TY - JOUR
T1 - Novel metabolites are associated with augmentation index and pulse wave velocity
T2 - Findings from the Bogalusa Heart Study
AU - Li, Changwei
AU - He, Jiang
AU - Li, Shengxu
AU - Chen, Wei
AU - Bazzano, Lydia
AU - Sun, Xiao
AU - Shen, Luqi
AU - Liang, Lirong
AU - Shen, Ye
AU - Gu, Xiaoying
AU - Kelly, Tanika N.
N1 - Publisher Copyright:
© American Journal of Hypertension, Ltd 2019. All rights reserved.
PY - 2019/5/9
Y1 - 2019/5/9
N2 - BACKGROUND Metabolomics study may help identify novel mechanisms underlying arterial stiffening. METHODS We performed untargeted metabolomics profiling among 1,239 participants of the Bogalusa Heart Study. After quality control, 1,202 metabolites were evaluated for associations with augmentation index (AI) and pulse wave velocity (PWV), using multivariate linear regression adjusting for age, sex, race, education, smoking, drinking, body weight, body height, physical activity, and estimated glomerular filtration rate. Heart rate, blood pressure and antihypertensive medication usage, lipids, and fasting glucose were sequentially adjusted in the sensitivity analyses for significant metabolites. Weighted correlation network analysis was applied to build metabolite networks. RESULTS Six novel metabolites were negatively associated with AI, of which, 3-methyl-2-oxobutyrate had the lowest P value and the largest effect size (β = –6.67, P = 5.99 × 10–6). Heart rate contributed to a large proportion (25%–58%) of the association for each metabolite. Twenty-one novel metabolites were identified for PWV, of which, fructose (β = 0.61, P = 6.18 × 10–10) was most significant, and histidine had the largest effect size (β = –1.09, P = 2.51 × 10–7). Blood pressure played a major contribution (9%–54%) to the association for each metabolite. Furthermore, 16 metabolites were associated with arterial stiffness independent of traditional risk factors. Network analysis identified 2 modules associated with both AI and PWV (P < 8.00 × 10–4). One was composed of metabolites from the glycerolipids synthesis and recycling pathway, and the other was involved in valine, leucine, and isoleucine metabolism. One module related to sphingomyelin metabolism was associated with PWV only (P = 0.002). CONCLUSIONS This study has identified novel and important metabolites and metabolic networks associated with arterial stiffness.
AB - BACKGROUND Metabolomics study may help identify novel mechanisms underlying arterial stiffening. METHODS We performed untargeted metabolomics profiling among 1,239 participants of the Bogalusa Heart Study. After quality control, 1,202 metabolites were evaluated for associations with augmentation index (AI) and pulse wave velocity (PWV), using multivariate linear regression adjusting for age, sex, race, education, smoking, drinking, body weight, body height, physical activity, and estimated glomerular filtration rate. Heart rate, blood pressure and antihypertensive medication usage, lipids, and fasting glucose were sequentially adjusted in the sensitivity analyses for significant metabolites. Weighted correlation network analysis was applied to build metabolite networks. RESULTS Six novel metabolites were negatively associated with AI, of which, 3-methyl-2-oxobutyrate had the lowest P value and the largest effect size (β = –6.67, P = 5.99 × 10–6). Heart rate contributed to a large proportion (25%–58%) of the association for each metabolite. Twenty-one novel metabolites were identified for PWV, of which, fructose (β = 0.61, P = 6.18 × 10–10) was most significant, and histidine had the largest effect size (β = –1.09, P = 2.51 × 10–7). Blood pressure played a major contribution (9%–54%) to the association for each metabolite. Furthermore, 16 metabolites were associated with arterial stiffness independent of traditional risk factors. Network analysis identified 2 modules associated with both AI and PWV (P < 8.00 × 10–4). One was composed of metabolites from the glycerolipids synthesis and recycling pathway, and the other was involved in valine, leucine, and isoleucine metabolism. One module related to sphingomyelin metabolism was associated with PWV only (P = 0.002). CONCLUSIONS This study has identified novel and important metabolites and metabolic networks associated with arterial stiffness.
KW - Arterial stiffness
KW - Blood pressure
KW - Hypertension
KW - Metabolite networks
KW - Metabolomics
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U2 - 10.1093/ajh/hpz046
DO - 10.1093/ajh/hpz046
M3 - Article
C2 - 30953049
AN - SCOPUS:85065857016
SN - 0895-7061
VL - 32
SP - 547
EP - 556
JO - American Journal of Hypertension
JF - American Journal of Hypertension
IS - 6
ER -