孟德尔随机化在COPD与合并症研究中的应用
Application of Mendelian Randomization in the Study of COPD and Comorbidities
DOI: 10.12677/acm.2024.1472033, PDF, HTML, XML, 下载: 12  浏览: 21 
作者: 张景红:山东大学齐鲁医院呼吸与危重症医学科,山东 济南
关键词: 慢性阻塞性肺疾病孟德尔随机化全基因组关联研究Chronic Obstructive Pulmonary Disease Mendelian Randomization Genome Wide Association Study
摘要: 疾病的病因对于正确理解疾病是必不可少的,也是预防和治疗疾病的关键。孟德尔随机化,被称为大自然的随机对照试验,正被广泛应用于探索疾病的病因。本文旨在综述该方法在慢性阻塞性肺疾病(COPD)领域的应用,为COPD的因果关联研究提供新的思路。
Abstract: The causes of disease are essential for a proper understanding of disease and are crucial for its prevention and treatment. Mendelian randomization, known as nature’s Randomized Controlled Trial, is being widely used to explore the etiology of diseases. The aim of this paper is to review the application of this method in the field of chronic obstructive pulmonary disease (COPD) and to provide new ideas for the study of causal associations in COPD.
文章引用:张景红. 孟德尔随机化在COPD与合并症研究中的应用[J]. 临床医学进展, 2024, 14(7): 435-441. https://doi.org/10.12677/acm.2024.1472033

1. 引言

慢性阻塞性肺疾病(Chronic obstructive pulmonary disease, COPD)是一种异质性肺部疾病,以呼吸困难、咳嗽、咳痰的慢性呼吸道症状为特征,是由于气道和/或肺泡异常导致的持续性(常为进展性)气流阻塞[1],是由个体一生中的基因–环境相互作用所致,这种相互作用会损害肺部和/或改变其正常发育或衰老过程[2],吸烟被认为是主要致病因素[3]。我国的流调数据显示,40岁或以上成年人群中COPD的总体患病率约为13.6%,COPD已成为我国的主要公共卫生问题[4]。加拿大一项基于人群的卫生管理数据的研究显示80岁时患COPD的总体风险约为28% [5]。2019年,全球更是共计报告了2.123亿例COPD病例[6]。此外,全球疾病负担研究(GBD2019)结果显示COPD已是全球第三大常见死因[7]。由于持续暴露于COPD危险因素和世界人口的老龄化,预计未来几十年COPD的患病率和负担将继续增加[8]

研究发现,大多数COPD患者至少合并一种临床相关慢性疾病[9],并且合并症在任何程度的COPD中都很常见[10],证据表明合并症对COPD患者的生活质量、加重和死亡率有很大负面影响[11],造成严重的经济负担[12]。尽管观察到COPD与合并症间存在相关关系,但其间的因果关系并不清楚,通过探究COPD与其他疾病间的因果关系对揭示COPD的病因、病理生理机制、采取有效的临床干预措施和制订公共卫生政策具有重要意义。

2. 孟德尔随机化

流行病学研究可以识别疾病的危险因素,探索疾病病因,减轻疾病负担[13]。随机对照试验(Randomized Controlled Trials, RCT)被认为是推断因果关系的金标准,然而由于RCT昂贵、耗时且往往不可行,存在比如长期依从性差和随机分配治疗方案的伦理问题[14],相比之下,观察性研究更容易实施,但却存在因果推断结果可信度较低的问题,主要原因是传统观察性流行病学研究的结果存在混杂因素的干扰,并且横断面数据中暴露和结局的时间顺序问题无法解决,会存在反向因果关联。因此,需要更好的方法来评估COPD与合并疾病之间的因果关系。

