Two-sample Mendelian randomization analysis of the causal relationship between human inhalation injury and circulating inflammatory proteins
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摘要:
目的 探究人吸入性损伤与循环炎症蛋白之间的因果关系。 方法 该研究为基于双样本孟德尔随机化（MR）分析的研究。以吸入性损伤为暴露因素、循环炎症蛋白为结局,从全基因组关联分析数据库中获得吸入性损伤（216 993个样本）和91种循环炎症蛋白（14 824个样本）的数据,采用双样本MR分析方法进行分析。根据连锁不平衡分析获得与吸入性损伤显著相关的独立位点单核苷酸多态性（SNP）并将其作为工具变量,主要采用逆方差加权（IVW）法进行吸入性损伤与91种循环炎症蛋白之间因果关系的分析,进一步使用加权中位数法、加权模式法、MR-Egger法和简单模式法进行验证。根据前述IVW法分析结果,针对符合假设的吸入性损伤SNP,进行Cochran Q检验评估异质性,进行MR-Egger回归检验、MR-PRESSO离群值检验评估水平多效性,进行留一法分析评估可靠性。 结果 筛选出6个达到显著阈值（P<5×10-5）的SNP作为代表吸入性损伤的工具变量,其F值均>10,提示均为强相关工具变量。基于6个吸入性损伤SNP,IVW法分析显示,吸入性损伤与白细胞介素20（IL-20）、IL-20受体亚基α（IL-20RA）、IL-5、肿瘤坏死因子受体超家族成员9（TNFRSF9）之间均存在显著因果关系（比值比分别为1.01、1.01、1.02、1.01,95%置信区间分别为1.00~1.02、1.00~1.03、1.01~1.03、1.00~1.03,P<0.05）。经加权中位数法和MR-Egger法验证,吸入性损伤与IL-5（比值比分别为1.02、1.03,95%置信区间分别为1.00~1.04、1.01~1.04,P<0.05）、TNFRSF9（比值比分别为1.02、1.03,95%置信区间分别为1.00~1.04、1.01~1.04,P<0.05）之间均存在显著因果关系；经加权模式法和简单模式法验证,吸入性损伤与IL-20、IL-20RA、IL-5和TNFRSF9之间的因果关系不明显（P值均>0.05）,仍需以IVW法结果为准。根据前述IVW法分析结果,Cochran Q检验评估显示,与IL-20、IL-20RA、IL-5和TNFRSF9存在显著因果关系的6个吸入性损伤SNP均不存在显著异质性（Q值分别为2.67、5.00、5.17、5.29,P>0.05）；MR-Egger回归检验、MR-PRESSO离群值检验评估显示,与IL-20、IL-20RA、IL-5和TNFRSF9存在显著因果关系的6个吸入性损伤SNP均不存在显著水平多效性（截距分别为0.01、<0.01、-0.02、-0.03,RSSobs值分别为3.33、9.00、7.88、7.26,P>0.05）；留一法分析显示,吸入性损伤与IL-20、IL-20RA、IL-5和TNFRSF9之间的显著因果关系在逐个剔除6个吸入性损伤SNP后结果稳定可靠。 结论 通过双样本MR分析,明确吸入性损伤与4种循环炎症蛋白IL-20、IL-20RA、IL-5和TNFRSF9存在显著因果关系,提示发生吸入性损伤后以上4种循环炎症蛋白的生成呈增多趋势。 Abstract:Objective To explore the causal relationship between human inhalation injury and circulating inflammatory proteins. Methods This research was based on two-sample Mendelian randomization (MR) analysis. With inhalation injury as the exposure factor and circulating inflammatory proteins as the result, data on inhalation injury (216 993 samples) and 91 circulating inflammatory proteins (14 824 samples) were obtained from the genome-wide association study database, and analysis was conducted by two-sample MR analysis methods. Based on linkage disequilibrium analysis, independent site single nucleotide polymorphisms (SNPs) that were significantly associated with inhalation injury were identified as the instrumental variables. The inverse variance weighted (IVW) method was mainly used to analyze the causal relationship between inhalation injury and 91 circulating inflammatory proteins, which were further verified using the weighted median method, weighted pattern method, MR-Egger method, and simple pattern method. Based on the aforementioned IVW method analysis results, SNPs of inhalation injury conformed to the hypothesis were subjected to Cochran's Q test for heterogeneity assessment, the MR-Egger regression test and MR-PRESSO outlier test for assessment of horizontal pleiotropy, and the leave-one-out method analysis for reliability assessment. Results Six SNPs with a significant threshold (P<5×10-5) were identified as representative instrumental variables of inhalation injury, with F values greater than 10, indicating strong correlated instrumental variables. Based on the 6 inhalation injury SNPs, the IVW method