Vanessa L Z Gordon-Dseagu1, Andriy Derkach2, Qian Xiao3, Ishmael Williams2, Joshua Sampson2, Rachael Z Stolzenberg-Solomon2. 1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD, 20850, USA. nessdseagu@gmail.com. 2. Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD, 20850, USA. 3. Department of Health and Human Physiology, College of Liberal Arts and Sciences, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA.
Abstract
INTRODUCTION: Sleep is increasingly being viewed as an issue of public health concern, yet few epidemiologic studies have explored associations between sleep habits and metabolomic profile. OBJECTIVES: To assess the association between sleep and blood metabolites. METHODS: We examined the association between sleep and 891 fasting plasma metabolites in a subgroup of 106 participants from the Dietary Approaches to Stop Hypertension (DASH)-Sodium feeding trial (1997-1999). We produced two sleep variables to analyze, sleep midpoint (median time between bedtime and waketime) and sleep duration, as well as bedtime and wake time. Metabolites were measured using liquid and gas chromatography, coupled with mass spectrometry. We assessed associations between sleep variables and log transformed metabolites using linear mixed-effects models. We combined the resulting p-values using Fisher's method to calculate associations between sleep and 38 metabolic pathways. RESULTS: Sixteen pathways were associated (p < 0.05) with midpoint. Only the γ-glutamyl amino acid metabolism pathway reached Bonferroni-corrected threshold (0.0013). Eighty-three metabolites were associated with midpoint (FDR < 0.20). Similar associations were found for wake time. Neither bed time nor duration were strongly associated. The top metabolites (pathways given in brackets) associated with sleep were erythrulose (advanced glycation end-product) (positive association) and several γ-glutamyl pathway metabolites, including CMPF (fatty acid, dicarboxylate), isovalerate (valine, leucine and isoleucine and fatty acid metabolism) and HWESASXX (polypeptide) (inverse association). CONCLUSION: Within our study, several metabolites that have previously been linked to inflammation and oxidative stress (processes involved in diseases such as cardiovascular disease and cancer) were found to be associated with sleep.
INTRODUCTION: Sleep is increasingly being viewed as an issue of public health concern, yet few epidemiologic studies have explored associations between sleep habits and metabolomic profile. OBJECTIVES: To assess the association between sleep and blood metabolites. METHODS: We examined the association between sleep and 891 fasting plasma metabolites in a subgroup of 106 participants from the Dietary Approaches to Stop Hypertension (DASH)-Sodium feeding trial (1997-1999). We produced two sleep variables to analyze, sleep midpoint (median time between bedtime and waketime) and sleep duration, as well as bedtime and wake time. Metabolites were measured using liquid and gas chromatography, coupled with mass spectrometry. We assessed associations between sleep variables and log transformed metabolites using linear mixed-effects models. We combined the resulting p-values using Fisher's method to calculate associations between sleep and 38 metabolic pathways. RESULTS: Sixteen pathways were associated (p < 0.05) with midpoint. Only the γ-glutamyl amino acid metabolism pathway reached Bonferroni-corrected threshold (0.0013). Eighty-three metabolites were associated with midpoint (FDR < 0.20). Similar associations were found for wake time. Neither bed time nor duration were strongly associated. The top metabolites (pathways given in brackets) associated with sleep were erythrulose (advanced glycation end-product) (positive association) and several γ-glutamyl pathway metabolites, including CMPF (fatty acid, dicarboxylate), isovalerate (valine, leucine and isoleucine and fatty acid metabolism) and HWESASXX (polypeptide) (inverse association). CONCLUSION: Within our study, several metabolites that have previously been linked to inflammation and oxidative stress (processes involved in diseases such as cardiovascular disease and cancer) were found to be associated with sleep.
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