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Causal Inference of CNS-regulated Hormones in COVID-19: A Bidirectional Two-sample Mendelian Randomization Study (preprint)
medrxiv; 2022.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2022.12.07.22283193
ABSTRACT

Objectives:

We assessed the causal association of three COVID-19 phenotypes with insulin-like growth factor 1 (IGF-1), estrogen, testosterone, dehydroepiandrosterone (DHEA), thyroid-stimulating hormone (TSH), thyrotropin-releasing hormone (TRH), luteinizing hormone (LH), and follicle-stimulating hormone (FSH).

Methods:

We used a bidirectional two-sample univariate and multivariable Mendelian randomization (MR) analysis to evaluate the direction, specificity, and causality of the association between CNS-regulated hormones and COVID-19 phenotypes. Genetic instruments for CNS-regulated hormones were selected from the largest publicly available genome-wide association studies in the European population. Summary-level data on COVID-19 severity, hospitalization, and susceptibility were obtained from the COVID-19 host genetic initiative.

Results:

DHEA was associated with increased risks of very severe respiratory syndrome (OR=4.21, 95% CI 1.41-12.59), consistent with the results in multivariate MR (OR=3.72, 95% CI 1.20-11.51), and hospitalization (OR = 2.31, 95% CI 1.13-4.72) in univariate MR. LH was associated with very severe respiratory syndrome (OR=0.83; 95% CI 0.71-0.96) in univariate MR. Estrogen was negatively associated with very severe respiratory syndrome (OR=0.09, 95% CI 0.02-0.51), hospitalization (OR=0.25, 95% CI 0.08-0.78), and susceptibility (OR=0.50, 95% CI 0.28-0.89) in multivariate MR.

Conclusions:

We found strong evidence for the causal relationship of DHEA, LH, and estrogen with COVID-19 phenotypes.
Subject(s)

Full text: Available Collection: Preprints Database: medRxiv Main subject: Respiratory Insufficiency / COVID-19 Language: English Year: 2022 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Main subject: Respiratory Insufficiency / COVID-19 Language: English Year: 2022 Document Type: Preprint