孟德尔随机化(Mendelian randomization, MR)是一种新兴的流行病学方法,通过使用与暴露密切相关的遗传变异(如单核苷酸多态性,single neucleotide polymorphisms, SNPs)作为工具变量(instrumental variable, IV)来估计暴露与疾病结局之间的因果关系。根据孟德尔分离定律,亲代等位基因是随机分配给子代的,特征的遗传是相互独立的,因此可以排除一些常见的混杂因素对基因与结局间关联的影响,使得这些关联不太容易混淆。此外,由于遗传变异从出生起就已建立,符合因果关系的先后顺序,故反向因果关系的可能性也减小。因此,相较于传统流行病学分析中的关联相比,MR研究中的关联更有可能具有因果解释[15],孟德尔随机化法可能避免观察性研究中存在的混杂偏倚和反向因果问题,又被称为“大自然的随机对照试验”[16]-[18],并且不需要排除标准或适合随机分配治疗的志愿者[19],现已被流行病学家广泛使用。随全基因组关联研究(Genome wide association study, GWAS)的不断发展,大量与人类疾病相关的遗传变异被发现,基于此产生了大量的汇总数据。两样本MR分析利用已公开发表的大规模汇总数据,无需额外实验即可评估暴露因素对结局的因果效应,不仅降低了昂贵的实验成本,同时也能够更好地理解和利用生物数据,帮助推动医学进步,为人类健康带来积极影响。

3. 孟德尔随机化在COPD合并症中的应用

目前,孟德尔随机化已经在COPD合并症研究领域有了一定范围的应用,包括与心血管疾病、呼吸系统疾病、胃肠道疾病、肾脏病、内分泌疾病、风湿性疾病的因果关系等,下文就以上领域分别进行阐述。

3.1. 心血管疾病

目前MR被用于研究心血管疾病与COPD的因果关系。在德国古腾贝格健康研究中的,15,010名普通人群接受了肺活量测定、经胸超声心动图和生物标志物测量,结果发现用力呼气容积(FEV1)、用力肺活量(FVC)和FEV1/FVC比值与心脏的收缩和舒张功能以及明显心力衰竭(HF)相关[20]。一项基于IVW法的MR分析结果也显示COPD和HF之间存在正向因果关系,但没有表明HF对COPD的发病存在因果关系,该发现强调了积极主动的COPD管理作为预防HF发展的潜在策略的重要性,强调了对COPD患者进行有针对性的干预以降低其HF风险的必要性[21],验证了此前观察性研究的结果。而另一项针对COPD与其常见合并症之间因果关系的MR研究也发现COPD可能会增加HF风险,同时发现HF也可能增加对COPD的易感性[22]。此外,一项研究发现一般人群中的气流阻塞与左心室充盈存在因果关系,且MR分析和敏感性分析均提示气流阻塞减轻会导致流入左心室的血流量增加,即心功能改善[23]。关于呼吸功能与心房颤动(AF)之间关联的数据很少,一项研究从英国生物样本库前瞻性收集了348,219名白人个体的数据,旨在评估FEV1、FVC和FEV1/FVC与AF事件之间的关系的研究,发现AF风险随着FEV1/FVC比值的降低而线性增加,已知患有COPD的患者发生心房颤动的风险增加40% [24],即表明肺功能下降或者COPD病史与AF相关,但因果关系并不清楚。一项研究采用两样本MR评估了COPD与AF及房扑发生风险之间的潜在因果,结果显示COPD与AF及房扑发生之间呈显著正相关,得出了COPD与房颤及房扑发生之间可能存在正向因果关系的结论[25]

3.2. 呼吸系统疾病

COPD常常合并其他的呼吸系统疾病,然而因果关系却仍不清楚,MR已开始被应用于此。已有两项MR研究发现哮喘增加慢性阻塞性肺病风险,并且均没有发现COPD与哮喘存在明显的因果关联的证据[22] [26],这和既往研究的结果是一致的。COPD与特发性肺纤维化(IPF)间因果关系也已有MR研究,结果显示COPD与IPF风险降低有因果关系,没有发现IPF与COPD风险存在因果关系[27]。有研究者应用双样本MR研究过敏性鼻炎(AR)对与慢性下呼吸道疾病和肺功能的因果影响,发现没有证据支持AR对COPD的因果效应[28]

