Document Type

Journal Article

Publication Title

PNAS Nexus

Publisher

Oxford University Press

School

School of Medical and Health Sciences / Centre for Precision Health

RAS ID

58244

Funders

National Key R&D Program of China - European Commission Horizon 2020 / Beijing Talents Project / China Postdoctoal Science Foundation

Comments

Wanh, H., Cao, M., Xi, Y., Cao, W., Zhang, X., Meng, X., . . . Wang, Y. (2023). Externalizing traits: Shared causalities for COVID-19 and Alzheimer's dementia using mendelian randomization analysis. PNAS Nexus, 2(6), article pgad198. https://doi.org/10.1093/pnasnexus/pgad198

Abstract

Externalizing traits have been related with the outcomes of coronavirus disease 2019 (COVID-19) and Alzheimer's dementia (AD); however, whether these associations are causal remains unknown. We used the two-sample Mendelian randomization (MR) approach with more than 200 single-nucleotide polymorphisms (SNPs) for externalizing traits to explore the causal associations of externalizing traits with the risk of COVID-19 (infected COVID-19, hospitalized COVID-19, and severe COVID-19) or AD based on the summary data. The inverse variance–weighted method (IVW) was used to estimate the main effect, followed by several sensitivity analyses. IVW analysis showed significant associations of externalizing traits with COVID-19 infection (odds ratio [OR] = 1.456, 95% confidence interval [95% CI] = 1.224–1.731), hospitalized COVID-19 (OR = 1.970, 95% CI = 1.374–2.826), and AD (OR = 1.077, 95% CI = 1.037–1.119). The results were consistent using weighted median (WM), penalized weighted median (PWM), MR-robust adjusted profile score (MR-RAPS), and leave-one-out sensitivity analyses. Our findings assist in exploring the causal effect of externalizing traits on the pathophysiology of infection and severe infection of COVID-19 and AD. Furthermore, our study provides evidence that shared externalizing traits underpin the two diseases.

DOI

10.1093/pnasnexus/pgad198

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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