analysis revealed a significant causal relationship between inhalation injury and interleukin-20 (IL-20), IL-20 receptor subunit alpha (IL-20RA), IL-5, and tumor necrosis factor receptor superfamily member 9 (TNFRSF9), with odds ratios of 1.01, 1.01, 1.02, and 1.01, respectively, and 95% confidence intervals of 1.00-1.02, 1.00-1.03, 1.01-1.03, and 1.00-1.03, respectively, P<0.05. Verification through the weighted median method and MR-Egger method confirmed that the causal relationships between inhalation injury and IL-5 (with odds ratios of 1.02 and 1.03, respectively, confidence intervals of 1.00-1.04 and 1.01-1.04, respectively, P<0.05) as well as TNFRSF9 (with odds ratios of 1.02 and 1.03, respectively, confidence intervals of 1.00-1.04 and 1.01-1.04, respectively, P<0.05) were statistically significant. Conversely, verification through the weighted pattern method and simple pattern method indicated that the causal relationships between inhalation injury and IL-20, IL-20RA, IL-5, and TNFRSF9 were not statistically significant (with all P values >0.05), thus still needing IVW method results as standards. Based on the aforementioned IVW method analysis results, the Cochran's Q test demonstrated there was no significant heterogeneity in the 6 inhalation injury SNPs that had significant causal relationships with IL-20, IL-20RA, IL-5, and TNFRSF9 (with Q values of 2.67, 5.00, 5.17, and 5.29, respectively, P>0.05); assessments using the MR-Egger regression test along with MR-PRESSO outlier test showed that none of the 6 inhalation injury SNPs that had significant causal relationships with IL-20, IL-20RA, IL-5, and TNFRSF9 had significant horizontal pleiotropy (with intercepts of 0.01, <0.01, -0.02, and -0.03, respectively, RSSobs values of 3.33, 9.00, 7.88, and 7.26, respectively, P>0.05); the leave-one-out method analysis showed that the significant causal relationship between inhalation injury and IL-20, IL-20RA, IL-5, and TNFRSF9 was stable and reliable after removing the 6 inhalation injury SNPs one by one. Conclusions Through two-sample MR analysis, it is clear that there is a significant causal relationship between inhalation injury and four circulating inflammatory proteins, namely IL-20, IL-20RA, IL-5, and TNFRSF9, suggesting the production of the above four circulating inflammatory proteins is in an increasing trend following inhalation injury. -
参考文献
(42) [1] DeutschCJ,TanA,SmailesS,et al.The diagnosis and management of inhalation injury: an evidence based approach[J].Burns,2018,44(5):1040-1051.DOI: 10.1016/j.burns.2017.11.013. [2] JeschkeMG,van BaarME,ChoudhryMA,et al.Burn injury[J].Nat Rev Dis Primers,2020,6(1):11.DOI: 10.1038/s41572-020-0145-5. [3] 张宇翔,兰美娟,梁诗雨,等.物理性气道廓清技术在吸入性损伤治疗中的应用进展[J].