Context: Increasing evidence suggests that sleep is important for fat metabolism. However, the causal relationship between sleep duration and visceral adipose tissue (VAT) needs to be further clarified. Objective: This study investigated the linear and nonlinear causal association between sleep duration and VAT. Methods: This study used one-sample and two-sample Mendelian randomization MR). Single-nucleotide polymorphisms (SNPs) associated with sleep duration at genome-wide significance were obtained from published genome-wide association studies. We also recalculated the correlation between each SNP and sleep duration in the UK Biobank. The associations of SNPs with predicted VAT (396 858 participants) were conducted in the UK Biobank. Results: A total of 396 858 eligible participants (54.10% females, 57 ± 8 years old) were included in the study. The participants slept 7.17 ± 1.04hours and stored 1.25 ± 0.88kg of VAT on average. Genetically predicted sleep duration was significantly associated with VAT. For each 1-hour increase in genetically predicted sleep duration, the reduction in predicted VAT mass was 0.11kg (P = 8.18E-16) in total, 0.17kg (P = 3.30E-11) in men and 0.07kg (P = 1.94E-06) in women. Nonlinear MR analyses demonstrated nonlinearity (L-shaped associations) between genetically predicted sleep duration and VAT in all participants, men, and women. Complementary analyses provided confirmative evidence of the adverse effects of genetically predicted short sleep duration on the increased VAT. In contrast, no clear evidence on the causal effect of genetically predicted long sleep duration on VAT mass was found. Conclusion: The causal association of sleep duration with VAT was L-type. Our findings support that short sleep duration is a risk factor for increasing VAT, thus reinforcing the probability that increasing sleep duration may decrease VAT.
CITATION STYLE
Yu, Y., Chen, Y., Zhang, H., Ai, S., Zhang, J., Benedict, C., … Tan, X. (2022). Sleep Duration and Visceral Adipose Tissue: Linear and Nonlinear Mendelian Randomization Analyses. Journal of Clinical Endocrinology and Metabolism, 107(11), 2992–2999. https://doi.org/10.1210/clinem/dgac551
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