipid phenotypes. Correlation analyses of quantified cardiac imaging and cytokine expression levels were also performed.
Results: Heritability analysis and comparison between cardiac phenotypes and lipidomic data showed heritable correlations in systolic left ventricular mass, diastolic ventricular mass, and subcutaneous adipose tissue. Each of these cardiac phenotypes to lipid phenotype comparisons has a p-value less than 1.407143E-06, after Bonferroni correction. Systolic left ventricular mass showed a negative correlation with PC 42:2 and LPC 26:0 sn1 with estimated percent heritability of 50.67% and 42.43% of the cardiac phenotype, respectively. Diastolic left ventricular mass showed a negative correlation with PC 42:2 and LPC 26:0 sn1 with estimated percent heritability of 30.99% and 26.70% of the cardiac phenotype, respectively. Subcutaneous adipose tissue showed a positive correlation with DG(16:0/18:1) and TG (52:2)[NL-16:0] with an estimated percent heritability of 9.90% and 11.19%, respectively.
Correlation analysis of cytokine expression and quantified CMRI data shows that IL-6 has a significant correlation with 13 different imaging parameters, with the most significant including liver fat, heart rate, adipose tissues, and cardiac volumes. IL-8 has a significant correlation with six imaging parameters, including heart rate, heart volumes, and mitral valve pathology. TNFa has a significant correlation with five imaging parameters, with the most significant being mitral valve pathology. IL-7 had significant correlations with three imaging parameters, including liver fat, epicardial fat, and mitral valve pathology. IL-1ß had significant correlations with mitral valve pathology and chamber output. Lastly, GMCSF, IL-2, IL-12p70, IL-10, and IFNg each had one significant correlation with an imaging parameter. GMCSF with diastolic blood pressure; IL-2, IL-12p70, IL-10 with mitral valve pathology; and IFNg with heart rate.
Conclusions: Through the combination of cytokine expression analysis, lipidomics, and cardiac magnetic resonance imaging, we can further understand the interplay of pro- and anti-inflammatory processes and lipid phenotypes in cardiovascular and metabolic health outcomes. A better understanding of the heritability of pathological and protective lipid phenotypes can help us understand how to better treat and research cardiovascular disease in the high-risk Latino population.
Presentation Type
Talk
Recommended Citation
O'Brien, Veronica; Leandro, Ana; Almeida, Marcio; Blangero, John; and Curran, Joanne, "The Interplay of Cytokine Expression, Cardiac Phenotype, and Heritability in Cardiovascular Health in Mexican Americans." (2025). Research Colloquium. 12.
https://scholarworks.utrgv.edu/colloquium/2025/talks/12
The Interplay of Cytokine Expression, Cardiac Phenotype, and Heritability in Cardiovascular Health in Mexican Americans.
Background: Cardiovascular disease (CVD) is the leading cause of death worldwide, and the Hispanic population has a significantly higher risk of developing CVD. In this study, we measured plasma cytokine levels, lipidomic data, and cardiac magnetic resonance imaging (CMRI) in individuals from the San Antonio Family Heart Study (SAFHS). Statistical analysis was implemented to determine the heritability, the correlation between cytokine expression and cardiac phenotype and lipid and cardiac phenotype.
Methods: We analyzed frozen plasma samples from 254 participants using the MILLIPLEX Human Cytokine/Chemokine/Growth Factor Panel A Magnetic Bead Panel. The panel included GM-CSF, IFNg, IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17a, and TNFa. Out of the 254 plasma samples, 234 participants had CMRI performed. Lipidomic analysis of 799 lipid species was performed for each participant. Statistical analyses using Sequential Oligogenic Linkage Analysis Routines (SOLAR) were used to compare quantified cardiac phenotypes from CMRI and lipid phenotypes. Correlation analyses of quantified cardiac imaging and cytokine expression levels were also performed.
Results: Heritability analysis and comparison between cardiac phenotypes and lipidomic data showed heritable correlations in systolic left ventricular mass, diastolic ventricular mass, and subcutaneous adipose tissue. Each of these cardiac phenotypes to lipid phenotype comparisons has a p-value less than 1.407143E-06, after Bonferroni correction. Systolic left ventricular mass showed a negative correlation with PC 42:2 and LPC 26:0 sn1 with estimated percent heritability of 50.67% and 42.43% of the cardiac phenotype, respectively. Diastolic left ventricular mass showed a negative correlation with PC 42:2 and LPC 26:0 sn1 with estimated percent heritability of 30.99% and 26.70% of the cardiac phenotype, respectively. Subcutaneous adipose tissue showed a positive correlation with DG(16:0/18:1) and TG (52:2)[NL-16:0] with an estimated percent heritability of 9.90% and 11.19%, respectively.
Correlation analysis of cytokine expression and quantified CMRI data shows that IL-6 has a significant correlation with 13 different imaging parameters, with the most significant including liver fat, heart rate, adipose tissues, and cardiac volumes. IL-8 has a significant correlation with six imaging parameters, including heart rate, heart volumes, and mitral valve pathology. TNFa has a significant correlation with five imaging parameters, with the most significant being mitral valve pathology. IL-7 had significant correlations with three imaging parameters, including liver fat, epicardial fat, and mitral valve pathology. IL-1ß had significant correlations with mitral valve pathology and chamber output. Lastly, GMCSF, IL-2, IL-12p70, IL-10, and IFNg each had one significant correlation with an imaging parameter. GMCSF with diastolic blood pressure; IL-2, IL-12p70, IL-10 with mitral valve pathology; and IFNg with heart rate.
Conclusions: Through the combination of cytokine expression analysis, lipidomics, and cardiac magnetic resonance imaging, we can further understand the interplay of pro- and anti-inflammatory processes and lipid phenotypes in cardiovascular and metabolic health outcomes. A better understanding of the heritability of pathological and protective lipid phenotypes can help us understand how to better treat and research cardiovascular disease in the high-risk Latino population.