中华烧伤与创面修复杂志,2023,39(5):475-480.DOI: 10.3760/cma.j.cn501225-20220608-00226. [4] LanX,HuangZ,TanZ,et al.Nebulized heparin for inhalation injury in burn patients: a systematic review and meta-analysis[J/OL].Burns Trauma,2020,8:tkaa015[2024-04-29].https://pubmed.ncbi.nlm.nih.gov/32523966/.DOI: 10.1093/burnst/tkaa015. [5] ChongSJ,KokYO,TayRXY,et al.Quantifying the impact of inhalational burns: a prospective study[J/OL].Burns Trauma,2018,6:26[2024-04-29].https://pubmed.ncbi.nlm.nih.gov/30238012/.DOI: 10.1186/s41038-018-0126-z. [6] HengX,CaiP,YuanZ,et al.Efficacy and safety of extracorporeal membrane oxygenation for burn patients: a comprehensive systematic review and meta-analysis[J/OL].Burns Trauma,2023,11:tkac056[2024-04-29].https://pubmed.ncbi.nlm.nih.gov/36873286/.DOI: 10.1093/burnst/tkac056. [7] FengT,ZhouL,GaiS,et al.Acacia catechu (L.f.) Willd and Scutellaria baicalensis Georgi extracts suppress LPS-induced pro-inflammatory responses through NF-κB, MAPK, and PI3K-Akt signaling pathways in alveolar epithelial type II cells[J].Phytother Res,2019,33(12):3251-3260.DOI: 10.1002/ptr.6499. [8] DriesDJ,EndorfFW.Inhalation injury: epidemiology, pathology, treatment strategies[J].Scand J Trauma Resusc Emerg Med,2013,21:31.DOI: 10.1186/1757-7241-21-31. [9] ParkGY,ParkJW,JeongDH,et al.Prolonged airway and systemic inflammatory reactions after smoke inhalation[J].Chest,2003,123(2):475-480.DOI: 10.1378/chest.123.2.475. [10] CaoH,ShiC,AihemaitiZ,et al.Association between circulating inflammatory proteins and benign prostatic disease: a Mendelian randomization study[J].Sci Rep,2024,14(1):23667.DOI: 10.1038/s41598-024-74737-2. [11] XiaoY,FangH,ZhuY,et al.Multifunctional cationic hyperbranched polyaminoglycosides that target multiple mediators for severe abdominal trauma management[J].Adv Sci (Weinh),2024,11(1):e2305273.DOI: 10.1002/advs.202305273. [12] NiewczasMA,PavkovME,SkupienJ,et al.A signature of circulating inflammatory proteins and development of end-stage renal disease in diabetes[J].Nat Med,2019,25(5):805-813.DOI: 10.1038/s41591-019-0415-5. [13] WoolfB,RajasundaramS,CronjéHT,et al.A drug target for erectile dysfunction to help improve fertility, sexual activity, and wellbeing: mendelian randomisation study[J].BMJ,2023,383:e076197.DOI: 10.1136/bmj-2023-076197. [14] ClaytonGL,GonçalvesA,Soares,GouldingN,et al.A framework for assessing selection and misclassification bias in mendelian randomisation studies: an illustrative example between body mass index and covid-19[J].BMJ,2023,381:e072148.DOI: 10.1136/bmj-2022-072148. [15] TschidererL,van der SchouwYT,BurgessS,et al. Hypertensive disorders of pregnancy and cardiovascular disease risk: a Mendelian Randomisation study[J].Eur Heart J,2023,44(Suppl 2):S655.2726.DOI: 10.1093/eurheartj/ehad655.2726. [16] WeiY,ZhanY,CarlssonS.Childhood adiposity and novel subtypes of diabetes in adults: a Mendelian randomisation and genome-wide genetic correlation study[J].Lancet Glob Health,2023,11Suppl 1:S1.DOI: 10.1016/S2214-109X(23)00086-4. [17] ZhaoJH,StaceyD,ErikssonN,et al.Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets[J].Nat Immunol,2023,24(9):1540-1551.DOI: 10.1038/s41590-023-01588-w. [18] SannaS,van ZuydamNR,MahajanA,et al.Causal relationships among the gut microbiome, short-chain fatty acids and metabolic diseases[J].Nat Genet,2019,51(4):600-605.DOI: 10.1038/s41588-019-0350-x. [19] LiuX,TongX,ZouY,et al.Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome[J].Nat Genet,2022,54(1):52-61.DOI: 10.1038/s41588-021-00968-y. [20] BurgessS,DanielRM,ButterworthAS,et al.Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways[J].Int J Epidemiol,2015,44(2):484-495.DOI: 10.1093/ije/dyu176. [21] BowdenJ,HemaniG,Davey SmithG.Invited commentary: detecting individual and global horizontal pleiotropy in Mendelian randomization-a job for the humble heterogeneity statistic?[J].Am J Epidemiol,2018,187(12):2681-2685.DOI: 10.1093/aje/kwy185. [22] ZhengJ,BairdD,BorgesMC,et al.Recent developments in mendelian randomization studies[J].Curr Epidemiol Rep,2017,4(4):330-345.DOI: 10.1007/s40471-017-0128-6. [23] BurgessS,BowdenJ,FallT,et al.Sensitivity analyses for robust causal inference from mendelian randomization analyses with multiple genetic variants[J].Epidemiology,2017,28(1):30-42.DOI: 10.1097/EDE.0000000000000559. [24] DyamenahalliK,GargG,ShuppJW,et al.Inhalation injury: unmet clinical needs and future research[J].J Burn Care Res,2019,40(5):570-584.DOI: 10.1093/jbcr/irz055. [25] OuyangW,O'GarraA.IL-10 family cytokines IL-10 and IL-22: from basic science to clinical translation[J].Immunity,2019,50(4):871-891.DOI: 10.1016/j.immuni.2019.03.020. [26] SpinicelliS,NocentiniG,RonchettiS,et al.GITR interacts with the pro-apoptotic protein Siva and induces apoptosis[J].Cell Death Differ,2002,9(12):1382-1384.DOI: 10.1038/sj.cdd.4401140. [27] WuJ,WangG,HaoJ,et al.The correlation between IL-20 and the Th2 immune response in human asthma[J].Asian Pac J Allergy Immunol,2014,32(4):316-320. [28] BaradaO,Salomé-DesnoulezS,MadouriF,et al.IL-20 cytokines are involved in the repair of airway epithelial barrier: implication in exposure to cigarette smoke and in COPD pathology[J].Cells,2023,12(20):2464.DOI: 10.3390/cells12202464. [29] KolumamG,WuX,LeeWP,et al.IL-22R ligands IL-20, IL-22, and IL-24 promote wound healing in diabetic db/db mice[J].PLoS One,2017,12(1):e0170639.DOI: 10.1371/journal.pone.0170639. [30] PestkaS,KrauseCD,SarkarD,et al.Interleukin-10 and related cytokines and receptors[J].Annu Rev Immunol,2004,22:929-979.DOI: 10.1146/annurev.immunol.22.012703.104622. [31] BlumbergH,ConklinD,XuWF,et al.Interleukin 20: discovery, receptor identification, and role in epidermal function[J].Cell,2001,104(1):9-19.DOI: 10.1016/s0092-8674(01)00187-8. [32] NiroomandA,GhaidanH,HallgrenO,et al.Corticotropin releasing hormone as an identifier of bronchiolitis obliterans syndrome[J].Sci Rep,2022,12(1):8413.DOI: 10.1038/s41598-022-12546-1. [33] TakatsuK,NakajimaH.IL-5 and eosinophilia[J].Curr Opin Immunol,2008,20(3):288-294.DOI: 10.1016/j.coi.2008.04.001. [34] HammadH,LambrechtBN.The basic immunology of asthma[J].Cell,2021,184(9):2521-2522.DOI: 10.1016/j.cell.2021.04.019. [35] GandhiNA,BennettBL,GrahamNM,et al.Targeting key proximal drivers of type 2 inflammation in disease[J].Nat Rev Drug Discov,2016,15(1):35-50.DOI: 10.1038/nrd4624. [36] BurbankAJ,SchworerSA,SoodA,et al.Airway IL-1β associates with IL-5 production following dust mite allergen inhalation in humans[J].Respir Res,2021,22(1):309.DOI: 10.1186/s12931-021-01903-9. [37] 刘云峰,张勇,丁盛,等.重度吸入性损伤患者气道呼出气冷凝液中多种细胞因子水平变化及临床意义[J].