Background:
Obstructive sleep apnea (OSA) is one of the most common forms of
sleep-disordered breathing. Studies have shown that certain changes in metabolism play an important
role in the pathophysiology of OSA. However, the causal relationship between these metabolites
and OSA remains unclear.
background:
Obstructive sleep apnea (OSA) is one of the most common forms of sleep-disordered breathing. Studies have shown that certain changes in metabolism play an important role in the pathophysiology of OSA. However, the causal relationship between these metabolites and OSA remains unclear.
Aims:
We use a mendelian randomization (MR) approach to investigate the causal associations
between the genetic liability to metabolites and OSA.
objective:
We use a mendelian randomization (MR) approach to investigate the causal associations between the genetic liability to metabolites and OSA.
Methods:
We performed a 2-sample inverse-variance weighted mendelian randomization analysis
to evaluate the causal effects of genetically determined 486 metabolites on OSA. Multiple sensitivity
analyses were performed to assess pleiotropy. We used multivariate mendelian randomization
analyses to assess confounding factors and mendelian randomization Bayesian model averaging to
rank the significant biomarkers by their genetic evidence. We also conducted a metabolic pathway
analysis to identify potential metabolic pathways.
method:
We performed a 2-sample inverse-variance weighted mendelian randomization analysis to evaluate the causal effects of genetically determined 486 metabolites on OSA. Multiple sensitivity analyses were performed to assess pleiotropy. We used multivariate mendelian randomization analyses to assess confounding factors and MR Bayesian model averaging to rank the significant biomarkers by their genetic evidence. We also conducted a metabolic pathway analysis to identify potential metabolic pathways.
Results:
We identified 14 known serum metabolites (8 risk factors and 6 protective factors) and 12
unknown serum metabolites associated with OSA. These 14 known metabolites included 8 lipids(
1-arachidonoylglycerophosphoethanolamine, Tetradecanedioate, Epiandrosteronesulfate,
Acetylca Glycerol3-phosphate, 3-dehydrocarnitine, Margarate17:0, Docosapentaenoaten3;22:5n3),
3 Aminoacids (Isovalerylcarnitine,3-methyl-2-oxobutyrate,Methionine), 2 Cofactors and vitamins
[Bilirubin(E,ZorZ,E),X-11593--O-methylascorbate], 1Carbohydrate(1,6-anhydroglucose). We also
identified several metabolic pathways that involved in the pathogenesis of OSA.
Conclusion:
MR (mendelian randomization) approach was performed to identify 6 protective factors
and 12 risk factors for OSA in the present study. 3-Dehydrocarnitine was the most significant
risk factors for OSA. Our study also confirmed several significant metabolic pathways that were
involved in the pathogenesis of OSA. Valine, leucine and isoleucine biosynthesis metabolic pathways
were the most significant metabolic pathways that were involved in the pathogenesis of
OSA.
