Li Zengbin, Wei Yudong, Zhu Guixian, Wang Mengjie, Zhang Lei
China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an 710061, China.
Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC 3053, Australia.
Cancers (Basel). 2022 Apr 22;14(9):2086. doi: 10.3390/cancers14092086.
Observational studies have shown increased COVID-19 risk among cancer patients, but the causality has not been proven yet. Mendelian randomization analysis can use the genetic variants, independently of confounders, to obtain causal estimates which are considerably less confounded. We aimed to investigate the causal associations of cancers with COVID-19 outcomes using the MR analysis. The inverse-variance weighted (IVW) method was employed as the primary analysis. Sensitivity analyses and multivariable MR analyses were conducted. Notably, IVW analysis of univariable MR revealed that overall cancer and twelve site-specific cancers had no causal association with COVID-19 severity, hospitalization or susceptibility. The corresponding -values for the casual associations were all statistically insignificant: overall cancer ( = 0.34; = 0.42; = 0.69), lung cancer ( = 0.60; = 0.37; = 0.96), breast cancer ( = 0.43; = 0.74; = 0.43), endometrial cancer ( = 0.79; = 0.24; = 0.83), prostate cancer ( = 0.54; = 0.17; = 0.58), thyroid cancer ( = 0.70; = 0.80; = 0.28), ovarian cancer ( = 0.62; = 0.96; = 0.93), melanoma ( = 0.79; = 0.45; = 0.82), small bowel cancer ( = 0.09; = 0.08; = 0.19), colorectal cancer ( = 0.85; = 0.79; = 0.30), oropharyngeal cancer ( = 0.31; not applicable, NA; = 0.80), lymphoma ( = 0.51; NA; = 0.37) and cervical cancer ( = 0.25; = 0.32; = 0.68). Sensitivity analyses and multivariable MR analyses yielded similar results. In conclusion, cancers might have no causal effect on increasing COVID-19 risk. Further large-scale population studies are needed to validate our findings.
观察性研究表明癌症患者感染新冠病毒的风险增加，但因果关系尚未得到证实。孟德尔随机化分析可以使用遗传变异，独立于混杂因素，来获得混杂程度低得多的因果估计。我们旨在使用孟德尔随机化分析来研究癌症与新冠病毒感染结果之间的因果关联。采用逆方差加权（IVW）方法作为主要分析方法。进行了敏感性分析和多变量孟德尔随机化分析。值得注意的是，单变量孟德尔随机化的IVW分析显示，总体癌症和12种特定部位的癌症与新冠病毒感染的严重程度、住院情况或易感性没有因果关联。因果关联的相应P值均无统计学意义：总体癌症（P = 0.34；P = 0.42；P = 0.69）、肺癌（P = 0.60；P = 0.37；P = 0.96）、乳腺癌（P = 0.43；P = 0.74；P = 0.43）、子宫内膜癌（P = 0.79；P = 0.24；P = 0.83）、前列腺癌（P = 0.54；P = 0.17；P = 0.58）、甲状腺癌（P = 0.70；P = 0.80；P = 0.28）、卵巢癌（P = 0.62；P = 0.96；P = 0.93）、黑色素瘤（P = 0.79；P = 0.45；P = 0.82）、小肠癌（P = 0.09；P = 0.08；P = 0.19）、结直肠癌（P = 0.85；P = 0.79；P = 0.30）、口咽癌（P = 0.31；不适用，NA；P = 0.80）、淋巴瘤（P = 0.51；NA；P = 0.37）和宫颈癌（P = 0.25；P = 0.32；P = 0.68）。敏感性分析和多变量孟德尔随机化分析得出了类似的结果。总之，癌症可能对增加新冠病毒感染风险没有因果影响。需要进一步的大规模人群研究来验证我们的发现。
