Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization

Abstract Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an altern...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Noah Lorincz-Comi, Xiaofeng Zhu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/53192822b200446b81806a74013da393
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:53192822b200446b81806a74013da393
record_format	dspace
spelling	oai:doaj.org-article:53192822b200446b81806a74013da3932021-12-02T18:03:31ZCardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization10.1038/s41598-021-86757-32045-2322https://doaj.org/article/53192822b200446b81806a74013da3932021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86757-3https://doaj.org/toc/2045-2322Abstract Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences. We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n = 2956) and multi-ethnic populations (COVID-19 GWAS n = 10,908) to better understand extant causal associations between Type II Diabetes (GWAS n = 659,316), BMI (n = 681,275), diastolic and systolic blood pressure, and pulse pressure (n = 757,601 for each) and COVID-19 hospitalization risk across populations. Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI 1.67, 0.96–2.92) and pulse pressure (OR, 95% CI 1.27, 0.97–1.66) in the multi-ethnic sample. Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.Noah Lorincz-ComiXiaofeng ZhuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Noah Lorincz-Comi Xiaofeng Zhu Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization
description	Abstract Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences. We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n = 2956) and multi-ethnic populations (COVID-19 GWAS n = 10,908) to better understand extant causal associations between Type II Diabetes (GWAS n = 659,316), BMI (n = 681,275), diastolic and systolic blood pressure, and pulse pressure (n = 757,601 for each) and COVID-19 hospitalization risk across populations. Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI 1.67, 0.96–2.92) and pulse pressure (OR, 95% CI 1.27, 0.97–1.66) in the multi-ethnic sample. Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.
format	article
author	Noah Lorincz-Comi Xiaofeng Zhu
author_facet	Noah Lorincz-Comi Xiaofeng Zhu
author_sort	Noah Lorincz-Comi
title	Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization
title_short	Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization
title_full	Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization
title_fullStr	Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization
title_full_unstemmed	Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization
title_sort	cardiometabolic risks of sars-cov-2 hospitalization using mendelian randomization
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/53192822b200446b81806a74013da393
work_keys_str_mv	AT noahlorinczcomi cardiometabolicrisksofsarscov2hospitalizationusingmendelianrandomization AT xiaofengzhu cardiometabolicrisksofsarscov2hospitalizationusingmendelianrandomization
_version_	1718378686302912512

Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization

Ejemplares similares