BackgroundInflammation proteins including interleukins (ILs) have been reported to be related to obstructive sleep apnea (OSA). The aims of this study were to estimate the levels for several key interleukins in OSA and the causal effects between them.MethodWeighted mean difference (WMD) was used to compare the expression differences of interleukins between OSA and control, and the changed levels during OSA treatments in the meta-analysis section. A two-sample Mendelian randomization (MR) was used to estimate the causal directions and effect sizes between OSA risks and interleukins. The inverse-variance weighting (IVW) was used as the primary method followed by several other MR methods including MR Egger, Weighted median, and MR-Robust Adjusted Profile Score as sensitivity analysis.ResultsNine different interleukins—IL-1β, IL-2, IL-4, IL-6, IL-8, IL-12, IL-17, IL-18, and IL-23—were elevated in OSA compared with control to varying degrees, ranging from 0.82 to 100.14 pg/ml, and one interleukin, IL-10, was decreased by 0.77 pg/ml. Increased IL-1β, IL-6, and IL-8 rather than IL-10 can be reduced in OSA by effective treatments. Further, the MR analysis of the IVW method showed that there was no significant evidence to support the causal relationships between OSA and the nine interleukins—IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-17, and IL-18. Among them, the causal effect of OSA on IL-5 was almost significant [estimate: 0.267 (−0.030, 0.564), p = 0.078]. These results were consistent in the sensitivity analysis.ConclusionsAlthough IL-1β, IL-2, IL-4, IL-6, IL-8, IL-12, IL-17, IL-18, and IL-23 were increasing and IL-10 was reducing in OSA, no significant causal relationships were observed between them by MR analysis. Further research is needed to test the causality of OSA risk on elevated IL-5 level.

Background Obstructive sleep apnea (OSA) and inflammation are closely related. This study aimed to evaluate the associations and causal effect between C-reactive protein (CRP) and tumour necrosis factor-alpha (TNF-α) levels andOSA. Methods Pooled analysis was conducted to compare the expression differences of CRP and TNF-α between OSA patients with different severity and controls, and between continuous positive airway pressure (CPAP) and non-CPAP interventions for OSA patients. Using published GWAS summary statistics, we conducted a bidirectional two-sample Mendelian Randomization (MR) to estimate the causal relationships between CRP and TNF-α levels and OSA risk. Effect estimates were evaluated using inverse-variance weighted (IVW) as primary method, and several other MR methods as sensitivity analysis. Results Both TNF-α (WMD [95%CI] = 5.86 [4.80–6.93] pg/ml, p < .00001) and CRP (WMD [95%CI] = 2.66 [2.15–3.17] mg/L, p < .00001), showed a significant increase in OSA patients compared with controls and this increasing trend was associated with OSA severity. Besides, compared to blank control (non-CPAP), CPAP treatment can reduce high TNF-α (WMD [95%CI]= −4.44 [−4.81, −4.07]pg/ml, p < .00001) and CRP (WMD [95%CI]= −0.91 [−1.65, −0.17] mg/l, p = .02) in OSA. Moreover, the primary MR analysis by IVW showed that OSA was the genetically predicted cause of elevated CRP (estimate: 0.095; 95% CI, [0.010–0.179]; p = .029) using six SNPs as the instrument variable, which were repeated by weighted median (estimate: 0.053; 95% CI, [0.007, 0.100]; p =.024) and MR RAPS (estimate: 0.109; 95% CI, [0.079, 0.140]; p = 1.98x10 −12 ). Besides, the causal effect from elevated CRP on increased OSA risk was almost significant by IVW (OR:1.053; 95% CI, [1.000, 1.111]; p = .053). However, there were no causal associations between TNF-α and OSA from both directions. Conclusions Increased CRP and TNF-α were associated with OSA severity and sensible to CPAP treatment. Also, OSA had a suggestive causal effect on elevated CRP.

Background The researches on the associations between different candidate genes and obstructive sleep apnea (OSA) are inconsistent. Here, we performed a comprehensive qualitative and quantitative analysis to estimate the contribution of variants from candidate genes to the risk of OSA. Methods Qualitative analysis was conducted to find the relationships for all included genes. Then, quantitative analysis of both allele models and genotype models was applied to evaluate the risk variants for OSA. Furthermore, a similar analysis was performed in different ethnic groups. Results We included 152 publications containing 75 genes for qualitative analysis. Among them, we included 93 articles containing 28 variants from 16 genes for quantitative analysis. Through allele models, we found 10 risk variants for OSA (rs1801133 of MTHFR, ɛ4 of ApoE, −1438G/A of 5‐HT2A, −308G/A of TNF‐α, Pro1019Pro of LEPR, rs1130864 and rs2794521 of CRP, D/I of ACE, LPR and VNTR of 5‐HTT) with the ORs of 1.21–2.07 in global population. We found that the variant of ɛ2 of ApoE could uniquely decrease the risk of OSA in the East Asian subgroup, while the other 6 variants, including ɛ4 in ApoE, −308G/A in TNF‐α, Pro1019Pro in LEPR, D/I in ACE, LPR and VNTR in 5‐HTT, could increase the risk of OSA. As for the European subpopulation, we only found that −308G/A in TNF‐α could increase the risk for OSA. Conclusions Eleven variants from the candidate genes are associated with the risk of OSA, which also show ethnicity differences in East Asian and European subgroups.