3.3. COPD与胃肠道疾病

观察性研究表明胃肠道疾病与COPD之间存在关联,但因果关系尚不清楚,为此有研究者进行了双向MR分析,探讨了常见胃肠道疾病与COPD之间的因果关系,结果支持胃食管反流病(GERD)和COPD之间存在双向因果关系,还发现COPD会增加肠易激综合征和便秘的风险,研究还发现消化性溃疡病和COPD之间存在双向因果关系,另外,没有发现克罗恩病、溃疡性结肠炎、功能性消化不良、非感染性胃肠炎和COPD之间存在因果关系[29]。另外有一项研究也揭示GERD和COPD之间可能存在双向因果关系[30]。此外,两项旨在估计GERD与呼吸系统疾病之间的因果关系的研究,结果均显示遗传预测的GERD与COPD的风险增加有因果关系[31] [32]。越来越多的队列研究表明肺部疾病与食管癌之间存在相关性,但确切的因果关系尚未明确,一项为评估肺部疾病与食管癌之间因果关系的研究,发现食管癌与COPD没有显著相关性[33]。但值得注意的是,尽管MR得出的结论一致,仍需要进一步的大样本前瞻性研究来验证这些发现。

3.4. COPD与慢性肾脏病

慢性肾脏病(CKD)是全球另一种主要慢性病,2017年,全球有120万人死于CKD,1990年至2017年间,全球CKD的全年龄死亡率增加了41.5% [34]。有研究者采用双向双样本MR分析调查了肾功能与阻塞性肺疾病之间的因果关系,结果显示肾功能损害是阻塞性肺疾病的致病因素,没有发现COPD与肾功能存在明显因果关系,这提示我们适当的肾功能管理可能改善肺功能,此外,这些证据鼓励对CKD患者进行早期筛查[35]

3.5. COPD与内分泌疾病

为研究肥胖如何影响呼吸系统疾病,研究者对体重指数(BMI)和腰围与35种呼吸系统疾病进行了MR分析,结果表明,肥胖会增加大多数呼吸系统疾病(包括所有35种呼吸系统疾病中的20种)的风险,但不包括COPD,即肥胖不会增加COPD的风险[36]。而另一项关于BMI与慢性疾病之间关联的研究发现,遗传预测较高的BMI与2型糖尿病、哮喘、COPD等的风险增加有关,即MR研究的证据支持过度肥胖在多种慢性疾病中的因果作用,包括COPD,并提出继续努力降低超重和肥胖的发生率是一项主要的公共卫生目标[37]。临床研究表明,COPD的发病和加重与肥胖和饮食行为有关,但两者之间的遗传关系尚不清楚,一项MR研究关注了肥胖的遗传决定因素、饮食习惯(饮酒、甜食摄入、盐摄入)与COPD之间的关系,结果显示,BMI、体脂率与COPD风险和急性COPD入院风险呈正相关,强调了体重较重、体脂率较高的患者,应指导他们减重减脂,预防慢性阻塞性肺病的发生,而对于肥胖的COPD患者,应更加注意提前预防COPD急性加重的发生[38]。既往研究发现肺功能低下与心脏代谢健康不良的特征有关,但尚不清楚这些合并是反映了因果关系,还是共同的遗传遗传性或是受到环境因素的混淆,为此研究者进行了肺功能和心脏代谢特征间的MR分析,结果显示2型糖尿病(T2D)对肺功能具有独立因果效应[39]。由于观察性研究指出COPD和T2D之间存在潜在联系,为了阐明这种因果关系,研究者采用了MR分析,结果表明,COPD和T2D之间存在明显的因果关系,即COPD是T2D的危险因素[40]。COPD和骨质疏松症的发病率在世界范围内呈上升趋势,观察性研究表明,慢性阻塞性肺病与骨质疏松症的风险增加有关,为研究COPD对骨质疏松症的因果关系,研究者进行了MR研究,发现遗传预测的COPD与骨质疏松症风险增加有因果关系[41]

