Frontiers in Microbiology · 2023 · 33 citations · 50 references
Life SciencesGeneticsMicrobiologyMicrobial GeneticsMicrobiome ResearchStatistical GeneticsGut MicrobiomeGut MicrobiotaMendelian RandomizationMicrobiome DiversityBidirectional Mendelian RandomizationCausal Effects Of Genetic VariantsGenome-wide Association Study DesignGut-brain Axis SignalingMicrobiome-gut-brain AxisMicrobiota-gut-brain AxisMr-egger RegressionWeighted Median Estimation
Introduction: Previous research has reported that the gut microbiota performs an essential role in sleep through the microbiome-gut-brain axis. However, the causal association between gut microbiota and sleep remains undetermined. Methods: We performed a two-sample, bidirectional Mendelian randomization (MR) analysis using genome-wide association study summary data of gut microbiota and self-reported sleep traits from the MiBioGen consortium and UK Biobank to investigate causal relationships between 119 bacterial genera and seven sleep-associated traits. We calculated effect estimates by using the inverse-variance weighted (as the main method), maximum likelihood, simple model, weighted model, weighted median, and MR-Egger methods, whereas heterogeneity and pleiotropy were detected and measured by the MR pleiotropy residual sum and outlier method, Cochran's Q statistics, and MR-Egger regression. Results: In forward MR analysis, inverse-variance weighted estimates concluded that the genetic forecasts of relative abundance of 42 bacterial genera had causal effects on sleep-associated traits. In the reverse MR analysis, sleep-associated traits had a causal effect on 39 bacterial genera, 13 of which overlapped with the bacterial genera in the forward MR analysis. Discussion: In conclusion, our research indicates that gut microbiota may be involved in the regulation of sleep, and conversely, changes in sleep-associated traits may also alter the abundance of gut microbiota. These findings suggest an underlying reciprocal causal association between gut microbiota and sleep.
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The MR-Base platform supports systematic causal inference across the human phenome
Gibran Hemani, Jie Zheng, Benjamin Elsworth et al. · eLife · 2018 · 8.4K citations · Full text