Ruiyuan Zhang1, Xiao Sun1, Zhijie Huang1, Yang Pan1, Adrianna Westbrook2, Shengxu Li3, Lydia Bazzano1, Wei Chen1, Jiang He1, Tanika Kelly1, Changwei Li1. 1. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA. 2. Pediatric Biostatistics Core, Department of Pediatrics, Emory University, Atlanta, Georgia, USA. 3. Children's Minnesota Research Institute, Children's Hospitals and Clinics of Minnesota, Minneapolis, Minnesota, USA.
Abstract
OBJECTIVE: The authors hypothesize that an untargeted metabolomics study will identify novel mechanisms underlying smoking-associated weight loss. METHODS: This study performed cross-sectional analyses among 1,252 participants in the Bogalusa Heart Study and assessed 1,202 plasma metabolites for mediation effects on smoking-BMI associations. Significant metabolites were tested for associations with smoking genetic risk scores among a subset of participants (n = 654) with available genomic data, followed by direction dependence analysis to investigate causal relationships between the metabolites and smoking and BMI. All analyses controlled for age, sex, race, education, alcohol drinking, and physical activity. RESULTS: Compared with never smokers, current and former smokers had a 3.31-kg/m2 and 1.77-kg/m2 lower BMI after adjusting for all covariables, respectively. A total of 22 xenobiotics and 94 endogenous metabolites were significantly associated with current smoking. Eight xenobiotics were also associated with former smoking. Forty metabolites mediated the smoking-BMI associations, and five showed causal relationships with both smoking and BMI. These metabolites, including 1-oleoyl-GPE (18:1), 1-linoleoyl-GPE (18:2), 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4), α-ketobutyrate, and 1-palmitoyl-GPE (16:0), mediated 26.0% of the association between current smoking and BMI. CONCLUSIONS: This study cataloged plasma metabolites altered by cigarette smoking and identified five metabolites that partially mediated the association between current smoking and BMI.
OBJECTIVE: The authors hypothesize that an untargeted metabolomics study will identify novel mechanisms underlying smoking-associated weight loss. METHODS: This study performed cross-sectional analyses among 1,252 participants in the Bogalusa Heart Study and assessed 1,202 plasma metabolites for mediation effects on smoking-BMI associations. Significant metabolites were tested for associations with smoking genetic risk scores among a subset of participants (n = 654) with available genomic data, followed by direction dependence analysis to investigate causal relationships between the metabolites and smoking and BMI. All analyses controlled for age, sex, race, education, alcohol drinking, and physical activity. RESULTS: Compared with never smokers, current and former smokers had a 3.31-kg/m2 and 1.77-kg/m2 lower BMI after adjusting for all covariables, respectively. A total of 22 xenobiotics and 94 endogenous metabolites were significantly associated with current smoking. Eight xenobiotics were also associated with former smoking. Forty metabolites mediated the smoking-BMI associations, and five showed causal relationships with both smoking and BMI. These metabolites, including 1-oleoyl-GPE (18:1), 1-linoleoyl-GPE (18:2), 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4), α-ketobutyrate, and 1-palmitoyl-GPE (16:0), mediated 26.0% of the association between current smoking and BMI. CONCLUSIONS: This study cataloged plasma metabolites altered by cigarette smoking and identified five metabolites that partially mediated the association between current smoking and BMI.
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