3.6. COPD与风湿性疾病

尽管慢性阻塞性肺病(COPD)和风湿性疾病(RD)都很常见,每种病对患者的整体健康和生活质量也都有显著影响,但对它们共同发生的关注很少,对此,有研究者对RD (类风湿性关节炎(RA)、强直性脊柱炎(AS)、银屑病关节炎(PsA)、系统性红斑狼疮(SLE)、原发性干燥综合征疾病(pSS)和系统性硬化症(SSc))与COPD的合并症进行了文献检索,共纳入27篇文章进行研究,强有力的证据显示,与一般人群相比,RD患者中COPD的发病率或患病率增加[42]。最近一项MR研究分析了COPD与四种常见自身免疫性疾病之间的潜在因果关系,其中包括了RA和OA,发现COPD与RA、OA不存在明显因果关系,但反向MR结果显示RA、OA与发生COPD的风险之间存在显著相关性[43],这支持了上述观察性研究的发现。

观察性研究发现类风湿性关节炎(RA)与阻塞性肺病(ORD)风险之间存在关联,然而,RA是否在ORDs的发展中发挥作用仍不清楚,为此一项研究旨在探讨RA与ORD的因果关系,采用单变量和多变量MR分析,应用汇总统效应估计(CAUSE)方法进行因果分析,采用多变量和两步中介MR计算独立效应和中介效应,结果表明,RA遗传易感性增加对ORDs(包括COPD和哮喘)、哮喘/COPD相关感染、肺炎或肺炎衍生败血症风险增加有因果关系[44],与既往研究发现是一致的。

4. 小结与展望

孟德尔随机化是一种强大的流行病学研究方法,为COPD的研究提供了新的思路。随着GWAS数据不断发展和孟德尔随机化模型的不断规范,它必将越来越广泛地应用于研究疾病的危险因素、疾病的中间机制以及复杂疾病之间的双向因果关联等领域。尽管由于基因的复杂性,相关的生物学机制很难完全阐明,但这并不能削弱其对疾病因果关联研究的重要意义。我们相信随着遗传流行病学的不断发展和统计学算法的不断完善,孟德尔随机化发挥的作用将越来越大,能帮助我们更好的认识疾病。

