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Cancers and COVID-19 Risk: A Mendelian Randomization Study
SIMPLE SUMMARY: During the COVID-19 pandemic, cancer patients are regarded as a highly vulnerable population. Given the unavoidable bias and unmeasured confounders in observational studies, the causal effects of cancers on COVID-19 outcomes are largely unknown. In the study, we tried to evaluate the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099868/ https://www.ncbi.nlm.nih.gov/pubmed/35565215 http://dx.doi.org/10.3390/cancers14092086 |
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author | Li, Zengbin Wei, Yudong Zhu, Guixian Wang, Mengjie Zhang, Lei |
author_facet | Li, Zengbin Wei, Yudong Zhu, Guixian Wang, Mengjie Zhang, Lei |
author_sort | Li, Zengbin |
collection | PubMed |
description | SIMPLE SUMMARY: During the COVID-19 pandemic, cancer patients are regarded as a highly vulnerable population. Given the unavoidable bias and unmeasured confounders in observational studies, the causal effects of cancers on COVID-19 outcomes are largely unknown. In the study, we tried to evaluate the causal effects of cancers on COVID-19 outcomes using the Mendelian randomization (MR) approach. No strong evidence was observed to support a causal role of cancer in COVID-19 development. Previous observational correlations between cancers and COVID-19 outcomes were likely confounded. Large and well-conducted epidemiological studies are required to determine whether cancers causally contribute to increased risk of COVID-19. ABSTRACT: 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 p-values for the casual associations were all statistically insignificant: overall cancer (p = 0.34; p = 0.42; p = 0.69), lung cancer (p = 0.60; p = 0.37; p = 0.96), breast cancer (p = 0.43; p = 0.74; p = 0.43), endometrial cancer (p = 0.79; p = 0.24; p = 0.83), prostate cancer (p = 0.54; p = 0.17; p = 0.58), thyroid cancer (p = 0.70; p = 0.80; p = 0.28), ovarian cancer (p = 0.62; p = 0.96; p = 0.93), melanoma (p = 0.79; p = 0.45; p = 0.82), small bowel cancer (p = 0.09; p = 0.08; p = 0.19), colorectal cancer (p = 0.85; p = 0.79; p = 0.30), oropharyngeal cancer (p = 0.31; not applicable, NA; p = 0.80), lymphoma (p = 0.51; NA; p = 0.37) and cervical cancer (p = 0.25; p = 0.32; p = 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. |
format | Online Article Text |
id | pubmed-9099868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90998682022-05-14 Cancers and COVID-19 Risk: A Mendelian Randomization Study Li, Zengbin Wei, Yudong Zhu, Guixian Wang, Mengjie Zhang, Lei Cancers (Basel) Article SIMPLE SUMMARY: During the COVID-19 pandemic, cancer patients are regarded as a highly vulnerable population. Given the unavoidable bias and unmeasured confounders in observational studies, the causal effects of cancers on COVID-19 outcomes are largely unknown. In the study, we tried to evaluate the causal effects of cancers on COVID-19 outcomes using the Mendelian randomization (MR) approach. No strong evidence was observed to support a causal role of cancer in COVID-19 development. Previous observational correlations between cancers and COVID-19 outcomes were likely confounded. Large and well-conducted epidemiological studies are required to determine whether cancers causally contribute to increased risk of COVID-19. ABSTRACT: 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 p-values for the casual associations were all statistically insignificant: overall cancer (p = 0.34; p = 0.42; p = 0.69), lung cancer (p = 0.60; p = 0.37; p = 0.96), breast cancer (p = 0.43; p = 0.74; p = 0.43), endometrial cancer (p = 0.79; p = 0.24; p = 0.83), prostate cancer (p = 0.54; p = 0.17; p = 0.58), thyroid cancer (p = 0.70; p = 0.80; p = 0.28), ovarian cancer (p = 0.62; p = 0.96; p = 0.93), melanoma (p = 0.79; p = 0.45; p = 0.82), small bowel cancer (p = 0.09; p = 0.08; p = 0.19), colorectal cancer (p = 0.85; p = 0.79; p = 0.30), oropharyngeal cancer (p = 0.31; not applicable, NA; p = 0.80), lymphoma (p = 0.51; NA; p = 0.37) and cervical cancer (p = 0.25; p = 0.32; p = 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. MDPI 2022-04-22 /pmc/articles/PMC9099868/ /pubmed/35565215 http://dx.doi.org/10.3390/cancers14092086 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Zengbin Wei, Yudong Zhu, Guixian Wang, Mengjie Zhang, Lei Cancers and COVID-19 Risk: A Mendelian Randomization Study |
title | Cancers and COVID-19 Risk: A Mendelian Randomization Study |
title_full | Cancers and COVID-19 Risk: A Mendelian Randomization Study |
title_fullStr | Cancers and COVID-19 Risk: A Mendelian Randomization Study |
title_full_unstemmed | Cancers and COVID-19 Risk: A Mendelian Randomization Study |
title_short | Cancers and COVID-19 Risk: A Mendelian Randomization Study |
title_sort | cancers and covid-19 risk: a mendelian randomization study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099868/ https://www.ncbi.nlm.nih.gov/pubmed/35565215 http://dx.doi.org/10.3390/cancers14092086 |
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