中华危重病急救医学,2023,35(8):818-822.DOI: 10.3760/cma.j.cn121430-20221219-01105. [38] GieseckRL3rd,WilsonMS,WynnTA.Type 2 immunity in tissue repair and fibrosis[J].Nat Rev Immunol,2018,18(1):62-76.DOI: 10.1038/nri.2017.90. [39] FinnertyCC,HerndonDN,PrzkoraR,et al.Cytokine expression profile over time in severely burned pediatric patients[J].Shock,2006,26(1):13-19.DOI: 10.1097/01.shk.0000223120.26394.7d. [40] SchmidtMJ,NaghdlooA,PrabakarRK,et al.Polyploid cancer cells reveal signatures of chemotherapy resistance[J].bioRxiv[Preprint],2024:2024.08.19.608632.DOI: 10.1101/2024.08.19.608632. [41] GuoX,ZhangY,ZhengL,et al.Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing[J].Nat Med,2018,24(7):978-985.DOI: 10.1038/s41591-018-0045-3. [42] LiL,LiY,LinJ,et al.A pyroptosis-related gene signature predicts prognosis and tumor immune microenvironment in colorectal cancer[J].Technol Cancer Res Treat,2024,23:15330338241277584.DOI: 10.1177/15330338241277584. -
图 1 人吸入性损伤与循环炎症蛋白的双样本孟德尔随机化分析核心假设与分析流程图
注：SNP为单核苷酸多态性；实线箭头和“√”代表存在关联性,虚线箭头和“×”代表不存在关联性；①表示工具变量与暴露因素强相关,②表示工具变量不受暴露因素之外的混杂因素干扰,③表示工具变量不会通过暴露因素以外的途径影响结局
图 2 人吸入性损伤与91种循环炎症蛋白因果关系的双样本MR分析结果
注：基于6个吸入性损伤单核苷酸多态性分析；最内圈蓝色点代表逆方差加权法的比值比,黑色虚线代表0刻度线,虚线以内表示比值比小于0,虚线以外代表比值比大于0；从外到内的彩色圆环依次代表循环炎症蛋白的逆方差加权法的P值、孟德尔随机化（MR）-Egger法的P值、加权模式法的P值、简单模式法的P值、加权中位数法的P值；同一个圆环的不同扇环块代表一种循环炎症蛋白,与吸入性损伤有明确因果关系的4种循环炎症蛋白由箭头指示,红色箭头指示肿瘤坏死因子受体超家族成员9,黑色箭头指示白细胞介素5（IL-5）,绿色箭头指示IL-20受体亚基α,紫色箭头指示IL-20
图 3 留一法分析的与4种循环炎症蛋白存在显著因果关系的6个人吸入性损伤SNP的可靠性。3A.SNP与白细胞介素20（IL-20）的因果关系；3B.SNP与IL-20受体亚基α的因果关系；3C.SNP与IL-5的因果关系；3D.SNP与肿瘤坏死因子受体超家族成员9的因果关系
注：SNP为单核苷酸多态性；每个SNP对应的线段为误差线,线段中的圆点代表β值,均在0点右侧,提示结果可靠
Table 1. 连锁不平衡分析筛选出的作为吸入性损伤工具变量的6个SNP的详细信息
SNP名称 效应等位基因 其他等位基因 β值 β值的标准误 等位基因频率 P值（×10-6） F值 rs118055061 C T 2.47 0.55 0.02 8.610 19.80 rs139738340 T C 6.67 1.48 <0.01 0.638 20.37 rs11950253 A G 0.58 0.13 0.48 5.130 20.79 rs324341 A G 4.12 0.92 0.01 0.691 20.22 rs5760255 G A 0.91 0.17 0.19 0.100 28.37 rs8813 A G 0.70 0.16 0.24 0.642 20.37 注：P<5×10-5为筛选单核苷酸多态性（SNP）的显著阈值,F值≥10代表强相关工具变量 
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Table 2. 人吸入性损伤与4种循环炎症蛋白因果关系的双样本MR分析结果
循环炎症蛋白与分析方法 比值比 95%置信区间 P值 IL-20 IVW法 1.01 1.00~1.02 0.035 MR-Egger法 1.01 0.99~1.02 0.379 加权中位数法 1.01 1.00~1.03 0.144 简单模式法 1.01 0.99~1.03 0.258 加权模式法 1.01 0.99~1.03 0.231 IL-20RA IVW法 1.01 1.00~1.03 0.023 MR-Egger法 1.01 0.99~1.03 0.247 加权中位数法 1.01 1.00~1.03 0.084 简单模式法 1.02 1.00~1.05 0.152 加权模式法 1.00 0.98~1.02 0.869 IL-5 IVW法 1.02 1.01~1.03 0.003 MR-Egger法 1.03 1.01~1.04 0.035 加权中位数法 1.02 1.00~1.04 0.024 简单模式法 1.02 1.00~1.05 0.136 加权模式法 1.02 1.01~1.03 0.145 TNFRSF9 IVW法 1.01 1.00~1.03 0.036 MR-Egger法 1.03 1.01~1.04 0.035 加权中位数法 1.02 1.00~1.04 0.011 简单模式法 1.02 1.00~1.04 0.188 加权模式法 1.02 1.00~1.04 0.083 注：基于6个吸入性损伤单核苷酸多态性分析；MR为孟德尔随机化,IL为白细胞介素,IVW为逆方差加权,IL-20RA为IL-20受体亚基α,TNFRSF9为肿瘤坏死因子受体超家族成员9
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Table 3. 与4种循环炎症蛋白存在显著因果关系的6个人吸入性损伤SNP的异质性与水平多效性分析结果
循环炎症蛋白 Cochran Q检验 MR-Egger回归检验 MR-PRESSO离群值检验 Q值 P值 截距 P值 RSSobs P值 IL-20 2.67 0.756 0.01 0.507 3.33 0.805 IL-20RA 5.00 0.416 <0.01 0.895 9.00 0.400 IL-5 5.17 0.396 -0.02 0.237 7.88 0.456 TNFRSF9 5.29 0.382 -0.03 0.085 7.26 0.464 注：SNP为单核苷酸多态性,IL为白细胞介素,IL-20RA为IL-20受体亚基α,TNFRSF9为肿瘤坏死因子受体超家族成员9,MR为孟德尔随机化
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