参考文献

[1] Celli, B., Fabbri, L., Criner, G., Martinez, F.J., Mannino, D., Vogelmeier, C., et al. (2022) Definition and Nomenclature of Chronic Obstructive Pulmonary Disease: Time for Its Revision. American Journal of Respiratory and Critical Care Medicine, 206, 1317-1325.
https://doi.org/10.1164/rccm.202204-0671pp
[2] Agustí, A., Melén, E., DeMeo, D.L., Breyer-Kohansal, R. and Faner, R. (2022) Pathogenesis of Chronic Obstructive Pulmonary Disease: Understanding the Contributions of Gene-Environment Interactions across the Lifespan. The Lancet Respiratory Medicine, 10, 512-524.
https://doi.org/10.1016/s2213-2600(21)00555-5
[3] Kaur, M., Chandel, J., Malik, J. and Naura, A.S. (2022) Particulate Matter in COPD Pathogenesis: An Overview. Inflammation Research, 71, 797-815.
https://doi.org/10.1007/s00011-022-01594-y
[4] Fang, L., Gao, P., Bao, H., Tang, X., Wang, B., Feng, Y., et al. (2018) Chronic Obstructive Pulmonary Disease in China: A Nationwide Prevalence Study. The Lancet Respiratory Medicine, 6, 421-430.
https://doi.org/10.1016/s2213-2600(18)30103-6
[5] Gershon, A.S., Warner, L., Cascagnette, P., Victor, J.C. and To, T. (2011) Lifetime Risk of Developing Chronic Obstructive Pulmonary Disease: A Longitudinal Population Study. The Lancet, 378, 991-996.
https://doi.org/10.1016/s0140-6736(11)60990-2
[6] Safiri, S., Carson-Chahhoud, K., Noori, M., Nejadghaderi, S.A., Sullman, M.J.M., Ahmadian Heris, J., et al. (2022) Burden of Chronic Obstructive Pulmonary Disease and Its Attributable Risk Factors in 204 Countries and Territories, 1990-2019: Results from the Global Burden of Disease Study 2019. BMJ, 378, e069679.
https://doi.org/10.1136/bmj-2021-069679
[7] Vos, T., Lim, S.S., Abbafati, C., Abbas, K.M., Abbasi, M., Abbasifard, M., et al. (2020) Global Burden of 369 Diseases and Injuries in 204 Countries and Territories, 1990-2019: A Systematic Analysis for the Global Burden of Disease Study 2019. The Lancet, 396, 1204-1222.
https://doi.org/10.1016/s0140-6736(20)30925-9
[8] Mathers, C.D. and Loncar, D. (2006) Projections of Global Mortality and Burden of Disease from 2002 to 2030. PLOS Medicine, 3, e442.
https://doi.org/10.1371/journal.pmed.0030442
[9] Fabbri, L.M., Celli, B.R., Agustí, A., Criner, G.J., Dransfield, M.T., Divo, M., et al. (2023) COPD and Multimorbidity: Recognising and Addressing a Syndemic Occurrence. The Lancet Respiratory Medicine, 11, 1020-1034.
https://doi.org/10.1016/s2213-2600(23)00261-8
[10] Agusti, A., Calverley, P.M., Celli, B., Coxson, H.O., Edwards, L.D., Lomas, D.A., et al. (2010) Characterisation of COPD Heterogeneity in the ECLIPSE Cohort. Respiratory Research, 11, Article No. 122.
https://doi.org/10.1186/1465-9921-11-122
[11] Cavailles, A., Brinchault-Rabin, G., Dixmier, A., Goupil, F., Gut-Gobert, C., Marchand-Adam, S., et al. (2013) Comorbidities of COPD. European Respiratory Review, 22, 454-475.
https://doi.org/10.1183/09059180.00008612
[12] Menzin, J., Boulanger, L., Marton, J., Guadagno, L., Dastani, H., Dirani, R., et al. (2008) The Economic Burden of Chronic Obstructive Pulmonary Disease (COPD) in a U.S. Medicare Population. Respiratory Medicine, 102, 1248-1256.
https://doi.org/10.1016/j.rmed.2008.04.009
[13] Pearce, N. (2012) Classification of Epidemiological Study Designs. International Journal of Epidemiology, 41, 393-397.
https://doi.org/10.1093/ije/dys049
[14] Larsson, S.C., Butterworth, A.S. and Burgess, S. (2023) Mendelian Randomization for Cardiovascular Diseases: Principles and Applications. European Heart Journal, 44, 4913-4924.
https://doi.org/10.1093/eurheartj/ehad736
[15] Carter, P., Yuan, S., Kar, S., Vithayathil, M., Mason, A.M., Burgess, S., et al. (2022) Coffee Consumption and Cancer Risk: A Mendelian Randomisation Study. Clinical Nutrition, 41, 2113-2123.
https://doi.org/10.1016/j.clnu.2022.08.019
