Untargeted metabolome atlas for sleep-related phenotypes in the Hispanic community health study/study of LatinosResearch in context
Ying Zhang,
Brian W. Spitzer,
Yu Zhang,
Danielle A. Wallace,
Bing Yu,
Qibin Qi,
Maria Argos,
M Larissa Avilés-Santa,
Eric Boerwinkle,
Martha L. Daviglus,
Robert Kaplan,
Jianwen Cai,
Susan Redline,
Tamar Sofer
Affiliations
Ying Zhang
Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
Brian W. Spitzer
CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
Yu Zhang
CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
Danielle A. Wallace
Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
Bing Yu
Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
Qibin Qi
Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
Maria Argos
Department of Epidemiology and Biostatistics, School of Public Health, University of Illinois Chicago, Chicago, IL, USA; Department of Environmental Health, School of Public Health, Boston University, Boston, MA, USA
M Larissa Avilés-Santa
Division of Clinical and Health Services Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
Eric Boerwinkle
Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
Martha L. Daviglus
Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
Robert Kaplan
Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
Jianwen Cai
Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
Susan Redline
Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
Tamar Sofer
Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA; Corresponding author. Center for Life Sciences, CLS-934, 3 Blackfan St, Boston, MA, 02115, USA.
Summary: Background: Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep-related phenotypes and blood metabolites. Methods: Utilising data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep-related phenotypes, grouped in several domains (sleep disordered breathing (SDB), sleep duration, sleep timing, self-reported insomnia symptoms, excessive daytime sleepiness (EDS), and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualise and interpret the associations between sleep phenotypes and metabolites. Findings: The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, primary bile acid metabolism showed the highest cumulative percentage of statistically significant associations across all sleep phenotype domains except for SDB and EDS phenotypes. Several metabolites were associated with multiple sleep phenotypes, from a few domains. Glycochenodeoxycholate, vanillyl mandelate (VMA) and 1-stearoyl-2-oleoyl-GPE (18:0/18:1) were associated with the highest number of sleep phenotypes, while pregnenolone sulfate was associated with all sleep phenotype domains except for sleep duration. N-lactoyl amino acids such as N-lactoyl phenylalanine (lac-Phe), were associated with sleep duration, SDB, sleep timing and heart rate during sleep. Interpretation: This atlas of sleep–metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health. Funding: R01HL161012, R35HL135818, R01AG80598.
