Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses

Maxime M. Bos, Neil J. Goulding, Matthew A. Lee, Amy Hofman, Mariska Bot, René Pool, Lisanne S. Vijfhuizen, Xiang Zhang, Chihua Li, Rima Mustafa, Matt J. Neville, Ruifang Li-Gao, Stella Trompet, Marian Beekman, Nienke R. Biermasz, Dorret I. Boomsma, Irene de Boer, Constantinos Christodoulides, Abbas Dehghan, Ko Willems van DijkIan Ford, Mohsen Ghanbari, Bastiaan T. Heijmans, M. Arfan Ikram, J. Wouter Jukema, Dennis O. Mook-Kanamori, Fredrik Karpe, Annemarie I. Luik, L. H. Lumey, Arn M.J.M. van den Maagdenberg, Simon P. Mooijaart, Renée de Mutsert, Brenda W.J.H. Penninx, Patrick C.N. Rensen, Rebecca C. Richmond, Frits R. Rosendaal, Naveed Sattar, Robert A. Schoevers, P. Eline Slagboom, Gisela M. Terwindt, Carisha S. Thesing, Kaitlin H. Wade, Carolien A. Wijsman, Gonneke Willemsen, Aeilko H. Zwinderman, Diana van Heemst, Raymond Noordam, Deborah A. Lawlor

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Abstract

Background: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. Methods: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. Results: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (− 0.08 standard deviation (SD)[95% confidence interval (CI) − 0.12, − 0.03] in AMV and − 0.03SD [− 0.07, − 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (− 0.04SD [− 0.08, 0.00] in AMV and − 0.05SD [− 0.09, − 0.02] in MR), and lower phospholipids in very large HDL particles (− 0.04SD [− 0.08, 0.002] in AMV and − 0.05SD [− 0.08, − 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. Conclusions: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

Original languageEnglish
Article number69
Pages (from-to)1-20
Number of pages20
JournalBMC medicine
Volume19
Issue number1
Early online date18 Mar 2021
DOIs
Publication statusPublished - 1 Dec 2021

Keywords

  • Epidemiology
  • Mendelian randomization
  • Metabolomics
  • Sleep

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