[16] Sekula, P., Del Greco M, F., Pattaro, C. and Köttgen, A. (2016) Mendelian Randomization as an Approach to Assess Causality Using Observational Data. Journal of the American Society of Nephrology, 27, 3253-3265.
https://doi.org/10.1681/asn.2016010098
[17] Birney, E. (2021) Mendelian Randomization. Cold Spring Harbor Perspectives in Medicine, 12, a041302.
https://doi.org/10.1101/cshperspect.a041302
[18] Zheng, J., Baird, D., Borges, M., Bowden, J., Hemani, G., Haycock, P., et al. (2017) Recent Developments in Mendelian Randomization Studies. Current Epidemiology Reports, 4, 330-345.
https://doi.org/10.1007/s40471-017-0128-6
[19] Lawlor, D.A., Harbord, R.M., Sterne, J.A.C., Timpson, N. and Davey Smith, G. (2008) Mendelian Randomization: Using Genes as Instruments for Making Causal Inferences in Epidemiology. Statistics in Medicine, 27, 1133-1163.
https://doi.org/10.1002/sim.3034
[20] Baum, C., Ojeda, F.M., Wild, P.S., Rzayeva, N., Zeller, T., Sinning, C.R., et al. (2016) Subclinical Impairment of Lung Function Is Related to Mild Cardiac Dysfunction and Manifest Heart Failure in the General Population. International Journal of Cardiology, 218, 298-304.
https://doi.org/10.1016/j.ijcard.2016.05.034
[21] Jiang, R., Sun, C., Yang, Y., Sun, Q. and Bai, X. (2024) Causal Relationship between Chronic Obstructive Pulmonary Disease and Heart Failure: A Mendelian Randomization Study. Heart & Lung, 67, 12-18.
https://doi.org/10.1016/j.hrtlng.2024.04.007
[22] Wang, Z. and Sun, Y. (2024) Unraveling the Causality between Chronic Obstructive Pulmonary Disease and Its Common Comorbidities Using Bidirectional Mendelian Randomization. European Journal of Medical Research, 29, Article No. 143.
https://doi.org/10.1186/s40001-024-01686-x
[23] Harbaum, L., Hennigs, J.K., Simon, M., Oqueka, T., Watz, H. and Klose, H. (2021) Genetic Evidence for a Causative Effect of Airflow Obstruction on Left Ventricular Filling: A Mendelian Randomisation Study. Respiratory Research, 22, Article No. 199.
https://doi.org/10.1186/s12931-021-01795-9
[24] Noubiap, J.J., Tu, S.J., Emami, M., Middeldorp, M.E., Elliott, A.D. and Sanders, P. (2023) Incident Atrial Fibrillation in Relation to Ventilatory Parameters: A Prospective Cohort Study. Canadian Journal of Cardiology, 39, 614-622.
https://doi.org/10.1016/j.cjca.2023.02.004
[25] 于晓慧, 程雪, 吕琳, 等. 慢性阻塞性肺疾病与房颤及房扑因果关系的孟德尔随机化研究[J]. 武汉大学学报(医学版), 2023: 1-6.
[26] Li, Y., Wang, W., Zhou, D., Lu, Q., Li, L. and Zhang, B. (2023) Mendelian Randomization Study Shows a Causal Effect of Asthma on Chronic Obstructive Pulmonary Disease Risk. PLOS ONE, 18, e0291102.
https://doi.org/10.1371/journal.pone.0291102
[27] Zhu, J., Zhou, D., Wang, J., Yang, Y., Chen, D., He, F., et al. (2023) A Causal Atlas on Comorbidities in Idiopathic Pulmonary Fibrosis: A Bidirectional Mendelian Randomization Study. Chest, 164, 429-440.
https://doi.org/10.1016/j.chest.2023.02.038
[28] Zhang, Z., Li, G., Yu, L., Jiang, J., Zhou, S. and Jiang, Y. (2023) Using a Two-Sample Mendelian Randomization Study Based on Genome-Wide Association Studies to Assess and Demonstrate the Causal Effects of Allergic Rhinitis on Chronic Lower Respiratory Diseases and Lung Function. International Archives of Allergy and Immunology, 184, 311-319.
https://doi.org/10.1159/000528350
[29] Shen, Z., Qiu, B., Chen, L. and Zhang, Y. (2023) Common Gastrointestinal Diseases and Chronic Obstructive Pulmonary Disease Risk: A Bidirectional Mendelian Randomization Analysis. Frontiers in Genetics, 14, Article ID: 1256833.
https://doi.org/10.3389/fgene.2023.1256833
[30] Liu, B., Chen, M., You, J., Zheng, S. and Huang, M. (2024) The Causal Relationship between Gastroesophageal Reflux Disease and Chronic Obstructive Pulmonary Disease: A Bidirectional Two-Sample Mendelian Randomization Study. International Journal of Chronic Obstructive Pulmonary Disease, 19, 87-95.
https://doi.org/10.2147/copd.s437257
[31] Cheng, X., Shi, J., Zhang, D., Li, C., Xu, H., He, J., et al. (2023) Assessing the Genetic Relationship between Gastroesophageal Reflux Disease and Chronic Respiratory Diseases: A Mendelian Randomization Study. BMC Pulmonary Medicine, 23, Article No. 243.
https://doi.org/10.1186/s12890-023-02502-8
[32] Dong, R., Zhang, Q. and Peng, H. (2024) Gastroesophageal Reflux Disease and the Risk of Respiratory Diseases: A Mendelian Randomization Study. Journal of Translational Medicine, 22, Article No. 60.
https://doi.org/10.1186/s12967-023-04786-0
[33] Zhou, J., Fang, P., Liang, Z., Li, X., Luan, S., Xiao, X., et al. (2023) Causal Relationship between Lung Diseases and Risk of Esophageal Cancer: Insights from Mendelian Randomization. Journal of Cancer Research and Clinical Oncology, 149, 15679-15686.
https://doi.org/10.1007/s00432-023-05324-7
[34] GBD Chronic Kidney Disease Collaboration (2020) Global, Regional, and National Burden of Chronic Kidney Disease, 1990-2017: A Systematic Analysis for the Global Burden of Disease Study 2017. The Lancet, 395, 709-733.
[35] Park, S., Lee, S., Kim, Y., Cho, S., Kim, K., Kim, Y.C., et al. (2021) Kidney Function and Obstructive Lung Disease: A Bidirectional Mendelian Randomisation Study. European Respiratory Journal, 58, Article ID: 2100848.
https://doi.org/10.1183/13993003.00848-2021
[36] Yang, W., Yang, Y., Guo, Y., Guo, J., Ma, M. and Han, B. (2023) Obesity and Risk for Respiratory Diseases: A Mendelian Randomization Study. Frontiers in Endocrinology, 14, Article ID: 1197730.
https://doi.org/10.3389/fendo.2023.1197730
[37] Larsson, S.C. and Burgess, S. (2021) Causal Role of High Body Mass Index in Multiple Chronic Diseases: A Systematic Review and Meta-Analysis of Mendelian Randomization Studies. BMC Medicine, 19, Article No. 320.
https://doi.org/10.1186/s12916-021-02188-x
[38] Sun, T., Wang, J., Zheng, M., Cai, C., Yu, J., Fu, L., et al. (2024) Assessment of the Relationship between Genetic Determinants of Obesity, Unhealthy Eating Habits and Chronic Obstructive Pulmonary Disease: A Mendelian Randomisation Study. COPD: Journal of Chronic Obstructive Pulmonary Disease, 21, Article ID: 2309236.
https://doi.org/10.1080/15412555.2024.2309236
[39] Wielscher, M., Amaral, A.F.S., van der Plaat, D., Wain, L.V., Sebert, S., Mosen-Ansorena, D., et al. (2021) Genetic Correlation and Causal Relationships between Cardio-Metabolic Traits and Lung Function Impairment. Genome Medicine, 13, Article No. 104.
https://doi.org/10.1186/s13073-021-00914-x
[40] Wang, T., Li, J., Huang, C., Wu, X., Fu, X., Yang, C., et al. (2024) COPD and T2DM: A Mendelian Randomization Study. Frontiers in Endocrinology, 15, Article ID: 1302641.
https://doi.org/10.3389/fendo.2024.1302641
[41] Dou, Z., Chen, X., Chen, J., Yang, H. and Chen, J. (2024) Chronic Obstructive Pulmonary Disease and Osteoporosis: A Two-Sample Mendelian Randomization Analysis. Chronic Obstructive Pulmonary Diseases: Journal of the COPD Foundation.
https://doi.org/10.15326/jcopdf.2024.0501
[42] Gergianaki, I. and Tsiligianni, I. (2019) Chronic Obstructive Pulmonary Disease and Rheumatic Diseases: A Systematic Review on a Neglected Comorbidity. Journal of Comorbidity, 9, 1-10.
https://doi.org/10.1177/2235042x18820209
[43] Yu, X., Cheng, X., Lv, L., Wang, N., Li, M., Ji, W., et al. (2024) The Association between Chronic Obstructive Pulmonary Disease and Autoimmune Diseases: A Bidirectional Mendelian Randomization Study. Frontiers in Medicine, 11, Article ID: 1331111.
https://doi.org/10.3389/fmed.2024.1331111
[44] Cao, Z., Li, Q., Wu, J. and Li, Y. (2023) Causal Association of Rheumatoid Arthritis with Obstructive Lung Disease: Evidence from Mendelian Randomization Study. Heart & Lung, 62, 35-42.
https://doi.org/10.1016/j.hrtlng.2023.05.020